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Landscape and Urban Planning xxx (2007) xxx–xxx

Africanized honey bees in urban environments: A spatio-temporal analysis

Kristen A. Baum a,∗, Maria D. Tchakerian b, Steven C. Thoenes c, Robert N. Coulson b

a Department of Zoology, 430 Life Sciences West, Oklahoma State University, Stillwater, OK 74078, USAb Knowledge Engineering Laboratory, Department of Entomology, Texas A&M University, College Station, TX 77843-2475, USA

c BeeMaster, Inc., 11358 N. Mandarin Lane, Tucson, AZ 85737, USA

Received 22 May 2007; received in revised form 30 July 2007; accepted 17 October 2007

bstract

For honey bees in the desert southwest, urban environments may provide abundant cavities and a more spatially and temporally continuous supplyf nectar, pollen and water than would be available in surrounding natural desert areas. The presence of abundant cavities and food resources inrban environments places honey bees in close proximity to humans, creating concerns over public health and safety, particularly in areas dominatedy Africanized honey bees. Africanized honey bee colonies are abundant in the greater Tucson metropolitan area, and requests for colony andwarm removals increased from 14 in 1994 to 1613 in 2001. We obtained invoices with data on honey bee colony and swarm removals from994 to 2001 from a private company in Tucson, Arizona, which specializes in the removal and control of Africanized honey bees. We evaluatedpatio-temporal patterns in the distribution of Africanized honey bee colonies and swarms and evaluated the role of precipitation in generating thebserved patterns. Colonies and swarms showed a shift from no spatio-temporal clustering in the initial years following the arrival of Africanized
oney bees to significant spatio-temporal clustering in later years. Precipitation was a good predictor of honey bee abundance, with more colonynd swarm removals following wet seasons and fewer following dry seasons. These patterns suggest the greatest likelihood of human–honey beenteractions in urban areas in the desert southwest will occur with high honey bee abundances following wet winters.
2007 Elsevier B.V. All rights reserved.

eywords: Apis mellifera; Feral colonies; Swarms; Cross-correlation; Mantel test; Sonoran desert

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. Introduction

Urban environments provide suitable habitat for many organ-sms, including native and nonnative species. In some cases,rban environments may provide ideal habitat compared to sur-ounding natural areas, with some species thriving in cities,uch as European starlings (Clergeau and Quenot, 2007) andosquitoes (Leisnham et al., 2006). Species that thrive in urban

nvironments are often widespread and may be consideredests because of their overlap in resource use with humans.oney bee colonies nest in natural, wildlife- and human-made

Please cite this article in press as: Baum, K.A., et al., Africanized honeyUrban Plann (2007), doi:10.1016/j.landurbplan.2007.10.005

avities, such as tree hollows and buildings, and will exploitrban sources of nectar, pollen and water. For honey bees inhe desert southwest, urban environments may provide abun-

∗ Corresponding author. Tel.: +1 405 744 7424; fax: +1 405 744 7824.E-mail addresses: [email protected] (K.A. Baum),

[email protected] (M.D. Tchakerian), [email protected]. Thoenes), [email protected] (R.N. Coulson).

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169-2046/$ – see front matter © 2007 Elsevier B.V. All rights reserved.oi:10.1016/j.landurbplan.2007.10.005

ant cavities and a more spatially and temporally continuousupply of nectar, pollen and water than would be availablen surrounding natural areas (Buchmann, 1996; Rabe et al.,005; Shochat et al., 2006; Stuart et al., 2006). The presencef abundant cavities and food resources in urban environmentslaces honey bees in close proximity to humans (Pereira andhaud-Netto, 2005), creating concerns over public health and

afety, particularly in areas dominated by Africanized honeyees (Schmidt and Boyer-Hassen, 1996; Johnston and Schmidt,001).

