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Interrelations Between Environmental Heterogeneity, Competition, and Phylogeny in the Structure of a Lizard Assemblage in a Hypoxerophilic Caatinga Area of Brazil

Authors:
  • CEMAFAUNA CAATINGA
  • Secretaria Municipal do Meio Ambiente da Barra dos Coqueiros - SE/Universidade Federal de Sergipe

Abstract and Figures

The dynamics of a lizard assemblage are influenced by both stochastic and deterministic factors. Structure within the assemblage can result from contemporary factors and differences in evolutionary history among lineages. The objective of this study was to analyze the spatial and trophic structure of a lizard assemblage in Serra dos Macacos, Sergipe, Brazil, and its relationship with historical and ecological factors. We collected data between March and September 2019 during four 14-d-long campaigns using pitfalls, glue traps, and an active search to capture lizards. We recorded information on the substrates occupied by lizards, collected individuals, and we removed their digestive tracts for dietary analysis. We measured the structural characteristics of the microhabitats around the pitfalls and we related these to the abundance of captured species. The results showed that the assembly was structured only with respect to the trophic niche, with most species showing preferences for certain features related to vegetation cover, probably reflecting inherent differences in thermoregulation, as well as spatial heterogeneity itself. We recorded 16 lizard species belonging to 10 families, and phylogenetic analysis revealed a greater contribution of the historical component, although phylogeny alone did not significantly explain the variation. Therefore, it is important to consider the ecological and historical factors when interpreting the results. Serra dos Macacos is a hypoxerophytic Caatinga formation with perennial vegetation strata, and there is an association between spatial heterogeneity and the saurofauna. Thus, forest suppression and habitat loss may negatively affect the diversity of these animals. Resumo.-A dinâmica de um taxocenose de lagartos é influenciada por fatores estocásticos e determinísticos. A estrutura da comunidade pode resultar de fatores contemporâneos e de diferenças na história evolutiva das lin-hagens. O objetivo deste estudo foi analisar a estrutura espacial e trófica de uma taxocenose de lagartos na Serra dos Macacos, Sergipe, Brasil, e sua relação com fatores históricos e ecológicos. Coletamos dados entre março e setembro de 2019, durante quatro campanhas de 14 dias de duração, utilizando armadilhas de queda, armadilhas de cola e busca ativa. Registramos informações sobre os substratos ocupados pelos lagartos, coletamos indivíduos e removemos seus tratos digestivos para análise da dieta. Medimos as caraterísticas estruturais dos microhabitats em torno das armadilhas e as relacionamos com a abundância de espécies capturadas. Os resultados mostraram que a taxocenose esteve estruturada apenas no nicho trófico, com a maioria das espécies mostrando preferências por certas caraterísticas relacionadas à cobertura vegetal, provavelmente refletindo diferenças inerentes à termor-regulação, bem como a própria heterogeneidade espacial. Foram registadas 16 espécies de lagartos pertencentes a 10 famílias, e a análise filogenética revelou uma maior contribuição do componente histórico, embora a filogenia por si só não tenha explicado significativamente a variação. Portanto, é importante considerar os fatores ecológicos e históricos na interpretação dos resultados. A Serra dos Macacos é uma formação de Caatinga hipoxerófita com estratos de vegetação perene, e há uma associação entre a heterogeneidade espacial e a saurofauna. Assim, a 521 Herpetological Conservation and Biology
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520
Herpetological Conservation and Biology 19(3):520–540.
Submitted: 12 May 2023; Accepted: 2 December 2024; Published: 16 December 2024
Copyright © 2024. José Leilton Vilanova-Júnior
All Rights Reserved.
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1Programa de Pós Graduação em Ecologia e Conservação, Universidade Federal de Sergipe,
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Abstract             
            

 
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      
               
 

  
     

       

     

community ecology; diet; ecological factors; historical factors; niche; space use; Squamata
   
     

      




  






521
Herpetological Conservation and Biology

A community is a group of organisms with multiple
species that coexist in space and time (Vellend 2010).
Identifying and studying their patterns (e.g., diversity,
abundance, and species composition) as well as the
processes underlying these patterns have been a main
interest in ecology (McGill et al. 2006; Weber et al.
2018; Catford et al. 2022). Owing to their complex
and dynamic nature, however, it is extremely dicult
to study communities. Therefore, scientists usually
work with subsets of organisms with dened anities
(e.g., guilds and assemblages) to identify patterns of
interactions between them (Pianka 1973; Fauth et al.
1996).
An assemblage of phylogenetically close
organisms is structured when the species and their
ecological traits are arranged non-randomly and
can be tested using null models (Winemiller and
Pianka 1990; Gotelli 2000). In modern coexistence
theory, two mechanisms (equalizers and stabilizers)
are responsible for maintaining and structuring
assemblages; they involve both stochastic and
deterministic elements that can operate at dierent
scales in space and time (Chesson 2000; Hubbell 2005;
Mohd 2022). From a deterministic perspective, the
structure can be a result of contemporary (ecological)
factors, and also a reection of evolutionary history
among the lineages that comprise the assemblages
(Webb et al. 2002; Rabosky et al. 2011; Gonçalves-
Sousa et al. 2019). To understand key elements,
therefore, it is important to consider both historical
(phylogeny) and ecological factors when interpreting
the results, because analyzing them separately can
lead to biased conclusions (Mesquita et al. 2007;
Winck et al. 2016; Gonçalves-Sousa et al. 2022).
In recent decades, improvements in phylogenetic
comparative methods have revealed the inuence
of historical aspects on the organization of lizard
assemblages; indeed, evolutionary divergence among
clades implies dierent ways of resource acquisition
and utilization (Cooper 1995; Vitt et al. 2003;
Mesquita et al. 2016). Thus, the closest lineages are
assumed to share ecomorphological traits acquired
through competitive and selective pressures that have
occurred in the past (Connell 1980; Losos 1996; Vitt
and Pianka 2005). It is thought that niche conservatism
and phylogenetic inertia have signicantly inuenced
the composition and organization of present-day
assemblages (Pyron and Burbrink 2014; Albuquerque
et al. 2018). Additionally, other historical factors
related to biogeography, such as spatial distribution,
a regional pool of species, and their relation to
local richness and composition, may contribute to
assemblage structure (Chase and Myers 2011; Weber
et al. 2018; Pavón‐Vázquez et al. 2022).
Recent studies suggest that ecological patterns
exhibit global convergence and are typically
inuenced by characteristics such as diet, activity,
habitat, and metabolism, indicating the existence
of functional groups of lizards (Pianka et al. 2017;
Vidan et al. 2019). In turn, ecological patterns related
to habits, such as the terrestrial, nocturnal, or ambush
foraging mode are strongly constrained by phylogeny,
and the most widespread and species-rich families
have multiple functional groups, thus contributing to
the high incidence of niche convergence (Pelegrin et
al. 2021). When examining global dietary patterns,
there are correlations between feeding habits,
periods of activity, and life history (Pianka et al.
2017). For example, myrmecophagy is an important
specialization that is phylogenetically concentrated in
Iguania and has only recently evolved in Lacertoidea,
with higher ingestion in lizards with smaller home
ranges and lower ingestion in lizards with extensive
home ranges (Cavalcanti et al. 2023a). In Brazil,
Mesquita et al. (2006a) observed similarities in
diet, microhabitat use, and activity time among
more closely related species in a Cerrado lizard
assemblage. In turn, Albuquerque et al. (2018) found
signs of niche delity in diet, microhabitat, body
temperature, and clutch size in three populations of
Neotropical Lava Lizards () and
Spix’s Whiptails () distributed in
dierent biomes in northeastern Brazil.
Regarding ecological factors, competition is
traditionally recognized as the most important
force in the organization of assemblages (Pianka
1973; Schoener 1977; Gotelli and McCabe 2002).
Thus, we assume the existence of a similarity limit
between sympatric species and that ecologically
similar species diverge on at least one of the niche
axes (trophic, spatial, or temporal). In the absence

