amphibian richness patterns in atlantic forest areas invaded by american bullfrogs

Amphibian richness patterns in Atlantic Forest areasinvaded by American bullfrogs

CAMILA BOTH,1,2* BRUNO MADALOZZO,3 RODRIGO LINGNAU4 ANDTARAN GRANT1,5

1Programa de Pós-Graudação em Zoologia, Pontifícia Universidade Católica do Rio Grande do Sul,Porto Alegre, 3Programa de Pós-Graduação em Biodiversidade Animal, Universidade Federal de SantaMaria, Santa Maria, 4Universidade Tecnológica Federal do Paraná, Francisco Beltrão, and5Departamento de Zoologia, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil; and2School of Biological Sciences, University of Sydney, Sydney, New SouthWales, Australia (Email:[email protected])

Abstract The relationship between invasion success and native biodiversity is central to biological invasionresearch. New theoretical and analytical approaches have revealed that spatial scale, land-use factors and commu-nity assemblages are important predictors of the relationship between community diversity and invasibility and thenegative effects of invasive species on community diversity. In this study we assess if the abundance of Lithobatescatesbeianus, the American bullfrog, negatively affects the richness of native amphibian species in Atlantic Forestwaterbodies in Brazil. Although this species has been invading Atlantic Forest areas since the 1930s, studies thatestimate the invasion effects upon native species diversity are lacking. We developed a model to understand theimpact of environmental, spatial and species composition gradients on the relationships between bullfrogs andnative species richness.We found a weak positive relationship between bullfrog abundance and species richness ininvaded areas. The path model revealed that this is an indirect relationship mediated by community compositiongradients. Our results indicate that bullfrogs are more abundant in certain amphibian communities, which can bespecies-rich. Local factors describing habitat heterogeneity were the main predictors of amphibian species richnessand composition and bullfrog abundance. Our results reinforce the important role of habitats in determining bothnative species diversity and potential invasibility.

Key words: Anura, Brazil, diversity, invasion, Lithobates catesbeianus, Ranidae.

INTRODUCTION

The immigration of novel species into communities oruncolonized patches is an important process for com-munity development, structure and composition(MacArthur & Wilson 1967; Connell & Slatyer 1977;Loreau & Mouquet 1999).We are currently witnessingan age of biological invasions, with novel speciesbeing incorporated into local communities not onlyby dispersal, but also by intentional or accidentalintroductions. Such invasions are not restricted totaxa, regions, biomes, or continents (Soulé 1990), andthey have attracted much attention because they canbe economically expensive. For instance, exotic speciescan negatively affect crops, fisheries, public healthsystems etc., resulting in the expense of billions ofdollars (Pimentel et al. 2001). Further, invasions canalso be expensive in an ecological and evolutionarycontext, since they have been linked to recent speciesextinctions (Clavero & García-Berthou 2005).

Charles Elton predicted a scenario of ecological andeconomical losses linked with species invasions(Simberloff 2011), and since his seminal synthesis in‘The Ecology of Invasions by Animals and Plants’(Elton 1958) there is growing interest to identifyspecies traits linked to invasion propensity and com-munity properties facilitating or preventing invasions.In his book, Elton observed that ‘tropical systems are lessinvaded than species poor temperate and boreal systems’.Elton associated ‘tropical resistance’ with highlydiverse communities, harbouring large numbers ofenemies and parasites, which, in turn, can impede theestablishment of novel species. This idea is currentlyrecognized as the diversity–invasibility hypothesis (seeJustus 2008). Elton himself recognized that this shouldonly partially explain the low invasion rates in thetropics. Studies subsequent to Elton (1958) explainedthe diversity–invasibility hypothesis in the light ofresource exploitation. Following this rationale, diversetropical communities are more resistant because richercommunities tend to be saturated with species thatexploit resources in complementary ways (MacArthur& Levins 1967; MacArthur 1970).

*Corresponding author.Accepted for publication April 2014.

