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Austral Ecology (2014) 39, 864–874
Amphibian richness patterns in Atlantic Forest areas
invaded by American bullfrogs
CAMILA BOTH,1,2* BRUNO MADALOZZO,3 RODRIGO LINGNAU4 AND
TARAN GRANT1,5
1
Programa 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 Santa
Maria, Santa Maria, 4Universidade Tecnológica Federal do Paraná, Francisco Beltrão, and
5
Departamento de Zoologia, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil; and
2
School of Biological Sciences, University of Sydney, Sydney, New South Wales, Australia (Email:
camilaboth@gmail.com)
Abstract The relationship between invasion success and native biodiversity is central to biological invasion
research. New theoretical and analytical approaches have revealed that spatial scale, land-use factors and community assemblages are important predictors of the relationship between community diversity and invasibility and the
negative effects of invasive species on community diversity. In this study we assess if the abundance of Lithobates
catesbeianus, the American bullfrog, negatively affects the richness of native amphibian species in Atlantic Forest
waterbodies in Brazil. Although this species has been invading Atlantic Forest areas since the 1930s, studies that
estimate the invasion effects upon native species diversity are lacking. We developed a model to understand the
impact of environmental, spatial and species composition gradients on the relationships between bullfrogs and
native species richness. We found a weak positive relationship between bullfrog abundance and species richness in
invaded areas. The path model revealed that this is an indirect relationship mediated by community composition
gradients. Our results indicate that bullfrogs are more abundant in certain amphibian communities, which can be
species-rich. Local factors describing habitat heterogeneity were the main predictors of amphibian species richness
and composition and bullfrog abundance. Our results reinforce the important role of habitats in determining both
native species diversity and potential invasibility.
Key words: Anura, Brazil, diversity, invasion, Lithobates catesbeianus, Ranidae.
INTRODUCTION
The immigration of novel species into communities or
uncolonized patches is an important process for community development, structure and composition
(MacArthur & Wilson 1967; Connell & Slatyer 1977;
Loreau & Mouquet 1999).We are currently witnessing
an age of biological invasions, with novel species
being incorporated into local communities not only
by dispersal, but also by intentional or accidental
introductions. Such invasions are not restricted to
taxa, regions, biomes, or continents (Soulé 1990), and
they have attracted much attention because they can
be economically expensive. For instance, exotic species
can negatively affect crops, fisheries, public health
systems etc., resulting in the expense of billions of
dollars (Pimentel et al. 2001). Further, invasions can
also be expensive in an ecological and evolutionary
context, since they have been linked to recent species
extinctions (Clavero & García-Berthou 2005).
*Corresponding author.
Accepted for publication April 2014.
© 2014 The Authors
Austral Ecology © 2014 Ecological Society of Australia
Charles Elton predicted a scenario of ecological and
economical 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 identify
species traits linked to invasion propensity and community properties facilitating or preventing invasions.
In his book, Elton observed that ‘tropical systems are less
invaded than species poor temperate and boreal systems’.
Elton associated ‘tropical resistance’ with highly
diverse communities, harbouring large numbers of
enemies and parasites, which, in turn, can impede the
establishment of novel species. This idea is currently
recognized as the diversity–invasibility hypothesis (see
Justus 2008). Elton himself recognized that this should
only partially explain the low invasion rates in the
tropics. Studies subsequent to Elton (1958) explained
the diversity–invasibility hypothesis in the light of
resource exploitation. Following this rationale, diverse
tropical communities are more resistant because richer
communities tend to be saturated with species that
exploit resources in complementary ways (MacArthur
& Levins 1967; MacArthur 1970).
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The diversity–invasibility hypothesis is still a central
issue in ecology (Fridley et al. 2007).There is evidence
from observational studies that alien species diversity
is low in richer systems, although some studies have
found no relationship at all (e.g. Case & Bolger 1991).
Experimental studies supplied evidence that supports
both negative (e.g. Tilman 1997) and positive relationships (e.g. Robinson et al. 1995) between diversity and
invasion. Nevertheless, there are also experimental
studies highlighting the lack of a relationship between
diversity and invasion (e.g. Robinson & Dickerson
1984). The presence of such contrasting results has
been termed ‘the invasion paradox’ (Fridley et al.
