biodiversity conservation, yield, and alternative products in covee

Biodivers Conserv (2008) 17:1805–1820 DOI 10.1007/s10531-007-9267-2

ORIGINAL PAPER

Biodiversity conservation, yield, and alternative products in coVee agroecosystems in Sumatra, Indonesia

Stacy M. Philpott · Peter Bichier · Robert A. Rice · Russell Greenberg

Received: 27 April 2007 / Accepted: 23 October 2007 / Published online: 6 November 2007© Springer Science+Business Media B.V. 2007

Abstract Agroecology and conservation must overlap to protect biodiversity and farmerlivelihoods. CoVee agroecosystems with complex shade canopies protect biodiversity. Yet,few have examined biodiversity in coVee agroecosystems in Asia relative to the Americasand many question whether coVee agroecosystems can play a similar role for conservation.We examined vegetation, ant and bird diversity, coVee yields and revenues, and harvest ofalternative products in coVee farms and forests in SW Sumatra, Indonesia near BukitBarisan Selatan National Park (BBS). BBS is among the last habitats for large mammals inSumatra and >15,000 families illegally cultivate coVee inside of BBS. As a basis for inform-ing management recommendations, we compared the conservation potential and economicoutputs from farms inside and outside of BBS. Forests had higher canopy cover, canopydepth, tree height, epiphyte loads, and more emergent trees than coVee farms. CoVee farmsinside BBS had more epiphytes and trees and fewer coVee plants than farms outside BBS.Tree, ant, and bird richness was signiWcantly greater in forests than in coVee farms, and rich-ness did not diVer in coVee farms inside and outside of BBS. Species similarity of forest andcoVee trees, ants, and birds was generally low (<50%). Surprisingly, farms inside the parkwere signiWcantly older, but farm size, coVee yields, and revenues from coVee did notdepend on farm location. Farmers outside BBS received higher prices for their coVee andalso more often produced other crops in their coVee Welds such that incentives could becreated to draw illegal farmers out of the park. We also discuss these results with referenceto similar work in Chiapas, Mexico to compare the relative contribution of coVee Welds toconservation in the two continents, and discuss implications for working with farmers inSumatra towards conservation plans incorporating sustainable coVee production.

S. M. Philpott · P. Bichier · R. A. Rice · R. GreenbergSmithsonian Migratory Bird Center, National Zoological Park, 3001 Connecticut Ave. NW, Washington, DC 20008, USA

S. M. Philpott (&)Department of Environmental Sciences, University of Toledo, 2801 W. Bancroft St, Toledo, OH 43606, USAe-mail: [email protected]

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1806 Biodivers Conserv (2008) 17:1805–1820

Keywords Alternative products · Ants · Birds · CoVee agroecosystem · Indonesia · Revenue · Species similarity · Trees

Introduction

Understanding the causes and consequences of tropical biodiversity loss is a priority inconservation biology. Because agriculture covers a high proportion of arable lands (Young1999) it is often viewed as a detriment to biodiversity conservation. However, conservationbiologists and economists increasingly acknowledge a need to incorporate sustainable agri-culture into tropical conservation strategies (Angelsen and Kaimowitz 2001; McNeeley andScherr 2003). CoVee agroecosystems have received substantial attention because of theireconomic and ecological importance. CoVee is the second-largest export commodity ofdeveloping countries (O’Brien and Kinnaird 2003) and provides livelihood to millions.Furthermore, coVee production areas overlap with areas of conservation concern (Hardnerand Rice 2002) and in many regions coVee farms provide much of remaining tree cover(Rice and Ward 1996; Panayotou et al. 1997). Some argue that increased agricultural inten-sity per unit area will allow for more protected land to be set aside (O’Brien and Kinnaird2003; Green et al. 2005), but both agricultural management and market Xuctuations incrops may strongly inXuence what happens in surrounding natural habitats (Philpott andDietsch 2003; Vandermeer and Perfecto 2007). For these reasons incorporating sustainablymanaged agroecosystems such as some coVee systems, into conservation plans is criticallyimportant.

CoVee was traditionally cultivated under a shade canopy, and where still practiced,farms are prized for protecting biodiversity and enhancing ecosystem services. Highlyshaded farms including systems with coVee planted under a native forest canopy or adiverse planted shade provide important habitat refuges for biodiversity in some regions(Perfecto et al. 1996; Philpott and Armbrecht 2006; Perfecto et al. 2007). Additionally,shaded farms facilitate dispersal of forest fauna between fragments and plant and animalbiodiversity found within shaded coVee systems can augment ecosystem services like pestcontrol, pollination, weed control, fungal disease limitation, erosion control, and carbonsequestration (e.g., Beer et al. 1998; Perfecto et al. 2007). But intensiWcation of the coVeesystem (reducing shade density and diversity) provokes losses of mammal, bird, and arthro-pod diversity (i.e., Philpott and Armbrecht 2006; Perfecto et al. 2007). Although it isincreasingly clear that vegetatively complex farms protect biodiversity, it is the over-whelming perception of farmers that increasing shade cover in farms will diminish yields(Perfecto et al. 2005). Yet, in the scientiWc literature, there are contradictory results regard-ing the relationships between canopy cover, yields, and proWts. Some studies have found10–30% increases in yields when shade is removed, whereas other studies Wnd no eVect ofshade on yields, or Wnd maximum yields at intermediate levels of canopy cover (Perfectoet al. 2005). For CoVea canephora (robusta coVee), shade cover can directly increase yieldsespecially where soil conditions are sub-optimal (DaMatta 2004). For C. arabica (arabicacoVee) yields may be greatest under 35–65% shade cover (Soto-Pinto et al. 2000; Staveret al. 2001; Perfecto et al. 2005). Shade is also associated with increased ecosystem ser-vices such as pollination and fruit set (Klein et al. 2003a, b), reduced pathogen infectionand weed growth (Soto-Pinto et al. 2002), and reduced losses from frost (DaMatta 2004)—factors directly relating to increased yields and/or proWts. One examination of relationshipsbetween bird biodiversity and incomes found there was no clear reduction in net revenue infarms with higher bird biodiversity (Gordon et al. 2006). In fact, their study sites with the

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Biodivers Conserv (2008) 17:1805–1820 1807

highest and second highest forest bird richness (out of 11 sites) had relatively high yields(third and sixth place) and the highest and third highest net revenues considering that thesetwo sites also received price premiums for organic certiWcation (Gordon et al. 2006). Thus,in sum, there are not obvious negative or linear relationships between biodiversity, yield,and proWtability, but instead, complicated relationships involving coVee prices, shadecover, pests and disease, non-coVee products and price premiums are involved.