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The diversity–invasibility hypothesis is still a centralissue in ecology (Fridley et al. 2007).There is evidencefrom observational studies that alien species diversityis low in richer systems, although some studies havefound no relationship at all (e.g. Case & Bolger 1991).Experimental studies supplied evidence that supportsboth negative (e.g. Tilman 1997) and positive relation-ships (e.g. Robinson et al. 1995) between diversity andinvasion. Nevertheless, there are also experimentalstudies highlighting the lack of a relationship betweendiversity and invasion (e.g. Robinson & Dickerson1984). The presence of such contrasting results hasbeen termed ‘the invasion paradox’ (Fridley et al.2007) and seems to be related to spatial scale. In anextensive review, Fridley et al. (2007) showed thatlarge-scale studies suggest a positive relationshipbetween invasive species and native richness. Suchpositive correlation indicates that richer communitiesare able to accommodate introduced species, despitehigh numbers and abundance of native species, knownas ‘biotic acceptance’ (Stohlgren et al. 2006). In con-trast, at smaller scales relationships are often negative,especially in experimental studies (Fridley et al. 2007).Nonetheless, a positive relationship between non-native and native species might be due to samplingartefacts (Fridley et al. 2004). Apparently positive ornegative relationships might also result from analyticalmodels that ignore important co-variables that mightbe related to invasive species abundance or richnessand native species diversity (Taylor & Irwin 2004).Factors such as propagule pressure, disturbance andother environmental gradients often function synergis-tically to explain invasion patterns (Elton 1958; VonHolle & Simberloff 2005). Therefore, in situ studiesthat consider distinct spatial scales and address therelationship between native richness and invasivespecies are required for a thorough understanding ofthe diversity–invasibility hypothesis. This is especiallytrue for approaches that consider causal links connect-ing environmental and community gradients.

In many systems, invasions are a concrete reality,despite several decades of research and efforts for theirprevention (Richardson 2011). In previously invadedecosystems, we are challenged to estimate the invasivespecies effects on diversity rather than to understandwhether diversity will prevent invasions.The same pre-dictions about the relationship between diversity andinvasibility described above also hold for the relation-ship between invasive species effects on diversity.Accordingly, at fine spatial scales negative relation-ships are expected to occur, because it is at smallerspatial scales that species interact. The problem facedwhen studying an invasion that has reached the finalstages is that, without data collected prior to the inva-sion, we cannot know if invasive species promotedchanges to communities in the past. Nevertheless, wecan study the relationship between current invasive

species and community diversity patterns, askingwhether invasions are related to less diverse commu-nities or differences in community composition, whilecontrolling for environmental and spatial variation.

Classical examples of invasion effects on ecosystemdiversity come from freshwater habitats that have suf-fered historically from structural modifications. Theseare among the most endangered ecosystems, andbiotic modifications imposed by the addition of inva-sive species could lead to local extinction of freshwaterspecies (Witte et al. 1992; Dodds & Whiles 2010).Waterbodies such as lakes, ponds, pools and tempo-rary streams can be viewed as small islands, whichseem to be very sensitive to invasions (Ricciardi &MacIsaac 2011). The bullfrog (or American bullfrog)Lithobates catesbeianus (Shaw 1802) is a member of the‘hall of fame’ of freshwater invasive species. It is citedas one of the 100 worst alien species in the world(Lever 2003) and is one of the causes of amphibiandeclines in North America. Furthermore, the speciesappears to be an important vector of fatal amphibiandiseases such as chytridiomycosis (Daszak et al. 2004;Schloegel et al. 2010). Bullfrogs benefit from human-modified landscapes (Adams 1999; Zampella &Bunnell 2000; D’Amore et al. 2010; Fuller et al.2011), the presence of non-native fish in fresh waters(Adams & Wasson 2000; Adams et al. 2003), andsimple aquaculture enclosures that enable a continu-ous source of propagules (Liu & Li 2009).

Bullfrogs originate from eastern North Americaand are distributed from Mexico to south Canada;however, invasive populations occur in western NorthAmerica, Europe, Asia, and Central and South Ameri-can countries where they were introduced for aquacul-ture practices (Santos-Barrera et al. 2009). In invadedsites, they can be negatively correlated with native frogabundance and with the occurrence of certain nativefrog species; they can also reduce tadpole survival(Kupferberg 1997; Kiesecker & Blaustein 1998; Kats& Ferrer 2003; Wang & Li 2009) and are often impli-cated as a factor in the decline of native amphibiansand potential species loss (Kraus 2009). A negativerelationship between bullfrogs and native anuran rich-ness has been reported in China (Li et al. 2011).

Bullfrogs have been present in Brazil since the1930s, and invasions have continued to occur andexpand since then, probably growing exponentiallyfrom the 1970s to the 1990s when bullfrog farmsreceived governmental incentives (Lima & Agostinho1988). Brazil is highly suitable for bullfrog establish-ment, especially in the Atlantic Forest, and climatechange might make protected forest areas even moreprone to invasion by bullfrog populations (Nori et al.2011; Loyola et al. 2012). Although the relationshipbetween invasive bullfrogs and the diversity of nativecommunities in the Atlantic Forest is currentlyunknown, we do know that bullfrogs are widespread in

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Brazil and that the number of known localities isincreasing (Both et al. 2011b).