2007) and seems to be related to spatial scale. In an
extensive review, Fridley et al. (2007) showed that
large-scale studies suggest a positive relationship
between invasive species and native richness. Such
positive correlation indicates that richer communities
are able to accommodate introduced species, despite
high numbers and abundance of native species, known
as ‘biotic acceptance’ (Stohlgren et al. 2006). In contrast, at smaller scales relationships are often negative,
especially in experimental studies (Fridley et al. 2007).
Nonetheless, a positive relationship between nonnative and native species might be due to sampling
artefacts (Fridley et al. 2004). Apparently positive or
negative relationships might also result from analytical
models that ignore important co-variables that might
be related to invasive species abundance or richness
and native species diversity (Taylor & Irwin 2004).
Factors such as propagule pressure, disturbance and
other environmental gradients often function synergistically to explain invasion patterns (Elton 1958; Von
Holle & Simberloff 2005). Therefore, in situ studies
that consider distinct spatial scales and address the
relationship between native richness and invasive
species are required for a thorough understanding of
the diversity–invasibility hypothesis. This is especially
true for approaches that consider causal links connecting environmental and community gradients.
In many systems, invasions are a concrete reality,
despite several decades of research and efforts for their
prevention (Richardson 2011). In previously invaded
ecosystems, we are challenged to estimate the invasive
species effects on diversity rather than to understand
whether diversity will prevent invasions.The same predictions about the relationship between diversity and
invasibility described above also hold for the relationship between invasive species effects on diversity.
Accordingly, at fine spatial scales negative relationships are expected to occur, because it is at smaller
spatial scales that species interact. The problem faced
when studying an invasion that has reached the final
stages is that, without data collected prior to the invasion, we cannot know if invasive species promoted
changes to communities in the past. Nevertheless, we
can study the relationship between current invasive
© 2014 The Authors
Austral Ecology © 2014 Ecological Society of Australia
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species and community diversity patterns, asking
whether invasions are related to less diverse communities or differences in community composition, while
controlling for environmental and spatial variation.
Classical examples of invasion effects on ecosystem
diversity come from freshwater habitats that have suffered historically from structural modifications. These
are among the most endangered ecosystems, and
biotic modifications imposed by the addition of invasive species could lead to local extinction of freshwater
species (Witte et al. 1992; Dodds & Whiles 2010).
Waterbodies such as lakes, ponds, pools and temporary streams can be viewed as small islands, which
seem 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 cited
as one of the 100 worst alien species in the world
(Lever 2003) and is one of the causes of amphibian
declines in North America. Furthermore, the species
appears to be an important vector of fatal amphibian
diseases such as chytridiomycosis (Daszak et al. 2004;
Schloegel et al. 2010). Bullfrogs benefit from humanmodified 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), and
simple aquaculture enclosures that enable a continuous source of propagules (Liu & Li 2009).
Bullfrogs originate from eastern North America
and are distributed from Mexico to south Canada;
however, invasive populations occur in western North
America, Europe, Asia, and Central and South American countries where they were introduced for aquaculture practices (Santos-Barrera et al. 2009). In invaded
sites, they can be negatively correlated with native frog
abundance and with the occurrence of certain native
frog species; they can also reduce tadpole survival
(Kupferberg 1997; Kiesecker & Blaustein 1998; Kats
& Ferrer 2003; Wang & Li 2009) and are often implicated as a factor in the decline of native amphibians
and potential species loss (Kraus 2009). A negative
relationship between bullfrogs and native anuran richness has been reported in China (Li et al. 2011).
Bullfrogs have been present in Brazil since the
1930s, and invasions have continued to occur and
expand since then, probably growing exponentially
from the 1970s to the 1990s when bullfrog farms
received governmental incentives (Lima & Agostinho
1988). Brazil is highly suitable for bullfrog establishment, especially in the Atlantic Forest, and climate
change might make protected forest areas even more
prone to invasion by bullfrog populations (Nori et al.
2011; Loyola et al. 2012). Although the relationship
between invasive bullfrogs and the diversity of native
communities in the Atlantic Forest is currently
unknown, we do know that bullfrogs are widespread in
doi:10.1111/aec.12155
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C . B OT H ET AL.
Brazil and that the number of known localities is
increasing (Both et al. 2011b).
In this study, we tested relationships between the
abundance of the non-native American bullfrog and
native diversity in areas where the invasion had
reached a fully invasive degree (sensu Blackburn et al.