Because of diVerences in agricultural landscapes, and coVee management, the role ofcoVee as a sustainable solution may signiWcantly diVer in coVee growing regions. Forexample, although shade coVee production is often hailed in Latin America, some arguethat shade coVee, as a conservation strategy, cannot work in some areas of Asia because ofthe growing conditions, species of coVee grown, or because the coVee habitats themselvescannot protect the species that are targets of conservation concern (e.g., O’Brien andKinnaird 2003). Although estimates diVer, the Lampung province of Sumatra, Indonesia,has a forest cover somewhere between 10 and 35% (Suyanto 2000; World Bank 2001).Most of this forest cover is contained in approximately 270,000 ha of mostly contiguousforest in Bukit Barisan Selatan National Park (BBS) (WWF 2007). BBS provides most ofthe last remaining habitat in this area for protection of important endangered species suchas the Sumatran tiger, Asian elephant, and Sumatran rhinoceros (O’Brien et al. 2003).Another 45,000 ha of the park (»14% of the total Park area) consist of several largeencroachment areas that are currently in coVee production. Transmigration programs in the1970’s and promotion of sun coVee by Asian governments in the 1990’s encouraged theseencroachments into BBS threatening forests and key wildlife (O’Brien and Kinnaird 2003;WWF 2007). Now, over 15,000 families illegally grow coVee inside the Park (WWF 2007).Generally, most coVee in Lampung, especially that grown directly around BBS is perceivedto oVer little conservation value (i.e., O’Brien and Kinnaird 2003), but few have investi-gated coVee habitats and biodiversity therein. Park staV and conservation organizations inthe region place much emphasis on removing farmers from the park, but little work hasbeen done to examine how farms inside and outside of BBS compare in terms of their rela-tive biodiversity value, yields, or contributions to farmer revenue. Ensuring that farmers donot have added Wnancial incentives for growing inside the park is important, as is docu-menting speciWcally the shade management practices of these farmers.

Studies are needed to understand whether coVee systems near and inside of BBS con-tribute to conserving the biodiversity of the original forest ecosystems both inside and out-side of the Park. Further, we should examine whether diVerences in actual or potentialproWtability of coVee farms in and outside the Park provide incentives for farmers to farmoutside rather than inside the park, or whether such incentives could be created throughappropriate interventions. To begin to amend this lack of empirical data, we speciWcallyaddressed the following questions using ecological studies and farmer surveys both incoVee farms located inside and outside of BBS: (1) Does vegetative complexity (Xoristicdiversity and structure) of coVee farms diVer in the two areas? (2) How do numbers of spe-cies, % of forest species, and similarity of species assemblages of trees, ants, and birdsfound in coVee and forest habitats compare? (3) Do coVee yields and revenues from coVeeproduction diVer? (4) Do farmers grow alternative products or have outside revenuesources? We chose to study birds, ants, and trees as these taxonomic groups have receivedthe most attention in the coVee literature from the Americas. Furthermore, birds and antsare often hailed as important indicator species, and both provide important ecosystem ser-vices such as pest control, seed dispersal, and soil aeration (Philpott and Armbrecht 2006;Perfecto et al. 2007). Furthermore, ants represent large fractions of the biomass present intropical forests (Davidson et al. 2003), and remain very understudied in Sumatra. To

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answer these questions, we examined coVee farms and nearby forests comparing vegetationcharacteristics, ant, and bird diversity. We also investigated economic information onyields, revenue from coVee, and alternative crops provided by farmers to examine relation-ships between biodiversity, yields, and incomes.

Methodology

We conducted Weld studies in the Lampung province of Sumatra, Indonesia in and aroundBukit Barisan Selatan National Park (BBS) between March and May 2005. We set up studysites in three regions: (a) North BBS near Lake Ranau (in the communities of Suka Banjar[104°26� E, 4°56� S], Talang Suharto [103°49� E, 4°54� S], and in BBS forest [103°50� E,4°56� S]), (b) Central BBS near Sukabumi (Sidodadi [104°9� E, 5°6� S], Kububalak[104°13� E, 5°7� S], and in BBS forest [104°10� E, 5°7� S]), and (c) South BBS nearSedayu (Kuyung Arang [104°26� E, 5°31� S], Kali Sembilan [104°27� E, 5°32� S], and inBBS forest [104°25� E, 5°32� S]) (Fig. 1). In each region, we established one study site inthe BBS forest, one study site in a coVee-growing area outside of BBS, and one site in acoVee-growing area located within the park boundaries (inside of BBS). Most farmers inthis region of Sumatra, and all farms included in our study, cultivate CoVea canephora (orrobusta) coVee. CoVee sites were selected such that areas inside and outside of the parkwere equidistant to forest, and areas between study sites and forests where large matrices ofagricultural (mostly coVee) land. In each site, we sampled 40 study plots for a total of 120plots in forest, and 240 in coVee. Plots consisted of 25-m radius circles at least 100 m fromany other plot. In each plot, we recorded elevation, assessed Xoristic and structural diver-sity and sampled ant and bird diversity.

