Quiroga et al. 2016. Local and continental determinant of giant anteater (2) .pdf
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Título: Local and continental determinants of giant anteater (Myrmecophaga tridactyla) abundance: Biome, human and jaguar roles in population regulation
Autor: Verónica Andrea Quiroga
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Mammalian Biology 81 (2016) 274–280
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/mambio
Local and continental determinants of giant anteater (Myrmecophaga
tridactyla) abundance: Biome, human and jaguar roles in population
Verónica Andrea Quiroga a,b,∗ , Andrew Jay Noss c , Gabriel Iván Boaglio d ,
Mario Santiago Di Bitetti a,b,e
Instituto de Biología Subtropical, Universidad Nacional de Misiones—Consejo Nacional de Investigaciones Cientíﬁcas y Técnicas (CONICET), Bertoni 85, CP:
3370, Puerto Iguazú, Misiones 423511, Argentina
Asociación Civil Centro de Investigaciones del Bosque Atlántico (CeIBA), Bertoni 85, CP: 3370, Puerto Iguazú, Misiones, Argentina
Department of Geography, University of Florida, 1405 NW 38th St., Gainesville, FL, USA
Instituto de Ecología Animal (IDEA), FCEFyN, Universidad Nacional de Córdoba (UNC), León 2022, CP: 5014, Córdoba Capital, Argentina
Facultad de Ciencias Forestales (UNaM), Bertoni 124, CP: 3380. Eldorado, Misiones, Argentina
a r t i c l e
i n f o
Received 1 June 2015
Accepted 14 March 2016
Handled by Nelika K. Hughes
Available online 19 March 2016
a b s t r a c t
The giant anteater (Myrmecophaga tridactyla) is currently found in a wide variety of habitats from Honduras to Argentina. Across this wide range, researchers have postulated that anteater populations are
negatively affected by several factors, including hunting, habitat loss and fragmentation, ﬁre, vehicle collisions, and predation by jaguars. But no studies to date have evaluated the relative importance of these
factors across sites, either at a regional or continental scale. We used camera traps to analyze variation
in giant anteater abundance at two spatial scales. At a regional scale, we conducted camera trap surveys
in the dry Chaco of Argentina and used occupancy models to explore the effect of protection status and
human accessibility on giant anteaters’ relative abundance. At a continental scale, we used data from 40
camera trap studies (representing 42 different locations) and Generalized Linear Models (GLM) to assess
the potential relation of biome, human disturbance and the presence of jaguars on giant anteater camera
trap records. In the Argentine Chaco, protection and human disturbance do not signiﬁcantly affect the
proportion of area used by the species. The average anteater records/100 camera days and the proportion
of sites used are very high across the study area. At a continental scale, anteaters are more frequently
recorded in dry forests than in moist forests. Locations with very high human disturbance have camera
trap rates that are 5–10 times lower compared to intermediate or low disturbance locations. Finally, giant
anteater capture frequency increases up to 70% where jaguars are absent. Dry biomes and intermediate
levels of human disturbance may favor anteaters by providing greater habitat heterogeneity coupled
with a lower jaguar abundance. This may explain the relatively high abundance of giant anteaters in the
Argentine Chaco. However, growing human populations, the advancing agriculture-livestock frontier,
and an expanding road network may in time eliminate giant anteaters from most of this region.
© 2016 Deutsche Gesellschaft für Säugetierkunde. Published by Elsevier GmbH. All rights reserved.
The giant anteater (Myrmecophaga tridactyla; Linnaeus, 1758)
is currently found in a wide variety of habitats from Honduras
∗ Corresponding author at: Instituto de Biología Subtropical, – Universidad
Nacional de Misiones – Consejo Nacional de Investigaciones Cientíﬁcas y Técnicas
(CONICET), Bertoni 85, CP: 3370, Puerto Iguazú, Misiones, Argentina.
