Amazonian species within the Cerrado savanna: new records and potential distribution for Aglae

12 Pages·2017·0.58 MB·English

Amazonian species within the Cerrado savanna: new
records and potential distribution for Aglae caerulea
(Apidae: Euglossini)
Daniel Silva, Antonio Aguiar, Gabriel Melo, Evandson Anjos-Silva, Paulo
Marco
To cite this version:
Daniel Silva, Antonio Aguiar, Gabriel Melo, Evandson Anjos-Silva, Paulo Marco. Amazonian species
within the Cerrado savanna: new records and potential distribution for Aglae caerulea (Apidae: Eu-
glossini). Apidologie, 2013, 44 (6), pp.673-683. ￿10.1007/s13592-013-0216-7￿. ￿hal-01201337￿
HAL Id: hal-01201337
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Apidologie(2013)44:673–683 Original article
*INRA,DIBand Springer-Verlag France,2013
DOI: 10.1007/s13592-013-0216-7
Amazonian species within the Cerrado savanna: new
records and potential distribution for Aglae caerulea
(Apidae: Euglossini)
Daniel P. SILVA1,Antonio J. C. AGUIAR2,Gabriel A. R. MELO3,
Evandson J. ANJOS-SILVA4,Paulo De MARCO Jr5
1ProgramadePós-GraduaçãoemEcologiaeEvolução,DepartamentodeEcologia,ICB,UniversidadeFederalde
Goiás,RodoviaGoiânia-Nerópolis,Km5,CampusII,SetorItatiaia,CEP:74001-970Goiânia,GO,Brazil
2DepartamentodeZoologia,UniversidadedeBrasília,IB-UnB,CampusDarcyRibeiro,AsaNorte,CEP:70910-
900Brasília,DF,Brazil
3Lab.Biol.ComparadaHymenoptera,SetordeCiênciasBiológicas,DepartamentodeZoologia,Universidade
FederaldoParaná,CaixaPostal19020,CEP81531-990Curitiba,PR,Brazil
4Lab.deAbelhaseVespasNeotropicais,DepartamentodeBiologia,UniversidadedoEstadodeMatoGrosso,
AvenidaTancredoNevess/n,Cavalhada,CEP:78200-000Cáceres,MT,Brazil
5DepartamentodeEcologia,ICB,UniversidadeFederaldeGoiás,RodoviaGoiânia-Nerópolis,Km5,CampusII,
SetorItatiaia,CEP:74001-970Goiânia,GO,Brazil
Received21December2012–Revised7May2013–Accepted22May2013
Abstract– Givenhuman-relatedchanges,qualitydistributionaldataarerequiredforconsistentconservation.
Still, the lack of proper biogeographic information is a major setback for many groups. Here, we use new
occurrencesforAglaecaeruleaintheCerradotomodelitspotentialdistribution.WeusedMaximumEntropy
(MaxEnt) and Genetic Algorithm for Rule-Set Production (GARP) algorithms in different modeling runs and
bothpreviousandnewA.caeruleaoccurrencestopredictthisspeciesdistribution.Modelswhichusedonlythe
previousA.caerulea’srecordsdidnotpredictedthenewCerradorecords,whilethosewhereweusedthelatter
did predict the new ones as minimally suitable. A. caerulea distribution significantly increased towards the
Cerrado according toboth MaxEnt and GARP algorithms. Gallery forests are important dispersal alternatives
forseveralspeciesdwellingtheAmazonandtheAtlanticforest.NichemodelsofotherrareEuglossinibeesare
advisedtobetterevaluate theirdistributions.
Aglaecaerulea/Amazon/Cerrado/dispersalcorridor/Wallaceanshortfall/speciesdistributionmodeling
1. INTRODUCTION Whittaker et al. 2005; Brooks et al. 2006). Still,
the Wallacean shortfall, i.e., lack of proper
In a continuously changing world, which is biogeographic information, is one of the major
directly and indirectly affected by human activi- setbackshamperingconservationactions(Biniet
ties (Tylianakis et al. 2008; Dobrovolski et al. al. 2006). Such situation is even worse in mega-
2011), high-quality distributional data are essen- diverse but poorly sampled tropical regions
tial to help on the task of setting priorities and (Newbold 2010; Kamino et al. 2011), which
efficientconservationactions(Myersetal.2000; usuallylackextensivebiogeographicinformation
but suffer deep and fast environmental changes
(Bawaetal.2004;HongandLee2006).
