animal biodiversity and conservation issue 25.2 (2002)

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AnimalBiodiversity Conservation25.2

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Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretària de Redacció / Secretaria de Redacción / Managing EditorMontserrat Ferrer

Consell Assessor / Consejo asesor / Advisory BoardOleguer EscolàEulàlia GarciaAnna OmedesJosep PiquéFrancesc Uribe

Editors / Editores / Editors Pere Abelló Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, SpainJavier Alba–Tercedor Univ. de Granada, Granada, SpainAntonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, SpainXavier Bellés Centre d' Investigació i Desenvolupament–CSIC, Barcelona, SpainJuan Carranza Univ. de Extremadura, Cáceres, SpainLuís Mª Carrascal Museo Nacional de Ciencias Naturales–CSIC, Madrid, SpainMichael J. Conroy Univ. of Georgia, Athens, USAAdolfo Cordero Univ. de Vigo, Vigo, SpainMario Díaz Univ. de Castilla–La Mancha, Toledo, SpainXavier Domingo–Roura Univ. Pompeu Fabra, Barcelona, SpainGary D. Grossman Univ. of Georgia, Athens, USADamià Jaume IMEDEA–CSIC, Univ. de les Illes Balears, SpainJordi Lleonart Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, SpainJorge M. Lobo Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Pablo J. López–González Univ de Sevilla, Sevilla, SpainFrancisco Palomares Estación Biológica de Doñana, Sevilla, SpainFrancesc Piferrer Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, SpainMontserrat Ramón Inst. de Ciències del Mar CMIMA –CSIC, Barcelona, SpainIgnacio Ribera The Natural History Museum, London, United KingdomPedro Rincón Museo Nacional de Ciencias Naturales–CSIC, Madrid, SpainAlfredo Salvador Museo Nacional de Ciencias Naturales–CSIC, Madrid, SpainJosé Luís Tellería Univ. Complutense de Madrid, Madrid, SpainFrancesc Uribe Museu de Ciències Naturals de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial BoardJosé A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, SpainJean C. Beaucournu Univ. de Rennes, Rennes, FranceDavid M. Bird McGill Univ., Québec, CanadaMats Björklund Uppsala Univ., Uppsala, SwedenJean Bouillon Univ. Libre de Bruxelles, Brussels, BelgiumMiguel Delibes Estación Biológica de Doñana–CSIC, Sevilla, SpainDario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, SpainAlain Dubois Museum national d’Histoire naturelle–CNRS, Paris, FranceJohn Fa Durrell Wildlife Conservation Trust, Jersey, United KingdomMarco Festa–Bianchet Univ. de Sherbrooke, Québec, CanadaRosa Flos Univ. Politècnica de Catalunya, Barcelona, SpainJosep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, SpainEdmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The NetherlandsFernando Hiraldo Estación Biológica de Doñana–CSIC, Sevilla, SpainPatrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, FranceSantiago Mas–Coma Univ. de Valencia, Valencia, SpainJoaquín Mateu Estación Experimental de Zonas Áridas–CSIC, Almería, SpainNeil Metcalfe Univ. of Glasgow, Glasgow, United KingdomJacint Nadal Univ. de Barcelona, Barcelona, SpainStewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, SpainTaylor H. Ricketts Stanford Univ., Stanford, USAJoandomènec Ros Univ. de Barcelona, Barcelona, SpainValentín Sans–Coma Univ. de Málaga, Málaga, SpainTore Slagsvold Univ. of Oslo, Oslo, Norway

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Museu de Ciències Naturals (Zoologia)Passeig Picasso s/n08003 Barcelona, SpainTel. +34–93–3196912Fax +34–93–3104999E–mail [email protected]

Animal Biodiversity and Conservation 25.2, 2002© 2002 Museu de Ciències Naturals (Zoologia), Institut de Cultura, Ajuntament de BarcelonaAutoedició: Montserrat FerrerFotomecànica i impressió: Sociedad Cooperativa Librería GeneralISSN: 1578–665XDipòsit legal: B–16.278–58

The journal is freely available online at: http://bcn.cat/ABC

"Cepaea nemoralis Linneo" Fauna malacológica terrestre y de agua dulce de Cataluña, Dr. F. Haas; Treballs del Museu de Zoologia, 5 (1991). Làmina XLVI.

1Animal Biodiversity and Conservation 25.2 (2002)

© 2002 Museu de Ciències NaturalsISSN: 1578–665X

Deharveng, L. & Smolis, A., 2002. Pronura bidoup n. sp. (Collembola, Neanuridae, Neanurinae, Paleonurini)from southern Vietnam. Animal Biodiversity and Conservation, 25.2: 1–5.

AbstractAbstractAbstractAbstractAbstractPronura bidoup n. sp. (Collembola, Neanuridae, Neanurinae, Paleonurini) from southern Vietnam.— A newspecies of Pronura Delamare Debouteville, 1953, Pronura bidoup n. sp. is described from the Bi Doup massif insouthern Vietnam, where it is largely distributed above 1,350 m. The new species exhibits a combination ofcharacters unusual for the genus: shift of chaeta f towards chaeta e on labium, large central reticulate plate onhead, presence of microchaetae on furcal rest, reduced chaetotaxy of legs and abdominal segment VI. It isrelated to Pronura ornata Deharveng & Bedos, 1993 from high altitude in Thailand.

Key words: Pronura bidoup n. sp., Collembola, Neanuridae, Vietnam.

ResumenResumenResumenResumenResumenPronura bidoup sp. n. (Collembola, Neanuridae, Neanurinae, Paleonurini) del sur de Vietnam.— Se describe unanueva especie de Pronura Delamare Debouteville, 1953, Pronura bidoup sp. n., del macizo Bi Doup, situado enel sur de Vietnam, donde se distribuye ampliamente por encima de los 1.350 m de altitud. Esta nueva especiepresenta una serie de caracteres poco usuales para el género: desplazamiento de la queta f hacia la queta e enel labium, placa central grande reticulada en la cabeza, presencia de microquetas en la base de la furca,quetotaxia reducida en las patas y en el segmento abdominal VI. P. bidoup sp. n. está relacionada con P. ornataDeharveng y Bedos, 1993, que se encuentra a gran altitud en Tailandia.

Palabras clave: Pronura bidoup sp. n., Collembola, Neanuridae, Vietnam.

(Received: 7 III 02; Conditional acceptance: 7 V 02; Final acceptance: 6 VI 02)

1 Louis Deharveng, Museum National d’Histoire Naturelle, Laboratoire d’Entomologie, ESA 8043 du CNRS, 45rue Buffon, 75005–Paris, France.2 Adrian Smolis, Zoological Institute of Wroclaw Univ., Sienkiewicza 21, 50–335 Wroclaw, Poland.

1 E–mail: [email protected] E–mail: [email protected]

Pronura bidoup n. sp.(Collembola, Neanuridae, Neanurinae,Paleonurini) from southern Vietnam

L. Deharveng1 & A. Smolis2

2 Deharveng & Smolis

Introduction

The Bi Doup massif above Dalat in southernVietnam has retained large patches of undisturbedprimary forest, which host a very rich Neanurinaefauna including more than 25 species, all new toscience (Deharveng & Le Cong Kiet, pers. com.). Inthis paper, we describe Pronura bidoup n. sp., amorphologically remarkable species of the genusPronura Delamare Debouteville, 1953, related toPronura ornata Deharveng & Bedos, 1993, knownfrom the top of Doi Inthanon, the highestmountain of Thailand.

Material and methods

The terminology and abbreviations used in thetext and the tables are standard conventions fortaxonomic descriptions in the subfamilyNeanurinae (DEHARVENG, 1983, modified).

Abbreviations used in the text and tables

Types of chaetae: bms. Buried s–microchaeta; M.Macrochaeta; me. Mesochaeta; mi. Microchaeta;ms. S–microchaeta; or. Organite of antenna IV; S.S–chaeta; x. Labial papilla.

General morphology: abd. Abdominal segment;ant. Antennal segment; th. Thoracic segment.

Chaetal groups and tubercles on head: Af.Antenno–frontal; CL. Clypeal; De. Dorso–external;Di. Dorso–internal; DL. Dorso–lateral; L. Lateral ;Oc. Ocular; So. Subocular; Ve. Ventro–external;Vi. Ventro–internal; VL. Ventro–lateral.

Chaetal groups and tubercles on tergites: De.Dorso–external; Di. Dorso–internal; DL. Dorso–lateral; L. Lateral.

Chaetal groups and tubercles of sternites: Ag.Ante–genital; An. Anal; Fu. Furcal; Ve. Ventral;VL. Ventro–lateral.

Appendages: Cx. Coxa; Fe. Femur; Scx2. Subcoxa2; Tr. Trochanter; Ti. Tibiotarsus; VT. Ventral tube.

Types are deposited in the Museum Nationald’Histoire Naturelle de Paris.

Results

Pronura bidoup n. sp. (tables 1, 2; figs. 1–6)

Studied materialHolotype female and one paratype female.Vietnam, Lam Dong province, Bi Doup massif,Nui Gia Rich, 1hr 1/2 from Klong Lanh by foot,1,440 m, litter, Berlese extraction, 18 XII 98, leg.L. Deharveng & A. Bedos (sample VIET–689).Types mounted on slides in Marc–André II.

Additional specimens (leg. L. Deharveng & A. Bedos)Vietnam, Lam Dong province, Bi Doup massif:1,545 m, litter, Berlese extraction, 28 II 97,

8 specimens (sample VIET–281); ibid: 1,900 m,litter, Berlese extraction, 1 III 97, 2 specimens(samples VIET–302, VIET–304); ibid: near the schoolof Klong Lanh, 1,410 m, litter, Berlese extraction,18 XII 98, 8 specimens (sample VIET–675). Vietnam,Lam Dong province, near Dalat, Cam Ly area,1,380 m, litter, Berlese extraction, 16 XII 98,2 specimens (samples VIET–657, VIET–665).

DescriptionLength: 0.55 to 0.75 mm. Colour: white in alcohol.Dorsal tubercles weak or absent; only the tuberclesof head and of abd. V and VI, and the dorso–lateral tubercles of abd. II–IV are well developed;they are constituted by stronger secondarygranules, with tertiary granules and slightreticulation on head. In some specimens, secondarygranules are slightly stronger on the axial area ofthe tergites where Di chaetae are more or lessgrouped. Dorso–internal tubercles of abd. V notoverhanging abd. VI. Homochaetotic clothing ofsmooth, slender, tapering and curved meso-chaetae, with frequent asymmetries. S–chaetaeon abd. I–V thin, 1.5 to 3 times longer thannearby mesochaetae.

Head (table 1, figs. 1, 2, 4). S–chaetae of ant. IVthick and rather short, like in P. ornata (figured inDEHARVENG & BEDOS, 1993); apical vesicle of ant.IVfused to the apex, hardly distinct. Buccal conerather elongate compared to that of P. ornata;labrum rounded at the apex; labium with chaetaeA, C, D, E, F, G, d, e and f, with f closer to e thanto G, and a minute x papilla (fig. 4); chaeta c (orpossibly d) not observed. Maxilla styliform,mandible tridentate. Ocelli either absent, orpossibly 2+2 covered with primary granules andnot clearly distinct from secondary granules. Theclypeal, antennal, frontal and ocular tubercles arefused in a single central plate, with a completeset of chaetae (A, B, C, D, E, F, O, Oca, Ocm, Ocp),and 2 to 4 additional chaetae between A and B,often asymmetrically arranged. Laterally, thetubercles DL, L and So are fused in a unique plate.

Tergites (table 2, figs. 1, 5). No plurichaetosisnor additional S–chaetae. Strong and irregularintegument bumps on abd. IV and sometimes onabd. II between and behind the dorso–externaland dorso–lateral chaetal groups. Dorso–internalchaetae shift towards dorso–external ones onabd. V. One lateral chaeta L on abd. V, withouttubercle. Abd. VI not bilobed, with an unevenchaeta and a reduced chaetotaxy.

Sternites and appendages. Chaeta M absenton tibiotarsi. Vestigial furcal microchaetae of thesternites of abd. III–IV very distinct, on a smallsmooth plate (fig. 6). Genital plate with 4–5(female) or 6 (male) circumgenital chaetae, and2 (female) or 4+4 (male) genital chaetae; nomodified chaetae in the male (male specimenfrom VIET–281).

Derivatio nominisThe new species is named after its type locality.

Animal Biodiversity and Conservation 25.2 (2002) 3

Figs. 1–6. 1, 2, 4–6. Pronura bidoup n. sp.: 1. Dorsal view; 2. Central plate on head; 4. Labium; 5.Tubercle (Di + De + DL) on abd. V; 6. Furcal rest with its 6 microchaetae. 3. Pronura ornata Deharveng& Bedos, 1993, labium.

Figs. 1–6. 1, 2, 4–6. Pronura bidoup sp. n.: 1. Vista dorsal; 2. Placa central de la cabeza; 4. Labium; 5.Tubérculo (Di + De + DL) del segmento abdominal V; 6. Base de la furca con 6 microquetas. 3. Pronuraornata Deharveng & Bedos, 1993, labium.

2–62–62–62–62–627 27 27 27 27 �mmmmm 9 9 9 9 9 �mmmmm11111

4 Deharveng & Smolis

Table 1. Cephalic chaetotaxy of Pronura bidoup n. sp.: G. Group of chaetae; Tu. Tubercle; N. Numberof chaetae; Ty. Type of chaetae; * other chaetae not analysed on ant. IV. .

Tabla 1. Quetotaxia cefálica de Pronura bidoup sp. n.: G. Grupo de quetas; Tu. Tubérculo; N. Númerode quetas; Ty. Tipo de queta; * en antena IV no se analizaron otras quetas.

G Tu N Ty Chaetae

CL + Af + 2Oc yes 23–25 me A, B, C, D, E, F, O, Oca, Ocm, Ocp and 2–4 additional chaetae

Di (yes) 1 me Di1

De yes 3 me De1, Di2, De2

DL + L + So yes 2 M

14 me

Vi 5 me

Ve 6–7 me

Prelabral ? ?

Labrum basal 2 me

Labrum distal 2 me

2 M

Labium 1 M F

8 me A, C, D, E, G, d, e, f

1 x

Ant. I 7 me

Ant. II 11 me

Ant. III 16 me

2 S S2, S5

3 ms s1, s3, s4

Ant. IV* 8 S S1 to S8

1 bms or

Table 2. Post–cephalic chaetotaxy of Pronura bidoup n. sp.: * 1 mi on the upper valve and ?2 mion the lateral valves.

Tabla 2. Quetotaxia postcefálica de Pronura bidoup sp. n.: * 1 mi en la valva superior y ?2 mi enlas valvas laterales.

Di De DL L Scx2 Cx Tr Fe Ti

Th. I 1 2 1 – 0 3 5 12 18

Th. II 3 3+S 3+S+ms 3 2 7 5 11 18

Th. III 3 3+S 3+S 3 2 8 5 10 17

Abd. I 2 2+S 2 3–(4) VT: 4

Abd. II 2 2+S 2 3–(4) Ve: 4–5 (Ve1 present)

Abd. III 2 2–(3)+S 2 3 Ve: 4 Fu: 3 me, 6 mi

Abd. IV 2 — (1+S, 3) —— 5 Ve: 8 VL: 4

Abd. V ——— (S+4–5) —— 1 Ag: 3 VL: 1

Abd. VI (6+6+1) ————— Ve: 11 An: 1–2 mi*


Discussion

With its clothing of subequal chaetae, its strongocular reduction, its large central plate andsupernumerary chaetae on head and its reducedchaetotaxy on legs and abd. VI, Pronura bidoupn. sp. is close to Pronura ornata Deharveng &Bedos, 1993 from Doi Inthanon in northernThailand. Both are limited to moutain foresthabitats in their respective region. They differin their labial chaetotaxy (chaeta f much closerto G than to e in ornata, closer to e than to G inbidoup), their furcal remnant (microchaetaepresent in bidoup, absent in ornata), and anumber of chaetotaxic details. The labium of P.ornata is quite unusual among Paleonurini, withthe chaeta f shift towards G like in severalother unrelated species of Neanurinae with shortbuccal cones (like Coecoloba sp., figured inDEHARVENG, 1983).

As the two species share a number ofsingular characters among Paleonurini, we donot however consider this striking differencein labial chaetotaxy to be phylet ical lymeaningful, though it would deserve deeperinvestigation.

Acknowledgements

Prof. Le Cong Kiet (University of Ho Chi MinhCity, department of Ecology and Botany) and theForest authorities of Dalat efficiently organisedour expeditions to the Bi Doup massif. UniversitéPaul Sabatier and Bourse Germaine Cousin ofthe Société Entomologique de France financiallysupported part of the field work. We also thankan anonymous reviewer for useful comments onan earlier version of the manuscript.

References

DEHARVENG, L., 1983. Morphologie évolutive desCollemboles Neanurinae en particulier de lalignée néanurienne. Travaux du Laboratoired’Écobiologie des Arthropodes édaphiques,Toulouse, 4: 1–63.

DEHARVENG, L. & BEDOS, A., 1993. New Paleonuraand Pronura species (Collembola, Neanurinae)from Thailand. Zoologica Scripta, 22: 183–192.

DELAMARE DEBOUTTEVILLE, C., 1953. Collemboles duKilimandjaro récoltés par le docteur GeorgeSalt. Ann. Mag. Hist. Nat., 12(6): 817–831.




Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, SpainXavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, SpainJuan Carranza Univ. de Extremadura, Cáceres, SpainLuís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, SpainAdolfo Cordero Univ. de Vigo, Vigo, SpainMario Díaz Univ. de Castilla–La Mancha, Toledo, SpainXavier Domingo Univ. Pompeu Fabra, Barcelona, SpainFrancisco Palomares Estación Biológica de Doñana, Sevilla, SpainFrancesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, SpainIgnacio Ribera The Natural History Museum, London, United KingdomAlfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, SpainJosé Luís Tellería Univ. Complutense de Madrid, Madrid, SpainFrancesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial BoardJosé A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, SpainJean C. Beaucournu Univ. de Rennes, Rennes, FranceDavid M. Bird McGill Univ., Québec, CanadaMats Björklund Uppsala Univ., Uppsala, SwedenJean Bouillon Univ. Libre de Bruxelles, Brussels, BelgiumMiguel Delibes Estación Biológica de Doñana CSIC, Sevilla, SpainDario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, SpainAlain Dubois Museum national d’Histoire naturelle CNRS, Paris, FranceJohn Fa Durrell Wildlife Conservation Trust, Trinity, United KingdomMarco Festa–Bianchet Univ. de Sherbrooke, Québec, CanadaRosa Flos Univ. Politècnica de Catalunya, Barcelona, SpainJosep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, SpainEdmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The NetherlandsFernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, SpainPatrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, FranceSantiago Mas–Coma Univ. de Valencia, Valencia, SpainJoaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, SpainNeil Metcalfe Univ. of Glasgow, Glasgow, United KingdomJacint Nadal Univ. de Barcelona, Barcelona, SpainStewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, SpainTaylor H. Ricketts Stanford Univ., Stanford, USAJoandomènec Ros Univ. de Barcelona, Barcelona, SpainValentín Sans–Coma Univ. de Málaga, Málaga, SpainTore Slagsvold Univ. of Oslo, Oslo, Norway


Museu de ZoologiaPasseig Picasso s/n08003 Barcelona, SpainTel. +34–93–3196912Fax +34–93–3104999E–mail [email protected]

"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Brux-elles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

Animal Biodiversity and Conservation 24.1, 2001© 2001 Museu de Zoologia, Institut de Cultura, Ajuntament de BarcelonaAutoedició: Montserrat FerrerFotomecànica i impressió: Sociedad Cooperativa Librería GeneralISSN: 1578–665XDipòsit legal: B–16.278–58



Limits to natural variation:implications for systemic management

C. W. Fowler1 & L. Hobbs2

Fowler, C. W. & Hobbs, L., 2002. Limits to natural variation: implications for systemic management. AnimalBiodiversity and Conservation, 25.2: 7–45.

AbstractAbstractAbstractAbstractAbstractLimits to natural variation: implications for systemic management.— Collectively, the tenets and principles ofmanagement emphasize the importance of recognizing and understanding limits. These tenets require thedemonstration, measurement and practical use of information about limits to natural variation. It is importantto identify limits so as not to incur the risks and loss of integrity when limits are exceeded. Thus, by managingwithin natural limits, humans (managers) simultaneously can achieve sustainability and minimize risk, as wellas account for complexity. This is at the heart of systemic management. Systemic management embodies thebasic tenets of management. One tenet requires that management ensure that nothing exceed the limitsobserved in its natural variation. This tenet is based on the principle that variation is constrained by a varietyof limiting factors, many of which involve risks. Another tenet of management requires that such factors beconsidered simultaneously, exhaustively, and in proportion to their relative importance. These factors, incombination, make up the complexity that managers are required to consider in applying the basic principlesof management. This combination of elements is reflected in observed limits to natural variation that accountfor each factor and its relative importance. This paper summarizes conclusions from the literature that hasaddressed the concept of limits to natural variation, especially in regard to management. It describes: 1. Howsuch limits are inherent to complex systems; 2. How limits have been recognized to be important to theprocess of management; 3. How they can be used in management. The inherent limits include both thoseset by the context in which systems occur (extrinsic factors) as well as those set by the components andprocesses within systems (intrinsic factors). This paper shows that information about limits is of utility inguiding human action to fit humans within the normal range of natural variation. This is part of systemicmanagement: finding an integral and sustainable place for humans in systems such as ecosystems and thebiosphere. Another part of sustainability, however, involves action to promote systems capable of sustainablysupporting humans and human activities, not only as individuals, but also as a species. It is important todistinguish what can and what can not be done in this regard.

Key words: Systemic management, Limits, Variation, Ecosystems, Single species, Resources.

ResumenResumenResumenResumenResumenLímites a la variación natural: implicaciones para el manejo o gestión sistémica.— En conjunto, los dogmas yprincipios del manejo enfatizan la importancia del reconocimiento y la comprensión de los límites. Estosprincipios requieren la demostración, medida y uso práctico de la información sobre los límites de la variaciónnatural. Es importante identificar los límites para no incurrir en riesgos y pérdida de integridad cuando dichoslímites se sobrepasan. Con el manejo dentro de unos límites naturales, el hombre (el responsable del manejo)puede conseguir simultáneamente sostenibilidad y minimización de riesgos, así como explicar la complejidad.Ésto está en el núcleo central del manejo sistémico. El manejo sistémico engloba los principios básicos decualquier tipo de manejo. Uno de los principios requiere que el manejo asegure que nada exceda los límitesobservados en la variación natural. Este principio se basa en que la variación está condicionada por variosfactores limitantes, muchos de los cuales conllevan riesgos. Otro principio del manejo requiere que estosfactores sean considerados simultáneamente, exhaustivamente y en proporción a su importancia relativa.Dichos factores, en combinación, constituyen la complejidad que los responsables del manejo deben considerar

8 Fowler & Hobbs

al aplicar los principios básicos de su función controladora. Esta combinación de elementos se refleja en loslímites observados en la variación natural referentes a cada factor natural y su importancia relativa. El presenteartículo resume conclusiones extraídas de la literatura científica respecto el concepto de variación natural,especialmente en el ámbito del manejo describe: 1. En qué medida estos límites son inherentes a los sistemascomplejos; 2. Cómo se ha reconocido la importancia de estos límites para el proceso de manejo; y 3. Cómopueden utilizarse para el manejo. Los límites inherentes incluyen tanto los establecidos por el contexto dondelos sistemas se desarrollan (factores extrínsecos) como los establecidos por los componentes y procesos internosde los sistemas (factores intrínsecos). La información sobre los límites es útil como guía de la acción humanapara acomodar los seres humanos al espectro normal de la variación natural. Esto forma parte del manejosistémico: encontrar un lugar integral y sostenible para el hombre en sistemas tales como los ecosistemas y labiosfera. Otra parte de la sostenibilidad, sin embargo, implica acciones destinadas a promover sistemas capacesde proporcionar apoyo sostenible al hombre y a sus actividades, no sólo como individuo sino también comoespecie. Es importante distinguir qué puede y que no puede hacerse a este respeto.

Palabras clave: Manejo o gestión sistémica, Límites, Variación, Ecosistemas, Especies individuales, Recursos.

(Received: 17 IV 02; Conditional acceptance: 30 VII 02; Final acceptance: 13 IX 02)

1 Charles Fowler, National Marine Mammal Laboratory, Alaska Fisheries Science Center, 7600 Sand PointWay N.E., Bin C15700, Seattle, Washington 98115–0070, U.S.A.2 Larry Hobbs, P. O. Box 51, Big Pine, CA 93513, U.S.A.



Introduction

Considerable time and effort has been devotedto defining “ecosystem management” (e.g., VAN

DYNE, 1969; CLARK & SAROKWASH, 1975; AGEE &JOHNSON, 1988a, 1988b; MITCHELL et al., 1990;COSTANZA, 1992; COSTANZA et al., 1992; GRUMBINE,1992, 1994a, 1997; SLOCOMBE, 1993a, 1993b;WOODLEY et al., 1993; MAERZ, 1994; MOOTE et al.,1994; WOOD, 1994; ALPERT, 1995; LACKEY, 1995;MALONE, 1995; PASTOR, 1995; STANLEY, 1995; UNITED

STATES INTERAGENCY ECOSYSTEM MANAGEMENT TASK

FORCE, 1995; CHRISTENSEN et al., 1996; COOPERRIDER,1996; MANGEL et al., 1996; NOSS, 1996; SAMPSON &KNOPF, 1996; SCHRAMM & HUBERT, 1996; NATIONAL

MARINE FISHERIES SERVICE ECOSYSTEM PRINCIPLES

ADVISORY PANEL, 1998; COMMITTEE ON ECOSYSTEM

MANAGEMENT FOR SUSTAINABLE MARINE FISHERIES,1999; MCCORMICK, 1999 and the referencestherein). This collective effort, in part, was areaction to the trouble that is encountered inpursuing other forms of management, especiallymanagement historically practiced at the single-species level and particularly when managementis aimed at non–human species rather thanhumans. These traditional approaches includeresource management with approaches basedon the concept of maximum sustainable yield(MSY, and its failures; LUDWIG et al., 1993;GOODLAND, 1995; CALLICOTT & MUMFORD, 1997;STRUHSAKER, 1998), pest and predator control,and crop management.

However, management cannot proceed byfocusing on ecosystems to the exclusion ofcomparable consideration of species orindividuals. A form of management is neededthat includes consideration of individuals,species, and the biosphere —in other words, allof the various levels of biological organization.These have to be considered in addition toecosystems. If other levels of biological organi-zation are excluded by restricting focus toecosystems, management will get into even deepertrouble than already experienced —troublestemming, in part, from a focus that is toonarrow, as experienced by focusing on individualspecies, or on individuals (e.g., individualhumans). Especially problematic is managementthat assumes that humans can control otherspecies or ecosystems and simultaneously avoidthe side effects or unintended consequences ofmanagement action (ROHMAN, 1999). Systemicmanagement (management that embodies theprinciples and tenets of management asdeveloped in the literature on management, torepresent the best thinking available, and asshown in appendix 1; see also: FOWLER, 1999a,1999b; FOWLER & PEREZ, 1999; FOWLER et al.,1999; FOWLER, 2002) avoids these problems byconsidering and accounting for all levels ofbiological organization as part of an applicationof the tenets of management in general. Itextends beyond the management of human use

of natural resources; it also applies in otherrealms (e.g., CO2 production or energyconsumption: FOWLER & PEREZ, 1999; or socialand psychological issues: JOHNSON, 1992; CONN,1995).

Management, regardless of its form, is basedon tenets and principles that are seen asimportant. Systemic management is no differentin this regard, and is based, in part, on theprinciple requiring that elements of variousnatural systems be maintained within theirnormal range of natural variation (RAPPORT etal., 1981, 1985; CHRISTENSEN et al., 1996; HOLLING

& MEFFE, 1996; MANGEL et al., 1996; FOWLER,1999a, 1999b; FOWLER et al., 1999; MCCORMICK,1999 and references for appendix 2) —a themetreated more thoroughly below as a primarypoint in this paper. In developing this point,there is documentation of the recognition ofthis principle, the full history of which deservesmore extensive treatment than is possible here.Part of this history involves the conclusion thatadhering to this principle requires the use ofempirical information about variation and itslimits (FOWLER, 1999a, 1999b; FOWLER & PEREZ,1999; FOWLER et al., 1999).

The existence of a normal range of naturalvariation implies that there are limits to suchvariability, but does not rule out the possibilitythat natural variation will change over time,space and environmental circumstances (e.g.,weather and climate). Thus, variation is itselfone of the things that varies; but even it haslimits. It is often pointed out that everything hasits limits (PIMENTEL, 1966; HYAMS, 1976; RAPPORT etal., 1981; PIMM, 1982; RAPPORT et al., 1985; SALTHE,1985; O’NEILL et al., 1986; SLOBODKIN, 1986;KOESTLER, 1987; CLARK, 1989; GRIME, 1989;ROUGHGARDEN, 1989; ORIANS, 1990; ANDERSON, 1991;MEADOWS et al., 1992; PICKETT et al., 1992; MCNEILL,1993; MOOTE et al., 1994; WILBER, 1995; AHL &ALLEN, 1996; CHRISTENSEN et al., 1996; HOLLING, &MEFFE, 1996; MANGEL et al., 1996; NATIONAL MARINE

FISHERIES SERVICE ECOSYSTEM PRINCIPLES ADVISORY PANEL,1998; MULLER et al., 2000; UHL et al., 2000).

Limits are one of the more recognized elementsof nature, as frequently seen in the study ofecology. Limits define natural patterns. Mostgeneral ecology texts address this concept andmany contain words such as limits, or limitingfactors in their indices (e.g., ALLEE et al., 1949;BROWN, 1995; DIAMOND & CASE, 1986; EMLEN, 1973;KREBS, 1972; ODUM, 1959; PLATT & REID, 1967;RICKLEFS, 1973). Any automated search of theavailable ecological or biological literature byusing the term “limits” reveals the extent of itsimportance, especially in the titles and key wordsof many papers published in the biologicalsciences. Limiting factors are often treated interms of the constraints posed by availablenutrients, or other resources, but also include theeffects of predation and disease on populationnumbers, biomass, productivity, or species

10 Fowler & Hobbs

numbers. While the concept is generally welldeveloped in a variety of ecological settings, it ismost commonly used to describe constraints onpopulation size (and the variation of populationnumbers or biomass in space and time).

Some aspects of limits are straightforward(usually hard limits, see below). A populationcannot use more resources than are available,either in total biomass or numbers of species.Similarly, consuming nothing is not an optionfor any species because zero consumptionguarantees extinction. An ecosystem cannotconstitute more than 100% of the biomass inthe biosphere. Other limits are more complicatedas exemplified by the population dynamics ofany species. The limits set on populations resultin central tendencies (commonly called carryingcapacity, K) such that any species’ numbersordinarily tend away from zero and cannot beinfinite —they find a dynamic balance. These aresystemic limits set by combinations of bothintrinsic and extrinsic factors (INGRAM & MOLNAR,1990), or the soft limits of processes, competingor opposing forces, and related rates. For apopulation, these factors include disease,resource limitations, metabolic needs, densitydependence, social dynamics, life history, bodysize, temperature, habitat, behavior, reproductivestrategy, environmental variation, and predation—the list is virtually endless (PIMENTEL, 1966).

This paper includes a partial review of theliterature that addresses limits inherent to naturalvariation to help bring the concept of limits toits proper place in management. The followingmaterial presents a much broader perspective,however, than any focus on populations wouldallow. There is a bias, nevertheless, in considera-tion of biological and ecological systems at theexpense of attention to physical systems (e.g.,variation in tidal cycles, climate change, or riverflow). This bias tends to place emphasis on factorsexemplified by consumption of energy (by bioticsystems), consumption of biomass from thebiosphere, production of CO2, and predationrates. It is a primary goal of this paper tostimulate recognition of the concept of limits asa way to guide human action in regard toinfluence on living systems, as well as finding anappropriate place for humans within suchsystems. A major question is faced in manage-ment: “Can scientifically meaningful 'limits' or'boundaries’ be defined that would provideeffective warning of conditions beyond whichthe nature–society systems incur a significantlyincreased risk of serious degradation?” (KATES etal., 2001).

The sections below begin with a considerationof the terminology used to discuss andcharacterize limits and limitations along withterms used to describe the results of such factors.Following this, there is a section on the factorsthat contribute to limitations —those things thatdo the limiting. It contains a sample of what

collectively comprises the full complexity ofnature —or what many call reality. Next is asection containing examples of the kinds of thingsthat are limited. Again complexity or reality isinvolved because virtually everything finite islimited. The fact that there are risks involved inexceeding the normal range of natural variationis emphasized. These risks are among the factorsthat contribute to establishing limits (e.g., thereare risks to each individual human, exemplifiedby the risk of death associated with bodytemperature outside the normal range of naturalvariation). The paper ends with consideration ofthe application of information about limits, therole of such information in management, andthe definition of management based on suchinformation —systemic management.

Terminology

It is helpful to recognize two categories of limitsintroduced above, each of which will be involvedin the remainder of this paper: soft limits andhard limits. Soft limits arise from a balance offorces or competing rates in natural processes.They are usually invoked long before hard limitsare approached and can be exceeded for variousperiods of time, but not indefinitely. Hard limitsinclude physical limits such as space, or the energycontent of a resource. Thus, true sustainabilityexists only within the combination of limits thatgovern natural systems, each with its own timescale. Temporal scales for soft limits involve thelength of time such limits can be exceeded beforesystemic restorative (homeostatic) forces prevail.

Appendix 2 presents various quotations fromthe literature where it is seen that a wide varietyof terms are used to deal with the concept oflimits to natural variation. Equivalent terms areused in both the scientific and managementliterature, but in different ways. In scientificpublications, various words are used to representlimits that are identified, observed, describedand measured. Descriptions often include theways in which limitation is brought about by thefactors involved —the processes of limitation orthe elements that contribute to limitation. Theterms used in scientific work also describe andidentify the things that are limited. In contrast,the literature on management uses the sameterminology to stress the point that it is importantto do what is possible to maintain systems (suchas ecosystems, and their component species orpopulations) within the normal range of naturalvariation (tenet 3, appendix 1). The literaturealso makes it clear that managers are increasinglyaware that limiting humans becomes bothparamount and the only viable option. It isimportant to limit action so as to avoid risks,including those of doing things that make othersystems fall outside the normal range of theirnatural variation (appendix 1, MCCORMICK, 1999).


Constrain

Variations on this term are often used tocharacterize nature and natural processes(appendix 2; FARNWORTH & GOLLEY, 1974; ALLEN &STARR, 1982; PIMM, 1982, 1984; SALTHE, 1985; FISHER,1986; O’NEILL et al., 1986; STEARNS, 1986; BROWN &MAURER, 1987; GLAZIER, 1987; KOESTLER, 1987; AGEE

& JOHNSON, 1988a; GRIME, 1989; GRUBB, 1989;TILMAN, 1989; BURNS et al., 1991; PONTING, 1991;HANNON, 1992; NARINS, 1992; BROWN, 1995; AHL &ALLEN, 1996; HOLLING & MEFFE, 1996; MANGEL etal., 1996; MULLER et al., 2000). As will be seenbelow, systems place limits on their componentsand the term constrain is used along with othersto convey this concept (e.g., BURNS et al., 1991).Constraining effects are involved in speciesinteracting with each other (e.g., KNOLL, 1989).The term constrain is also used in the literatureon management but it is applied in two ways.First, it is used in terms of action (constraininghuman options, and as a matter of exhibitingconstraint). Second, it is used interpretively. Thatis, empirical information observed in scientificstudies is seen as guidance for action —what toachieve in carrying out constraining action. Theguidance to be used in management is providedby information about natural limits (AGEE &JOHNSON, 1988a; PICKETT et al., 1992; PONTING,1991; CHRISTENSEN et al., 1996; FOWLER et al.,1999).

Limit, limitations, limiting

These words, and other derivatives of the wordlimit are used often, again both with respect tocharacterizing nature (DARWIN, 1953; PIMENTEL,1966; BATESON, 1972; HYMANS, 1976; LEVINTON,1979; STANLEY et al., 1983; YODZIS, 1984; O’NEILL

et al., 1986; AGEE & JOHNSON, 1988a; BUSS, 1988;CLARK, 1989; ROUGHGARDEN, 1989; ORIANS, 1990;WOODWELL, 1990; ANDERSON, 1991; PONTING, 1991;PICKETT et al., 1992; MCNEILL, 1993; SWIMME &BERRY, 1994; WOOD, 1994; ROSENZWEIG, 1995; AHL

& ALLEN, 1996; CHRISTENSEN et al., 1996; NATIONAL


ADVISORY PANEL, 1998) and as important tomanagement (HYMANS, 1976; AGEE & JOHNSON,1988a; ANDERSON, 1991; PONTING, 1991; PICKETT etal., 1992; MCNEILL, 1993; MOOTE et al., 1994;WOOD, 1994; HARDIN, 1995). The concept ofmanagement as a process of limiting humaninfluence is interwoven with the observationand characterization of natural limits.

Threshold, boundary, border

The concept of limits is also embodied in wordsthat refer to transition points (see the use ofthese words or their derivatives in referencessuch as BROWN, 1995; BROWN & MAURER, 1989;CLARK, 1989; ELDREDGE, 1991; HASSELL & MAY, 1989;HENGEVELD, 1990; FUENTES, 1993; MANGEL et al.,

1996; NATIONAL MARINE FISHERIES SERVICE ECOSYSTEM

PRINCIPLES ADVISORY PANEL, 1998; SALTHE, 1985). Inpredator/prey interactions, for example, thereare various component processes that result incyclic or chaotic population dynamics when theyexceed certain levels, often referred to asthresholds or boundaries, also reflected in certainforms of single–species population dynamics (e.g.,HASSELL et al., 1976). However, bounds and bordersalso refer to the combination of upper and lowerlimits that confine sets of viable options (BOTKIN

& SOBEL, 1975; CHRISTENSEN et al., 1996). As withother terms, these are also used both in definingand guiding the process of management (e.g.,see SCHAEFFER & COX, 1992; FUENTES, 1993) as wellas in scientific characterization of nature.

Control

This word is also used in reference to the conceptof limits, especially in regard to the constrainingeffects of a system’s influence on its components(e.g., KOESTLER, 1987; O’NEILL et al., 1986; SALTHE,1985; WILBER, 1995). The collective effects of allparts of a system on any one part are greaterthan the effects of the one on any other (singlepart). Following this observation, it is recognizedthat management cannot ignore the fact thathuman influence on one component of anycomplex system results in indirect effects onother parts of the system as well as those systemsin within which it occurs (secondary effects:PIMM & GILPIN, 1989; second order effects, rippleeffects: DIAMOND, 1989; non–linear effects,domino effects: STANLEY, 1984; “down stream”effects, delayed effects, side effects: PONTING,1991 —all parts of the unintended consequencesof human influence: ROHMAN, 1999) and controlis seen as a concept restricted primarily to humanendeavor (HOLLING & MEFFE, 1996; MANGEL et al.,1996). Humans have no control over othersystems in the sense that no one can change thefact that there will always be secondary (orhigher order) effects of human influence, evenwhen control is attempted. This includes thefeedback of such effects on humans. There arealways unintended consequences (ROHMAN, 1999)to management action and one of the limitsexperienced in management is the inability tochange this fact.

Other terms used in regard to limits andlimiting processes include regulated (LEVIN, 1989),governed, restricted, restrained, confined,proscribed, suppressed, curtailed, channeled,circumscribed, curbed, contained, barriers (CLARK,1989), and resistance.