Honey bees are not native to North America, but generallyre considered an important component of many ecosystemsecause of the pollination services they provide (Allen-Wardellt al., 1998; Morse and Calderone, 2000). Feral and managedoney bee colonies extract large amounts of pollen and nectar

bees in urban environments: A spatio-temporal analysis, Landscape

rom all habitats where they live and may compete for limitedoral resources with native bees and other pollinating animalsBuchmann, 2000). Colonies reproduce by swarming when partf the colony leaves with the queen in search of a new nest site.

dx.doi.org/10.1016/j.landurbplan.2007.10.005

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ARTICLEAND-1542; No. of Pages 10

K.A. Baum et al. / Landscape an

hus, colonies occupy relatively permanent locations, whereaswarms occupy transient locations until they select a new nestite. Feral, unmanaged honey bee colonies can be found in manyifferent settings, including urban/suburban (Morse et al., 1990;e Mello et al., 2003), forest/woodland (Galton, 1971; Kerr,974; Visscher and Seeley, 1982; Oldroyd et al., 1994; Coulsont al., 2005), agricultural (Ratnieks et al., 1991), coastal prairieBaum et al., 2005), and semi-desert and desert habitats (Taber,979; Boreham and Roubik, 1987; Schneider and Blyther, 1988;cNally and Schneider, 1996; Loper et al., 2006). Few studies

ave evaluated spatial patterns in honey bee colony distribu-ions (Oldroyd et al., 1995, 1997; McNally and Schneider, 1996)r spatial patterns through time (Baum et al., 2005). However,hose studies that have evaluated spatial distributions suggesteral honey bee colonies tend to form aggregations (Oldroydt al., 1995, 1997; McNally and Schneider, 1996; Baum et al.,005). Possible explanations for colony aggregations includeggregated resources, short swarm dispersal distances, attrac-ion of swarms to existing colonies, increased predator defensesnd increased mating efficiency (Seeley and Morse, 1977, 1978;aycox and Parise, 1980, 1981; Seeley et al., 1982; Oldroyd etl., 1995; Schmidt, 1995; Baum et al., 2005).

Africanized honey bees, hybrids between African honey beesApis mellifera scutellata) and European honey bees (Clarke etl., 2002; Pinto et al., 2005), first arrived in the United Statesrom South America in 1990 (Hunter et al., 1993; Rubink et al.,996; but see Pinto et al., 2007) and Arizona in 1993 (Guzman-ovoa and Page, 1994; Loper, 1997). Africanized honey bees

re characterized by stronger defensive behavior, higher repro-uctive rates, smaller colony sizes, and less selectivity in nestites than colonies of European origin (Winston et al., 1983;

inston, 1992; Schneider et al., 2004b). Africanized coloniesill utilize smaller cavities than European colonies (Schmidt

nd Hurley, 1995), expanding the range of suitable nest sites tonclude flower pots, underground concrete water meter boxes,ires, cement blocks, garbage cans, etc., thereby increasing theroximity of Africanized honey bees to humans. In African-zed areas in the United States the feral honey bee population isredominantly Africanized (Pinto et al., 2004; Schneider et al.,004b), including Arizona (Rabe et al., 2005; Harrison et al.,006).

Temperature and precipitation have been identified as poten-ial factors contributing to the invasion pattern of Africanizedoney bees in North America (Schneider et al., 2004b). For areaselow the 34◦N latitude line proposed as the potential northernimit for Africanized honey bees based on similar limits in Southmerica (Taylor and Spivak, 1984), winter temperatures andinter survival are unlikely to limit their distribution. However,recipitation and associated patterns of floral resource availabil-ty could influence the distribution and abundance of honey beeolonies in the desert southwest. African colonies are adapted toeasonally arid habitats and may respond more strongly to pre-ipitation patterns than photoperiod, which is linked to annual


ycles in European honey bee colonies. This response to precip-tation reflects the ability of Africanized honey bees to rapidlyespond and exploit transient “flushes” in floral resource avail-bility.

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PRESSan Planning xxx (2007) xxx–xxx

Feral honey bee colonies are abundant in the greater Tucsonetropolitan area, generating demand for pest control compa-

ies that specialize in removing honey bee colonies and swarms.equests for honey bee colony and swarm removals increased

rom less than 20 in 1994 to more than 1,800 in 2001 (unpubl.ata, S.C. Thoenes), representing a dramatic increase in removalequests with the arrival and establishment of Africanized honeyees in the area. We obtained invoices with data on honey beeolony and swarm removals from 1994 to 2001 from BeeMaster,nc., a private company in Tucson, Arizona, which specializesn the removal and control of Africanized honey bees. The goalf this study was to evaluate spatio-temporal patterns in the dis-ribution of feral honey bee colonies and swarms in the greaterucson metropolitan area based on removal records. We pre-icted that colony and swarm removals would show a strongpatio-temporal correlation, with removed colonies and swarmsocated close together in space also occurring close together inime.