E-mail addresses: email@example.com (V.A. Quiroga), anoss@uﬂ.edu
(A.J. Noss), firstname.lastname@example.org (G.I. Boaglio), email@example.com
(M.S. Di Bitetti).
to northern Argentina (Miranda et al., 2014). Across much of its
range, the giant anteater is threatened primarily by poaching, habitat loss and fragmentation, ﬁre, and vehicle collisions (Cáceres et al.,
2010; Lacerda et al., 2009; Noss et al., 2008; Merritt, 2008). Overall, the species is particularly threatened where human activities
are relatively intense (Lacerda et al., 2009). Within Argentina its
range has decreased by approximately 45% in the past 40 years,
and the species persists only in sub-tropical forests in the north
(Pérez Jimeno and Llarín Amaya, 2009; Superina et al., 2012). The
species is categorized as Vulnerable both in Argentina and across
its range (IUCN, 2014; Superina et al., 2012). However, very little
1616-5047/© 2016 Deutsche Gesellschaft für Säugetierkunde. Published by Elsevier GmbH. All rights reserved.
V.A. Quiroga et al. / Mammalian Biology 81 (2016) 274–280
Fig. 1. The 42 Neotropical locations considered in this study. For the three study locations in the Argentine Chaco, we included the minimum polygon convex (MPC) covered
by the camera trap survey in each location. (T&S = tropical and subtropical).
information exists on the population status of the giant anteater
across its range, or on what factors affect its distribution and abundance.
Large-bodied specialist-insectivores like M. tridactyla depend
on resources that are energetically poor and, for that reason, they
have a relatively low metabolism and require large areas for their
survival (Mourão and Medri, 2007; Zimbres et al., 2013). Giant
anteaters prefer environments presenting a mosaic of habitats,
because they generally use forest patches for shelter and rest, and
ﬁre-managed grasslands and/or shrub savannas for foraging and
daytime rest (Desbiez and Medri, 2010; Di Blanco et al., 2015;
Mourão and Medri, 2007; Prada and Marinho-Filho, 2004; Shaw
et al., 1987). Apparently they tolerate a certain degree of disturbance such as livestock and moderate ﬁres (Shaw et al., 1987).
However, they avoid areas with high levels of contact with humans,
cattle and other domestic animals, and they seem to require wellconserved forest patches (Shaw et al., 1987; Vynne et al., 2011;
Di Blanco et al., 2015). Their natural predators include the jaguar
(Panthera onca; Linnaeus, 1758) and, occasionally, the puma (Puma
concolor; Linnaeus, 1771) (De Oliveira, 2002; Silveira, 2004). Normally the giant anteater is not an important prey species for
jaguars (Cavalcanti and Gese, 2010; Crawshaw and Quigley, 2002),
except in some semi-arid environments, namely the Caatinga, the
Paraguayan Chaco and the Cerrado (Astete et al., 2008; De Oliveira,
2002; Mc Bride et al., 2010; Rodrigues et al., 2008; Silveira, 2004).
Our study is the ﬁrst attempt to assess the determinants of
giant anteater abundance across its range. This study is also the
ﬁrst systematic ﬁeld survey of giant anteaters in the Argentine
Chaco, where its population status is unknown. The Gran Chaco
is the second most extensive forest ecoregion in the Americas after
the Amazon, and is the largest sub-tropical dry forest in the world
(Morello and Adámoli, 1974; Morello et al., 2009). Currently several
of the Chaco’s mammal species are under threat from direct hunting
and from deforestation (Altrichter, 2006; Gasparri and Grau, 2009;
Quiroga et al., 2014). Compared to forests without hunting, the
density of mammal species may decrease by as much as 80% under
moderate hunting pressure, and as much as 93% where hunting
is intense (Redford, 1992). In the Argentine semi-arid Chaco, over
95% of rural ranch residents consume wildlife, mostly mammals
(Altrichter, 2006), resulting in the local extinction of some species
(e.g., peccaries, Altrichter and Boaglio, 2004). On the other hand,
the Argentine Chaco is one of the few areas where giant anteaters
coexisted for a long time with their principal predators, jaguars, but
where jaguars are virtually extinct today (Quiroga et al., 2014).
