Contrasting Patterns of Gene Flow for Amazonian Snakes That Actively Forage and Those That Wait in Ambush

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Advance Access publication May 20, 2017

Original Article

Contrasting Patterns of Gene Flow for

Amazonian Snakes That Actively Forage and

Those That Wait in Ambush

Rafael de Fraga, Albertina P. Lima, William E. Magnusson, Miquéias Ferrão, and

Adam J. Stow

From the Programa de Pós-Graduação em Ecologia, Instituto Nacional de Pesquisas da Amazônia (INPA), Av. Efgênio

Salles, 2936, Aleixo, CEP 69067–375, Manaus, Amazonas, Brazil (Fraga and Ferrão); Coordenação de Biodiversidade

(CBio), Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Brazil (Lima and Magnusson); and Department

o Biological Sciences, Macquarie University, Sydney, Australia (Stow).

Address correspondence to R. de Fraga at the address above, or e-mail: r.de [email protected]. Received September 12, 2016; First decision November 16, 2016; Accepted May 18, 2017.

Corresponding Editor: Tomas Hrbek

Abstract

Knowledge o genetic structure, geographic distance and environmental heterogeneity can be used

to identi y environmental eatures and natural history traits that in uence dispersal and gene ow.

Foraging mode is a trait that might predict dispersal capacity in snakes, because actively oragers

typically have greater movement rates than ambush predators. Here, we test the hypothesis that

2 actively oraging snakes have higher levels o gene ow than 2 ambush predators. We evaluated

these 4 co-distributed species o snakes in the Brazilian Amazon. Snakes were sampled along an

880 km transect rom the central to the southwest o the Amazon basin, which covered a mosaic o

vegetation types and seasonal di erences in climate. We analyzed thousands o single nucleotide

polymorphisms to compare patterns o neutral gene ow based on isolation by geographic distance

(IBD) and environmental resistance (IBR). We show that IBD and IBR were only evident in ambush

predators, implying lower levels o dispersal than the active oragers. There ore, gene ow was

high enough in the active oragers analyzed here to prevent any build-up o spatial genotypic

structure with respect to geographic distance and environmental heterogeneity.

Subject area: Conservation genetics and biodiversity

Keywords: dispersal, isolation by distance, isolation by resistance, landscape genomics, SNPs

Quan i ying he pa ial di ribu ion o gene ic varia ion ha pro-vided knowledge o he environmen al ac or in uencing gene ow and di per al (e.g., S ow e al. 2001; Dudaniec e al. 2013). The e da a have been applied o mea ure how he erogenei y o he na ural environmen in uence di per al and gene ow, and al o evalua e an hropogenic habi a lo and ragmen a ion (Bank e al. 2007; Pe erman e al. 2014). In more recen year , pa ial model have been u ed o provide more en i ive e o land cape in uence on

gene ic ruc ure, bu he e land cape gene ic approache have rarely been applied o ropical rain ore axa (Ruiz-Lopez e al. 2016). Ob aining in orma ion on di per al via direc ob erva ion can be ex remely di fcul (Lowe and Allendor 2010), or example, due o pecie ize, heir habi a u e, or level o de ec abili y. In hi re pec , pecie o ropical rain ore are o en ypifed by low de ec abili y (e.g., Fraga e al. 2014) and a uch, here i a pauci y o da a on pa

-ern o gene ow and di per al or ome axonomic group . Thi i

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exemplifed by nake or which mo da a on gene ow and di per-al are available rom empera e biome (e.g., Lougheed e al. 1999; Blouin-Demer and Wea herhead 2002).

Tropical rain ore are known o con ain a pec acular diver i y o nake (Bernarde e al. 2012; Fraga e al. 2013a), exhibi ing a va range o na ural hi ory rai , ye here i a lack o da a on gene ow and di per al or hi group. The e da a can be u ed o com-pare level o connec ivi y or pecie wi h di eren li e hi ory rai ,

hu con ribu ing o our knowledge on he ecology o he e pecie , and he mechani m underpinning heir curren di ribu ion . Thi in orma ion can al o be valuable or con erva ion, becau e i pro-vide da a on how habi a lo in uence gene ow, and how much in ra pecifc gene ic varia ion i cap ured wi hin re erve y em (S ow e al. 2004; Bell and Okamura 2005).

The rela ion hip among gene ic ruc ure, geographic di ance, and environmen al he erogenei y allow he di per al charac er-i er-ic and gene ow or par er-icular pecer-ie o be charac erer-ized, and an a e men o he environmen al ea ure ha hape pecie di

-ribu ion (Lowe and Allendor 2010; Wang and Bradburd 2014). I ola ion-by-di ance (herea er IBD) and i ola ion-by-re i ance (herea er IBR) are he 2 model o which pa ial pa ern o gene ic variabili y can be f ed (e.g., Wrigh 1943; McRae 2006; Koen e al. 2012; Marro e e al. 2014). The fr i e ima ed imply by e ing or correla ion be ween gene ic di ance and geographic di ance. The la er may be quan ifed by calcula ing he probabili y o an individual di per ing rom one loca ion o ano her a er weigh ing he “re i ance” o di per al in each o he in ervening environmen . The implica ion o hi re i ance-weigh ing o di per al be ween he e 2 poin i hen a e ed over a range o po ible pa hway (Man hey and Moyle 2015; Wang and Bradburd 2014).