In this study, we tested relationships between theabundance of the non-native American bullfrog andnative diversity in areas where the invasion hadreached a fully invasive degree (sensu Blackburn et al.2011). Our primary goal was to test whether bullfrogabundance can predict richness patterns by assessinghow amphibians in Atlantic Forest communities varyin richness in invaded areas. We expected a negativerelationship because we were investigating the relation-ship between invasive species abundance and nativecommunity richness at a fine spatial scale. Further-more, we developed a model to understand the inter-play of environmental, spatial and species compositiongradients with the relationship between bullfrogs andnative species richness.

METHODS

Study areas

The study was conducted in three different areas of theAtlantic Forest domain in southern Brazil: the central regionof Rio Grande do Sul State and the western and easternportions of Santa Catarina State (see Appendix S1 forcoordinates). These areas are highly susceptible to bullfroginvasions and are in regions where records of L. catesbeianusin Brazil are concentrated (Both et al. 2011b). Invasions dateto at least 10 years ago in all cases. There were no activebullfrog farms near the study areas. In study area A1 (centralRio Grande do Sul), the vegetation is characterized by sea-sonal deciduous forest (IBGE (Instituto Brasileiro deGeografia e Estatística 2004). In western Santa Catarina,study area A2, two phytogeographic forms of Atlantic Forestoccur, including seasonal deciduous forest and mixedombrophilous forest (IBGE (Instituto Brasileiro deGeografia e Estatística 2004; Lucas & Fortes 2008). Ineastern Santa Catarina, study area A3, the vegetation isformed by dense ombrophilous forest (IBGE (InstitutoBrasileiro de Geografia e Estatística 2004). The AtlanticForest in the three study areas is highly fragmented. Thegeneral land use is farming and cattle grazing, with largerforest fragments found in protected areas. In A1, ParqueEstadual da Quarta Colonia protects 1847.90 ha along theborder of the Dona Francisca hydroelectric dam. A2 includesthe Floresta Nacional de Chapecó, with 1606.3 ha divided intwo areas. Parque Nacional da Serra do Itajaí, with57 374 ha, is located within A3.

Waterbody selection and sampling

In spring 2009, we carried out initial surveys to selectwaterbodies for subsequent sampling, including naturalmarshes, ponds, stream sections with low water flow(streamside pools), and artificial ponds. In each area weidentified 15 waterbodies with evidence of L. catesbeianus

breeding (calling males, eggs, tadpoles), and 15 waterbodieswithout, alternating spatially.This site selection allowed us tocollect data for invaded and non-invaded sites in each studyarea.We considered sites that presented evidence of breedingto be invaded, given that eggs, tadpoles or adults werepresent.Water bodies with no evidence of breeding are likelyto be non-invaded. Juveniles are known to disperse from theirnatal waterbody and can occasionally be found in ephemeralpools or when crossing roads at night (Both, pers. obs.,2010); therefore, the presence of juveniles in ponds is likelyto be temporary and we did not consider it to be evidencethat a site has been invaded.

We sampled a total of 90 waterbodies: 32 in A1, 30 in A2and 28 in A3 (see Appendix S1).We surveyed each site twicefor post-metamorphic individuals, tadpoles and egg clutches.Collections were made over two 25-day periods in February/March (late summer) and October/November (spring) of2010. Sampling months were chosen to represent periods oflonger photoperiod, which is a predictor of high nativeamphibian breeding activity in subtropical regions (Canavero& Arim 2009), and also coincides with the breeding period ofbullfrogs in southern Brazil (Kaefer et al. 2007).

We sampled 4–6 waterbodies per day for eggs and tadpolesin the daytime and post-metamorphic individuals at night.We sampled tadpoles in distinct microhabitats with dip netsweeps (40 × 30 cm, mesh 0.02 mm), always using the samecollector. At least five sweeps were undertaken in eachmicrohabitat (covering approx. 1 m2).The effort was propor-tional to pond size and heterogeneity (Shaffer et al. 1994).Microhabitats were classified into marginal/shallow veg-etated, marginal/shallow non-vegetated, centre/deep veg-etated and centre/deep non-vegetated types. Marginal/shallow microhabitas are generally <30–50 cm deep, whilecentre/deep habitats are generally >50 cm deep. Heterogene-ity is positively correlated with waterbody depth and size;therefore, fewer microhabitats were sampled in small,shallow, non-vegetated waterbodies (approx. 4–6) than inlarge, permanent, vegetated waterbodies with all four types ofmicrohabitats (approx. 20 microhabitats sampled). In thelargest ponds we also sampled microhabitats midwaybetween the margin and the centre. The total number ofmicrohabitats sampled in each waterbody in a single surveyranged from 4–30. Samples were spaced at least 2 m apart.Samples were taken between 09:00–19:00 h, always duringdaylight.