We also evaluated the role of precipitation in generating thebserved patterns of colony and swarm abundance based on theemoval data. We predicted swarm abundance should be cor-elated with precipitation at lag times reflecting faster colonyrowth during years with early and/or abundant pollen produc-ion as indicated by fall/winter precipitation and precipitationuring the summer monsoon period (July to mid-September).ag times reflecting slower colony growth should occur duringears with late and/or limited pollen production due to little pre-ipitation during the fall and/or winter. Colonies should showimilar correlations with precipitation as swarms because flightctivity levels are high for colonies producing swarms and forewly founded colonies, and high activity levels would increasehe likelihood of a colony being detected and removed. Identi-ying patterns in the spatio-temporal distribution of feral honeyee colonies in urban environments will provide informationeeded to develop strategies to control Africanized honey beesnd minimize human–honey bee interactions in urban areas.

. Methods

.1. Study site

The Tucson metropolitan area is located in Pima County inoutheastern Arizona in the northern Sonoran Desert. The city ofucson is a highly urbanized area with a population of 946,362U.S. Census Bureau, 2007). The climate is arid with an aver-ge annual rainfall of 29.7 cm. Most of the precipitation occursuring the summer monsoon period (July to mid-September),ith additional precipitation in the winter (December to earlyarch). April, May and June are often without rain. Maximum

emperature regularly exceeds 38 ◦C during the summer, withn average annual high of 27 ◦C and a low of 12 ◦C.

The vegetation in the study area is characteristic of the Ari-ona Upland subdivision of the Sonoran Desert as described


y Shreve (1951). Succulent cacti, drought tolerant shrubs andildflowers are common plants found in this subdivision. Theowering patterns in the northern Sonoran Desert have been wellocumented with many species flowering when seasonal soil


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oisture is greatest (Bowers and Dimmitt, 1994). The Arizonapland subdivision desert has two flowering periods: the firstowering season extends from mid-February to mid-June withpeak from early March to late April and the second flowering

eason begins near the end of the summer rains and continuesnto late fall (O’Neal and Waller, 1984; Dimmit, 2000). Thesewo periods represent the major natural flushes of nectar andollen availability for honey bees in the area.

Within the greater Tucson metropolitan area, native vegeta-ion is mostly intact in riparian, low-density housing and naturalpen space areas (Shaw et al., 1998; Livingston et al., 2003).owever, rapid urbanization has fragmented patches of nativeegetation with commercial and residential development (Canet al., 2006), and much of the natural vegetation community haseen replaced by exotic species in these areas. The presencef exotic species combined with irrigation and other landscap-ng practices have likely extended the flowering periods in theucson area beyond those encountered under natural conditions.atural cavity sources in the area are probably relatively rare,ith rock crevices being used by colonies in nearby natural areas

Taber, 1979; Loper et al., 2006). However, human-made sourcesf cavities are abundant in the greater Tucson metropolitan area,ncluding openings in buildings, water meter boxes, tires, cement


locks, garbage cans, flower pots and a variety of other hol-ow spaces of adequate size. Therefore, the urban environment

ay represent ideal habitat for Africanized honey bees, withbundant cavities and a more spatially and temporally continu-

cmaa

Fig. 1. Shaded relief map of the greater Tucson metropolitan area wit

PRESSan Planning xxx (2007) xxx–xxx 3

us supply of nectar, pollen and water compared to surroundingatural desert areas.

.2. Bee colony data

Invoices with data on honey bee colony and swarm removalsrom 1994 to 2001 were obtained from BeeMaster, Inc., a privateompany in Tucson, Arizona, which specializes in the removalnd control of Africanized honey bees. For each removed colonyr swarm, recorded information included date, address, prob-em type (i.e., colony, swarm or individual honey bees), andpecific location (i.e., building, tree, swarm trap, ground oriscellaneous). The miscellaneous category included flower

ots, water meter boxes, tires, cement blocks, garbage cans,tc. Only data on colonies and swarms were included in thenalyses.