In this study we evaluate variation in giant anteater abundance
at two different spatial scales. At a regional scale, across three locations in the Argentine semi-arid Chaco, we use camera trap data and
occupancy models to study the effects of different levels of protection and human disturbance on photo-capture rates, detectability
and the proportion of the area used by giant anteaters. At a continental scale, we use data from 40 camera trap studies reporting
the frequency of records of giant anteaters to compare their relative abundance across different biomes, different levels of human
disturbance, and presence versus absence of their main predator,
The regional study was conducted in the Argentine semi-arid
Chaco, where median annual temperature is 24 ◦ C, but the climate
is markedly seasonal with annual precipitation of 400–800 mm
concentrated between December and April (Prohaska, 1959).
The region is characterized by extensive plains (average altitude of 160 m above sea level) of dry forests dominated by red
quebracho (Schinopsis lorentzii; Anacardiaceae), white quebracho
(Aspidosperma quebracho-blanco; Apocynaceae), palo santo (Bulnesia sarmientoi; Zygophyllaceae), and mistol (Ziziphus mistol;
Rhamnaceae). The dense shrub understory, from 1–10 m high,
V.A. Quiroga et al. / Mammalian Biology 81 (2016) 274–280
is dominated by Capparis retusa (Capparidaceae), Acacia praecox
(Fabaceae), Celtis pallida (Ulmaceae), Achatocarpus praecox (Achatocarpaceae) and Schinus polygamus (Anacardiaceae) (Tálamo and
Caziani, 2003). The area was colonized early in the 20th century by
non-indigenous ranchers, who settled in isolated ranches, displacing the aboriginal people. The natural characteristics of the region
support extensive cattle ranching combined with heavy hunting of
wildlife (Baxendali and Buzai, 2009). We compared three locations,
100–260 km apart from each other (Fig. 1), across a gradient of conditions related to protection status of the area, human population
density and degree of human disturbance.
Copo National Park (1180 km2 )
This site has the highest legal protection level, with four park
rangers (1 park ranger/295 km2 ) responsible for anti-poaching and
other activities within the park. Livestock from neighboring ranch
outposts enters the Park, but the livestock burden is relatively low
in comparison to the other sites (Quiroga, 2013).
The Aborigen Reserve (2500 km2 )
Although it is categorized as an indigenous Reserve, no indigenous people reside inside its boundaries. It is sparsely populated
(0.8 outposts/100 km2 ), and has an intermediate livestock burden
relative to the other two survey sites. The Reserve has no game
rangers and no anti-poaching activities (Quiroga, 2013).
El Cantor (1966 km2 )
This site is not legally protected, and has neither game rangers
nor anti-poaching activities. The local people hunt. The cattle stocking rate is the highest of the three sites and cattle have been
established the longest here. The density of ranches is also the
highest, at 1.3 outposts/100 km2 (Quiroga, 2013).
For the continental study we compiled data from 42 Neotropical
locations, from Honduras to northern Argentina (Fig. 1), covering three types of biome: tropical and subtropical moist broadleaf
forests; tropical and subtropical dry broadleaf forests; tropical
and subtropical grasslands-savannas and scrublands (Olson et al.,
2001). We also characterized the level of human disturbance and
assessed the presence or absence of jaguars for each site (Appendices A and C of Supplementary information).
Material and methods
Giant anteaters at a local scale: the Argentine Chaco
At the three Argentine locations, we collected camera trap data
in the context of a larger study on jaguar, puma and their prey in
the area (Quiroga et al., 2014). We undertook camera-trap surveys
over three consecutive years (2008–2010), during a three-month
period in the dry season each year. At each location we installed
24–35 camera-trap stations, separated by an average of 3000 m,
along footpaths, abandoned roads or active unpaved roads. We used
the camera-trap photographs to estimate the proportion of camera
trap stations where the species was recorded, and to generate a relative abundance index based on the average anteater records per
100 camera trap days (considering records to be independent if they
were separated by at least one hour). We used a Kruskal–Wallis
test to compare this relative abundance index across sites, and
a likelihood-ratio test to compare the proportion of camera trap
stations per site where the species was recorded.