Correspondingauthor:D.P.Silva,
[email protected] Beside their diversity, insects and other terres-
Manuscript Editor:KlausHartfelder trial invertebrates play several important
674 D.P.Silvaetal.
ecosystemicroles(e.g.,pollination,plaguecontrol, Initially, we assess whether previous occur-
nutrientcycling).However,theyhavebeenusually rences of A. caerulea are sufficient to predict
neglected in conservation actions (Diniz-Filho et the new information obtained for the Cerrado
al.2010a;Cardosoetal.2011).Eveninsectgroups biome and a doubtful Panamanian record
withextensivetaxonomic,biological,andecolog- (Moure 1967; Cameron 2004; Michener 2007).
ical dataavailable(e.g., ants, bees,odonates,and Iftheydo,dispersalofA.caeruleafromitscore
butterflies) lack consistent biogeographic data distribution can be considered the only process
(Diniz-Filho et al. 2010a; Vianna and De Marco accounting for the new data. If they do not, we
Jr2012).Despitesuchproblems,Diniz-Filhoetal. evaluate whether the inclusion of the new
(2010a)providedanoptimisticviewonhowtouse occurrences increases the total distribution for
theoretical approaches and modern methods to this species, pinpointing new suitable areas
conserveinsects,suchasecologicalnichemodels outside the Amazon for A. caerulea. Second,
(ENM).Basedonstatisticallyorderivedresponse considering all A. caerulea occurrences, we
surfaces,ENMsrelatepresencerecordsofagiven evaluate its possible dispersal paths from its
species to the available predictor variables from core distribution in the Amazon basin through
those places where it was sampled to predict the Cerrado, with particular attention to the role
environmentally suitable areas for its occurrence of riparian areas of large rivers.
(GuisanandZimmermann2000).Consequently,it
is possible to fill gaps in the biogeographic 2. MATERIAL AND METHODS
knowledge concerning species distribution and
improve the implementation of conservation ac- 2.1. A.caeruleaanditsknowndistribution
tions(NóbregaandDeMarcoJr2011).
Considering that species distribution is DifferentfromtheotherEuglossinibees,therarely
delimited by the intersection of environmen- sampled A. caerulea has a long (23–25 mm long),
tally suitable, biologically available, and slender, and flattened body and slender hind legs
biogeographically/historically reachable habi- (Cameron 2004). The only bionomical observations
tats (Soberón 2007), ENMs are useful tools in available for this species indicate that it parasitizes
the attempt to overcome Wallacean shortfall nests of Eulaema bees (Myers 1935). Given its
and implement insect-oriented biogeography rareness in entomological collections and in
conservation plans (Diniz-Filho et al. 2010a). Euglossini surveys using scent baits, it is considered
ENM techniques have been used quite often to to be a rare species in nature (Cameron 2004). Its
study insects, particularly due to the following distribution has been considered to be mostly
reasons: (1) determine potential distribution of restricted to the Amazon basin (Cameron 2004;
taxagivennewoccurrences(Almeidaetal.2010), Michener 2007). Nevertheless, this species has been
(2) assess suitable areas for future samplings latelysampledoutsideitsAmazoncoredistributionin
(Diniz-Filho et al. 2010b), (3) pinpoint areas for fourdifferentoccasions(Anjos-Silvaetal.2006,and
the implementation of new conservation units three new occurrences for the state of Goiás, Brazil,
(Nóbrega and De Marco Jr 2011), and (4) sampled by Silva, DP). Additionally, Moure (1967)
determineareaspronetoinvasionofalienspecies reported its presence in Panama. Nonetheless, such
(Mataetal.2010)orsuitableforspeciesdistribu- occurrence has been flagged as uncertain since no
tion under different global warming scenarios other specimen of A. caerulea was sampled in that
(Gianninietal.2012). country again, even after decades of new surveys
Considering new distributional data for the after thedateofthefirst record(Cameron2004).