2011). Our primary goal was to test whether bullfrog
abundance can predict richness patterns by assessing
how amphibians in Atlantic Forest communities vary
in richness in invaded areas. We expected a negative
relationship because we were investigating the relationship between invasive species abundance and native
community richness at a fine spatial scale. Furthermore, we developed a model to understand the interplay of environmental, spatial and species composition
gradients with the relationship between bullfrogs and
native species richness.
METHODS
Study areas
The study was conducted in three different areas of the
Atlantic Forest domain in southern Brazil: the central region
of Rio Grande do Sul State and the western and eastern
portions of Santa Catarina State (see Appendix S1 for
coordinates). These areas are highly susceptible to bullfrog
invasions and are in regions where records of L. catesbeianus
in Brazil are concentrated (Both et al. 2011b). Invasions date
to at least 10 years ago in all cases. There were no active
bullfrog farms near the study areas. In study area A1 (central
Rio Grande do Sul), the vegetation is characterized by seasonal deciduous forest (IBGE (Instituto Brasileiro de
Geografia e Estatística 2004). In western Santa Catarina,
study area A2, two phytogeographic forms of Atlantic Forest
occur, including seasonal deciduous forest and mixed
ombrophilous forest (IBGE (Instituto Brasileiro de
Geografia e Estatística 2004; Lucas & Fortes 2008). In
eastern Santa Catarina, study area A3, the vegetation is
formed by dense ombrophilous forest (IBGE (Instituto
Brasileiro de Geografia e Estatística 2004). The Atlantic
Forest in the three study areas is highly fragmented. The
general land use is farming and cattle grazing, with larger
forest fragments found in protected areas. In A1, Parque
Estadual da Quarta Colonia protects 1847.90 ha along the
border of the Dona Francisca hydroelectric dam. A2 includes
the Floresta Nacional de Chapecó, with 1606.3 ha divided in
two areas. Parque Nacional da Serra do Itajaí, with
57 374 ha, is located within A3.
breeding (calling males, eggs, tadpoles), and 15 waterbodies
without, alternating spatially.This site selection allowed us to
collect data for invaded and non-invaded sites in each study
area.We considered sites that presented evidence of breeding
to be invaded, given that eggs, tadpoles or adults were
present. Water bodies with no evidence of breeding are likely
to be non-invaded. Juveniles are known to disperse from their
natal waterbody and can occasionally be found in ephemeral
pools or when crossing roads at night (Both, pers. obs.,
2010); therefore, the presence of juveniles in ponds is likely
to be temporary and we did not consider it to be evidence
that a site has been invaded.
We sampled a total of 90 waterbodies: 32 in A1, 30 in A2
and 28 in A3 (see Appendix S1). We surveyed each site twice
for post-metamorphic individuals, tadpoles and egg clutches.
Collections were made over two 25-day periods in February/
March (late summer) and October/November (spring) of
2010. Sampling months were chosen to represent periods of
longer photoperiod, which is a predictor of high native
amphibian breeding activity in subtropical regions (Canavero
& Arim 2009), and also coincides with the breeding period of
bullfrogs in southern Brazil (Kaefer et al. 2007).
We sampled 4–6 waterbodies per day for eggs and tadpoles
in the daytime and post-metamorphic individuals at night.
We sampled tadpoles in distinct microhabitats with dip net
sweeps (40 × 30 cm, mesh 0.02 mm), always using the same
collector. At least five sweeps were undertaken in each
microhabitat (covering approx. 1 m2).The effort was proportional to pond size and heterogeneity (Shaffer et al. 1994).
Microhabitats were classified into marginal/shallow vegetated, marginal/shallow non-vegetated, centre/deep vegetated and centre/deep non-vegetated types. Marginal/
shallow microhabitas are generally <30–50 cm deep, while
centre/deep habitats are generally >50 cm deep. Heterogeneity is positively correlated with waterbody depth and size;
therefore, fewer microhabitats were sampled in small,
shallow, non-vegetated waterbodies (approx. 4–6) than in
large, permanent, vegetated waterbodies with all four types of
microhabitats (approx. 20 microhabitats sampled). In the
largest ponds we also sampled microhabitats midway
between the margin and the centre. The total number of
microhabitats sampled in each waterbody in a single survey
ranged from 4–30. Samples were spaced at least 2 m apart.
Samples were taken between 09:00–19:00 h, always during
daylight.
Post-metamorphic surveys were begun 30 min after
sunset, and we searched for individuals along the perimeters
of breeding sites.We counted all post-metamorphic individuals, separating calling and non-calling individuals. Sampling
effort was proportional to size and heterogeneity of the
waterbody (Scott & Woodward 1994).