Re i ance ur ace can be u ed o de ec ub le in uence o environmen al di erence on gene ow ha may no be de ec ed u ing popula ion gene ic mea ure uch a gene ic diver i y, diver-gence and ruc ure, inbreeding and gene ic bo leneck (Rade piel and Bru ord 2014). Land cape in uence on gene ow or auna in ropical ore have been e pecially hard o evalua e (Rade piel and Bru ord 2014). However, he applica ion o analy e ba ed on re i ance ur ace ha been hown o be an e ec ive mean o di en angling an hropogenic and na ural in uence on ropical ore (Ruiz-Lopez e al. 2016). By op imizing re i ance ur ace , re earcher are able o be er evalua e ecological proce e (e.g., level o di per al) underlying gene ow and habi a connec ivi y. Environmen al re i ance-ba ed model are ui able o compare pa ern o gene ow o di eren pecie , becau e hey a ume ha gene ow may be in uenced by diver e mechani m , uch a non-random migra ion, di per al capabili y, li e hi ory, and he geo-graphic ea ure o he udy area (Dudaniec e al. 2013). The e approache clearly have u e ul applica ion wi hin very he erogene-ou environmen , and wi h organi m ha have low de ec abili y,

or which mea uring he e ec o habi a on connec ivi y ha hi h-er o been unachievable.

Snake con i u e approxima ely 6% o ver ebra e diver i y (Ue z and Hošek 2015) and are known o have key ecological unc ion , in addi ion o making numerou con ribu ion o human ocie ie in cul ure, medicine, and economic (Konar and Monak 2010). Knowledge o heir di per al pa ern will enable con erva ion man-ager o be er predic he con equence o environmen al change. However, knowledge o di per al in nake can be di fcul o ob ain becau e o heir ypically cryp ic li e yle (S een 2010). Quan i ying level o connec ivi y a land cape cale and pecie –habi a a

ocia-ion may be di fcul o achieve in he Amazon rain ore (Fraga

e al. 2014). Thi include ob aining knowledge o di per al or par-icular pecie hrough con inuou he erogeneou ore , and con-equen ly, whe her ome habi a acili a e gene ow more o han o her . In par icular, ob aining u fcien number o individual or analy e o gene ow and he in erence o di per al i challeng-ing. Recen ly, more power ul analy e ba ed on hou and o ingle nucleo ide polymorphi m (SNP ) have become acce ible, and he e analy e allow reliable e ima e o gene ic ruc ure rom ewer individual (e.g., Willing e al. 2012).

Al hough he Amazon lowland have an excep ionally high num-ber o nake pecie (e.g. Bernarde e al. 2012), he mechani m gen-era ing and main aining nake diver i y over land cape are poorly known. Environmen al gradien may in uence pa ern o nake communi y a embly a regional cale (Fraga e al. 2011) and di -per al hrough di eren habi a a local cale (Fraga e al. 2013b). However, gene ow and gene ic ruc uring o nake in he Amazon ha no been udied. The biodiver i y o he region ampled in hi udy i under pre ure by rapid urban grow h in he la decade (Filho 1997), road con ruc ion (Soare -Filho e al. 2006) and ar if-cial ooding by hydroelec ric power plan (Fearn ide 2014).

Knowledge o pa ern o gene ow and di per al or organi m haring par icular rai may allow generaliza ion o be drawn, whereby one could u e he e rai o predic he con equence o habi a change o di per al po en ial and gene ic ruc ure. When evalua ing he impac o environmen al change on di per al, de ailed pecie -level knowledge o di per al i o en lacking, and in he e ca e , pecie rai have been u ed o predic di per al po en ial, or example, larval mode in marine organi m and wing morphology in bird and in ec (Anger e al. 2011). There ore, charac erizing gene ow and di per al in nake pecie wi h

con-ra ing ocon-raging mode migh con ribu e o da a ha will even u-ally enable predic ion on connec ivi y o nake , o be made on he ba i o pecie rai .

In hi udy, we inve iga e whe her gene ic varia ion can be explained by IBD and/or IBR in order o de cribe pa ern o di -per al or nake pecie o he Amazon Ba in. We e whe her gene ow ollow IBD and/or IBR pa ern or 4 co-di ribu ed nake pecie , 2 o which are ambu h preda or (Bothrops atrox and Corallus hortulanus) and he o her 2 are ac ive orager (Leptodeira annulata and Philodryas georgeboulengeri). Foraging mode may be a ocia ed wi h di per al hrough a ribu e uch a ac ivi y pa ern (Cooper e al. 2001), habi a u e (Fedriani e al. 1999), dige ive phy iology (Hil on e al. 1999), ea onal pa ern o reproduc ion (Colli e al. 1997) and mor ali y (Wille e e al. 1999). Radio racking da a have hown ha ome ambu h

preda-or nake have low mobili y, preda-or example, B. atrox can move up o 150 m in our mon h (Fraga e al. 2013b), and Crotalus duris-sus can move up o 20 m per day on average (Toze i e al. 2009). In con ra , ac ive orager uch a Natrix natrix can cover 150 m in a ingle day (Mad en 1984), and emale o Stegonotus cucul-latus can move up o 400 m per day during he breeding ea on (Brown e al. 2005). Here, we hypo he ize ha lower level o di per al ob erved in he ambu h preda or will re ul in le gene ow a he land cape cale han he wo pecie o nake ha ac ively orage.

Here, we pre en a land cape- cale overview where we examine how a combina ion o geographic di ance, environmen al he eroge-nei y, and pecie behavioral rai in uence gene ow. Specifcally, we are in ere ed in quan i ying pa ern o pa ial gene ic varia ion driven by IBD and/or IBR, and e whe her oraging mode i a oci-a ed wi h level o gene ic ruc ure.