Still more terms are involved in characterizingthe results of limitations seen in the empiricallyobserved limits to variation. Such characteristicsare the qualities of the limits seen in variation(e.g., range spanned), and the kinds of variationobserved (e.g., bimodal or unimodal) within thenormal ranges of variation between upper and

12 Fowler & Hobbs

lower limits. Natural variation is constrained byboth upper and lower limits. Limits, constraintsand risks do not always increase or decreasemonotonically. The combined effects of thenumerous limitations, as they act in concert, areeven more complicated. An example that is easyto relate to as individual human beings is therisk of mortality from various factors —risks thatincrease for body weight, blood pressure, andbody temperature both above and below themidpoints of the ranges that they span (e.g., seeCALLE et al., 1999, and references therein,regarding weight). Therefore, upper and lowerlimits preclude many options; they function toallow as the only viable alternatives those seenbetween upper and lower limits. The remainingoptions are usually realized with their greatestfrequency at some midpoint between the limits.Thus, there is always an emergence of centraltendencies between upper and lower limits.Limits often operate as opposing forces (oftensoft limits), and the collective balance found insuch opposition contribute to the formation ofpatterns in nature (e.g., see the stochastic analogof equilibrium; BOTKIN & SOBEL, 1975; CHRISTENSEN

et al., 1996). There is terminology associatedwith these patterns, or central tendencies, justas there is for the consideration of any singlecomponent among the factors that contribute tolimiting natural variation.

Mean, mode and median

Statistical names for the measure of centraltendencies include terms such as these (SNEDECOR,1956) to refer to the magnitude of the centraltendency (i.e., its position) within the infiniterange of options among real numbers.

Kurtosis and skewness

These terms refer to the position and concentrationof central tendencies with respect to the upperand lower bounds of variation (SNEDECOR, 1956).Kurtosis refers to the distance between the centraltendency and its limits, the concentration ofobserved measures near the central tendency, orthe flatness and spread of the distribution.Skewness relates more to the degree to whichthere is a lack of symmetry in the variation. Thus,both terms are used in regard to the shape of thefrequency distribution (or probability distribution)of empirically observed variation. Variousmathematical models (e.g., log normal, binomial,Poisson, and others, SNEDECOR, 1956) are availableto represent the probability distribution of variationin its different forms. Transformations are oftenused to convert measures showing non–symmetricdistributions to more symmetric or normaldistributions (especially log transformations, LIMPERT

et al., 2001).Terminology is not confined to the concept of

limits, measures of limits, or the characterization

of variation within limits as treated above.Various terms are also used in reference to theprocesses that contribute to the production ororigin of central tendencies, especially theirpositions. Naturally, these include the limitingprocesses that affect constraint above and belowthe central tendencies. However,, such processesalso include other factors, such as processesinvolving replication or positive feedback thatcontribute to the position of central tendenciesthrough the accumulation of more numerousexamples in the regions of central tendencies.

Homeostasis, balance and feedback

These terms are examples of words regardingthe processes that contribute to the origins ofcentral tendencies (as opposed to simpleconstraint). Specific examples of the elementsinvolved in these processes will be consideredbelow. These processes operate in conjunctionwith all other processes in nature as none canoperate in isolation from the others. The resultsof the synergistic combination of all the processesare the patterns observed to characterize nature(ALLEN & STARR, 1982) —often seen as emergentpatterns (KAUFFMAN, 1993; EL–HANI & EMMECHE,2000) that include the stochastic analog ofequilibrium (BOTKIN & SOBEL, 1975; CHRISTENSEN etal., 1996). These processes are part of what thevarious species (including humans, tenet 9,appendix 1) are exposed to by being part ofsystems such as ecosystems.

Integrity, balance and normal (or natural)

These are terms related to such patterns as thosethat make up, or characterize, natural systems(e.g., GRUMBINE, 1994a) often found in the titlesof papers describing nature (e.g., WILLIAMS, 1964).Many of these patterns are correlative, meaningthat the magnitude of the mean of a variable isrelated to that of another variable (measure) asexemplified by the relationship between thecentral tendency of population density and bodysize for animals (fig. 1, see also DAMUTH, 1987;PETERS, 1983). Others relate to the physicalenvironment as found in relationships betweengeographic range size and latitude (e.g., STEVENS,1992) or predation rates and temperature. Theword integrity is sometimes used with regard tomanagement objectives in the sense of achievingnormal states of nature (e.g., KARR, 1990). Balanceis often seen as a property of nature in view ofthe limits to variation (e.g., PIPER, 1993) andsomething that occurs in spite of variation (i.e.,equilibria are rarely static properties of nature,especially biological systems; BOTKIN & SOBEL, 1975;CHRISTENSEN et al., 1996).

There is yet another set of terms used tocharacterize statistical outliers, extremes, orthings beyond the normal range of naturalvariation (e.g., beyond the limits, MEADOWS et


al., 1992), especially as cases subject to the risksof limiting factors and include words such asabnormal, pathological, deviant, aberrant,atypical, and anomalous. The word unnatural isalso used but must be treated with care.Everything happens naturally and extremesbeyond the normal ranges of natural variationare subject to the natural limits and risks thatmake such extremes rare. Thus, it is not so muchunnatural, as it is abnormal, to observe acharacteristic or condition (such as a fever) as anextreme. Extreme fluctuation is abnormal(CHRISTENSEN et al., 1996) as is often observed forpopulations. Thus the term pathological, orcarcinogenic is used in reference to humanoverpopulation (CALHOUN, 1962; BATESON, 1972;HERN, 1993). At the ecosystem level pathology isalso used to describe problems when atypicalconditions arise (e.g., RAPPORT, 1989a). These arewords that help clarify the distinction betweenthe natural occurrence of extremes and thingsthat fall in the normal range of natural variation.

Factors contributing to limits: complexity I

Limiting factors combine in nature to make up aninterconnected set of forces, risks, and constraints.A major part of scientific endeavor is dedicatedto documenting these factors and the lists thatare available now, while long, only scratch the

surface of the complexity of reality —even intheir combination. The entire complexity withinand among natural systems contributes to boththe collective constraints on variation and to theformation of the central tendencies within suchvariation (e.g., see PIMENTEL, 1966 regarding limitsto population size) as introduced above. Researchon the limits to variation in biological systems hasresulted in the recognition of a great manycontributing factors and an exhaustive list isbeyond the scope of this paper. However, thereare examples worth mention, some of which arefound in appendix 2.

A great deal of literature has accumulatedfrom studies of the factors that limit populationsize. There is a long list, and various categories ofsuch factors are considered to be of importance.Among such categories are parasites, predators,disease, behavior (COHEN et al., 1980), energy,resources (food, prey), space, competition, andnutrition (including needs for individual elementsand their compounds such as amino acids) —allsubjects of a long history of research on populationecology and represented by a sample of referencesin appendix 2 (e.g., PIMENTEL, 1966; FARNWORTH &GOLLEY, 1974; O’NEILL et al., 1986; TILMAN, 1989;MCNEILL, 1993). Other factors include limits on theoptions for life history strategy especially as relatedto body size (DAMUTH, 1987), or the options forpopulation growth and kinds of mortality asrelated to life history strategy (FOWLER, 1988).

Fig. 1. Population density of 368 terrestrial mammalian herbivore species in relation to adultbody mass (DAMUTH, 1987; FOWLER & PEREZ, 1999) as an example of variation in one measure ofa species in relationship to variation in another.

Fig. 1. Densidad de población de 368 especies de mamíferos herbívoros terrestres en relación conla masa corporal de los adultos (DAMUTH, 1987; FOWLER & PEREZ, 1999) como ejemplo de variaciónde una medida en una especie respecto a la variación en otra especie.

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14 Fowler & Hobbs

The limitation of populations by micro-organisms (diseases or pathogens) or other pestshas been of special focus in many studies and arefactors recognized by PIMENTEL (1966), FARNWORTH

& GOLLEY (1974), STANLEY et al. (1983), and TILMAN

(1989). A review of such limitations has beenconducted by MCCALLUM & DOBSON (1995).However, it is clear that microscopic or smallbodied consumers are not the only category ofspecies known to contribute to the limitationson the population size of their hosts. Consumerspecies that are of larger body size than theirconsumed prey/resources are also involved (e.g.,predators and herbivores; STANLEY et al., 1983;O’NEILL et al., 1986; MCNEILL, 1993). Whethermicroscopic or not, the degree to which onespecies acts to limit the population of anothervaries from case to case. Removing predatorsexperimentally to rid their resources of suchinfluence often results in population increases,but not always. Limiting influence is thus only atendency and rarely predictable owing to thecomplicated nature of the interactions and factorsthat influence them (PIMM, 1991). In the finalanalysis, mortality caused by consumers or diseasecount among the many factors that contributeto limiting population size but are not the onlyfactors involved.

Sunlight provides the energy that is passedthrough the food webs of communities andecosystems. This energy is involved in metabolism,growth, reproduction and survival. It is notlimitless in its flow through biological systems,however, and is among the factors that havebeen studied for a variety of such systems fromcells to the biosphere. As such, energeticconstraints are not confined to setting limits onpopulation size and the various limits involvingenergy are represented by a voluminousliterature. Energy has been noted as a limitingfactor in a variety of biological systems by BROWN

(1981), PIMM (1982, 1984), YODZIS (1984), BROWN

& MAURER (1987), GLAZIER (1987), GASTON (1988),TILMAN (1989), and HANNON (1992). Energy isclearly not the only limiting factor for biologicalsystems. The more general issue of resources(including nutrients of various kinds) asconstraining factors is often noted (STANLEY etal., 1983; O’NEILL et al., 1986; MCNEILL, 1993),occasionally as expressed through competition(PIMENTEL, 1966; STANLEY et al., 1983).

Another important resource is space (or habitatsize). Thus, space is also frequently identified asa limiting factor, including its limitations onspecies numbers in addition to its constraints onpopulation size (e.g., STANLEY et al., 1983; O’NEILL

et al., 1986; ROSENZWEIG, 1995; BROWN, 1995).Extinction is also a limiting factor (BROWN &

MAURER, 1987), perhaps an ultimate limiting factor(at times a soft limit with a long time scale), andone that has its effects on species numbers,diversity, communities (ARNOLD & FRISTRUP, 1982;FOWLER & MACMAHON, 1982; GOULD, 1982;

ELDREDGE, 1985; KITCHELL, 1985; LEVINTON, 1988;BROWN, 1995; ROSENZWEIG, 1995), and body size(i.e., as a contributing factor in limiting themaximum size observed among species, e.g., seeVAN VALEN, 1973; BARANOSKY, 1989; FOWLER &MACMAHON, 1982; BROWN, 1995). Thus, extinctionat the species–level, like death at the individual–level, is one of the risks associated with theextremes characterized as pathological orabnormal. Extinction is a limiting factor thatalso exemplifies a process rather than a physicalentity in its limiting action (soft limit in involvinglong time scales).

Other limitations involve morphological factors(PIMM, 1982, 1984; FISHER, 1986; BROWN, 1995),functional, historical, and evolutionary elements(PICKETT et al., 1992), physiology, and behavior(BROWN, 1995), various population dynamical forces(as well as other dynamics; PIMENTEL, 1966;LEVINTON, 1979; PIMM, 1982, 1984; ROSENZWEIG,1995), environmental predictability (LEVINTON,1979), environmental heterogeneity (PIMENTEL,1966), evolutionary forces (including geneticfeedback mechanisms, PIMENTEL, 1966; FOWLER &MACMAHON, 1982; PIMM, 1984), and the availabilityof genetic (raw) material (GRUBB, 1989). Nutrition,space, toxic materials, competition, predation,cannibalism, and stress are all limiting factors(ROSENZWEIG, 1974). There is little, if anything,that can be ignored in the complexity of factorsthat limit variability (PIMENTEL, 1966).

It must be recognized that there are two moreclosely interrelated categories of limiting factors(each involving both hard and soft limits)depending on whether they are extrinsic orintrinsic to the system showing variation (INGRAM

& MOLNAR, 1990). Variation limited by extrinsicfactors in biological systems includes the effectsof disease, predation, competition, habitat size,and resource availability on population size.Intrinsic factors limiting population size include,body size, behavior, and the birth and death ratesinvolved in life history strategies. At the sametime such factors are observed to contribute tolimitations, they also have their influence on theposition of central tendencies. Intrinsic andextrinsic factors are involved in the limitation ofany system and its interactions with other systems.

As amplified in the next section, there are avariety of levels of biological organization towhich limiting factors apply. These span therange from sub–cellular structures, to cells,organs, individual organisms, populations,species, communities and ecosystems, throughto biomes and the biosphere. It is easy to findexamples of limiting factors for each level ofbiological organization. At the individual level,body size is limited by extrinsic factors such asfood availability, and intrinsic factors such asmetabolic dynamics. This list goes on to includemortality at the individual level, and extinctionat the species level. At the community orecosystem level, species numbers are limited


extrinsically through factors exemplified by energyand space, and intrinsically by evolutionary factorsand population dynamics. Collectively, all speciesin an ecosystem interact with each other suchthat each one is subject to the constraintsemergent from the combined effects of the others.This happens in all systems such that the extrinsicfactors that impose limits include those throughwhich a system poses limits to its parts or itscomponents (e.g., AHL & ALLEN, 1996; MULLER etal., 2000). These include the processes of naturalselection involving death and extinction.

Both intrinsic and extrinsic factors operatesimultaneously and collectively in natural systems(INGRAM & MOLNAR, 1990) —sometimes reinforcing,sometimes nullifying each other. The degree towhich such things happen varies from case tocase. Furthermore, synergistic effects andinteractions among such factors are common. Thecombined action of such factors result in observedpatterns (e.g., as observed in the results of variousforms of natural selection; ARNOLD & FRISTRUP,1982; FOWLER & MACMAHON, 1982; GOULD, 1982;LEVINTON, 1988). Thus, patterns are the results ofsystemic effects, or the effects of the entire suiteof limiting factors and all of their interactions.Some of these patterns in nature are partiallyexplained by the balances that result from limitingfactors that function to reinforce or oppose oneanother. Balances resulting from the latter areespecially important in observed patterns.Extinction acting to limit the options for naturalselection at the individual level provides a goodexample (ALEXANDER & BORGIA, 1978; FOWLER &MACMAHON, 1982; GOULD, 1982; LEVINTON, 1988).Other patterns result from parallel, or reinforcing,effects. Examples of factors that may work inconcert are seen in the interplay of body size,population size and geographic range (BROWN &MAURER, 1987; GASTON & BLACKBURN, 2000) onextinction rates. Species of large body size andspecies with small geographical ranges appear tohave higher extinction rates. This may contributeto there being fewer species that are large bodiedwith small geographic ranges compared to specieswith small bodies and large ranges.

The things with constrained variation:complexity II

Limitations are imposed on all components andprocesses at each level of biological organization.Whether it be a cell, physiological process,population, predation rate, total populationbiomass, speciation, or number of species, it issomething with variation that is subject to limits.This section turns from the things that exert limitinginfluences reviewed in the previous section toexamples of the things that are subject tolimitations. These include such things as body size,blood pressure, and heart rates for individualanimals. The components of ecosystems and

ecosystems themselves are also subject to limitations(NATIONAL MARINE FISHERIES SERVICE ECOSYSTEM PRINCIPLES

ADVISORY PANEL, 1998; HAGEN, 1992).Population size and population variation are

limited. There is a voluminous literature treatinglimits to population size (e.g., HOLLING, 1966;PIMENTEL, 1966; FARNWORTH & GOLLEY, 1974; O’NEILL

et al., 1986; GLAZIER, 1987; SINCLAIR, 1989; TILMAN,1989) that cannot be ignored. Many things thatlimit population size per se are also factors thatlimit population variation which is limited withinspecies as well as among species (SPENCER & COLLIE,1997; FOWLER & PEREZ, 1999). Variation in generalis limited and population variation is an example(BUSS, 1988; HOLLING, 1966; O’NEILL et al., 1986).The results of work on populations serve as anexample of insight that would be expected forother aspects of biological systems had theybeen the subject of equivalent study.

Other factors are far from ignored, however. Inaddition to population size and variation, the limitsin variation have been shown for a variety ofbiological processes and dynamics. The evolutionaryprocess is not free of limitations (e.g., GRUBB, 1989).For example, the extent of evolutionary change islimited (FISHER, 1986) because evolution is“channeled” by various constraints (GRIME, 1989).The general concept is exemplified by the lack ofevolutionary options as limited by cell structure.There are no single celled organisms that weigh ametric ton. Other processes are also limited. Thebehavior of organisms and its evolution is limited(NARINS, 1992). The variety of dynamics of (andwithin) communities and ecosystems are limited(LEVIN, 1989; PIMM, 1982). These include the flow ofenergy among species (owing to the limitationsestablished by the inefficiency of metabolic,photosynthetic, and digestive processes). As willbe seen, processes such as predation, CO2production, reproduction and mortality all fit withinlimits.

The size of cells and the qualities of individualorganisms are limited just as the qualities ofpopulations and ecosystems are (again by bothintrinsic and extrinsic factors, INGRAM & MOLNAR,1990; HAGEN, 1992; TILMAN, 1989). The charac-teristics and qualities of species are limited by,among other things, a variety of evolutionaryprocesses as well as intrinsic factors. Amongspecies groups, attributes are limited by selectiveextinction which often involves intrinsic andextrinsic factors operating in concert (ARNOLD &FRISTRUP, 1982; FOWLER & MACMAHON, 1982; GOULD,1982; STANLEY et al., 1983; LEVINTON, 1988). Thereare limits to diversity (HUTCHINSON, 1972; INGRAM

& MOLNAR, 1990).Other factors that are subject to limits include

range size (PAGEL et al., 1991; STANLEY, 1989;GASTON & BLACKBURN, 2000), the total number ofspecies (VALENTINE, 1990) and length of foodchains (PIMM & LAWTON, 1977; LEVINTON, 1979;PIMM, 1984; YODZIS, 1984). Variation within andamong ecosystems and that of ecological

16 Fowler & Hobbs

communities are constrained by the influence offactors such as selective extinction (ALEXANDER &BORGIA, 1978; FOWLER & MACMAHON, 1982; ARNOLD

& FRISTRUP, 1982; GOULD, 1982; ELDREDGE, 1985;KITCHELL, 1985; LEVINTON, 1988; HERRERA, 1992;GASTON & BLACKBURN, 2000), including limitationson the numbers of species (e.g., the size of themembership of a community as the count ofspecies, ROUGHGARDEN, 1989; GLAZIER, 1987) orspecies richness (LEVINTON, 1979). The numbers ofspecies consumed by a consumer and the numberof consumers that consume a particular preyspecies are constrained (MARTINEZ, 1994). Thequalities of species involved in communities andecosystems are limited as exemplified by thesmall number of species with large body sizecompared to small–bodied species (FOWLER &MACMAHON, 1982; BROWN & MAURER, 1987). Withincommunities and ecosystems the number oftrophic levels are limited (ROSENZWEIG, 1995).Constraints influence most of the patterns anddynamics of (and within) communities andecosystems (LEVIN, 1989; PIMM, 1982).

The components of systems are limited, amongother things, by the systems of which they are apart. There is a substantial body of literature thatpresents a helpful interpretation of the collectiveeffects of limiting factors —that is, the limitationsresulting from the suite of all factors actingtogether, regardless of what is being limited. Insuch work, it is pointed out that the collectiveeffects of complex systems control, constrain orotherwise limit their components (e.g., DYLE, 1988;KOESTLER, 1987; O’NEILL et al., 1986; SALTHE, 1985;WILBER, 1995; MULLER et al., 2000). An examplewould be the limiting influence of an ecosystemon its component species and their populations(O’NEILL et al., 1986).

Such work adds to the importance of theobservation that everything is subject to limits.Everything (everything finite) is part of a moreinclusive system which includes all of the factorsthat contribute to setting limits. Thus, withinbiological systems, each thing chosen for scientificstudy will be limited by the more inclusive orcollective level of biological organization of whichit is a part, along with the non–biological elementsand processes of its environment (sometimesreferred to as context, appendix 1). This is amatter of scale as noted by AHL & ALLEN (1996)who point out that small–scale entities are limitedby the larger scale entities. Much of the literaturemakes the point more generally: all componentsof more inclusive systems are limited by thecollective influence of the factors to which theyare exposed (e.g., BATESON, 1972; ALLEN & STARR,1982; MAYR, 1982; SALTHE, 1985; O’NEILL et al.,1986; KOESTLER, 1987; BUSS, 1988; ORIANS, 1990;BURNS et al., 1991; MCNEILL, 1993; AHL & ALLEN,1996; MULLER et al., 2000). And everything finite isa component of some larger system (WILBER, 1995).It must be concluded that everything is subject tolimits in its natural variation.

Personal experience emphasizes this fact.Perhaps this is recognized most clearly in observingthat humans are limited in what can be known(FOWLER et al., 1999) or what can be conceptualized(MCINTYRE, 1997). Thus, not only are there limitsto what can be done and what humans can be,but humans are limited in what can be understood.Knowledge itself is limited. In part, the experienceof these limits, along with other limitations, isrelated to the fact that finite things are, by theirvery nature, limited. The models used to representthings can not be all inclusive and the results ofexercises based on models are thereby subject toerror; being limited, models are real but notreality, just as maps are not the territory (BATESON,1972, 1979; models are never the reality theyrepresent). Thus, science is limited. This isexperienced in the inability to recombineinformation from the things that are studied(what might be called the Humpty–Dumpty effect,or syndrome, NIXON & KREMER, 1977; DUNSTAN &JOPE, 1993; REGAL, 1996; HORGAN, 1999). Even moreof the limits of science are experienced in theinability to adequately or accurately assignimportance to the influence (limiting or otherwise)of each factor made the focus of research (ALLEN

& STARR, 1982; BARTHOLOMEW, 1982; ROSENBERG,1985; SALTHE, 1985; GROSS, 1989; PETERS, 1991;PICKETT et al., 1994).

There is a continued experience of limitationsin progression from science (e.g., PETERS, 1991;STANLEY, 1995) to management. As alreadymentioned, the options for management arelimited in that humans cannot control the factthat there will always be unintended consequencesto management action. There is no control overother systems to avoid such effects. The tenets ofmanagement limit what can be done; they arebased on principles that exert a form of naturalselection among the options. Humans are limited,as in everything else, in management. It is time tomanage with limits in mind.

Utility / practical application

Patterns arise, in part, from the limits to variationresulting from the vast array of inter-relationshipsamong the various elements of nature operatingsimultaneously. Variation itself, both within, andas a part of pattern, is also a product of thiscomplexity. Everything is subject to the influenceof the elements in its environment (context,BATESON, 1972, and extrinsic factors) along withthe influence of its components (WILBER, 1995;intrinsic factors). Are these observations of nomore than philosophical interest? Many can beeasily documented or experienced personally,but of what use are they?

One tenet of management requires that things(e.g., biological systems and processes) bemaintained within the normal range of naturalvariation (tenet 3, appendix 1). There is an


especially important element of responsibility forimplementing this element of management withrespect to biological systems. Such requirementshave long been recognized in human andveterinary medicine. This is now being extendedto ecosystems and all of their components,including humans (e.g., CHRISTENSEN et al., 1996;MANGEL et al., 1996; MCCORMICK, 1999, appendix 1and 2). Various panels and groups convened toaddress the management process (especially atthe ecosystem level) have reached the conclusionthat this is an essential tenet of management(e.g., NATIONAL MARINE FISHERIES SERVICE ECOSYSTEM

PRINCIPLES ADVISORY PANEL, 1998, appendix 2). MOOTE

et al. (1994) were clear that ecosystems and naturalpatterns are the result of limits and that humanshave the responsibility to fall within such limits.Managers are responsible for doing what can bedone to ensure that ecosystems fall within thenormal range of natural variation. However, thisconclusion is not restricted to individuals, species,ecosystems or communities. It applies to nature(e.g., combinations of biological systems) ingeneral (e.g., DARWIN, 1953; PICKETT et al., 1992;SALZMAN, 1994; WOOD, 1994; CHRISTENSEN et al.,1996; NATIONAL MARINE FISHERIES SERVICE ECOSYSTEM

PRINCIPLES ADVISORY PANEL, 1998). Managementshould be carried out by doing everything possibleto ensure that biological systems fall within theirnormal range of natural variation. Doing so is atthe core of systemic management.

Part of the concept of normal involves what isnatural. Much of the literature on managementemphasizes the importance of doing things tomaintain or recover natural states regardless ofwhether it is for individuals, species, communitiesor ecosystems. Recent literature regardingecosystems illustrates the progression in thedevelopment of this concept from its acceptanceat the individual level to its application at higherlevels of biological organization (HOLLING & MEFFE,1996; MANGEL et al., 1996; RAPPORT et al., 1981,1985; DAVIS & SIMON, 1994; CHRISTENSEN et al., 1996;FOWLER, 1999a, 1999b; FOWLER et al., 1999). Theword intact is used to refer to systems that are“healthy” or “undamaged” (ANDERSON, 1991). Suchconcepts are meaningless without frames ofreference. Thus, “natural” patterns are often seenas those that fall within the normal limits ofvariation, not only for physical structure but also fornatural processes. There is need for care here. It isimportant to be mindful of the fact that it is naturalfor there to be occasional outliers as examplesbeyond the normal range of natural variation andwhen such occasions arise, they are subject to thenatural effects of limits (i.e., the natural phenomenathat set limits, pose risks, and prevent the occurrenceof more such extremes —risks exemplified by deathand extinction).

It is also important to account for humaninfluence. There are few if any systems left on theplanet that have not been subjected to abnormalhuman influence and the problem of providing

reference points is growing (DAYTON, 1998).However, all species influence their ecosystemsand the other species in such systems. The extentof human influence would not be a particularlylarge problem if anthropogenic effects were notthemselves abnormal as will be seen in the sectionsahead. As a result of the extensive humaninfluence it is important to define “normal” and“natural” so as to focus more on situationswherein human influence itself is not abnormal;that is, within the range of natural variation ofinfluences that other species exhibit.

Attempts to apply the concepts of “normal”and “natural” include efforts to return ecosystemsto normal states. However, restoration (e.g.,ecosystem restoration, JORDAN et al., 1987) cannotbe a recovery of the past —a clear hard limit isthe irreversibility of time. It is possible to learnfrom history, and seek guiding information frompatterns historically observed, but it is impossibleto reconstruct what existed in the past. Changeis a permanent part of the processes that cannotbe avoided, especially change resulting fromaction taken in management.

When considering management, it is impossibleto escape the concept of what should be andhence, the matter of ethics. The material presentedhere is based on the assumption that the tenetsthat have been accepted in the literature are, infact, important. Tenet 3 (appendix 1) emphasizesthe importance of acting so as to facilitate anybiological system’s falling within its normal rangeof natural variation (whether such a system be acell, organ, individual, population, species,ecosystem or the biosphere). It is worth pointingout, however, that there are religious elements tothe ethic behind this tenet that are of longstanding importance (e.g., CLARK, 1989; PONTING,1991). An in–depth treatment of ethical issues, ortheir history, is beyond the scope of this paper.

Another tenet of management is that of havingmeasurable goals and objectives; there need to benorms, standards, reference points, guidelines andcriteria to go by (tenet 7, appendix 1). These areprovided through systemic management: thecentral tendencies and statistical confidence limitsobserved in natural variation provide such guidance.They represent options that are optimal inminimizing risk —not just any particular set, butall risks working in concert. These risks andconstraints are the entire suite of factorsexperienced by systems such as cells, species, orindividuals in the real world. Thus, the empiricallyobserved central tendencies fall between the upperand lower limits observed for variation subject tothe all limiting factors of the real world actingsynergistically. Therefore, understanding limits, andtaking advantage of the results of their action,provides a great deal to go on in this regard andprovides hope of implementing sound management(DARWIN, 1953).

This is the concept behind the medicalperception of health when action is taken to

18 Fowler & Hobbs

restore body temperature, blood pressure, or bodyweight that is abnormal. Thus, the normativeconcept of health can be applied whether toindividuals (e.g., in maintaining proper cholesterolor blood sugar levels) or ecosystems (RAPPORT, 1989b;EHRENFELD, 1993; HOLLING & MEFFE, 1996) byimplementing the concept of evaluation withregard to normal variation (KING, 1993). Just asprocesses within individuals (e.g., metabolism,digestion, respiration) are important to manage-ment in this regard, so are the processes withinthe higher levels of biological organization, suchas nutrient flow in ecosystems (e.g., HOLLING &MEFFE, 1996). Other ecosystem features that aresubject to limited natural variation include numbersof species, trophic structure, energy storage,population variation and total biomass levels.

How are the goals and standards from centraltendencies of use? Such information can be usedto evaluate both human and non–human systems.What happens if the characteristics of anecosystem are outside the normal range of naturalvariation? Direct management of ecosystems isimpossible because of the lack of control overecosystems (EHRENFELD, 1981; MCNEILL, 1989; HOLLING

& MEFFE, 1996; MANGEL et al., 1996; COMMITTEE ON

ECOSYSTEM MANAGEMENT FOR SUSTAINABLE MARINE

FISHERIES, 1999; FRANCIS et al., 1999). That is,management cannot be carried out to avoid manyof the effects of attempted control (whether it becontrol of other individuals, species ecosystems,or the biosphere); many such consequences areunintentional and unpredicted. However,, humansdo influence ecosystems, as do all species. Bothpast and present human influence has resulted inecosystems that exhibit abnormal qualities, butinfluence is something that every species has.Human influence may be interpreted as a limitedform of control over ecosystems, but managementcan not control the fact that there will beunintended consequences (ROHMAN, 1999) as theside effects of influence. This lack of control isone of the limitations that is experienced inmanagement in general. It is impossible to exertinfluence and, at the same time, know or controlall of the effects. In part, the lack of control stemsfrom being a part of ecosystems —humans arecomponents (and the human species is acomponent, tenet 9, appendix 1) subject to thecollective limits described above (BATESON, 1972;O’NEILL et al., 1986; KOESTLER, 1987; O’NEILL et al.,1986; SALTHE, 1985; WILBER, 1995).

So where do the central tendencies havepractical application? How can management usesuch information in view of the fact that allinfluences lead to secondary (or other higherorder) effects, at least some of which will resultin feedback over various scales of time thatplaces (or will place) limits on humans? The 8thtenet of management (appendix 1) is based onthe fact that the elements over which there ismost control are the human elements, recogniz-ing that even in self control there will be

ramifications in the rest of the systems of whichhumans are a part. Some of these effects will bedesirable from certain points of view, but otherswill be negative (that is, many of the effects ofmanagement action will result in feedback thatwill have limiting effects on individual humansand our species). All effects would be positive ifmanagers had full control, but it is humanlyimpossible to control or predict which will bebeneficial and which will not (WOOD, 1994). Eventaking mitigating action to avoid influencesbeyond those intended will always have itsunintended consequences. There is one remainingalternative. It is the option of exerting self control(intransitive or passive management in whichhumans regulate what humans do, MCCORMICK,1999). To exercise this option humans doeverything possible so that humans fall withinthe normal range of natural variation, guided bycentral tendencies.

This is a critical point. What it means tomanagement is: humans undertake change to exertinfluence and exhibit characteristics so as to be apart of biological systems in which humans fallwithin the normal range of natural variation(DARWIN, 1953; OVINGTON, 1975; PICKETT et al., 1992;FUENTES, 1993; MCNEILL, 1993; GRUMBINE, 1994b;MOOTE et al., 1994; SALZMAN, 1994; WOOD, 1994;MANGEL et al., 1996; CLARK, 1989; UHL et al., 2000).As suggested by APOLLONIO (1994), humans havethe alternative of mimicking other species. Otherspecies serve as empirical examples of sustainability.Mimicking can be accomplished by ensuring thathumans fall within the normal range of naturalvariation (especially in finding positions near centraltendencies as standards of reference, ormanagement guidelines, FOWLER et al., 1999). Thisamounts to an extension of biomimicry (BENYUS,1997) to the species level to address not onlyquestions about how to feed ourselves, but alsohow many humans there should there be to feed.Alternatively it can be viewed as parallel to theprocess of benchmarking in business management(SPENDOLINI, 1992; BOGAN & ENGLISH, 1994; BOXWELL,1994; CAMP, 1995), with hierarchical options. First,managers can find the advisable constraints onwhat businesses are and do (as in conventionalbenchmarking), and secondly, managers can addressthe meta–level question of whether or not anyparticular business should even exist, and if so atwhat level they carry out their functions andinfluence. It is an application of restoration ecologyto restore human involvement in nature so as tofall within the normal range of natural variation.Nature has been carrying out a form of adaptivemanagement (HOLLING, 1978; WALTERS & HILBORN,1978; WALTERS, 1986) over evolutionary time scalesso that it is now possible to take advantage ofeons of natural experiments with sample sizesinvolving millions of trials. In short, it is possible tolearn from nature (GRUMBINE, 1994b), or learn tolive as humans by observing other species, much inline with the philosophy of Thoreau and Muir


(who saw “...sensitive observation of nature as thesource of wisdom,” NORTON, 1994), or Leopold“who pointed out that wilderness provides a ‘base–datum of normality’” (CHRISTENSEN et al., 1996).

The degree to which current forms ofmanagement are transitive varies. Terrestrialsystems are often more engineered in agriculturalpractices than are marine systems (however,aquaculture is quite transitive in this regard).Most fisheries are managed by controlling thefishing effort; nevertheless fish populations aretransitively driven to predetermined levels to elicitdesired productivity without serious or exhaustiveconsideration of the systemic consequences. Nosuch transitive management has withstood thetest of evolutionary time scales and suchapproaches fail to acknowledge the track recordof human failure in similar circumstances interrestrial settings (e.g., PONTING, 1991).

Regardless of context, however, what is beingdone in most of current management ignoreslimits as they apply to humans. Management failsto place humans within the normal range ofnatural variation in conventional approaches —afact that is often mentioned in the literature onmanagement and especially in literature criticalof conventional management practices (e.g.,GADGIL & BERKES, 1991). This point is maderepeatedly in work that draws empiricalinformation produced in scientific studies to theattention of society, particularly managers.Shortcomings and failures are most clear withregard to management at the ecosystem levelwhere the need for changes and alternatives areemphasized (e.G., AGEE & JOHNSON, 1988a).However, among scientists, the full importance oflimits is not always recognized (GRUBB, 1989).Socially, freedom is often confused with ignoringthe laws of nature (JOHNSTON, 1991). PIANKA (1974)sees a generic pattern in human failure to see thewisdom of finding a place (“balance”) betweenupper and lower limits. Many of the world’sproblems today can be attributed to the lack ofthis mode of management (WOODWELL, 1990).Continuing to ignore limits is no longer a tenableoption (CLARK, 1989; MANGEL et al., 1996; NATIONAL


ADVISORY PANEL, 1998). It is of paramountimportance to find a place for humans within thenormal limits of natural variation. As will be seenlater in this paper, there are many cases wherehumans are so far outside the normal range ofnatural variation that other elements of biologicalsystems have responded to show abnormalvariation themselves (CHRSITENSEN et al., 1996). Inthe end, there is really no choice but that offinding the human place within the limits of thesystems of which humans are a part (MCNEILL,1993). The effects already caused by the cases ofhuman abnormality, or pathology, continue tounfold through delayed consequences. Hopefullythese are not so extreme as to preclude otherwiseviable options for management. The risks resulting

from past actions are risks that are yet to befaced (OVINGTON, 1975) and the remaining hope isthat actions taken now will both avoid furtherrisk as well as reduce risk from past mismanage-ment. One of the challenges will be to conductresearch that provides needed information (ORIANS,1990; KATES et al., 2001, tenets 5 and 6,appendix 1). This clearly includes demonstrationof the central tendencies of natural variation,and displaying them in graphic form (FOWLER &PEREZ, 1999). These central tendencies occurbetween limits. As maintained by CLARK (1989),one of the main functions of scientific endeavor isthe production of information about limits —theybound the central tendencies and present managerswith viable options to address one of the mainquestions of sustainability science (as quoted inthe introduction, KATES et al., 2001).

Discussion: systemic management, a movein the right direction

What happens if management follows theguidelines established to avoid the problemscreated by current approaches? The various tenetsof management in appendix 1 have been developedover the last several decades in trying to solvemanagement problems (e.g., CHRISTENSEN et al.,1996; MANGEL et al., 1996; NATIONAL MARINE FISHERIES

SERVICE ECOSYSTEM PRINCIPLES AAVISORY PANEL, 1998;UNITED STATES INTERAGENCY ECOSYSTEM MANAGEMENT

TASK FORCE, 1995; COMMITTEE ON ECOSYSTEM

MANAGEMENT FOR SUSTAINABLE MARINE FISHERIES, 1999;MCCORMICK, 1999). Can management adhere tothem? Is it possible to avoid exacerbating problemsinherited from past actions while expanding thescope of management? Is it possible to includeecosystems or the biosphere without giving up onspecies or individuals as important levels ofbiological organization to which managementapplies? The implementation of systemicmanagement will lead toward accomplishingthese objectives (even if there is no guaranteethat future problems from the failures of pastmanagement can be avoided). It is a form ofmanagement that emerges from past practicesand draws on the lessons learned fromexperience. As stated at the outset, it embodiesthe principles that have emerged from concertedeffort to deal with problems that have not beenavoided in traditional management. Thefollowing sections provide more depth to thedefinition of systemic management.

There is progress toward systemic managementseen in some of the conclusions reached inattempts to develop management at theecosystem level (“ecosystem management”). Oneconclusion is particularly important. As reviewedabove, it is not possible to manage ecosystems,but, at the same time, it is imperative thatecosystems be taken into account —along withthe rest of complexity (especially in managing

20 Fowler & Hobbs

human interactions with various biotic systems).It is important that management proceed in waysthat apply, not only at the ecosystem level, butalso at the levels of individual, species, and thebiosphere. Single–species approaches should notbe abandoned to focus on ecosystems, or viseversa. How are such multiple goals accomplishedby systemic management? How can managementdeal with the fact that the forces and process ofindividuals, populations, species, ecosystems andthe biosphere are often in opposition (e.g., WILSON

& SOBER, 1989; WILLIAMS, 1992)? Highly trainedand experienced specialists are often at odds witheach other based on conflicting interpretations inconventional management, in part because ofthe many opposing forces of nature. How doesadopting the principle of confining variation towithin its normal limits lead to adhering to thetenets of management, one of which requiresthat such issues be dealt with consistently (e.g.,across disciplines)?

Limits to management options

There are limitations on the options formanagement, consistent with there beinglimitations on everything. This is seen in theapplication of the tenets of management. Suchlimits lead to the elimination of many manage-ment options. Applying these limits is a processthat helps focus on what is possible and avoidsthe waste and problems created by trying thingsthat will not work. Within the full, or unlimited,suite of options are those that involve controllingnon–human species, ecosystems, or the biosphere,as often attempted in the past. Attempts havebeen made, and more might be undertaken, todirectly control these systems without fullyconsidering the effects, especially those that resultin risks —particularly to humans, and particularlyin the long run. However, it is increasingly clearthat these options can no longer be considered(tenet 8, appendix 1 and 2, and as concluded inthe literature referred to above) because, in eachand every case, there are always uncontrollableside effects that are systemic in nature —somewith negative consequences for ourselves (e.g.,through the effects on the human environmentthat result in problems such as emergent diseases,RAPPORT & WHITFORD, 1999, or loss of resources).There are unintended consequences (negative orpositive, ROHMAN, 1999) to every managementaction. They may involve humans directly as parti-cipants in various systems, or indirectly througheffects on other members of such systems (whetherindividuals, species, ecosystems). It is impossible tocontrol the fact that such things happen. Thisleaves only options involving the control of humanactivities and the regulation of human influence(e.g., fish can not be regulated but commercialfishing can). By taking this approach, managementinvolves finding appropriate levels of influence byhumans (complete with all of their ramifications,

positive or negative). Management can, forexample, proceed by addressing appropriate levelsof biomass consumption, whether from a speciesor an ecosystem, the numbers of species used asresources, or the extent of habitat to be protected(habitat for which direct influence is prohibited).