Fig. 1 Map showing the distribution of study sites in and around Bukit Barisan Selatan National Park in theLampung province of Sumatra, Indonesia

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To quantify vegetation, we counted numbers of shade trees, coVee plants, and epiphytes,and recorded species and height of each tree. At Wve points per plot (at the circle center and10 m to the north, south, east, and west) we measured canopy cover using a convex spheri-cal densitometer and estimated height of low and high points of vegetation overhead to cal-culate average canopy depth. We sampled vegetation >18 m tall using a rangeWnder. Treeswere identiWed in the Weld and unknown trees were given a unique morphospecies number.Using vegetation data, we created a vegetation complexity index to summarize farm man-agement strategy (similar to the management index of Mas and Dietsch 2003). Raw valuesfor each variable (per plot) were converted numbers on a scale from 0 (least complex vege-tation) to 1 (most complex vegetation). To convert most variables (no. trees, no. tree spe-cies, vegetation depth, average tree height, percent shade cover, no. epiphytes, and percentemergent trees (>15 m)) we divided each measurement by the highest recorded value. ForcoVee density, proportional to management intensity, we divided each measurement by thehighest recorded value and subtracted this from one. We summed values for each variablefor a possible total of 8 per plot, and divided by the total number of variables to obtain avalue between 0 and 1. The vegetation complexity index for forest samples diVered in thatcoVee densities were not included and thus the sum was divided by 7, the total number offorest variables. We used univariate analyses of variance (ANOVA) with Bonferonni cor-rections (� = 0.00625) to test for diVerences in the eight vegetation variables and a separateANVOA to examine diVerences in the vegetation complexity index. We used Tukey’spost-hoc tests to distinguish between habitat types (forest vs. coVee inside vs. coVee out-side). Numbers of epiphytes and trees and tree heights were log-transformed to meet condi-tions of normality.

We sampled ants using two methods. First, we used mini-winkler traps to sample a 1 m2

area of leaf litter randomly taken from inside the circular plots following standard protocolfor sampling leaf-litter ants (Agosti and Alonso 2000). We chopped leaf litter then sifted itfor approximately 5 min per sample. We place sifted litter (including arthropods) into meshbags that remained inside traps aYxed with alcohol-Wlled cups for 48 h. We then removedall ants from cups and stored them in 70% alcohol for later identiWcation. We also sampledants using visual and nest searches on the coVee plants. In each plot, we searched 4 haphaz-ardly selected coVee plants (or understory plants in forest plots) that were Wrst shaken todisturb workers. We broke oV all dry twigs on coVee or understory plants examining for antoccupants. All ants seen were collected for later identiWcation. We combined both samplingmethods for biodiversity analyses. All ants were identiWed by SMP with assistance frommyrmecologists at Harvard University and the Smithsonian Institution. Voucher specimenshave been deposited in LIPI Cibinong (Bogor, Indonesia).

We surveyed birds by sight and sound with 10 min point counts in each of the 25-mplots (Hutto et al. 1986; Petit et al. 1994). In coVee plots, all birds were easily seen andidentiWcations conWrmed with Weld guides. In forest plots, where some birds were heard butnot seen, sound recordings were made and later compared audio recordings of Birds ofTropical Asia 3.0 to conWrm identiWcations. Fewer than 5% of birds were identiWed usingrecordings.

To compare tree, ant, and bird richness in coVee and forest sites, we generated sample-based rarefaction curves (MaoTao estimates) with EstimateS Version 7.5 (Colwell andCoddington 1994). We rescaled sample-based rarefaction curves to the number of individu-als (or occurrences for ants) to best compare richness between sites (Gotelli and Colwell2001; Longino et al. 2002). Statistical comparisons of richness are made possible usingMaoTao estimates and the corresponding 95% conWdence intervals both produced usinganalytical formulas. We examined similarity in ant, bird, and tree species composition in

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the coVee and forest plots using similarity indices calculated by EstimateS and by examin-ing raw numbers of shared species in each habitat type. We compared the composition ofeach coVee site (inside and outside of BBS) to the forest site in that same area for a total ofsix comparisons. For each comparison, all tree, ant, or bird species found in coVee plots ofone site made up one sample, and all species found in forest plots comprised the secondsample. We also compared species similarity between forest plots in each area (three com-parisons). We used the Bray–Curtis and Jaccard Similarity Indices (Magurran 1988) andthe Chao-Jaccard Raw Abundance and Chao-Jaccard Estimated Abundance Indices(CJEAI; Chao et al. 2005). The latter two of these indices is based on the probability thattwo individuals, chosen at random from two samples, belong to a species shared by both,but not necessarily the same species. The CJEAI includes a bias correction for those spe-cies that may occur in a site, even if not encountered in samples. Because we made a totalof three comparisons between coVee inside or outside of BBS and forest plots, we wereable to statistically compare whether coVee inside or outside of the park had more similarspecies composition to forest plots with ANOVA with Tukey’s post-hoc tests to distinguishcomparisons.

Local project interviewers carried out informal surveys with farmers to investigate: (1)age and size of coVee production area, (2) total coVee yield and revenue from coVee pro-duction, (3) costs for agrochemicals including herbicides, fertilizers, or pesticides, (4) num-ber and types of alternative products, and (5) revenue from oV-farm jobs. In eachcommunity visited, we haphazardly selected and interviewed 10 farmers for a total of 60.We examined for diVerences in coVee landholding, coVee yields, coVee price, and grossrevenue per hectare, and agrochemical costs for farmers inside and outside of BBS usingunivariate analysis of variance with location as the grouping factor. We summarized thenumber of farmers growing or not growing alternative products in their coVee plots, andexamined frequencies with Fisher exact tests. Finally, to examine for relationships betweenmanagement intensity and coVee yield per hectare we performed linear regressions withcoVee yields per hectare as the dependent variable and both management index and percentcanopy cover as the dependent variable. Each study site represented one point in the regres-sion (n = 6). We used log-transformed data to meet conditions of normality.