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Materials and Methods

Target Species

The common lancehead, B. atrox, i a noc urnal pi viper (Cro alinae), widely di ribu ed hroughou he Amazon Ba in. The pecie i pri-marily erre rial, bu individual , e pecially juvenile , can climb in vege a ion up o 2 m rom he ground. I i an ambu h preda or ha i ound in a varie y o habi a (Mar in and Oliveira 1999), bu a grea er den i y o individual ha been ound in area near ream (Fraga e al. 2013b).

The garden reeboa, C. hortulanus, i a noc urnal boid (Boinae), widely di ribu ed in di eren ore ed habi a in Sou h America. The pecie i an ambu h preda or, arboreal, and i end o be ed-en ary, ped-ending long period in mall area (Hender on 1997). The

pecie how marked polychroma i m, wi h up o 5 ympa ric color morph (Duar e e al. 2015).

The ca -eyed banded nake Leptodeira annulata annulata i a noc urnal dip adid (Dip adinae), widely di ribu ed in nor hern Sou h America. The pecie i an ac ive orager, which o en move and hun a ground level, al hough i may climb on o vege a ion o leep (Mar in and Oliveira 1999). The pecie i a habi a -general-i , and -general-ind-general-iv-general-idual may be ound -general-in d-general-i urbed area .

The ou hern harpno e nake P. georgeboulengeri (Dip adinae) ha he malle geographic range o he pecie inve iga ed in hi udy, being limi ed o ou h- ou hwe ern Amazonia (Pruden e e al. 2008). I biology i poorly known, bu i how imilar habi o he clo ely rela ed Philodryas argentea ( ee Xenoxybelis argentea in Mar in and Oliveira 1999). I i an ac ive, diurnal, arboreal preda or.

Study Area and Snake Sampling

We ampled nake along approxima ely 880 km rom he cen ral (Manau ) o he ou hwe (Por o Velho) region o he Amazon lowland . Environmen al he erogenei y along he udy area

con-i o gradcon-ien o vege a con-ion cover ype and clcon-ima con-ic ea onalcon-i y

(Figure 1). In he nor h o our udy area we ampled he Ducke Re erve, which i covered by 100 km2_{o primary non ooded ore}

and uppor perennial ream . In he cen ral region o our udy area (Puru – Madeira in er uve) we ampled primary and old ec-ondary ore which are cro ed by a ederal highway (BR-319) which wa par ially abandoned in he 1980 . Thi region i char-ac erized by ore which are ea onally ooded by over ow rom in ermi en ream , and pa che o arboreal Campinarana, which i a ore growing on whi e and. In he ou hern par o our udy area (Madeira River, Por o Velho) we ampled primary and old ec-ondary ore , charac erized by a drier clima e compared o he re o he udy area, wi h mo ream being comple ely dry in he dry ea on. The region i mo ly covered by primary and old econd-ary rain ore , bu pa che o ore ea onally ooded by river and open under ory ore are al o pre en . De pi e nake co-occurrence o en being in uenced by ecological gradien in he Amazon region (Fraga e al. 2011), all he pecie udied here are ound in he di

-eren habi a wi hin he udy area.

We ampled nake rom 21 RAPELD module (Magnu on e al. 2013), each o which i 5 km2_{, wi h an average di ance o 40}

km be ween neighboring module . Each module con ain 10 plo , 250 m long and 10 m wide each, ollowing he al i udinal con our line , and di ribu ed along 2 parallel rail (5 plo per rail), wi h 1 km be ween neighboring plo .

We ound nake by ac ively earching he module a nigh , lim-i ed by pace (plo area) and lim-ime (1 h per plo ), wlim-i h 2 ob erver per plo . We ampled each plo 4 ime , a in erval o 2–8 mon h . We cap ured nake by hand or wi h Pil rom ong and main ained hem in o co on bag un il he nex day, when hey were acrfced, ma erial removed or gene ic analy e , and fxed or depo i-ion in he Herpe ological ec i-ion o he Zoological collec i-ion o he In i u o Nacional de Pe qui a da Amazônia (INPA-H, Manau , Brazil). We collec ed nake under permi rom IBAMA/SISBIO (Mini ry o Environmen , Governmen o Brazil) proce number 02001.000508/2008–99 and 13777. De ailed in orma ion on ample

Figure 1. Sampling modules (blue circles) across the Amazon basin, that have been used to contrast patterns o gene ow among 4 snake species. The study area comprises di erent habitats based on vegetation-cover types and climate seasonality. The rectangles zoom in on areas with modules that are too close together to be distinguished on larger scale. The ellipse on the map o South America shows the study area on a continental scale, and the acronyms are the Brazilian states o Amazonas (AM), Pará (PA), and Mato Grosso (MT).

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ize per pecie and locali ie may be ound in he Supplemen ary Ma erial (Appendix 1).

SNP Data

We ex rac ed and purifed DNA rom mu cle i ue ample u ing he GenCa ch™ Genomic DNA Ex rac ion Ki . We mo ly ollowed he pro ocol ugge ed by he manu ac urer, bu we added an ex ra hour o incuba ion or dige ion. We checked DNA quali y vi ually u ing 0.8% agaro e gel. We en ub ample o 0.5 µg o high quali y DNA ample o Diver i y Array Technology P y. L d. (Canberra, Au ralia), where SNP were di covered and geno yped u ing he andard Dar Seq™ pro ocol (Pe roli e al. 2012). I i ba ed on a combina ion o Diver i y Array (DArT) marker (Jaccoud e al. 2001; Kilian e al. 2012) and nex -genera ion Illumina equenc-ing (San aloni e al. 2011). We pre en a brie de crip ion o he Dar Seq™ pro ocol in he Supplemen ary Ma erial (Appendix 2).