 ecologia de comunidades; dieta; fatores ecológicos; fatores históricos; nicho; uso do
espaço; Squamata
522
Vilanova-Júnior et al.—Structure of a lizard assemblage in a Caatinga area of Brazil.
of mechanisms to equalize tness dierences,
species generally occur in allopatry (Pianka 1973;
Chesson 2000; Faria and Araújo 2004). Despite the
emphasis on competition, other ecological factors,
such as predation, parasitism, seasonality, and habitat
heterogeneity can inuence an assemblage (Chesson
2000; Brito et al. 2014; Passos et al. 2016; Barros et
al. 2022).
Diet, microhabitat use, thermoregulation, and
life history of lizards can be strongly inuenced by
environmental, physical, and climatic aspects (Brandt
and Navas 2011; Dell et al. 2014; Albuquerque et al.
2018). At the physical level, more heterogeneous
habitats have more available resources that can
support more species than more homogeneous and/
or degraded environments (Ricklefs and Miller
1999; Luiselli et al. 2022). In addition, structural
variables that inuence light, temperature, and
humidity can directly aect the tness of organisms
and, consequently, determine the occurrence or
non-occurrence of a species (Dias and Rocha 2014;
Arenas-Moreno et al. 2021; Žagar et al. 2023).
Several authors have discussed the eect of
seasonality on lizard ecology (Huey and Pianka
1977; Maia-Carneiro et al. 2012; Passos et al. 2016).
In highly seasonal environments such as the Brazilian
Caatinga, characterized by high temperatures, a
prolonged dry season, and scarce and irregular
rainfall (Prado 2005; Albuquerque et al. 2012), some
species alter their diet and avoid breeding during dry
periods in response to the low availability of trophic
resources (James and Shine 1985; Albuquerque et al.
2018). As ectothermic organisms, lizards can also
restrict their daily activity due to high temperatures
in warmer seasons, a choice that aects their foraging
activity (Huey and Pianka 1977; Winck et al. 2011;
Maia-Carneiro et al. 2012).
Over the last few decades, studies on lizard
assemblages have been conducted in several habitats
in the Neotropical region (e.g., Vitt 1995; Vitt and
Zani 1998; Winck et al. 2016; Souza et al. 2021);
however, only a few studies have investigated the
real inuence of historical and ecological factors
on these groupings (e.g., Werneck et al. 2009;
Gonçalves-Sousa et al. 2019; Gonçalves-Sousa et al.
2022; Cavalcanti et al. 2023b). Some authors suggest
that historical factors have a greater inuence on
the trophic axis than on the spatial axis (Gainsbury
and Colli 2003; Werneck et al. 2009; Cavalcanti et
al. 2023b). In contrast, a recent study conducted
in the Caatinga indicated that ecological factors
have a greater inuence on both spatial and trophic
niche structures (Gonçalves-Sousa et al. 2019). It
is possible to conclude that ecological and historical
factors (individually or together) act in distinct ways
on assemblage structures, culminating in dierent
patterns among localities. To study the possible causes
of lizard assemblage in a tropical environment, we
analyzed the trophic and spatial structure of a lizard
community in an area of hypoxerophilous Caatinga in
the northeast region of Brazil. We expected that: (1)
the structural characteristics of the habitat inuence
the abundance of lizards; (2) the assemblage is
structured in at least one of the investigated niche
dimensions (spatial or trophic), given the irregularity
of the environmental conditions observed in the
Caatinga and the oscillations in the availability of
resources; and (3) ecological factors exert a greater
inuence on the assemblage because of the water
irregularities and severity of some abiotic parameters
typical of the Caatinga

