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Less than six generations to save the chacoan peccary


Abstract and Figures

The Dry Chaco has one of the highest deforestation rates of the world. The chacoan peccary (Catagonus wagneri; ChP) is endemic to the forests of this region and faces a high risk of extinction. However, we lack sufficient information about this species to develop effective conservation actions. This is the first study to determine the relevance of primary and secondary forest as habitat for the species and to address opportunities for conservation. We used occupancy modelling to study habitat selection. Using additional information on the species and the region, we then estimated the time left before the ChP’s habitat outside of protected areas is completely lost, and the number of ChP generations likely to exist before this happens. Finally, we identified protected areas that can sustain viable populations, and estimated the number of individuals that can survive within them. We found that the ChP occupies both primary forests and secondary forests. Also, that if deforestation rates remain consistent, the habitat for the ChP outside protected areas will have disappeared before 2051 (< 6 peccary generations). Furthermore, we found that most protected areas are too small and isolated to sustain viable populations. Our results have great management implications. Well-managed forests may allow the conservation of the ChP. Initiatives focused on forest conservation should increase, alongside the restoration of degraded and deforested areas. We also recommend the creation of new protected areas and wildlife corridors, and working horizontally with local communities.
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Biodiversity and Conservation
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Less thansix generations tosavethechacoan peccary
MicaelaCamino1,2 · JereyThompson3,4· PabloArriagaVelasco‑Aceves1·
SebastiánCirignoli5· RiccardoTiddi1· SaraCortez1· SilviaD.Matteucci6·
Received: 28 October 2020 / Revised: 10 November 2021 / Accepted: 15 November 2021
© The Author(s), under exclusive licence to Springer Nature B.V. 2021
The Dry Chaco has one of the highest deforestation rates of the world. The chacoan pec-
cary (Catagonus wagneri; ChP) is endemic to the forests of this region and faces a high
risk of extinction. However, we lack sufficient information about this species to develop
effective conservation actions. This is the first study to determine the relevance of primary
and secondary forest as habitat for the species and to address opportunities for conserva-
tion. We used occupancy modelling to study habitat selection. Using additional informa-
tion on the species and the region, we then estimated the time left before the ChP’s habitat
outside of protected areas is completely lost, and the number of ChP generations likely to
exist before this happens. Finally, we identified protected areas that can sustain viable pop-
ulations, and estimated the number of individuals that can survive within them. We found
that the ChP occupies both primary forests and secondary forests. Also, that if deforesta-
tion rates remain consistent, the habitat for the ChP outside protected areas will have disap-
peared before 2051 (< 6 peccary generations). Furthermore, we found that most protected
areas are too small and isolated to sustain viable populations. Our results have great man-
agement implications. Well-managed forests may allow the conservation of the ChP. Initia-
tives focused on forest conservation should increase, alongside the restoration of degraded
and deforested areas. We also recommend the creation of new protected areas and wildlife
corridors, and working horizontally with local communities.
Keywords Conservation· Habitat selection· Deforestation· Habitat loss· Extinction·
Catagonus wagneri
Communicated by Dirk Sven Schmeller.
* Micaela Camino;
Extended author information available on the last page of the article
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Most wildlife species are rapidly disappearing across the globe as a consequence of human
activities (Ceballos etal. 2015; Chase etal. 2020; Díaz etal. 2019). The main driver of this
decline is habitat loss, which occurs predominantly at the frontier of industrial-agricultural
and urban expansion (Díaz etal. 2019; Foley etal. 2005). Large terrestrial mammals are
particularly threatened by habitat loss, because of their usually low reproductive rates, low
densities, and large spatial requirements (Ceballos etal. 2015). Furthermore, large terres-
trial mammals are often under pressure from hunting, which has direct negative effects on
wildlife populations and interacts synergistically with habitat loss (Romero-Muñoz etal.
2020). Among large terrestrial mammals, the most threatened species are typically habitat
specialists and endemic species (Ceballos etal. 2015).
One of the regions of the world with the highest rate of human-driven loss of natural
ecosystems is the Dry Chaco (Hansen etal. 2013; Kuemmerle etal. 2017; Vallejos etal.