Colony and swarm removal records were assigned geo-raphic coordinates by linking street addresses for each colonyo line segments contained in the Pima County Departmentf Transportation street network coverage (1999) using aommercial GIS product (ArcGIS® v. 9.2; Fig. 1). An addressas considered “matched” if the street address of the removalad the same number and street name as the street network


overage. When an exact match could not be made, interactiveatching was used to refine misspelled addresses, directions,

nd street type errors. An “unmatched” address occurred ifn address was not found in the street network coverage or

h point locations for all colonies and swarms removed in 2001.


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Table 1Mantel test results for the detection of spatio-temporal clustering of honey beecolonies and honey bee colonies and swarms in the greater Tucson metropolitanarea

Year # colonies R p # colonies +swarms

R p

1994 14 −0.071 0.376 14 −0.071 0.3761995 323 0.009 0.286 458 0.004 0.3851996 474 0.011 0.187 665 0.009 0.2031997 445 0.022 0.096 617 0.021 0.0751998 1012 0.019 0.061 1407 0.017 0.051122

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ecessary information was lacking (no street number or name,.O. Box listing, etc.) and these were excluded from all analyses.

.3. Data analysis

We used a Mantel test to evaluate whether or not honey beeolony and swarm removals located close together in space werelso located close together in time. We conducted two sepa-ate analyses (one for colonies only and one for colonies andwarms) because colonies occupy relatively permanent locationsnd swarms occupy transient locations until they select a nestite. The Mantel test compares two distance matrices (for ourtudy, distance in space between colony removal locations andistance in time between colony removal dates; Fortin and Dale,005). The units in space (m) and time (days) were not compara-le, so we ranked the values in each data matrix prior to analysisDietz, 1983; Fortin and Dale, 2005). We used a randomizationest with 100,000 permutations to evaluate significance, withignificant values occurring when the Mantel statistic is morextreme than the reference distribution as ascertained using thepearman rank correlation coefficient. We used zt to conduct thenalysis (Bonnet and Van de Peer, 2002). For all analyses theignificance level was set at α = 0.05.

We used a cross-correlation analysis to evaluate if weeklyrecipitation was correlated with weekly swarm or colonyemoval numbers. Daily precipitation data were obtained fromhe National Climatic Data Center (http://www.ncdc.noaa.gov/a/ncdc.html, accessed 20 October 2006) using data inventoriesrom a first order weather station located in Tucson, Arizona.

e evaluated weekly lags from 0 to 50 and used 95% upper


nd lower confidence limits to evaluate significance. Cross-orrelation values range from 1 to −1, with 1 indicating strongositive correlation, 0 indicating no correlation and −1 indicat-ng strong negative correlation. The cross-correlation analysis

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able 2ross-correlation results testing for correlation between weekly swarm and colony re

ear Swarms (% change) Precipitation (mm)a

995 245

996 +41 120

997 −10 138

998 +230 187

999 −10 35

000 −49 35

001 +336 227

ignificant weekly lags are listed separately for lags with positive and negative correlear and fall and winter precipitation is also provided.a Precipitation is the total amount during the fall of the previous year (beginning 22arch).

999 871 0.027 0.036 1225 0.025 0.024000 353 0.039 0.021 525 0.046 0.005001 1035 −0.029 0.009 1613 −0.033 0.000

as performed using SPSS for Windows, Release Version 15.0©SPSS, Inc., 2006, Chicago, IL).

. Results

After excluding records without accurate spatial informa-ion, BeeMaster, Inc., removed 6, 524 colonies and swarms fromhe greater Tucson metropolitan area from 1994 through 2001Table 1). The number of colony and swarm removals increasedrom 14 in 1994 to 458 in 1995 following the arrival of African-zed honey bees in 1993. Removals increased 228% from 1997o 1998 for colonies + swarms, decreased by 43% from 1999 to000 and increased by 307% from 2000 to 2001 (Table 1). Aajority of the colonies were located in buildings (55%), fol-

owed by the miscellaneous category (27.9%), trees (10.1%)nd in the ground (7%). Swarms were primarily located in trees


55%), followed by buildings (22.5%), the miscellaneous cate-ory (13%) and in the ground (9.5%).