Post-metamorphic surveys were begun 30 min aftersunset, and we searched for individuals along the perimetersof breeding sites.We counted all post-metamorphic individu-als, separating calling and non-calling individuals. Samplingeffort was proportional to size and heterogeneity of thewaterbody (Scott & Woodward 1994).

Waterbody and landscape descriptors

We measured the distance from the waterbody to the nearestforest fragment and to the nearest road using GPScoordinates. We expanded these distances in second- andthird-order monomials to test for potential non-linear rela-tionships with richness. Area and depth of each waterbodywere measured at each collection event. For depth, we tookthe measurements in each of the microhabitats sampled for

BULLFROG INVASION AND ANURAN DIVERSITY 3


tadpoles and recorded the mean, maximum, and minimumdepth. Water surface area ratio obtained from the two sam-pling events (summer area/spring area) was used as ameasure of pond permanence. We recorded hydrophytemorphotype (floating and emergent macrophytes) richness inthe pond. We visually estimated the hydrophyte coverage ofwaterbodies and classified it into three classes: <30%,30–60% and >60%. Fish presence/absence was determinedby visual surveys or dip net captures or was based on infor-mation provided by local rural owners. We classified thevegetation of waterbody banks into low grass, tall grass,shrubs, and trees and used the sum of types present in a siteas a descriptor of the bank vegetation structure.

Spatial descriptors

This study was performed at two major scales: between areas(A1, A2 and A3) and within areas.To account for this nestedspatial arrangement, we considered two kinds of spatialdescriptors: the three large study areas represented bydummy variables, and Moran’s eigenvector maps (MEMs).MEMs provide orthogonal spatial variables ranging frombroad, inter-area scales to the finest scales derived from thegeographic coordinates of the sites (Dray et al. 2006). Thespatial arrangement in this study shows a high truncationvalue (minimum distance connecting all points = 334 km)between study areas. We used a nested MEM model(Declerck et al. 2011), where MEM variables are blockedwithin study areas to describe spatial relationships at thisscale.We used the R function create.MEM.model (Declercket al. 2011) to build the MEM model using a matrix ofdummy variables that described the three regions as theconnectivity criteria. The nested analysis resulted in sevenspatial vectors describing the spatial arrangement of siteswithin areas. These seven MEM vectors and the dummyvariables of the three large study areas were used as spatialdescriptors.

Data analyses

To remove the effects of sampling effort on richness values,we regressed richness on the abundance of post-metamorphic individuals, which showed a 96% concordancewith total richness, and used the residuals, henceforth calledrichness, in subsequent analyses.To describe species compo-sition across waterbodies, we calculated Jaccard’s index ofsimilarity for pairs of communities and performed a principalcoordinate analysis (PCoA) (Legendre & Legendre 1998)using only occurrence (presence/absence) data. We choseoccurrences instead of species abundances because theyallowed us to combine post-metamorphic and tadpolesurveys, thereby dispensing with further weighting assump-tions about the importance of distinct life history stages tothe characterization of community composition.The stabilityof ordination axes was evaluated by bootstrap resampling(Pillar 1999). The PCoA analysis was performed in Multiv(Pillar 2006).

We used successive regression models to analyse the effectsof bullfrogs on richness, taking into account environmental

and spatial variation. This analytical approach allowed us todepict the co-variation structure between predictors (Shipley2000). First, we tested whether bullfrog abundance affectsnative richness. Using path analysis, we then tested whetherspecies richness is related to (i) waterbody, (ii) landscape,and (iii) spatial descriptors, jointly with (iv) community com-position and (v) bullfrog abundance. In order to assess therelative importance of all five sets of predictors, we built ahierarchical theoretical model of potential causal relation-ships explaining native species richness (Fig. 1). This modelassumes a hierarchical causal order between predictors,where spatial descriptors have the highest causal order and allother variables are endogenous (see causal links in Fig. 1).We tested this model using the analytical steps proposed byBrum et al. (2012). First, we performed a model selectionprocedure using each set of descriptors as predictors of nativerichness to identify the descriptors that are directly relatedwith native richness. We then regressed all selected descrip-tors from all sets against richness to test for direct causallinks. Obeying the causal hierarchy, we regressed all variablesdirectly linked with richness on their respective potentialpredictors (immediate higher hierarchy factors, Fig. 1), andso on, until we reached the exogenous descriptors, or spatialdescriptors in this case. For instance, if a waterbody descrip-tor was directly related to local richness, we furtherinvestigated which landscape and spatial descriptors couldexplain this descriptor. If a landscape descriptor wasselected, we inspected its relationships with high-orderspatial descriptors. Fish presence was considered togetherwith other waterbody descriptors. However, we investigatedfurther causal links associated with this variable (see Fig. 1)because it is a well-known filter for lentic communities(Wellborn et al. 1996). Beta regression coefficients of linearmodels were taken as path coefficients. Model selection wasbased on corrected Akaike information criterion (Anderson2008). All regression models were performed in R (RDevelopment Core Team 2012).