 .—We conducted this study at Serra
dos Macacos (10º52’52”S, 37º59’12”W), which is
approximately 360 km² in area at an elevation of 600
m, in the Tobias Barreto municipality, Sergipe State,
Brazil (Fig. 1). The mountain is located in the central-
southern part of Sergipe, where the predominant
vegetation type is the hypoxerophilous Caatinga,
characterized by larger trees and forest physiognomies
(Arboreal Caatinga or Dry Forest; Instituto Brasileiro
de Geograa e Estatística [IBGE] 2011; Fernandes
et al. 2015). The climate is hot and semi-arid, with
annual temperature and precipitation averages of
approximately 28º C and 780 mm, respectively
(Nimer 1989; IBGE 2011). Serra dos Macacos
 . Map showing the location of Serra dos Macacos,
Tobias Barreto, Sergipe, Brazil. Map A is South America, map B
is Brazil, and map C is Sergipe with Tobias Barreto shown in red.
523
Herpetological Conservation and Biology
presents strong seasonality: May to July show the
highest rainfall rates, while October to December
show the lowest rainfall (http://www.semarh.se.gov.
br/meteorologia). The peak of Serra dos Macacos is
the headwater of the Macacos stream, which is part
of the Rio Real watershed. The riparian forest on
the rocky banks along the stream presents substantial
semideciduous arboreal vegetation, favoring the
formation of a dense understory associated with large
terrestrial bromeliads and epiphytes (Soares et al.
2018)
 .—We conducted the eldwork
between March and September 2019, in four
campaigns each lasting 14 d, totaling 56 d of
sampling. We selected three sample sites: (1) Site
A (10°52’48.83”S, 37°59’15.43”W) refers to a forest
area on the mountain slope, on the margins of the
stream, with large arboreal vegetation, leaf litter, rocky
outcroppings, and walls; (2) Site B (10°52’41.76”S,
37°59’24.65”W) was a tree-shrub area without leaf
litter formation and with grazing by goats; (3) Site C
(10°52’39.16”S, 38°0’36.81”W) was a mosaic area
of large tree vegetation with leaf litter, interspersed
with open areas due to logging activity on-site.
We used three sampling methods to maximize the
amount of information and the number of species we
could collect: (1) Active Search (Blomberg and Shine
2004) - A three-person team spent 3 h/d systematically
searching for lizards in their preferred microhabitats.
The team collected lizards by hand and using rubber
bands and nooses. They evenly distributed the search
time across morning, afternoon, and early evening
shifts; (2) Pitfall traps (Blomberg and Shine 2004) -
We installed 30 sets of traps (stations) consisting of
four 30-L buckets buried in the ground and connected
by 5-m plastic drift fences arranged in a Y pattern.
We evenly distributed these traps among the sampling
sites (10 sets in each area) across a wide range of
environments. We checked and cleaned the traps
twice a day during the sampling period to prevent the
lizards from dying or eating other animals. We sealed
the buckets with lids between the campaigns to avoid
unnecessary capture; (3) Glue traps (Bauer and
Sadlier 1992) - We deployed six strips of glue traps
(about 5 × 35 cm) in the vicinity of each pitfall trap.
We placed three on elevated substrates (tree trunks,
branches, and tall rocks) and three on lower substrates
(fallen logs and smaller rocks). We monitored these
traps twice a day and extracted captured specimens
using cotton swabs pre-saturated with mineral oil.
For each lizard observed or captured during
active searches, we recorded species, date, and
microhabitat used during the rst sighting. We
categorized microhabitats into shrub, cactus, human
construction, rock, leaf litter, open ground, vine, tree
trunk, and fallen log and used their frequencies in the
pseudocommunity and phylogenetic analyses. Upon
reaching the number of individuals determined by the
collection license (SISBIO nº 66720), we recorded
the surplus specimens, marked them with water-
based correction uid (non-toxic), and released them
into the environment to avoid pseudoreplication of
the abundance data with the pitfalls. We pooled the
data obtained from the three sites for all analyses.
We euthanized the collected individuals by injecting
high doses of anesthetic (lidocaine 2%), xed them
in 10% formalin, and preserved them in 70% alcohol
for further analysis. After analysis, we registered the
specimens and incorporated them into the Coleção
Herpetológica da Universidade Federal de Sergipe
(CHUFS).
 .—To establish a correlation
between lizard abundance and microhabitats, we
recorded structural parameters within a 6-m radius of
the central bucket of each pitfall array at the end of
each campaign: (1) the number of bromeliads (NBro);
(2) the number of cacti (Ncac); (3) the number of
holes in the ground (NHG) with a diameter greater
than 5 cm; (4) the number of fallen logs (NFL) with
a minimum circumference of 5 cm and a length of
1 m; (5) the distance (DTCB) of the closest tree to
the central bucket with a minimum breast height
circumference (CTCB) of 5 cm; (6) the percentage of
exposed soil (%OG) or litter (%LL) in three random
50 × 50 cm quadrants; (7) the distance from the
random points described in (6) (DTRP) to the closest
tree with at least a 5-cm circumference at breast
height (CTRP); and (8) the number of stems (Nste)
of all vegetation at least 0.2 cm in circumference and
over 25 cm in height in a 1-m radius area at the same
random locations as in parameter 6. To measure the
parameters DTRP, CTRP, %OG, %LL, and Nste, we
used a 50 × 50 cm frame quadrat with a 5 × 5 cm
grid. A blindfolded person positioned in the center
of the trap randomly threw the quadrat three times
after rotating around its axis a few times. We used
the average of the three measurements to obtain a
single measurement for each parameter for each set
per campaign. We adapted this protocol from a study
by Garda et al. (2012b).
524
Vilanova-Júnior et al.—Structure of a lizard assemblage in a Caatinga area of Brazil.
where p is the proportion of the prey or substrate
category used and i and n correspond to the number
of prey or substrate categories. The value of Ba
varied from 0 (exclusive use of one type of food or
spatial resource) to 1 (homogeneous use of all types
of resources).
We calculated the trophic niche and spatial overlap
(Ø) between species by using the symmetric overlap
index (Pianka 1973), where the symbols are the same
as above, but j and k represent the pair of species
being compared.
We checked the possible interrelationships
between the trophic and spatial niches of the lizards
and whether they were complementary with a partial