Considerable progress has been made in thestep outlined in the previous paragraph —progressmade by eliminating options, as tempting as theymight be, that would be counterproductive,wasteful or impossible. This is an important juncture—that of recognizing what remains as viablemanagement options. Among the remainingpossibilities is that of finding sustainable levels ofhuman influence. Human influences on each levelof biological organization are things that can beaddressed and things that are critically importantto be addressed. However, the list of such things isenormous; this again brings managers to aconfrontation with the complexity of nature, butall as part of considering complexity in achievingsustainability. Here it appears in regard to thewealth of ways in which humans (and all individualsand species) exert influence or interact with otherelements of the human environment. This diversityis only superficially exemplified by measures ofsuch things as how much humans eat, the quantityof fish harvested from a population, volume ofCO2 added to the atmosphere, or the portion ofthe various habitats that humans occupy in anyecosystem.

Using empirically observed limits

This section returns to the point of addressinghow information on variation, and especiallyinformation on the limits to variation, is useful.At this point, what might appear esotericregarding the concept of limits becomes practicalthrough empirically observed limits. How canmanagement make the transition from traditionalto systemic?

Every species has a wealth of influences on theother elements of related systems —all consistentwith, and emergent from, the complexity ofreality. The limits that they experience are thoseobserved. Observed limits include both thecharacteristics of other species as well as theirinfluences. Thus, what is seen are the things thatwork, the things that can be done to minimizethe risk of failure as exemplified by death orextinction. Other species survive the full range ofconsequences of such influence, whether on otherspecies, ecosystems or individuals. Managers thushave the full benefit of knowing that theinfluences of other species, along with all relatedprocesses and consequences, have normal ranges ofnatural variation —limits. There are empirical limitsto the variation of such influences because theinfluence species have on each other and othersystems also has limits. In this regard, existing speciesrepresent empirical examples of sustainability.

However, some alternatives within the normal


range of natural variation are better than others.These are the various alternatives between theupper and lower limits of natural variation thatare emphasized in being represented by apredominance of examples —by their abundance,or frequency of occurrence. For individualorganisms this is exemplified by the abundanceof people with body temperatures close to 37ºCcompared to the less frequent occurrence ofindividuals at either the high or low extremesbounding variation in body temperature. Forspecies, it is the same. Better examples are foundin the abundance of species representing aparticular measure, especially the cluster ofspecies near the central tendencies of naturalvariation. Species, as empirical examples ofsustainability, represent the successes in nature’smulti–level, trial–and–error, game of survival(FOWLER & MACMAHON, 1982; LEVINTON, 1988).Measures of other species reveal probabilitydistributions as naturally occurring Nashequilibria (NASH, 1950) in which the centraltendencies change over time and space accordingto environmental conditions. Nash equilibria aredefined in terms of game theory, and, in thiscase, the games involve players (such as species)which are parts of systems (such as ecosystems)involved in their own games. Things have towork for both the systems and their parts atmultiple levels.

Beyond the limits of variation among species,examples are rare because, by definition, risksand limits prevent the occurrence of such species.For example, there are no 100 ton mammals thatgive birth to one offspring at the end of a 400 yearlifetime, that consume only one carnivorousspecies from the 14th trophic level, and that areconfined to arid deserts — they don’t exist (FOWLER

& MACMAHON, 1982). Likewise, there is so muchinfluence exerted by species that consume all oftheir resources that their existence is precluded.By confining human species–level influence towithin the normal range of natural variation, it ispossible to simultaneously avoid risk and achievesustainability. Decisions to seek the extremes, tacitor overt, are actions bound to lead to increasedand unwanted risks. It is impossible to avoid theside effects of any action, but there is emphasis tobe placed on the need to avoid the risks thatprevent the accumulation of species beyond thenormal range of natural variation. It is possible toachieve sustainability as exemplified by empiricalexamples that have faced the complexity of risksand constraints over various time scales —timescales that include the evolutionary andgeological.

Accounting for complexity

How does systemic management account forcomplexity (tenet 2, appendix 1)? There are threeways in which complexity gets taken into accountif humans manage by finding and achieving a

place within the normal range of natural variation(as amplified in the following paragraphs). Twoof these are matters of human activity —wheremanagers and scientists do the accounting/considering. The third, and most crucial, is anautomatic process central to the guidinginformation used in systemic management.

The three ways complexity is taken intoaccount are:

1. Addressing variety in management issues/questions, the identification of which is amanagement responsibility,

2. Making use of correlative relationships, amatter of importance in science for translatinginformation into appropriate guidance, and

3. Using empirical patterns in limited variationas automatic integrations of complexity. All threecan involve human interactions with ecosystems(to solve the problem of management at theecosystem level).

However, it should be noted that it is not“ecosystem management” as transitive manage-ment wherein managers would manipulateecosystems to achieve some desired state, butrather intransitive management wherein humansfit in sustainably. All three also involve humaninteractions with the biosphere (to include“biosphere management” —but, again, not as atransitive form of management). All involvespecies–level variation, and all involve interactionswith the various levels of biological organization.The following paragraphs examine how all threeare treated in systemic management.

First, complexity is involved in the wide varietyof management questions that have to beaddressed. It is not just a matter of finding,achieving and maintaining individual sustainabilitysuch as appropriate body temperature or bloodpressure; it includes sustainability in the speciescomposition of fisheries catches, the amount ofCO2 released to the biosphere, the consumptionof biomass from ecosystems, the habitat preservedfor other species, the age composition of harvestedresources, the numbers of species that humansdrive to extinction, the number of prey organismsconsumed, and the places where humans live orexploit resources. The relevant questions involvethe countless ways in which species interact withother species, their ecosystems, and the biosphere.To account for complexity in this regard, managersare faced with the responsibility of addressing allsuch issues, at least all that they can think of (andit is impossible to think of them all). It isinsufficient to simply find a sustainable rate forconsuming biomass from a particular resourcespecies. Managing fisheries systemically is notenough; carbon dioxide production must beincluded. Complexity is involved in the huge varietyof issues to be addressed, issues that do not goaway. They are also issues that can only beaddressed by what humans do; nobody else, andcertainly no other species, is going to do thework that only humans can do.

22 Fowler & Hobbs

Second, complexity is involved in recognizingthat the limits to variability are interrelated (e.g.,fig. 1) and function jointly. In nature, things arecorrelated. Thus, the appropriate limits must bechosen carefully (FOWLER, 1999a; FOWLER et al.,1999) to account for relationships among variousmeasures of biological systems. The frequencyand kinds of such relationships have yet to beappreciated but can not be ignored. For example,judging the status of a marine mammal populationby using comparisons with bacterial populationsis not an option (fig. 1), any more than is anattempt to find a sustainable level of net CO2production for humans with information fromspecies capable of photosynthesis. Managerswould need to take the physical environmentinto account in correlative relationships such asthese and the relationship between range sizeand latitude (STEVENS, 1992; GASTON & BLACKBURN,2000). For example, climate change would betaken into account through correlative relation-ships in which climate is known to be related topatterns in limited variation relevant to anyspecific management question (e.g., rate ofbiomass consumption from a resource species).

Third, as described in earlier sections, complexityis automatically involved in the patterns ofvariation that provide empirically observedguidance for systemic management. Such patternsare of systemic origin. Complexity is behind themeasurable limits and central tendencies involvedin the variation inherent to such patterns. Thesepatterns represent an integration of all of thefactors important to their origin. Importantly,this integration involves an accounting of thesefactors in proportion to their relative importance.This third point deserves further considerationeven though it is something that happensautomatically when empirical information is usedin systemic management.

The empirical examples of sustainabilityembodied by other species are informative becausethese species have survived an evolutionary historyof exposure to all the risks and factors that are tobe taken into account. They have survived themultitude of risks that constrain variation,including the risks of extinction. These species,and the patterns of variation they exhibit, areproducts of complexity. In other words, what isseen in empirical information about naturalvariation and its limits is the result of the collectiveinfluence of all limiting factors, the aggregate offorces that come into play in producing thedistributions. Forces or factors that are relativelyunimportant are taken into account in proportionto their effects and the weight of their influencein the origin of observed patterns (including thevariation of such patterns). If the rotation of theEarth influences biomass consumption (e.g., bydetermining the amount of daylight), then thisfactor is included in the empirical variation, withits limits, seen in observed rates of biomassconsumption. Perhaps of equal importance, such

factors are included in proportion to the strengthof their influence; each factor is consideredcompletely objectively relative to the influence ofall other factors (i.e., without direct humaninvolvement in the consideration —thus avoidingthe risk of misleading human choices based onhuman values). The same holds true for otherfactors as well, whether they be the forces ofevolution through natural selection, the natureof the carbon/oxygen chemical bond, extinction,the spectral composition of ambient light, therelative abundance of elements in the universe,or the structure and composition of cells.

Thus, this third point is that complexity getstaken into account automatically in systemicmanagement. This happens by virtue of the factthat empirical examples of sustainability shownatural variation that is both produced andlimited in ways that integrate contributingfactors amongst all aspects of complexity. Theydo so through their exposure to the collectiveset of factors that make up the context withinwhich they occur and have occurred overgeological time scales. This happens in a naturalBayesian–like integration process (FOWLER, 1999a,1999b; FOWLER et al., 1999). This integrationhappens in reality, as opposed to throughmanmade models that cannot capture the fullextent of reality (BATESON, 1972). Perhaps ofgreatest value is the fact that this integrationhappens in a way that gives proper emphasis orweight to each of the factors involved. Thisrelieves managers of the need to decide whetherembryological factors are more or less importantthan evolutionary factors, or long time scales aremore important than short time scales. There is asynthesis of such information that scientists areincapable of achieving, thus overcomingreductionism as one of the limitations of science(ALLEN & STARR, 1982; BARTHOLOMEW, 1982;ROSENBERG, 1985; SALTHE, 1985; GROSS, 1989; PETERS,1991; PICKETT et al., 1994; STANLEY, 1995) whiletaking advantage of the strength of this facet ofscience to find the empirical information aboutvariation that is so critically important tomanagement regarding each specific managementquestion.

It is important here to emphasize thelimitations inherent to science because in humanculture it is often thought that science is capableof providing answers to all questions. First, it isimportant to remember that science is merely amethodology —a formula for inquiry that seekstruth, understanding and explanation of theuniverse in which humans find themselves.Science, by definition, seeks knowledge. Thepursuit of knowledge, however, explores com-ponents of systems and will, by definition, havelimited success in knowing the system itself,especially the full system of reality. Part of thisstems from the fact that the whole is always morethan the sum of its parts. Part of the limitationstems from each system being part of more inclusive


systems. Bateson (e.g., BATESON, 1972, 1979) spokeof a knowledge and understanding of the greatersystem as wisdom. It is wisdom that is sought inmanagement rather than merely more knowledgeof system components and it is wisdom whichscience does not, and is not designed to, address. Itis the deeper understanding or wisdom that isused in systemic management —where science isa tool for seeing useful information exemplifiedin the probability distributions that characterizepatterns of limited variation.

Thus, it should be emphasized that theautomatic aspect of the integration describedabove works two ways. Empirical information isinformative as guidance and it accounts for theconsequences of management action. The impactsof human actions are part of what is considered.The complexity of these impacts is automaticallytaken into account because all components ofcomplex systems (e.g., species) have the kinds ofeffects that humans have, and of the magnitudethat humans will have if it is possible to manageto fit within the normal range of natural variation.These impacts include those that generate riskthrough feedback in proportion to their relativeimportance. Thus empirical information accountsfor complexity both in its informative role (basedon the products of complexity) and in itsaccounting for the effects of human actions(nature in its complexity has experienced sucheffects over evolutionary time frames).

An overview of systemic management and thenine tenets

Systemic management was introduced above asa form of management that adheres to basictenets and principles of management that havebeen established in trying to deal with theinadequacies of conventional approaches. It isimportant to have a more detailed understandingof what systemic management is, in order for itto be implemented. It is important to understandhow it should be carried out to meet therequirements embodied in the tenets ofmanagement found in appendix 1. How does itcomply with basic principles? The followingparagraphs consider the answer to this questionin a way that simultaneously emphasizes theinterrelated nature of the tenets and principlesof management.

Natural systems are internally consistent andfully interconnected; no laws involving theconservation of mass and energy are broken innature. Thus, empirical examples of sustainabilityembodied in species and their interactions withtheir environments are role–models of consistency.In addition to this, humans, as participants inecosystems and the biosphere, are required toapply information about natural variation insustainability to all management questions (thusinvolving both tenets 1 and 2, appendix 1).Therefore, consistency is accomplished in applying

these principles of management by achieving aposition for humans within the normal ranges ofnatural variation, not by choosing a few easy orsimple cases, but by doing so broadly. Thisautomatically involves consistency in application,but does so while simultaneously accounting forcomplexity. This, of course, would be a directadherence to tenet 3 while also complying withtenet 8 (appendix 1) because managers would bechoosing to act only on those issues where there ismost control. This form of management woulddirectly place humans into a sustainable role in thesystems of which our species is a part (but not justas parts of ecosystems, tenet 9, appendix 1). Itwould do so by taking action to fall within thenormal range of natural variation so as to avoidthe risks and constraints reviewed above (tenet 4,appendix 1). Science would be crucial to theproduction of information on the limits to naturalvariation (CLARK, 1989, tenets 5 and 6).

There remains the need to meet the requirementsof the tenet 7. How is it possible to establish goals,standards of reference, and guidelines? The answerto this question was introduced above in thediscussion of central tendencies between upper andlower limits. Figures 2–6 (with relevant informationand sources identified in appendix 3) show empiricaldata regarding variation and its limits (see alsoFOWLER & PEREZ, 1999; FOWLER et al., 1999; FOWLER,1999a, 1999b; FOWLER, 2002), and the deviation ofhumans from the normal ranges of natural variation(with quantitative measures shown in table 2,appendix 3). The goals and objectives for systemicmanagement are found near the central tendenciesof frequency distributions (FOWLER & PEREZ, 1999)such as shown in these figures (recognizing thatthere are imperfections in current data and thatsystems change; e.g., FOWLER, 1999a; FOWLER et al.,1999). By virtue of their relative numericalabundance, the species in the region of the centraltendencies emphasize the forms of sustainabilitythey represent. These figures also emphasize thebreadth of application of management that canbe used to fit within the normal range of naturalvariation (FOWLER & PEREZ, 1999).

It should be clear that systemic managementis, strictly speaking, neither restricted to being aconventional systems approach to management,nor merely a holistic approach. One distinctionbetween traditional systems approaches and thesystemic approach is particularly important.Systems approaches usually focus on a singlecomplex system like a population, ecosystem,family, community or individual that give it, andits components, a form of significance orrelevance different from the significance itactually has in nature in relation to other systems,especially those of which it is a part. Thus, systemsapproaches that exist as precedents lack sufficientconsideration of complexity, especially context,which is necessary for a fully developed systemsapproach to adequately account for hierarchicalstructure of reality (GRUMBINE, 1994a). Part of

24 Fowler & Hobbs

Fig. 2. Six frequency distributions showing a comparison between the rates at whichhumans consume biomass from individual resource species compared to the rates otherspecies consume the same resource, all measured in units of log10 metric tons per year:A. Eleven species of marine mammals as consumers of hake; B. Twelve species of bird,mammals and fish as consumers of herring; C. Sixteen species of birds, mammals and fishas consumers of mackerel; D. Six species of mammals as consumers of walleye pollock; E.Twelve species of birds as consumers of anchovy; F. Twenty species of birds, mammals andfish as consumers of walleye pollock. Further details are provided in appendix 3 (tables1 and 2).

Fig. 2. Seis distribuciones de frecuencia en las que se comparan los índices de consumo debiomasa procedente de una especie utilizada como recurso por el hombre y los de otrasespecies que consumen el mismo recurso, todos medidos en log10 toneladas métricas poraño: A. Once especies de mamíferos marinos como consumidores de merluza; B. Doceespecies de aves, mamíferos y peces como consumidores de arenques; C. Dieciséis especiesde aves, mamíferos y peces como consumidores de caballa; D. Seis especies de mamíferoscomo consumidores de colín de Alaska; E. Doce especies de aves como consumidores deanchoas; F. Veinte especies de aves, mamíferos y peces como consumidores de colin deAlaska. Para más detalles ver apéndice 3 (tablas 1 y 2).

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what has to be embraced in management arethe more inclusive systems within which thefocal systems occur (e.g., the biosphere thatcontains ecosystems). As such, existing attemptsat systems approaches find it difficult to addressquestions regarding desirable emergent oraggregate qualities of a focal system, or evenmore difficult questions such as whether or notthe system should exist at all. Insufficientimportance is attached to the interactions of anyparticular system with other systems or thephysical environment. For biological systems theother systems would include those at the same

Fig. 3. Four frequency distributions showing a comparison between the rates at which humansconsume biomass from various groups of resource species compared to that of other consumerspecies, all measured in units of log10 metric tons per year: A. Twenty species of marinemammals as consumers of finfish; B. Sixteen species of birds, mammals, and fish as consumersof hake, herring and mackerel (with humans in the same bar as dog fish); C. Thirteen speciesof birds and mammals as consumers of hake, herring and mackerel; D. Eighteen species of birdsas consumers of anchovy, lanternfish, lightfish, and hake. Further details are provided inappendix 3 (tables 1 and 2).

Fig. 3. Cuatro distribuciones de frecuencia en las que se comparan los índices de consumo debiomasa de varios grupos de especies utilizadas como recurso por el hombre y por otras especiesconsumidoras, medidos en log10 toneladas métricas por año: A. Veinte especies de mamíferosmarinos consumidores de peces óseos; B. Dieciséis especies de aves, mamíferos y peces, consumi-dores de merluza, arenques y caballa (con el hombre en la misma franja que la lija); C. Treceespecies de aves y mamíferos, consumidores de merluza, arenques y caballa; D. Dieciochoespecies de aves, consumidores de anchoas, pez linterna, luciérnaga perlada y merluza. Para másdetalles ver apéndice 3 (tablas 1 y 2).

level of biological organization, such asindividuals interacting with individuals, speciesinteracting with species, or ecosystems interactingwith other ecosystems. Of possible greaterrelevance is the lack of attention given to theinteractions between a system and the moreinclusive systems of which they are a part. Theinteractions between a species and its ecosystemwould be an example, as would the effects of anindividual on its species, or a species on thebiosphere. Perhaps of greatest importance is thefact that previous attempts at a systems approachhave not accounted for the relative importance

HumansHumansHumansHumansHumans



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26 Fowler & Hobbs

Fig. 4. Six frequency distributions showing a comparison between the rates at which humansconsume biomass from various ecosystems compared to that of other species, all measured inunits of log10 metric tons per year: A. Twenty–one species of mammals in Eastern Bering Sea (twospecies, including humans, in the bar representing the highest consumption rates); B. Forty–sixspecies of fish, birds, and mammals from the Georges Bank; C. Thirty–three species of birds offthe southwest coast of Africa (with humans sharing one bar with two species of birds); D.Twenty–three species of birds and mammals from the Georges Bank. E. Sixteen species of birds,mammals and fish from the Northwest Atlantic. F. Twelve species of marine mammals from theGeorges Bank. Further details are provided in appendix 3 (tables 1 and 2).

Fig. 4. Seis distribuciones de frecuencia en las que se comparan los índices de consumo debiomasa procedente de varios ecosistemas por el hombre y por otras especies, todas las medidasen log10 toneladas métricas por año. A. Veintiuna especies de mamíferos del este del mar deBering (dos especies, incluido el hombre, en la franja correspondiente a la mayor tasa deconsumo); B. Cuarenta y seis especies de peces, aves y mamíferos del banco Georges; C. Treintay tres especies de aves en el litoral de la costa suroeste de África (con el hombre compartiendouna franja con dos especies de aves); D. Veintitrés especies de aves y mamíferos del bancoGeorges; E. Dieciséis especies de aves, mamíferos y peces del noroeste Atlántico; F. Doce especiesde mamíferos marinos del banco Georges. Para más detalles ver apéndice 3 (tablas 1 y 2).

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Fig. 5. Six frequency distributions showing a comparison of humans with other species: four in regardto the rate of consumption of biomass (A–D), CO2 production (E), and energy ingestion (F), withbiomass consumption and CO2 production measured in units of log10 metric tons per year, and energyconsumption measured in log10 billion joules per year: A. Fifty–four species of marine mammals asconsumers of biomass; B. Forty–two species of terrestrial mammals as consumers of biomass; C. Sixty–three species of mammals of body size similar to humans and as consumers of biomass; D. Ninety–sixspecies of mammals as consumers of biomass; E. Sixty–three species of mammals of human body sizeas producers of CO2. F. Sixty–three species of marine mammals of human body size as consumers ofenergy. Further details are provided in appendix 3 (tables 1 and 2).

Fig. 5. Seis distribuciones de frecuencia en las que se compara el hombre con otras especies: cuatroreferidas a la tasa de consumo de biomasa (A–D), producción de CO2 (E) e ingestión de energía (F), conel consumo de biomasa y la producción de CO2 medidos en log10 toneladas métricas por año, y elconsumo de energía medido en log10 1.000 millones de julios por año: A. Cincuenta y cuatro especiesde mamíferos marinos, consumidores de biomasa; B. Cuarenta y dos especies de mamíferos terrestres,consumidores de biomasa; C. Sesenta y tres especies de mamíferos de tamaño corporal similar al delhombre, consumidores de biomasa; D. Noventa y seis especies de mamíferos, consumidores debiomasa; E. Sesenta y tres especies de mamíferos de tamaño corporal equivalente al del hombre,productores de CO2; F. Sesenta y tres especies de mamíferos marinos de tamaño corporal equivalenteal del hombre, consumidores de energía. Para más detalles ver apéndice 3 (tablas 1 y 2).

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28 Fowler & Hobbs

Fig. 6. Six frequency distributions showing a comparison of humans with other species inregard to geographic range size (A, log10 1,000 k2), population size (B, D, F, log10 numbers),energy consumption per unit area (C, log10 million joules per k2 per day), and percent ofNorth America unoccupied (E, arcsine scale): A. Five hundred and twenty–three species ofterrestrial mammals and their geographic range, in comparison to humans assumed to useeither 20% or 70% of the non–Antarctic land surface area of the Earth; B. Twenty–onespecies of marine mammals of human body size and their total population size; C. Threehundred sixty–eight species of mammals in their consumption of energy per unit area incomparison to humans assumed to use either 20% or 70% of the non–Antarctic land surfacearea of the Earth; D. Forty–two species of terrestrial mammals of human body size and theirtotal population size; E. Five hundred twenty–three species of terrestrial mammals with theportion of North America that they leave un–occupied. F. Sixty–three species of mammals ofhuman body size and their total population size —a combination of B, and C. Further detailsare provided in appendix 3 (tables 1 and 2).

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Percent unoccupied (arcsine scale)Percent unoccupied (arcsine scale)Percent unoccupied (arcsine scale)Percent unoccupied (arcsine scale)Percent unoccupied (arcsine scale) logloglogloglog1010101010(population size)(population size)(population size)(population size)(population size)

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–1–1–1–1–1 00000 11111 22222 33333 44444 55555 66666 11111 22222 33333 44444 55555 66666 77777 88888 99999 1010101010 1111111111logloglogloglog1010101010(geographic range, 1000k(geographic range, 1000k(geographic range, 1000k(geographic range, 1000k(geographic range, 1000k22222))))) logloglogloglog1010101010(population size)(population size)(population size)(population size)(population size)

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HumansHumansHumansHumansHumans20% 70%20% 70%20% 70%20% 70%20% 70% HumansHumansHumansHumansHumans

HumansHumansHumansHumansHumans20% 70%20% 70%20% 70%20% 70%20% 70% HumansHumansHumansHumansHumans

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of these categories of interactions. Conventionalsystems approaches can not assign importance inproportion to the importance realized in nature.

Systemic management builds on the com-ponents provided by analogous approachesexemplified by biomimicry (BENYUS, 1997) orbenchmarking (SPENDOLINI, 1992; BOGAN & ENGLISH,1994; BOXWELL, 1994; CAMP, 1995). In addition toasking how to feed ourselves there has to be away to address the question of how many ofhumans there should be to feed. In addition toasking how to run a business enterprise, it isnecessary to be able to address the matter ofwhether or not there should be such a business.In the use of tools, it should be possible to askwhether their manufacture, use and disposalhave effects that are within the normal range ofnatural variation. In order to use technology tosolve problems, it must be possible to addressthe effects of such technology (e.g., manufacture,disposal, side effects). Management must applyat various levels of complexity and systemicmanagement accomplishes this task.

Systemic management is an outgrowth of thesystems approach and it accounts for the nature ofsystems, including the limits of human systems.However, the systemic approach (as used here) isbased, in part, on the fact that each system is part ofa more inclusive system, such that an individual ispart of a species, an ecosystem is part of a biosphereand a cell is part of an organism. In addition, systems(e.g., ecosystems, individuals, cells, species) interactwith each other. Thus, systemic management is basedon the recognition that the limits discussed in theearlier sections of this paper (i.e., the limits of natureor reality on its components) are limits that includethose stemming from each system being parts ofsystems on larger scales. This means that a sustainablepopulation is one that is sustainable by its supportingecosystems and that the ecosystems providing thesupport to the population are in a state that cansustainably provide the support —balance (dynamic)within limits.

There is another difference between systemsapproaches and systemic management. The latteris not merely holistic. It is not restricted toconsidering whole systems (i.e., an ecosystem, ora species) because it is also based on recognitionof intrinsic limits, and that every system hascomponents. The intrinsic limits are the limitsimposed by virtue of systems being made up ofcomponents that themselves contribute to limits.That is, systemic management recognizes thereare both intrinsic and extrinsic factors that cometo bear in all cases, and their influences areconsidered in proportion to their relative effectsin nature. Thus, part of sustainability at thepopulation level involves the effects of apopulation or species on the ecosystems of whichit is a part in combination with the effects thatindividuals have from within the population.

Perhaps most importantly, systemic manage-ment requires that action and decisions be basedon observed limits to natural variation. Theseinclude the ways that humans interact with othersystems (e.g., consuming resource species, releaseof CO2 to the biosphere, or sharing habitat withother species). This is done, while avoiding beingconfined to focus on any one level or system,while clearly acknowledging the importance ofthe limits that systems place on their components(e.g., species and the limits that are placed onthem by the ecosystems and all of the species ofwhich they are comprised; KOESTLER, 1987; O’NEILL

et al., 1986; SALTHE, 1985; WILBER, 1995). Findingwhat can effectively be controlled and acquiringinformation to guide control may be challenging,but gathering such information is a crucialscientific exercise in management (CLARK, 1989).Scientists cannot control things to makemanagement happen at the species level (andhigher levels) but can, and must, be part of theprocess, especially by discovering, observing andmeasuring limits, then contributing the resultinginformation for use in guiding management (e.g.,FOWLER & PEREZ, 1999). Many forms of conven-

Fig. 6. Seis distribuciones de frecuencia en las que se compara el hombre con otras especies enrelación con el tamaño de área de distribución geográfica (A, log10 1.000 k2), tamaño de población(B, D, F, números en log10), consumo de energía por unidad de superficie (C, log10 millón de juliospor k2 y día) y porcentaje de América del Norte no ocupado (E, escala en arcoseno): A. Quinientasveintitrés especies de mamíferos terrestres y su distribución geográfica comparadas con el hombresuponiendo el uso del 20% o el 70% de la superficie no Antártica de la Tierra; B. Veintiuna especiesde mamíferos marinos de tamaño corporal equivalente al del hombre y el tamaño total de supoblación; C. Trescientas sesenta y ocho especies de mamíferos y su consumo de energía por unidadde superficie en comparación con el hombre suponiendo el uso del 20% o el 70% de la superficieterrestre no Antártica; D. Cuarenta y dos especies de mamíferos terrestres de tamaño corporalequivalente al del hombre y el tamaño total de su población; E. Quinientas veintitrés especies demamíferos terrestres con la porción de América del Norte no ocupada por ellos; F. Sesenta y tresespecies de mamíferos de tamaño corporal equivalente al humano y el tamaño total de supoblación —es una combinación de B y C. Para más detalles ver apéndice 3 (tablas 1 y 2).

30 Fowler & Hobbs

tional management can no longer be used owingto their failure to adhere to one or more of theprinciples of management and the resultingfailures observed as the consequences of suchmanagement. The question before managers is:Is it possible to manage to achieve sustainability?It is our species (and the individuals who aremembers of our species) that must do what isnecessary to undertake the needed change. Innavigation, knowing where one is and whereone wants to be are both crucial pieces ofinformation necessary to getting there. The pathis then specified by other information. Likewise,the path for change is not specified in systemicmanagement by information confined toestablishing the endpoints or objectives. Thedetails of actually undertaking change involveseparate questions also to be addressedsystemically as further steps in accounting forcomplexity.

It is now possible to see how the tenets ofmanagement laid out in appendix 1 actually definesystemic management. These tenets owe some oftheir origins to efforts to move forward byamplifying upon and solving the problems ofconventional practices. However, even though thetenets have been well developed in the literature,they have made little difference in what is actuallydone in management. Nevertheless, these tenets,provide a basis for doing things differently toachieve a realistic management process. Many ofthe roots of these tenets can be found inconsideration of the inadequacies of past practices.In this regard, systemic management holds promisein that it is different enough to be the changecalled for by those seeing a need for a completelynew approach (ClARK, 1989; SANTOS, 1990; NORTON,1991; GRUMBINE, 1992; KNIGHT & GEORGE, 1995;COMMITTEE ON ECOSYSTEM MANAGEMENT FOR

SUSTAINABLE MARINE FISHERIES, 1999). Systemicmanagement is management through humanaction to find a sustainable role in the systems ofwhich the human species is a part. It is systemic inthat it accounts for complexity, applies broadly,and involves all levels of biological organization.However, to fully account for complexity it mustbe applied broadly in practice, not just in concept.It is also systemic in that it requires dealing withthe complexity of human systems by achievingchange in human behavior, human influence, andhuman qualities through management. It shouldbe noted that the complexity of this processinvolves social, economic, political, religious,scientific, and psychological issues —anything buta simple process and one that includes each andevery person (CLARK, 1989). Thus, changes requiredof the human species do not free individuals fromtheir part in the process. Individuals are also partsof natural systems and individual humans arecomponents comprising our species. Individuals,regardless of species, contribute to what suchsystems (e.g., species) are and, as parts of suchsystems, are subject to the natural laws involved

in limits and constraints. The daunting nature ofthis task lends to the personal experience of thechallenge of systemic management.

Systemic management has to be applied withregard to every system, emphasizing action wherethere is most control, especially in makingdecisions. There are “systems” components ofsystemic management in a variety of realms(CONN, 1995; O’CONNER, 1995; O’NEILL, 1999).However, to be truly systemic, it is imperative togo beyond dealing with the internal workings ofthe respective systems to address questionsregarding the interactions of such systems withothers —their context. Systemic managementemphasizes the responsibility shouldered byindividuals, society, and the human species forthe consequences experienced from failing toundertake such management all levels (PIANKA,1974; CLARK, 1989; MOOTE et al., 1994; WILBER,1995). To consider humans part of ecosystems orthe biosphere (tenet 9, appendix 1) it is alsonecessary to consider humans subject to limitsand risks (ROSENZWEIG, 1974).

Acknowledgments

The authors wish to thank Robyn Angliss, MaryClark, Jean Fowler, Carolyn Kurle, Alec MacCall,Shannon McCluskey, Susan Picquelle and at leastone anonymous reviewer for very helpful reviewsof earlier drafts of this paper. Shannon McCluskey,Laura Murray and Gyda May were very helpful inlibrary work regarding examples of limitations,and references for both the “law of unintendedconsequences” and publications recognizing theimportance of limits. Thanks are extended to themall for their efforts.

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Appendix 1. A list of tenets (criteria and principles) that must be met, or adhered to, inmanagement. These tenets define systemic management (e.g., see FOWLER et al. 1999), however,they are extracted from a large body of literature dealing with management, especially inregard to management at the ecosystem level, most published in the last several decades ofthe 20th century (with references found throughout the text of this paper).

Apéndice 1. Relación de dogmas (criterios y principios) que deben conocerse u observarse en elmanejo. Dichos dogmas definen el manejo sistémico (ver FOWLER et al., 1999), aunque se hanextraído de una amplia literatura relacionada con el manejo, en especial con el manejo a nivelde ecosistemas, la mayoría publicada en las últimas décadas del siglo XX (las referenciasaparecen a lo largo del texto de este trabajo).

1. Any application of management must be consistent with other applications and any form ofmanagement must apply simultaneously at the various levels of biological organization. Forexample, the harvest of biomass from individual resource species can not be in conflict withmanagement of the harvest of biomass from the ecosystems in which the harvested species occur.Similarly, biomass consumption by humans from the biosphere must be guided by principles thatare not in conflict with those guiding the harvest of biomass from either an individual resourcespecies or any particular ecosystem.

2. Management action must be based on an approach that accounts for reality in its complexity overthe various scales of time, space, and biological organization. The context of environmentalfactors (e.g., ecological complexity) must be accounted for along with the elements of stochasticityand the diversity of processes, mechanics, and dynamics. The complexes of chemical and physicalsubstances and processes as well as energetic dynamics must be taken into account, along withevolutionary processes at all levels. These factors must be given weight in decision-making thatis in proportion to their relative importance and all must be dealt with simultaneously.Furthermore, managers must be able to deal with uncertainty, including what cannot be known.

3. A core principle of management is that of undertaking actions that ensure that processes,relationships, individuals, species and ecosystems are within (or will return to) their respectivenormal ranges of natural variation as components of the more aggregated levels of biologicalorganization. Included are evolutionary processes, and all those involved in ecosystemdynamics, as well as physiological and embryological processes. Any form of managementmust apply this principle (appendix 2, and the central theme of this paper).

4. Management must be risk averse and exercise precaution in achieving sustainability.Sustainability is, by definition, not achieved by any form of management that generates riskrather than minimizing it.

5. Management must be information based. Guidance must be available to management in theform of useful information that enables managers to develop meaningful, measurable andreasonable goals and objectives (tenet 7). This information must be based on interdisciplinaryapproaches involving science (tenet 6) to adhere to the principle behind tenet number 2 above.

6. Management must include science (scientific methods and principles) in research, monitoringand assessment, not only to produce the information that is used for guidance (tenet 5), butalso for evaluation of progress in achieving established goals and objectives (tenet 7).

7. There must be clearly defined goals and objectives that are measurable to provide quantitativeevaluation of problems to be solved and gauge progress in solving them. There must beguidelines, criteria, and standards of reference.

8. It must be recognized that control over other species and ecosystems is impossible. The onlyoption for control is the control of human action (CHRISTENSEN et al., 1996; MANGEL et al., 1996;HOLLING & MEFFE, 1996). For example, it is possible to control fishing effort but not the fish northe fact that fishing will have its consequences, many of which will be both unintended andundesirable. It is not possible to control resource populations or ecosystems. It is possible toinfluence any resource population and its ecosystem, but not to control them to avoidindirect changes, side effects, or secondary reactions brought about by our influence. Theguidance (tenet 7) needed for management is guidance regarding the level of influence (e.g.,harvest rate) that meets the other criteria of this list.

9. Humans must be considered as parts of complex biological systems. Humans must have theoption of being components of at least some ecosystems to avoid the unrealistic option ofprecluding human existence. Humans are not separate from, unaffected by, or free of thelimits of the systems of which any species is a part.

38 Fowler & Hobbs

Appendix 2. Limits to Natural Variation (including biophysical limits): quotations from the literature.

Apéndice 2. Límites de la variación natural (incluye límites biofísicos): citas de la literatura.

AGEE & JOHNSON (1988a): “...limits and constraints.. [are not a] ...commonly understood conceptof ecosystem management...”

AHL & ALLEN (1996): “By being unresponsive, higher levels constrain and thereby impose generallimits on the behavior of small–scale entities.”

ALEXANDER & BORGIA (1978): “One implication is that while ecological communities may often besignificantly affected by differential extinction of species, species are not necessarily likelyto have been greatly influenced by differential extinction of populations or demes...”

ALLEN & STARR (1982): “It is sometimes advantageous, however, to view organization notpositively as a series of connections, but rather negatively, as a series of constraints.Ordered systems are so, not because of what the components do, but rather becauseof what they are not allowed to do.”“Thus the large reductionistic ecosystem models may tell something of the how ofecosystems but lose much of the why. They focus on system dynamics rather than rateindependent system constraints...”

ANDERSON (1991): “Intact suggests that all of the critical ecosystem components are present andstructured in such a way that processes function within normal limits...over the long term.”

ANGERMEIER & KARR (1994): “[Integrity is] the capability of supporting and maintaining a balanced,integrated, adaptive community of organisims having a species composition, diversity,and functional organization comparable to that of natural habitat of the region.”

APOLLONIO (1994): “[Fisheries] ...must have characteristics comparable to apex predators if thesystems are to be manageable, that is, the vessels must emulate the essentialcharacteristics of K–selected species.”

ARNOLD & FRISTRUP (1982): “Selection at a given level can be opposed, reinforced, or unaffectedby processes operating at other levels.”

BATESON (1972): "...the steady state and continued existence of complex interactive systems dependupon preventing the maximization of any variable, and that any continued increase inany variable will inevitably result in, and be limited by, irreversible changes in thesystem.” “In principle, the homeostatic controls of biological systems must be activatedby variables which are not in themselves harmful.”

BROWN (1995): “...morphology, physiology, and behavior of individual organisms play major rolesin causing, or at least constraining, large-scale patterns of distribution and abundance,both within and among species.” [others have] “...recently developed a statisticalmethod to fit lines to the boundaries of ... two–dimensional scatter plots of data torepresent estimates of constraints.”

BROWN & MAURER (1987): “Since species of large body size are constrained to have low populationdensities, such species with small geographical ranges should have high probability ofextinction because the total species population is small.” “A more interesting exampleof an apparently absolute constraint is an energetic trade–off between maximumpopulation density and body size.”

BURNS et al. (1991): “Existing theories of evolution as a general process of ordered change havecome not from biology, but from physics and general systems theory... In addition, agreat deal of corroborating evidence is accumulating in the study of chemical reactionsystems..., life’s origin..., epigenetic systems..., cell evolution... and the biosphere...that there is a common and fundamental description of self–organizing change in far–from–equilibrium systems. What these theories share is a recognition that entities aresystems evolving within still larger interactive systems, entities with environmentsboth modified by and constraining their evolution.”

BUSS (1988): “Traits expressed in the higher unit now act as selective agents on the variation arising inthe lower unit. The organization of the higher unit is, however, a function of prior variationin the lower unit. Thus, the lower unit can influence the replication of the higher unit bymodification of its organization to suit the lower unit, but only to the extent thatreplication of the lower unit does not disadvantage the higher unit in its interaction with


the external environment.” “The external environment will act solely on the higher unitonly if the lower unit is physically contained within the higher unit, as in the case of geneswithin cells or cells within multi–cellular organisms. When the lower unit is not physicallyenclosed within the higher unit, e.g., organisms within species, the external environmentmay actively select both units.” “A second factor, however, is equally important. Variancewill also arise which disrupt the higher unit, that is, they will favor the lower unit at theexpense of the higher unit. The rate and magnitude of such conflicts must be limited, or thehigher unit will perish. If variants arise in the lower unit whose affect is to limit theoccurrence or magnitude of subsequent variation, then the higher unit will eventuallybecome resistant to further perturbation.”

CHRISTENSEN et al. (1996): “Extreme fluctuation is abnormal in most ecosystems and, when causedby human activity, is what often threatens ecosystem functioning.”

CLARK (1989): “Science, by illuminating for us at least some of the complexities of Nature, can provideus with an ultimate boundary for our actions. If we perceive how Nature works we can tellwhen we are threatening its ability to function in a healthy fashion.” “Science can only tellus, if we decide we want to survive, what the boundary conditions are, what the ‘rules ofthe survival game are’, so to speak.” “Science is for discovering the limits of the naturalworld and the laws by which it proceeds and within which we are free to act. This aspectof science can add greatly to the maps and signposts we need to guide us into the future.”