orchid bee Aglae caerulea Lepeletier and WealsocompiledA.caerulearecordsfrommuseum
Serville (Apidae: Euglossini) outside its previ- collections [(1) DZUP—Coleção Entomológica
ously known core Amazonian distribution (see Padre J.S. Moure, Universidade Federal do Paraná,
below), here we use both previous and new Curitiba, PR, Brazil; (2) RPSP—Coleção Camargo,
distribution data to deal with two questions. UniversidadedeSãoPaulo,RibeirãoPreto,SP,Brazil;
Newrecordsand distributionofAglaecaerulea 675
(3)MZUSP—MuzeudeZoologia,UniversidadedeSão eigenvectors.Thecutoffloadingtoconsideranenviron-
Paulo,SãoPaulo,SP,Brazil;(4)COENTOL—Coleção mentalvariableasinfluentinthePCAanalysiswas0.6.
Entomológica do Departamento de Biologia,
Universidade do Estado de Mato Grosso, Cáceres, 2.3. Modeling procedures and model
MT, Brazil], online databases[(1)DiscoverLife Bee evaluation
Species Guide and World Checklist (http://
www.discover-life.org); (2) Species Link (http:// Wedividedtheoccurrencedatasetintothreecatego-
splink.cria.org.br)],andliterature(Morato2001;Otero ries: (1) “Previous” (n=36), (2) “Cerrado” (n=4), and
andSandino2003;Anjos-Silvaetal.2006).Atotalof (3) “Doubtful” Panamanian record (n=1). In a first
41occurrencesforA.caeruleawerecompiled,mostof modeling run, we randomly split the previous and
themintheAmazonbasin,butwithtworecordsfrom mostly Amazonian occurrences into70 %:30 % train-
theChocoregion,inwesternEcuadorandsouthwestern ing/testing subsets and evaluated whether the training
Colombia.Forrecordslackingtheexactsamplingsite subsetwasabletopredictthenewerandthedoubtfulA.
information,weusedGoogleEarth(GoogleInc.2012) caerulea occurrences. In a second modeling run, we
tofindcitycentercoordinatesasaproxyinformationfor includedallthenewCerradooccurrencesinthetraining
sampling sites. The geographical coordinates of the subsetandreevaluatedA.caeruleadistributionconsid-
threenewA.caeruleaoccurrencesfoundinBrazilmay ering a testing subset composed by 30 % of all A.
be found in the Supplementary Materials section caerulea occurrences (except the newer and the
(TableS1). Panamanian ones). Finally, we used all occurrences to
predictthespeciesdistribution.Thedoubtfuloccurrence
2.2. Environmental data wasneverusedinanyofthemodelingprocedures.The
modelingproceduresaresummarizedinFigureS1.
We derived seven environmental variables to be WetrainedA.caeruleadistributionmodelswithtwo
usedinourENMproceduresandproduceA.caerulea widely used algorithms: Maximum Entropy
distributionmodels.Sixofthem[annualtemperature, implemented inMaxEnt(Phillipset al. 2006; Phillips
temperature seasonality (coefficient of variation), andDudik2008)andtheGeneticAlgorithmforRule-
mean temperature of the driest quarter, annual Set Production (GARP; Stockwell and Peters 1999)
precipitation, precipitation seasonality (coefficient of implementedinopenModellerDesktopv.1.1.0(Munoz
variation), and precipitation of the warmest quarter] et al. 2011). MaxEnt is a machine-learning presence/
wereobtainedfromWorldClim(Hijmansetal.2005; pseudo-absence method which is very reliable when
http:\\www.worldclim.org). The last variable (terrain occurrence dataset have few and/or biased records
slope) was derived from Hydro-1K global digital (Pearson et al. 2007). We only modeled A. caerulea
elevation model (http://eros.usgs.gov). We selected distributionswithlinearandquadraticfeaturesselected,
these variables since they were already used as toproducesimplerbiologicalmodels(Elithetal.2011).