RESULTS

Across the three study areas we recorded 40 nativeamphibian species: 19 species in A1, 19 in A2 and 23in A3 (Table 1). Native amphibian richness rangedfrom 0–11 species, with an average of 3.9 species perwaterbody (SD = 2.8).The ordination of species com-position resulted in 37 PCoA axes.The first three axesrepresented 41% of the species composition gradientsand were used in the regression models. The stabilityof the first three ordination axes was validated by boot-strap resampling. The first two axes represented thecomposition gradient from ombrophilous vegetationto mixed ombrophilous vegetation to seasonal decidu-ous forest amphibian communities (Fig. 2A). Thefirst principal coordinate (PC1) axis clearly variedfrom amphibian compositions restricted to denseombrophilous forest (e.g. Sphaenorhynchus sp. andBokermanohyla hylax) to those occurring in high fre-quencies across the study regions (e.g. Dendropsophusminutus and Physalaemus cuvieri) (Fig. 2B).

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We detected bullfrogs at 62 of the 90 sampledwaterbodies, 44 of which showed evidence of breeding(16 in A1, 16 in A2 and 12 in A3), indicating thepresence of established populations. At least eight sitesin each study area lacked evidence of bullfrogs at anylife stage. The linear model relating native amphibianrichness to bullfrog abundance showed a weak positiverelationship (Table 2). Richness was also positivelyrelated to the first two principal coordinates of com-munity composition, PC1 and PC2 (Fig. 2). ThreeMEMs were selected in the spatial model: MEM-2,which described spatial structure within A2; MEM-3,which described spatial structure within A3; andMEM-7 describing spatial structure within A1. Themodel relating richness with local waterbody des-criptors selected maximum depth, hydrophyte rich-ness, bank vegetation structure, fish presence andstreamside pools as predictors (Table 2).

The path model showed that native amphibian rich-ness was directly determined by the first two principalcoordinates of community composition (PC1 andPC2), maximum depth, and the binary descriptors forfish presence, as well as by one spatial model, MEM-2(Fig. 3).The composition gradients described by PC1and PC2 showed the highest path coefficients, andtherefore are the main predictors of native amphibianrichness. Stream side waterbodies and two spatialmodels (MEM-3 and MEM-4), did not show signifi-cant causal links with amphibian richness. Bullfrogabundance was only indirectly related to amphibianspecies richness through its relationship with the com-munity composition gradient of PC1. Hydrophyte

richness was also only indirectly linked to richnessthrough the composition gradients. Hydrophyte rich-ness directly determined bullfrog abundance and com-munity composition gradients PC1 and PC2 (Fig. 3).The final model accounted for 63% of native richnessvariation.

DISCUSSION

Traditionally, the diversity–invasibility relationship hasbeen explored in order to investigate whether diversitywill prevent invasions. In the face of increasing inva-sion rates and successful establishment of invaders, ithas become important to explore the effect of inva-sions on species diversity at a local scale. In this study,we assessed whether invasion affects diversity inalready successfully occupied areas, expecting a nega-tive relationship between bullfrog abundance andnative amphibian richness. Contrary to our initialexpectation, we found a weak positive relationship,which was revealed to be indirectly linked to speciescomposition gradients. Local environmental gradientsdescribing waterbody features directly explained allbiotic components of the model. They also showed anadditional and important influence of species compo-sition gradients on native richness. Bullfrog abundancealso responded to the same waterbody gradients.Across the three Atlantic Forest areas, the influence ofspace upon richness patterns was small.We found onlyweak relationships between micro-regions and lowerrichness in A1 and A2, and higher richness in A3.

Fig. 1. Theoretical path model explaining relationships of native amphibian richness with community gradients, space,landscape, waterbody descriptors and American bullfrog abundance in invaded areas.



However, only one spatial model was causally signifi-cant when considering the entire co-variation struc-ture between all sets of predictors.