Mantel test, from the crossing of both generated
overlap matrices (trophic and spatial niche), by using
the vegan package (Oksanen et al. 2022) in the R
software (R Development Core Team 2022).
To examine the presence of trophic and/or spatial
structures in the assemblage, we used the EcoSim
niche overlap module (Gotelli and Entsminger
2010). Specically, we built a matrix in which the
rows corresponding to the species and resource
categories (spatial or trophic) arranged in the
columns. We reformulated the matrix based on
the 30,000 randomizations (pseudocommunities)
expected in the absence of a structure. Based on
the comparison between the observed and simulated
overlap averages, it was possible to infer whether
the assemblage was structured; in other words, if the
observed mean was lower than the simulated mean,
adopting a signicance of 5%, then we considered
the assemblage to be structured. In EcoSim, we
selected the options Pianka Niche Overlap Index and
Randomization Algorithm 2, which correspond to the
zero retained state and relaxed niche width settings.
Following the method by Werneck et al. (2009) and
Caldas et al. (2019), we ran the analyses twice, once
considering all species in the assemblage and once
excluding species with fewer than four individuals,
to assess whether rare species had a signicant eect
on the results. For trophic overlap analysis, we
used the volume of prey consumed. In addition, we
 .—To analyze the relationship
between lizard abundance and environmental
variables, we considered only species with more
than three specimens captured in the pitfalls and glue
traps. For this purpose, we built two matrices: one
composed of the sum of the abundance data from all
campaigns at each station and the other containing the
averages of the measured environmental variables.
To standardize the variables of dierent scales, we
converted those whose values corresponded to a
linear measure (cm; DTCB, CTCB, DTRP, and
CTRP) into log+1, whereas we converted percentage
values (%OG and %LL) to the arc sine of its square
root (Zar 1999). To test for this association, we
performed a Canonical Correlation Analysis (CCA)
using the vegan package (Oksanen et al. 2022) in
the R software (R Development Core Team 2022).
This is a restricted ordination focused on identifying
and quantifying the association between two datasets
(e.g., species and environmental variables) through
their linear relationship in the same sample sites
(Silva et al. 2022).
For diet analysis, in the laboratory we removed the
entire digestive tract from the collected specimens
and analyzed it under a stereoscopic microscope. We
identied and quantied the food items to the order
level by using a specialized bibliography (Triplehorn
and Jonnson 2011). We classied ants and termites
down to family (Formicidae) and suborder (Isoptera)
levels, respectively. We measured the length and
width of the intact items by using a digital caliper
with an accuracy of 0.01 mm.
We estimated the prey volume (V) by using the
ellipsoid volume formula (Magnusson et al. 2003):
where l is the length and w is the width of food items.
To determine the relative contribution of each prey
category to the diet of the species, we calculated the
Importance Value Index (IVI) by using the following
equation (Acosta 1982):
where F%, N%, and V% correspond to the relative
frequency, abundance, and volume, respectively, of
each prey type consumed by the species.
We calculated food and spatial niche breadths (Ba)
for each lizard species by using the standardized
version of Levin’s index (Hurlbert 1978):
jk pij pikn1
pij
2n
i1 pik
2n
i1
V = (π*l*w2)
6
IVI F%N%V%
3
B
1pi
2
n
i1
ቇെ1
n1
B 1pi2
n
i1
1
n1
525
Herpetological Conservation and Biology
selected the resource status option and entered the
electivity values (sum of the raw volume values of
each prey item for the entire assemblage). Thus, if
structuring is observed, then the diet is not a random
sample of electivity but rather an indication of greater
specialization in resource use.
To evaluate the contribution of the historical
component to assemblage organization, we employed
a phylogenetic Principal Component Analysis
(pPCA), considering the same species evaluated in
the pseudocommunity analyses. It also allowed us to
understand the extent to which the observed patterns
can be attributed to the inuence of ecological factors.
This multivariate analysis tests the dependence of
a given trait along specic phylogenetic lineages
through autocorrelation (Gittleman and Kot 1990;
Jombart et al. 2010). For this purpose, we assembled
two matrices, X and W. In matrix X, we inserted the
ecological variables collected in the eld, that is, the
diet data (the IVI for each category consumed by the
species) and substrate use (the frequency of use for
each substrate category) of the lizards. We chose
to use the IVI to construct the diet matrix because
it covers a larger number of taxa, as seen in the
study by Gonçalves-Sousa et al. (2019). Matrix W
corresponds to a phylogenetic matrix of the species
and their respective phylogenetic distances based
on the Squamata phylogeny by Pyron et al. (2013).
We replaced the absent species in this phylogeny:
the Naked-toed Gecko ( );
Brazilian Galliwasp (Diploglossus lessonae);
  (no common name); and Striped
Lava Lizard ( ) with the
closest taxa present: Peraiba Gecko (
periosus); Puerto Rican Galliwasp (Diploglossus
pleii); Two-lined Fathead Anole ();
and Reinhardt’s lava lizard (). In
a previous study that used the same analysis (Caldas
et al. 2019), we found that this approach should
not signicantly aect the results, given that major
evolutionary changes usually occur in the most basal
branches of the lizard phylogenetic tree (Simões and
Pyron 2021). Higher autocorrelation values indicate
that closely related lineages show similar resource
use, while lower values indicate divergence among
the same taxa; that is, positive eigenvalues indicate
historical eects and negative eigenvalues indicate
ecological eects (Jombart et al. 2010).
To assess whether historical factors alone explain
the niche dierences present in the assemblage, we
performed a partial Mantel test by crossing overlap
data and phylogenetic distances of the assemblage
for both spatial and trophic niches. We performed
a pPCA by using ade4 (Dray et al. 2018), adephylo
(Jombart et al. 2017), and ape (Paradis et al. 2019)
packages in R for Windows (R Development Core
Team 2022). For the partial Mantel test, we used the
vegan package (Oksanen et al. 2022). We adopted a
signicance level of 5% for all analyses.