We used occupancy models (PRESENCE version 4.4; Hines,
2006) to reveal which factors affect the proportion of sites used
( ), modeling the effects of these factors according to the species’
detection probability (p) (MacKenzie et al., 2006). Depending on
the detection probability, the models may suggest that additional
individuals are present even though they were not photographed,
and therefore actual occupancy is greater than observed occupancy
(MacKenzie et al., 2002). In our analyses
should be interpreted
as the proportion of sites used, because individual giant anteaters
probably entered and left the survey area during the study period
and because the camera stations are relatively close together
(compared to likely ranging behavior) and probably were not independent for giant anteaters. We ranked models by their Akaike
Information Criteria (AIC) weights. When one or more models had
AIC weights > 10% of the highest ranked model, we used model
averaging (Buckland et al., 1997; Burnham and Anderson, 2002;
MacKenzie et al., 2006).
We evaluated the effects of four variables on or p:
(1) The distance (in km) to the nearest active vehicle road (range
0–15 km; the value was 0 when the camera station was installed
on the active road itself). We expected that and p would vary
positively with this distance, because of road kills as well as the
hunting pressure concentrated along active roads. For this and
the next variable we applied one-tailed statistical tests because
our hypotheses were directional.
(2) The linear distance (in km, range 0.5–13.8) to the nearest ranch
outpost (main building). We expected this distance to be positively related to
and p, because the combined disturbance
effects of the ranch—human presence, cattle, goats, dogs, vegetation modiﬁcation—decrease with distance from the ranch
(3) The type of path/road (active vehicle road, abandoned road,
or footpath) where the camera-trap station was installed. We
predicted this variable would affect p because we expected
anteaters to use footpaths more than abandoned roads, and the
latter more than active roads.
(4) The three camera-trap survey locations (Copo National Park,
Aborigen Reserve, and El Cantor). We expected both and p to
be highest in Copo National Park, the best-protected location,
intermediate in the Aborigen Reserve, and lowest in El Cantor
where human pressures are the highest.
Giant anteaters at a continental scale: the Neotropics
Based on our experience and results in the Argentine Chaco
where jaguars are absent, we sought to evaluate the relationship between giant anteater abundance and human disturbance
across the Neotropics, considering jaguar presence/absence as
well as biome at this continental scale. We compiled cameratrap data from 40 studies conducted in areas within the giant
anteater’s range, spanning 42 locations and eight countries (Fig. 1
and Appendix A of Supplementary information). We applied Generalized Linear Models (GLM) in R (R Development Core team,
2012) to assess the relation between giant anteater abundance
(records/100 camera trap days) with the following three variables:
1) Degree of human disturbance: high, intermediate, or low. From
the study description or by consulting the researchers directly,
we assigned each site to one of these three categories, taking
into consideration levels of hunting, cattle ranching, extractive
activities like logging, human residents, and effective protection
(Appendix C of Supplementary information). This was perhaps
the most subjective and difﬁcult-to-measure variable, because
there are many anthropogenic factors that can affect giant
anteaters. Therefore, the inclusion of this variable in the analysis
is a ﬁrst approach to assess the effect that human disturbance
can have on the abundance of giant anteaters. We predicted
V.A. Quiroga et al. / Mammalian Biology 81 (2016) 274–280
Camera-trap survey effort and records of giant anteater at the three Argentine locations. a) % stations with giant anteater records; b) records/100 camera days ± SE.
No of stations
(km ± SD)
convex polygon (km2 )
Copo National Park
2.99 ± 0.32
3.04 ± 0.98
2.85 ± 0.65
that giant anteater abundance would be lowest where human
disturbance was highest.
2) Presence or absence of jaguars in the photo records. Most locations lack jaguar density data or occupancy estimation. No
correlation exists between the frequency of camera trap records
and jaguar population density (Maffei et al., 2012), therefore we
decided to use the presence or absence of jaguars instead of a relative abundance measure as a response variable. We evaluated
this variable when the presence of jaguars was assessed in the
same camera trap study estimating giant anteater abundance.
We predicted that giant anteaters would be more abundant
where jaguars were absent.
3) Biome: tropical and subtropical moist broadleaf forest; tropical
and subtropical dry broadleaf forest and tropical and subtropical grasslands, savannas and shrublands (Olson et al., 2001). We
predicted that giant anteaters would be more abundant in dry
forests than in moist ones.