Results

Vegetation and tree, ant, and bird richness

CoVee sites inside BBS, coVee sites outside BBS and forest plots all signiWcantly diVeredin terms of vegetation characters and the vegetation complexity index (ANOVAS for eachvariable examined, F2,357 > 8.525, P < 0.001, Table 1). There was a fairly large range incanopy cover between diVerent coVee sites (22 to 46%), but canopy cover was nearly threetimes as high in the forests (91.5%) than in coVee plots (33.3% outside of BBS and 31.1%inside of BBS) (Table 1). Further, canopy vegetation was more than twice as thick, speciesrichness per plot was nearly double, and mean tree height was higher in the forests than incoVee plots (Table 1). There were almost twice as many epiphytes in forests than coVeeplots inside the park, and ten times as many as outside the park. The only variable that didnot diVer between forests and both coVee locations was tree density; there were similarnumbers of trees per plot in forests and coVee farms inside the park, with signiWcantlyfewer trees in farms outside of the park (Table 1). CoVee plots inside BBS had Wve times asmany epiphytes as those outside, 40% more trees, and 20% lower coVee densities than

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farms outside the park (Table 1). The vegetation complexity index diVered in each habitattype with forests having the highest vegetation complexity, coVee farms inside intermedi-ate, and coVee farms outside with the lowest vegetation complexity index (Table 1,F2,357 = 1284.32, P < 0.001).

In the vegetation surveys, we recorded a total of 160 tree morphospecies and 9,435 indi-viduals in forest plots, 105 morphospecies and 4,994 individuals in coVee plots outside ofBBS and 93 morphospecies and 8362 individuals in coVee plots inside of BBS (Fig. 2a).Including only those species that could be identiWed at least to family or using a commonname, we found 141 morphospecies in forest plots, 92 in coVee plots outside of BBS and 90in coVee plots inside of BBS. Species richness was signiWcantly higher in forests than ineither coVee habitats, but tree richness did not diVer between coVee plots inside and outsideof BBS. The most commonly seen trees in the forest plots were: Eugenia sp. 1 (14.6%),unknown Annonaceae species (9.7%), Dysoxylum sp. 1 (7.6%), Aglaia sp. 1 (4.3%), andLitsea sp. 1 (3.9%). In the coVee plots outside BBS, the most common trees were Gliricidiasepium (35.8%), Erythrina subumbrans (34.7%), Leucaena leucocephala (4.2%), Perseaamericana (3.6%), and Parkia sp. (3.2%). In the coVee farms inside BBS, the most com-mon trees were Calliandra sp. 1 (61.7%), Dalbergia latifolia (11.0%), Gliricidia sepium(7.3%), Erytrhina suburbans (7.1%), and Cinnamomum sp. 1 (2.5%). Of note, Gliricidiasepium, Leucaena leucocephala, Persea americana, and Calliandra spp. are not native toSE Asia.

We recorded a total of 214 morphospecies of ants in 3,869 occurrences. We found 171in BBS forest plots, 125 in coVee outside of BBS, and 136 morphospecies in the coVeeplots inside BBS (Fig. 2b). The ants collected belong to 9 subfamilies: Aenictinae (1 spe-cies), Amblyoponinae (1), Cerapachyinae (4), Dolichoderinae (13), Dorylinae (1), Form-icinae (47), Myrmecinae (107), Poneromorphs (37), and Pseudomyrmecinae (3). The mostcommonly encountered morphospecies in the forest were: Romblonella sp. 1 (67 occur-rences), Strumigenys sp. 1 (58), Ponera sp. 7 (57), Pheidole sp. 28 (49), and Tapinoma sp.4 (47). In the coVee plots outside of BBS, the most common ants were: Crematogasterlongipilosa (59 occurrences), Dolichoderus sp. 2 (59), Pheidole sp. 28 (48), Strumigenyssp. 1 (46), and Pheidole sp. 18 (45). In the coVee plots inside BBS, the most commonly

Table 1 Vegetation characteristics and vegetation complexity index (mean § standard error) of coVee farmsinside and outside of Bukit Barisan Selatan National Park and in forest plots within the Park in Lampung,Sumatra, Indonesia

All variables showed signiWcant diVerences between the three habitats (forests, coVee inside BBS, and coVeeoutside BBS), and coVee sites inside and outside diVered in 4 of 9 variables measured. SigniWcant diVerencesbetween plots are shown with small letters. See text for an explanation of the Vegetation complexity index

Forest CoVee

Inside BBS Outside BBS

Canopy cover (%) 0.915 § 0.007a 0.333 § 0.017b 0.311 § 0.016bVegetation depth (m) 21.25 § 0.598a 8.770 § 0.407b 8.312 § 0.356bNo. coVee bushes na 239.417 § 6.565b 310.733 § 6.972aNo. Epiphytes 100.808 § 6.907a 55.917 § 6.375b 10.358 § 1.304c# Tree individuals 78.625 § 3.092a 69.683 § 10.766a 41.617 § 2.395b# Tree species 9.45 § 0.245a 5.583 § 0.199b 5.35 § 0.239bMean tree height (m) 11.563 § 0.490a 9.368 § 0.315b 9.474 § 0.267bEmergent trees (%) 0.209 § 0.012a 0.123 § 0.017b 0.133 § 0.016bVegetation complexity index 0.5316 § 0.005a 0.237 § 0.005b 0.199 § 0.005c

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Fig. 2 Species accumulation curves for trees (a), ants (b), and birds (c) in forests and coVee plots inside andoutside of Bukit Barisan Selatan National Park in Lampung province, Sumatra, Indonesia. Error bars show95% conWdence intervals and non-overlapping bars show signiWcant diVerences between habitat types

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encountered ants were: Tapinoma sp. 4 (74 encounters), Strumigenys sp. 1 (57), Crema-togaster sp. 9 (55), Strumigenys konings-bergeri (51), and Podomyrma sp. 1 (44). Antrichness was signiWcantly higher in the forests than in coVee plots, but ant richness incoVee farms inside and outside BBS did not diVer (Fig. 2b).