DARWIN (1953): “...we certainly can do something to control the world around us, and if we canappreciate the limits of what is possible, we may have some hope...”

EHRENFELD (1993): “So it is with communities in the organismic view. They have recognizable identity,and in the final stage of community embryology, or succession, that identity becomesfixed and normative: a prairie, a beech–sugar maple forest, a desert. Because communitieshave fixed identifies, because they are normative likes organisms, we can easily apply thenormative idea of health to them: if they are functionally and structurally similar to theirabstract ideal, they are healthy; if they deviate significantly, they are sick.”

FARNWORTH & GOLLEY (1974): “Both plant and animal pests challenged the progenitors of domesticatedspecies long before the invention of agriculture, but counter selection pressures constrainedtheir populations within the long term carrying capacity of their environments andregulated the virulence of pathogens at moderate levels that would preserve the hosts.”

FISHER (1986): “Thus, on average, the most conspicuous, sustained trends will be in the directionof least morphological constraints.”

FRANCIS et al. (1999): [Ecosystem Management should:] “Strive to retain critical types and ranges ofnatural variation in ecosystem. That is, management should facilitate existing processesand variabilities rather than changing and controlling them.”

FUENTES (1993): “...we should concentrate on defining the borders of a sustainability space...”GOODLAND (1995): “Humanity must learn to live within the limitations of the biophysical environment.”GLAZIER (1987): “The present hypothesis represents a modified version of a model used to explain

correlations between species diversity and productivity among ecological communities...According to this modified model, an increase in energy availability and/or a decrease inenergy demand permits more congeneric species to subdivide the energy supply of agiven generic niche such that each species still obtains a sufficient portion to maintain apopulation size having a low probability of extinction. This model assumes that evolutiontends to produce increasingly specialized species (i.e., those having a narrower range ofresources), because they are more efficient at using resources than generalized species.”

GRIME (1989): “These appear to reflect fundamental constraints of habitat and organism whichchannel evolution into predictable paths. A current challenge is to assess the extent towhich recognition of these patterns provides the essential clues to community andecosystem structure.”

GRUBB (1989): “It seems that increasingly practitioners write explicitly that optimization isconstrained by the available genetic material. However, I seriously doubt whether thatpoint is sufficiently emphasized to beginning students.”

GRUMBINE (1994b): “...our purpose in protecting wildness is not to preserve nature or to improveit, but rather to learn a sense of limits from it and to model culture after it.”

HAGEN (1992): “[Odum] stressed the homeostatic nature of ecosystems such that they should beexpected to have properties... [and] the much stronger claim that all living systems —cells,organisms, populations and ecosystems— share this common self–regulatory property.”

40 Fowler & Hobbs

HANNON (1992): “We will be required to reduce our GNP per capita and probably our populationto comply with this solar constraint. Such a change is unprecedented in recordedworld history, except perhaps for Ireland.”

HOLLING (1966): “Those organisms, those communities that lacked the mechanisms necessary topermit adaption to major changes cannot survive the many short– and long–termdislocations of the environment that occurred long before man appeared. These mechanismsare homeostatic or feedback processes that tend to resist change and promoted stability.Any departure from a norm tends to be opposed, and opposed with increasing vigor asthe departure becomes greater and greater. One example is found in the not necessarilycontroversial idea of density dependence, so familiar to students of population dynamics.”

HOLLING & MEFFE (1996): “Natural resource management should strive to retain critical types andranges of natural variation in ecosystems.” “...when the range of natural variation ina system is reduced, the system loses resilience.” “That is, management shouldfacilitate existing processes and variabilities rather than changing or controllingthem.” “...effective natural resource management that promotes long–term systemviability must be be based on an understanding of the key processes that structure anddrive ecosystems, and on acceptance of both the natural ranges of ecosystem variationand the constraints of that variation for long-term success and sustainability.”

HYAMS (1976): “It is possible to rearrange the parts within the whole without permanentlyimpairing the balance; but only within certain limits.”

INGRAM & MOLNAR (1990): “Overall, nature is not very diverse.” “When one looks at the livingworld, what impresses is the lack of diversity. While there may be a multitude ofentities, what is noticeable is their sameness.”

JOHNSTON (1991): “...fallacy of equating freedom with "soft" containers.”KING (1993): “Maintenance of an ecosystem integrity implies maintenance of some normal state

or norm of operation (e.g., homeostasis or homeorhesis). Measuring or observingecosystem integrity, or its loss, thus requires observations over sufficient temporalextent to identify and characterize this normalcy. We are prisoners of perspective, andour concept of normal is empirically bound to the scales with which we observe asystem. ...concepts of normalcy, constancy, variability, and thus, ecosystem integrity,are only meaningful within bounds set by the scale of observation.”

KOESTLER (1987): “...while the canon imposes constraints and controls on the holons activities, it doesnot exhaust its degrees of freedom... guided by the contingencies of the environment.”

LEVIN (1989): “What are the natural patterns and dynamics of ecosystems, how are theyregulated, and how robust are they to perturbation?”“We must develop a theory forthe response pattern of different ecosystems to stresses. We must develop standardsof comparisons among ecosystems, based on the identification of common, functionallyimportant processes and properties. Such understanding can emerge only fromtheoretical syntheses based on a comprehensive program of microcosm research andexperimental manipulation coupled with the retrospective studies.”

LEVINTON (1979): “Therefore, the equilibrium species richness is less in unpredictable environments.”“...length of food chains may also be limited by population dynamical forces...”

MANGEL et al. (1996): “The goal of conservation should be to secure present and future optionsby maintaining biological diversity at genetic, species, population and ecosystemlevels; as a general rule neither the resource nor other components of the ecosystemshould be perturbed beyond natural boundaries of variation” “The best possible relationship between humans and nature safeguards the viabilityof all biota and the ecosystems of which they are a part and on which they depend,while allowing human benefit (for present and future generations) through varioususes. Conservation thus includes the consumptive and non–consumptive use of resources(management) and the preservation of critical resources so that future options can bekept open and so that normal ecological structure and function may continue. Thechallenge is to determine the appropriate balance between the health of resourcesand ecosystems and the health and quality of human life.”“...economic interests are given priority over biological reality and constraints. ...Thedisparity between economic and ecological time scales presents a great challengebecause the economic system responds to change much faster than the ecologicalsystem; that is, biological systems are constrained by much slower time scales thaneconomic systems.”“Treating wild living resources as has been done in the past is untenable for the longterm. The fundamental relationship between people and the rest of nature needs tobe rethought, and policies developed that fully recognize the realities of the biophysicalconstraints under which humans must function.”


MCCORMICK (1999): “When limits of acceptable change are exceeded, the corrective action mostoften required is regulation and restoration of human intervention.”

MCNEILL (1993): “We will never escape the ecosystem and the limits of the ecosystem. Whether welike it or not, we are caught in the food chain, eating and being eaten. It is one of theconditions of life.”

MOOTE et al. (1994): “Ecosystem management focuses on the maintenance of an ecosystem’s naturalflows, structures, and cycles, displacing the traditional emphasis on the protection of suchindividual elements as popular species or natural features” “Ultimately, we shoulder theresponsibility to live within the limits of our environment or to decide not to...”

NATIONAL MARINE FISHERIES SERVICE ECOSYSTEMS PRINCIPLES ADVISORY PANEL (1998): “Ecosystems have realthresholds and limits which must not be exceeded.”

O’NEILL et al. (1986): “Each level in the hierarchy can be over ridden by the next higher level, andis thereby under the constraint or control of the next higher level. The higher–levelcontrol in a sense is pursuing a more general strategy to which the more local strategyof the lower-level controls are subordinated.” “The higher level appears as an immovablebarrier to the behavior of the lower level. This constraint is a natural consequence ofthe asymmetry in rate constants.” “In the natural world, population growth rate cannotapproach its maximum because of limited food, space, predators, and so forth.”

ORIANS (1990): “Ecological theory is currently insufficient to predict when such limits may bereached.” “Simple solutions are not possible and should not be sought. However,determining system specific limits is nonetheless vital.”

OVINGTON (1975): “...it is possible that the impact of man can be accommodated within theforeseeable future until the disturbing influence of man can be brought into a morestable and intimate balance with the global environment realities.”

PIANKA (1974): “[Balances] are obvious and incontestable, yet modern man has largely failed toappreciate their relevance to his own existence.”

PICKETT et al. (1992): “If nature is a shifting mosaic or in essentially continuous flux, then somepeople may be wrong to conclude that whatever societies choose to do in or to thenatural world is fine. The question can be stated as, ‘If the state of nature is flux, thenis any human–generated change okay?’ The answer to this question is a resounding‘No!’ ... Human–generated changes must be constrained because nature has functional,historical, and evolutionary limits. Nature has a range of ways to be, but there is alimit to those ways, and therefore, human changes must be within those limits.”

PIMENTEL (1966): “To date no one has described all the factors which limit the numbers in anypopulation of a natural community. One factor is clear: no population can increaseindefinitely and convert all the food of its environment into itself and its seed. Thenumber of all populations is limited. The mechanisms which regulate and limit populationsare numerous and varied, but basically all are density–dependent. The various limitingmechanisms can be classified into four general categories and are listed according totheir relative speed of action: (1) interspecific competition, (2) natural enemies (parasitesand predators), (3) environmental heterogeneity, (4) genetic feedback mechanisms.”“The action of the genetic feedback mechanism leads to regulation of numbers ofparasites, predators, herbivores and competitors into the gradual evolution of speciestoward ecological homeostasis with the community associates...”

PIMM (1982): “...Constraints on population dynamics, energy flow, and the structural designs ofanimals explain... [observed patterns].”

PIMM (1984): “The causes of the short food chains, so frequently observed in the real world, arefar from certain. There are four hypotheses: energetic constraints, size or designrestrictions, a balance between evolutionary tendencies to lengthen and shortenchains, and dynamical constraints.”

PIPER (1993): “A major theme running through the book is the conceptual problem between suchecosystem–level phenomena as the apparent balance and homeostasis of nature andsuch population–level phenomena as competition, randomness, and chaos.”

PONTING (1991): “Other religious traditions in the world did not place humans in such a specialand dominant position. Chinese Taoist thought emphasized the idea of a balance offorces within both the individual and society. Both ought to try to live in a balanced andharmonious way with the natural world.” “Human history is, at one level, the story ofhow these limitations have been circumvented and of the consequences for theenvironment of doing so. Overwhelming the most important departure from basicecological constraints has been the increase in human numbers far beyond the levelthat could be supported by natural ecosystems. ...this depended on a number ofspecial attributes stemming from their greatly increased brain size–speech, socialcooperation and the development of various technologies...”

42 Fowler & Hobbs

RAPPORT et al. (1981): “Distress would be reflected in abnormal values for vital signs and/orpreclinical indicators.” “Diagnosis involves pattern recognition, or correlating theabnormal values of signs with ecosystems breakdown syndromes.”

REICHLE et al. (1975): “Ecosystems... all appear to exhibit common properties of persistence andgrowth.” “...all ecosystems have also developed mechanisms for energy storage as anoperational basis for maintaining homoeostasis.”

ROSENZWEIG (1995): “Perhaps some combination of the thermodynamic hypothesis, the area hypothesis,and the dynamics hypothesis limits the number of trophic levels in all systems.”

ROUGHGARDEN (1989): “The first generation of models traces to Hutchinson’s ...conceptualizationof the ideas of limited membership.”

SALTHE (1985): “Everything controls its parts and, as a part is controlled by the whole it is a partof.” “In it the dynamics of upper and lower levels produce output that can influencethe dynamics of the focal level. Lower level constraints, dubbed initiating conditions,will be seen to give rise autonomously to focal level dynamics which exemplify somelaw(s) of nature, while higher–level constraints, which I propose should be referred toas boundary conditions, regulate the results of focal level dynamics.”

SALZMAN (1994): [We need to] “ ...agree to abide by the same ecological and evolutionary rulesof behavior governing nonhuman species and ecosystems.”

STANLEY et al. (1983): “Species selection may be driven by internal factors, such as traits thatendow a particular kind of species with a propensity to speciate, or it may be drivenby external agents. The external agents of species selection are ecological limitingfactors, the biotic varieties of which are predation (including parasitism), competition,and provision of food or substratum.”

SWIMME & BERRY (1994): “It was a moment when the human was able to establish its speciesidentity with new clarity, an achievement that had it admirable but also its dangerousaspects since this clarity of species identity tended toward isolating the human withinitself over against the nonhuman components of the larger Earth community. Onceagain we can observe that every perfection imposes limitations.”

TILMAN (1989): “As has long been recognized, the most general constraint comes from the universalrequirement of all living organisms for energy and matter. ...Each individual organismexists within a web of consumer-resource relations. Its reproductive rate is constrainedby the availabilities of the items it consumes–it resources. Its survivorship is constrainedby the organisms that attempt to consume it. The universality of consumer–resourceinteractions has motivated both theory and experiments..., but has not yet become ascentral a concept in ecology as its universality demands. ...Conversely, if populationecologists had started in 1916, to seek the causes of the broad, general patternsClements described, that subdiscipline could have advanced much more quickly. Thereis much about the evolution of the organismal traits that can be best understood interms of ecosystem-level constraints, just as there are many ecosystem-level patternsthat are best explained in terms of constraints on the evolution of individual organisms....In this paper, I have suggested that we should study broad, general patterns. Instudying such patterns, we should pursue ecological abstraction by using the simplestpossible approach that explicitly includes the most universal constraints of theenvironment and the unavoidable trade–offs that organisms face in dealing with theseconstraints. The most universal constraints may come from consumer–resource interactionsbecause all species are, of necessity, parts of food webs.”

UHL et al. (2000): “Live within limits.” “Recognize that our natural resources are finite endowmentsto be used with care and prudence at a rate consonant with their capacity forregeneration.” “There are limits to growth and consumption...”

WOOD (1994): “Respecting limits to land use and acknowledging that we often lack the ability topredict the land’s response to management activities are critical points of departurefor the ecosystem management concept.” “...ecosystem management entails settinglimits on the use of the land.”

WOODWELL (1990): “The cause of the disruption is a single species, Homo sapiens, which hasescaped the normal limitations that keep the numbers of individuals of each speciesin check and has swarmed over the earth as no species has ever done previously.”

YODZIS (1984): “If there is any property of whole ecosystems that almost every ecologist wouldregard as universal, it is the limitation of food chains to two or three links for the mostpart, with food chains having more than five links being rare.” “The data are consistentwith the hypothesis that food chain lengths are limited by the available energy.”


Appendix 3. Empirical data on observed limits to natural variation and the degree to whichhumans exceed such limits.

Apéndice 3. Datos empíricos sobre límites observados en la variación natural y el grado en quelos humanos exceden estos límites.

Table 1. A list of descriptions for the data shown graphically in figures 2–6 with sample sizesfor the nonhuman species (units for the measure are indicated in corresponding graphs): F.Figure; N. Number of species; C. Category of species (B. Birds; F. Fish; M. Mammals; MHbs.Mammals of human body size; MM. Marine mammals; MMHbs. Marine mammals of humanbody size; TM. Terrestrial mammals; TMHbs. Terrestrial mammals of human body size); S. Source(1. FOWLER et al., 1999, 2. OVERHOLTZ et al., 1991; 3. LIVINGSTON, 1993; 4. FOWLER & PEREZ, 1999;5. CRAWFORD et al., 1991; 6. BACKUS & BOURNE, 1986).

Tabla 1. Lista de descripciones para los datos que se muestran en las figuras 2–6, con indicacióndel tamaño de las muestras para las especies no humanas (las unidades de medida se indican enlos gráficos correspondientes): F. Figura; N. Número de especies; C. Categoria de especies (B.Aves; F. Peces; M. Mamíferos; MHbs. Mamíferos de tamaño corporal similar al humano; MM.Mamíferos marinos; MMHbs. mamíferos marinos de tamaño corporal similar al humano; TM.Mamíferos terrestres; TMHbs. mamíferos terrestres de tamaño corporal similar al humano); S.Fuente (1. FOWLER et al., 1999, 2. OVERHOLTZ et al., 1991; 3. LIVINGSTON, 1993; 4. FOWLER & PEREZ,1999; 5. CRAWFORD et al., 1991; 6. BACKUS & BOURNE, 1986).

TopicF N C Measure Region / Location S2A 11 B, M & F Biomass consumption of Marine ecosystem off 1,2

hake (Merluccius bilinearis) NE coast of North America2B 12 B, M & F Biomass consumption of Marine ecosystem off 1,2

of herring (Clupea harengus) NE coast of North America2C 16 B, M & F Biomass consumption of Marine ecosystem off 1,2

mackerel (Scomber scombrus) NE coast of North America2D 6 MM Biomass consumption of Bering Sea and 1,3,4

walleye pollock North Pacific ecosystem(Theragra chalcogramma)

2E 12 B Biomass consumption of Marine ecosystems off 4,5anchovy (Engraulis capensis) SW coast of Africa

2F 20 B, M & F Biomass consumption of Eastern Bering Sea and 1,3,4walleye pollock North Pacific

3A 20 MM Biomass consumption Eastern Bering Sea 4of finfish

3B 16 B, M & F Biomass consumption of Marine ecosystem off 2,4hake, herring, and mackerel NE coast of North America

3C 13 B & M Biomass consumption from Marine ecosystem off 2,4hake, herring, and mackerel NE coast of North America

3D 18 B Biomass consumption of anchovy, Marine ecosystems off 4,5lanternfish, lightfish, and hake SW coast of Africa(E. capensis, Lampanyctodes hectoris,Maurolicus mulleri, and Merluccius spp.)

4A 21 MM Total biomass consumption Eastern Bering Sea 44B 46 F, B & M Total biomass consumption George Bank ecosystem 64C 33 B Total biomass consumption Marine ecosystems off 5

SW coast of Africa4D 23 B & M Total biomass consumption Georges Bank ecosystem 64E 16 B, M & F Total biomass consumption Marine ecosystem off 2

NE coast of North America4F 12 MM Total biomass consumption Georges Bank ecosystem 65A 54 MM Total biomass consumption Marine environment 4

44 Fowler & Hobbs

Tabla 1. (Cont.)

TopicF N C Measure Region / Location S5B 42 TM Total biomass consumption Entire Earth 45C 63 MHbs Total biomass consumption Entire Earth 45D 96 M Total biomass consumption Entire Earth 45E 63 MHbs CO2 production Entire Earth 45F 63 MHbs Energy ingestion Entire Earth 46Aa 523 TM Geographic range Entire Earth 4

(humans at 20% of Earth’snon–Antarctic land surface)

6Ab 523 M Geographic range Entire Earth 4(humans at 70% of Earth’snon–Antarctic land surface)

6B 21 MMHbs Total Population size Entire Earth 46Ca 368 M Consumption of energy Entire Earth 4

per unit area (human value basedon consumption spread over 20%of the Earth’s terrestrial surface)

6Cb 368 M Consumption of energy Entire Earth 4per unit area (human value basedon consumption spread over 70%of the terrestrial Earth’s surface)

6D 42 TMHbs Total population size Terrestrial environment 46E 523 TM Portion of North America unoccupied North America 46F 63 MHbs Total population size Entire Earth 4


Table 2. Results of statistical tests of the hypothesis that humans are within the normal rangeof natural variation among other species for a variety of measures (listed for the correspondinggraph numbers in table 1, with units shown in the corresponding graphs) and measures ofhumans expressed as multiples of measures of non–human species (expresed as the antilog ofdifferences between columns): F. Figure; Mean. Geometric mean among non–human species; V.Value for humans; P. Probability of human value, or more extreme; * The measure of humansexpressed as a multiple of non–human species is based on the raw values corresponding to thearcsin measures rather than log values.

Tabla 2. Resultados de las pruebas estadísticas referentes a la hipótesis de que los humanos seencuentran dentro del espectro normal de variación natural entre otras especies para unavariedad de medidas (consignadas para los gráficos correspondientes en la tabla 1 y con lasunidades indicadas asimismo en los gráficos correspondientes) y medidas de humanos expresadascomo múltiplos de las medidas de especies no humanas (expresadas como el antilogaritmo de lasdiferencias entre columnas): F. Figura; Mean. Media geométrica entre especies no humanas; V.Valor para los humanos; P. Probabilidad del valor humano, o más extremo; * La medida de loshumanos expresada como múltiplo de especies no humanas está basada en mayor medida en losvalores brutos correspondientes al arcoseno de las medidas que en los valores logarítmicos

Confidence limit Human value as multiple of

F Mean V P 0.95 0.99 Mean 0.95 limit 0.99 limit

2A 3.068 4.255 0.043 4.209 4.681 15.4 1.1 0.4

2B 3.122 4.929 0.000 3.986 4.344 64.2 8.8 3.8

2C 3.127 4.792 0.055 4.840 5.549 46.2 0.9 0.2

2D 4.360 6.072 0.001 5.278 5.659 51.5 6.2 2.6

2E 2.829 5.681 0.000 4.202 4.770 712.3 30.2 8.1

2F 3.866 6.072 0.028 5.760 6.546 160.7 2.0 0.3

3A 4.170 6.301 0.024 5.949 6.686 135.2 2.2 0.4

3B 3.870 5.218 0.038 5.118 5.635 22.3 1.3 0.4

3C 3.344 5.218 0.006 4.567 5.074 74.8 4.5 1.4

3D 3.209 5.681 0.002 4.575 5.141 296.4 12.8 3.5

4A 1.865 3.301 0.035 3.170 3.711 27.3 1.4 0.4

4B 0.613 2.049 0.137 2.770 3.664 27.3 0.2 0.02

4C 2.294 5.681 0.000 3.964 4.655 2,436.8 52.2 10.6

4D 0.389 2.049 0.005 1.460 1.903 45.7 3.9 1.4

4E 3.870 5.218 0.038 5.118 5.635 22.3 1.3 0.4

4F 0.294 2.049 0.000 1.149 1.502 56.9 8.0 3.5

5A 5.572 9.478 0.001 7.556 8.378 8,066.1 83.6 12.6

5B 5.158 9.478 0.001 7.396 8.323 20,900.6 120.9 14.3

5C 5.222 9.727 0.001 7.538 8.497 31,979.3 154.6 17.0

5D 5.391 9.478 0.001 7.506 8.382 12,234.0 93.9 12.5

5E 4.650 10.301 0.000 6.969 7.930 447,951.9 2,148.8 235.2

5F 6.067 10.572 0.001 8.383 9.342 31,979.3 154.6 17.0

6Aa 2.355 4.318 0.035 4.135 4.873 91.9 1.5 0.3

6Ab 2.355 5.030 0.007 4.135 4.873 473.0 7.8 1.4

6B 5.235 9.761 0.002 7.789 8.848 33,627.9 93.7 8.2

6Ca 1.912 4.719 0.000 2.992 3.440 640.5 53.3 19.0

6Cb 1.912 4.020 0.001 2.992 3.440 128.1 10.7 3.8

6D 5.265 9.761 0.000 7.250 8.072 1,370.3 324.9 48.9

6E* 1.295 0.030 0.000 0.801 0.597 0.0010 0.0017 0.0029

6F 5.196 9.761 0.001 7.483 8.430 36,762.0 190.0 21.4



Is growing tourist activityaffecting the distribution ornumber of breeding pairs ina small colony of the Eleonora’s Falcon?

A. Martínez–Abrain1,2,*, D. Oro2, V. Ferrís3 &R. Belenguer3

Martínez–Abrain, A., Oro, D., Ferrís, V. & Belenguer, R., 2002. Is growing tourist activity affecting thedistribution or number of breeding pairs in a small colony of the Eleonora’s Falcon. Animal Biodiversity andConservation, 25.2: 47–51.

AbstractAbstractAbstractAbstractAbstractIs growing tourist activity affecting the distribution or number of breeding pairs in a small colony of theEleonora’s Falcon?— Human disturbance is a common threat for species of conservation concern such as theEleonora’s Falcon. This paper shows that the rise in tourist presence from 1992 to 2000 has not affected theoverall number of breeding pairs or their productivity in a small archipelago of the western Mediterranean(Columbretes Islands). However, the increasing tourist activity has coincided with a shift in the degree ofoccupancy on two islands within the archipelago, favouring that with a lower human presence close tocolonies. Several conservation actions are reported and suggested, aimed at both testing and preventing therole of human presence as a factor influencing long–term colony persistence and growth.

Key words: Eleonora’s Falcon, Human disturbance, Navigation tourism, Columbretes, Conservation, westernMediterranean.

ResumenResumenResumenResumenResumen¿Está afectando la actividad turística creciente a la distribución o al número de parejas reproductoras de unapequeña colonia de halcón de Eleonora?— Las perturbaciones de origen antrópico son un factor de amenazacomún para especies vulnerables como el halcón de Eleonora. El presente artículo muestra que el incrementode la presencia humana en un archipiélago del Mediterráneo occidental (islas Columbretes), durante el periodo1992–2000, no ha afectado ni al número de parejas nidificantes ni a su productividad. Sin embargo, dichoincremento de la actividad turística ha coincidido con un cambio en el nivel de ocupación de dos islas delarchipiélago, favoreciendo a la isla menos frecuentada por embarcaciones turísticas. Se sugieren algunasmedidas de gestión que pueden servir para comprobar si las visitas turísticas pueden influir en el mantenimientoy crecimiento de la colonia a largo plazo, así como para prevenir estos posibles efectos.

Palabras clave: Halcón de Eleonora, Perturbaciones de origen antrópico, Embarcaciones turísticas, Columbretes,Conservación, Mediterráneo occidental.

(Received: 11 II 02; Conditional acceptance: 7 V 02; Final acceptance: 6 VI 02)

1 Alejandro Martínez–Abrain,CPEMN Conselleria de Medi Ambient, Avda. de los Pinares 106, 46012–El Saler, Valencia, Spain.2 A. Martínez–Abrain & D. Oro, Instituto Mediterráneo de Estudios Avanzados IMEDEA (CSIC–UIB), MiquelMarqués 21, 07190–Esporles, Mallorca, Spain.3 V. Ferrís & R. Belenguer, Reserva Natural de las Islas Columbretes, Conselleria de Medio Ambiente, Avda.Hermanos Bou 47, 12003 Castellón, Spain.

* Corresponding author: A. Martínez–Abrain, CPEMN Conselleria de Medi Ambient, Avda. de los Pinares 106,46012–El Saler, Valencia, Spain.

E–mail: [email protected]

48 Martínez–Abrain et al.

WesternWesternWesternWesternWesternMediterraneanMediterraneanMediterraneanMediterraneanMediterranean

Introduction

The Eleonora’s Falcon (Falco eleonorae) is a highlymigratory species which breeds on Mediterraneanislands and winters in the Indian Ocean (WALTER,1979). It is presently considered to have anunfavourable conservation status in Europe(TUCKER & HEATH, 1994). This species has evolveda late breeding calendar as an adaptation tofeeding chicks, taking advantage of the pulse ofmigrant birds moving southwards late in thesummer over the Mediterranean basin (WALTER,1979). Human disturbance is presently consideredone of the major threats to birds and othervertebrates (TUCKER & HEATH, 1994; HILL et al.,1997; RISTOW, 1999). Hence, Eleonora’s Falconsare prone to suffer from human presence sincetourist visits to colonies commonly peak duringthe breeding period.

This paper presents the effects of the increasingnumber of tourist boats on Eleonora’s Falconsbreeding on a small archipelago of the westernMediterranean, following a long period ofmonitoring their breeding performance.


The study took place on the Columbretes Islands(39º51’N 0º40’E), a 19 ha volcanic outcrop(comprising four major islet groups: Carallot,Ferrera, Foradada–Lobo and Grossa) located closeto the edge of the wide continental shelf ofCastellón, E Spain (fig. 1).

The Columbretes archipelago has been anature reserve since 1988 and a marine reservesince 1990. The total area of the marine reserveis 4,400 ha. Two of the islands (the largest andthe smallest, Grossa and Carallot) have a specialprotection regime (integral reserve).

Our main prediction was that changes indistribution or number of breeding pairs onthese two islands would be small whereaschanges in both parameters on Ferrera andForadada–Lobo would be larger.

Data regarding public use of the islands andbreeding performance of Eleonora’s Falcons wereobtained from unpublished reports (ReservaNatural Islas Columbretes, 1988–2001) suppliedby the regional government from 1988 to 2001.

Fig. 1. Map of the study area showing the location of Eleonora’s Falcons nests in 2001 and theapproximate location of buoys for tourist boats in Grossa Island (dotted circle).

Fig. 1. Mapa de las islas Columbretes. Se muestra la localización de los nidos de halcón deEleonora en la Isla Grossa en 2001 y la localización aproximada de las boyas de amarre paraembarcaciones turísticas (círculo con puntos).

NNNNN

NNNNN

0 0 0 0 0 20 m20 m20 m20 m20 m

1 1 1 1 1 350 350 350 350 350 700 km700 km700 km700 km700 kmLoboLoboLoboLoboLobo

FerreraFerreraFerreraFerreraFerrera

GrossaGrossaGrossaGrossaGrossa

MancolibreMancolibreMancolibreMancolibreMancolibre

ForadadaForadadaForadadaForadadaForadada

CarallotCarallotCarallotCarallotCarallot

IberianIberianIberianIberianIberianpeninsulapeninsulapeninsulapeninsulapeninsula


Human presence was measured as the numberof boat licence plates recorded daily (boats–dayhereafter).

Boats were tied up to the buoys located aroundthe islands and the team of three wardens livingon the main island counted them daily by meansof a terrestrial telescope.

The monitoring of boats was constantthroughout the study period. The number ofbreeding pairs was also determined by know-ledgeable wardens of the reserve by inspectingthe islands from a boat early in the breedingseason to locate and count breeding pairs andlater by double–checking the existence of nestsfrom the mainland.

Productivity (i.e. number of fledglings per nest)was estimated from the content of nests whenvisited for chick ringing in mid September, usingfield procedures developed by two members ofthe study team (AM, DO).

Monitoring and ringing of falcons wasapproximately constant throughout the studyperiod. In 1999, the overall number of breedingpairs was not estimated due to lack of anappropriate boat to visit all the islands, butproductivity was estimated from nests locatedon Grossa Island and Mancolibre (fig. 1).

Results

Inter–annual variation in the number of boats–day is shown in table 1. The overall trend was aprogressive increase in human presence on theislands (rs = 0.97, n = 13, p < 0.001). Monthlyvariations in the number of boats–day are shownin figure 2. Boats–day clearly peaked in July andAugust precisely the time when falcons werelaying and incubating their eggs (DOLZ & DIES,1987). However, the number of breeding pairsremained approximately constant through theyears (26 ± 2.16 pairs, mean ± SD, n = 13) as didtheir productivity (1.64 ± 0.33, mean ± SD, n = 13)(table 1). In fact, correlations between years andnumber of pairs (rs = 0.18, n = 13, p > 0.05) andproductivity (rs = 0.50, n = 13, p > 0.05) were notsignificant.

No significant correlation was found eitherbetween overall numbers of boats–day duringthe breeding period (July–September) andnumbers of breeding pairs (rs = –0.14, n = 12,p = 0.66,) or between overall number of boats–day during the breeding period and productivity(rs = 0.23, n = 12, p = 0.46). Inter–annual variationin the use of the various islands by breedingfalcons and tourist boats is shown in table 1.

Table 1. Number of nests and productivity of Eleonora’s Falcons (Falco eleonorae) detected oneach island of the Columbretes archipelago during the period 1988–2000 (source: ReservaNatural Islas Columbretes, 1988–2001): ND. No data available; In brackets number of boats–day.

Tabla 1. Número de nidos y productividad de halcones de Eleonora (Falco eleonorae) detectadosen cada una de las islas del archipiélago de las Columbretes durante el periodo 1988–2000 (datosextraídos de: Reserva Natural Islas Columbretes, 1988–2001): ND. Información no disponible;entre paréntesis se indica el número de barcos–día durante el periodo reproductor.

Year Carallot Foradada–Lobo Ferrera Grossa Productivity Total

1988 1 6 5 11 – 23 (184)

1989 – – – – 1.37 22 (242)

1990 – – – – 1.73 28 (374)

1991 – – – – 1.41 27 (509)

1992 0 (2) 8 (31) 4 (11) 15 (592) 1.53 27 (636)

1993 1 (12) 3 (65) 7 (31) 15 (537) 1.66 26 (645)

1994 1 (19) 4 (131) 5 (36) 14 (606) 1.0 24 (792)

1995 0 (33) 5 (86) 8 (40) 13 (493) 1.61 26 (652)

1996 1 (106) 3 (107) 6 (38) 13 (481) 1.89 23 (732)

1997 1 (0) 3 (94) 6 (66) 13 (695) 1.35 23 (855)

1998 1 (0) 3 (93) 8 (45) 15 (715) 2.0 27 (853)

1999 1 (0) – (75) – (66) 12 (804) 2.0 – (945)

2000 1 (0) 1 (86) 9 (51) 14 (758) 1.6 25 (895)

2001 1 4 10 15 2.17 30

50 Martínez–Abrain et al.

The percentage of falcons breeding on Ferrera(in relation to the total breeding pairs of Ferrera+ Foradada–Lobo) increased over time (table 1).Indeed, a non–parametric correlation run tocheck whether this percentage had changedover with time showed a significant strongcorrelation (rs = 0.78, p = 0.014), althoughcorrelations between annual numbers ofbreeding pairs and annual numbers of boats–day at Ferrera and Foradada (considering boththe number of boats–day at years t and t–1, totest for any influence of tourist presence theyear before) were all not significant.

Discussion

Shifts in island use by Eleonora’s falcons seemto have affected only the colonies on Ferreraand Foradada, the two islands with no specialprotection regime. Anchoring of boats aroundCarallot is not permitted as the distance fromGrossa makes it difficult to keep activities carriedout within the restricted area under control.Nevertheless, tourist activities such as scuba–diving are allowed on Grossa, where the islandwardens, who have a permanent base on thisisland, can more easily monitor the activities ofvisitors; boats must be tied up to buoys in thebay, thereby remaining far from falcon nestswhich are mostly located in the outer cliffs ofthe island (see fig. 1).

We are not aware of any factor (e.g. food, nest–site availability, competing species, ectoparasites)

other than human presence that may haveinfluenced the change in the distribution ofbreeding pairs, albeit the exact way in whichhuman presence may have affected falcons remainsunknown. However, the fact that scuba–diversprefer Foradada as compared to Ferrera, becauseof the existence of submerged archs (S. Sales, pers.com.) may have played some role.

Our data indicate that high tourist presencecoincideds with a loss of pairs at Foradada–Loboand that low tourist presence coincided with anincrease in the number of pairs at Ferrera, andthat there were no changes in the overall numberof breeding pairs (i.e. the colony remains stableand hence increases and decreases in the numberof falcon pairs in each island are only rearrange-ments within the archipelago). However, onlyexperimental manipulation of the number ofboats–day could unequivocally demonstrate acause–effect relationship. We predict that anymarked decreased in the number of boats aroundForadada–Lobo would be paralleled by an increasein the number of falcon breeding pairs.

These spatial changes may not be dangerousfor short–term colony persistence. The clumpingof breeding pairs in social species, such as theEleonora’s Falcon, can have positive consequencesfor breeding performance; one possible short–term conservation option would be to increaseprotection of Ferrera (where the level of humanpresence is quickly approaching that of Foradada–Lobo), allowing only Foradada–Lobo as a touristdestination. However, given the reduced size ofthe archipelago, high protection on Foradada–

Fig. 2. Monthly variation in the number of boats–day at the Columbretes Islands during theperiod 1997–2000: E. January; F. February; M. March; A. April; Ma. May; J. June; Jl. July; Ag.August; S. September; O. October; N. November; D. December.

Fig. 2. Variación mensual en el número de barcos–día en las islas Columbretes durante elperiodo 1997–2000: E. Enero; F. Febrero; M. Marzo; A. Abril; Ma. Mayo; J. Junio; Jl. Julio; Ag.Agosto; S. Septiembre; O. Octubre; N. Noviembre; D. Diciembre.

700700700700700

600600600600600

500500500500500

400400400400400

300300300300300

200200200200200

100100100100100

00000EEEEE FFFFF MMMMM AAAAA MaMaMaMaMa JJJJJ JlJlJlJlJl AgAgAgAgAg SSSSS OOOOO NNNNN DDDDD

MonthsMonthsMonthsMonthsMonths

19971997199719971997

19981998199819981998

19991999199919991999

20002000200020002000

Bo

ats

/da

yB

oa

ts/d

ay

Bo

ats

/da

yB

oa

ts/d

ay

Bo

ats

/da

y


Lobo should also be attained in the future so asnot to threaten long–term colony persistenceand growth (e.g. banning the presence of boatswithin a buffer zone around the island).

Tourism affecting Eleonora’s Falcons in theColumbretes Islands was previously reported in1997, when a marked decrease in breeding pairsoccurred in a small rocky islet located besidethe main island (Mancolibre, see fig. 1). Thisreduction was probably caused by excessivepresence of scuba divers according to SÁNCHEZ

(1997). The environmental authorities expe-rimentally removed a buoy placed close to theisle, and banned the transit of boats around theislet. This sub–colony quickly recovered its usualnumber of breeding pairs in 1998. Hence,conservation measures addressed to reducehuman presence around the colonies ofEleonora’s Falcons can give positive results andshould be further employed to determine therole of human presence on the patterns ofisland use by falcons.

Acknowledgements

This study is contribution no. 7 to the LIFE–NATUREprogram BA–3200/98/447 “Conservation of islandSPAs in the Valencian region”, financed by theGeneralitat Valenciana and the EU. Thisinvestigation would not have been possiblewithout the work of all the wardens on theColumbretes reserve. We specially thank Roque

Belenguer and Vicente Ferrís for their valuableassistance during field work. Eduardo Mínguezand a second anonymous referee providedvaluable comments. Covadonga Viedma and MarioGiménez, critically read drafts of the manuscript.

References

DOLZ, J. C. & DIES, I., 1987. El halcón de Eleonor(Falco eleonorae, Gené) en las Islas Columbretes.In: Islas Columbretes: Contribución al estudio desu medio natural: 241–263 (L. A. Matilla, J. L.Carretero & A. M. García–Carrascosa, Eds.).Generalitat Valenciana, Valencia.

HILL, D., HOCKIN, D., PRICE, D., TUCKER, G., MORRIS, R.& TREWEEK, J., 1997. Bird disturbance: Improvingthe quality and utility of disturbance research.Journal of Applied Ecology, 34: 275–288.

RISTOW, D., 1999. International species action planfor Eleonora’s Falcon Falco eleonorae. BirdLifeInternational. Unpublished report.

SÁNCHEZ, A., 1997. Preliminary report on theimpact of scuba–diving on the breedingpopulation of Eleonora’s Falcon of theColumbretes Islands. Generalitat Valenciana,unpublished report.

TUCKER, G. M. & HEATH, M. F., 1994. Birds in Europe:their conservation status. BirdLife ConservationSeries No. 3. BirdLife International, Cambridge.

WALTER, H., 1979. Eleonora’s Falcon: adaptationsto prey and habitat in a social raptor. ChicagoUniversity Press, Chicago.



Nekola, J. C., 2002. Effects of fire management on the richness and abundance of central North Americangrassland land snail faunas. Animal Biodiversity and Conservation, 25.2: 53–66.

AbstractAbstractAbstractAbstractAbstractEffects of fire management on the richness and abundance of central North American grassland land snail faunas.— The landsnail faunas from 72 upland and lowland grassland sites from central North America were analyzed. Sixteen of these had beenexposed to fire management within the last 15 years, while the remainder had not. A total of 91,074 individuals in 72 differentspecies were observed. Richness was reduced by approximately 30% on burned sites, while abundance was reduced by 50–90%.One–way ANOVA of all sites (using management type as the independent variable), a full 2–way ANOVA (using management andgrassland type) of all sites, and a 2–way ANOVA limited to 26 sites paired according to their habitat type and geographic location,demonstrated in all cases a highly significant (up to p < 0.0005) reduction in richness and abundance on fire managed sites.Contingency table analysis of individual species demonstrated that 44% experienced a significant reduction in abundance on fire-managed sites. Only six species positively responded to fire. Comparisons of fire response to the general ecological preferencesof these species demonstrated that fully 72% of turf–specialists were negatively impacted by fire, while 67% of duff–specialistsdemonstrated no significant response. These differences were highly significant (p = 0.0006). Thus, frequent use of firemanagement represents a significant threat to the health and diversity of North American grassland land snail communities.Protecting this fauna will require the preservation of site organic litter layers, which will require the increase of fire return intervalsto 15+ years in conjunction with use of more diversified methods to remove woody and invasive plants.