.—We recorded
491 lizards (pitfalls = 189, glue traps = 45, active
search = 257) belonging to 16 species and 10
families (Supplemental Information Table S1). The
nomenclature we adopted is in accordance with
Sociedade Brasileira de Herpetologia (Guedes et al.
2023). Regarding relative abundance, three species
accounted for more than 60% of the total records: 
 (26.2%),   (21.6%), and 
 (14.7%).
 ×  .—The abundance of
lizards and the structural characteristics of the habitat
were signicantly associated (F11,234 = 1.86, P <
0.01). We generated a biplot, and the main canonical
axes (CCA1 and CCA2) accounted for 31% of the
variation in the data. In the rst axis, responsible for
20.17% of this variation (Table 1), only ,
 , and   correlated with the
distance of the nearest tree to the central bucket, the
number of holes in the ground, and the number of
cacti. Conversely, eight species were associated with
sites with trees of larger circumference and sparser
distribution, with fallen logs, and with bromeliads
(Fig. 2; Table 1). On the CCA2 axis, which
accounted for 10.83% of variation (Table 1), two
gymnophthalmids, two phyllodactylids, one teiid,
and one geckonid were mainly associated with the
distance of the nearest tree to the central bucket, leaf
litter, the abundance of bromeliads, and the number
holes in the ground. In contrast,  , the
Brazilian Mabuya (), ,
, and  were associated with
sparser and larger trees, a high cacti abundance, and
open ground (Fig 2; Table 1).
.—Spatial niche breadths ranged from
0 to 0.37, with the lowest values for the Brazilian
Bush Anole ( ), Argentine
Black and White Tegu ( ), and 
 (Table 2). We observed the largest
breadths for the Brazilian Gecko (
526
Vilanova-Júnior et al.—Structure of a lizard assemblage in a Caatinga area of Brazil.
pollicaris), , and  (Table 2). The
Giant Ameiva (; 57.1%, n = 7), 
(90.9%, n = 33), and  (100%, n = 2) along
with  (75.0%, n = 4) had open ground
as the main category. Species that used rock as
the primary substrate included   (46.3%,
n = 82),  (93.0%, n = 100), and 
pollicaris (42.9%, n = 14). The typical arboreal
species, Kluge’s Dwarf Gecko (;
85.7%, n = 7) and   (100%, n = 1),
almost exclusively used tree trunks. Spatial overlap
values ranged from 0 to 1, with   and
  being the species pair with maximum
overlap, followed by   and  
( = 0.99), and  with  and
 ( = 0.95). Conversely, there was no
degree of sharing between arboreal ( and 
) and terrestrial (, ,
 and ) species (Table 3).
We found a lack of spatial structure in the
assemblage: the mean overlap was higher than
expected if random ( = 0.39; esp = 0.37; P >
0.05), even disregarding less frequent species (n ≤ 4;
 = 0.70; esp = 0.46; P > 0.05). Finally, the pPCA
results indicated a greater phylogenetic inuence on
. The matrix of the structural measures of the microhabitat
with the matrix of the abundance of (A) lizard species and (B) and
pitfalls arrays for the rst two axes of the Canonical Correlation
Analysis (CCA). Structural measures are Nbro = number of
bromeliads, Ncac = number of cacti, NHG = number of holes in
the ground, NFL = number of fallen trunks, DTCB = distance from
the nearest tree to the central bucket, CTCB = circumference of the
nearest tree to the central bucket, DTRP = distance from the nearest
tree in a random point, CTRP = circumference of the closest tree
to a random point, %OG = percentage of open ground, %LL =
percentage of ground covered by leaf litter, and Nste = number
of stems. Lizard species are Am = , Aa = ,
Ao = , Bh = , Cm = , Dl = 
lessonae, Eb = , Gg = , Hb = ,
Lk = , Mm = , Pp = , Sm = 
merianae, Th = , Ts = . See Table 2 for
common names of species. In subgraph B, pitfall sites are A1–10
= pitfalls of sampling site A (arboreal forest, red), B1–10 = pitfalls
of sampling site B (grazed forest, yellow), and C1–10 = pitfalls of
sampling site C (logged forest, green).
Variable CCA1 CCA2
Species
Giant Ameiva ()˗0.723 0.013
Amaral’s Colobosaura ()˗0.283 0.953
Spix’s Whiptail ()0.554 ˗0.070
Brazilian Mabuya (i)˗1.668 ˗0.127
 (no common name) ˗1.473 ˗0.787
Naked-toed Gecko ()0.357 0.385
Kluge’s Dwarf Gecko ()˗0.233 0.400
Maximilian’s Blue-tailed Microteiid
()˗1.164 0.742
Brazilian Gecko ()˗1.136 0.300
Neotropical Lava Lizard ()0.092 ˗0.753
Striped Lava Lizard ()˗0.236 ˗0.362
Structural microhabitat variables
Number of bromeliads ˗0.396 0.243
Number of Cactaceae 0.477 ˗0.272
Number of holes in the ground 0.164 0.327
Number of fallen logs ˗0.509 0.078
Distance from nearest tree to central bucket 0.779 0.184
Circumference of tree closest to central bucket ˗0.794 ˗0.097
Distance from nearest tree to artifact 1 ˗0.308 ˗0.141
Circumference of the nearest tree to artifact 1 ˗0.296 ˗0.388
Percentage of open ground ˗0.365 ˗0.292
Percentage of ground covered by leaf litter ˗0.078 0.123
Number of stems close to artifact 1 ˗0.261 ˗0.166
Explained Variation 20.17% 10.83%
Cumulative Variation 20.17% 31.00%
. Results of the rst two axes of CCA using the structural
variables of microhabitats and the sample size of lizard species
recorded in Serra dos Macacos, Tobias Barreto/Sergipe, Brazil.
527
Herpetological Conservation and Biology
spatial resource usage in the studied assemblage.
Both components (historical and ecological) together
explained approximately 80% of the variation in the
data (H = 50.50%, E = 30.18%; Fig. 3). The teiids (
,  , and  ), along with
, had positive eigenvalues in the global
component (history); this axis mainly included the
open ground and leaf litter categories. On the other
hand, members of Iguania (, ,
and  ) and Gekkota (  and
 ) presented negative eigenvalues,
with rock, tree trunks, and fallen log as the most
signicant categories on this axis. Regarding the
local components (ecological),  and 
 showed positive eigenvalues, with tree trunks
being the most expressive substrates on this axis. The
Species BaS (n) BaF (n)
Amaral’s Colobosaura ()-- 0.07 (17)
Giant Ameiva ()0.12 (7) 0.25 (13)
Spix’s Whiptail ()0.03 (33) 0.07 (38)
Brazilian Mabuya ()0.25 (3) 0.01 (10)
Meridian Gecko ()-- 0.04 (2)
Brazilian Galliwasp (Diploglossus lessonae)-- 0.05 (1)
 -- 0.04 (8)
Naked-toed Gecko ()0.08 (4) 0.03 (37)
Amaral’s Brazilian Gecko ()-- 0.00 (1)
Kluge’s Dwarf Gecko ()0.04 (7) 0.24 (35)
Maximilian’s Blue-tailed Microteiid ()-- 0.10 (7)
Brazilian Gecko ()0.37 (14) 0.29 (10)
Brazilian Bush Anole ()0.00 (1) 0.02 (1)
Argentine Black and White Tegu ()0.00 (2) 0.12 (2)
Neotropical Lava Lizard ()0.27 (82) 0.06 (33)
Striped Lava Lizard ()0.02 (100) 0.11 (35)
. Niche breadths (Ba) of lizards from Serra dos Macacos, Tobias Barreto, Sergipe, Brazil. Acronyms are BaS = spatial niche
breadth, BaF = food niche breadth, and n = sample size.
. Spatial (left diagonal) and food (right diagonal) niche overlap values of lizards from Serra dos Macacos,
Tobias Barreto, Sergipe, Brazil. Species are Am = , Aa = , Ao= ,
Bh = , Eb = , Gg = , Lk = , Pp =
, Pa= , Sm= , Th= , Ts = Tropidurus
. See Table 2 for common names of species.
Aa Ao Bh Eb Gg Lk Pp Pa Sm Th Ts
Am 0.20 0.28 0.15 0.04 0.02 0.01 0.03 -- -- 0.19 0.31