DArT geno yped more han 14,000 SNP or each pecie . We fl ered hi da a e by excluding SNP wi h unknown core or gen-o yping, read dep h <10, call ra e <70%, and repea abili y <90%. Addi ionally, we excluded monomorphic loci and loci wi h more han one SNP o reduce a i ical bia rom linkage di equilibrium.

Pa ern o neu ral gene ow were evalua ed u ing 2 me hod o iden i y loci wi h a ignal o elec ion. The e were F_st ou lier e ba ed on Baye ian modeling (Baye can, Foll and Gaggio i 2008) and he la en ac or mixed model (LFMM) approach, which e or correla ion be ween gene ic polymorphi m and environmen al variable . The LFMM approach wa applied u ing he LEA package (Fricho and Françoi 2015) in R (R Developmen Core Team 2015). We e bo h Baye can and LEA wi h al e di covery ra e o 0.01. However, we did no iden i y any locu wi h a rong ignal o po

i-ive or nega i-ive elec ion and here ore our da a e only de ec ed pa ern expec ed under neu rali y.

Investigating Genetic Structure

The mall ample ize preven ed u rom u ing analy e ba ed on allele requencie e ima ed per locali y. In ead, we inve iga ed global gene ic ruc ure or each pecie and al o carried ou indi-vidual-ba ed analy e . U ing he en ire da a e or each pecie , we

e ed or ignifcan devia ion rom Hardy–Weinberg Equilibrium (HWE) per locu , o evalua e he null hypo he i o random ma ing. We al o con ra ed he value per locu or expec ed he erozygo i y (H_E) and ob erved he erozygo i y (H_O). Limi ed gene ow and he pre ence o gene ic ruc ure will re ul in a pa ial Wahlund e ec (Wahlund 1928). Thi i becau e pooling gene ic da a where gene ic ruc ure i pre en will re ul in he erozygo i y defci compared o HWE expec a ion.

Measuring Genetic Di erentiation

To mea ure gene ic di eren ia ion be ween individual we u ed pair-wi e gene ic di ance ba ed on geno ypic rela edne , which i be er

ui ed o de ec ing ub le gene ic varia ion. Thi i becau e geno ype are hu ed a each genera ion and geno ypic ruc ure derived rom geno ypic imilari y be ween individual can be in uenced by hor

-erm proce e , uch a he pa ial di ribu ion o clo e rela ive (S ow e al. 2001). We u ed he R-package rela ed (Pew e al. 2015), which e ima e pairwi e rela edne wi h 7 di eren indice , and iden ife he be index or he da a e by comparing Pear on’ cor-rela ion be ween ob erved and expec ed cor-rela edne value or each e ima or (Pew e al. 2015). The Ri land index (Ri land 1996) wa iden ifed a he be e ima or o rela edne be ween individual

or all pecie in our da a e . We u ed di ance ma rice ba ed on he Ri land index o e he e ec o IBD and IBR on gene ic di

eren-ia ion, and in PCA’ o a e or gene ic clu ering.

Constructing the Environmental Resistance

Sur aces

The udy area i charac erized by a mo aic o di eren vege a ion ype in uenced by di erence in clima ic ea onali y over a la i u-dinal gradien o abou 7 degree . The ou hern ore o he udy area con ain more open vege a ion and more pronounced clima ic ea onali y compared o he nor hern ore o he udy area. The e, in urn, are den er and more humid hroughou mo o he year (Supplemen ary Ma erial, Appendix 3). There ore, in order o cap ure environmen al he erogenei y in our re i ance ur ace, we elec ed vege a ion-cover ype a a di cre e variable and ea onali y in empera ure and rain all a con inuou variable . Each o he e variable i likely o drive, or re ec large- cale ecological change , and con equen ly we con idered he e a likely o be a ocia ed wi h any change in connec ivi y or he pecie in que ion. The environ-men al variable were ob ained in ra er orma in he public repo i-ory Ambda a (Amaral e al. 2013; www.dpi.inpe.br/Ambda a). Ambda a provide environmen al da a or he en ire Amazon ba in, and he ra er fle have a re olu ion o 1 km. We cropped he ra er fle o our udy area and reduced he re olu ion o 12 km. Thi i an appropria e cale, becau e he cale a which we defned habi a , uch a he di ribu ion o di eren vege a ion cover ype and varia-ion in clima e ea onali y along he udy area i ar grea er han 12 km. Likewi e, he di ance be ween locali ie where ampling ook place i ar grea er han 12 km (Supplemen ary Ma erial, Appendix 1). We modifed he ra er fle u ing he ra er R-package (Hijman 2015).

Mo o he me hod u ed o build re i ance ur ace require a priori defni ion o maximum re i ance value o environmen al variable . Fac or limi ing di per al can be con picuou , uch a low al i ude o moun ain goa in nor hern Uni ed S a e (Shirk e al. 2010). However, here we were in ere ed in inve iga ing ac or in uencing gene ow acro ub le varia ion in vege a ion and clima ic ea onali y in he Amazon rain ore . There ore, we weigh ed re i ance u ing gene ic algori hm ha combine

geno-ype , geographic loca ion , and environmen al layer (Pe erman 2014). Gene ic algori hm (GA ) are u ed o olve op imiza ion problem and imula e he evolu ionary proce in na ural y em (Scrucca 2013). The op imum weigh ing o re i ance ur ace wa apprai ed by running he evolu ionary proce imula ed by he GA a implemen ed by he R-package Re i anceGA (Pe erman 2014). Thi approach overcome he challenge o complex environmen al he erogenei y and having no a priori in orma ion on he in uence o habi a ype on di per al. In addi ion, he me hod u ed in hi udy allow mul iple re i ance ur ace (e.g., 3 environmen al layer com-bined) o be op imized (Pe erman 2014).