At fine spatial scales, negative relationships areexpected because it is at these scales that individualsactually interact. At this local scale, biotic resistance ofthe native community or impact of invasive species are

expected to operate, and both would lead to negativerelationships (Elton 1958). However, it has beenshown that native species differ greatly in the way theyare affected by invasive species. For instance, Thomazand Michelan (2011) studied the effects of an invasivemacrophyte on several native macrophytes at distinctspatial scales and observed that only some of the native

Table 1. Amphibian composition from southern Atlantic Forest areas invaded by Lithobates catesbeianus

Species Abbreviation Post-metamorphics Tadpoles A1 A2 A3

BufonidaeRhinella abei Rab 1 1 1Rhinella fernandezae Rfe 1 1Rhinella icterica Ric 1 1 1 1

CycloramphidaeLimnomedusa macroglossa Lma 1 1

HylidaeBokermannohyla hylax Bhy 1 1 1Dendropsophus minutus Dmin 1 1 1 1Dendropsophus microps Dmic 1 1 1Dendropsophus nahdereri Dnah 1 1Dendropsophus nanus Dnan 1 1 1Dendropsophus sanborni Dsa 1 1 1Dendropsophus werneri Dwe 1 1 1Hypsiboas albomarginatus Halb 1 1 1Hypsiboas albopunctatus Halbp 1 1Hypsiboas bishoffi Hbi 1 1Hypsiboas faber Hfa 1 1 1 1 1Hypsiboas pulchellus Hpu 1 1 1Hypsiboas semilineatus Hse 1 1 1Hypsiboas cf. semiguttatus 1 Hsm1 1 1Hypsiboas cf. semiguttatus 2 Hsm2 1 1Phyllomedusa tetraploidea Pte 1 1 1Phyllomedusa distincta Pdi 1 1Scinax alter Sal 1 1Scinax fuscovarius Sfu 1 1 1 1 1Scinax granulatus Sgr 1 1 1 1 1Scinax perereca Spe 1 1 1 1Sphaenorhynchus sp. Sphe 1 1

HylodidaeCrossodactylus sp. Cro 1 1

LeiuperidaePhysalaemus gracilis Pgr 1 1 1 1Physalaemus cuvieri Pcu 1 1 1 1 1Physalaemus nanus Pna 1 1 1Pseudopaludicola falcipes Pfa 1 1 1 1

LeptodactylidaeLeptodactylus fuscus Lfu 1 1 1 1 1Leptodactylus gracilis Lgr 1 1 1 1Leptodactylus labyrynthicus Llab 1 1Leptodactylus joly Ljo 1 1Leptodactylus latinasus Llat 1 1 1Leptodactylus latrans Llat 1 1 1 1 1Leptodactylus mystacinus Lmy 1 1 1Leptodactylus plaumani Lpl 1 1

MicrohylidaeElachistocleis bicolor Ebi 1 1 1 1

Total 34 30 19 19 23

A1 = central region of Rio Grande do Sul, deciduous forest; A2 = western region of Santa Catarina, deciduous and mixedombrophilous forest; A3 = east of Santa Catarina, ombrophilous forest.

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macrophytes were affected, and, further, that thesenegative associations are more common at smallerscales. A frequently neglected issue is that at fine scalesspecies facilitation can occur, which would lead topositive relationships (Bruno et al. 2003). In our case,a structurally complex community might providegreater resources for bullfrogs, which are generalistpredators (Bury & Whelan 1984). In turn, bullfrogsmight be able to explore diverse resources inwaterbodies, including anuran prey, without affectingnative diversity.

Here, we tested whether bullfrog abundance canpredict anuran richness and found that this relation-

ship is mediated by community composition. Bull-frogs were more abundant in certain species-richcommunities. Bullfrog abundance was positivelyrelated to the PC1 community gradient, varying in asimilar fashion in this gradient to common specieslike Physalaemus cuvieri and Dendropsophus minutusthat are broadly distributed in South America (IUCN2011). These species have been recognized asanthropogenically adapted (Santos et al. 2007), likebullfrogs. These results are in accordance with thoseof Bunnell and Zampella (2008), who found thatbullfrogs are associated with distinct species compo-sitions, being more closely associated with speciesthat have a widespread distribution. However, bull-frogs do co-occur with other communities in theAtlantic Forest, albeit at lower abundance, and mightaffect the communities by other pathways. Forinstance, Both and Grant (2012) found evidence thatbullfrogs have the potential to affect the acousticniche of native amphibians: tree-frogs naïve to bull-frog vocalizations significantly altered advertisementcall frequencies in response to bullfrog advertisementcalls. In this case, bullfrogs might not cause animmediate decrease in richness but could affectfemale mate selection and result in important but lessimmediate fitness consequences (Both & Grant2012).