We considered locations separated by at least 45 km to be independent, based on the maximum recorded home range size and
displacement of wild giant anteaters (Rodrigues et al., 2008). But we
also used the Moran’s I spatial autocorrelation analysis (Gittleman
and Kot, 1990) to test for lack of independence among sites. Ten
locations lacked jaguar data, but we were unable to conﬁrm that
jaguars are absent there. Therefore, we ﬁrst ran the models with all
42 sites but excluding the jaguar presence variable. We modeled
the data as a negative binomial function, using a logarithmic link
due to the over-dispersion of the data, and a polynomial relation
introduced in the GLM models as an offset term to control for the
uneven camera trap survey effort across locations.
Of the 32 locations which included jaguar presence data,
we excluded the single remaining location in the “grasslandssavannas” biome, and we ran the subsequent models with only the
remaining 31 locations and two biomes. In this analysis we evaluated the effect of jaguars and the interaction between biome and
jaguar presence, predicting that jaguar presence would affect giant
anteater abundance more strongly in dry biomes, where the species
more commonly preys on giant anteaters (Astete et al., 2008; Mc
Bride et al., 2010; Rodrigues et al., 2008). For this subset of data we
again ran the Moran’s I spatial autocorrelation analysis.
In both analyses using GLM we estimated the AIC parameters for
all models and ranked the models according to their AIC values. We
followed the same criteria used for occupancy models to conduct
model averaging (Buckland et al., 1997; Burnham and Anderson,
Giant anteaters in the Argentine Chaco
We found no statistically signiﬁcant differences in giant anteater
camera trap records among Argentine locations: neither the capture rate (records/100 camera trap days/station) (H = 4.5; p = 0.08)
nor the proportion of camera trap stations where the giant anteater
was recorded (G = 2.5, p = 0.29) varied signiﬁcantly among the three
surveyed locations (Table 1).
3.4 ± 1.0
1.2 ± 0.4
2.9 ± 0.6
Estimated parameter values in the model averaging of the four highest-ranked occupancy models, their standard errors and 95% conﬁdence intervals, at the Argentinean
Site use ( )
Distance to ranch
Distance to road
Location El Cantor
The best-ranked model was the one that included “location” as a
covariate that affected detectability (p). Three other models had an
AIC weight > 10% of the AIC weight of the top model. These models
include an effect of distance to ranches and distance to roads on
(Appendix B1 of Supplementary information). The averaging of
these four models indicates that none of the variables affected the
proportion of sites used ( ) by giant anteaters (zero fell within the
95% conﬁdence interval for each), and only the variable “location”
affected the detectability of giant anteaters (p) (Table 2). According
to the top-ranked model [ (.); p(location)], the detection probability for the species ranged (lower and upper 95% conﬁdence
intervals) from 8 to 24% in the Aborigen Reserve, 17–36% in Copo
National Park, and 26–44% in El Cantor. With no overlap in the conﬁdence intervals observed for the Aborigen Reserve and El Cantor,
we consider these two sites to differ signiﬁcantly. All the other variables include zero in the 95% conﬁdence interval, with respect to
both p and , thus their inﬂuence is not considered to be signiﬁcant. According to the highest-ranked model, the proportion of the
study area utilized by giant anteater varied (95% conﬁdence intervals) from 46 to 72% at the three locations (compared to a naïve
occupancy of 50%).
Giant anteaters at a continental scale: the Neotropics
Across the 42 locations the model averaging of the two highest ranked models suggests that the frequency of giant anteater
records is higher in dry broadleaf forests and grasslands than in
moist broadleaf forests, and three to four times higher at low and
intermediate human disturbance locations than at high disturbance
locations. However, Moran’s I for this data set indicates spatial autocorrelation for the abundance of giant anteater (observed value:
0.11; expected value: −0.02; sd: 0.04; p value: 0.002), and the
model results are therefore unreliable due to lack of independence of the study locations. When we include the variable “jaguar
presence”, the data set is reduced to 31 locations, but with no
spatial autocorrelation (Moran’s I analysis = observed value: 0.04;
expected value: −0.03; sd: 0.06; p value: 0.20). Our analysis therefore focuses on this subset of data.