Overall, we recorded a total 157 bird species during point count censuses during 20 h ofobservation; an additional 23 species were seen in the study habitats during other times. Wefound 107 species and 802 individuals in BBS forest plots, 64 species and 700 individualsin coVee outside BBS, and 52 bird species and 625 individuals in the coVee plots insideBBS. The most commonly encountered species in the forest were: Rufous–Browed Fly-catcher (Ficedula solitaries; 50 individuals), Oriental White-Eye (Zosterops palpebrosus;43), Black-capped White-Eye (Zosterops atricapilla; 42), Grey-throated Babbler (Stachyrisnigriceps; 39), and the Golden Babbler (Stachyris chrysaea); 38). In the coVee plots outsideof BBS, the most common birds were the Orange-bellied Flowerpecker (Dicaeum trigono-stigma; 103 individuals), Sooty-headed Bulbul (Pycnonotus aurigaster; 93), Ashy Tailor-bird (Orthotomus ruWceps; 64), Black-crested Bulbul (Pycnonotus melanicterus; 58), andthe Bar-winged Prinia (Prinia familiaris; 48). In the coVee plots inside BBS, the most com-monly encountered birds were the Orange-bellied Flowerpecker (Dicaeum trigonostigma;117 individuals), Black-crested Bulbul (Pycnonotus melanicterus; 53), Ashy Tailorbird(Orthotomus ruWceps; 46), Hill Prinia (Prinia atrogularis; 42), and Sooty-headed Bulbul(Pycnonotus aurigaster; 42). Bird richness was signiWcantly higher in the forest than incoVee plots, yet bird richness did not diVer in coVee plots inside and outside BBS (Fig. 2c).

In general, species similarity between coVee and forest plots was low for trees, birds,and ants. Of all tree species recorded, 37.2% were shared between coVee plots inside andoutside, 22.7% were shared between coVee inside BBS and forest, and only 17.2% wereshared between coVee outside BBS and forest. Yet, according to similarity indices exam-ined, tree species similarity with forests was not higher in coVee plots inside or outside ofBBS (ANOVA; Bray–Curtis (F2,8 = 0.375, P = 0.702), Jaccard (F2,8 = 0.414, P = 0.678),Chao–Jaccard Raw (F2,8 = 0.484, P = 0.638) Chao–Jaccard Estimated (F2,8 = 0.428,P = 0.670)). Ant species similarity between habitat types was somewhat higher than fortrees, but still just over half (57.8%) of the ant species were shared between coVee plotsinside and outside, 55.0% were shared between coVee inside BBS and forest, and 50.0% ofants were shared between coVee outside BBS and forest. Again, similarity of coVee antassemblages with forest fauna did signiWcantly diVer with coVee farm location (ANOVA;Bray–Curtis (F2,8 = 0.155, P = 0.859), Jaccard (F2,8 = 0.518, P = 0.620), Chao–JaccardRaw (F2,8 = 0.123, P = 0.886) Chao–Jaccard Estimated (F2,8 = 0.040, P = 0.961)). Finally,bird species similarity between habitat types was relatively low; 19.7% of species wereshared between coVee plots inside and outside, 17.8% were shared between coVee insideBBS and forest, and 21.0% were shared between coVee outside BBS and forest. Similarityof coVee bird assemblages with forest fauna did not diVer with coVee farm location(ANOVA; Bray–Curtis (F2,8 = 1.502, P = 0.296), Jaccard (F2,8 = 6.884, P = 0.028[Tukey’s test show diVerences between forest–forest similarity and forest–coVee similarity,but not between coVee inside and outside BBS]), Chao–Jaccard Raw (F2,8 = 1.827,P = 0.240) Chao–Jaccard Estimated (F2,8 = 1.526, P = 0.291)).

Farmer interviews

The farmer surveys were conducted with ten farmers in each village for a total of 30 sur-veys of farmers farming inside BBS and 30 farming outside BBS. First, the coVee plots thatwe sampled inside the park were signiWcantly older, and coVee plants in their Welds had

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been there for signiWcantly longer than for those plots and plants outside the park (Table 2).The farmers outside of BBS were paid a higher price per kg for their coVee than were thefarmers inside (Table 2). The amount of coVee produced by each farmer, the total land areain coVee, the amount of money spent on agrochemicals, and the total and net income fromcoVee production did not diVer between farmers inside and outside of the national park(Table 2). Most of the farmers noted that they had other, non-agricultural income sources.Of the 30 farmers with farms inside BBS, 29 had other non-agricultural income sources; 21work for other farmers, and 8 had a business. Of the 30 farmers with farms outside of BBS,25 had other incomes; 14 work for other farmers, 1 had a steady city job, and 10 had a busi-ness. The total income generated by these other jobs was about half of the reported incomeearned by coVee farmers. In the case of both farmers inside and outside of BBS, about halfof their incomes (49.9% and 51.6%, respectively) came from coVee. Many more farmersoutside of BBS grew non-coVee crops in their coVee Welds, and grew more other crops thandid farmers inside of BBS (Fisher Exact Test, P < 0.001) (Table 3). There were a total of 17other products grown alongside coVee including spices, fruits, and timber (Table 3). Eachof the products (except jackfruit and rambutan) was grown more often by farmers outsideBBS.