Aa 0.47 0.04 0.10 0.01 0.01 0.35 -- -- 0.13 0.08
Ao 0.84 0.18 0.14 0.02 0.01 0.25 -- -- 0.11 0.12
Bh 0.46 0.58 0.11 0.07 0.02 0.11 -- -- 0.32 0.14
Eb -- -- -- 0.01 0.00 0.08 -- -- 0.09 0.02
Gg 0.76 0.95 0.73 -- 0.28 0.02 -- -- 0.17 0.03
Lk 0.00 0.00 0.57 -- 0.00 0.06 -- -- 0.07 0.21
Pp 0.23 0.31 0.33 -- 0.27 0.28 -- -- 0.33 0.21
Pa 0.00 0.00 0.58 -- 0.00 0.99 0.28 -- -- --
Sm 0.80 1.00 0.58 -- 0.95 0.00 0.28 0.00 -- --
Th 0.46 0.53 0.49 -- 0.51 0.23 0.90 0.24 0.50 0.18
Ts 0.02 0.05 0.04 -- 0.03 0.02 0.86 0.02 0.02 0.84
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Vilanova-Júnior et al.—Structure of a lizard assemblage in a Caatinga area of Brazil.
. Phylogenetic tree (on the right) and scatter plot of the phylogenetic Principal Component Analysis (pPCA) for the spatial niche
data of lizards from Serra dos Macacos, Tobias Barreto, Sergipe, Brazil. The eigenvalues of the canonical axes in the phylogenetic tree
are represented by black circles (positive autocorrelation) and white circles (negative autocorrelation) of the rst global component (PC1)
and the rst local component (PC6). The acronyms Shr = shrub, Cac = cacti; HC = human constructions, Roc = rock, LL = leaf litter, OG
= open ground, Vin = vines, TT = upright tree trunk, and FL = fallen tree trunk.
 Am Aa Ao Bh Cm Dl Eb Gg Hb Lk Mm Pp Pa Sm Th Ts
Aca -- 3.4 1.0 -- -- -- -- 1.0 -- 7.8 -- -- -- 32.1 3.1 1.0
Ara  11.0  7.3 -- -- 14.8 6.4  7.6  9.8 -- -- 9.4 5.3
Ave -- -- -- -- -- -- -- -- -- -- -- -- -- 17.9 -- --
Bla -- 12.3 3.9 --  -- 4.4 5.5 -- 3.5 -- 4.7 34.6 -- 5.6 1.0
Chi -- -- 1.9 -- -- -- -- 4.7 -- -- -- -- -- -- 2.1 --
Col --  15.4  --   3.3 --  --   17.9  
Dipl -- 2.9 -- -- -- -- -- -- -- -- -- -- -- -- 3.2 --
Dipt -- 3.4 -- 3.5  -- 4.4 2.0 -- 2.5 -- -- -- -- 3.1 6.4
For -- 17.5  7.0 -- --   -- -- --  --   
Gas -- -- -- -- -- -- -- -- -- -- -- -- -- -- 1.1 --
Hem -- 2.9 2.9 7.0 -- -- 4.4 -- -- 2.9 -- 9.3 -- -- 6.9 3.0
Hym  6.0 12.6 11.5 -- -- -- 2.1 --   7.3 -- -- 19.4 
Iso -- 18.2   -- --   -- 11.3 -- 6.0 -- 19.0  18.7
Lac -- -- -- -- -- -- -- -- -- -- -- -- --  -- 1.0
LarI 6.9 13.1 11.5  -- -- 13.2  --  --  --  27.8 20.5
Lep -- -- 1.0 -- -- -- 6.1 -- -- -- -- -- -- -- 3.1 --
PMat -- 7.7 1.8 -- -- -- -- 5.4 -- 1.9 4.8 6.7 33.3 16.7 9.1 4.8
Opi -- -- -- -- -- -- -- 1.1 -- -- -- -- -- -- -- --
Ort   6.6 -- -- -- 15.4 7.4 -- --  10.7  17.9 12.6 5.8
Pha -- -- -- -- -- -- 14.6 -- -- -- -- -- 34.6 -- 1.0 --
Psc -- -- -- -- -- -- -- 1.1 -- 2.6 -- -- -- -- -- --
Sco --  8.6 -- --  6.0 -- -- -- -- -- -- -- -- 3.2
. Importance Value Index (IVI) of prey categories consumed by lizards in Serra dos Macacos, Tobias Barreto, Sergipe, Brazil.
Prey categories (left vertical column) are: Aca = Acari, Ara = Araneae, Bla = Blattodea, Chi = Chilopoda, Col = Coleoptera, Dipl
= Diplopoda, Dipt = Diptera, For = Formicidae, Gas = Gastropoda, Hem = Hemiptera, Hym = Hymenoptera, Iso = Isoptera, Lac =
Lacertilia, LarI = insect Larva, Lep = Lepidoptera, PMat = plant material, Opi = Opiliones, Ort = Orthoptera, Pha = Phasmatodea, Psc
= Pseudoscorpiones, and Sco = Scorpions. Lizard species (top line) are: Am = , Aa= , Ao=, Bh = 
, Eb = , Gg = , Lk =  , Pp = , Pa= , Sm= , Th= ,
Ts = . See Table 2 for common names of species. The three highest IVI values for the species are highlighted in bold.
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Herpetological Conservation and Biology
other species had negative eigenvalues, represented
mainly by rocks, fallen logs, and open ground (Fig.
3). Phylogeny was not signicantly correlated with
spatial niche (r = ˗0.204, P = 0.898).
 .—We analyzed 250 stomachs,
counting 4,210 food items distributed into 22
categories (empty stomachs: n = 10; advanced
digestion: n = 20). The most frequent prey items,
regardless of the ingesting species, were Coleoptera (F
= 15.97%), Formicidae (F = 15.04%), and Isoptera (F
= 14.73%), while the most abundant were Isoptera (
= 53.60%), Formicidae ( = 26.92%), and Coleoptera
( = 6.41%). The most volumetrically representative
categories were Coleoptera (V = 30.25%), insect
larvae (V = 21.30%), and Lacertilia (V = 13.58%;
Supplemental Information Table S2). Concerning
the IVI, Isoptera was the most important category for
, , , , and
, while Coleoptera and Formicidae were
among the most important categories for ,
, , and (Table
4).
We observed the largest niche breadths for 
pollicaris, , and , and the smallest
for Amaral’s Brazilian Gecko (
), , and  (Table 2).
We recorded low overlaps in food resource sharing:
 and  showed the highest degree
of sharing, followed by  , 
pollicaris, and   (Table 3). Spatial niches
were not signicantly related to trophic niches (r =
0.206, P = 0.137).
The assemblage was structured based on the
trophic niche, both with ( = 0.10; esp = 0.30;
P < 0.001) and without (n ≥ 4;  = 0.13; esp =
0.50; P < 0.001) the less frequent species. Although
rare species did not exert a signicant inuence on our
results, we still disregarded those with n ≤ 4 because
of a better t in the pPCA (Mesquita et al. 2006a).
The pPCA results indicated a greater contribution
of the historical components compared with the
ecological components, and together they explained
more than 70% of the variation in the data (H =
45.68, E = 28.96; Fig. 4). The ecological component
was most prominent in Teiidae ( and 
ameiva), Gekkota (,  and 
), and . Among these, , 
, and  showed positive eigenvalues
and this axis mainly included Isoptera, while 
ameiva,   and   had negative
eigenvalues, the axis that mainly included beetles and
insect larvae. Conversely, the historical component
was prominent in Iguania ( ,  ,
and  ) and Gymnophthalmidae (
 and  ). Iguania lizards had
negative eigenvalues, and Coleoptera, Formicidae,
and Isoptera were the main representatives of this
axis. Finally,  and  showed
positive eigenvalues for the global component,
. Phylogenetic tree (on the right) and scatter plot of the phylogenetic Principal Component Analysis (pPCA) for the trophic
niche data of lizards from Serra dos Macacos, Tobias Barreto, Sergipe, Brazil. The eigenvalues of the canonical axes in the phylogenetic
tree are represented by black circles (positive autocorrelation) and white circles (negative autocorrelation), of the rst global component
(PC1) and the rst local component (PC10). In the pPCA scatter plot, the IVI matrix data has been standardized (IVI×0.01) to allow
for a coupled visualization. Food items are Aca = Acari, Ara = Araneae, Bla = Blattodea, Chi = Chilopoda, Col = Coleoptera, Dipl
= Diplopoda, Dipt = Diptera, For = Formicidae, Gas = Gastropoda, Hem = Hemiptera, Hym = Hymenoptera, Iso = Isoptera, Lac =
Lacertilia, LarI = Insect Larva, Lep = Lepidoptera, PMat = Plant Material, Opi = Opiliones, Ort = Orthoptera, Pha = Phasmatodea, Psc =
Pseudoscorpiones, Sco = Scorpiones.
530
Vilanova-Júnior et al.—Structure of a lizard assemblage in a Caatinga area of Brazil.
which was represented by Orthoptera, Araneae,
and Hymenoptera (Fig. 4). Phylogeny was not
signicantly correlated with trophic niche (r = 0.127,
P = 0.148).