Key words: Land snail, Biodiversity, Conservation, Fire management, Grassland, North America.

ResumenResumenResumenResumenResumenEfectos de la gestión con fuego sobre la riqueza y abundancia de la fauna de caracoles terrestres de las praderas deAmérica del Norte.— Se analiza la fauna de caracoles terrestres de 72 praderas en mesetas y llanuras de la regióncentral de América del Norte. En 16 de ellas se habían efectuado intervenciones de incendio controlado durante losúltimos 15 años, mientras en el resto no. Se observaron un total de 91.074 individuos de 72 especies diferentes. Lariqueza en especies estaba reducida en un 30% en las áreas quemadas, mientras que la abundancia de individuosestaba reducida en un 50–90%. Un ANOVA unidireccional de todas las áreas (usando como variable independiente eltipo de intervención), un ANOVA bidireccional completo (usando el tipo de intervención y el tipo de pradera) en todaslas áreas y un ANOVA bidireccional limitado a 26 áreas agrupadas según su tipo de hábitat y localización geográfica,demostró en todos los casos una reducción altamente significativa de la riqueza y de la abundancia (hasta p < 0,0005)en áreas sometidas a incendio. Un análisis individual de las especies mediante tablas de contingencia demostró queel 44% experimentaron una reducción significativa de su abundancia en las áreas quemadas. Sólo seis especiesrespondieron positivamente al fuego. Comparando la respuesta al fuego con las preferencias ecológicas generales deestas especies se demostró que al menos el 72% de las especialistas que viven en sustrato herbáceo fueron afectadasnegativamente por el fuego mientras que el 67% de las que viven en sustrato húmico no demostraron ningunarespuesta significativa. Estas diferencias fueron altamente significativas (p = 0,0006). Así pues, el uso frecuente delfuego representa una amenaza significativa para la salud y diversidad de las comunidades de caracoles terrestres delas praderas de América del Norte. La protección de esta fauna requerirá la preservación de las capas de materiaorgánica y la ampliación de los intervalos entre las actuaciones de quema a periodos superiores a 15 años, así comoel uso de métodos más diversos para eliminar las plantas leñosas e invasivas.

Palabras clave: Caracol terrestre, Biodiversidad, Conservación, Gestión con fuego, Praderas, América del Norte.

(Received: 9 IV 02; Final acceptance: 18 VI 02)

Jeffrey C. Nekola, Dept. of Natural and Applied Sciences, Univ. of Wisconsin–Green Bay, Green Bay, Wisconsin54311 USA.


Effects of fire management on therichness and abundance ofcentral North Americangrassland land snail faunas

J. C. Nekola

54 Nekola

Introduction

Fire has long been implicated in the maintenanceof central North American grassland communities(WEAVER, 1954; CURTIS, 1959). Numerous nativeplant species respond to fire by increasing theirgrowth and reproductive rates (EHRENREICH &AIKMAN, 1963; KUCERA & KOELLING, 1964; TOWNE &OWENSBY, 1984). One of the most direct effectsof prairie fire is the removal of the soil mulchlayer, which has been implicated in the‘stagnation’ of prairie plant communities throughthe delay of initial spring growth, thinning ofgrass stem density, and prevention of herbaceousunderstory development (WEAVER & ROWLAND,1952; KUCERA & KOELLING, 1964). Fire is alsothought to limit invasion of woody and exoticplants into native prairie habitats (e.g., PAULY,1985; ROOSA, 1984). For these reasons, prescribedfire has become the management tool of choiceby prairie conservation groups throughout themidwestern USA (COLLINS & WALLACE, 1990).

However, an increasing body of research suggeststhat fire is not universally beneficial all prairiebiota. Fire depresses growth and reproductive ratesof native C3 prairie plants (DIX, 1960; HADLEY, 1970;HILL & PLATT, 1975), which make up at least 50% ofthe native flora north of 44o N (STOWE & TEERI, 1978;SIMS, 1988). Fire has also been implicated in the lossand/or reduction of numerous native prairieinvertebrate species including Lepidoptera,Homoptera, Hymenoptera, and Araneae (SWENGEL,1996, 1998; HARPER et al., 2000). The effects of suchpractices on prairie soil biodiversity are largelyundocumented. Combustion of mulch throughrepeated fire episodes will remove the detritusphere,one of the most important reservoirs for soilbiodiversity (COLEMAN & CROSSLEY, 1996). HARPER etal. (2000) documented significant reductions inCollembola following Illinois prairie fires. As thesoil fauna represents one of the largest speciespools in terrestrial ecosystems (BEHAN–PELLETIER &NEWTON, 1999), the potential impacts of suchprocesses on total site biodiversity may be large.

Although not as hyper–diverse as bacteria,fungi, nematodes, and arthropods, molluscs stillrepresent one of the more important componentsof soil biodiversity (RUSSELL–HUNTER, 1983). Almost600 species are known from eastern NorthAmerica (HUBRICHT, 1985), with up to 21 taxa co-occurring within 400 cm2 microhabitats (NEKOLA

& SMITH, 1999). Most of these taxa representgeneralist detritivores that live in and on deadorganic material (BURCH & PEARCE, 1990)

As almost 90% of snails occur within 5 cm ofthe soil surface (HAWKINS et al., 1998), protectionof this fauna will likely be tied to the fate ofmulch layers. Disturbances such as logging,recreational or urban development, or bedrockand soil removal cause dramatic changes inwoodland snail communities with duff soilsurfaces (NEKOLA, in press a). The impact of fire,and associated detritusphere removal, on snail

communities is unclear. Fire has been suggestedto negatively influence the faunas of Aegeanislands (WELTER–SCHULTES & WILLIAMS, 1999),Queensland fens (STANISIC 1996), and Tasmanianwoodlands (REGAN et al., 2001). However, FREST &JOHANNES (1995) state that molluscs are able tosurvive natural fires in northwestern NorthAmerica, and THELER (1997) argued that xericprairie faunas in Wisconsin owe their existenceto frequent fires that keep grassland areastreeless. Unfortunately, no data was presentedby these various authors to validate suchconflicting statements.

To evaluate this issue, the richness andabundance of land snails was quantitativelycompared between unburned and recently(< 15 year) burned sites in the midwestern USA,including 13 pairs of sites which possess similarhabitats and are spatiall proximate. From these,the following questions will be considered: 1. Isthere a significant difference in land snailcommunity richness between burned andunburned grasslands? 2. Is there a significantdifference in land snail abundance betweenburned and unburned grasslands? 3. What speciesshow positive, negative, or no response to fire?What ecological factors (if any) may help explainthese responses?

Materials and methods

Study Sites

Seventy two grassland sites were surveyedbetween May 1996–November 2001 for terrestrialmolluscs across a 850 km extent of central NorthAmerica (fig. 1, table 1). Sites are generallycentered on northwestern Minnesota andnortheastern Iowa. Forty–two occur in Minnesota,25 in Iowa, and 5 in Wisconsin. Thirty–two sitesrepresent upland habitats (including tallgrassprairie, sand prairie, and bedrock glades), whilethe remaining 40 are lowland sites (includingwet prairie, sedge meadow, and fens). Previoususe of fire management on sites was assessed byeither observing carbonized woody plant stemsor other debris on the ground surface, or throughinterviews with site managers or otherknowledgeable individuals. No use of firemanagement was noted from 56 sites (88% oftotal), while 16 (22%) had been subjected tosome amount of prescribed burning. Eleven ofthese burned sites occur in Minnesota, while theremaining five occur in Iowa. The latitude–longitude location of each site was determinedusing either USGS 7.5 minute topographic mapsor a hand–held GPS.

Field Methods

Documentation of terrestrial gastropod faunasfrom each site was accomplished by hand


collection of larger shells and litter sampling forsmaller taxa within 100–1,000 m2 areas thatcontained examples of all major microhabitatsand were thus representative of the larger site.The actual grain size employed was determinedby the minimum size necessary to emcompass allmicrohabitats. Soil litter sampling was primaryused as it provides the most complete assessmentof grassland faunas (OGGIER et al., 1998). A singlesite sample consisted of a composite of individualsoil litter subsamples of approximately 200 mlcollected from appropriate microhabitats. Assuggested by EMBERTON et al. (1996), littercollections were made at places of high micro-mollusc density, with a constant volume(approximately 4 liters) being gathered fromeach site. Sampling was generally comprised of:1. Small blocks (ca. 125 cm3) of turf; 2. Loose soiland leaf litter accumulations under or adjacentto shrubs, cobbles, boulders, and/or hummocks;and 3. Other microsites supporting relativelythick mulch layers.

LLLLLaboratory procedures

Samples were slowly and completely dried ineither a low–temperature soil oven (ca. 80–95oC)or in full sun in a greenhouse. Dried sampleswere then soaked in water for 3–24 hours, andsubjected to careful but vigorous waterdisaggregation through a standard sieve series(ASTME 3/8" (9.5 mm), #10 (2.0 mm), #20 (0.85),and #40 (0.425 mm) mesh screens). Sieved samplefractions were then dried and passed againthrough the same sieve series. These dry, resortedfractions were hand picked against a neutral-brown background. All shells and shell fragmentswere removed.

All identifiable shells from each site wereassigned to species (or subspecies) using theauthor’s reference collection and the HubrichtCollection at the Field Museum of Natural History(FMNH), with the total number of shells perspecies per site being recorded. The total numberof unassignable, immature individuals was alsocounted from each site. All specimens have beencatalogued and are housed in the author’scollection at the University of Wisconsin–GreenBay. Nomenclature generally follows that ofHUBRICHT (1985), with updates and corrections byFREST (1990, 1991) and NEKOLA (in press b). Thegeneral ecological preferences (turf specialist,duff–specialist or generalist) of each species isbased upon analyses presented in NEKOLA (inpress a).

Statistical procedures

Differences in species richness and total shellabundance between burned and unburnedgrassland sites were analyzed via ANOVA. Initially,1–way ANOVAs were preformed on the entiredataset. However, the effect of fire may be

obscured in this analysis due to confoundingeffects of habitat type and geographic location.To help control for this, two additional sets ofANOVAs were conducted. First, full 2–way ANOVAswere calculated for all sites using grassland type(upland vs. lowland) and management history(burned vs. unburned) as the independentvariables. Second, 13 pairs of sites representingclosely similar habitats within the same geographicregion, but differing in their fire managementhistory, were selected. These site pairs are (firstsite is burned, second is unburned): MalmbergPrairie vs. Sandpiper Prairie; Pankratz Mesic Prairievs. Radium NE; Pankratz Low Prairie vs. BjornsonWMA; Pankratz Fen vs. Faith South; MarcouxWMA vs. Cyr Creek; East Park WMA vs. GooseLake; Felton Fen 1 vs. Ogema West; Waubun SEvs. Eastlund Lake; Chicog vs. Tansen; Beemis Creekvs. Hampton East; Fayette vs. Decorah Glade; BatyGlade vs. Canton Glade; Brayton–Horsley vs.Stapleton Church. A 2–way ANOVA withoutinteraction was then calculated for these sites,with site pair identity and management typerepresenting independent variables.

Fig. 1. Map of study region, showing locationof surveyed grassland sites: � Unburnedupland; � Burned upland; � Unburnedlowland; � Burned lowland.

Fig. 1. Mapa del área de estudio que mues-tra la localización de las praderas estudia-das: � Meseta no quemada; � Meseta que-mada; � Llanura no quemada; � Llanuraquemada.

56 Nekola

Table 1. Location, grassland type, management, species richness and total number of collectedindividuals from sample sites: GT. Grassland type; M. Management; R. Richness; I. Individuals.

Tabla 1. Localización, tipo de pradera, gestión, riqueza de especies y número total de individuosrecogidos en cada área de estudio: GT. Tipo de pradera; M. Gestión; R. Riqueza; I. Individuos.

State / County / Site Name Location GT M R I

Iowa

Allamakee County

Fish Farm Mounds 91°17'12" W – 43°27'13" N Upland Unburned 21 632

Williams Creek 3 91°29'1" W – 43°8'1" N Upland Unburned 23 2,708

Bremer County

Brayton–Horsley Fen 92°6'29" W – 42°48'36" N Lowland Burned 16 627

Buchanan County

Rowley Fen 91°51'7" W – 42°22'27" N Lowland Unburned 16 3,217

Rowley North Fen 91°51'3" W – 42°22'35" N Lowland Unburned 17 3,231

Rowley West Fen 91°54'40" W – 42°22'15" N Lowland Unburned 22 2,250

Cerro Gordo County

Buffalo Slough 93°11'11" W – 43°10'36" N Lowland Unburned 19 4,770

Chickasaw County

Stapelton Church Fen 92°6'14" W – 43°1'35" N Lowland Unburned 18 1,065

Clayton County

Postville Fen 91°33'59" W – 43°2'3" N Lowland Unburned 12 252

Turkey River Mounds 91°2'11" W – 42°42'46" N Upland Unburned 22 870

Clinton County

Maquoketa South 90°39'5" W – 42°1'12" N Upland Unburned 12 310

Dubuque County

Roosevelt Road 90°44'30" W – 42°32'55" N Upland Unburned 18 375

Fayette County

Fayette 91°47'28" W – 42°50'11" N Upland Burned 13 254

Turner Creek 1 Fen 91°52'11" W – 42°58'15" N Lowland Unburned 16 1,071

Floyd County

Beemis Creek 93°1'18" W – 42°59'39" N Upland Burned 8 192

Juniper Hill 92°59'2" W – 43°3'10" N Upland Unburned 12 206

Franklin County

Hampton East 93°8'13" W – 42°43'42" N Upland Unburned 15 381

Howard County

Hayden Prairie 92°23'4" W – 43°26'30" N Upland Burned 12 132

Staff Creek Fen 92°30'34" W – 43°26'41" N Lowland Unburned 15 1,599

Jackson County

Hamilton Glade 90°34'9" W – 42°4'23" N Upland Unburned 15 340

Jones County

Canton Glade 90°59'52" W – 42°10'46" N Upland Unburned 19 446

Linn County

Baty Glade 91°39'14" W – 42°11'44" N Upland Burned 16 345

Paris Fen 91°35'42" W – 42°13'40" N Lowland Unburned 12 1,254



Mitchell County

Stone School Fen 92°38'11" W – 43°22'49" N Lowland Unburned 18 2,926

Winneshiek County

Decorah Glade 91°46'11" W – 43°18'55" N Upland Unburned 18 605

Minnesota

Becker County

Audubon South Fen 95°58'47" W – 46°49'58" N Lowland Unburned 15 1,816

Callaway North 95°55'22" W – 47°3'57" N Upland Unburned 19 362

Greenwater Lake Fen 95°29'59" W – 46°59'20" N Lowland Unburned 20 2,132

Ogema West Fen 95°55'59" W – 47°6'32" N Lowland Unburned 16 5,001

Straight Lake 95°18'40" W – 46°58'40" N Upland Unburned 13 281

Beltrami County

Fourtown Fen 95°18'21" W – 48°15'56" N Lowland Unburned 14 1,403

Clay County

Barnesville WMA 96°17'34" W –46°43'5" N Upland Unburned 11 469

Barnesville WMA Fen 96°17'38" W – 46°43'9" N Lowland Unburned 13 436

Bjornson WMA 96°21'24" W – 46°45'44" N Lowland Unburned 14 436

Bluestem Prairie 96°28'45" W – 46°51'18" N Upland Burned 15 371

Felton Prairie 1 Fen 96°26'21" W – 47°3'51" N Lowland Burned 15 2,370

Felton Prairie 2 Fen 96°26'20" W – 47°4'0" N Lowland Unburned 14 3,131

Felton Prairie 96°26'1" W – 47°3'34" N Upland Unburned 5 63

Tansen 96°11'17" W – 46°42'14" N Upland Unburned 10 146

Clearwater County

Bagley Lake Fen 95°14'35" W – 47°45'41" N Lowland Unburned 9 126

Filmore County

Vesta Creek 91°45'0" W – 43°40'5" N Upland Unburned 21 1,151

Houston County

Twin Pines Farm 91°22'45" W – 43°44'48" N Upland Unburned 24 591

Yucatan Twp. 91°38'28" W – 43°43'23" N Upland Unburned 20 765

Mahnomen County

Eastlund Lake 95°47'5" W – 47°26'41" N Upland Unburned 13 490

Mahnomen North 95°58'8" W – 47°21'27" N Upland Unburned 18 806

Waubun SE 95°54'55" W – 47°9'57" N Lowland Unburned 18 2,915

Waubun SE 95°55'4" W – 47°10'5" N Upland Burned 8 220

Marshall County

East Park WMA 96°16'44" W – 48°31'57" N Lowland Burned 14 735

Florian WMA 96°33'21" W – 48°26'33" N Lowland Unburned 17 3,923

Radium NE 96°32'38" W – 48°16'49" N Upland Unburned 12 493

Norman County

Faith South 96°5'12" W – 47°15'42" N Lowland Unburned 16 3,047

Prairie Smoke Dunes 96°18'22" W – 47°27'44" N Upland Unburned 3 19

Sandpiper Prairie 96°24'22" W – 47°14'43" N Lowland Unburned 12 1,261

Table 1. (Cont.)

58 Nekola

The central tendencies in these variousrelationships were graphically represented via boxplots. In box plots, the central line represents themedian of the sample, the margins of the boxrepresent the interquartile distances, and the fencesrepresent 1.5 times the interquartile distances. Fordata having a Gaussian distribution, approximately99.3% of the data will fall inside of the fences(VELLEMAN & HOAGLIN, 1981). Outliers falling outsideof the fences are shown with asterisks.

The average number of individuals per speciesper site was determined for burned uplands,unburned uplands, burned lowlands, and

unburned lowlands. The average proportion ofeach species in the total community for each sitewas calculated for each management/habitat type.These proportions were placed in rank order, andplotted vs. log–transformed frequency to createdominance–diversity curves (WHITTAKER, 1975).

The response of individual species to fire wasanalyzed through log–linear modelling, aspredicted values in the associated contingencytable were sparse (< 5) in more than one–fifth ofcells (ZAR, 1984). The total number of individualswithin all burned or unburned sites was comparedto a null expectation of equal occurrence

Pennington County

Goose Lake 96°27'44" W – 48°5'37" N Lowland Unburned 17 996

Higenbotham WMA 96°17'41" W – 48° 0'22" N Lowland Unburned 22 1,114

Sanders Fen 96°21'9" W – 48°3'52" N Lowland Unburned 15 2,218

Polk County

Chicog Prairie 96°23'14" W – 47°35'53" N Upland Burned 2 153

Erskine North 96°0'3" W – 47°44'17" N Lowland Unburned 19 741

Gulley Fen 95°37'22" W – 47°48'13" N Lowland Unburned 19 2,032

Malmberg Prairie 96°49'25" W – 47°43'52" N Lowland Burned 7 563

Pankratz Prairie 96°26'37" W – 47°43'23" N Lowland Burned 12 314

Pankratz Prairie 96°26'31" W – 47°43'23" N Upland Burned 11 159

Pankratz Prairie 96°26'48" W – 47°43'9" N Lowland Burned 7 190

Red Lake County

Crane WMA 95°42'49" W – 47°53'27" N Lowland Unburned 15 425

Cyr Creek 96°16'12" W – 47°48'10" N Lowland Unburned 22 1,845

Marcoux WMA 96°13'27" W – 47°47'55" N Lowland Burned 12 688

Winona County

Great River Bluffs 91°23'28" W – 43°56'53" N Upland Burned 19 788

Wisconsin

Green Lake County

Berlin Fen 88°54'20" W – 43°57'47" N Lowland Unburned 20 3,454

Manitowoc County

Point Beach St. Forest 87°30'40" W – 44°11'52" N Upland Unburned 4 6

Walworth County

Bluff Creek Fen 88°40'54" W – 42°48'2" N Lowland Unburned 20 1,106

Washington County

Allenton Fen 88°18'25" W – 43°22'42" N Lowland Unburned 20 2,858

Waushara County

Bass Lake Fen 89°16'59" W – 44°0'16" N Lowland Unburned 19 1,466

Table 1. (Cont.)



Table 2. List of encountered species, with their average abundances from burned and unburnedsites. P–values are based on log-likelihood ratio tests, with the two–tailed significance thresholdbeing lowered to p = 0.000347 to account for the 72 tested species. General ecological preferencesare based on NEKOLA (in press a). Turf–specialists represent those species demonstrating at leasta p < 0.05 preference to sites with a friable upper A soil horizon supporting few living plant roots.Turf specialists represent those species demonstrating at least a p < 0.05 preference to sites withan upper A soil horizon that is bound together with living plant roots. Species without preferenceswere too infrequently encountered by NEKOLA (in press a) to be statistically assigned: AvU. Averageunburned; Abb. Abundance burned; Ecp. Ecological preference (T. Turf; D. Duff; G. Generalist.)

Tabla 2. Lista de especies detectadas, con sus abundancias medias en áreas quemadas y noquemadas. Los valores de P se basan en tests de cociente de probabilidad logarítmica, con el umbralde significación de doble cola reducido hasta p = 0,000247 para las 72 especies estudiadas. Laspreferencias ecológicas generales se basan en NEKOLA (in press a). Las especies que viven en sustratoherbáceo presentan una preferencia de al menos p < 0,05 por las zonas con horizonte de tierrafriable superior A provisto de escasas raíces de plantas vivas. Las especies que viven en sustratoherbáceo presentan una preferencia de al menos p < 0,05 por las zonas cuyo horizonte se mantieneunido por raíces de plantas vivas. Las especies sin preferencias resultaron excesivamente infrecuentessegún NEKOLA (in press a) para consignarlas estadísticamente: AvU. Medias en áreas no quemadas;Abb. Abundancia en áreas quemadas; Ecp. Preferencia ecológica (T. Sustrato herbáceo; D. Sustratohúmico; G. Generalista.)

Species AvU Abb P–value Ecp

Negative responses

Carychium exiguum (Say, 1822) 273.607 90.250 0.0000000 T

Carychium exile H. C. Lea, 1842 5.196 0.000 0.0000000 D

Catinella exile (Leonard, 1972) 58.446 1.625 0.0000000 T

Catinella "vermeta" 1.482 0.000 0.0000001 T

Deroceras laeve (Müller, 1774) 4.036 1.188 0.0000050 G

Discus cronkhitei (Newcomb, 1865) 16.143 5.000 0.0000000 G

Euconulus alderi (Gray, 1840) 43.054 8.375 0.0000000 T

Gastrocopta contracta (Say, 1822) 21.232 5.875 0.0000000 G

Gastrocopta holzingeri (Sterki, 1889) 36.196 17.938 0.0000000 D

Gastrocopta pentodon (Say, 1821) 9.661 4.875 0.0000072 D

Gastrocopta procera Gould, 1840 2.304 0.000 0.0000000 T

Gastrocopta rogersensis Nekola & Coles, 2001 5.518 0.062 0.0000000 T

Gastrocopta similis (Sterki, 1909) 21.518 4.125 0.0000000 T

Gastrocopta tappaniana (C. B. Adams, 1842) 112.929 33.375 0.0000000 T

Hawaiia minuscula (A. Binney, 1840) 36.286 23.062 0.0000000 G

Helicodiscus n. sp. 1.071 0.062 0.0001509 T

Nesovitrea binneyana (Morse, 1864) 1.500 0.000 0.0000001 D

Nesovitrea electrina (Gould, 1841) 80.179 22.688 0.0000000 T

Oxyloma retusa (I. Lea, 1834) 21.268 8.750 0.0000000 T

Pomatiopsis lapidaria (Say, 1817) 1.196 0.000 0.0000021 –

Punctum minutissimum (I. Lea, 1841) 26.286 10.500 0.0000000 D

Punctum n. sp. 41.982 12.625 0.0000000 T

Punctum vitreum H. B. Baker, 1930 16.536 2.812 0.0000000 D

Stenotrema leai leai (A. Binney) 2.696 0.375 0.0000004 T

Striatura milium (Morse, 1859) 0.714 0.000 0.0002470 G

Strobilops affinis Pilsbry, 1893 74.911 4.312 0.0000000 T

Triodopsis multilineata (Say, 1821) 1.571 0.062 0.0000016 G

Vallonia pulchella (Müller, 1774) 23.321 11.688 0.0000000 T

60 Nekola

Species AvU Abb P–value Ecp

Vertigo elatior Sterki, 1894 41.875 5.875 0.0000000 T

Vertigo milium (Gould, 1840) 59.357 36.375 0.0000000 T

Vertigo morsei Sterki, 1894 3.589 0.375 0.0000000 T

Vitrina limpida Gould, 1850 1.143 0.000 0.0000035 G

No response

Anguispira alternata (Say, 1817) 0.018 0.000 0.5622176 D

Catinella avara (Say, 1824) 7.286 8.000 0.5185276 T

Cochlicopa lubrica (Müller, 1774) 0.464 0.000 0.0031253 D

Cochlicopa lubricella (Porro, 1838) 1.714 1.938 0.6798546 G

Columella simplex (Gould, 1841) 0.071 0.188 0.4068651 D

Discus catskillensis (Pilsbry, 1898) 0.357 0.000 0.0095467 D

Euconulus fulvus (Müller, 1774) 3.429 1.625 0.0040433 D

Euconulus polygyratus (Pilsbry, 1899) 0.018 0.000 0.5622176 D

Gastrocopta abbreviata (Sterki, 1909) 0.000 0.062 0.2039785 –

Gastrocopta armifera (Say, 1821) 1.232 1.188 0.9197258 G

Glyphyalinia indentata (Say, 1823) 2.732 3.250 0.4543545 D

Haplotrema concavum (Say, 1821) 0.411 0.000 0.0054455 G

Hawaiia n. sp. 2.571 1.750 0.1616094 T

Helicodiscus inermis H. B. Baker, 1929 0.679 1.812 0.0089186 –

Helicodiscus parallelus (Say, 1817) 5.393 6.438 0.2831711 G

Helicodiscus shimeki Hubricht, 1962 0.286 0.000 0.0204383 D

Helicodiscus singleyanus (Pilsbry, 1890) 0.375 1.125 0.0247064 G

Hendersonia occulta (Say, 1831) 0.036 0.062 0.7606162 D

Mesodon clausus clausus (Say, 1821) 0.054 0.000 0.3154693 D

Oxyloma peoriensis (Wolf in Walker, 1892) 0.125 0.000 0.1251903 –

Pupoides albilabris (C. B. Adams, 1821) 8.393 7.062 0.2324971 T

Stenotrema barbatum (Clapp, 1904) 0.107 0.000 0.1557229 D

Stenotrema fraternum fraternum (Say, 1824) 0.054 0.062 0.9262276 D

Succinea indiana Pilsbry, 1905 0.000 0.188 0.0277912 –

Succinea ovalis Say, 1817 0.143 0.188 0.7834904 D

Triodopsis alleni (Wetherby in Sampson, 1883) 0.071 0.000 0.2464148 D

Vallonia gracilicosta Reinhardt, 1883 11.500 11.062 0.7459095 D

Vertigo arthuri (von Martens, 1884) 0.643 0.000 0.0005065 –

Vertigo gouldi (A. Binney, 1843) 0.018 0.000 0.5622176 D

Vertigo nylanderi Sterki, 1909 0.036 0.000 0.4124393 T

Vertigo ovata Say, 1822 5.750 4.000 0.0472312 T

Vertigo tridentata Wolf, 1870 0.375 0.062 0.0738709 D

Zonitoides arboreus (Say, 1816) 4.143 4.625 0.5650976 D

Zonitoides nitidus (Müller, 1774) 0.464 0.000 0.0031253 T

Positive response

Gastrocopta corticaria (Say, 1816) 0.732 3.500 0.0000003 D

Strobilops labyrinthica (Say, 1817) 9.661 22.375 0.0000000 D

Vallonia costata (Müller, 1774) 1.804 6.438 0.0000000 G

Vallonia parvula Sterki, 1892 8.250 13.250 0.0001267 T

Vallonia perspectiva Sterki, 1892 2.143 5.625 0.0000055 D

Vertigo pygmaea (Draparnaud, 1801) 0.000 0.562 0.0001385 G

Tabla 2. (Cont.)


Fig. 2. Box–plot diagram of the response of species richness and abundance to management typeon all sampled sites.

Fig. 2. Diagrama de la respuesta en riqueza y abundancia de especies al tipo de actuacióndesarrollado en todas las áreas estudiadas.

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Unburned BurnedUnburned BurnedUnburned BurnedUnburned BurnedUnburned Burned Unburned Burned Unburned Burned Unburned Burned Unburned Burned Unburned BurnedManagement typeManagement typeManagement typeManagement typeManagement type Management type Management type Management type Management type Management type

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p = 0.001 p = 0.001 p = 0.001 p = 0.001 p = 0.001 p = 0.008 p = 0.008 p = 0.008 p = 0.008 p = 0.008

frequency. This null expectation was calculatedby assigning 88% of all encountered individualsto unburned sites, with the remaining 22% toburned sites. This procedure was necessary asthe number of unburned vs. burned sites wasnot balanced (88% vs. 22%). A two–tailedsignificance threshold was employed so thatspecies with positive and negative responses tofire could both be identified. As these analyseswere repeated for each species, a Bonferronicorrection was used to adjust the significancethreshold. Differences between fire responsesacross the three general ecological preferencetypes were documented via a contingency table,with significance being estimated using bothlog–linear modelling and Fisher’s Exact test.

Results

These grassland habitats were generally foundto support a diverse and abundant land snailfauna. A total of 91,074 individuals in 72 differentspecies were recovered from the 72 surveyedsites (tables 1, 2). The number of species pereach 4 l litter sample ranged from two (Chicoggravel prairie) to 24 (Twin Pines Farm sandstoneglade). Average richness ranged from roughly 15in upland sites, to 17 in lowland. Snail abundanceper site ranged from 6 (Point Beach State Forestdunes) to 5,001 (Ogema West fen). Averageabundance ranged from roughly 500 in uplandsites to 2,000 in lowlands.

One–way ANOVA, using all sites, demonstratedthat both species richness (p = 0.001) andabundance (p = 0.008) were significantly loweron sites that had experienced fire management(fig. 2). Median species richness was approximately18 on unburned vs. 12 on burned sites. Likewise,median shell abundance was 1,000 on unburnedvs. 300 on burned sites.

Full 2–way ANOVA, using all sites andconsidering both management type and habitattype (upland vs. lowland) as independentvariables, demonstrated a highly significant(p = 0.002) reduction (approximately 30%) inspecies richness in both upland and lowland sites(fig. 3). Habitat type and the interaction betweenhabitat and fire history were not significantpredictors (p = 0.209 and p = 0.628, respectively).Likewise, a significant (p = 0.010) reduction inshell abundance (50–70%) was noted on burnedsites (fig. 3). In this case, however, habitat typewas a more significant (p < 0.0005) predictor,with lowlands having 4–10 times the number ofshells as uplands. Additionally, a marginallysignificant (p = 0.088) interaction betweenmanagement and habitat was observed, withthe reduction appearing to be roughly 50%greater in lowlands.

Two–way ANOVA restricted to the 26 pairedsites (fig. 4) demonstrated that even afterblocking of variation due to site pair identity, asignificant reduction in richness (p < 0.0005) andabundance (p = 0.015) still occurred on fire–managed sites.

62 Nekola

Fig. 3. Box–plot diagram of the response of species richness and abundance to management andhabitat type on all sampled sites.

Fig. 3. Diagrama de la respuesta en riqueza y abundancia de especies al tipo de actuacióndesarrollado y el hábitat en todas las áreas estudiadas.

Comparison of dominance–diversity diagramsfor these sites (fig. 5) demonstrates that bothburned upland and lowland sites have truncatedcurves, with the rarest 40–50% of species beingmuch less common as compared to unburnedsites. However, the more common species appearto have largely similar dominance–diversitydiagrams.

Contingency table analysis of individual speciesresponses to fire (table 2) indicate that 32 (44%)experience a significant reduction in abundanceon fire–managed sites, even following use of aBonferroni–corrected two–tailed significancethreshold (p = 0.000347). Only six species (8%)demonstrated positive responses to fire, whilethe remaining 34 (47%) demonstrated no

ANOVANOVANOVANOVANOVA results: fire p = 0.002A results: fire p = 0.002A results: fire p = 0.002A results: fire p = 0.002A results: fire p = 0.002habitat p = 0.209habitat p = 0.209habitat p = 0.209habitat p = 0.209habitat p = 0.209interaction p = 0.628interaction p = 0.628interaction p = 0.628interaction p = 0.628interaction p = 0.628

ANOVANOVANOVANOVANOVA results:A results:A results:A results:A results: fire p = 0.010fire p = 0.010fire p = 0.010fire p = 0.010fire p = 0.010habitat p < 0.0006habitat p < 0.0006habitat p < 0.0006habitat p < 0.0006habitat p < 0.0006interaction p = 0.088interaction p = 0.088interaction p = 0.088interaction p = 0.088interaction p = 0.088

Lowland sites Lowland sites Lowland sites Lowland sites Lowland sites Upland sites Upland sites Upland sites Upland sites Upland sites

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Unburned Burned Unburned Burned Unburned Burned Unburned Burned Unburned Burned Unburned Burned Unburned Burned Unburned Burned Unburned Burned Unburned Burned Management type Management type Management type Management type Management type Management type Management type Management type Management type Management type


Fig. 4. Box–plot diagram of the response of species richness and abundance to management on26 sites paired by habitat type and geographic location.

Fig. 4. Diagrama de la respuesta en riqueza y abundancia de especies a la actuación desarrolladaen 26 áreas emparejadas según el tipo de hábitat y localización geográfica.

Fig. 5. Dominance–diversity curve for upland/lowland sites which have been burned/unburned.

Fig. 5. Curva de la dominancia–diversidad para las mesetas/llanuras que hayan sido quemadas/no quemadas.

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Unburned Burned Unburned Burned Unburned Burned Unburned Burned Unburned Burned UnburnedUnburnedUnburnedUnburnedUnburned BurnedBurnedBurnedBurnedBurned Management type Management type Management type Management type Management type Management typeManagement typeManagement typeManagement typeManagement type

ANOVANOVANOVANOVANOVA results:A results:A results:A results:A results: ANOV ANOV ANOV ANOV ANOVA results:A results:A results:A results:A results:Pairs p = 0.001Pairs p = 0.001Pairs p = 0.001Pairs p = 0.001Pairs p = 0.001 Pairs p = 0.009 Pairs p = 0.009 Pairs p = 0.009 Pairs p = 0.009 Pairs p = 0.009Fire p < 0.0005Fire p < 0.0005Fire p < 0.0005Fire p < 0.0005Fire p < 0.0005 Fire p = 0.015 Fire p = 0.015 Fire p = 0.015 Fire p = 0.015 Fire p = 0.015

Lowland sites Lowland sites Lowland sites Lowland sites Lowland sites Upland sites Upland sites Upland sites Upland sites Upland sites–1–1–1–1–1

–4–4–4–4–4

–7–7–7–7–7

–10–10–10–10–10 0 0 0 0 0 10 10 10 10 10 20 20 20 20 20 30 30 30 30 30 40 40 40 40 40 50 50 50 50 50 60 60 60 60 60 0 0 0 0 0 10 20 30 10 20 30 10 20 30 10 20 30 10 20 30 40 40 40 40 40 50 50 50 50 50 60 60 60 60 60

Rank order Rank order Rank order Rank order Rank order Rank orderRank orderRank orderRank orderRank order BurnedBurnedBurnedBurnedBurned Unburned Unburned Unburned Unburned Unburned

ln (

% f

recu

en

cy)

ln (

% f

recu

en

cy)

ln (

% f

recu

en

cy)

ln (

% f

recu

en

cy)

ln (

% f

recu

en

cy)

64 Nekola

significant changes in population size. Contingencytable analysis of ecological preference vs. fireresponse indicated that fully 72% of turf–specialists were negatively impacted by fire(table 3). However, only 22% of duff–specialistsexhibited negative responses. While 67% of duff–specialists demonstrated no significant responseto fire only 24% of turf–specialists wereunaffected. Generalist species demonstrated littlediscernable trend to fire, with seven decreasing,two increasing, and five with no response. Log–likelihood ratio and Fisher’s Exact tests bothindicated these differences as being highlysignificant (p = 0.0006 and p = 0.004, respectively).

Discussion

These data clearly indicate that fire managementcauses significant reductions in land snailcommunity richness and abundance in bothupland and lowland grasslands throughout asignificant section of the tallgrass prairie biomein central North America. At a species–level, firemost strongly impacts the rarest species, andcauses significant population reductions in 44%of the 72 encountered taxa. These negativeimpacts were most strongly felt in turf–specialists,where almost 75% experienced significantreductions. Thus, statements regarding thebenign nature of fire on snail populations (FREST

& JOHANNES, 1995), and the beneficial impact offire on North American grassland faunas (THELER,1997) can be proven false. Rather, frequent useof fire management appears to represent asignificant threat to the health and diversity ofNorth American grassland land snails.

It is not possible through these analyses todefinitively identify the factors that directly leadto these impacts. However, at least part of theanswer must lay in grassland detritusphereremoval. This will lead to direct mortality, as thegreat majority of land snails are limited to thislayer (HAWKINS et al., 1998). As land snailabundance (BERRY, 1973), diversity (CAIN, 1983;LOCASCIULLI & BOAG, 1987), and composition(CAMERON & MORGAN–HUWS, 1975; BAUER et al.,1996; BARKER & MAYHILL, 1999) is often positivelycorrelated with litter depth, detritusphere removalwould be expected to have a strong negativeimpact on land snail community structure.

Redevelopment of an equilibrium thickness oforganic detritus takes at least five years insouthern Plains grasslands (KUCERA & KOELLING,1964), with even longer intervals being requiredin more northern locations (HILL & PLATT, 1975).The optimal interval between fires for land snailsmight be even longer, depending upon the timerequired for more refractory plant debris (such aslignified grass stems) to break down, allowing acomplete suite of decompositional microhabitatsto develop. Litter architecture is known to effectsnail community composition in forests of Virginia

(BURCH, 1956), British Columbia (CAMERON, 1986),and Puerto Rico (ÁLVAREZ & WILLIG, 1993) andgrasslands of England (YOUNG & EVANS, 1991). Itshould thus not be surprising that in the currentdata set, sites burned up to 15 years ago havemaintained lowered land snail richness andabundance as compared to unburned sites.

As grassland land snails presumably evolved inconjunction with natural fire regimes, it is alsointriguing to note that turf–specialists experiencedthe most severe negative impacts to fire. If firewas a common process structuring central NorthAmerican grasslands, evolution should have selectedfor individuals that were more tolerant of, orfavored by, this disturbance. Like other nativegrassland invertebrate groups (SWENGEL, 1996;HARPER et al., 2000), land snails in the presettlementlandscape may have been able to tolerate fires bybeing able to easily recolonize from source poolsin adjacent unburned areas. Even when suchadjacent source pools are present, recolonizationmay take over a dozen years (MÄND et al., 2001). Inmodern landscapes, where grasslands are highlyfragmented and surrounded by agricultural, urban,or forest habitats, such recolonization has becomemuch more difficult. Thus, turf–specialist taxa maycontinue to decrease in burned grasslands due to alack of recolonization sources, while generalistand duff-specialist woodland taxa, which are morecommon in the surrounding landscape, may beable to maintain their populations through masseffect (SHMIDA & ELLNER, 1984).