There was no signiWcant relationship between mean management index in a site and theyield of coVee (kg per ha) in that site (y = 4.298x + 7.182, R2 = 0.049, P = 0.670). CoVeeyields did not vary with percent canopy cover (y = ¡0.719x + 5.283, R2 = 0.095,P = 0.551).

Discussion

The results presented here show generally that coVee gardens in the Lampung province ofSumatra maintain a high number of tree, ant, and bird species, when examined in severalsites across coVee growing regions. However, the coVee gardens have signiWcantly fewerspecies of birds, ants, and trees than native forests in BBS. Furthermore, species similaritybetween birds, ants, and trees found in the coVee gardens and forests was either very orrelatively low (fewer than 25% shared species for trees and birds and around 50% for ants),showing that the farms to not maintain the majority of forest species. Most aspects of

Table 2 Mean (§standard error) landholding, coVee yields, and farmer revenue (from coVee and othersources) inside and outside of Bukit Barisan Selatan National Park in Lampung, Sumatra, Indonesia based onfarmer surveys carried out in 2005

Statistical results are from univariate ANOVA comparing farms inside and outside the Park

Inside BBS Outside BBS df F P

Age of coVee farm (Yrs) 19.73 § 1.26 14.03 § 1.09 1, 58 11.68 0.001Age of coVee plants (Yrs) 19.00 § 1.38 13.83 § 1.10 1, 58 8.550 0.005CoVee landholding (Ha) 1.80 § 0.15 2.17 § 0.16 1, 58 2.625 0.111CoVee production (kg) 1101.61 § 198.47 1186.15 § 254.82 1, 56 0.071 0.792CoVee yield ha¡1 (kg) 546.51 § 71.24 527.94 § 99.38 1, 56 0.024 0.877CoVee Price kg¡1 (USD) 0.317 § 0.005 0.385 § 0.014 1, 56 24.341 <0.001Total coVee revenue (USD) 348.26 § 64.06 458.85 § 97.57 1, 56 0.951 0.334CoVee revenue ha¡1 (USD) 171.78 § 22.77 205.53 § 38.96 1, 56 0.603 0.441Other revenue (USD) 245.44 § 29.91 196.62 § 29.86 1, 57 1.327 0.254Revenue from coVee (% of total) 48.95% § 4.52% 57.00% § 4.86% 1, 55 0.951 0.232Agrochemical costs (USD) 38.82 § 5.73 40.46 § 4.15 1, 45 0.056 0.814

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canopy and understory vegetation were similar in farms inside and outside of the Park, butthose farms inside had higher numbers of epiphytes and trees, and fewer coVee plants perplot leading to a signiWcantly lower vegetation complexity values in farms outside of thepark. Ant and bird richness however did not diVer between coVee gardens inside and out-side of BBS.

There were no signiWcant diVerences between farms inside and outside of BBS in termsof coVee yields, revenues from coVee production or outside jobs, percent of total revenuefrom coVee, or agrochemical costs. Farmers outside of the National Park received signiW-cantly higher prices per kg for coVee sold, but because of slightly (but not signiWcantly)lower yields, overall coVee revenues did not diVer. In addition, a much higher proportion offarmers outside BBS grew other crops in their coVee Welds. Because of the ways in whichsurveys were designed, we cannot infer the direct incomes (or household use) to farmersprovided by alternative products. Previous studies have shown that alternative incomes canprovide a large proportion of household income. In Peru, shade tree products may accountfor »30% of revenues from coVee farms—especially fruits and Wrewood rather than timber(R. Rice, unpublished data 2002). Escalante and colleagues (1987) found that fruits fromthe shade canopy in coVee farms accounted for 55–60% of income, and timber for 3%. InCosta Rica, fruits sales accounted for 5–11% of income from coVee growing areas(Lagemann and Heuveldop 1983). Furthermore, having available products from mixedgardens can reduce the use of forest plots for extraction (Murniatai et al. 2001). The ability

Table 3 Products other than coVee grown in farms inside and outside of Bukit Barisan Selatan National Parkin Lampung, Sumatra, Indonesia

Numbers are based on survey responses of individual farmers regarding crops they reported growing. Therewere signiWcantly more farmers outside of the Park growing non-coVee products than inside the park (Fisher’sexact test, P < 0.001)

No. of farmers inside BBS

No. of farmers outside BBS

Total

Grow alternative productsNo 21 8 29Yes 9 22 31Number of products grownOne 5 6 11Two or more 4 15 19Name of products grownAvocado (Persea americana) 0 3 3Banana (Musa spp.) 1 8 9Black Pepper (Piper nigrum) 2 11 13Cacao (Theobroma cacao) 5 8 13Candlenut (Aleurites moluccana) 0 2 2Cinnamon (Cinnamomum spp.) 0 1 1Clove (Syzygium aromaticum) 0 1 1Coconut (Cocos nucifera) 0 1 1Duku (Lansium domesticum) 1 8 9Durian (Durio spp.) 0 2 2Jackfruit (Artocarpus heterophyllus) 1 0 1Mango (Manguifera indica) 0 1 1Orange (Citrus spp.) 0 3 3Petai (Parkia sp.) 3 8 11Rambutan (Nephelium lappaceum) 1 0 1Jengkol (Pithecellobium jiringa) 1 3 4Teak (Tectona grandis) 0 1 1

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to harvest from the shade tree canopy reduces the vulnerability to market Xuctuations andhousehold dependence on outside products while increasing local commerce (Dietsch et al.2004). It is unclear from these published studies what fraction of the shade trees in farms iscomprised of trees that produce fruit or timber products. If Sumatran farmers have similarcanopy composition, than they may also be able to beneWt from canopy products. SpeciW-cally, it is thus likely that those farmers outside of BBS may have added income and foodfor household consumption provided by these alternative products that farmers inside thePark do not have. It is still the case, however, that farms both inside and outside of parkshad extremely low yields. When intensively managed robusta coVee can yield 3.5 t ha¡1

(Söndahl et al. 2005) whereas coVee farms in this study yielded only approximately0.55 t ha¡1 consistent with other data from the region (O’Brien and Kinnaird 2003). Impor-tantly, however, we did not Wnd signiWcant negative or linear relationships between thevegetation complexity of farms or percent canopy cover and coVee yields per hectare insites which likely have similar climatic, soil, and regional conditions. This adds to thegrowing body of knowledge that factors associated with increased biodiversity protection(higher shade tree diversity and shade cover) do not necessarily lead to lower yields forcoVee farmers.