climate predictors in other studies which modeled GARP is a non-deterministic algorithm based in a
insectdistributions(e.g.,Almeidaetal.2010;Serraet random set of mathematical rules which may be
al.2012).Oncesomeofouroccurrenceswererelated interpreted as the limiting environmental conditions
to city center coordinates instead of actual GPS determiningspeciesoccurrences(StockwellandPeters
coordinates, we re-scaled all variables to a 5-min 1999).Definingtheareawithinwhichthespeciesmay
resolution(0.0833º≈8km). potentiallyreachisanimportantstep,whilemodeling
InordertodefinethelocationofthenewA.caerulea speciesdistribution,oncethepotentialareathespecies
occurrences in the species environmental space, we may reach, is an important feature which affects the
performedaprincipalcomponentsanalysis(PCA)with developmentofitsecologicalniche(Barveetal.2011).
all variables. Once all environmental variables had Here,wetrainedtheA.caerulea’sdistributionmodels
different units, prior to the analysis, we standardized usingthewholeextentofSouthAmericaasthespecies
them. We considered the Kaiser–Guttmann criterion maximumpotentialranges.Althoughdifferentbiogeo-
(eigenvectors with eigenvalues higher than 1; Peres- graphicregionsmaybecontemplatedwithinthisregion
Neto et al. 2005) to retain the most important PCA (e.g.,Amazonbasin,Cerrado,MataAtlântica;Nemésio
676 D.P.Silvaetal.
and Silveira 2007), once the species was already 3. RESULTS
sampledintwoofthose,totrainthemodelsconsidering
thewholeSouthAmericancontinentwasadvisedand WeretainedthreeeigenvectorsfromourPCA
methodologicallyindicated. analysis (Figure 1; Table S2). Nevertheless, we
FollowingLiuetal.(2011),weusedbothareaunder only show the results comparing the first two
the receiver–operator curve (AUC) and true skilled eigenvectors because such interpretation is
statistics (TSS) to assess models performance. The simpler and the other comparisons (PC1 vs.
AUCisathreshold-independentstatisticsvaryingfrom PC3 and PC2 vs. PC3) had similar results
0to1.Valuesaround0.5representdistributionmodels (Figure S2A–B). All new occurrences from
nobetterthanrandomandvaluesaround1representa Cerrado were separated from all previously
perfect fittingbetweentheobservedandthepredicted known occurrences for A. caerulea. On the
speciesdistribution.Acceptabledistributionmodelsare otherhand,thedoubtfulPanamanianoccurrence
thosewithvalueshigherthan0.7.TSSisathreshold- was always among the previous records for the
dependent statistics which varies from −1 to +1 modeled species (Figures 1 and S2A–B).
(Allouche et al.2006). TSSvaluesnear0 ornegative The four new A. caerulea occurrences con-
represent distributions no better than random, while siderably increased its distribution range, espe-
values equal to +1 represent a perfect agreement cially considering their distances to the nearest
between the observed and the predicted distribution. occurrence records previously sampled in the
Weused10,000randompseudo-absencesduringmodel Amazon [∼2,000 km for the occurrences in
evaluationprocedures. Goiás and ∼1,000 km for the one sampled by
We used the lowest predicted suitability value Anjos-Silva et al. (2006)]. Generally, the distri-
associated with a given observed presence record bution models produced only with the previous
(lowest presence threshold—LPT; Pearson et al. occurrences showed a fair to good performance
2007),todetermineA.caeruleadistributiongenerated when considering both TSS and AUC values,
byeachmodelingalgorithm.Ecologicallyspeaking,the respectively (Table I).
LPTidentifiesthepixelspredictedtobeasminimally The doubtful Panamanian record was pre-
suitableforthespeciesoccurrenceasitsactualobserved dicted as suitable for A. caerulea in all models
records.ForthefinalA.caeruleadistribution,weuseda (Figure 2). On the other hand, the models using
single mean consensus map between both modeling only the previous occurrences as the training
algorithmsinorder todetermineA. caerulea distribu- subsethadalowpredictivepowerregardingthe
tion,consideringtheLPTvaluesthateachindependent new occurrences for the Cerrado savanna
model(MaximumEntropyandGARP)obtainedwhen (Figure 2a–b). The model generated only with
all occurrences (including the new Cerrado records) the previously known A. caerulea occurrences
were used. This consensus method considers the predicted areas in northern Peru, southeastern
separated values in each grid cell for all predictions Colombia, northeastern Ecuador, southern
obtained from different modeling algorithms to deter- Venezuela, and Amazonas and Para states in
mine the mean modeled species distribution. This Brazil as suitable for A. caerulea.