We developed IBR model or each pecie in an i era ive a hion u ing he GA o weigh he re i ance impo ed by vege a ion cover ype, ea onali y in empera ure, and ea onali y in rain all. A each i era ion, we hen calcula ed pairwi e re i ance value be ween our ampling locali ie u ing bo h circui heory (Circui cape, McRae and Beier 2007; McRae e al. 2008; McRae and Shah 2009) and lea -co pa h (e.g., Driezen e al. 2007; Wang e al. 2009). The Re i anceGA R-package hen f a linear mixed e ec model where our ob erved pairwi e gene ic di ance were he re pon e and pair-wi e re i ance di ance wa he predic or (Pe erman 2014). The be

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model or each pecie wa de ermined u ing Akaike in orma ion cri-erion (AIC; Pe erman 2014). The e ep are carried ou i era ively, wi h he individual belonging o he popula ion wi h he be AIC carried orward o he nex genera ion in he evolu ionary proce modeled u ing he GA. I era ion are con inued o a maximum o 1000 i era ion and are opped a er 25 genera ion have pa ed wi hou improvemen o AIC.

To ur her compare level o di per al be ween ambu h preda or and ac ive orager we u ed he PopGenRepor R-package (Gruber and Adamack 2015). We u ed pairwi e co di ance ma rice (gen-era ed by Re i anceGA) o e ima e he probabili y o 5% o indi-vidual rom a ampling module di per ing o a neighboring module, u ing he average di ance be ween module (40 km). We predic ed ha ambu h preda or would have lower di per al probabili ie han ac ive orager . Becau e we can’ make any a priori predic ion o migra ion ra e or he pecie udied, we imula ed he ame di per al ra e or all pecie , and hen e ed or di erence in di

per-al probabili ie according o oraging mode u ing a Kru kper-al–Wper-alli e . Di per al probabili ie are given by exp (x/d0) × log (p), where exp = exponen ial unc ion, x = co di ance ma rix, d0 = di per al di ance, and p = propor ion o all individual in a “popula ion.”

Evaluating the Role o Isolation-By-Distance

To a e he a i ical coe fcien o he linear rela ion hip be ween he geno ype and geographic di ance (IBD) decoupled rom co di ance (IBR), we u ed redundancy analy i (RDA) per pecie in he Vegan R-package (Ok anen e al. 2016), a uming a ull model wi h IBD and IBR a independen variable , a model wi h IBD a independen variable, condi ioned on IBR, and a hird model wi h IBR condi ioned on IBD. The di eren model were u e ul o e or he e ec o re pec ively IBD + IBR, only IBD and only IBR on gene ic varia ion among ample . We ob ained a i ical coe -fcien rom each RDA model u ing ANOVA.

A an al erna ive o he RDA analy i , we u ed PCoA core (axi 1) rom each di ance ma rix in mul iple linear regre ion . We a umed he general ormula PCoA1-Ri land gene ic di ance = a + b (PCoA1-geographic di ance) + b (PCoA1-co di ance). Plo o he par ial rom each model are pre en ed in he Supplemen ary Ma erial (Appendix 8).

To ur her e or IBD, we carried ou an independen e or pa ial au ocorrela ion o gene ic imilari y and geographic di ance. IBD wa concluded i he whole correlogram re ec ed a ignifcan ly nega ive correla ion. Thi wa e ed u ing a he erogenei y e , where he null hypo he i wa no geno ypic divergence a ocia ed wi h geographic di ance a P < 0.01 (Bank and Peakall 2012). We e geographic di ance ca egorie o give approxima ely even num-ber o pairwi e compari on in each di ance cla . Spa ial correlo-gram were ob ained or each pecie u ing GenAlEx (Peakall and Smou e 2012).

Results

Global Genetic Structure Based on HWE

U ing SNP da a pooled acro all individual ampled per pecie , ambu h preda or con i en ly had higher propor ion o loci ha ignifcan ly devia ed rom HWE, compared o ac ive orager (Table 1). Addi ionally, he majori y o loci ha ignifcan ly devi-a ed rom HWE howed devi-a homozygo e exce , ugge ing ronger gene ic ruc ure in ambu h preda or (Supplemen ary Ma erial, Appendix 4). Thi re ul i con i en wi h ac ive orager hav-ing ignifcan ly grea er di per al probabili ie (Kru kal–Walli chi- quared = 60.808, P < 0.0001) be ween neighboring ampling module (Supplemen ary Ma erial, Appendix 5). PCA provided no evidence o di cre e gene ic clu er or any o he pecie udied here (Supplemen ary Ma erial, Appendix 6).

Isolation by Geographic Distance and

Environmental Resistance

The RDA ull model ignifcan ly cap ured 8% (F_2,29 = 1, 121; P = 0.01) o he variance in geno ype o he lancehead (Figure 2) and 18% (F_2,12 = 1.378; P = 0.001) o he variance in he reeboa (Figure 3). However, he par ial model howed ha gene ic

varia-ion in he lancehead i exclu ively a ocia ed o he e ec o IBD (F2,29 = 1.207; P = 0.01), while he gene ic varia ion in he reeboa wa

a ec ed by bo h IBD (F_2,12 = 1.301; P = 0.01) and IBR (F_2,12 = 1.572; P = 0.006). Fore ooded by ream and over owing river had grea er re i ance core , howing ha ooded habi a are no op i-mal rou e or di per al o garden reeboa . We ound no ignifcan e ec o IBD or IBR on he gene ic varia ion or he ac ive orager , he ca -eyed banded (Figure 4) and ou hern harpno e (Figure 5) nake (P > 0.34 in all analy e ). The coe fcien rom he RDA model are ummarized in Table 2.