Waterbody and landscape descriptors
Waterbody selection and sampling
In spring 2009, we carried out initial surveys to select
waterbodies for subsequent sampling, including natural
marshes, ponds, stream sections with low water flow
(streamside pools), and artificial ponds. In each area we
identified 15 waterbodies with evidence of L. catesbeianus
doi:10.1111/aec.12155
We measured the distance from the waterbody to the nearest
forest fragment and to the nearest road using GPS
coordinates. We expanded these distances in second- and
third-order monomials to test for potential non-linear relationships with richness. Area and depth of each waterbody
were measured at each collection event. For depth, we took
the measurements in each of the microhabitats sampled for
© 2014 The Authors
Austral Ecology © 2014 Ecological Society of Australia
B U L L F R O G I N VA S I O N A N D A N U R A N D I V E R S I T Y
tadpoles and recorded the mean, maximum, and minimum
depth. Water surface area ratio obtained from the two sampling events (summer area/spring area) was used as a
measure of pond permanence. We recorded hydrophyte
morphotype (floating and emergent macrophytes) richness in
the pond. We visually estimated the hydrophyte coverage of
waterbodies and classified it into three classes: <30%,
30–60% and >60%. Fish presence/absence was determined
by visual surveys or dip net captures or was based on information provided by local rural owners. We classified the
vegetation of waterbody banks into low grass, tall grass,
shrubs, and trees and used the sum of types present in a site
as 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 nested
spatial arrangement, we considered two kinds of spatial
descriptors: the three large study areas represented by
dummy variables, and Moran’s eigenvector maps (MEMs).
MEMs provide orthogonal spatial variables ranging from
broad, inter-area scales to the finest scales derived from the
geographic coordinates of the sites (Dray et al. 2006). The
spatial arrangement in this study shows a high truncation
value (minimum distance connecting all points = 334 km)
between study areas. We used a nested MEM model
(Declerck et al. 2011), where MEM variables are blocked
within study areas to describe spatial relationships at this
scale. We used the R function create.MEM.model (Declerck
et al. 2011) to build the MEM model using a matrix of
dummy variables that described the three regions as the
connectivity criteria. The nested analysis resulted in seven
spatial vectors describing the spatial arrangement of sites
within areas. These seven MEM vectors and the dummy
variables of the three large study areas were used as spatial
descriptors.
867
and spatial variation. This analytical approach allowed us to
depict the co-variation structure between predictors (Shipley
2000). First, we tested whether bullfrog abundance affects
native richness. Using path analysis, we then tested whether
species richness is related to (i) waterbody, (ii) landscape,
and (iii) spatial descriptors, jointly with (iv) community composition and (v) bullfrog abundance. In order to assess the
relative importance of all five sets of predictors, we built a
hierarchical theoretical model of potential causal relationships explaining native species richness (Fig. 1). This model
assumes a hierarchical causal order between predictors,
where spatial descriptors have the highest causal order and all
other variables are endogenous (see causal links in Fig. 1).
We tested this model using the analytical steps proposed by
Brum et al. (2012). First, we performed a model selection
procedure using each set of descriptors as predictors of native
richness to identify the descriptors that are directly related
with native richness. We then regressed all selected descriptors from all sets against richness to test for direct causal
links. Obeying the causal hierarchy, we regressed all variables
directly linked with richness on their respective potential
predictors (immediate higher hierarchy factors, Fig. 1), and
so on, until we reached the exogenous descriptors, or spatial
descriptors in this case. For instance, if a waterbody descriptor was directly related to local richness, we further
investigated which landscape and spatial descriptors could
explain this descriptor. If a landscape descriptor was
selected, we inspected its relationships with high-order
spatial descriptors. Fish presence was considered together
with other waterbody descriptors. However, we investigated
further 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 linear
models were taken as path coefficients. Model selection was
based on corrected Akaike information criterion (Anderson
2008). All regression models were performed in R (R
Development Core Team 2012).