The depression of land snail richness andabundance following fire episodes, the lengthof time required to redevelop a maturedetritusphere, and the greater sensitivity of turf–specialist taxa to fire casts doubt on the wide–

Table 3. Contingency table analysis of fireresponse vs. general ecological preferences.Log–likelihood ratio p = 0.000634; Fisher’sExact Test p = 0.004 (Ecological preferences:T. Turf; D. Duff; G. Generalist.)

Tabla 3. Análisis de la tabla de contingenciade la respuesta al fuego frente a laspreferencias ecológicas generales. Logaritmode la razón de verosimilitudes p = 0,000634;Test exacto de Fisher p = 0,004 (Preferenciasecológicas: T. Sustrato herbáceo; D. Sustratohúmico; G. Generalista.)

Ecological preferences

Fire response T D G

Negative 18 6 7

None 6 18 5

Positive 1 3 2


held belief (e.g., PAULY, 1985) that North Americangrasslands should be burned at 2–6 year intervals.Rather, these data support the contention thatpresettlement return intervals ranged between20–30 years (SIMS, 1988). These data also stronglysuggest that other factors, such as large herbivoregrazing (COLLINS et al., 1998) and periodic drought(BORCHERT, 1950), may have also played essentialroles in keeping prairies treeless, as theseprocesses do not lead to the wholesaledetritusphere removal.

Protecting the health of North Americangrassland land snail populations will require thepreservation of mulch layers on sites. Such effortswill also help protect a large percentage of theentire grassland soil biota. The detritusphere canonly be protected if more realistic fire returnintervals (20–30 years) are adopted by conservationagencies, and used in conjunction with morediversified approaches towards woody andinvasive plant removal. Activities like grazing,haying, and hand cutting/pulling will not causewidespread removal of the detritusphere, andshould thus be more compatible with land snail(and soil biodiversity) conservation.

Acknowledgements

Alyssa Barnes, Tracy Kuklinski, J. J. Schiefelbeinand Angela Sette helped processed many soillitter samples, and assisted in shell counting.Additional assistance in litter processing was alsoprovided by students of the Land Snail EcologyPracticum at the University of Wisconsin – GreenBay. Funding was provided by the MinnesotaNongame Wildlife Tax Checkoff and MinnesotaState Park Nature Store Sales through theMinnesota Department of Natural ResourcesNatural Heritage and Nongame Research Program.

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Ranius, T. & Douwes, P., 2002. Genetic structure of two pseudoscorpion species living in tree hollows inSweden. Animal Biodiversity and Conservation, 25.2: 67–74.

AbstractAbstractAbstractAbstractAbstractGenetic structure of two pseudoscorpion species living in tree hollows in Sweden.— Two saproxylic pseudoscorpions,Larca lata and Allochernes wideri, were compared in an analysis of genetic structure in southern Sweden. Allocherneswideri is a relatively widely distributed species that occurs in single–standing trees and in small tree hollows, while L. latais on the Swedish red list and confined to larger assemblages of very old trees with hollows containing large amountsof wood mould. In A. wideri, the polymorphism of PGM was used, whereas in L. lata the variation for PGI was studied.The genetic differentiation between trees within a site was low for both species, indicating that the migration betweennearby trees is considerable despite the fact that phoretic dispersal has only been occasionally observed in these species.Between sites, situated four to 900 km from each other, the genetic differentiation was small both in A. wideri and L.lata with no difference between the species, when considered on the mainland only. The small differentiation suggeststhe habitat was fragmented recently (100–170 years ago). The relation between the rate of migration and long–termpopulation survival and the risk of mis–interpretation due to selection for alleles is discussed.

Key words: Allochernes wideri, Allozymes, Dispersal, Habitat fragmentation, Larca lata, Phoresy.

ResumenResumenResumenResumenResumenEstructura genética de dos especies de pseudoescorpión que viven en los huecos de árboles en Suecia.— Se comparandos pseudoescorpiones saproxílicos, Larca lata y Allochernes wideri, del sur de Suecia mediante un análisis de suestructura genética. Allochernes wideri es una especie de distribución relativamente amplia que se encuentra en árbolesaislados y en pequeños huecos de árboles, mientras que L. lata aparece en la lista roja sueca y se encuentra confinadoen grandes agrupaciones de árboles muy viejos cuyos huecos contienen gran cantidad de moho. En A. wideri se empleóel polimorfismo de PGM mientras que en L. lata se estudió la variación por PGI. La diferenciación genética entre árbolesde un mismo lugar fue baja para ambas especies, indicando que la migración entre árboles cercanos es considerableaun cuando sólo se observó dispersión forética ocasionalmente en ambas especies. Entre zonas situadas a una distanciade 4 a 900 km, la diferenciación genética fue escasa en ambas especies, A. wideri y L. Lata, sin ninguna diferencia entrelas mismas cuando se consideró únicamente la zona principal. Esta pequeña diferenciación sugiere que el hábitat sefragmentó recientemente (100–700 años antes). Se discute la relación entre la tasa de migración y la supervivencia dela población a largo plazo y el riesgo de una mala interpretación debida a la selección de los alelos.

Palabras clave: Allochernes wideri, Aloenzimas, Dispersión, Fragmentación del hábitat, Larca lata, Foresis.

(Received: 4 IV 02; Conditional acceptance: 6 VI 02; Final acceptance: 26 VII 02)

Thomas Ranius & Per Douwes, Lund Univ., Dept. of Zoology, Helgonav. 3, SE–223 62 Lund, Sweden.

* New address for corresponding author: Thomas Ranius, Swedish Univ. of Agricultural Sciences, Dept. ofEntomology, P. O. Box 7044, SE–750 07 Uppsala, Sweden.


Genetic structure oftwo pseudoscorpion species living intree hollows in Sweden

T. Ranius* & P. Douwes

68 Ranius & Douwes

Introduction

Most species are associated with a habitat that ismore or less patchy, resulting in a populationstructure with areas of high abundances separatedby areas in which the species is rare or absent. Inthe last few centuries, human activities havecaused many habitats to become subdivided intopatches which are much smaller and more isolatedthan in the primaeval landscape (e.g. ANGELSTAM,1992; HARRISON & FAHRIG, 1995). Especially forthose species that have evolved in a spatiallymore continuous habitat, fragmentation intosmaller, isolated populations may increasesusceptibility to extinction both for genetic anddemographic reasons (NILSSON & ERICSON, 1997).

Genetic differentiation measurements mightprovide an understanding of the populationstructure and migration, which are important inconservation work (STACEY et al., 1997). The impactof decreased habitat patch size and increasedisolation on population genetics have, amonginvertebrates, mainly been studies on butterfliesand moths (e.g. VAN DONGEN et al., 1998; HOOLE etal., 1999; MEGLÉCZ et al., 1999; CLARKE & O’DWYER,2000; FIGURNY–PUCHALSKA et al., 2000), while othertaxa have been less studied (see however VOGLER

et al., 1993; KNUTSEN et al., 2000; JONSSON, 2002 onbeetles).

The present study considers the geneticdifferentiation in two pseudoscorpion species thatare associated with tree hollows. One of thespecies, Larca lata H. J. Hansen (Pseudoscorpionida,Larcidae), is only found in larger assemblages ofancient, hollow oaks, whereas the other,Allochernes wideri C. L. Koch (Pseudoscorpionida,Chernetidae), has a broader habitat and occurs atmore localities (RANIUS & WILANDER, 2000). Oldoaks occur mainly in old–growth deciduous forestsand pasture woodlands, and in Europe both thesehabitats have decreased severely in the last fewcenturies (HANNAH et al., 1995; KIRBY & WATKINS,1998). In Sweden, the major decrease of old oaksoccurred 100–170 years ago (ELIASSON & NILSSON,1999). A rare and endangered saproxylic fauna,mainly consisting of beetles, flies and pseudo-scorpions, is associated with tree hollows (SPEIGHT,1989). It seems that only one genetic study on arare saproxylic invertebrate has been performed(JONSSON, 2002) and that was not on a speciesassociated with tree hollows. Tree hollows areexpected to be a stable habitat, with narrowfluctuations in microclimate and nutrient supply.In a living hollow tree, partly decomposed woodinside the trunk is surrounded by growing soundwood, resulting in a continuous nutrient supplyfor the saproxylic fauna. The daily microclimatefluctuation is much smaller in a trunk hollowthan at the surface of the trunk (KELNER–PILLAULT,1974; PARK & AUERBACH, 1954). This might causeinhabiting species to have narrow populationfluctuations, which decrease their extinction ratein comparison with other invertebrate populations

of the same size (RANIUS, 2001). Therefore it ispossible that these species have relictualdistributions, with small, isolated populationssurviving in small remnants over long periodsafter the habitat density has become too low toallow long–term metapopulation persistence(RANIUS, 2000).

Many pseudoscorpion species dispersephoretically, which means that they hitch–hikewith other animals, usually insects. There iscircumstantial evidence that both L. lata and A.wideri perform phoretic dispersal, but it is notknown how frequent this behaviour is (RANIUS &WILANDER, 2000). As L. lata is confined to largerassemblages of hollow trees, whereas A. widerioccurs also in single trees far from other hollowtrees, it has been suggested that L. lata has amore restricted colonization ability (RANIUS &WILANDER, 2000).

In this study, the degree of genetic differentia-tion was examined in order to estimate the extentof genetic drift and migration. Being the lessabundant species and inhabiting a narrowecological range L. lata was expected to havelower population sizes within a given area andlower frequency of migration, which would giverise to higher levels of genetic differentiationthan for A. wideri.


Sampling

Sampling was designed to determine the degree ofgenetic differentiation at two geographic levels: 1.Samples were taken from trees situated 100–700 mfrom each other in Bjärka–Säby (fig. 1). About30 individuals of A. wideri were then sampled fromeach of three trees and individulas of L. lata fromfour trees. 2. Samples were taken from sites situatedfour to 900 km apart, all within southern Sweden(fig. 1). Allochernes wideri was sampled from ten,and L. lata from six sites (table 1 and 2). A totalsample of about 30 individuals of each species wastaken from one to five hollow trees at each site,except at Bjärka–Säby where larger samples weretaken as all those at the tree level were pooledwhen used as a sample at the site level.

The sampling was carried out from 1995 to1999. It was performed by sieving wood mould,and in the field the fine fraction was spread outon a white sheet where the pseudoscorpionswere searched for. The pseudoscorpions werestored alive before transfer to a freezer.Electrophoresis was performed within two yearsof sample collecting.

Electrophoresis

Horizontal starch–gel electrophoresis was used toinvestigate allozyme variation. The electrophoresistechnique used has been described by SELANDER et


al. (1971). The loci of six enzymes were screened:(ME (malic enzyme), �–GPD (�–glucosephosphatedehydrogenase), MDH (malate dehydrogenase), PGI(phosphoglucose isomerase), PGM (phosphogluco-mutase) and IDH (isocitrate dehydrogenase) inspecimens from Bjärka–Säby of both species. ME,�–GPD and MDH had scorable activity in none oronly a few individuals, and no variation wasobserved among scorable individuals. Therefore,these loci were not further used in this study. PGI,PGM and IDH had scorable activity in all individualsand were thus assessed in all samples. Sufficientmaterial was normally obtained from eachindividual to load two starch gels, but some smallnymphs did not give any visible bands. To controlfor possible between–gel artefacts, specimens fromat least two sites were run in each gel.

Statistical analyses

The statistical package POPGEN vers. 1.31 (by F.Yeh, R. Yang & T. Boyle) was used to calculateallele frequencies, expected and observed

heterozygosity and F–statistics.Patterns of genetic structure were revealed

through the analysis of allele frequencies usingF–statistics (HEDRICK, 1983). The most commonlyused statistic, Fst, is a measure of the extent towhich subpopulations show spatial geneticheterogeneity. Fst values range from 0, suggestinglack of differentiation or panmixia, to 1,indicating fixation of alternate alleles andcomplete differentiation. Chi–square was usedto test the significance of the allele frequencydifferences among populations:

�2 = 2NFst(k – 1) d.f. = (k – 1)(s – 1)

(BAKER, 1981; BILTON, 1992). N is the total numberof individuals, k is the number of alleles for thelocus and s is the number of subpopulations. Thegene flow between trees within a site wasestimated from F–statistics (HEDRICK, 1983):

Fst = 1 / (4Nm + 1)

where Nm is the average number of migrants

Fig. 1. Sampling sites in Sweden: � Sites where A. wideri samples have been taken; � Siteswhere L. lata samples have been taken; �� Sites where both A. wideri and L. lata samples havebeen taken. Localities: 1. Strömsholm; 2. Kinnekulle; 3. Långvassudde; 4. Bjärka–Säby; 5. Grebo;6. Tjärstad; 7. Kättilstad; 8. Djursö; 9. Sankt Anna; 10. Strömserum; 11. Halltorp; 12. HallandsVäderö; 13. Yddingen.

Fig. 1. Áreas de estudio de Suecia: � Áreas donde se tomaron muestras de A. wideri; � Áreasdonde se tomaron muestras de L. lata; � Áreas donde se recogieron muestras de ambas A. wideriy L. lata. Localidades: 1. Strömsholm; 2. Kinnekulle; 3. Långvassudde; 4. Bjärka–Säby; 5. Grebo;6. Tjärstad; 7. Kättilstad; 8. Djursö; 9. Sankt Anna; 10. Strömserum; 11. Halltorp; 12. HallandsVäderö; 13. Yddingen.

Northern EuropeNorthern EuropeNorthern EuropeNorthern EuropeNorthern Europe

1212121212

1313131313

22222

11111

3333344444 5555566666 77777

8888899999

1010101010

1111111111

70 Ranius & Douwes

between subpopulations per generation. This geneflow estimate is developed from an island modelof population structure, with every subpopulationinhabiting an island equally accessible from everyother, with a balance between genetic drift andmigration. Although few populations actuallyconform to the assumption of this model it isuseful as an approximation of the magnitude ofgene flow, as dispersal has a strong correlationwith the genetic structure in most populations(BOHONAK, 1999). The gene flow was not calculatedat the site level, as the effects of genetic drift andmigration were not considered to be in equilibriumthere.

The genetic distance D (NEI, 1972) was calculatedin both species at the site level for each pair ofpopulations. The coefficient of correlationbetween D and the geographical distance was

calculated, and the statistical significance of thecorrelation was tested with a one–tailed Manteltest with 200 randomized values calculated (SOKAL

& ROHLF, 1995).

Results

In A. wideri only PGM was polymorphic, while inL. lata variation both in PGM and PGI was found.However, in L. lata the heterozygotes of PGMdid not segregate properly and it was thereforeimpossible to score the genotypes unambiguously.It was therefore decided to omit this locus fromfurther analysis. IDH was monomorphic through-out in both species and PGI was monomorphic inA. wideri.

At the PGM locus (A. wideri) four alleles were

Table 1. Allele frequencies at the PGM locus in populations of Allochernes wideri: Samplesize. Number of individuals in the sample; Stand size. Roughly estimated number of hollowtrees with wood mould; He Expected heterozygosity; Ho Observed heterozygosity; Frequencyof alleles (Z. Very slow, S. Slow, M. Medium, F. Fast).

Tabla 1. Frecuencia de alelos en el locus PGM en una población de Allochernes wideri: Samplesize. Número de individuos de la muestra; Stand size. Número estimado aproximado de huecosde árboles con moho de madera; He Heterocigosis esperada; Ho Heterocigosis observada;Frequencia de alelos (Z. Muy baja, S. Baja, M. Media, F. Alta).

A. Sites in southern Sweden situated 4–500 km from each other Frequency of alleles

Locality Sample size Stand size He Ho Z S M F

Strömsholm 26 100–200 0.50 0.58 0.00 0.56 0.44 0.00

Kinnekulle 27 50 0.48 0.48 0.00 0.33 0.65 0.02

Långvassudde 38 100–200 0.55 0.58 0.00 0.41 0.54 0.05

Bjärka–Säby 90 200 0.53 0.50 0.01 0.46 0.52 0.02

Tjärstad 29 1 0.61 0.52 0.03 0.19 0.57 0.21

Kättilstad 31 20 0.49 0.48 0.00 0.37 0.61 0.02

Sankt Anna 31 20–50 0.55 0.55 0.00 0.26 0.61 0.13

Strömserum 29 50–200 0.67 0.52 0.03 0.19 0.45 0.33

Halltorp 21 20 0.61 0.57 0.02 0.29 0.55 0.14

Yddingen 30 10–30 0.53 0.43 0.02 0.27 0.63 0.08

B. Trees within the Bjärka–Säby site, situated 100–300 m from each other

38 0.52 0.45 0.00 0.40 0.58 0.03

27 0.52 0.56 0.02 0.41 0.57 0.00

25 0.51 0.52 0.02 0.60 0.36 0.02


found, one of which (Z) occurred in very lowfrequencies (< 5%, table 1). The three alleles atthe PGI locus (L. lata) appeared in almost allsamples except the rather frequent M allele,which was not found at Hallands Väderö (table 2).

The Ho did not deviate from Hardy–Weinbergequilibrium (table 2) when it was tested by �2 foreach population (p > 0.05). This suggests thatthe samples were taken from fairly panmicticpopulations. The genetic differentiation betweenthe populations (Fst) at sites was low in A. wideriand moderate in L. lata (table 3). However,without the Hallands Väderö population, the Fstin L. lata was considerably lower (Fst = 0.0241),yet still significantly above zero. The geneticdifferentiation between trees was low butsignificant in A. wideri, whereas in L. lata Fst didnot deviate significantly from zero (table 3).

In A. wideri, there was no significantcorrelation between Nei’s genetic distance Dand the geographic distance between sites(r = 0.03), as 19.5% of the correlation coefficients

Table 2. Allele frequencies at the PGI locus in populations of Larca lata: Sample size. Numberof individuals in the sample; Stand size. Roughly estimated number of hollow trees with woodmould; He Expected heterozygosity; Ho Observed heterozygosity; Frequency of alleles (S. Slow,M. Medium, F. Fast).

Tabla 2. Frecuencia de alelos en el locus PGI de una población de Larca lata: Sample size. Númerode individuis de la muestra; Stand size. Número estimado aproximado de huecos de árboles conmoho de madera; He Heterocigosis esperada; Ho Heterocigosis observada; Frequencia de alelos (S.Baja, M. Media, F. Alta).

A. Sites in Sweden, situated 7–500 km from each other Frequency of alleles

Locality Sample size Stand size He Ho S M F

Strömsholm 44 100–200 0.57 0.68 0.55 0.35 0.10

Bjärka–Säby 129 200 0.60 0.61 0.37 0.50 0.13

Grebo 49 130 0.62 0.57 0.52 0.28 0.20

Djursö 38 80 0.59 0.58 0.50 0.40 0.10

Strömserum 29 50–200 0.52 0.55 0.60 0.35 0.05

Hallands Väderö 27 50–100 0.33 0.19 0.80 0.00 0.20

B. Trees within the Bjärka–Säby site, 100–700 m from each other

36 0.48 0.50 0.39 0.61 0.00

30 0.65 0.77 0.35 0.43 0.22

30 0.60 0.57 0.38 0.50 0.12

33 0.64 0.63 0.35 0.45 0.20

Table 3. Fst for four separate sets ofsamples: G. Geographic level; Np. Numberof populations; Na. Number of alleles; ns.Not significant; ** p < 0.01; *** p < 0.001.

Tabla 3. Fst para cuatro grupos de muestrasseparadas: G. Nivel geográfico; Np.Número de poblaciones; Na. Número dealelos; ns. No significativo; ** p < 0,01;*** p < 0,001.

Species G Np Na Fst

A. wideri Trees 3 4 0.0369**

Sites 10 4 0.0481***

L. lata Trees 4 3 0.0206 ns

Sites 6 3 0.0761***

72 Ranius & Douwes

resulting from the Mantel test randomizationswere higher than the observed correlationcoefficient. In L. lata, the correlation betweenNei’s genetic distance D and the geographicaldistance between sites was positive (r = 0.49) andstatistically significant (3.5% of the correlationcoefficients resulting from the Mantel testrandomizations were higher than the observedcorrelation coefficients). The signficant relationarose because Hallands Väderö was geographicallythe most isolated site, and its population was thegenetically most deviant. Without Hallands Väderö,no significant relation was found (r = – 0.48, 92.5%of the correlation coefficients from the Mantelrandomizations were higher than the observedcorrelation coefficient.

The gene flow between trees in Bjärka–Säbywas estimated from F–statistics (HEDRICK, 1983):

Fst = 1 / (4Nm + 1)

Nm (the average number of migrants betweentrees per generation) was estimated to sevenindividuals for A. wideri and twelve for L. lata.

Discussion

The small genetic differentiation between siteswas not unexpected as until 150–200 years ago,old hollow oaks were a widespread habitat,probably occurring contiguously over large areasof southern Sweden (ELIASSON & NILSSON, 1999).The generation time of the study species isunknown, but for other pseudoscorpion speciesthe life time is 2–5 years (WEYGOLDT, 1969;GÄRDENFORS & WILANDER, 1992). Thus, the reductionin connectivity and population sizes should notyet be fully manifested in the genetic variationbetween sites, as fragmentation of the habitathas occurred within the last 100 generations ofthe pseudoscorpions and the population size persite may be relatively large. Many threatenedinvertebrates would be expected to show patternssimilar to L. lata in this respect; they suffer fromhabitat fragmentation and become extinct fromsmall sites (RANIUS & WILANDER, 2000). However,because the local populations are often stillrelatively large it is difficult to detect geneticeffects of fragmentation before the populationhas disappeared for other reasons.

In L. lata, the genetic differentiation was largerthan in A. wideri only when the Hallands Väderöpopulation was included in the analysis. Also thecorrelation between genetic and geographicdistances between sites was dependent on thatthe Hallands Väderö population was included.This indicates that in L. lata the gene flow betweenHallands Väderö, which is on an island, and themainland might have been low or absent over alonger period than between the mainlandpopulations. Thus, the larger differentiationbetween all sites in L. lata compared to A. wideri

does not suggest any difference in the migrationrate between mainland populations.

Within the Bjärka–Säby site, the conditions wouldnot be expected to have changed much over thepast 150 years. Under the assumption that there isno selection that affects gene frequencies, theobserved genetic variation between trees shouldtherefore reflect the ongoing genetic drift, migrationand extinction–colonization process. The extinction–recolonization turnover, which might take place inhollow trees within a stand, results in imprecisecorrelations between Fst and Nm, and most casesyielding too low estimates of Nm (WADE & MCCAULEY,1988). In spite of this, the estimated migration ratewas fairly high both in L. lata and A. wideri (12 and7 tree-1 year-1, respectively). From observations inthe field the population size was estimated asbeing five to 500 individuals per tree, and the meanmight be 50 individuals per occupied tree for bothspecies (calculated from the field data set used inRANIUS & WILANDER, 2000). The relatively frequentmigrations that seem to occur in both species arealmost certainly performed by phoresy, even thoughit has infrequently been observed for these species.As there is a positive relation between occupancyper tree and stand size in L. lata, it has beenhypothesized that the L. lata populations in standsconform to metapopulations, with each tree possiblysustaining a local population (RANIUS & WILANDER,2000). The results from the present study suggestthat the migration rate might be too high formetapopulation dynamics to be important at thisscale, but as the estimates are very rough thishypothesis can not be rejected.

The underlying assumption of the Fst calculationis that there is no selection for any alleles. Ifselection maintains different alleles in highfrequencies in different local populations, the Fstestimation indicates little or no gene flow even ifit is actually large. Selection for heterozygosity,however, may generate similar gene frequenciesfor many local poulations and the Fst calculationthen suggests a gene flow larger than reality. Theloci used in this study are for two metabolicallyadjacent enzymes, PGI (phosphoglucose isomerase)and PGM (phosphoglocosemutase). Both these locihave been found to experience natural selection instudies on butterflies (PGM: GOULSON, 1993; PGI:CARTER & WATT, 1988, indications of selection inboth: CARTER et al., 1989). Also in a beetle,Chrysomela aenicollis, natural selection probablyacts on PGI (RANK, 1992). A further genetic studybased on a larger number of loci would thereforebe interesting to control possible effects ofselection, chance or history which may act onindividual alleles in the pseudoscorpion species.

Acknowledgements

We thank Mattias Jonsson and Sven G. Nilssonfor their valuable comments on the manuscriptand Per Wilander for help with the species


identification. This study was financially supportedby Larsénska fonden, Kungliga FysiografiskaSällskapet i Lund and Hierta–Retzius stipendiefond(Kungliga Vetenskapsakademien).

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Sanmartín, I. & Ronquist, F., 2002. New solutions to old problems: widespread taxa, redundant distributions andmissing areas in event–based biogeography. Animal Biodiversity and Conservation, 25.2: 75–93.

AbstractAbstractAbstractAbstractAbstractNew solutions to old problems: widespread taxa, redundant distributions and missing areas in event–basedbiogeography.— Area cladograms are widely used in historical biogeography to summarize area relationships.Constructing such cladograms is complicated by the existence of widespread taxa (terminal taxa distributed inmore than one area), redundant distributions (areas harboring more than one taxon) and missing areas (areasof interest absent from some of the compared cladograms). These problems have traditionally been dealt withusing Assumptions 0, 1, and 2, but the assumptions are inapplicable to event–based methods of biogeographicanalysis because they do not specify the costs of alternative solutions and may result in non–overlappingsolution sets. The present paper presents the argument that only widespread terminals pose a problem toevent–based methods, and three possible solutions are described. Under the recent option, the widespreaddistribution is assumed to be the result of recent dispersal. The ancient option assumes that the widespreaddistribution is the result of a failure to vicariate, and explains any mismatch between the distribution and thearea cladogram by extinction. The free option treats the widespread taxon as an unresolved higher taxonconsisting of one lineage occurring in each area, and permits any combination of events and any resolution ofthe terminal polytomy in explaining the widespread distribution. Algorithms implementing these options aredescribed and applied to Rosen (1978)’s classical data set on Heterandria and Xiphophorus.

Key words::::: Historical biogeography, Widespread taxa, Missing areas, Redundant distributions, Assumptions 0,1, and 2.

ResumenResumenResumenResumenResumenNuevas soluciones a viejos problemas: taxones de amplia distribución, distribuciones redundantes y áreasausentes en la biogeografía cladista de procesos.— El análisis biogeográfico cladista se basa en la comparaciónde cladogramas de áreas de organismos que habitan una misma región (sustituyendo el nombre de los taxonesen la filogenia por las áreas que éstos ocupan) para obtener un patrón común, el cladograma general de áreas.La construcción del cladograma de áreas se complica cuando existen taxones presentes en más de un área dedistribución (“taxones de amplia distribución”), áreas que albergan más de un taxón (“distribucionesredundantes”), o áreas que no están presentes en alguno de los grupos (“áreas ausentes”). En biogeografíacladista de procesos, los taxones de amplia distribución se resuelven aplicando las Asunciones: 0, 1, y 2, quedifieren en la relación cladogenética permitida entre las áreas donde se distribuye el taxon. Se proponen tresnuevas soluciones para abordar este problema dentro de un nuevo enfoque en biogeografía cladista queincorpora los procesos al análisis biogeográfico: “biogeografía cladista de procesos”. Estas opciones difieren nosólo en las relaciones entre las áreas implicadas sino también en los procesos biogeográficos que pudieron haberdado lugar a la distribución. La opción recent considera la amplia distribución como si fuera de origen recientey la explica por dispersión. La opción ancient considera que la amplia distribución es ancestral y la explicamediante vicarianza y extinción. La opción free considera la amplia distribución como un taxón de alto rangocon un linaje en cada una de las áreas implicadas y cuyas relaciones no han sido establecidas, permitiendocualquier combinación de procesos biogeográficos y cualquier solución de la politomía para explicar ladistribución. Se comparan estas opciones utilizando el famoso análisis de Rosen (1978) sobre Heterandria yXiphophorus. También se discute brevemente como tratar las distribuciones redundantes y las áreas ausentesdentro de este nuevo enfoque.

New solutions to old problems:widespread taxa, redundant distributionsand missing areasin event–based biogeography

I. Sanmartín* & F. Ronquist

76 Sanmartín & Ronquist

Palabras clave: Biogeografía histórica, Taxones de amplia distribución, Áreas ausentes, Distribuciones redundantes,Asunciónes 0, 1 y 2.

(Received: 11 I 02; Conditional acceptance: 25 IV 02; Final acceptance: 6 VI 02)

Isabel Sanmartín & Fredrik Ronquist, Dept. of Systematic Zoology, Evolutionary Biology Centre, Uppsala Univ.,Norbyvägen 18D, SE–752 36 Uppsala, Sweden.

* Corresponding author: Isabel Sanmartin, Dept. of Systematic Zoology, Evolutionary Biology Centre, UppsalaUniv., Norbyvägen 18D, SE–752 36 Uppsala, Sweden.



Introduction

Cladistic biogeography seeks to summarizeinformation on distribution and phylogeneticrelationships of organisms in area cladograms,branching diagrams that express the inter–relationships of areas based on their biotas(fig. 1a). The analysis usually starts with taxon–area cladograms (TAC) (ENGHOFF, 1993; MORRONE

& CRISCI, 1995), which are constructed by replacingthe terminal taxa in a phylogeny with the areasin which they occur. Comparing area cladogramsof different organisms that occur in the sameregion may reveal common biogeographicpatterns that can be represented in a generalarea cladogram (GAC).

If every terminal taxon is endemic to a uniquearea and every area harbors only one terminaltaxon, the TAC represents a valid hypothesisabout area relationships. However, the situationbecomes more complicated when the “one–area–one–taxon” assumption is violated, in which casethe TAC may be incomplete or indicate conflictingarea relationships. The sources of these problemsare often divided into three categories:widespread taxa (taxa present in more than onearea, fig. 1b), redundant distributions (areasharboring more than one taxon, fig. 1c), andmissing areas (areas of interest absent from someof the compared taxon–area cladograms, fig. 1d).The latter problem is only relevant when severalTACs are analyzed simultaneously.

Problematic TACs can be converted intoresolved area cladograms (RACs; that is, taxon–specific GACs), in which each area is representedby only one terminal (ENGHOFF, 1996), byapplying Assumptions 0, 1, and 2 (fig. 2). Theseassumptions mainly differ in their treatment ofwidespread taxa. Assumption 0 (A0, ZANDEE &ROOS, 1987) regards the widespread distributionas the result of a failure to speciate in responseto vicariance events affecting other lineages.The areas inhabited by the widespread taxonare considered to form a monophyletic clade(fig. 2: RAC1) and the widespread taxon is thustreated as a synapomorphy of the areas in whichit occurs. Assumption 1 (A1, NELSON & PLATNICK,1981) explains the widespread distribution asthe result of a failure to vicariate, possibly incombination with subsequent extinction. Theareas inhabited by the widespread taxon areconsidered to form a monophyletic or para-phyletic group of areas (fig. 2: RACs 1–3) andthe widespread taxon is treated as a symple-siomorphy of areas. Assumption 2 (A2, NELSON &PLATNICK, 1981), finally, allows failure to vicariate,extinction, dispersal, or any combination ofthese events, in explaining the origin ofwidespread distributions (VAN VELLER et al.,1999). The areas inhabited by the widespreadtaxon are regarded as constituting a poly–, para–or monophyletic group of areas (fig. 2: RACs 1–7),and the widespread taxon is treated as a possible

convergence of the areas. In practice, A2 isimplemented by locking each of the areasinhabited by the widespread taxon in turn,while the other areas are allowed to “float” onthe RAC (ENGHOFF, 1995; MORRONE & CRISCI, 1995).

The solutions allowed under the threeassumptions form inclusive sets (PAGE, 1990; VAN

VELLER et al., 1999): the A0 solutions are a subsetof the A1 solutions, and these in turn are asubset of the A2 solutions (fig. 2). Usually, thereare also solutions that violate all threeassumptions, namely those in which none of theareas of a widespread taxon occurs in the RAC inthe position predicted by the place of thewidespread taxon in the TAC (fig. 2: RACs 8–15).Thus, the A2 solutions are usually a small subsetof the “Full Solution Set” (all possible branchingarrangements of the studied areas).

Redundant distributions (sympatric taxa) areessentially handled in the same way aswidespread distributions. Under A0 and A1, eachoccurrence of the redundant area is consideredas equally valid, i.e., as representing duplicatedarea patterns. A2 also considers the possibilitythat the redundant distributions are the resultof dispersal, that is, each occurrence of theredundant distribution is considered separately(ENGHOFF, 1995). Missing areas are treated asmissing data under A1 and A2, and explained byprimitive absence (the taxon has never been inthe area), extinction (the taxon went extinct inthe area) or inadequate sampling. Under A0,missing areas are considered as observations oftrue absence and explained as due to primitiveabsence or extinction (ENGHOFF, 1995; MORRONE &CRISCI, 1995).

Application of these assumptions to empiricaldata has been controversial, as results can differgreatly when the same data set is processedunder different assumptions (MORRONE &CARPENTER, 1994; ENGHOFF, 1995; DE JONG, 1998;VAN VELLER et al., 2000). A0 (and A1) has beencriticized as being too restrictive and unrealisticbecause it does not consider the possibility ofdispersal in explaining widespread distributions,which means that areas may be groupedtogether solely based on recent range expansioninvolving geographically adjacent areas (NELSON

& PLATNICK, 1981; HUMPHRIES & PARENTI, 1986;PAGE, 1989, 1990; MORRONE & CARPENTER, 1994).A2, on the other hand, has been considered asuninformative or indecisive in that it allowsmany more solutions than the stricter A0 andA1, and therefore often gives a less resolvedresult (ENGHOFF, 1995; VAN VELLER et al., 1999). Ithas also been argued that A2 (and A1) distortthe historical (phylogenetic) relationshipsestablished in the original taxon cladogram fromwhich the area cladogram is derived (ZANDEE &ROOS, 1987; WILEY, 1988; ENGHOFF, 1996; VAN

VELLER et al., 1999, 2000) but this claim seems toarise from a confusion on the meaning of theassumptions: A2 and A1 are interpretations of


the relationships between areas, not betweentaxa (PAGE, 1989, 1990).

The problems of widespread taxa, redundancy,and missing areas have mainly been discussedwithin the traditional pattern–based approachto historical biogeography. Pattern–basedmethods search for general patterns of arearelationships (general area cladograms) allegedlywithout making any assumptions about evolu-tionary processes (RONQUIST, 1997; 1998a).Biogeographic processes, such as dispersal orextinction, are only considered a posteriori (orusing ad hoc procedures) in interpretingincongruence between the general areacladogram and the taxon–area cladograms (WILEY,1988; PAGE, 1994). However, several differentcombinations of events can usually explain eachcase of incongruence, leaving the choice of aspecific set of events that could explain theobservations to the investigator. Pattern–basedmethods may also give counter–intuitive resultsin some cases because they do not necessarilyfavor reconstructions implying likely events overthose implying improbable events (RONQUIST,1995).

Event–based methods, which are explicitlyderived from models of biogeographic processes,have gained in popularity recently (RONQUIST &NYLIN, 1990; PAGE, 1995; RONQUIST, 1995, 1998a,1998b). Unlike pattern–based methods, theevent–based reconstructions directly specify theancestral distributions and the biogeographicevents responsible for those distributions, andno a posteriori interpretation is necessary. Eachtype of biogeographic event in the recons-truction is associated with a cost that should beinversely related to the likelihood of that eventoccurring in the past: the more likely the event,the lower the cost. The optimal biogeographicreconstruction is found by searching for thereconstruction that minimizes the total cost ofthe implied events (RONQUIST, 1998a, 1998b, inpress).

The purpose of this paper is to reexamine theproblems of widespread taxa, redundantdistributions and missing areas in the light of theevent–based approach to historical biogeography.We find that it is only widespread terminaldistributions that cause problems in the event–based approach. Because the pattern–based A0,

Fig. 1. a. Steps of a cladistic biogeographic analysis: a taxon–area cladogram (TAC) is constructedby replacing the taxa in the phylogeny with the areas in which they occur. Comparing the taxon–area cladograms for different groups reveals the existence of a general biogeographic pattern(GAC). Conflicting area relationships (incongruence) may be indicated by the TAC if this includes:b. Widespread taxa; c. Redundant distributions; d. Missing areas.

Fig. 1. a. Un análisis biogeográfico cladista comprende dos pasos: construcción del cladogramade áreas (TAC) sustituyendo el nombre de los taxones en la filogenia por el área que ocupan yderivación del cladograma general de áreas (GAC). El cladograma de áreas puede indicarrelaciones conflictivas entre las áreas si existen: b. Taxones de amplia distribución; c. Distribucio-nes redundantes; d. Áreas ausentes.


A1 and A2 only define the set of allowed solutionsbut not the cost of each solution nor the impliedevents, they cannot be applied to event–basedanalyses. Instead, this paper describes three event–based options that may be used to reconcile theoccurrence of widespread terminals with the

common assumption of each lineage beingrestricted to a single area at a time: the recent,ancient and free options. We give algorithms thatimplement these options and illustrate theirproperties by reexamining a classical biogeo-graphic data set, that of ROSEN (1978).

Fig. 2. Taxon–area cladogram with a widespread taxon and three alternative methods ofresolution under the pattern–based approach: Assumptions 0, 1, and 2 (A0, A1, and A2). Notethat A2 excludes some solutions that are part of the “Full solution set” (all 15 possible rootedbinary trees on 4 taxa). (Modified from MORRONE & CRISCI, 1995.)

Fig. 2. Aplicación de las asunciones 0, 1 y 2 (A0, A1 y A2) a la resolución de un cladograma deáreas con un taxón de amplia distribución. Obsérvese que A2 excluye algunas de las solucionesque son parte del “Full solution set” (los 15 posibles cladogramas dicotómicos para 4 áreas).(Adaptado de MORRONE & CRISCI, 1995.)

Assumption 0

Assumption 1

Assumption 2

"Full solution set"


The event–based method

Event–based biogeographic methods rely onexplicit models with states (distributions) andtransitions between states (biogeographicprocesses). The most commonly used modelincludes four different processes (PAGE, 1995):vicariance, duplication, extinction and dispersal.Vicariance (v) is allopatric speciation in responseto a general dispersal barrier (i.e., a barrieraffecting many organisms simultaneously).Duplication (d) is sympatric speciation or,alternatively, allopatric speciation due toidiosyncratic events such as a temporary dispersalbarrier affecting only a single organism lineage.Extinction (e) may simply mean that organismsbecome extinct in an area but it can also resultfrom the organisms occupying only part of alarge ancestral area and therefore being absentin one of the fragments resulting from divisionof this area. Dispersal (i) occurs when organismscolonize a new area separated from theiroriginal distribution by a dispersal barrier; thisis assumed to be followed by allopatricspeciation separating the lineages in the newand old areas.

Once each event type is associated with acost, the cost of fitting a TAC to a particularGAC can be found by simply summing over theimplied events. The GAC with the lowest cost,the most parsimonious GAC, is that which bestexplains the taxon distributions in the TAC. Thisoptimal GAC can be found, for instance, byexplicit enumeration of all possible GACs or byheuristic search for the best GAC. Becauseinference is based on cost minimization, thisapproach may be referred to as parsimony–basedtree fitting. Similar methods are applicable toproblems in coevolutionary inference and in genetree–species tree fitting (RONQUIST, 1995, 1998a;PAGE & CHARLESTON, 1998).