Our results highlight how all biotic components –species richness, composition, fish presence, andbullfrog abundance – respond directly or indirectly towaterbody descriptors. These waterbody descriptorsact as local scale filters, structuring both nativespecies diversity and bullfrog abundance. Hydrophyterichness and maximum depth were the main predic-tors describing waterbodies selected in our finalmodel. These predictors could be viewed as ameasure of habitat heterogeneity, which undoubtedlyplays an important role for both faunal biodiversityand abundance. Heterogeneity has the potential todecouple trophic interactions, promoting greaterdiversity (Kovalenko et al. 2012). Despite using asimplistic measure of heterogeneity of the watersurface (richness of hydrophyte morphotypes), wefound that it was an important predictor of commu-nity gradients. Hydrophytes could promote diversityby providing shelter for tadpoles and post-metamorphic individuals and calling sites or for adultmales. Maximum depth is a gradient that containsvariation related to pond area, permanence, availabil-ity of other lower depths, and is also an importantresource for communities in small waterbodies. Itgoverns the coexistence of nektonic and benthic tad-poles in ponds and streams (Eterovick & Fernandes2001; Both et al. 2011a). Fish and bullfrog presenceare also regulated by this gradient, because onlywaterbodies with a certain depth can support theseorganisms (Kushlan 1976; Bury & Whelan 1984).

Fig. 2. Ordination of amphibian species compositionacross the three study areas. (A) First two axes of principalcoordinate analysis (PCoA) revealing composition gradientsacross the study areas (PC1 and PC2). Triangles indicatespecies composition from A1 (seasonal deciduous forest),circles indicate compositions from A2 (mixed ombrophilousforest), and squares from A3 (ombrophilous forest). (B) Cor-relation scatter plot for amphibian species with the first twoPCoA axes. Amphibian species are identified by abbrevia-tions (see Table 2).



Habitat heterogeneity has been recognized as a keyfactor determining the persistence of native frogpopulations in areas invaded by bullfrogs in NorthAmerica. Adams et al. (2011) studied extinctionprobabilities of Rana aurora populations, testingwhether they could be related to bullfrog invasionand habitat modification. They did not find support-ing evidence for an effect of bullfrogs on local extinc-tion probability for the native species. Their resultsshowed that vegetation cover and riparian vegetationare the best predictors of low extinction risk on localscales for the native frog populations. The relation-ship between species composition and bullfrog

abundance with local waterbody descriptors observedhere are encouraging, because they suggest a meansfor habitat management to protect native frogs. Inthis study, we found that waterbody depth was caus-ally linked with bullfrog abundance and species rich-ness through positive and negative paths, respectively.In addition, previous studies showed that waterbodymodification favours bullfrogs and promotes changesin community composition (e.g. Bunnell & Zampella2008; Fuller et al. 2011). Waterbodies in areas ofspecial interest for conservation could be managed tofavour native amphibians, or to prevent the establish-ment of bullfrogs.

Table 2. Linear model relating native amphibian richness and bullfrog abundance (1) and best models relating native richnesswith three different sets of predictors: (2) community gradients, (3) waterbody descriptors and (4) spatial models

R2 AICc AICc wi

(1) Bullfrog abundance 0.05 405.17 –(2) Community gradientsPC1 + PC2

0.51 348.24 0.75

(3) Waterbody descriptorsDepthmax + bank vegetation structure* + hydrophyte richness + stream* + fish presence*

0.31 384.94 0.27

(4) Spatial descriptorsMEM.2 + MEM.3 + MEM.7

0.14 401.22 0.10

The selection of best models was based on corrected Akaike information criterion (AICc) and Akaike weight (AICc wi). Theselected models have the highest AICc wi, which describes the relative likelihood of the model, normalized across the set of allpossible models to sum 1. Fixed factors are identified by (*). Principal coordinates of community composition (PC) were usedas predictors in model 2 and Moran’s eigenvector maps (MEM) were used as predictors in model 4. Abbreviations in model (3):Depthmax = maximum depth recorded for a given waterbody; bank vegetation structure = number of types of vegetation presentin waterbody banks; stream = stream side pool (dummy variable describing type of waterbody).

Fig. 3. Causal relationships between selected spatial and environmental predictors, amphibian species composition gradients,bullfrog abundance and native amphibian richness. Standardized path correlation coefficient values follow each path. Solidarrows (—) represent positive relationships and dashed arrows (- - -) represent negative relationships. Only paths with P ≤ 0.05are shown. U = non-determination coefficient (U = 1 − R2). Richness = native amphibian richness; Hydrophyte R = hydrophyterichness; Veg. types = number of structural vegetation types around the ponds; Depth = maximum depth recorded for awaterbody; bullfrogs = Lithobates catesbeianus abundance; Fish = fish presence/absence; PC1 = first principal coordinate of com-munity composition; PC2 = second principal coordinate of community composition; MEM.2 = Moran’s eigenvector two,describing spatial structure within study area A1.