RESULTS
Data analyses
To remove the effects of sampling effort on richness values,
we regressed richness on the abundance of postmetamorphic individuals, which showed a 96% concordance
with total richness, and used the residuals, henceforth called
richness, in subsequent analyses. To describe species composition across waterbodies, we calculated Jaccard’s index of
similarity for pairs of communities and performed a principal
coordinate analysis (PCoA) (Legendre & Legendre 1998)
using only occurrence (presence/absence) data. We chose
occurrences instead of species abundances because they
allowed us to combine post-metamorphic and tadpole
surveys, thereby dispensing with further weighting assumptions about the importance of distinct life history stages to
the characterization of community composition.The stability
of 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 effects
of bullfrogs on richness, taking into account environmental
© 2014 The Authors
Austral Ecology © 2014 Ecological Society of Australia
Across the three study areas we recorded 40 native
amphibian species: 19 species in A1, 19 in A2 and 23
in A3 (Table 1). Native amphibian richness ranged
from 0–11 species, with an average of 3.9 species per
waterbody (SD = 2.8). The ordination of species composition resulted in 37 PCoA axes. The first three axes
represented 41% of the species composition gradients
and were used in the regression models. The stability
of the first three ordination axes was validated by bootstrap resampling. The first two axes represented the
composition gradient from ombrophilous vegetation
to mixed ombrophilous vegetation to seasonal deciduous forest amphibian communities (Fig. 2A). The
first principal coordinate (PC1) axis clearly varied
from amphibian compositions restricted to dense
ombrophilous forest (e.g. Sphaenorhynchus sp. and
Bokermanohyla hylax) to those occurring in high frequencies across the study regions (e.g. Dendropsophus
minutus and Physalaemus cuvieri) (Fig. 2B).
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C . B OT H ET AL.
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.
We detected bullfrogs at 62 of the 90 sampled
waterbodies, 44 of which showed evidence of breeding
(16 in A1, 16 in A2 and 12 in A3), indicating the
presence of established populations. At least eight sites
in each study area lacked evidence of bullfrogs at any
life stage. The linear model relating native amphibian
richness to bullfrog abundance showed a weak positive
relationship (Table 2). Richness was also positively
related to the first two principal coordinates of community composition, PC1 and PC2 (Fig. 2). Three
MEMs were selected in the spatial model: MEM-2,
which described spatial structure within A2; MEM-3,
which described spatial structure within A3; and
MEM-7 describing spatial structure within A1. The
model relating richness with local waterbody descriptors selected maximum depth, hydrophyte richness, bank vegetation structure, fish presence and
streamside pools as predictors (Table 2).
The path model showed that native amphibian richness was directly determined by the first two principal
coordinates of community composition (PC1 and
PC2), maximum depth, and the binary descriptors for
fish presence, as well as by one spatial model, MEM-2
(Fig. 3). The composition gradients described by PC1
and PC2 showed the highest path coefficients, and
therefore are the main predictors of native amphibian
richness. Stream side waterbodies and two spatial
models (MEM-3 and MEM-4), did not show significant causal links with amphibian richness. Bullfrog
abundance was only indirectly related to amphibian
species richness through its relationship with the community composition gradient of PC1. Hydrophyte
doi:10.1111/aec.12155
richness was also only indirectly linked to richness
through the composition gradients. Hydrophyte richness directly determined bullfrog abundance and community composition gradients PC1 and PC2 (Fig. 3).
The final model accounted for 63% of native richness
variation.
DISCUSSION
Traditionally, the diversity–invasibility relationship has
been explored in order to investigate whether diversity
will prevent invasions. In the face of increasing invasion rates and successful establishment of invaders, it
has become important to explore the effect of invasions on species diversity at a local scale. In this study,
we assessed whether invasion affects diversity in
already successfully occupied areas, expecting a negative relationship between bullfrog abundance and
native amphibian richness. Contrary to our initial
expectation, we found a weak positive relationship,
which was revealed to be indirectly linked to species
composition gradients. Local environmental gradients
describing waterbody features directly explained all
biotic components of the model. They also showed an
additional and important influence of species composition gradients on native richness. Bullfrog abundance
also responded to the same waterbody gradients.
Across the three Atlantic Forest areas, the influence of
space upon richness patterns was small.We found only
weak relationships between micro-regions and lower
richness in A1 and A2, and higher richness in A3.
© 2014 The Authors
Austral Ecology © 2014 Ecological Society of Australia
B U L L F R O G I N VA S I O N A N D A N U R A N D I V E R S I T Y
Table 1.