Al hough gene ic algori hm were u ed o op imize he re i ance ur ace , hi doe no appear o have in uenced he IBR analy e , which were ba ed on an independen ly genera ed di ance mea -ure. Pa ern o re i ance or 3 o he 4 pecie were no ignif-can ly a ocia ed wi h gene ic di ance. Thi how ha he u e o a gene ic algori hm o op imize re i ance ur ace did no bia our da a oward fnding a correla ion be ween re i ance ur ace and

he mea ure o gene ic di ance ha we u ed.

The re i ance core ba ed on lea -co pa h and Circui cape were a lea 86% correla ed (P < 0.001 in all ca e ). There ore, we how only he re ul rom LCP in he main ex , bu , re i ance ur-ace ba ed on LCP and CS are given in he Supplemen ary Ma erial, Appendix 7.

The mul iple linear regre ion ba ed on PCoA core re urned re ul ha were con i en wi h he RDA model . Mul iple regre

-ion explained 35% (P = 0.001) and 79% (P > 0.001) o he rela-ion hip or he lancehead and he reeboa, re pec ively. The in uence

Table 1. Summary o genetic structure o snakes rom the Amazon based on deviation rom HWE

Specie Foraging behavior N Fil ered loci HWE (P ≤ 0.05) % Devia ing

rom HWE H_E > H_O % H_E > H_O Lancehead AP 32 3169 466 14.89 329 10.51 Treeboa AP 15 7805 898 11.50 853 10.92 Ca -eyed AF 23 2173 32 1.47 28 1.28 Sharpno e AF 19 720 2 0.27 1 0.27

The able how he propor ion o loci ha ignifcan ly devia ed rom HWE and propor ion o loci or which HE wa grea er han HO. Gene ic ruc ure wa

compared be ween ambu h preda or (AP) and ac ive orager (AF).

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Figure 2. Patterns o gene ow in the common lancehead Bothrops atrox based on spatial autocorrelation in genetic similarity, isolation by geographic distance and isolation by cost distance. In the correlogram, the error bars around mean genotypic similarity per distance class show 95% confdence intervals, the dashed lines show 95% confdence intervals or the null hypothesis o no spatial structure and the values in brackets show numbers o pairwise comparisons per geographic distance class. The biplot shows individuals as open circles and the explanatory variables as vectors (black arrows).

Figure 3. Patterns o gene ow in the garden treeboa Corallus hortulanus based on spatial autocorrelation in genetic similarity, isolation by geographic distance and isolation by cost distance. In the correlogram, the error bars around mean genotypic similarity per distance class show 95% confdence intervals, the dashed lines show 95% confdence intervals or the null hypothesis o no spatial structure and the values in brackets show numbers o pairwise comparisons per geographic distance class. The biplot shows individuals as open circles and the explanatory variables as vectors (black arrows).

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Figure 4. Patterns o gene ow in the cat-eyed banded snake Leptodeira annulata annulata based on spatial autocorrelation in genetic similarity, isolation by geographic distance and isolation by cost distance. In the correlogram, the error bars around mean genotypic similarity per distance class show 95% confdence intervals, the dashed lines show 95% confdence intervals or the null hypothesis o no spatial structure and the values in brackets show numbers o pairwise comparisons per geographic distance class. The biplot shows individuals as open circles and the explanatory variables as vectors (black arrows).

Figure 5. Patterns o gene ow in the southern sharpnose Philodryas georgeboulengeri based on spatial autocorrelation in genetic similarity, isolation by geographic distance and isolation by cost distance. In the correlogram, the error bars around mean genotypic similarity per distance class show 95% confdence intervals, the dashed lines show 95% confdence intervals or the null hypothesis o no spatial structure and the values in brackets show numbers o pairwise comparisons per geographic distance class. The biplot shows individuals as open circles and the explanatory variables as vectors (black arrows).

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o IBR on gene ic di ance wa re ric ed o he reeboa (P < 0.001). All PCoA ordina ion o di ance ma rice (gene ic, geographic, and environmen al co ) re urned axi 1 repre en ing a lea 70% o he varia ion in he original di ance ob erved. The coe fcien rom mul iple linear regre ion are ummarized in Table 3, and he

par-ial rom each model are plo ed in he Supplemen ary Ma erpar-ial, Appendix 8.

The pa ial au ocorrela ion o gene ic imilari y or cla e o geographic di ance were generally con i en wi h he RDA and mul iple regre ion model . They howed a con inuou decrea e in gene ic imilari y over geographic di ance cla e in he ambu h preda or (P < 0.01 in all ca e ), and no pa ern in gene ic imilari y over geographic di ance cla e or he ca -eyed banded (P = 0.01). However, he ou hern harpno e howed ignifcan pa ial corre-logram (P = 0.003), de pi e hi pa ern no being cap ured by he linear model .

Discussion

Our da a rom 4 nake pecie co-di ribu ed acro ~880 km in he cen ral- ou hwe ern Amazon how ha in he e pecie ’ oraging mode i a ocia ed wi h gene ic divergence. The 2 ambu h preda or howed grea er geno ypic par i ioning wi h geographic and environ-men al co di ance han he ac ive oraging pecie . Fur hermore,

he higher propor ion o loci wi h homozygo e exce in ambu h preda or may be due o he Wahlund e ec , where an apparen homozygo e exce re ul rom da a being pooled acro a gene i-cally ubdivided ample (Wahlund 1928). Overall, he e da a imply higher level o gene ow and di per al acro he ampled land cape

or he ac ive orager .