The best-ranked model was the one that included jaguar
presence, biome and human disturbance as predictive variables (Appendix B2 of Supplementary information). The model
V.A. Quiroga et al. / Mammalian Biology 81 (2016) 274–280
Estimated parameter values in the model averaging of GLM, their standard errors
and 95% conﬁdence intervals (considering 31 locations at the continental scale).
Biome moist: jaguar presence
averaging indicates a strong relation between biome and giant
anteater records, with nearly 80% higher abundance in dry forests
as compared to moist forests (Table 3). The model also shows a negative relation with jaguar presence: giant anteater records are up
to 70% higher at locations where jaguars are absent. Finally, giant
anteater abundance at locations with intermediate and low disturbance is 6–13 times greater than those at high human disturbance
locations (excluding sites where giant anteaters were not recorded
at all). The interaction between biome and jaguar presence, though
present in the second-ranked model, was not important (the 95%
conﬁdence interval included zero) (Table 3).
In the semi-arid Chaco in Argentina, across the three locations surveyed, neither the legal protection status nor the degree
of human disturbance signiﬁcantly affects giant anteater abundance. Although anteaters may be accidentally killed by dogs
during hunting outings, local residents agree that anteaters are
rarely hunted intentionally and that their meat does not taste
good (Altrichter, 2006; Quiroga, personal observation). Although
the species’ detectability varied among the three locations, we
found no effect of any other variable either on p or . Studies
from the Paraguayan and Bolivian Chaco, Brazilian Pantanal and
Cerrado report that hunting, ﬁre and vehicle collisions are the principal threats to the species (Cáceres et al., 2010; Ferreira da Cunha
et al., 2010; Merritt, 2008; Silveira et al., 1999; Tarifa, 2009), with
strong giant anteater declines near human settlements (Lacerda
et al., 2009). However, we found only a weak tendency for giant
anteaters to avoid ranch outposts and active roads, and these factors did not strongly affect their abundance. Perhaps the differences
between our three locations, in degree of human disturbance, were
not as important for the giant anteater as for other species which
are indeed affected in the Argentine Chaco (Altrichter, 2006).
At the continental scale, the species is more frequently recorded
in dry forests (and possibly in grasslands-savannas) than in moist
forests. Dry biomes may provide more food for anteaters, accessible at ground level, compared to humid biomes where prey species
and biomass may be concentrated in the canopy. The giant anteater
generally beneﬁts from habitat heterogeneity (Desbiez and Medri,
2010; Prada and Marinho-Filho, 2004; Vynne et al., 2011), and
the vegetation structure of dry biomes may favor giant anteaters
by providing greater habitat heterogeneity as compared to more
humid biomes (Cardoso Da Silva and Bates, 2002). Some studies
even report giant anteater preference for areas with intermediate
levels of disturbance, because of the greater habitat heterogeneity
that results (Shaw et al., 1987). The same environmental patterns
of the Argentine Chaco are replicated in parts of the Paraguayan
Chaco and Bolivian Chiquitano dry forest, coinciding with the relatively high photo-capture rates for giant anteaters there (Arispe
et al., 2006; McBride, 2004).
Although a high level of disturbance correlates negatively with
giant anteater records, giant anteaters may also withstand and even
prefer some degree of habitat fragmentation, because this habitat heterogeneity may be associated with a higher availability of
food sources. For instance, leaf cutter ants (Atta spp.) are relatively
scarce in undisturbed Atlantic and Amazonian moist forests, but
increase in abundance with disturbance (Dohm et al., 2011; FarjiBrener, 2001; Jaffe and Vilela, 1989; Urbas et al., 2007; Vasconcelos
and Malcolm Cherrett, 1995). However, disturbance reduces abundance of another key prey category, termites, in the same forests
(Martius et al., 1996; Vasconcellos et al., 2010), and the potential
net beneﬁt/cost to giant anteaters remains unknown.