8 C. BOTH ET AL.


Our study is not the first to note a positive relation-ship between amphibian community richness andinvasion.This pattern has been reported for native andinvasive amphibian and reptile communities onbroader spatial scales, suggesting the occurrence ofbiotic acceptance (Stohlgren et al. 2006). Poessel et al.(2013) studied how native richness and alien amphib-ian species establishment are related in Europe andNorth America and found positive relationships inboth regions. They used invasive species richness as ameasure of invasibility, and not single species abun-dance, as we used in the present study to access bull-frog effects. Nevertheless, they also concluded thatenvironmental gradients favouring higher nativespecies richness also favour invasions. Additionally, itis worth noting that only recent studies dealing withbullfrog invasion patterns highlight neutral relation-ships between bullfrogs and richness or emphasize therole of habitat filtering to promote or facilitate inva-sions (e.g. D’Amore et al. 2010; Adams et al. 2011).Such results might be due to study spatial scale and/orrefinement of analytical approaches. Another possibil-ity is that over time, some communities might reach anew dynamic equilibrium state in which bullfrogs arenot a major threat.

An important consideration when comparing theresults of the present study with those of previousstudies in other regions is that the phylogenetic rela-tionship between bullfrogs and native species is muchcloser in those regions than in the Atlantic Forestlocalities we studied. In Asia, Europe and NorthAmerica there are more ranid species. In China, wherebullfrogs are known to negatively affect richness, nativespecies composition mostly consists of ranids (Li et al.2011). In contrast, only a single native ranid speciesoccurs in the Atlantic Forest (Lithobates palmipes; Hillis& de Sá 1988), and it is restricted to the northernportion of the biome. No ranids occurred at any of thelocalities we studied, and the closest relative we foundin sympatry with bullfrogs is the microhylidElachistocleis bicolor.The potential influence of related-ness upon invasions was recognized by Darwin (1859)in ‘The Origin of Species’. He suspected that a lowdegree of relatedness should give some advantage tonovel species in new habitats. This idea deservesfurther investigation, considering the global scale ofinvasions by bullfrogs and many other alien species.

In conclusion, we found only a weak and indirect,positive relationship between native anuran richnessand bullfrog abundance, which is mediated by speciescomposition at the invaded sites. Our results indicatebiotic acceptance of bullfrogs in the Atlantic Forest.Weobserved that bullfrogs were more abundant in someamphibian communities that include anthropogenic-adapted species. The main result is that localwaterbody descriptors predict native richness andcomposition and bullfrog abundance. These results

agree with recent studies suggesting that environmen-tal gradients directly affect both native and invasivespecies. Although we did not detect negative effects ofbullfrogs on native richness, we do not conclude thatsuch effects are absent in general. Disease transmis-sion, differential predation, and competition by inter-ference are mechanisms that could plausibly operatein invaded areas, even when bullfrogs have lowabundance.

ACKNOWLEDGEMENTS

This study was supported by IGRE Associação SócioAmbientalista and received grants from Fundação oBoticário de Proteção a Natureza (0835_20092) andthe Rufford Small Grants Foundation. The ConselhoNacional de Desenvolvimento Científico provided astudent fellowship to CB and a grant (Proc. 476789/2009-5) and fellowship (Procs. 305473/2008-5,307001/2011-3) to TG. The Fundação de Amparo àPesquisa do Estado de São Paulo provided a grant toTG (Proc. 2012/10000-5). ICMBio granted a collec-tion permit for this study (Proc. 23009-1).This manu-script benefited from comments by Sandra Hartz,Célio Haddad, Márcio Borges-Martins, AdrianoSanches Melo, and three anonymous reviewers.We arethankful to all rural owners who granted access tostudy sites and the Parque Nacional da Serra do Itajaífor logistical support. We also thank S. Declerck forsharing the nested MEM function, V.F. Caorsi for herhelp with laboratory procedures, and D. Borges-Provette for help with the literature for tadpoleidentification.

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SUPPORTING INFORMATION

Additional Supporting Information may be found inthe online version of this article at the publisher’sweb-site:

Appendix S1. Geographic coordinates of the 90sampled waterbodies.



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amphibian richness patterns in atlantic forest areas invaded by american bullfrogs

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