Knowledge o gene ow in nake may be everely limi ed by he abili y o ob ain large enough ample ize in place where de ec -abili y i low (S een 2010; Fraga e al. 2014). De pi e lower han

ypical ize u ed in popula ion-gene ic udie , he ample ize ob ained here were u fcien o de ec di erence in pa ern o gene ic di ance among pecie . The ignifcan a ocia ion o gen-o ypic di ance wi h gegen-ographic gen-or cgen-o di ance gen-or he ambu h preda or ma che our predic ion ha a eden ary li e yle re ul in lower level o gene ow han ha mea ured in ac ive orager . Ambu h hun ing ha been a ocia ed wi h low vagili y and endency o pend long period in rela ively mall area in bo h he garden reeboa (Hender on 1997) and he common lancehead (Fraga e al. 2013b). Limi ed di per al ha al o been linked o f ne advan age in par icular habi a , uch a ma ching organi m and background color (Ro enblum and Harmon 2011). I ha been unclear whe her hi could be he ca e o he pecie udied here, becau e bo h gar-den reeboa and common lancehead are polychroma ic, bu di eren colormorph are o en ympa ric a local cale (Fraga e al. 2013a; Duar e e al. 2015). Thi ob erva ion ha been hough o indica e high gene ow regardle o geographic di ance and environmen al he erogenei y (Hender on 1997; Duar e e al. 2015). However, in hi udy, IBD i pre en in bo h pecie o ambu h nake , and IBR i pre en in he garden reeboa. Fur hermore, i i po ible ha he e pecie are di playing high level o pheno ypic pla ici y. Pheno ypic pla ici y wi h re pec o color ype ha been demon ra ed or everal rep ile pecie (Broadie 1992; King and Law on 1995; Ro enblum e al. 2004). In ere ingly, pheno ypic pla ici y i el may be under elec ion (Pigliucci e al. 2006), po en ially explaining he lack o IBR ha we ob erved in 3 o he 4 pecie udied.

The only pecie or which we ound ignifcan e ec o IBR on gene ow i he garden reeboa. In hi pecie , non ooded

rain-ore are habi a providing gene ic connec ivi y. E ec o IBR on gene ow ha been linked o localized adap a ion in everal organ-i m , uch a gra e (Freeland e al. 2010), f he (Smi h e al. 2005), amphibian (Dudaniec e al. 2012; Pe erman e al. 2014), bird (Smi h e al. 2005; Man hey and Moyle 2015) and inver ebra e Table 2. Summary o RDA showing the e ects o IBD and IBR on genetic distance o snakes rom the Amazon

Specie IBD + IBR Pure IBD Pure IBR

Iner ia CP P Geo P Co Iner ia CP P Iner ia CP P

Lancehead 142 0.07 0.01 0.76 74.93 0.03 0.01 59.76 0.02 0.76

Treeboa 771.1 0.18 0.002 0.002 359.9 0.08 0.03 377.2 0.09 0.008

Ca -eyed 28.41 0.05 0.38 0.97 8.39 0.03 0.46 6.21 0.01 0.99

Sharpno e 13.07 0.11 0.44 0.33 6.42 0.05 0.39 6.85 0.06 0.32

The P value were ob ained by ANOVA, epara ely o geographic di ance (P Geo) and environmen al re i ance (P Co ). The iner ia value are equivalen o variance, and he CP value how he con rained propor ion o variance on gene ic da a cap ured by RDA. Bolded P value how ignifcan e ec o IBD and/ or IBR on gene ic di ance.

Table 3. Coe fcients rom multiple linear regressions using PCoA scores representing genetic distance as response variables and PCoA scores representing geographic distance (IBD) and environmental cost (IBR) as predictor variables

Specie Predic or r2 _{Re idual} _{S andard error} _t-value _P

Lancehead IBD 0.35 0.004 0.001 3.97 <0.001 IBR −0.0002 0.0003 −0.77 0.44 Treeboa IBD 0.79 0.005 0.002 2.64 0.02 IBR 0.08 0.013 6.35 <0.001 Ca -eyed IBD 0.06 5.065 0.03 1.73 0.1 IBR −0.01 0.03 −0.35 0.72 Sharpno e IBD 0.01 −0.11 0.17 −0.64 0.52 IBR 0.09 1.12 −0.08 0.93

Bolded value are a i ically ignifcan .

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(Funk e al. 2011). However, becau e we were no able o iden i y loci wi h elec ion ignal in hi udy, he e ec o IBR on gene ow in garden reeboa i more likely explained by nonrandom di

per-al acro he erogeneou environmen (Davi and S amp 2004; S even e al. 2005; Feder and Forbe 2007). Garden reeboa have mainly been ound in he under ory acro he udy area (Mar in and Oliveira 1999), which i rela ively open in he ooded ore in he Amazon, becau e many plan pecie canno urvive ooding or long period . I i po ible ha he higher expo ure o preda or and prey in ooded ore migh render hi habi a le ui able or di per al by reeboa . We are no , however, concluding ha di eren elec ive pre ure have no been ac ing on reeboa in he e di eren habi a . I i po ible ha we did no de ec any loci under elec ion becau e we did no recover any SNP wi hin or clo ely linked o gene under elec ion.