The annual temporal distribution of colony and swarmemovals did not exhibit any strong trends, but some years (i.e.,

moval numbers and weekly precipitation

Correlation Swarms Colonies

Pos ns nsNeg ns ns

Pos ns nsNeg ns 0

Pos 31, 32, 34, 35 31, 32, 34Neg ns ns

Pos 12 15Neg 0 4

Pos ns nsNeg ns ns

Pos 35, 36 nsNeg ns ns

Pos 24, 26, 27, 28 28, 29, 30Neg ns ns

ation. The percent change in the number of swarms removed from the previous

–23 September) and the winter of the current and previous years (ending 19–20


http://www.ncdc.noaa.gov/oa/ncdc.html

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Fig. 2. Weekly precipitation (mm), number of colonies rem

995, 1996, and 2001) showed a bimodal distribution with anarly peak from March through May and a late peak in Octo-er and November (Fig. 2). Overall precipitation was highestn 1998 and lowest in 2001 (Fig. 2). Fall and winter precip-tation was the lowest during 1998/1999 and 1999/2000 andighest during 1994/1995 and 2000/2001 (Table 2). Coloniesnd colonies + swarms showed a shift from no significant spatio-emporal clustering from 1995 through 1998 to significantpatio-temporal clustering from 1999 through 2001 (Table 1).patio-temporal clustering was positive in 1999 and 2000 andegative in 2001 for both colonies and colonies + swarms.

The number of colonies removed was positively cross-orrelated with precipitation in 1997 (31, 32, and 34 week lags),998 (15 week lag) and 2001 (28–30 week lags) and negativelyross-correlated with precipitation in 1996 (0 week lag) and 19984 week lag; Table 2, Fig. 3). The number of swarms removedas positively cross-correlated with precipitation in 1997 (31,2, 34, and 35 week lags), 1998 (12 week lag), 2000 (35 and 36eek lags) and 2001 (24 and 26–28 week lags) and negatively

ross-correlated with precipitation in 1998 (0 week lag; Table 2,ig. 4).

. Discussion


Several factors could potentially bias the spatio-temporalnterpretation of the honey bee colony and swarm removal data.irst, socio-economic considerations, in particular the ability to

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and number of swarms removed from 1995 through 2001.

ay for the removal service, could influence the completeness ofhe dataset. The detectability of colonies and associated requestsor removals also could differ based on the location of theolony, proximity to human activity, frequency of human activ-ty, etc. Tolerance of stinging insects and insects in general couldnfluence the likelihood of someone choosing to have a colonyemoved once detected. These factors also could influence theemoval options considered, such as an individual attemptingo remove a colony or swarm on their own. However, given thextensive media coverage given to Africanized honey bees (akakiller bees”), the bias of these factors is probably much lesshan would be expected for similar data obtained for other pestpecies.

Honey bee colony densities based on colony and swarmemovals ranged from 0.36 colonies/km2 (or 0.51 colonies andwarms) in 1995 to 1.12 colonies/km2 (or 1.80 colonies andwarms) in 2001. These densities fall within the range of previ-usly reported densities for aggregations of honey bee coloniesn other areas (Ratnieks et al., 1991; Oldroyd et al., 1994, 1997;

cNally and Schneider, 1996; Baum et al., 2005), although onlyorse et al. (1990) examined feral colonies in an urban area. This

tudy represents the largest number of colonies and/or swarmseported for any published study, even considering the data rep-


esent removed (killed) colonies and swarms which no longerontribute to population growth (Table 1).

From 1995 to 1998, colonies and colonies + swarms showedo significant spatio-temporal clustering. However, from 1999 to



6 K.A. Baum et al. / Landscape and Urban Planning xxx (2007) xxx–xxx

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ig. 3. Cross-correlation coefficients for precipitation and colony removals forower confidence limits indicating significance.