×.—We found signicant
correlations between lizard abundances and certain
habitat characteristics, a pattern observed in other
assemblages (Garda et al. 2012b; Dias and Rocha
2014; Flores et al. 2023). The rst axis (CCA1)
represented the dierences between the pitfalls placed
in areas with more forest cover, sparser and larger
trees, and a greater number of bromeliads and fallen
logs, in contrast to pitfalls placed in modied areas,
farther from trees, and with a greater abundance of
cacti and holes in the ground. On the other hand,
the CCA2 axis represented more specic variations
found in the microhabitats, including the gradient
from sites with leaf litter, bromeliads, fallen logs,
and holes in the ground to sites with open ground,
a greater number of cacti, and/or larger trees. Based
on our results, there are indications that species
preferences for certain characteristics related to the
level of vegetation cover may reect the temperature
dierences inherent in thermoregulation, as well as
the level of spatial heterogeneity.
Among the species that were more associated with
open and/or human-disturbed areas, the abundance of
the small lizard   was correlated to the
number of holes in the ground and more weakly to
leaf litter, which can be explained by the availability
of shelter against the high temperatures of site B (the
absence of leaf litter and little canopy cover) and
possible predators (Gaudenti et al. 2021). 
 was correlated with the abundance of cacti,
which were associated with more open areas (B and
C), where we captured all specimens used in the
analysis. We expected this relationship because the
terrestrial habit and heliophilic behavior of this lizard,
as well as its predominance in open formations, have
been well described in the literature (Mesquita and
Colli 2003; Dias and Rocha 2007; Machado et al.
2016). Finally, although   did not show
an expressive preference for more preserved or
human-disturbed areas, it was associated with sites
with a higher vertical stratication. This result
reinforces the plastic and habitat-generalist character
of the species, which can occupy forested, open, and
human-disturbed areas (Santana et al. 2014; Andrade
2019).
  and  
were associated with more humid microhabitats,
with bromeliads and leaf litter. Access to these
spatial resources is very conservative for the
Gymnophthalmidae family, which is composed of
small lizards that constantly seek refuge and avoid
high temperatures (Vanzolini et al. 1980; Delm
and Freire 2007; Oliveira and Pessanha 2013).
The general abundance data support this inference,
because neither species occurred in site B, which
lacked leaf litter
  and   belong
to the Gekkota clade, which comprises several
predominantly arboreal taxa capable of occupying
dierent stratications in the environment (Vitt et al.
2003). We conrmed this association based on the
presence of these species in areas with high forest
cover; however, we observed distinct ecological
adjustments between the two. 
preferred habitats with more bromeliads and fallen
logs, which can be used as perches, shelters, or
thermoregulation substrates (Rodrigues 1987). In
contrast,  did not exhibit a strong relationship
with tree diameter or spacing. The small size of
this species probably allows for the use of trees of
various sizes, some of which are unsuitable for larger
arboreal species (Galdino et al. 2011), such as 
, which is strongly related to larger trees.
Species of the genus Enyalius are typically arboreal
or semiarboreal (Rodrigues et al. 2014). In addition,
the small size of  implies limited mobility,
which explains the minimal relationship between this
species and the distance between trees.
It has been well documented in the literature that 
ameiva can be found in open areas, forest edges, and
more preserved environments (Sales et al. 2011b). The
low correlation of this species with CCA2 variables
may be related to its plasticity in environments
with dierent spatial characteristics. Additionally,
although the traps indicated a greater association
between  and conserved areas, the records
of the active search revealed a relatively uniform
presence among sampling sites, supporting the
previously mentioned pattern. 
was predominant in forested environments, with
lower direct insolation rates. Despite its heliophilic
habit, this lizard has a smaller body temperature range
than teiids and tropidurids (Vitt 1995; Ribeiro et al.
2019), that is, it can thermoregulate more eciently
in shadier habitats.
Although  has widely understood
saxicolous habits (Gomes et al. 2015), this was not
531
Herpetological Conservation and Biology
evident because of the positioning of the pitfalls,
given the diculty of burying them near rocky slabs
and walls. Thus, our results imply that we collected
the specimens during the movement between their
usual microhabitats (rocky outcrops), resulting in the
absence of a correlation between  
and the environmental variables measured. The
records obtained by the active search corroborated
the traditional pattern. Additionally, Andrade-Lima
et al. (2022) suggested that, despite its high delity
to this substrate,   may increase its
movement rate in response to low food availability.
Finally, the relatively low explanatory power of the
main canonical axes of the analysis may be due to
methodological issues related to scale and sampling.
Open formations such as the Caatinga have greater
horizontal heterogeneity, making the detection
of these patterns at the local scale more dicult
compared with continuously forested environments,
whose habitats vary more vertically (Garda et al.
2012b).
 .—When analyzing the use
of microhabitats, we noticed that the majority
of species exhibited specialist behavior. The
saxicolous  , the arboreal  
and   maintained high delity to their
respective substrates (Vitt and Lacher 1981; Galdino
et al. 2011; Caldas et al. 2015). The similarity in the
use of the same resources in dierent environments
by these species or congeners (Simbotwe 1983;
Nogueira et al. 2005; Pelegrin et al. 2017) suggests a
strong inuence of historical factors on their spatial
niche. Among those species more closely associated
with the ground, we observed   and 
 in open ground without leaf litter cover,
and the latter was also related to open areas with
higher insolation rates (Teixeira-lho et al. 1995;
Mesquita and Colli 2003; Albuquerque et al. 2018).
In contrast, , a species widely distributed in
the Brazilian biomes (e.g., Caatinga, Mata Atlântica,
Restinga, and Cerrado), similarly occupied soils with
and without leaf litter, seen both in forested and open
areas, demonstrating a certain plasticity in this aspect
(Werneck and Colli 2006; Sales et al. 2011b; Benício
et al. 2019).
We mainly observed  on open ground,
in contrast to other studies, where it was primarily
associated with leaf litter, rocks, and fallen logs
(Vitt 1995; Muniz et al. 2016; Oitaven et al. 2022).
Among the species that use substrates more broadly,
  is recognized as a habitat generalist: it
has been recorded in a wide variety of microhabitats
in natural or even human-disturbed environments
(Gomes et al. 2015; Machado et al. 2016; Albuquerque
et al. 2018). Despite its wide niche breadth, we also
primarily observed the nocturnal lizard 
on rocks, probably using the accumulated heat in this
substrate to satisfy its thermal requirements, as well
as to nd shelter from potential predators (Recoder et
al. 2012; Ferreira et al. 2014; Condez et al. 2021).
Although most species showed low niche breadths,
we observed high overlap rates among some,
suggesting the inuence of niche conservatism on the
selection of the same substrate categories by certain
lineages. According to Pianka (1973), sympatric
species that use the same spectrum of resources
available along one of the niche axes, in this case
the spatial axis, tend to diverge in at least one of the
other two axes (temporal and trophic). Although
there was no signicant complementarity between
the trophic and spatial niches in the overall aspect
of assemblage, by observing some ecological and
morphological elements known to the taxa, we can
infer that regardless of the high overlap observed,
some species do not eectively compete for the
same resources. A good example is  and 
, which almost entirely overlap with the
use of trees as perches; however, the discrepancy
between their body sizes and shapes may allow
the dierential use of spatial and trophic resources
(Carvalho and Araújo 2007; Pelegrin et al. 2017). The
same can be said regarding the overlap we observed
between  and other terrestrial lizards (
ameiva,  , and ). Despite the
high overlap between , , and
, they were temporally segregated, as
 has nocturnal habits and the other two
are diurnal (Recoder et al. 2012; Ferreira et al. 2014;
Gomes et al. 2015).
Similarly to other studies in the Neotropics,
including in the Caatinga, we found no signs of
spatial structure (Machado et al. 2016; Winck et al.
2016; Gonçalves-Sousa et al. 2022). This suggests
that space is not a limiting resource for lizards at
Serra dos Macacos and that competition is not a
relevant force in substrate selection (Mesquita et al.
2006a,b). Some of these authors have related the
lack of structuring to the bias imposed by the scarcity
of microhabitat data for some taxa because of the
diculty in recording the habits of some cryptic,
discrete-moving, and/or less abundant species
(Mesquita et al. 2006a,b; Werneck et al. 2009). It
is important, however, to highlight the inuence of
532
Vilanova-Júnior et al.—Structure of a lizard assemblage in a Caatinga area of Brazil.
environmental heterogeneity demonstrated by the
CCA. Although the species showed high overlap in
substrate use, they were segregated at the habitat level.
Thus, there was not necessarily an intensication in
the use of certain resources in the same locality, as
they would be available in other areas.
The pPCA revealed a greater contribution of
historical components to the spatial niche, although
phylogeny alone did not explain the variation we
found. The main indication of phylogenetic inuence
is the relationship between microhabitat use and
foraging strategies (Huey and Pianka 1981; Brito et
al. 2014; Rodda 2020). In our study, all species that
had the ground as their main substrate (except for 
) were active foragers, whereas the other
taxa (sit-and-wait foragers) used vertical substrates
such as rocks, tree trunks, and fallen logs (Vitt et al.
2003). Thus, substrate selection would be mediated