Another important factor with a strong inﬂuence on giant
anteater abundance across its distribution is the presence of
jaguars. In some areas the giant anteater is one of the jaguar’s principal prey species, particularly in habitats such as the Caatinga, the
Paraguayan Chaco and Cerrado in Brasil (Astete et al., 2008; De
Oliveira, 2002; Mc Bride et al., 2010; Silveira, 2004). Researchers
have hypothesized that high giant anteater abundance at some
locations in the Caatinga may result from low jaguar density
(Rodrigues et al., 2008). The relatively high photo capture rates
of anteaters in the Argentine Chaco—some of the highest rates
recorded anywhere, when compared to other Neotropical sites
(Appendix A of Supplementary information)—may result in part
from the absence or very low abundance of jaguars. At the three
locations surveyed, the level of human disturbance has not greatly
affected anteaters but has produced the ecological extinction of
jaguars (Quiroga et al., 2014). The convergence of these two
factors—a moderate level of disturbance with the decline of its principal predator—may have favored giant anteater populations (or at
least not negatively affected them). Similarly, across the species’
distribution, capture rates only decline where human disturbance
is high, perhaps because at intermediate disturbance levels, the
two effects—negative effect from the disturbance versus positive
effect from jaguar decline—cancel each other out. These results
suggest again that top predators exert an important top-down regulation of populations of the other species in the ecosystem (Ripple
et al., 2014). Although only correlational, this result is particularly
important because few (if any) previous studies provide empirical
evidence of a relationship between the presence of jaguars and the
population status of their prey.
Although a certain level of disturbance may not affect or may
even favor giant anteaters, the beneﬁt in regions like the Argentine Chaco or the Brazilian Cerrado may be transitory. Colleagues
working in the southern reaches of the Argentine Chaco report very
high human-induced mortality of giant anteaters (Ignacio Jiménez
Perez, personal communication). Higher human population density and the advancing agriculture-livestock frontier in these areas
imply a higher density of ranch outposts and roads, a higher abundance of dogs, and an increase in hunting, compared with the
locations we surveyed farther to the north, where hunting of giant
anteaters is still very rare. The same factors that have extirpated
jaguars in much of the region may in time eliminate giant anteaters
as well, if current trends continue (Lacerda et al., 2009; Vynne
et al., 2011; Zimbres et al., 2013). The giant anteaters that we surveyed in Argentina represent one of the largest populations in the
American Gran Chaco, thanks to a set of fortuitous factors that
make the region an optimal refuge for the species. Although relatively well-conserved dry forests remain, the region faces a strongly
advancing agriculture-livestock frontier from the south, east, and
west, threatening in particular those wildlife species with large territorial requirements (Altrichter and Boaglio, 2004; Quiroga et al.,
2014). Without the creation and effective management of sufﬁciently large strictly-protected areas, the giant anteaters in the
Argentine Chaco will surely decline as they have elsewhere in the
V.A. Quiroga et al. / Mammalian Biology 81 (2016) 274–280
We thank the volunteers who helped with ﬁeld work; the
Agency of Wildlife, Parks and Ecology, Chaco Province; the Ministry
of Production and Environment, Formosa Province; Copo National
Park, the National Parks Administration; the National University,
Córdoba and the National Wildlife Service. Financial and logistical
support was provided by CONICET-Argentina, Jaguar Conservation Program-WCS, Rufford Small Grants Foundation, Cleveland
Metroparks Zoo and Cleveland Zoological Society, Mohamed bin
Zayed Species Conservation Fund, Idea Wild, Elé Project, Stephen
F. Austin State University, Yaguareté Project Misiones and Tapir
Project Salta. We thank Pablo Perovic, Adrián Díaz, Daniel Scognamillo, Agustín Paviolo, Yamil Di Blanco, Paula Cruz, Carlos De
Angelo and Ignacio Jimenez for their support and advice at different
stages of this project. We particularly thank Luis Lucifora, Walter
Svagelj, Ilaria Agostini, Mariano Giombini and Mariela Martinez for
their collaboration on the data analysis with GLM.
Appendix A. Supplementary data
Supplementary data associated with this article can be found, in
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