method was considered to be one of the most robust TheinclusionofthenewCerradorecordshad
while determining the agreement of species distribu- a great effect on models performance (Table I),
tions(Marmionetal.2009).Forthesakeofdiscussing with overall decreases in both AUC and TSS
the distribution of A. caerulea, considering its known values. Although the new occurrences were
occurrencesandtheknownEuglossinisamplingeffort predicted as minimally suitable in both model-
in South American, we also show the ensemble ing algorithms, they increased A. caerulea
distribution obtained from the threshold derived from potential distribution by almost 30 and 50 %,
the “receiver–operator curve” (ROC;Liu etal. 2011). according to GARP and MaxEnt, respectively
While LPT minimizes omission but maximizes com- (Figure 2c–d). After their inclusion, we ob-
missionerrors,ROCbalancesbotherrorsandproduces served additional range increases towards the
smallerdistributionswhencomparedLPT. Cerrado savanna and Bolivia. The Panamanian
Newrecordsand distributionofAglaecaerulea 677
Figure 1.Principal components analysis results showing the separation of the new Cerrado occurrences
(asterisks)fromthepreviousones(blackcircles)recordedforA.caerulea.NotethatthedoubtfulPanamanian
occurrence (diamonds) is suitable for A. caerulea occurrence. The arrows represent which environmental
variables were positively and negatively related to each retained eigenvector. The percentages represent the
amountofvariationexplainedbyeacheigenvector.
occurrencewasstillpredictedassuitableinboth occurrences records for A. caerulea within the
modeling algorithms and in the A. caerulea Cerradobiome(Figure3a),it also increased its
consensus map (Figure 3a, b). distribution into arid areas in northwestern
Considering the consensus maps, although the Venezuela and northern Colombia, where the
LPT threshold minimally predicted the new species is assumed to be absent. On the other
TableI.PerformanceofA.caeruleamodelsconsideringtrainingsubsetswithoutandwiththenewoccurrences
fromtheCerrado. ThedoubtfulPanamanian occurrencewasnotusedinthemodels.
Amazonian occurrences All occurrences Alloccurrences
(70:30) (70:30) (100:100)
Modelingalgorithm AUC TSS AUC TSS AUC TSS
MaxEnt 0.769 0.609 0.699 0.424 0.816 0.532
GARP 0.839 0.598 0.769 0.422 0.858 0.487
Numbersinbracketsrefertotheproportionofoccurrencesusedinthetraining/testsubsetsinallmodelingprocedures
TSSvaluesconsidertheLPTthreshold,SDstandarddeviation
678 D.P.Silvaetal.
Figure 2.Distribution models generated by MaxEnt (a, c) and GARP (b, d) using only the previous (left) or
both the previous and the newer occurrences from the Cerrado (right) in the training subset to predict A.
caeruleapotentialdistribution.CirclesrefertothepreviousA.caerulea’sknownrecords;starsrefertothenew
occurrences foundintheCerradoBiome;questionmarksrefer tothedoubtfulPanamanian occurrence.
hand, although the ROC threshold minimized A. rence(Cameron2004)issuitableasanoccurrence
caerulea distribution in those areas, it record and that A. caerulea distribution range,
did not predict the new occurrences sampled in previouslybelievedtoberestrictedmostlytothe
the Cerrado as suitable for A. caerulea distribu- Amazon basin (Cameron 2004), also includes
tion. Nevertheless, neighboring areas near those some portions of the Brazilian Cerrado. These
new occurrences were predicted as suitable results have important implications for under-
(Figure3b). standing the dispersal and distribution of
EuglossinibeesinSouthAmerica.