869
Amphibian composition from southern Atlantic Forest areas invaded by Lithobates catesbeianus
Species
Bufonidae
Rhinella abei
Rhinella fernandezae
Rhinella icterica
Cycloramphidae
Limnomedusa macroglossa
Hylidae
Bokermannohyla hylax
Dendropsophus minutus
Dendropsophus microps
Dendropsophus nahdereri
Dendropsophus nanus
Dendropsophus sanborni
Dendropsophus werneri
Hypsiboas albomarginatus
Hypsiboas albopunctatus
Hypsiboas bishoffi
Hypsiboas faber
Hypsiboas pulchellus
Hypsiboas semilineatus
Hypsiboas cf. semiguttatus 1
Hypsiboas cf. semiguttatus 2
Phyllomedusa tetraploidea
Phyllomedusa distincta
Scinax alter
Scinax fuscovarius
Scinax granulatus
Scinax perereca
Sphaenorhynchus sp.
Hylodidae
Crossodactylus sp.
Leiuperidae
Physalaemus gracilis
Physalaemus cuvieri
Physalaemus nanus
Pseudopaludicola falcipes
Leptodactylidae
Leptodactylus fuscus
Leptodactylus gracilis
Leptodactylus labyrynthicus
Leptodactylus joly
Leptodactylus latinasus
Leptodactylus latrans
Leptodactylus mystacinus
Leptodactylus plaumani
Microhylidae
Elachistocleis bicolor
Total
Abbreviation
Post-metamorphics
Tadpoles
Rab
Rfe
Ric
1
1
1
1
Lma
1
Bhy
Dmin
Dmic
Dnah
Dnan
Dsa
Dwe
Halb
Halbp
Hbi
Hfa
Hpu
Hse
Hsm1
Hsm2
Pte
Pdi
Sal
Sfu
Sgr
Spe
Sphe
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Cro
A1
1
1
1
1
Lfu
Lgr
Llab
Ljo
Llat
Llat
Lmy
Lpl
1
1
Ebi
A3
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
34
1
30
1
19
1
1
1
1
1
1
1
Pgr
Pcu
Pna
Pfa
A2
1
1
1
1
1
1
1
1
1
1
1
19
1
23
A1 = central region of Rio Grande do Sul, deciduous forest; A2 = western region of Santa Catarina, deciduous and mixed
ombrophilous forest; A3 = east of Santa Catarina, ombrophilous forest.
However, only one spatial model was causally significant when considering the entire co-variation structure between all sets of predictors.
At fine spatial scales, negative relationships are
expected because it is at these scales that individuals
actually interact. At this local scale, biotic resistance of
the native community or impact of invasive species are
© 2014 The Authors
Austral Ecology © 2014 Ecological Society of Australia
expected to operate, and both would lead to negative
relationships (Elton 1958). However, it has been
shown that native species differ greatly in the way they
are affected by invasive species. For instance, Thomaz
and Michelan (2011) studied the effects of an invasive
macrophyte on several native macrophytes at distinct
spatial scales and observed that only some of the native
doi:10.1111/aec.12155
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C . B OT H ET AL.
Fig. 2. Ordination of amphibian species composition
across the three study areas. (A) First two axes of principal
coordinate analysis (PCoA) revealing composition gradients
across the study areas (PC1 and PC2). Triangles indicate
species composition from A1 (seasonal deciduous forest),
circles indicate compositions from A2 (mixed ombrophilous
forest), and squares from A3 (ombrophilous forest). (B) Correlation scatter plot for amphibian species with the first two
PCoA axes. Amphibian species are identified by abbreviations (see Table 2).
macrophytes were affected, and, further, that these
negative associations are more common at smaller
scales. A frequently neglected issue is that at fine scales
species facilitation can occur, which would lead to
positive relationships (Bruno et al. 2003). In our case,
a structurally complex community might provide
greater resources for bullfrogs, which are generalist
predators (Bury & Whelan 1984). In turn, bullfrogs
might be able to explore diverse resources in
waterbodies, including anuran prey, without affecting
native diversity.
Here, we tested whether bullfrog abundance can
predict anuran richness and found that this relationdoi:10.1111/aec.12155
ship is mediated by community composition. Bullfrogs were more abundant in certain species-rich
communities. Bullfrog abundance was positively
related to the PC1 community gradient, varying in a
similar fashion in this gradient to common species
like Physalaemus cuvieri and Dendropsophus minutus
that are broadly distributed in South America (IUCN
2011). These species have been recognized as
anthropogenically adapted (Santos et al. 2007), like
bullfrogs. These results are in accordance with those
of Bunnell and Zampella (2008), who found that
bullfrogs are associated with distinct species compositions, being more closely associated with species
that have a widespread distribution. However, bullfrogs do co-occur with other communities in the
Atlantic Forest, albeit at lower abundance, and might
affect the communities by other pathways. For
instance, Both and Grant (2012) found evidence that
bullfrogs have the potential to affect the acoustic
niche of native amphibians: tree-frogs naïve to bullfrog vocalizations significantly altered advertisement
call frequencies in response to bullfrog advertisement
calls. In this case, bullfrogs might not cause an
immediate decrease in richness but could affect
female mate selection and result in important but less
immediate fitness consequences (Both & Grant
2012).