Although coVee is commonly promoted as an example of a biodiversity-friendly farm-ing technique is and prized for its contribution to various ecosystem services, this has beenbased primarily on literature from Northern Latin America. One diYculty in making policyrecommendations regarding such sustainable coVee production has arisen due to perceiveddiVerences between coVee management strategies, economic incentives available to farm-ers, and diVerences in coVee production near to very large protected areas (such as BBS). Acompanion study to that presented here was conducted in Chiapas, Mexico during the sameyear (Philpott et al. 2007) and used the same methodology and analyses to examine vegeta-tion and economic characteristics of farms, and tree, bird, and ant richness in coVee farmsand forest fragments. Although there are signiWcant diVerences between the study regions(Sumatra and Chiapas) in terms of elevation (803 m in Sumatra, 1244 m in Mexico), lati-tude (Sumatra is equatorial [4–5° S] and Chiapas is subtropical [16–17° N]), coVee speciescultivated (arabica in Chiapas and robusta in Sumatra), and the amount of forest in eachlandscape, we nonetheless wanted to provide some comparative information because of theimportant conservation implications. In the same size plots, Mexican farms had on average56 § 1 (SE) % canopy cover, 45 § 4 trees, 11 § 0.3 tree species, 2.8 § 0.11 m canopydepth, 15.2 § 2 epiphytes, a mean tree height of 7.8 § 0.11 m, 204 § 2 coVee plants perplot, and an overall vegetation complexity index of 0.27 § 0.01 (recalculated from themanagement index reported in Philpott et al. 2007). Thus, vegetative complexity is greaterand management intensity generally (and signiWcantly) less in coVee farms sampled in Chi-apas than in Sumatra. In Mexico, 44.8% of tree species, 55.5% of ant species, and 58.8% ofbirds were shared by coVee and forest plots compared with 24.3% of tree species, 57.2% ofants, and 27.1% of birds shared between all coVee sites and forests in Sumatra. All similar-ity indices (accounting for shared species and also diVerences in abundance) showed sig-niWcantly higher similarity between forest and coVee plots in Mexico than in Sumatra. Oneimportant caveat is that Mexican forests may be somewhat degraded in comparison to for-ests in Sumatra thereby inXating species overlap between forests and farms. Nevertheless,farms in Mexico with higher vegetation complexity maintain a higher proportion of speciesand of forest species than farms with low vegetation complexity (Mas and Dietsch 2004;Philpott et al. 2007). The results presented here show that the Mexican farms can preservefar more of the forest Xora and fauna than do their Sumatran counterparts, and importantlythat within regions (i.e., Mexico) that those farms with higher vegetation complexity

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provide more important habitat refuges for biodiversity because of the diversity of nativeand planted shade trees and other aspects of the vegetation.

Many characteristics of the shade canopy of Sumatran farms may contribute to the over-all low biodiversity value at present and in fact, the vegetation features in which Sumatranfarms are low are directly linked to reduced abundance and diversity of birds and ants.Sumatran farms have very low tree species richness compared with farms in other regions,and lower than required for shade certiWcation. Sumatran farms also have relatively lowcanopy cover (30–35% on average). Ant species may be strongly aVected by nest-siteavailability, the diversity of trees producing twig-nests and other nest sites, or presence of aparticular species’ or composition of species for nesting (Philpott and Armbrecht 2006).Ants are also strongly aVected by microclimatic conditions such as changes in temperatureand moisture resulting from drastic reductions in canopy cover as seen in Sumatran farms(Philpott and Armbrecht 2006). The low canopy cover is likely a result of using Erythrinasubumbrans and Gliricidia sepium as the most common shade trees. These species arelargely deciduous and provide very low canopy cover per tree. Furthermore, G. sepium isan exotic in this region, and thus may not provide resources needed by native fauna. In gen-eral, the mix of exotic and native species in the coVee agroforests may not produce enoughresources such as fruits and nesting sites needed for native birds (i.e., Thiollay 1995). Birdabundance, in particular is strongly tied to fruit abundance in tree canopies (Levey 1988).For these reasons shade certiWcation programs advise against using exotics as the main can-opy trees in coVee plantations. Thus the relatively low tree diversity and shade cover andhigh proportion of exotic species in the coVee plots may contribute to relatively low main-tenance of forest fauna. Although currently having relatively low biodiversity value, thefarms nonetheless had speciWc attributes that might contribute to maintenance of biologicaldiversity. The farms studied had generally high tree height, many emergent trees per plot,high vegetation depth, and more epiphytes than is common in farms in other regions(Philpott et al. 2007) and these and other aspects of the vegetation complexity could beenhanced to increase biodiversity value of farms.