4. DISCUSSION As the second largest biome and the largest
savannainSouthAmerica(Ab’Saber1977),the
In this study, we presented three new occur- Cerrado separates two important biomes: the
rences for A. caerulea, a rare Euglossini bee Amazon and the Atlantic forests. Despite its
species from South America, and modeled its usualxeric-likeenvironment,itcommonlybears
distribution considering these additional records. evergreengalleryforestsnearriversandstream-
We showed thatthe doubtfulPanamanianoccur- lets. Studies with plants (Méio et al. 2003),
Newrecordsand distributionofAglaecaerulea 679
Figure 3.Mean ensemble forecast produced by MaxEnt and GARP considering both a LPT and b ROC
thresholds.Notethatsemi-desertareasinnorthernColombiaandnorthwesternVenezuelaarenotpredictedas
suitable when we consider only the ROC threshold. The depicted polygon in a and b refers to areas where
future surveys for A. caerulea in gallery forests should take place. Circles refer to the previous A. caerulea’s
known records; stars refer to the new occurrences found in the Cerrado Biome; question marks refer to the
doubtfulPanamanian occurrence.
birds (Silva 1996), butterflies (Brown Jr 1987; inhabit in the Amazon were recently sampled
1992), mammals (Redford and Da Fonseca in Cerrado (see Almeida et al. 2010 for an
1986), and solitary bees (Aguiar and Melo example). Although large rivers within the
2007) have already suggested the importance Cerrado (e.g., Araguaia and Paranã rivers) may
of the gallery forest while facilitating dispersal actasimportantdispersalbarriersfornon-flying
of species dwelling either in the Amazon or in organisms (Cáceres et al. 2008), such barriers
the Atlantic Forest. In Cerrado, gallery forests maynotrestrictthedispersalofEuglossinibees,
provide important habitat conditions which given their excellent flight capacities and un-
allow Euglossini bees (and insects associated common vagility (Janzen 1971).
with mesic environments) to easily disperse The distribution model trained only with the
(Moura and Schlindwein 2009). They also previous, mostly Amazonian, occurrences did not
provide humidity for the development and predict the newer Cerrado records and even the
establishment of orchid plant species, which modelwithall occurrences predictedtheobserved
are generally used by the males of Euglossini Cerrado occurrences as minimally suitable for A.
bees as scent sources (Dressler 1982). Such caerulea.Thenewerrecordsappeartobeoutliersin
dependence on the gallery forest to disperse in theenvironmentalnicheparametersoftheknownA.
the Cerrado may be the reason why other caerulearecords,whichexplainthelowpredictive
insects species previously thought only to power for these occurrences. Similar results were
680 D.P.Silvaetal.
alsoobservedforthemodeleddistributionofother (GAR Melo, unpublished data). Nevertheless,
Amazonian species sampled within the Cerrado considering the strong association of
(Almeidaetal.2010),aswellasforotherEuglossini Euglossini with mesic environments, future
beessampledoutsidetheirpreviouslyknownranges sampling surveys in the humid formations
(Hinojosa-Díazetal.2009). found in those dry areas should be consid-
At first, these results may indicate that A. ered in order to validate model predictions,
caerulea populations in Cerrado are in fact sink independently of the thresholds and modeling
populations (Pulliam and Danielson 1991; algorithms used. Future field surveys should
Pulliam 2000), since the suitability in these areas also take placeingalleryforestsfoundinthearea
supportthepredictionoftheoccurrenceunderthe comprehending the southeastern Para and
LPT threshold (but at minimal values) and was Amazonas states, as well as northern Mato
predicted as absent under the ROC threshold. Grosso and Tocantins states, areas predicted as
Considering the distribution of habitat suitability, suitable in the consensus maps considering both
only sites deep in the Amazon (areas with high theLPTandtheROCthresholds(polygonshown
habitat suitability) would be considered as source inFigure3a,b).