Gene ow wa high enough in ac ive orager o preven ignif-can devia ion rom he HWE rom ample pooled acro he whole da a e , or any evidence o IBR and limi ed evidence o IBD. The e fnding ugge ha here ha been a u fcien level o gene ow o o e gene ic di eren ia ion ha would o herwi e re ul rom he localized accumula ion o mu a ion , and he e ec o gene ic dri (Wrigh 1931; Sla kin 1987). Fur her, our modeling ugge ha ac ive orager more o en di per e o neighboring plo , irre pec ive o he in ervening habi a ype . While high level o gene ow imply higher level o di per al acro di eren habi a , i i al o po i-ble ha e ec ive popula ion ize are o a u fcien ize ha demo-graphically independen group o individual are approxima ely gene ically homogeneou (Guo and Thomp on 1992). A pre en , here are in u fcien da a o e ima e e ec ive popula ion ize or he e pecie . In u ure work, our knowledge o how di per al capac-i y capac-i drcapac-ivcapac-ing gene capac-ic dcapac-i eren capac-ia capac-ion could be refned by radcapac-io elem-e ry da a and fnelem-er- calelem-e gelem-enelem-e ic analy elem-e ba elem-ed on a highelem-er delem-en i y o individual .

The rela ion hip be ween geographic di ance and gene ic vari-a ion provided in vari-ance o high gene ic di erence be ween indi-vidual rom i e in clo e proximi y o each o her, and low gene ic di erence be ween individual rom i e ur her apar . Thi wa e pecially prevalen in he ca -eyed banded nake (Supplemen ary Ma erial, Appendix 8c). High varia ion in individual-ba ed e ima e o gene ic di ance i a charac eri ic expec ed wi h high di per al (Goude e al. 2002) and hu con i en wi h our fnding o general high level o gene ow or all pecie .

Regardle o oraging mode, in each o he pecie udied here, gene ow i large enough ha he error bar around mean e ima e o geno ypic imilari y mo ly overlap acro he di

-ance ca egorie a e ed in he pa ial-au ocorrela ion analy i . The ample ize or each di ance ca egory are above ho e ha have genera ed ignifcan ly di eren in er-cla di erence o he ame mea ure o geno ypic imilari y in pa ial au ocorrela-ion analy i o o her pecie (e.g., bru h ail po um ; S ow e al. 2006). There ore, he high variance i mo likely a con equence o high level o gene ow acro he geographic ex en o ampling, and no a ampling bia . Thi fnding i con i en wi h udie o o her nake , where gene ow ha been hown o occur a high level , a di ance grea er han 1000 km (Law on and King 1996), and even among ample collec ed rom i land i ola ed rom he mainland by up o 108 km (Bi ner and King 2003). However, empera e nake ha u e communal hibernacula o overwin er may how gene ic ruc ure a fner cale , wi h IBD eviden a di ance o 15–50 km (Lougheed e al. 1999; Blouin-Demer and Wea herhead 2002).

De pi e he di erence in level o gene ow be ween ambu h preda or and ac ive orager , each o he pecie ha di

ribu-ion ha ex end o habi a no repre en ed wi hin our udy area. A e ing he in uence o IBD and IBR a larger cale (e.g., Amazon ba in) would ample biogeographically di eren region , which would incorpora e grea er geographic i ola ion and environmen al he erogenei y. Fur her a e men a larger cale may reveal gene ic ruc uring or he ac ive orager , and po en ially, iden i y habi a ha provide re i ance o gene ow. Addi ionally, by ampling larger area in Amazonia re earcher are able o di ingui h ecological

ac-or driving gene ow rom hi ac-orical ac ac-or , uch a vicariance cau ed by he river ac ing a barrier o di per al (e.g., Riba e al. 2012). We al o empha ize ha al hough we ound a con i en pa -ern o grea er gene ow in ac ive orager , da a rom addi ional pecie are required o ugge ha hi con i u e a general pa ern.

Tropical rain ore have provided an excep ionally challenging environmen o collec ba ic in orma ion on di per al or nake , a wi h many o her organi m , becau e o low de ec abili y and he e or required o collec enough individual . We have hown ha ob aining mea ure o gene ow and in erring pa ern o di per al migh now be acce ible u ing new echnologie ha allow

hou-and o SNP o be equenced de novo in nonmodel organi m (San aloni e al. 2011; Pe er on e al. 2012), in conjunc ion wi h new pa ial modeling echnique (Pe erman 2014).

Supplementary Material

Supplemen ary da a are ound a Journal of Heredity online.

Funding

Thi udy wa unded by he Con elho Nacional de De envolvimen o Cien ífco e Tecnológico (CNPq)—Programa Ciência em Fron eira (proce number 401327/2012–4) and Fundação de Amparo à Pe qui a do E ado do Amazona (FAPEAM/CNPQ PRONEX pro-ce number 653/2009). The Coordenação de Aper eiçoamen o de Pe oal de Nível Superior—CAPES provided cholar hip o R. F. in Brazil and Au ralia (PDSE proce number 99999.003966/2014-03).

Acknowledgments

We are very gra e ul o Pinduca, Neneco, Rubico, Joãozinho, and P. Glee on or feld a i ance. We hank he Cen ro de E udo In egrado da Biodiver idade Amazônica—CENBAM, Programa de Pe qui a em Biodiver idade—PPBio, San o An ônio Energia S.A. and LBA—Programa de Grande E cala da Bio era-A mo era na Amazônia or logi ical and in i u ional uppor . We hank P. Momigliano, W. Pe erman, and B. O ori or help u in develop-ing re i ance ur ace , C. S rü mann, T. Sanaio i, I. Kae er, R. Vog , and S. Borge or cri ical reading on early ver ion o he manu crip , and he eam rom Kyall Zenger’ lab a he Jame Cook Univer i y (Town ville, Au ralia) or u e ul di cu ion during work hop on genomic .

Data Availability

In accordance wi h he Journal o Heredi y da a archiving policy, we have ub-mi ed all he da a and R crip o Dryad (h p://da adryad.org/) doi:10.5061/ dryad.mq4p7.

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