Our results highlight how all biotic components –
species richness, composition, fish presence, and
bullfrog abundance – respond directly or indirectly to
waterbody descriptors. These waterbody descriptors
act as local scale filters, structuring both native
species diversity and bullfrog abundance. Hydrophyte
richness and maximum depth were the main predictors describing waterbodies selected in our final
model. These predictors could be viewed as a
measure of habitat heterogeneity, which undoubtedly
plays an important role for both faunal biodiversity
and abundance. Heterogeneity has the potential to
decouple trophic interactions, promoting greater
diversity (Kovalenko et al. 2012). Despite using a
simplistic measure of heterogeneity of the water
surface (richness of hydrophyte morphotypes), we
found that it was an important predictor of community gradients. Hydrophytes could promote diversity
by providing shelter for tadpoles and postmetamorphic individuals and calling sites or for adult
males. Maximum depth is a gradient that contains
variation related to pond area, permanence, availability of other lower depths, and is also an important
resource for communities in small waterbodies. It
governs the coexistence of nektonic and benthic tadpoles in ponds and streams (Eterovick & Fernandes
2001; Both et al. 2011a). Fish and bullfrog presence
are also regulated by this gradient, because only
waterbodies with a certain depth can support these
organisms (Kushlan 1976; Bury & Whelan 1984).
© 2014 The Authors
Austral Ecology © 2014 Ecological Society of Australia
B U L L F R O G I N VA S I O N A N D A N U R A N D I V E R S I T Y
871
Table 2. Linear model relating native amphibian richness and bullfrog abundance (1) and best models relating native richness
with three different sets of predictors: (2) community gradients, (3) waterbody descriptors and (4) spatial models
(1) Bullfrog abundance
(2) Community gradients
PC1 + PC2
(3) Waterbody descriptors
Depthmax + bank vegetation structure* + hydrophyte richness + stream* + fish presence*
(4) Spatial descriptors
MEM.2 + MEM.3 + MEM.7
R2
AICc
AICc wi
0.05
0.51
405.17
348.24
–
0.75
0.31
384.94
0.27
0.14
401.22
0.10
The selection of best models was based on corrected Akaike information criterion (AICc) and Akaike weight (AICc wi). The
selected models have the highest AICc wi, which describes the relative likelihood of the model, normalized across the set of all
possible models to sum 1. Fixed factors are identified by (*). Principal coordinates of community composition (PC) were used
as 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 present
in 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. Solid
arrows (—) represent positive relationships and dashed arrows (- - -) represent negative relationships. Only paths with P ≤ 0.05
are shown. U = non-determination coefficient (U = 1 − R2). Richness = native amphibian richness; Hydrophyte R = hydrophyte
richness; Veg. types = number of structural vegetation types around the ponds; Depth = maximum depth recorded for a
waterbody; bullfrogs = Lithobates catesbeianus abundance; Fish = fish presence/absence; PC1 = first principal coordinate of community composition; PC2 = second principal coordinate of community composition; MEM.2 = Moran’s eigenvector two,
describing spatial structure within study area A1.
Habitat heterogeneity has been recognized as a key
factor determining the persistence of native frog
populations in areas invaded by bullfrogs in North
America. Adams et al. (2011) studied extinction
probabilities of Rana aurora populations, testing
whether they could be related to bullfrog invasion
and habitat modification. They did not find supporting evidence for an effect of bullfrogs on local extinction probability for the native species. Their results
showed that vegetation cover and riparian vegetation
are the best predictors of low extinction risk on local
scales for the native frog populations. The relationship between species composition and bullfrog
© 2014 The Authors
Austral Ecology © 2014 Ecological Society of Australia
abundance with local waterbody descriptors observed
here are encouraging, because they suggest a means
for habitat management to protect native frogs. In
this study, we found that waterbody depth was causally linked with bullfrog abundance and species richness through positive and negative paths, respectively.