populations.Nevertheless,thepredictedsuitability Although standardized sampling protocols
maynotcorrespondtothetruehabitatsuitability,as may be considered inefficient on sampling rare
perceived by A. caerulea bees. For instance, species,thecontinuoususeofENMtechniques,
Anjos-Silvaetal.(2006)sampledeightA.caerulea whenever new occurrences for rare species are
bees in a gallery forest within the Cerrado, with discovered, may improve our knowledge on
vegetational features similar to both the Amazon their distribution range. Such strategy for rare
and the Atlantic forest (sensu lato) (Pinto and species has been used with success elsewhere
Oliveira-Filho 1999). In Cerrado gallery forests, (Raxworthy etal.2003;Pearsonetal.2007;De
either minimally or not predicted as suitable, we Siqueira et al. 2009) and should be used
sampled two specimens of A. caerulea (Silvânia continuouslyasitwilloptimizetoalargeextent
County,Goiásstate).Therefore,thedependenceon the amount of resources invested in field
gallery forests of Euglossini bees (Moura and surveys (Guisan et al. 2006). Similar ap-
Schlindwein 2009) may significantly increase A. proachestothisstudyshouldalsobeconsidered
caerulea habitat suitability within the Cerrado, a to other South American Euglossini species
biomewhichnaturallyharborlowEuglossinibees sampled outside their previously known distri-
diversity(NemésioandSilveira2007). butions (Anjos-Silva 2008; Silva and Rebêlo
A biased sampling effort in different habitats 2009), in order to properly assess the distribu-
(Kamino et al. 2011) may underestimate species tion patterns of these species and pinpoint not-
distribution, affecting the predicted suitability in sampled but potentially fruitful areas for future
thenewoccurrencerecords(Almeidaetal.2010). surveys. This suggestion is particularly appro-
Therefore, in order to validate both models and priate for areas of poor knowledge on
generatethresholdsforbinarypredictionbasedin Euglossini diversity, such as those in the
true absences instead of computer-generated Brazilian Cerrado (Nemésio and Silveira
pseudo-absences, future surveys should be 2007). Despite plenty of studies on Euglossini
performedeitherinareaswheremodelsuitability bees in humid environments from South
wasloworwherethespeciesdoesnotoccur. America (e.g., Mata Atlântica and the Amazon
Considering the known Euglossini sampling Forest), very few systematic studies have been
effort in South America, the arid areas in northern carried outindryareas ofthe continent,aswell
Colombia and northwestern Venezuela, as well as as in gallery forests within these biomes, which
the dry forests in northwestern Peru and southern may bear a still unknown Euglossini diversity.
Ecuador,aregoodcandidatesforfurtherevaluation Therefore, we advise future surveys of
of the models, since they seem too dry to be Euglossini bees to be conducted in gallery
consideredsuitablefortheoccurrenceofA.caerulea forests of such environments in order to fill a
Newrecordsand distributionofAglaecaerulea 681
gap on our current knowledge of the distribu- Allouche, O., Tsoar, A., Kadmon, R. (2006) Assessing
tion patterns of orchid bees. the accuracy of species distribution models: preva-
lence, kappa and the true skill statistic (TSS). J.
Appl.Ecol.43,1223–1232
ACKNOWLEDGMENTS Almeida, M.C., Côrtes, L.G., De Marco Jr, P. (2010)
New records and a niche model for the distribu-
tion of two Neotropical damselflies: Schistolobos
We would like to acknowledge John S. Ascher, boliviensis and Tuberculobasis inversa (Odonata:
from the American Museum of Natural History, and Coenagrionidae). Insect Conserv. Divers. 3, 252–
Eduardo Almeida, from Coleção Camargo USP-RP, 256
and Kelli Ramos, from Museu de Zoologia da USP, Anjos-Silva,E.J.(2008)DiscoveryofEuglossacognata
which provided us with several A. caerulea occur- Moure (Apidae: Euglossini) in the Platina Basin,
Mato Grosso State, Brazil. Biota Neotropical 8,
rencerecords.Wearealsogratefultotwoanonymous 80–83
reviewers which provided valuable comment to a
Anjos-Silva, E.J., Camillo, E., Garófalo, C.A. (2006)
previous version of this manuscript. DPS received a
OccurrenceofAglaecaeruleaLepeletier&Serville
doctorate scholarship from Conselho Nacional de (Hymenoptera: Apidae: Euglossini) in the Parque
Desenvolvimento Científico e Tecnológico (CNPq). Nacional da Chapada dos Guimarães, Mato Grosso
PDMandGARMhavebeencontinuouslysupportedby State.Brazil.Neotrop.Entomol.35,868–870
CNPq grants. EJAS was supported by Coordenação de Barve,N.,Barve,V.,Jiménez-Valverde,A.,Lira-Noriega,
AperfeiçoamentodePessoaldeNívelSuperior(CAPES; A.,Maher,S.P.,Peterson,A.T.,Soberón,J.,Villalobos,
F. (2011) The crucial role of the accessible area in
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