by the availability of historically preferred dietary
resources (Vitt et al. 1999; Werneck et al. 2009;
Lanna et al. 2022). Furthermore, the similarities
in space use of this assemblage with those in other
regions and biomes point to a certain degree of spatial
niche conservatism (Losos 1996).
 .—The dietary compositions of
some species were similar to those previously
reported for other populations distributed throughout
the Neotropical region (Vitt et al. 1999; Mesquita et
al. 2006a; Vilanova-Júnior et al. 2016; Gonçalves-
Sousa et al. 2019). The low variation in diet among
assemblages exposed to dierent scenarios suggests
a strong inuence of phylogeny (Vitt et al. 2003;
Vitt and Pianka 2005). For example,  
maintains a varied consumption pattern of prey in
dierent biomes, indicating that its trophic plasticity
has been conserved (Vitt et al. 1999; Mesquita et
al. 2006a; Sales et al. 2011a; Vilanova-Júnior et al.
2016; Gonçalves-Sousa et al. 2019). The degree of
importance of each of these categories in 
populations, however, is subject to ecological factors,
such as resource availability and/or competition
(Sales et al. 2011a). Additionally, the divergence
between our results and those of other studies
regarding the main diet components of Isoptera
and Isopoda in the Meridian Gecko (
meridionalis; Silva et al. 2015), and plant material in
 (Garda et al. 2012a) and 
(Kiefer and Sazima 2002) may be due to the low
number of specimens we collected.
Sit-and-wait foragers tend to be less selective in
their prey choice and, consequently, have a larger
niche width than active foragers (Bergallo and Rocha
1994; Vitt and Caldwell 2014). Among the more
generalist species of Serra dos Macacos, 
and  t this pattern well. In contrast, the other
sit-and-wait lizards showed considerably smaller
niche widths, and the active forager  had the
second-largest niche width of the assemblage. These
ndings suggest that ecological factors (e.g., resource
availability and/or competition) may contribute to
the expansion or reduction of the niches of species
(Mesquita et al. 2007; Caldas et al. 2019).
Contrary to our observations for the spatial
niche, the assemblage showed low trophic overlap.
The pair of species with the greatest similarity in
diet composition was   and  ;
however, they diered considerably in the most
important prey categories. Thus, pseudocommunity
analysis detected structure for the trophic niche. In
other words, competition is a relevant factor in prey
selection, and this segregation over time is likely
necessary to maintain the lizard richness of Serra dos
Macacos (Werneck et al. 2009; Gonçalves-Sousa et
al. 2019; Gonçalves-Sousa et al. 2022). Researchers
have reported similar results in other areas of the
Caatinga and in other environments where seasonality
has a great impact on the abundance and availability
of arthropods (Winemiller and Pianka 1990; James
1991; Gonçalves-Sousa et al. 2019).
We also found a higher inuence of historical
components compared with ecological ones,
reinforcing the importance of phylogeny in the diet
composition of lizards (Vitt and Pianka 2005; Lanna
et al. 2022). As indicated by the pseudocommunity
analysis, however, contemporaneous factors showed a
signicant eect on the assemblage, and some clades
were more inuenced by them. We detected signs
of niche conservatism in Iguania lizards (,
, and ) with respect to the
ingestion of ants and beetles. Similar results have
been reported in the literature (Kolodiuk et al. 2010;
Gomes et al. 2015; Ferreira et al. 2017), and this
relationship is attributed to the evolutionary origin of
this group, linked to the diversication of the major
ant lineages and, to a minor degree, Coleoptera (Vitt
and Pianka 2005; Sites-Junior et al. 2011; Cavalcanti
et al. 2023a). The members of Gymnophthalmidae
(  and  ), on the other
hand, ingested mainly Orthoptera, Araneae, and
Hymenoptera. The importance of phylogeny in
the diet of these taxa is reinforced by other studies
in the Cerrado, where orthoptera and spiders are
among the main items consumed by 
533
Herpetological Conservation and Biology
(Mesquita et al. 2006a; Werneck et al. 2009; Vechio
et al. 2014), or when Orthoptera is a relevant item
in the diet of  (Vieira et al.
2000). In contrast, other clades (Teiidae, Mabuyidae,
Phyllodactylidae, and Gekkonidae) were more
prominently inuenced by local components. Most
closely related species diverged in diet composition,
whereas   and  had positive
eigenvalues (represented mainly by termites), and
their respective relatives  and 
had negative eigenvalues (the latter represented by
beetles and insect larvae).
.—Our results demonstrate that lizard
lineages may respond dierently to environmental
pressures, reinforcing the importance of considering
both factors (ecological and phylogenetic) to interpret
the determinants of assemblage organization.
Additionally, the data have direct implications for the
conservation and management of Serra dos Macacos,
as lizards are usually abundant and represent a
signicant portion of vertebrate diversity in tropical
environments, especially in semi-arid regimes such
as the Caatinga. We found that even an aspect such
as the trophic niche, which is normally conservative,
can be inuenced by local factors that are crucial in
competitive interactions and resource sharing. We
also observed that the similarity in microhabitat
use may reect their high availability as habitats
vary, meaning that horizontal heterogeneity would
allow the use of similar resources along a vegetation
gradient. As a formation of hypoxerophilous
Caatinga, Serra dos Macacos represents an enclave of
humid forest (Moro et al. 2024), with the presence of
springs and watercourses that maintain the perennial
status of certain portions of the vegetation stratum.
Thus, as there is an association between spatial
heterogeneity and the lizard assemblage, and that
forest suppression and habitat loss directly aect
lizard diversity. Furthermore, there have been very
few studies evaluating the interrelationship between
spatial heterogeneity, competition, and phylogeny,
and our work is important in this regard. Therefore,
the development of integrative methods to measure
the action of these eects at the local scale and
their use in dierent assemblages is fundamental to
elucidate the patterns that emerge from the complex
synergy between historical and ecological factors.
This approach would facilitate the generalization
and formulation of more consistent theories at larger
scales.
.—Our study was made possible
thanks to the logistics provided by the inhabitants
of the Macacos settlement. We thank the Biology
undergraduate students for their help in the eldwork
and we are especially grateful to Jeerson Luduvice,
Gabriela Tupy, Whendel Rodrigues, and Silvia
Garcia for their signicant help during the various
stages of this study. We are grateful for the support
of Universidade Federal de Sergipe (UFS) during the
research execution, and to Sistema de Autorização e
Informação em Biodiversidade (SISBIO) for issuance
of a collection license (#66720). We also thank the
Coordenação de Aperfeiçoamento de Pessoal de
Nível Superior (CAPES) for the M.Sc. stipends to
JLV-J, SVS, RSPS, VGMS. Finally, FLSC thanks the
Conselho Nacional de Desenvolvimento Cientíco e
Tecnológico (CNPq) for the postdoctoral fellowships
(150827/2018-0 and 150063/2022-9).
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 has a Master's degree in Ecology and Conservation from the Federal
University of Sergipe, Brazil. He has about 10 y of experience working with herpetofauna, focusing on
the ecology and natural history of lizards. José is currently a Biologist at the Caatinga Fauna Conservation
and Management Center (CEMAFAUNA - UNIVASF) and a volunteer collaborator at the Laboratory of
Reptiles and Amphibians (LARA - UFS). His academic interests mainly involve assemblage structure and
the interrelationships between deterministic factors on the species niche. (Photographed by José Leilton
Vilanova-Júnior).
 has a Ph.D. in Biological Sciences (Zoology) at the Federal University
of Paraíba, Brazil. He is currently a Biologist allocated to the Municipal Environment Secretariat of Barra
dos Coqueiros/Sergipe. Francis has two postdoctoral degrees from the Federal University of Sergipe, an
institution where he is a Volunteer Professor in the Biology Department and the Postgraduate Program in
Ecology and Conservation. He has been working in herpetology for 17 y, mainly with the ecology and natural
history of frogs and lizards. His interests mainly involve population and assemblage structure, and ecological
and phylogenetic eects on the species niche. (Photographed by Francis Luiz Santos Caldas).
has a degree in Biology from the Federal University of Sergipe
(UFS), Brazil. She is currently pursuing her Master’s degree in Ecology and Biodiversity Conservation
at the State University of Santa Cruz (UESC), Brazil, where she is working on the role of environmental
heterogeneity in the ecology of lizards in a mosaic of forest remnants and agricultural crops. Rachel has
experience and an interest in community ecology, with a focus on herpetology. (Photographed by Rachel dos
Santos Pinto de Souza).
 graduated in Biological Sciences from the Federal University of Sergipe (UFS),
Brazil. She is a Master's student in the Graduate Program in Zoology at the State University of Santa Cruz,
Brazil. Samantha has experience in zoology, with an emphasis on herpetology, as a Researcher in the
Laboratory of Reptiles and Amphibians (LARA) at UFS and at the Tropical Herpetology Lab. Her research
mainly focuses on the trophic ecology of frogs. (Photographed by Samantha Vieira Silva).
is a graduate student at the Federal University of Paraíba, Brazil, currently
pursuing her Master's degree in Biological Sciences (Zoology) investigating ecological, phylogenetic, and
bioacoustic aspects in Anurans assemblages. Her main interests are ecology and the natural history of the
herpetofauna. (Photographed by Vitória Gomes de Melo Santos)
 has a Ph.D. in Animal Biology from the Brasília University, Brazil. He is currently
a Professor at the Federal University of Sergipe (Biology Department), Brazil, and a Professor of the
Postgraduate Program in Ecology and Conservation. Renato has extensive experience with ecology and
natural history of amphibians and reptiles. (Photographed by Renato Gomes Faria).
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