001, colonies and colonies + swarms showed significant spatio-emporal clustering (Table 1). The number of colony and swarmemovals was relatively low from 1995 through 1997, withewer than 700 removals per year, but more than doubled to407 removals in 1998. 1998 may represent a transition yearhere Africanized honey bees were becoming established in

he area and the colonies and swarms were responding to thebserved increase in population size, resulting in strong spatio-emporal clustering in the following years. Spatio-temporallustering was positive in 1999 and 2000 and negative in 2001Table 1). 1999 and 2000 were both dry years with reducedwarming activity throughout the year except during the springeak which typically occurs in April and May. 2001 was a veryet year with the largest peak in swarming activity recordeduring this study (Table 2, Fig. 2). During dry years, swarmemovals tended to be spatially and temporally restricted, withctivity occurring within specific areas of Tucson. However,uring wet years removals were broadly distributed in space


nd time (Schmidt and Edwards, 1998) and tended to occurhroughout the greater Tucson metropolitan area. The signif-cant negative spatio-temporal clustering in 2001 may reflecthe 40 and 49% decline in the number of colonies and swarms

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with significant lags. Lags from 0 to 50 weeks are shown with 95% upper and

emoved in 2000, respectively, and the subsequent 293 and 336%ncrease in the number of colonies and swarms removed in001.

Several potential explanations have been proposed for whyoney bee colonies may be spatially aggregated, including dis-ersal behavior, resource distributions, predator defenses andating efficiency (Seeley et al., 1982; Oldroyd et al., 1995).xisting studies on swarm dispersal distances have producedonflicting results, with some studies reporting short dispersalistances and others reporting longer dispersal distances (Seeleynd Morse, 1977; Jaycox and Parise, 1980, 1981; Schmidtnd Thoenes, 1990; Oldroyd et al., 1995; Schmidt, 1995;chneider, 1995). Genetic differences among study populationsay explain these conflicting results, such as if Africanized

oney bee swarms travel longer distances than European swarmsWinston, 1987; Schneider, 1995). Differences in resource avail-bility among study areas are another possible factor influencingwarm dispersal distances (Winston, 1987; Schneider, 1995).


everal studies have suggested swarms may select nearby cavi-ies when cavities are abundant (Jaycox and Parise, 1980, 1981;eeley and Morse, 1977, 1978). Cavity availability is probablyot limiting in our study area, especially considering the wide



K.A. Baum et al. / Landscape and Urban Planning xxx (2007) xxx–xxx 7

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ig. 4. Cross-correlation coefficients for precipitation and swarm removals forower confidence limits indicating significance.

ange of cavities utilized by Africanized honey bee colonies.ectar and pollen sources are probably not limiting either, anday be more consistently available in urban environments than

n surrounding natural areas (Schneider et al., 2004a). Aggre-ations could increase predator detection and defenses, butotential predators other than humans are rare in urban environ-ents and aggregations may serve to increase human detection

nd removal. Aggregations also could serve to increase matingfficiency, but this potential explanation is difficult to evalu-te without information on drone congregation areas or theelatedness of colonies. Thus, the mechanisms behind spatio-emporal clustering in the colony and swarm removal data isot clear, but likely reflects a combination of resource avail-bility, honey bee biology and the likelihood of detection andemoval. Spatio-temporal clustering suggests efforts to controlnd remove Africanized honey bees should be spatially and tem-orally focused in areas near where colonies and/or swarms areound.

Precipitation is directly tied to pollen availability, with more


ain resulting in more pollen. The timing of the precipitationlso matters, with colony survival being positively correlatedith winter rainfall (Loper et al., 2006). Heavy rainfall dur-

ng October initiates flower production in mid-February and

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with significant lags. Lags from 0 to 50 weeks are shown with 95% upper and

warming in the spring. The summer monsoon period (Julyo mid-September) initiates flowering that begins a few weeksfter the first summer rains and continues into late fall, leadingo swarming activity in the fall. The development period fromgg to adult worker is approximately 21 days and from egg todult queen is approximately 18 days, with Africanized honeyees emerging one to 2 days earlier than European honey bees.hus, peak swarming would be expected to occur approximately–8 weeks after the initiation of flowering in mid-February or4–26 weeks after precipitation in October. Precipitation duringhe monsoon period generates a more immediate floral responseithin several weeks. Thus, monsoon rains in July and Augustould lead to swarming in October and November, with a lag of

pproximately 10–12 weeks. Any negative correlations wouldave very short lags because precipitation would suppress honeyee activity levels and also decrease the likelihood of detectionnd removal.