An important problem in event-based methodsis to find the cost for each type of biogeographicprocess. The most common approach is to workwith simple event–cost assignments that focuson one or two of the events and ignore theothers (RONQUIST & NYLIN, 1990; RONQUIST, 1995).An example of this is Maximum vicariance (orMaximum cospeciation; PAGE, 1995; RONQUIST,1998a, 1998b), in which vicariance events aremaximized by associating them with a negativecost (a “benefit”, v = – 1), whereas the otherevents are not considered in the calculations(duplication (d) = extinction (e) = dispersal(i) = 0). The other approach is to set the costassignments according to some optimalitycriterion. A reasonable optimality criterion is tomaximize the likelihood of finding phylo-genetically conserved distribution patterns(RONQUIST, 1998a, 1998b, in press). Assume thatwe test for conserved distribution patterns byrandomly permuting the terminal taxa of theTAC and comparing the cost of the permuted

data sets with the cost of the original data set.Examination of simulated and real data suggeststhat, in most cases, chances of finding conservedpatterns are best when duplication andvicariance events carry a small cost relative toextinctions and dispersals (RONQUIST, in press).This occurs because both vicariance andduplication are phylogenetically constrainedprocesses, whereas dispersal and extinction arenot. In practice, it is often found that the optimalsolution is the same under a relatively widerange of event–cost assignments. In theexamples discussed in this paper, the cost ofvicariance (v) and duplication (d) events arearbitrarily set to 0.01; extinction events (e) to1.0; and dispersal events (i) to 2.0.

A simple example may illustrate parsimony–based tree fitting in historical biogeography.Consider a TAC with four terminals distributedin four areas (fig. 3a). Each possible GAC for thefour areas (there are 15 in all) is fitted in turnto the TAC. For example, only three vicarianceevents are needed to fit the TAC to GAC1(fig. 3b), whereas extra dispersal and extinctionevents must be postulated to explain theobserved TAC on GAC2 and GAC3 (figs. 3c–d),and extra duplication and extinction events areneeded for GAC4 (fig. 3e). Clearly, GAC1 will bethe most parsimonious solution among thoseconsidered in figure 3 given the chosen event–cost assignments. Actually, GAC1 will remainoptimal under a much wider range of costassignments: as long as dispersals and extinctionscost more than vicariance events, the optimalsolution will be the same. By explicitlyenumerating all the 15 GACs and finding thecost of fitting each of them to the given TAC, itcan also be demonstrated that GAC1 is theoptimal solution.

The optimal reconstruction and the cost forany TAC–GAC combination can be found usingfast dynamic programming algorithms (RONQUIST,1998b). This means that a particular GAC can befitted to a large set of TACs quickly. Nevertheless,searching for the best GAC using exhaustivealgorithms is impractical for problems with morethan around 10 areas, in which case heuristicalgorithms or other types of exact algorithmsshould be used instead.

Widespread taxa

Cladistic biogeography focuses on hierarchical(“branching”) patterns, in which a sequence ofvicariance events successively divides a continuousancestral area and its biota into smallercomponents (fig. 4a). This history is described bythe GAC (fig. 4b). The terminal branches in theGAC correspond to present areas (A, B, C) and theinternal branches to ancestral areas (E, D), whichare combinations of present areas.

In event–based methods (and in pattern–based


Fig. 3. Example of a reconstruction of the distribution history of a group of organisms in event–based methods: a. A taxon–area cladogram (TAC) distributed in four areas; b–e. Biogeographicreconstruction in which the TAC is fitted in turn into four GACs with alternative resolutions ofthe relationships between the areas occupied by the TAC. Fitting is evaluated as the cost of thebiogeographic events that must be postulated to explain the observed distributions in the TACaccording to the GAC. Four types of events are considered in the reconstruction: vicariance,duplication (sympatric speciation), extinction, and dispersal.

Fig. 3. Cómo reconstruir la historia biogeográfica de un grupo de organismos incorporando losprocesos en la reconstrucción biogeográfica (“biogeografía cladista de procesos”). a. Cladogramade áreas (TAC) distribuido en cuatro áreas; b–e. Reconstrucción biogeográfica en la que semuestra el grado de congruencia ("ajuste") entre el TAC y cuatro cladogramas generales de áreas(GAC), que difieren en la relación cladogenética entre las áreas que forman parte de la ampliadistribución. El “ajuste” se evalúa como el coste de los procesos biogeográficos que debenasumirse para explicar la distribución de los taxones en el TAC de acuerdo con las relacionesentre áreas establecidas por el GAC (ver texto). Se consideran cuatro tipos de procesosbiogeográficos: vicariancia, duplicación o especiación simpátrica, extinción y dispersión.

vicariance

duplication

extinction

dispersal


methods), organism lineages are commonlyassumed to be restricted to a single area at atime (for an exception see RONQUIST, 1997); thatis, an ancestral distribution must be either asingle present area or one of the ancestralareas (combinations of present areas) specifiedby the GAC. The one area–one lineageassumption makes parsimony–based tree fittingmathematically more tractable but it is alsobiologically sound: evolving lineages are notnormally expected to maintain their coherenceover long time periods across major dispersalbarriers. However, the assumption causesproblems with widespread terminals: how dowe reconcile the observation of widespreadterminals with the assumption of one area perlineage? The problem is analogous to that oftreating polymorphic characters in standardparsimony analysis, in which ancestors arenormally assumed to be monomorphic (MADDISON

& MADDISON, 1992).An obvious way of solving the dilemma is to

assume that the widespread terminal is in realitynot a homogeneous evolutionary lineage butan unresolved higher taxon consisting of anumber of lineages, each occurring in a singlearea (fig. 5a). This does not necessarily implythat the widespread taxon actually comprisesdifferent species that have failed to bedistinguished (HUMPHRIES & PARENTI, 1986; WILEY,1988; ENGHOFF, 1996; ZANDEE & ROOS, 1987; VAN

VELLER et al., 1999) but it suggests that thewidespread distribution is a temporarycondition. Now, assuming that the widespreadtaxon is a soft (unresolved) terminal polytomywith one lineage for each area occupied by the

taxon, we can obtain the minimum cost over allpossible resolutions of the polytomy for eachancestral distribution at the base of thepolytomy (the node marked with a black dot inthe TAC, fig. 5a). For each possible ancestraldistribution (i.e., each area in the GAC; fig. 5b),the terminal polytomy is resolved such that thecost of that distribution being ancestral isminimized (fig. 5c). This cost, in turn, is used inthe subsequent fitting of the TAC to the GAC.The cost will depend on the GAC because thesame ancestral distribution of a widespreadtaxon may have different costs on differentGACs (see fig. 6, table 1).

In determining the possible ancestral distribu-tions of the widespread taxon, we suggest threedifferent options: the recent, ancient and freeoptions. These options constrain the possibleancestral distributions of the widespread taxonin different ways, just like the traditionalAssumptions A0, A1 and A2. However, unlikethe traditional assumptions, the event–basedoptions constrain the solutions by explicitlyspecifying the processes allowed in explainingthe origin of the widespread distribution.Furthermore, each allowed solution is associatedwith a specific set of events and a specific cost.When many solutions are allowed, they oftendiffer in cost such that they still convey usefulinformation about the grouping of areas in theGAC. On continuation, the event–based optionsare described in more detail and comparedwith Assumptions 0, 1, and 2, both in terms ofhow they explain the widespread distribution(fig. 5) and how they affect the testing ofalternative GACs (fig. 6).

Fig. 4. a. Hierarchical scenario illustrated as a sequence of vicariance events successivelysubdividing a continuous ancestral area into smaller components; b. The same scenario representedin the form of a tree–shaped diagram, the general area cladogram (GAC).

Fig. 4. a. Escenario biogeográfico jerárquico en el que sucesivos eventos de vicariancia dividen unárea ancestral continua en fragmentos más pequeños; b. El mismo escenario, pero representadocomo un diagrama de árbol, el cladograma general de áreas (GAC).


Recent

Area: A B C D E F G H I

Cost: – 2i 2i – 2i – – – –

Ancient


Cost: – – – – – – – 2v+e (2v+2e)

Free


Cost: (3i) 2i 2i (3i) 2i v+i v+e+i 2v+e (2v+2e)

a b

c

Fig. 5. Resolving the problem of widespread taxa under the event–based approach: a. Taxon areacladogram with a widespread taxon represented as a terminal polytomy of single–area lineages; b.General area cladogram; c. The down–pass cost of each area in the GAC being the ancestraldistribution of the widespread taxon (the state at the node marked with a black dot in the TAC) isfound by resolving the terminal polytomy in congruence with area relationships in the GAC and thenrunning a down–pass optimization in this subtree. The recent, ancient and free options allow varioussets of possible ancestral distributions. The recent option only allows the GAC terminals occupied bythe taxon (B, C and E); the ancient option only allows the immediate ancestor in the GAC of these areas(H), and the free option allows both these possibilities plus all intermediates between them (F and G).(Symbols: – Areas not considered as possible ancestral distributions and associated with infinite cost; ( )Areas that are allowed as ancestral distributions but that will never occur in optimal reconstructionsbecause there will always be more parsimonious solutions; Abbreviations: d–duplication, e–extinction,i–dispersal, v–vicariance).

Fig. 5. Tratamiento de taxones de amplia distribución en “biogeografía cladista de procesos”: a.Cladograma de áreas (TAC) con un taxón de amplia distribución representado como una politomíaterminal formada por varios linajes, cada uno distribuido en un área; b. Cladograma general de áreas(GAC); c. Para calcular el coste de cada una de las áreas del GAC como posible distribución ancestraldel taxón de amplia distribución (el estado ancestral en el nodo señalado con un punto negro en elTAC), se resuelve la politomía terminal de acuerdo con las relaciones entre áreas establecidas por elGAC, y luego se realiza una optimización del coste moviéndose desde los terminales hacia la raíz delsubárbol. Las opciones recent, ancient y free permiten diferentes soluciones de las posibles distribu-ciones ancestrales. La opción recent sólo permite las áreas del GAC ocupadas por el taxón (B, C y E);la opción ancient sólo permite el área que representa el “ancestro común más reciente” de esas áreasen el GAC (H), mientras que la opción free permite cualquiera de estas posibilidades más todas lasáreas intermedias entre ellas (F y G). (Para los símbolos y abreviaturas ver arriba).


Recent option

This option is applicable when the widespreaddistribution can be assumed to be of recentorigin. One of the areas inhabited by thewidespread taxon is considered the true ancestralarea (the center of origin of the taxon) and theothers are treated as if added by recent,independent dispersal.

The possible ancestral distributions of thewidespread taxon are only those terminal areasoccupied by the taxon (B, C, E in fig. 5b).Regardless of whether we are using MaximumVicariance or any other set of cost assignments isused, the cost C of a present area being theancestral distribution is simply determined by:

C = (n – 1)i

where n is the number of areas inhabited by thewidespread taxon and i is the dispersal cost (e.g.,C = 2i in fig. 5c). The cost of all other GAC areas(terminal areas A, D and ancestral areas F–I infig. 5b) is set to infinity (an arbitrary high cost)(fig. 5c), since they are not allowed as ancestraldistributions.

In terms of explaining the widespreaddistribution, the recent option (“only dispersalallowed”) is not directly comparable to any ofthe traditional assumptions. In the context oftesting alternative GACs, it will weight againstA0 solutions in which the areas inhabited by thewidespread taxon form a monophyletic clade(fig. 6b; table 1). It will also weight against “Fullset” solutions in which all areas harboring thewidespread taxon occur in the GAC in positionsother than that predicted by the place of thewidespread taxon in the TAC (fig. 6e, table 1).These solutions, of course, violate A2.

Ancient option

This option is applicable when the widespreaddistribution can be assumed to be of ancientorigin. All areas inhabited by the widespreadtaxon are considered part of the ancestraldistribution. Any mismatch between thisdistribution and the GAC is then explained asdue to extinction; dispersals are not allowed.

Under the ancient option, the only possibleancestral distribution of the widespread taxon isthe most recent common ancestor in the GAC(“MRCA”) of all of the areas inhabited by thewidespread taxon (H in fig. 5b). The GAC areasthat are not ancestral to all of the recent areasinhabited by the taxon (A–G in fig. 5b) willrequire at least one dispersal and are thereforedisallowed under the ancient option and areassigned infinite cost (fig. 5c). Areas in the GACthat are ancestral to the MRCA (I in fig. 5b) areallowed but will never occur in optimalreconstructions, as they will always be morecostly than the MRCA (fig. 5c).

The cost of the MRCA is calculated assumingthat the terminal polytomy is resolved so thatthe topology fits the GAC perfectly. Underthese conditions, only extinction and vicarianceevents need to be considered becauseduplications are not required and dispersalsare, of course, not allowed. The cost (C) of theMRCA is then given by

C = pe + (n – 1)v

where p is the number of required extinctionevents, n is the number of areas inhabited by thewidespread taxon, and e and v the costs of theextinction and vicariance events, respectively.The number of required extinction events (p) iscomputed as follows:

In the GAC, focus on the subtree subtendedby the MRCA: ((B, C), (D, E)) in fig. 5b. Assign 1to the areas harboring the taxon (B, C, E) and 0to the other areas (D). Then, find the number oflosses (p) in this presence/absence characterassuming irreversibility (1 → 0). In fig. 5b, therewould be only one loss in area D so the cost is

C = 1e + (3 – 1)v = 2v + e

In terms of explaining the widespread distri-bution, the ancient option is similar to A1 in thatit allows extinctions but not dispersals. In thecontext of testing alternative GACs, however, itwill strongly favor A0 solutions in which theareas inhabited by the widespread taxon form amonophyletic clade (fig. 6b; table 1). Thus,widespread taxa provide strong evidence forgrouping the areas inhabited by them under theancient option.

Free option

Under the free option, all possible ancestralareas are considered and any mismatch betweenthe areas inhabited by the widespread taxonand the GAC is explained by the most favorablecombination of events. The minimum cost ofeach possible ancestral distribution is calculatedwithout any constraints on the type of assumedevents: dispersals, extinctions, duplications andvicariance events are all allowed.

For the Maximum Vicariance method, theoptimal cost of each possible ancestral dis-tribution is found if the terminal polytomy isresolved so that it becomes congruent with theGAC. This might hold for more complex event–cost assignments as well, if the cost of theancestral distributions is found with algorithmsignoring the complexity of dispersals, the so–called lower bound algorithms (RONQUIST, 1995,1998b, in press). Why the complexity ofdispersals should be ignored is because optimalsolutions may occasionally require combinationsof dispersals that are impossible on terminaltrees congruent with the GAC, but it seems that


Fig. 6. a. TAC with a widespread taxon; b–e. Four GACs with alternative resolutions of therelationships between the areas occupied by the widespread taxon. These solutions are associatedwith the traditional pattern–based Assumptions A0, A1, and A2 as follows: A0 would allow onlythe first solution (b), in which the areas of the widespread taxon form a monophyletic clade; A1would also allow the second GAC (c), in which the areas are paraphyletic; A2 would allow thethird GAC (d), in which the areas are polyphyletic. Finally, the “Full solution set” would includesome solutions (e) in which neither of the areas occurred in the position in the GAC predicted bythe TAC.

Fig. 6. a. Un TAC con un taxón de amplia distribución; b–e. Cuatro GACs mostrando solucionesdistintas de la relacion entre las áreas ocupadas por el taxón. Estas soluciones están relacionadascon A0, A1 y A2, de la siguiente manera: A0 permitiría sólo el primer GAC (b), en el que las áreasocupadas por el taxón de amplia distribución forman un grupo monofilético; A1 permitiríaademás el segundo GAC (c), en el que las áreas son parafiléticas; A2 permitiría el tercer GAC (d),en el que las áreas son polifiléticas. Finalmente, el “Full solution set” incluiría algunas soluciones(e) en las que ninguna de las áreas en el GAC aparecen en la posición en la que se encuentranen el TAC.


these conflicts can always be solved byrearranging the terminal tree without increasingthe total cost (Ronquist, unpublished data). Thelower–bound algorithms are computationallyextremely efficient so the implementation ofthe free option is straightforward if thisconjecture is true.

In terms of explaining the widespreaddistribution, the free option is similar to A2 inthat it allows all types of events. However, in thecontext of comparing alternative GACs, the freeoption will favor solutions in which the areasinhabited by the widespread taxon form amonophyletic clade, i.e., A0 solutions (fig. 6b,table 1). The relative cost difference betweenother solutions will depend on the set of areasinhabited by the widespread taxon and theirposition in the GAC (table 1). It is interesting tonote that, although the free option is similar to A2in terms of allowed events, it obviates one of themain criticisms raised against A2, namely that it isindecisive. According to the traditional view of A2,GACs 1–3 (figs. 6b–6d) would be equally probablesolutions, whereas the free option selects GAC 1(fig. 6b) as the most parsimonious solution. Thus,in this case the free option allows effective selectionamong alternative GACs.

Missing areas and redundant distributions

In pattern–based methods, missing areas (B infig. 1d) and redundant distributions (A in fig. 1c)are often identified in the TACs prior to theanalysis and different protocols (A0, A1, and A2)are then used to determine the possible RACs.For instance, missing areas can be treated eitheras missing data or as observations of true absence.If treated as missing data (A1, A2), absence maybe due to primitive absence, extinction, orinadequate sampling and the missing area canthus occupy any position in the RAC. If treated astrue absence (A0), only primitive absence orextinction are possible explanations. For instance,if several areas are missing from the TAC, thismay be taken as evidence that these areas shouldbe grouped in the RAC (extinction) or that thenon–missing areas should be grouped (primitiveabsence). Redundant distributions can be treatedunder A0, A1 (all occurrences due to ancestry,and any GAC–TAC mismatch explained byduplication and extinction) or under A2 (some ofthe occurrences possibly due to dispersal).

In event–based methods, it is difficult toseparate potential cases of incongruence that canbe identified in TACs prior to analysis (observed)from missing areas and redundant distributionsthat are introduced during the TAC–GAC fittingprocess (inferred). If an area is redundant ormissing in a TAC simply depends on the generalarea cladogram (GAC) being analyzed and on theparticular events postulated by the reconstructionfitting the TAC to the GAC. The reconstruction

may postulate TAC redundancy that is notapparent before analysis or change theinterpretation of which areas are truly missingfrom the TAC. For instance, a TAC fitted to acongruent GAC will have no missing or redundantareas (figs. 3a, 3b) but if the same TAC is fitted toan incongruent GAC (fig. 3c) one must postulatethat some TAC distributions are missing orredundant. A lineage (5) may have become extinctin area D and another taxon (4) may havesecondarily re–colonized the same area (fig. 3c).In this reconstruction, there is both a missing area(the absence of taxon 5 in area D) and a redundantdistribution (the presence of taxon 4 in area D).However, a different incongruent GAC (fig. 3d)postulates a different set of missing and redundantareas: in this case area C is both the missing area(the absence of taxon 5) and the redundantdistribution (the presence of taxon 3). Therefore,a priori (observed) and a posteriori (inferred)cases of redundancy and missing areas should betreated in the same way in event–based methods;there is no need for special protocols dealingwith these cases of incongruence prior to analysis.

The treatment of missing areas in event–basedmethods is of particular interest. Event–basedmethods treat missing areas as true absence andexplain them as due to primitive absence orextinction. If the missing data interpretationwere allowed, then parsimony–based tree fittingwould not work because any analysis would beswamped by low–cost solutions postulatingevents that left no trace in the observed TAC(RONQUIST, in press).

A simple example will illustrate the event-based treatment of missing areas: assume thatwe have a “two–taxa–two–area” TAC and a fourarea GAC (fig. 7). GAC 1 (fig. 7a) groups the TACareas into a monophyletic group (C–D) so avicariance event is sufficient to explain the historyof the organisms; absence of the group in areas Aand B is explained as primitive absence. Thiscould mean that the ancestor of the TAC dispersedfrom an area outside of the considered GAC tothe area in the GAC ancestral to C and D, that theoutgroups of the TAC occur in areas A and B, orsome other alternative. Since we have noinformation about the outgroups, we cannotdistinguish among the alternatives.

GAC 2 (fig. 7b) groups the TAC areas into aparaphyletic group so a vicariance and anextinction event are required to explain the historyof the organisms. In GAC 3 (figs. 7c–d), the TACareas form a polyphyletic group. The TAC can bemapped onto this GAC either by introducing avicariance and two extinction events (fig. 7c) orone dispersal event (fig. 7d). If vicariance andduplication events are associated with a low costand dispersal and extinction with high cost, assuggested above, GAC 1 would clearly be favoredover GAC 2 and GAC 3. Thus, in searching for theoptimal GAC, event–based methods favor scenariosin which the missing areas are explained as being


fitting the TAC to GAC3 (figs. 7c–d). The extinctionexplanation (fig. 7c; one vicariance (cost v) and2 extinctions (cost 2e)) is favored over the dispersalexplanation (fig. 7d; one dispersal (cost i)) unlessi < 2e + v. This is an event–cost assignmentscheme that in most cases has a low probabilityof discovering phylogenetically constraineddistribution patterns.

due to primitive absence, and the rest of the GACfits the TAC perfectly (GAC1, fig. 7a). The relativecost of other GACs depends on the event–costassignments. Generally speaking, extinctionexplanations are favored over dispersalexplanations unless the extinction cost isconsiderably higher than the dispersal cost.Consider, for instance, the two different ways of

Table 1. Testing alternative GACs using the event–based approach. For each of the GACs in figs.6b–e, the minimal cost of fitting them to the TAC in figure 6a is calculated using three differentoptions for treating widespread taxa (recent, ancient and free), and two different event–basedmethods having different event–cost assignments (parsimony–based tree fitting and maximumvicariance). For parsimony–based tree fitting, the costs of the events are: duplications (d) =vicariance (v) = 0.01, extinction (e) = 1.0 and dispersal (i) = 2.0. For maximum vicariance theevent costs are d = e = i = 0 and v = – 1. In calculating the costs, note that the constraintsimplied by the recent and ancient options ("only dispersals allowed" or "no dispersals allowed",respectively) were applied only to the ancestral distribution of the widespread taxon, not tothe distributions of the rest of the nodes in the TAC. Each of the GACs (figs. 6b–e) correspondsto one of the pattern–based Assumptions 0, 1 or 2 or the “Full solution set” (see text of fig. 6):* In general, the maximum vicariance reconstruction can be obtained directly from the parsimony–based reconstruction by replacing the cost assignments (d = i = e = 0, v = – 1). However, in thiscase the least costly reconstruction in parsimony–based tree fitting is cheaper (v + 2i) than theone with the maximum number of vicariance events (d + 2v + 4e).

Tabla 1. Comparación de distintos GACs utilizando las opciones recent, ancient y free en laresolución de taxones de amplia distribución. Para cada uno de los GACs en las figuras 6b–6e,calculamos el coste mínimo de “ajuste” al TAC (fig. 6a), utilizando tres opciones diferentes pararesolver taxones de amplia distribución (recent, ancient, y free) y dos métodos distintos quedifieren en el coste asignado a cada proceso (parsimony–based tree fitting y maximum vicariance).En parsimony–based tree fitting, el coste de cada proceso es: duplicación (d) = vicariancia (v) =0.01, extinción (e) = 1.0 y dispersión (i) = 2.0. En maximum vicariance, los costes son d = e = i =0 y v = – 1. Obsérvese que, al calcular los costes, las restricciones impuestas por las opcionesreciente y ancestral (“sólo se permiten dispersiones” o “no se permiten dispersiones”) se aplicansólo a la distribución ancestral del taxón de amplia distribución, no a las distribuciones del restode nodos en el TAC. Cada uno de los GACs (figs. 6b–6e) corresponde a una de las tradicionalesAsunciones 0, 1 y 2, o al “Full solution set” (ver pie de figura 6): * En general, la reconstruccióncon el método de maximum vicariance se obtiene directamente de la reconstrucción conparsimony–based tree fitting remplazando los costes de los procesos por (d = i = e = 0, v = – 1).Sin embargo, en este caso el coste de la reconstrucción óptima en parsimony–based tree fittinges menor (v + 2i) que la que se obtendría considerando el número máximo de eventos devicariancia (d + 2v + 4e).

GAC1, fig. 6b GAC2, fig. 6c GAC3, fig. 6d GAC4, fig. 6e

Option (Assumption 0) (Assumption 1) (Assumption 2) (“Full solution set”)

Parsimony–based tree fitting

Recent 2v+e+i = 3.02 2v+i = 2.02 2v+e+i = 3.02 v+2i = 4.01

Ancient 3v = 0.03 d+2v+3e = 3.03 d+2v+4e = 4.03 d+2v+4e = 4.03

Free 3v = 0.03 2v+i = 2.02 2v+e+i = 3.02 v+2i = 4.01

Maximum vicariance

Recent – 2 – 2 – 2 – 1

Ancient – 3 – 2 – 2 – 2

Free – 3 – 2 – 2 – 2*


Fig. 7. Treatment of missing areas in the event–based approach. A two–taxon–two–area TAC isfitted to a four–area GAC: a. If the TAC areas are monophyletic in the GAC, only one vicarianceevent is required; b. If the TAC areas are paraphyletic in the GAC, one extinction and onevicariance event are required; c–d. If the TAC areas are polyphyletic in the GAC, either avicariance and two extinction events (c) or a dispersal event (d) are required. (Symbols as infigure 3.)

Fig. 7. Tratamiento de las “áreas ausentes“ en “biogeografía cladista de procesos”. Un cladogramade áreas con dos taxones distribuidos en dos áreas superimpuesto en un GAC de cuatro áreas: a.Si las áreas del TAC son monofiléticas en el GAC, sólo se requiere un evento de vicarianza paraexplicar las distribuciones en el TAC; b. Si las áreas del TAC son parafiléticas en el GAC, unaextinción y un evento de vicarianza son necesarios para explicar la distribución; c–d. Si las áreasdel TAC son polifiléticas en el GAC, se necesitan o bien una vicarianza y dos eventos de extinción(c) o un evento de dispersión (d). (Símbolos como en la figura 3.)

As this example clearly demonstrates, absencedata are informative in the search for the optimalGAC with event–based methods. The cost ofextinction events determines the extent to whichabsence data influence the search for the GAC: thelower the weight of extinction, the smaller theeffect of absence data. A low extinction costdownplays the importance of absence data,regardless of whether this is caused by poor samplingor true absence. Thus, an event–based method witha low extinction cost mimics the missing datatreatment of true absences in pattern–basedmethods. This is a good argument for assigning alower cost to extinctions than to dispersals in event–based methods of biogeographic absence.

Which assumption should we choose?Which assumption should we choose?Which assumption should we choose?Which assumption should we choose?Which assumption should we choose?

Of the three event–based options described abovefor treating widespread taxa, there is none thatis ideally suited to all kinds of problems. Eachoption has its strengths and weaknesses, and thechoice should therefore depend on the nature ofthe data. The free option is more general in thatit allows more processes in explaining widespreadterminal distributions. On the negative side, it iscomputationally more demanding than the otheroptions and because it allows more solutions, itmay also be associated with loss of informationconcerning the optimal GAC. To some extent,however, the potential information loss may be


Fig. 8. Example of the application of the event–based options to treat widespread taxa. Taxon–area cladograms for the poeciliid fish genera: Heterandria (a) and Xiphophorus (b) (After ROSEN,1978), with areas 4 and 5 combined in accordance with PAGE (1989); c–e. General area cladogramderived with TreeFitter 1.0 (RONQUISt, 2001) for Heterandria / Xiphophorus under the threedifferent options to treat widespread taxa: recent, ancient, and free; f–h. General area cladogramsobtained with Component 2.0 (PAGE, 1993) under A0, A1, and A2 (After VAN VELLER et al., 2000).

Fig. 8. Ejemplo del tratamiento de taxones de amplia distribución en “biogeografía cladista deprocesos”. Cladograma de áreas (TAC) para los géneros de Poeciliidae: Heterandria (a) yXiphophorus (b) (modificado de ROSEN, 1978); las áreas 4 y 5 han sido combinadas en una solaárea de distribución como en PAGE (1989); c–e. GACs obtenidos con Tree Fitter 1.0 (RONQUIST,2001) para Heterandria / Xiphophorus utilizando tres opciones diferentes para resolver taxonesde amplia distribución: recent, ancient y free; f–h. GACs obtenidos con Component 2.0 (PAGE,1993) utilizando las opciones tradicionales A0, A1 y A2 (adaptado de VAN VELLER et al., 2000).

species A (6)

H. jonesi (1)

species B (9)

species C (4,5)

species D (10)

species E (7)

Chajmaic bimaculata (8)

other bimaculata (2)

variatus–group (1)

milleri (2)

maculatus (2)

pygmaeus (1)

nigrensis (1)

montezumae (1)

cortezi (1)

clemenciae (3)

alvarezi (4,5,6)Molagua–Polochic–Honduras helleri (9,10)

Chajmaic helleri (8)

other helleri (2)

Recent Ancient Free

Assumption 2 Assumption 0 Assumption 1

Heterandria Xiphophorus


Fig. 9. Event–based reconstructions showing the fit between the TACs of Heterandria andXiphophorus (figs. 8a, 8b) and the GACs obtained under the event–based options to treatwidespread taxa (figs. 8c–8e). Biogeographic reconstructions of Heterandria and Xiphophorus:a–b. Under the recent option; c–d. Under the ancient option; e–f. Under the free option. Thecost of the reconstruction is indicated under each figure (d = v = 0, e =1.0, i = 2.0). Symbols asin figure 3. Small black arrows: dispersal events within the terminals that are not considered inthe cost of the reconstruction under the recent option because they are invariable across thepossible GACs (“only dispersal allowed”). Hollow circles: vicariance events within the terminalsthat are not considered in the cost of the reconstruction under the ancient option because theyare invariable across the GACs (“only vicariance and extinction allowed”). Hollow arrows:dispersal events within the terminals that are included in the cost of the free reconstruction,since this option allows all types of events in explaining the widespread distribution.

Recent

Ancient

Free

Heterandria Xiphophorus


counteracted by the differences in the costassociated with the allowed solutions. The ancientoption makes the boldest assumptions about theorigin of the widespread distributions. If theassumptions are warranted, the search for theoptimal GAC should gain in power; if they arenot, the result of the analysis may be flawed. Forinstance, the ancient option might be useful inanalyzing the distribution history of old groupsthat are very unlikely to have dispersed, or inwhich the widespread taxon has lost the abilityto disperse (e.g., a wingless species in a fullywinged group).

In many cases, it is quite clear that thewidespread terminals are younger than any ofthe ancestral areas in the GAC, in which casethe recent option would be the only defensiblechoice. The recent option may also beadvantageous in the identification of phylo-genetically constrained biogeographic patternsbecause it does not allow vicariance eventswithin widespread terminals, in contrast to thefree and ancient options. Assume that we testfor constrained distributions by comparing thecost of the observed TAC with that of randomTACs obtained either by randomly drawing newTAC topologies or randomly shuffling the TACterminals. Because the widespread terminalsare the same in both the observed and randomTACs, the terminal events will not contribute todistinguishing the observed TAC from therandom TACs. However, it is quite likely thatseveral of the “terminal” events could be pushedonto the ancestral nodes in the observed TACbut not in the random TACs. This potentialsupport for the GAC is ignored by the free andancient options. The recent option forcesvicariance events onto ancestral nodes in theTAC and is therefore more powerful inseparating phylogenetically constraineddistribution patterns from random data in thiskind of test. For an empirical example, seeSANMARTÍN et al. (2001).

Software

The Recent, Ancient and Free event-based optionshave been implemented in the computer programTreeFitter 1.0 (RONQUIST, 2001). TreeFitter is aprogram for finding the optimal biogeographicreconstruction/s (GACs), given one or more TACs.TreeFitter is available as free software on thewebsite: http://www.ebc.uu.se/systzoo/research/treefitter/treefitter.html.

An empirical example: Xiphophorus andHeterandria (Rosen, 1978)

ROSEN (1978)’s study on the poeciliid fishesHeterandria and Xiphophorus is probably themost widely used benchmark data set in thedevelopment of biogeographic methods. Becausethe solutions under Assumptions 0, 1, and 2 forthis data set are well known, it provides a usefulcomparison with the results of the event–basedoptions.

Figure 8 shows the taxon-area cladograms forHeterandria (fig. 8a) and Xiphophorus (fig. 8b).They include widespread taxa (e.g., X. alvareziin areas 4, 5, 6), redundant distributions (e.g.,area 2 in Xiphophorus), and missing areas (e.g.,area 3 in Heterandria or area 7 in Xiphophorus).Using TreeFitter 1.0 (RONQUIST, 2001), wesearched for the optimal GAC for the two generatreating widespread taxa under the differentevent–based options.

The recent option (fig. 8c) finds an optimalGAC that basically follows the pattern of arearelationships in Heterandria. The areas includedin widespread (4–5, 6, 9 and 10) or redundant(2) distributions in Xiphophorus are positionedin the optimal GAC according to the TAC ofHeterandria; only area 3, missing in Heterandria,is placed according to its position in Xiphophorus(basal to areas 4–5). The optimal GAC under therecent option is one of the three GACs found

Fig. 9. Reconstrucción biogeográfica mostrando el grado de ajuste entre los TACs de Herterandriay Xiphophorus (figs. 8a, 8b) y los tres GACs obtenidos con las tres opciones para resolver taxonesde amplia distribución: recent, ancient y free (figs. 8c–8e) en la resolución de taxones de ampliadistribución (figs. 8c–8e). Reconstrucción de la historia biogeográfica de Heterandria y Xiphophorus:(a–b) con la opción recent, (c–d) la opción ancient y (e–f) la opción free. Debajo de cadareconstrucción se indica su coste en términos de procesos biogeográficos (v = d = 0, e = 1.0, i =2.0). Símbolos como en la figura 3. Pequeñas flechas negras: dispersiones dentro de losterminales no consideradas en el coste de la reconstrucción bajo la opción recent porque estaríanpresentes en todos los posibles GAC (“sólo se permite dispersión”, ver texto). Círculos blancos:vicarianzas dentro de los terminales no consideradas en el coste de la reconstrucción ancientporque estarían presentes en todos los posibles GAC (“sólo se permite vicarianza y extinción”,ver texto). Flechas blancas: dispersiones dentro de los terminales incluidas en el coste de lareconstrucción free porque esta opción permite cualquier tipo de evento (dispersión, vicarianza,o extinción) para explicar la amplia distribución.


under A2 (fig. 8f) by PAGE (1989) and VAN VELLER

et al. (2000) but is different from the single GACobtained under either A0 (fig. 8g) or A1 (fig. 8h).

The optimal GAC under the ancient option(fig. 8d) agrees mainly with the relationshipsamong areas in Xiphophorus. Areas 1 and 3 areplaced basally in the cladogram, whereas areas 4–5 and 6, and areas 9 and 10, are grouped togetheras sister–areas. This is the same GAC found by VAN

VELLER et al. (2000) using COMPONENT 2.0 (PAGE,1993) under A0 (fig. 8g), which is not surprisingconsidering that both the ancient option and A0group areas based on widespread distributions. Itis also similar to the GAC obtained under A1(fig. 8h) except that the areas forming part of thewidespread distribution are not monophyletic inA1. This assumption, like the ancient option,considers the widespread distribution to beancestral and only allows extinction and vicarianceevents as possible explanations. In this case,treating the widespread taxa as fully informativeabout area relationships conflicts with theevidence from endemic taxa because for eachpair of areas in a widespread terminal in theXiphophorus TAC (e.g., 9 and 10), the correspond-ing endemic taxa in the Heterandria TAC are notclosely related (species B and species D).Nevertheless, the grouping information providedby the widespread taxa is strong enough tooverride the signal from the endemic taxa.

The free option finds the same optimal GACas the recent option. Thus, the widespreadterminal distributions in Xiphophorus are bestexplained as due to recent dispersal when allprocesses are allowed and the cost of all impliedevents, ancestral as well as terminal, is considered(see fig. 9). As mentioned above, this GAC is oneof the three solutions found under A2 by PAGE

(1989: his fig. 10) and VAN VELLER et al. (2000:their fig. 13c). The other two solutions placearea 3 basal to area 9 or areas 3 and 9 in amonophyletic clade, in both cases requiring anextra extinction event in the event–basedframework. For these data, A2 is clearlyassociated with a loss in resolving powercompared to A0 and A1 because it allows threeinstead of one solution. This information lossdoes not occur for the free option in the event–based analyses.

Our analyses of the Rosen data show some ofthe similarities and differences between thetraditional pattern–based assumptions and theevent–based options. Clearly, there is no one–to–one correspondence between the options andassumptions. Both the recent and free optionsshare properties with A2, whereas the ancientoption is more similar to A0 and A1. For Rosen’sdata, the results obtained with the free optionsupport those obtained with the recent option.This suggests that the ancient option may forceunrealistic constraints onto the analysis and thatthe optimal GAC under the free and recentoptions may be preferable. This is also the GAC

that is better supported by the phylogeneticallydetermined (as opposed to the within–terminal)area relationships in the two TACs.

Conclusions

The controversy surrounding the treatment ofwidespread taxa, missing areas and redundantdistributions in historical biogeography has beendifficult to resolve because of the lack of acommon theoretical framework. The event–basedapproach provides such a framework withinwhich the nature of different methodologicaloptions and their effect on biogeographicreconstruction can easily be understood. We hopethat our exploration of event–based solutions tothe resolution of incongruence in biogeographicinference will contribute to a more focuseddebate on these issues in the future. The event–based solutions described here should beapplicable not only to biogeographic analysisbut also to coevolutionary inference.

Acknowledgments

We thank Henrik Enghoff and an anonymousreviewer for useful comments on this manuscript.This research was supported by the SwedishNatural Science Research Council (grant to FredrikRonquist) and through a European CommunityMarie Curie Fellowship (Isabel Sanmartín) underthe Improving Human Potential programme(Project MCFI–2000–00794).

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Vives†, J., Escolà, O. & Vives, E., 2002. Dos nuevas especies de Anillini cavernícolas pertenecientes al géneroSpeleotyphlus Jeanne, 1973 (Coleoptera, Carabidae). Animal Biodiversity and Conservation, 25.2: 95–99.

AbstractAbstractAbstractAbstractAbstractTwo new species of subterranean Anillini belonging to genus Speleotyphlus Jeanne, 1973 (Coleoptera,Carabidae).— Speleotyphlus comasi n. sp. and S. virgilii n. sp. from two caves Cueva del Turcacho (Teruelprovince) and Cova Bonica in Ulldecona (Tarragona province) are described. The former was collected in1981 and was a female. Despite several attempts the male was not found. Only one other species S. fideliViñolas & Escolà has been described for the province of Teruel but S. comasi clearly differs regarding theshape of the elytra and umbilicate series. S. virgilii n. sp. is very similar to S. fadriquei Español, 1999 butis slightly larger and the pronotum is transverse rather than elongated as in S. fadriquei Español.

Key words: Speleotyphlus comasi n. sp., Speleotyphlus virgilii n. sp., Coleoptera, Carabidae, Anillini, Spain.

ResumenResumenResumenResumenResumenDos nuevas especies de Anillini cavernícolas pertenecientes al género Speleotyphlus Jeanne,1973(Coleoptera, Carabidae).— Se describen dos nuevas especies Speleotyphlus comasi sp. n. y S. virgilii sp. n.procedentes de dos cuevas: Cueva del Turcacho (provincia de Teruel) y Cova Bonica de Ulldecona (provincia deTarragona). La primera fue recolectada en 1981 y es una hembra. A pesar de muchos intentos, no se pudolocalizar el macho. En la provincia de Teruel sólo se ha descrito otra especie S. fideli Viñolas & Escolà aunque S.comasi difiere claramente de ella en la forma de los elitros y las series umbilicadas. S. virgilii sp. n. es muy simlara S. fadriquei Español, 1999 pero es ligeramente más larga y el pronoto es transverso más que alargadocomo en S. fadriquei Español.

Palabras clave: Speleotyphlus comasi sp. n.; Speleotyphlus virgilii sp. n., Coleoptera, Carabidae, Anillini, España.

(Received: 9 IV 02; Conditional acceptance: 22 V 02; Final acceptance: 27 VIII 02)

Oleguer Escolà1 & Eduard Vives2, Museu de Ciències Naturals (Zoologia), Passeig Picasso s/n, 08003 Barcelona,Espanya (Spain).