These results have several implications for both conservation and for creating sustain-able coVee production systems in Sumatra. We show that Sumatran farms currently havelimited value in protecting biological diversity and also have somewhat limited valuebecause of low coVee yields and few alternative products (especially for farmers inside ofBBS). In the case of farms visited, this is likely do to very poor soil conservation practices,a complete lack of organic (or even synthetic) fertilizer use, and minimal ground cover.Thus, one important recommendation that has been made to farmers in Sumatra (and theirextension agents and conservation organizations) worth repeating here is to improve soilconservation techniques such as increasing ground cover and applying organic compost(i.e., O’Brien and Kinnaird 2003). Another speciWc recommendation is to incorporate moretree species, especially native species in their farms. This could potentially increase ecosys-tem services such as pollination, predation, erosion control, and could enrich the nutrientcontents of farm soils as has been found in other regions (Beer et al. 1998; Perfecto et al.2007). Increasing tree diversity would also beneWt associated biodiversity which is highlycorrelated with plant biodiversity and could provide more alternative products to farmers.Moreover, this could contribute to reforestation. Techniques such as reforestation farming,whereby intensive agricultural lands are planted with native forest trees, fruit, and timberspecies have been successful in recreating native habitat and beneWting farmers in otherparts of Asia (Goltenboth and Hutter 2004). Additionally, in areas of Lampung near to thestudy sites, damar (Shorea javanica) agroforets, which are tall, diverse, and vegetatively

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complex already exist at similar elevations and climatic conditions as areas where coVee isgrown (Thiollay 1995).

Our results show that currently, coVee farms in Sumatra do not protect a large fraction ofbird or tree fauna and that they do not therefore have high conservation value for these spe-cies either inside or outside of the park. However, for some groups, such as ants, coVeefarms in Lampung may protect a larger fraction of the biodiversity. It has been argued thatpromoting intensive production systems (including sun coVee with improved soil practices)result in higher yields per area thus reducing the footprint of coVee production, freeing landto be conserved as natural forest (O’Brien and Kinnaird 2003; Green et al. 2005). Thisstudy does not support that point of view, for even though the Sumatran farmers have rela-tively intensive plots in terms of low canopy cover production per hectare was very low.CoVee prices for farmers outside BBS are already signiWcantly higher and these same farm-ers more frequently produce alternative products. We have suggested many managementtechniques for improving yields and biodiversity, such as increasing soil conservation,reducing the amount of exotic species, and increasing native tree diversity, and increasinguse of alternative products. Were these farmers to have appropriate technical assistancetheir farms could increasingly support biodiversity and economic stability.

Another extremely important question is what will be the fate of the coVee farms locatedwithin BBS. Half of the Sumatran farmers included this study (and an estimated 15,000others) are currently growing coVee inside of Bukit Barisan Selatan National Park (WWF2007) and much eVort by park staV and others is being placed on how to remove thesefarmers growing coVee from the park to better protect wildlife. This approach is justiWedand important because farmers are illegally growing coVee inside of BBS, and their activi-ties are continually threatening endangered animals such as the Sumatran tiger, elephants,and rhinoceroses (O’Brien et al. 2003; WWF 2007). Without drastic measures, habitat forthese charismatic animals is likely to quickly disappear. In addition, increases in technicalassistance, incomes, and changes in coVee production for farmers outside the park may cre-ate incentives and opportunities to draw farmers from inside the park. Some conservationorganizations in the area are already working in this direction. Yet, the political realities ofthe situation in Lampung are very complex. Landscapes around BBS appear to already beheavily impacted by agriculture with few spaces left for creating new farms. It may be pre-cisely because of farmer location, lack of stability, and little access to labor that farmersinside the park less frequently plant alternative crops or invest in long term strategies forsoil conservation which will likely lead to increased encroachment (WWF 2007). Further-more, many farmers, such as those interviewed in this study, have been growing coVeeinside of the park for nearly 20 years having been moved to Sumatra as part of government-sponsored transmigration programs (WWF 2007). Interestingly, the farmers inside BBShave signiWcantly older farms than those outside the Park, despite (a) the heavy focus andblame on new agricultural encroachments for habitat destruction, and (b) the overlap of ourstudy areas with areas highlighted as having new encroachments in a recent land coveranalysis (Gaveau et al. 2007). It is unlikely that the estimated 15,000 families inside ofBBS will be removed from the Park rapidly enough to stop or erase the impact of encroach-ments. Those lands that have been in agricultural production for many years will regenerateslowly, and will require immense investments to restore (e.g., Holl et al. 2000). For exam-ple, agricultural lands in BBS from which farmers were evicted in 1986 were indistinguish-able from multi-strata tree cropping systems in a 2002 satellite image (Gaveau et al. 2007).Based on ground points, these areas were classiWed as re-growth areas characterized by sec-ond growth trees (Gaveau et al. 2007), demonstrating relatively slow succession in theseagricultural encroachments. We do not encourage increased encroachment or expansion of

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illegal farming within BBS or other protected areas. But for the reasons provided above, weadvocate working with farmers both inside and outside of parks towards improved agricul-tural management including primarily planting of native canopy trees. In our opinion, suchcooperation with farmers will increase biodiversity and produce more sustainable land-scapes more quickly and over the long term.

Acknowledgements Field work could not have been possible without the help of our collaborators inSumatra. Jangi Yanto, Sumargi, Supri, and A. Nurchayo greatly assisted in the project as did local guides inall communities. We thank members of the following communities in Sumatra (Suka Banjar, Talang Suharto,Sukabumi, Sidodadi, Kububalak, Sedayu, Kuyung Arang, and Kali Sembilan) that allowed us access to theirfarms and housed us. Dr. D. Buchori of IPB Bogor was the oYcial research sponsor in Indonesia and we givesincere thanks to her for her help. StaV of LIPI, Departemen Kehutanan, Balai Taman Nasional Bukit BarisanSelatan, ICRAF, and Wildlife Conservation Society assisted with permits. A. Gorog and G. Paoli providedinvaluable logistical support. M. Reiskind and S. Van Bael gave valuable comments on previous versions ofthe manuscript. Research funding was provided by the Smithsonian Migratory Bird Center in Washington,DC.

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