Seasonal absconding also may contribute to the distributionnd abundance of swarms and colonies. Seasonal absconding is


he abandonment of a nest site due to low resource availabilitynd the relocation of the colony to another nest site in an areaith presumably higher resource availability (Winston et al.,979; Schneider and McNally, 1992; Schneider et al., 2004a).


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easonal absconding in the Tucson area is associated with lowesource availability in the mountains surrounding Tucson inhe fall and winter months and higher resource availability inhe Tucson basin where agriculture and horticultural practicesncrease floral availability (Schneider et al., 2004a).

The significant precipitation lags for swarms in 2000 (35–36eeks) and 2001 (24 and 26–28 weeks) suggest pollen avail-

bility was low in 2000 and high in 2001 (Table 2, Fig. 4).hen heavy rainfall occurs during October, flowering begins

n mid-February and pollen becomes available to the honeyees. If precipitation is shifted later, pollen production woulde delayed and swarming activity will exhibit a correspondinghift with longer lags reflecting lower or later pollen availability.recipitation was extremely low in the fall/winter of 1999/2000,epresenting the driest winter during this study, whereas theall/winter of 2000/2001 was one of the wettest (Table 2, Fig. 2).n 1997 significant precipitation lags for swarms occurred at1, 32, 34 and 35 weeks, representing an intermediate year inerms of pollen availability (Table 2, Fig. 4). The precipitationag for 1998 was short (12 weeks), but can be explained by998 representing an El Nino year and being the wettest yearn terms of overall precipitation and number of days with rainTable 2, Figs. 2 and 4). Colonies showed significant precipita-ion lags very similar to those for swarms, which is not surprisingecause colony activity levels are high during periods of pollenbundance and swarm production (Table 2, Fig. 3). Also, newlyounded colonies would exhibit high levels of worker activity,hich could increase the likelihood of detection depending on

he cavity selected. Colonies and swarms in 1998 and coloniesn 1996 showed short negative lags with precipitation, whichould be expected based on immediate and temporary decrease

n honey bee activity due to rainfall (Table 2, Fig. 3). Precipita-ion and associated changes in productivity also have been showno influence the distribution and abundance of other speciesn the Sonoran Desert region, including vertebrates and othernvertebrates (Marshal et al., 2002; Shochat et al., 2004). Forxample, spider abundance was five times higher following an Elino winter (1997/1998) compared to a dry winter (1999/2000;hochat et al., 2004).

Overall, these data suggest precipitation may be a goodredictor of honey bee abundance in the greater Tucsonetropolitan area, with more colonies and swarms expected afteret winters. Significant spatio-temporal clustering in colony and

warm removals suggests control efforts should be concentratedn areas where colonies and swarms are found, although data fordditional years could clarify these patterns given the significantegative spatio-temporal clustering observed in 2001. Informa-ion on additional factors, such as disease and parasite loads,ould provide additional insights and further help target controlfforts. For example, Loper et al. (2006) documented an initialrastic decline in colony survival in a feral honey bee popula-ion after the arrival of the Varroa mite in 1995. Their study areaas located approximately 80 km northeast of Tucson, suggest-


ng infestation by Varroa mites also could have influenced theatterns observed in this study. Furthermore, this study definesethods for studying pest species in urban environments using

ata from pest control companies. Address matching within the

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ontext of a GIS can be used to create point data which can benalyzed using spatial or spatio-temporal statistics.

cknowledgements

A. Bunting, J. Yu and S. Kim provided valuable tech-ical assistance throughout this project. S. Buchmann andhree anonymous reviewers provided valuable comments on the

anuscript. Funding for this project was provided by the Texasegislative Initiative: Protection and Management of Honeyees—Pollinators of Agricultural Crops, Orchards, and Naturalandscapes.

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africanized honey bees in urban environments: a spatio-temporal … · such as european starlings...

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