† Joan Vives i Duran deceased in 15 XI 2000

Dos nuevas especies deAnillini cavernicolas pertenecientesal género Speleotyphlus Jeanne, 1973(Coleoptera, Carabidae)

J. Vives†, O. Escolà & E. Vives

96 Vives et al.

Introducción

En 1966 Español describió una especie deAnillini cavernícola, Microtyphlus aurouxi Es-pañol, 1966, procedente de las capturas deLluís Auroux en el Avenc de Serenge, Cabanes(Castelló). Posteriormente el mismo autor des-cribió también Catalanotyphlus jusmeti Espa-ñol, 1971 para otros ejemplares de Anillinicavernícolas de Coves de Vinromà, también enel norte de la provincia de Castelló. Estas dosespecies muy próximas sistemáticamente, fue-ron englobadas en una nueva división de losAnillini euro–mediterráneos, creada por JEANNE

(1973), para incluir aquellas especies caverní-colas de forma alargada y convexa cuya serieumbilicada de poros elitrales se ajustaba altipo B de JEANNEL (1963).

Recientemente ESPAÑOL ha descrito otra nuevaespecie Speleotyphlus fadriquei Español, 1999;procedente de una sima del sur de la provinciade Tarragona, en el término municipal de Serrad’Almos, también con una facies típicamentecavernícola.

Con estas nuevas aportaciones el géneroSpelotyphlus alcanza la cifra de cinco especiesconocidas, S. aurouxi, S. jusmeti, S. fadriquei, S.comasi sp. n. y S. virgilii sp. n. Muy probablemen-te aparecerán más especies de este género en lasnumerosas cavidades de Tarragona, Castelló yTeruel, especialmente en la zona montañosa dePorts de Caro (también denominados de Tortosao Beceite), donde hasta la fecha se conocen otroscarábidos cavernícolas como Paraphaenopsbreuilianus Jeannel, 1916 y Cephalosphodruslassallei Mateu, 1989; pero no se ha recolectadoningún representante de Carabidae Anillini(ZABALLOS & JEANNE, 1994).

Material y métodos

Gracias a las exploraciones espeleológicas denuestros colegas Florentino Fadrique y de JordiComas, han sido colectadas dos nuevas especiesprocedentes del sur de la provincia de Tarragonay del sureste de la provincia de Teruel respectiva-mente. Estas dos nuevas especies que aquí sedescriben se incluyen perfectamente entre losrepresentantes conocidos del mencionado géne-ro Speleotyphlus, si bien se pueden separar porlos caracteres que se indican en su descripción.

Descripción

Speleotyphlus comasi n. sp. (fig. 1)

Material estudiadoHolotipo: 1} Cueva del Turcacho, Iglesuela delCid, Teruel, 19 IV 1981, Jordi Comas leg. Deposi-tado en el Museu de Zoologia de Barcelona,(MZB nº 2002–0192).

DescripciónLongitud, 2 mm. Anchura, 0,8 mm. Coloracióntestácea, con las patas y antenas levemente másclaras casi amarillas. Aspecto general largo ysubparalelo, con la cabeza grande, netamentemas larga que ancha, con ausencia total de ojos,que tan solo están indicados por una leve manchaamarillenta y una seda supraorbital anterior muylarga y otra posterior más corta y arqueada.Antenas de once artejos, con el primero muchomas largo y robusto que el segundo, éstenetamente estrechado en su mitad, del tercero alsexto son subiguales, siempre mucho más largosque anchos del séptimo al décimo subcuadrados,el onceavo es ovalado y aplanado. Las mandíbulasson algo salientes y con su ápice curvado. El labroes rectangular, y está provisto de cuatro sedas ensu reborde anterior.

El protórax es tan largo como ancho en sucuarto anterior, con sus lados arqueados y sinuadosen el tercio posterior que es mucho más estrecho.Los ángulos posteriores son agudos y salientes, ypresentan una larga seda umbilicada. El surcolateral está rebordeado y provisto de una largaseda en su cuarto anterior. El disco pronotal esaplanado y posee un leve surco longitudinal me-diano. Toda la superficie protorácica estárecubierta por unas cortas sedas espaciadas, másnumerosas en el reborde marginal.

Los élitros son largos y subparalelos, casi eldoble de largos que anchos en la zona basal. Loshúmeros son muy salientes y están fuertementedentados. El reborde marginal es ancho y bientrazado, levemente estrechado en el quinto apical;todo él provisto de largas sedas umbilicadas talcomo se indica en la figura 1. La superficie elitrales convexa en el disco y levemente aplanada en elápice, con el ángulo apical poco marcado. Elápice elitral está levemente truncado, dejando aldescubierto el último segmento abdominal. Laserie umbilicada presenta nueve poros setígeroscon largas sedas, una pequeña seda yuxtaescutelary tres largas sedas discales alineadas. La superficieelitral es fuertemente chagrinada, sin restos deestrías y algo brillante.

Las patas son cortas, con los fémures anterio-res poco ensanchados en su parte distal. Lastibias intermedias y posteriores son finas y estanalgo sinuadas en su primer tercio. Todas laspatas y tarsos estan recubiertos por unas cortassedas doradas.

EtimologíaEl nombre de esta especie está dedicado a sudescubridor, Jordi Comas i Navarro, en reconoci-miento a su larga labor bioespeleológica.

ComentariosEspecie cavernícola hasta la fecha tan solo cono-cida por un ejemplar hembra recolectado en laCueva del Turcacho, provincia de Teruel. Duranteaños esta cueva ha sido visitada por numerososbioespeleólogos sin poder recolectar ningún


ejemplar más de dicha especie. Al parecer setrataría de un endogeo de cueva al igual queotros Anillini cavernícolas mediterráneos.

Es la segunda especie de carábido cavernícolaconocida como procedente de la provincia deTeruel, ya que recientemente VIÑOLAS & ESCOLÀ

(1999) han descrito otro Anillini correspondienteal género Microtyphlus, también procedente deuna cavidad de Teruel. Sin embargo S.comasin.sp. es muy diferente de Microtyphlus fideliViñolas & Escolà, 1999; especialmente por laforma de sus élitros y la topografía de la serieumbilicada.

Speleotyphlus virgilii sp. n. (figs. 2–4)

Material estudiadoHolotipo: 1{ Cova Bonica, Ulldecona (Tarragona–S)10 I 2000, F. Fadrique leg. Depositado en el Museude Zoologia de Barcelona (MZB nº 2000–0342).

Paratipos: 28 ejemplares de Cova Bonica,Ulldecona (Tarragona–S); 1} 13 III 2000, 6{ y

10} 10 I 2000; 4} 11 II 2000; 1} 19 II 2000; 4{2 III 2000; 1{ y 1} 8 IV 2000. Recolectados por F.Fadrique. Depositados en el Museu de Zoologiade Barcelona y en la colección J. & E. Vives(Terrassa).

DescripciónLongitud, 2 mm. Anchura 0,8 mm. Coloraciónamarillo testácea. Cabeza y protórax de colorcaramelo. Aspecto general largo y subparalelo,con la cabeza alargada, sin rastros de zona ocu-lar y con varias largas sedas en la zona orbital. Ellabro es rectangular y está provisto de seis sedas,las centrales más cortas (fig. 3). El cuello esgrueso y sin estrechamiento posterior. Las ante-nas son cortas, justo alcanzando la base elitral,con el primer artejo en forma de escapo y leve-mente más corto que el segundo; del tercero alquinto tienen forma fusiforme y del sexto aldécimo son subglobulares; el undécimo es fusi-forme y aplanado.

El protórax es levemente más ancho que largoen su borde anterior, con sus lados arqueados y

Fig. 1. Speleotyphlus comasi sp. n., habitusdel holotipo.

Fig. 1. Speleotyphlus comasi n. sp., habitusof the holotype.

Fig. 2. Speleotyphlus virgilii sp. n., habitusdel holotipo.

Fig. 2. Speleotyphlus virgilii n. sp. habitusof the holotype.

1 mm1 mm1 mm1 mm1 mm 1 mm1 mm1 mm1 mm1 mm

98 Vives et al.

sinuados en el tercio posterior, formando unospequeños ángulos agudos en su base posterior,muy poco salientes y provistos de una largaseda. El reborde lateral está bien marcado yprovisto de una larga seda en el quinto anterior,además de una serie de pequeñas sedas cortasrepartidas por todo el disco protorácico y susbordes laterales. El disco pronotal está divididopor un surco mediano longitudinal que no alcan-za el borde anterior ni el posterior.

Los élitros son largos y paralelos, levemente máslargos y convexos en el macho, y algo más aplana-dos en la hembra, con lo húmeros redondeados ylevemente dentados. El reborde marginal es estre-

Tabla 1. Caracteres diferenciales de Speleotyphlus comasi sp. n. y Spelotyphlus virgilii sp. n.

Table 1. Diferential characters of Speleotyphlus comasi n. sp. and Spelotyphlus virgilii n. sp.

Speleotyphlus comasi sp. n. Speleotyphlus virgilii sp. n.1. Presencia de dos sedas supraorbitales 1. Presencia de varias sedas orbitales cortas La posterior muy corta2. Labro con cuatro sedas 2. Labro con seis sedas3. Protórax tan largo como ancho 3. Protórax levemente más ancho que largo4. Angulos posteriores de protórax 4. Ángulos posteriores del protórax agudos y salientes poco salientes5. Elitros casi doble largos que anchos 5. Elitros más cortos y más convexos (7/4) en su base (8/4)6. Húmeros angulosos y muy salientes 6. Húmeros redondeados y poco salientes

Figs. 3, 4. Speleotyphlus virgilii sp. n.. 3. Labro: a. Visión dorsal; b. Visión ventral. 4. Edeago,visión lateral.

Figs. 3, 4. Speleotyphlus virgilii n. sp. 3. Labrum: a. Dorsal view; b. Ventral view. 4. Oedeagus,lateral view.

cho y no alcanza el ápice elitral; está provisto deuna serie umbilicada de macroquetas según la to-pografía que se aprecia en la figura 2. La superficieelitral es chagrinada y con brillo opaco. El ánguloapical apenas está indicado en el macho, y espracticamente ausente en la hembra. Las patas soncortas y finas, con el primer artejo de los protarsosdilatado en los machos, y provistos de un levediente en su lado interno.

El órgano copulador masculino es corto y grueso,sin piezas esclerotizadas aparentes en su saco inter-no (fig. 4). Los parámeros laterales son anchos en subase y acuminados en el ápice, provistos de doslargas macroquetas.

0,50 mm0,50 mm0,50 mm0,50 mm0,50 mm


EtimologíaDedicado como prueba de agradecimiento aJoaquim Virgili que ha colaborado en numerosascampañas espeleológicas de la región con sus estu-dios sobre arte rupestre de Ulldecona desde hacemás de 25 años y que en compañía de nuestrocolaborador Florentino Fadrique del Hospitalet del´Infant colectaron tan interesante especie.

ComentariosEsta especie tiene una morfología similar aSpeleotyphlus fadriquei Español, 1999; del que sesepara principalmente por su tamaño algo mayor,el color elitral mucho más claro que S. fadriquei,y especialmente por el protórax transverso en S.virgilii y alargado en S. fadriquei. El edeago esalgo más corto y robusto en S. virgilii.

Las dos especies pueden separase fácilmentesegún sus caracteres diferenciales (tabla 1).

Se actualiza la clave de las especies del géneroSpeleotyphlus Jeanne, 1973, publicada por Espa-ñol, 1999 y que permite una mayor discrimina-ción de las cinco especies conocidas.

Agradecimientos

Ante todo tenemos que agradecer a nuestro cole-ga de tantos años, el Sr. Jordi Comas, por suamabilidad en ceder el único ejemplar de S. comasi,así como por su artística colaboración al realizar

los dibujos que acompañan el presente trabajo.También hemos de agradecer al amigo FlorentinoFadrique, que tan activamente está realizando unafructífera labor bioespeleológica de exploraciónsistemática de las cavidades levantinas.

Referencias

ESPAÑOL, F., 1966. Interesantes descubrimientosbioespeleológicos en la provincia de Castellón.P. Inst. Biol. Apl., 40: 67–79.

– 1971. Nuevos Anillini cavernícolas del NE de Espa-ña (Col. Trechidae). P. Inst. Biol. Apl., 51: 79–88.

– 1999. Descripción de Speleotyphlus fadriqueisp. n., con revisión del género (Coleoptera,Carabidae). Misc. Zool., 22.1: 53–57.

JEANNE, C., 1973. Sur la classification desbembidiides endogés de la Region euro–mediterranéenne. Nou. Rev. Ent., 3: 83–102.

JEANNEL, R.,1963. Monographie des AnilliniBembidiides endogés (Coleoptera, Trechidae).Mém. Mus. Nat. Hist. Nat., Ser. A, Zool., 35(2):33–204.

VIÑOLAS, A. & ESCOLÀ, O., 1999. Microtyphlus fidelisp. n. de Anillina de la sima Latonero,Castellote, Teruel (Coleoptera, Carabidae,Bembidiini). Misc. Zool., 22.2: 85–89.

ZABALLOS, J. P. & JEANNE, C., 1994. Nuevo catálogode los carábidos (Coleoptera) de la PenínsulaIbérica. Monografías S. E. A., 1. Zaragoza.

Clave de las especies del género Speletyphlus Jeanne, 1973 actualizada.

Updated key of species of genera Speletyphlus Jeanne, 1973.

1 Superficie del cuerpo lisa, sin micro escultura;húmeros redondeados, nada salientes S. aurouxi (Español)Superficie del cuerpo provista de micro escultura;húmeros marcados y salientes 2

2 Talla igual o menor de 2 mm; cuerpo paralelo yconvexo; superficie elitral fuertemente rugosa 3Talla mayor de 2 mm; cuerpo de contorno no paralelo,muy poco convexo; superficie poco rugosa; protóraxpoco estrechado en la base S. jusmeti (Español)

3 Protórax transverso o casi; con los ángulos posterioresrectos, apenas salientes 4Protórax más largo que ancho; con losángulos posteriores muy agudos y salientes S. fadriquei Español

4 Los élitros casi el doble largos que anchos (8/4);los húmeros muy salientes S. comasi sp. n.Los élitros mas cortos (7/4) con la zonahumeral redondeada y dentada S. virgilii sp. n.

Animal Biodiversity and Conservation 25.2 (2002) I

ISSN: 1578–665X © 2002 Museu de Ciències Naturals

Animal Biodiversity and Conservation

Animal Biodiversity and Conservation (abans Miscel·lània Zoològica) és una revista interdisciplinària publicada, des de 1958, pel Museu de Zoologia de Barcelona. Inclou articles d'inves tigació empírica i teòrica en totes les àrees de la zoologia (sistemàtica, taxo nomia, morfo logia, biogeografia, ecologia, etologia, fisiologia i genètica) procedents de totes les regions del món amb especial énfasis als estudis que d'una manera o altre tinguin relevància en la biología de la conservació. La revista no publica catàlegs, llistes d'espècies o cites puntuals. Els estudis realitzats amb espècies rares o protegides poden no ser acceptats tret que els autors disposin dels permisos corresponents. Cada volum anual consta de dos fascicles.

Animal Biodiversity and Conservation es troba registrada en la majoria de les bases de dades més importants i està disponible gratuitament a internet a http://www.museuzoologia.bcn.es/servis/servis3.htm, de manera que permet una difusió mundial dels seus articles.

Tots els manuscrits són revisats per l'editor executiu, un editor i dos revisors independents, triats d'una llista internacional, a fi de garantir–ne la qualitat. El procés de revisió és ràpid i constructiu. La publicació dels treballs acceptats es fa normalment dintre dels 12 mesos posteriors a la recepció.

Una vegada hagin estat acceptats passaran a ser propietat de la revista. Aquesta es reserva els drets d’autor, i cap part dels treballs no podrà ser reproduïda sense citar–ne la procedència.

Normes de publicació

Els treballs s'enviaran preferentment de forma electrònica ([email protected]). El format preferit és un document Rich Text Format (RTF) o DOC que inclogui les figures (TIF). Si s'opta per la versió impresa, s'han d'enviar quatre còpies del treball juntament amb una còpia en disquet a la Secretaria de Redacció. Cal incloure, juntament amb l'article, una carta on es faci constar que el treball està basat en investigacions originals no publicades anterior ment i que està sotmès a Animal Biodiversity and Conservation en exclusiva. A la carta també ha de constar, per a aquells treballs en que calgui manipular animals, que els autors disposen dels permisos necessaris i que compleixen la normativa de protecció animal vigent. També es poden suggerir possibles assessors.

Quan l'article sigui acceptat, els autors hauran d'enviar a la Redacció una còpia impresa de la versió final acompanyada d'un disquet indicant el programa utilitzat (preferiblement en Word). Les proves d'impremta enviades a l'autor per a la correcció, seran retornades al Consell Editor en el termini de 10 dies. Aniran a càrrec dels autors les despeses degudes a modificacions substancials introduïdes per ells en el text original acceptat.

El primer autor rebrà 50 separates del treball sense càrrec a més d'una separata electrònica en format PDF.

Manuscrits

Els treballs seran presentats en format DIN A –4 (30 línies de 70 espais cada una) a doble espai i amb totes les pàgines numerades. Els manus crits han de ser complets, amb taules i figures. No s'han d'enviar les figures originals fins que l'article no hagi estat acceptat.

El text es podrà redactar en anglès, castellà o català. Se suggereix als autors que enviïn els seus treballs en anglès. La revista els ofereix, sense cap càrrec, un servei de correcció per part d'una persona especialitzada en revistes científiques. En tots els casos, els textos hauran de ser redactats correctament i amb un llenguatge clar i concís. La redacció del text serà impersonal, i s'evitarà sempre la primera persona.

Els caràcters cursius s’empraran per als noms científics de gèneres i d’espècies i per als neologismes intraduïbles; les cites textuals, independentment de la llengua, seran consignades en lletra rodona i entre cometes i els noms d’autor que segueixin un tàxon aniran en rodona.

Quan se citi una espècie per primera vegada en el text, es ressenyarà, sempre que sigui possible, el seu nom comú.

Els topònims s’escriuran o bé en la forma original o bé en la llengua en què estigui escrit el treball, seguint sempre el mateix criteri.

Els nombres de l’u al nou, sempre que estiguin en el text, s’escriuran amb lletres, excepte quan precedeixin una unitat de mesura. Els nombres més grans s'escriuran amb xifres excepte quan comencin una frase.

Les dates s’indicaran de la forma següent: 28 VI 99; 28, 30 VI 99 (dies 28 i 30); 28–30 VI 99 (dies 28 a 30).

S’evitaran sempre les notes a peu de pàgina.

Format dels articles

Títol. El títol serà concís, però suficientment indicador del contingut. Els títols amb desig nacions de sèries numèriques (I, II, III,...) seran acceptats previ acord amb l'editor.Nom de l’autor o els autors.Abstract en anglès que no ultrapassi les 12 línies mecanografiades (860 espais) i que mostri l’essència del manuscrit (introducció, material, mètodes, resultats i discussió). S'evitaran les especulacions i les cites bibliogràfiques. Estarà encapçalat pel títol del treball en cursiva.Key words en anglès (sis com a màxim), que orientin sobre el contingut del treball en ordre d’importància.Resumen en castellà, traducció de l'Abstract. De la traducció se'n farà càrrec la revista per a aquells autors que no siguin castellano parlants. Palabras clave en castellà.

II

Adreça postal de l’autor o autors.(Títol, Nom, Abstract, Key words, Resumen, Palabras clave i Adreça postal, conformaran la primera pàgina.)

Introducción. S'hi donarà una idea dels antecedents del tema tractat, així com dels objectius del treball.Material y métodos. Inclourà la informació pertinent de les espècies estudiades, aparells emprats, mètodes d’estudi i d’anàlisi de les dades i zona d’estudi.Resultados. En aquesta secció es presentaran únicament les dades obtingudes que no hagin estat publicades prèviament.Discusión. Es discutiran els resultats i es compararan amb treballs relacionats. Els sug geriments de recerques futures es podran incloure al final d’aquest apartat.Agradecimientos (optatiu).Referencias. Cada treball haurà d’anar acompanyat de les referències bibliogràfiques citades en el text. Les referències han de presentar–se segons els models següents (mètode Harvard):* Articles de revista:Conroy, M. J. & noon, B. r., 1996. Mapping of

species richness for conservation of biological diversity: conceptual and methodological issues. Ecological Applications, 6: 763–773.

* Llibres o altres publicacions no periòdiques:SeBer, G. A. F., 1982. The estimation of animal

abundance. C. Griffin & Company, London. * Treballs de contribució en llibres:MACdonAld, d. W. & JohnSon, d. P., 2001. Dispersal

in theory and practice: consequences for conservation biology. In: Dispersal: 358–372 (T. J. Clober, E. Danchin, A. A. Dhondt & J. D. Nichols, Eds.). Oxford University Press, Oxford.

* Tesis doctorals:Merilä, J., 1996. Genetic and quantitative trait vari

ation in natural bird populations. Tesis doctoral, Uppsala University.

* Els treballs en premsa només han d’ésser citats si han estat acceptats per a la publicació:riPoll, M. (in press). The relevance of population

studies to conservation biology: a review. Anim. Biodivers. Conserv.

La relació de referències bibliogràfiques d’un treball serà establerta i s’ordenarà alfabè ticament per autors i cronològicament per a un mateix autor, afegint les lletres a, b, c..., als treballs del mateix any. En el text, s’indi caran en la forma usual: “...segons WeMMer (1998) ... ”, “...ha estat definit per roBinSon & redFord (1991)...”, “...les prospeccions realitzades (BeGon et al., 1999)...” Quan en el text s’anomeni un autor de qui no es dóna referèn cia bibliogràfica el nom anirà en rodo na: “...un altre autor és Caughley...”Taules. Les taules es numeraran 1, 2, 3, etc. i han de ser sempre ressenyades en el text. Les taules grans seran més estretes i llargues que amples i curtes ja que s'han d'encaixar en l'amplada de la caixa de la revista. Figures. Tota classe d’il·lustracions (gràfics, figures o fotografies) entraran amb el nom de figura i es numeraran 1, 2, 3,... i han de ser sempre ressenyades en el text. Es podran incloure fotografies si són imprescindibles. La mida màxima de les figures és de 15,5 cm d'amplada per 24 cm d'alçada. S'evitaran les figures tridimensionals. Tant els mapes com els dibuixos han d'incloure l'escala. Els ombreigs preferibles són blanc, negre o trama. S'evitaran els punteigs ja que no es repro dueixen bé. Peus de figura i capçaleres de taula. Els peus de figura i les capçaleres de taula seran clars, concisos i bilingües en la llengua de l’article i en anglès.

Els títols dels apartats generals de l’article (Introducción, Material y métodos, Resultados, Discusión, Conclusiones, Agradecimientos y Referencias) no aniran numerats. No es poden utilitzar més de tres nivells de títols.

Els autors procuraran que els seus treballs originals no passin de 20 pàgines (incloent–hi figures i taules).

Si a l'article es descriuen nous tàxons, caldrà que els tipus estiguin dipositats en una insti tució pública.

Es recomana als autors la consulta de fascicles recents de la revista per tenir en compte les seves normes.

Animal Biodiversity and Conservation 25.2 (2002) III



Animal Biodiversity and Conservation (antes Miscel·lània Zoològica) es una revista interdisciplinar, publicada desde 1958 por el Museo de Zoología de Barcelona. Incluye artículos de investigación empírica y teórica en todas las áreas de la zoología (sistemática, taxo nomía, morfología, biogeografía, ecología, etología, fisiología y genética) procedentes de todas las regiones del mundo, con especial énfasis en los estudios que de una manera u otra tengan relevancia en la biología de la conservación. La revista no publica catálogos, listas de especies sin más o citas puntuales. Los estudios realizados con especies raras o protegidas pueden no ser aceptados a no ser que los autores dispongan de los permisos correspondientes. Cada volumen anual consta de dos fascículos.

Animal Biodiversity and Conservation está registrada en todas las bases de datos importantes y además está disponible gratuitamente en internet en http://www.museuzoologia.bcn.es/servis/servis3.htm, lo que permite una difusión mundial de sus artículos.

Todos los manuscritos son revisados por el editor ejecutivo, un editor y dos revisores independientes, elegidos de una lista internacional, a fin de garantizar su calidad. El proceso de revisión es rápido y constructivo, y se realiza vía correo electrónico siempre que es posible. La publicación de los trabajos aceptados se realiza con la mayor rapidez posible, normalmente dentro de los 12 meses siguientes a la recepción del trabajo.

Una vez aceptado, el trabajo pasará a ser propiedad de la revista. Ésta se reserva los derechos de autor, y ninguna parte del trabajo podrá ser reproducida sin citar su procedencia.

Normas de publicación

Los trabajos se enviarán preferentemente de forma electrónica ([email protected]). El formato preferido es un documento Rich Text Format (RTF) o DOC, que incluya las figuras (TIF). Si se opta por la versión impresa, deberán remitirse cuatro copias juntamente con una copia en disquete a la Secretaría de Redacción. Debe incluirse, con el artículo, una carta donde conste que el trabajo versa sobre inves tigaciones originales no publi cadas an te rior mente y que se somete en exclusiva a Animal Biodiversity and Conservation. En dicha carta también debe constar, para trabajos donde sea necesaria la manipulación de animales, que los autores disponen de los permisos necesarios y que han cumplido la normativa de protección animal vigente. Los autores pueden enviar también sugerencias para asesores.

Cuando el trabajo sea aceptado los autores deberán enviar a la Redacción una copia impresa de la versión final junto con un disquete del manuscrito preparado con un pro cesador de textos e

indicando el programa utilizado (preferiblemente Word). Las pruebas de imprenta enviadas a los autores deberán remitirse corregidas al Consejo Editor en el plazo máximo de 10 días. Los gastos debidos a modificaciones sustanciales en las pruebas de im pren ta, introducidas por los autores, irán a cargo de los mismos.

El primer autor recibirá 50 separatas del trabajo sin cargo alguno y una copia electrónica en formato PDF.

Manuscritos

Los trabajos se presentarán en formato DIN A–4 (30 líneas de 70 espacios cada una) a doble espacio y con las páginas numeradas. Los manuscritos deben estar completos, con tablas y figuras. No enviar las figuras originales hasta que el artículo haya sido aceptado.

El texto podrá redactarse en inglés, castellano o catalán. Se sugiere a los autores que envíen sus trabajos en inglés. La revista ofre ce, sin cargo ninguno, un servicio de corrección por parte de una persona especializada en revistas científicas. En cualquier caso debe presentarse siempre de forma correcta y con un lenguaje claro y conciso. La redacción del texto deberá ser impersonal, evitán dose siempre la primera persona.

Los caracteres en cursiva se utilizarán para los nombres científicos de géneros y especies y para los neologismos que no tengan traducción; las citas textuales, independientemente de la lengua en que estén, irán en letra redonda y entre comillas; el nombre del autor que sigue a un taxón se escribirá también en redonda.

Al citar por primera vez una especie en el trabajo, deberá especificarse siempre que sea posible su nombre común.

Los topónimos se escribirán bien en su forma original o bien en la lengua en que esté redactado el trabajo, siguiendo el mismo criterio a lo largo de todo el artículo.

Los números del uno al nueve se escribirán con letras, a excepción de cuando precedan una unidad de medida. Los números mayores de nueve se escribirán con cifras excepto al empezar una frase.

Las fechas se indicarán de la siguiente forma: 28 VI 99; 28, 30 VI 99 (días 28 y 30); 28–30 VI 99 (días 28 al 30).

Se evitarán siempre las notas a pie de página.

Formato de los artículos

Título. El título será conciso pero suficientemente explicativo del contenido del trabajo. Los títulos con designaciones de series numéricas (I, II, III, etc.) serán aceptados excepcionalmente previo consentimiento del editor.Nombre del autor o autores.Abstract en inglés de 12 líneas mecanografiadas (860 espacios como máximo) y que exprese la esencia del manuscrito (introducción, material, métodos, resultados y discusión). Se evitarán las

IV

especulaciones y las citas bibliográficas. Irá encabezado por el título del trabajo en cursiva.Key words en inglés (un máximo de seis) que especifiquen el contenido del trabajo por orden de importancia.Resumen en castellano, traducción del abstract. Su traducción puede ser solicitada a la revista en el caso de autores que no sean castellano hablan tes. Palabras clave en castellano.Dirección postal del autor o autores.(Título, Nombre, Abstract, Key words, Resumen, Palabras clave y Dirección postal conformarán la primera página.)

Introducción. En ella se dará una idea de los antecedentes del tema tratado, así como de los objetivos del trabajo.Material y métodos. Incluirá la información referente a las especies estudiadas, aparatos utilizados, metodología de estudio y análisis de los datos y zona de estudio.Resultados. En esta sección se presentarán únicamente los datos obtenidos que no hayan sido publicados previamente.Discusión. Se discutirán los resultados y se compararán con otros trabajos relacionados. Las sugerencias sobre investigaciones futuras se podrán incluir al final de este apartado.Agradecimientos (optativo).Referencias. Cada trabajo irá acompañado de una bibliografía que incluirá únicamente las publicaciones citadas en el texto. Las referencias deben presentarse según los modelos siguientes (método Harvard):* Artículos de revista:Conroy, M. J. & noon, B. r., 1996. Mapping of

species richness for conservation of biological diversity: conceptual and methodological issues. Ecological Applications, 6: 763–773

* Libros y otras publicaciones no periódicas:SeBer, G. A. F., 1982. The estimation of animal

abundance. C. Griffin & Company, London. * Trabajos de contribución en libros:MACdonAld, d. W. & JohnSon, d. P., 2001. Dispersal


* Tesis doctorales:Merilä, J., 1996. Genetic and quantitative trait vari

ation in natural bird populations. Tesis doctoral, Uppsala University.

* Los trabajos en prensa sólo se citarán si han sido aceptados para su publicación:riPoll, M. (in press). The relevance of population

studies to conservation biology: a review. Anim. Biodivers. Conserv.

Las referencias se ordenarán alfabética men te por autores, cronológicamen te para un mismo autor y con las letras a, b, c,... para los tra bajos de un mismo autor y año. En el texto las referencias bibliográficas se indicarán en la forma usual: "...según WeMMer (1998)...", "...ha sido definido por roBinSon & redFord (1991)...", "...las prospecciones realizadas (BeGon et al., 1999)..." Cuando en el texto se mencione un autor no incluido en la bibliografía el nombre irá en redonda: "...otro autor es Caughley..."Tablas. Las tablas se numerarán 1, 2, 3, etc. y se reseñarán todas en el texto. Las tablas grandes deben ser más estrechas y largas que anchas y cortas ya que deben ajustarse a la caja de la revista.Figuras. Toda clase de ilustraciones (gráficas, figuras o fotografías) se considerarán figuras, se numerarán 1, 2, 3, etc., y se citarán todas en el texto. Pueden incluirse fotografías si son imprescindibles. El tamaño máximo de las figuras es de 15,5 cm de ancho y 24 cm de alto. Deben evitarse las figuras tridimen sionales. Tanto los mapas como los dibujos deben incluir la escala. Los sombreados preferibles son blanco, negro o trama. Deben evitarse los punteados ya que no se reproducen bien.Pies de figura y cabeceras de tabla. Los pies de figura y cabeceras de tabla serán claros, concisos y bilingües en castellano e inglés.

Los títulos de los apartados generales del artículo (Introducción, Material y métodos, Resultados, Discusión, Agradecimientos y Referencias) no se numerarán. No utilizar más de tres niveles de títulos.

Los autores procurarán que sus trabajos originales no excedan las 20 páginas incluidas figuras y tablas.

Si en el artículo se describen nuevos taxones, es imprescindible que los tipos estén depositados en alguna institución pública.

Se recomienda a los autores la consulta de fascículos recientes de la revista para seguir sus directrices.

Animal Biodiversity and Conservation 25.2 (2002) V



Animal Biodiversity and Conservation (formerly Miscel·lània Zoològica) is an inter dis ci pli nary journal which has been published by the Zoological Museum of Bar celona since 1958. It includes empirical and theoretical research in all aspects of Zoology (Systematics, Taxo nomy, Morphology, Bio geography, Ecology, Etho logy, Physio logy and Genetics) from all over the world with special emphasis on studies that stress the relevance of the study of Conservation Biology. The journal does not publish catalogues, lists of species (with no other relevance) or punctual records. Studies about rare or protected species will not be accepted unless the authors have been granted all the relevant permits. Each annual volume consists of two issues.

Animal Biodiversity and Conservation is registered in all principal data bases and is freely available online at http://www.museuzoologia.bcn.es /servis/ABCag.htm, thus assuring world–wide access to articles published therein.

All manuscripts are screened by the Executive Editor, an Editor and two independent reviewers in order to guarantee the quality of the papers. The process of review is rapid and constructive. Once accepted, papers are published as soon as practicable, usually within 12 months of initial submission.

Upon acceptance, manuscripts become the property of the journal, which reserves copyright, and no published material may be reproduced without quoting its origin.

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Electronic submission of papers is encouraged (publi[email protected]). The preferred format is a document Rich Text Format (RTF) or DOC, including figures (TIF). In the case of sending a printed version, four copies should be sent together with a copy on a computer disc to the Editorial Office. A cover letter stating that the article reports on original research not published elsewhere and that it has been submitted exclusively for consideration in Animal Biodiversity and Conservation is also necessary. When animal manipulation has been necessary, the cover letter should also especify that the authors follow current norms on the protection of animal species and that they have obtained all relevant permissions. Authors may suggest referees for their papers.

Once an article has been accepted, authors should send a printed copy of the final version together with a disc. Please identify software (preferably Word). Proofs sent to the authors for correction should be returned to the Editorial Board within 10 days. Expenses due to any substantial alterations of the proofs will be charged to the authors.

The first author will receive 50 reprints free of charge and an electronic version of the article in PDF format.

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Manuscripts must be presented on A–4 format page (30 lines of 70 spaces each) with double spacing. Number all pages. Manuscripts should be complete with figures and tables. Do not send original figures until the paper has been accepted.

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Italics must be used for scientific names of genera and species as well as untrans latable neologisms. Quotations in whatever language used must be typed in ordinary print between quotation marks. The name of the author following a taxon should also be written in small print.

The common name of the species should be written in capital letters. When referring to a species for the first time in the text, both common and scientific names must be given when possible.

Place names may appear either in their original form or in the language of the manuscript, but care should be taken to use the same criteria throughout the text.

Numbers one to nine should be written in full in the text except when preceding a measure. Higher numbers should be written in numerals except at the beginning of a sentence.

Dates must appear as follows: 28 VI 99, 28,30 VI 99 (days 28th and 30th), 28–30 VI 99 (days 28th to 30th).

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Formatting of articles

Title. The title must be concise but as infor mative as possible. Part numbers (I, II, III,...) should be avoided and will be subject to the Editor’s consent.Name of author or authors.Abstract in English, no longer than 12 type written lines (840 spaces), covering the con tents of the article (introduction, material, methods, results and discussion). Speculation and literature citation must be avoided. Abstract should begin with the title in italics.Key words in English (no more than six) should express the precise contents of the manuscript in order of importance.Resumen in Spanish, translation of the Abstract.Summaries of articles by non –Spanish speaking authors will be trans lated by the journal on request. Palabras clave in Spanish.Address of the author or authors.(Title, Name, Abstract, Key words, Resumen, Palabras clave and Address should constitute the first page.)

Introduction. The introduction should in clude the historical background of the sub ject as well as the

VI

aims of the paper.Material and methods. This section should provide relevant information on the species studied, materials, methods for collecting and analysing data and the study area.Results. Report only previously unpublished results from the present study.Discussion. The results and their comparison with related studies should be discussed. Sug gestions for future research may be given at the end of this section.Acknowledgements (optional).References. All manuscripts must include a bibliography of the publications cited in the text. References should be presented as in the following examples (Harvard method):* Journal articles:Conroy, M. J. & noon, B. r., 1996. Mapping of

species richness for conservation of biological diversity: conceptual and methodological issues. Ecological Applications, 6: 763–773.

* Books or other non–periodical publications:SeBer, G. A. F., 1982. The estimation of animal

abundance. C. Griffin & Company, London.* Contributions or chapters of books:MACdonAld, d. W. & JohnSon, d. P., 2001. Dispersal


* Ph. D. Thesis:Merilä, J., 1996. Genetic and quantitative trait vari

ation in natural bird populations. Ph. D. Thesis, Uppsala University.

* Works in press should only be cited if they have been accepted for publication:riPoll, M. (in press). The relevance of population

studies to conservation biology: a review. Anim. Biodivers. Conserv. References must be set out in alphabetical

and chronological order for each author, add

ing the letters a, b, c,... to papers of the same year. Biblio graphic citations in the text must appear in the usual way: "...according to WeM-Mer (1998)...", "...has been defined by roBinSon & redFord (1991)...", "...the pros pec tions that have been carried out (BeGon et al., 1999)..." When an author is men tioned in the text but no bibliographical re ference is given, the name must appear in ordinary print: "...another of these authors is Caughley..."Tables. Tables must be numbered in Arabic numerals with reference in the text. Large tables should be narrow (across the page) and long (down the page) rather than wide and short, so that they can be fitted into the column width of the journal.Figures. All illustrations (graphs, drawings or photographs) must be termed as figures, numbered consecutively in Arabic numerals and with re ference in the text. Glossy print photographs, if essential, may be included. Maximum size of figures is 15.5 cm width and 24 cm height. Figures will not be tridimen sional. Both maps and drawings must include scale. The preferred shadings are white, black and bold hatching. Avoid stippling, which does not reproduce well. Legends of tables and figures. Legends of tables and figures must be clear, concise, and written both in English and Spanish.

Main headings (Introduction, Material and methods, Results, Discussion, Acknowled ge ments and References) should not be number ed. Do not use more than three levels of headings.

Manuscripts should not exceed 20 pages including figures and tables.

If the article describes new taxa, type material must be deposited in a public institution.

Authors are advised to consult recent issues of the journal and follow its conventions.

VIIAnimal Biodiversity and Conservation 25.2 (2002)

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Les cites o els abstracts dels articles d’Animal Biodiversity and Conservation es resenyen a /Las citas o los abstracts de los artículos de Animal Biodiversity and Conservation se mencionan en /Animal Biodiversity and Conservation is cited or abstracted in:

Abstracts of Entomology, Agrindex, Animal Behaviour Abstracts, Anthropos, Aquatic Sciences and Fisheries Abstracts, Behavioural Biology Abstracts, Biological Abstracts, Biological and Agricultural Abstracts, Current Primate References, Ecological Abstracts, Ecology Abstracts, Entomology Abstracts, Environmental Abstracts, Environmental Periodical Bibliography, Genetic Abstracts, Geographical Abstracts, Índice Español de Ciencia y Tecnología, International Abstracts of Biological Sciences, International Bibliography of Periodical Litera-ture, International Developmental Abstracts, Marine Sciences Contents Tables, Oceanic Abstracts, Recent Ornithological Literature, Referatirnyi Zhurnal, Science Abstracts, Serials Directory, Ulrich’s International Periodical Directory, Zoological Records.

Animal Biodiversity and Conservation 25.2 (2002) ISSN 1578–665X

Índex / Índice / Contents

1–5Deharveng, L. & SmoLiS, a.Pronura bidoup n. sp. (Collembola, Neanuri-dae, Neanurinae, Paleonurini) from southern Vietnam

7–45FowLer, C. w. & hobbS, L. ReviewLimits to natural variation: implications for systemic management

47–51martínez–abrain, a., oro, D., FerriS, v. & beLenguer, r.Is growing tourist activity affecting the distri-bution or number of breeding pairs in a small colony of the Eleonora’s Falcon?

53–66nekoLa, J. C. ReviewEffects of fire management on the richness and abundance of central North American grassland land snail faunas

67–74raniuS, t. & DouweS, P. Genetic structure of two pseudoscorpion species living in tree hollows in Sweden

75–93Sanmartín, i. & ronquiSt, F.New solutions to old problems: widespread taxa, redundant distributions and missing areas in event–based biogeography

95–99viveSH, J., eSCoLà, o. & viveS, e.Dos nuevas especies de Anillini cavernícolas pertenecientes al género Speleotyphlus Jeanne, 1973 (Coleoptera, Carabidae)

animal biodiversity and conservation issue 25.2 (2002)

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