In addition, previous studies showed that waterbody
modification favours bullfrogs and promotes changes
in community composition (e.g. Bunnell & Zampella
2008; Fuller et al. 2011). Waterbodies in areas of
special interest for conservation could be managed to
favour native amphibians, or to prevent the establishment of bullfrogs.
doi:10.1111/aec.12155
872
C . B OT H ET AL.
Our study is not the first to note a positive relationship between amphibian community richness and
invasion.This pattern has been reported for native and
invasive amphibian and reptile communities on
broader spatial scales, suggesting the occurrence of
biotic acceptance (Stohlgren et al. 2006). Poessel et al.
(2013) studied how native richness and alien amphibian species establishment are related in Europe and
North America and found positive relationships in
both regions. They used invasive species richness as a
measure of invasibility, and not single species abundance, as we used in the present study to access bullfrog effects. Nevertheless, they also concluded that
environmental gradients favouring higher native
species richness also favour invasions. Additionally, it
is worth noting that only recent studies dealing with
bullfrog invasion patterns highlight neutral relationships between bullfrogs and richness or emphasize the
role of habitat filtering to promote or facilitate invasions (e.g. D’Amore et al. 2010; Adams et al. 2011).
Such results might be due to study spatial scale and/or
refinement of analytical approaches. Another possibility is that over time, some communities might reach a
new dynamic equilibrium state in which bullfrogs are
not a major threat.
An important consideration when comparing the
results of the present study with those of previous
studies in other regions is that the phylogenetic relationship between bullfrogs and native species is much
closer in those regions than in the Atlantic Forest
localities we studied. In Asia, Europe and North
America there are more ranid species. In China, where
bullfrogs are known to negatively affect richness, native
species composition mostly consists of ranids (Li et al.
2011). In contrast, only a single native ranid species
occurs in the Atlantic Forest (Lithobates palmipes; Hillis
& de Sá 1988), and it is restricted to the northern
portion of the biome. No ranids occurred at any of the
localities we studied, and the closest relative we found
in sympatry with bullfrogs is the microhylid
Elachistocleis bicolor. The potential influence of relatedness upon invasions was recognized by Darwin (1859)
in ‘The Origin of Species’. He suspected that a low
degree of relatedness should give some advantage to
novel species in new habitats. This idea deserves
further investigation, considering the global scale of
invasions by bullfrogs and many other alien species.
In conclusion, we found only a weak and indirect,
positive relationship between native anuran richness
and bullfrog abundance, which is mediated by species
composition at the invaded sites. Our results indicate
biotic acceptance of bullfrogs in the Atlantic Forest.We
observed that bullfrogs were more abundant in some
amphibian communities that include anthropogenicadapted species. The main result is that local
waterbody descriptors predict native richness and
composition and bullfrog abundance. These results
doi:10.1111/aec.12155
agree with recent studies suggesting that environmental gradients directly affect both native and invasive
species. Although we did not detect negative effects of
bullfrogs on native richness, we do not conclude that
such effects are absent in general. Disease transmission, differential predation, and competition by interference are mechanisms that could plausibly operate
in invaded areas, even when bullfrogs have low
abundance.
ACKNOWLEDGEMENTS
This study was supported by IGRE Associação Sócio
Ambientalista and received grants from Fundação o
Boticário de Proteção a Natureza (0835_20092) and
the Rufford Small Grants Foundation. The Conselho
Nacional de Desenvolvimento Científico provided a
student 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 à
Pesquisa do Estado de São Paulo provided a grant to
TG (Proc. 2012/10000-5). ICMBio granted a collection permit for this study (Proc. 23009-1).This manuscript benefited from comments by Sandra Hartz,
Célio Haddad, Márcio Borges-Martins, Adriano
Sanches Melo, and three anonymous reviewers.We are
thankful to all rural owners who granted access to
study sites and the Parque Nacional da Serra do Itajaí
for logistical support. We also thank S. Declerck for
sharing the nested MEM function, V.F. Caorsi for her
help with laboratory procedures, and D. BorgesProvette for help with the literature for tadpole
identification.
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SUPPORTING INFORMATION
Additional Supporting Information may be found in
the online version of this article at the publisher’s
web-site:
Appendix S1. Geographic coordinates of the 90
sampled waterbodies.
© 2014 The Authors
Austral Ecology © 2014 Ecological Society of Australia