2015). Deforestation in the region is particularly high and as in many other regions, it is
the consequence of large-scale industrial agriculture for commodity production, principally
soybean and beef (Curtis etal. 2018; De Sy etal. 2015; Fehlenberg etal. 2017). As a result,
a large number of species in the Dry Chaco are losing their habitats and disappearing from
the region (Periago etal. 2015). Even species that tolerate some degree of habitat loss and
degradation seem to be threatened by landscape transformation in the region, and rarely
survive in these large-scale industrial agricultural systems (e.g. Dicotyles tajacu, Semper-
Pascual etal. 2019). Furthermore, protected areas seem insufficient to conserve large mam-
mals as these have poor representation of terrestrial vertebrates (Nori etal. 2016), are dis-
connected from each other (De la Sancha etal. 2021; Matteucci and Camino 2012), and
hunting and deforestation may occur within their boundaries (De la Sancha etal. 2021,
Saldivar-Bellassai etal. 2021). The Dry Chaco may be undergoing a defaunation process
whereby most wildlife species are rapidly disappearing, and we do not know how long
diversity can last (Periago etal. 2015; Romero-Muñoz etal. 2020).
For most species in the Dry Chaco, information and conservation attention is scarce
(Camino etal. 2020; Periago etal. 2015; Nori etal. 2016; Saldivar-Bellassai etal. 2021).
Such is the case of the chacoan peccary (Catagonus wagneri), that is endemic to the Dry
Chaco (over 90% of its habitat occurs in the region; Altrichter etal. 2016; Ferraz etal.
2016). The chacoan peccary (ChP hereafter) is a habitat specialist that only occupies areas
with high forest-cover (Altrichter and Boaglio 2004; Ferraz etal. 2016; Taber etal. 1993;
Torres etal. 2018), and it has not been detected in landscapes dominated by industrial agri-
culture (Ferraz etal. 2016; Núñez-Regueiro etal. 2015). Habitat loss is, therefore, the main
threat to the species (Altrichter etal. 2015, 2016; Camino and Torres 2019) and its popula-
tions are also negatively affected by high hunting pressure (Altrichter 2005; Camino etal.
2018; Romero-Muñoz etal. 2020; Saldivar-Bellassai etal. 2021). There are other threats
to the species, for example competition with introduced species, such as feral pigs (Sus
scrofa), diseases, or attacks by dogs, among others (Camino and Torres 2019). The three
extanct peccary species (the ChP, the white-lipped peccary Tayassu pecari and the collared
peccary D. tajacu) inhabit the Dry Chaco, and the ChP is the most threatened one, it is
classified as endangered at international and national scales (Altrichter etal. 2015; Camino
and Torres 2019; Cartes etal. 2017; Wallace etal. 2010).
We know that the ChP needs forests to survive but we have little understanding of its
habitat requirements. For example, we do not know which type or types of forests this
species selects and occupies. Thus, while some authors suggest that the ChP is dependent
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on old-growth, well-preserved, primary forest (Altrichter and Boaglio 2004; Taber etal.
1993), recent studies show that the species may use both primary and secondary forests
(Ferraz etal. 2016; Torres etal. 2018). Additionally, we lack information on how other
vegetation types, such as grasslands or bushlands (Morello etal. 2012), affect the habitat
selection of the ChP (Saldivar-Bellassai etal. 2021). This lack of information about the
habitat selection of the ChP makes it difficult to design and implement effective conserva-
tion actions (Altrichter etal. 2016). We do not know how long the ChP can survive under
current trends of natural ecosystem-loss, and protected areas may not be enough to con-
serve the species in the long-term.
In this study, our aim was to contribute to the conservation of the ChP. Our first objec-
tive was to improve our understanding of the habitat requirements of this species. We
determined the importance of primary and secondary forest, and of other ecosystems such
as grasslands, as habitat for the species. Our second objective was to assess the urgency of
developing conservation actions for the ChP. We estimated how long the forests in areas
that are suitable for the species can last under current trends of deforestation. Then, we pre-
dicted the number of ChP generations that can live in that time-frame. Our third and final
objective was to evaluate the conservation opportunities for the species within protected
areas. For this, we identified protected areas that can sustain viable populations in the long-
term, and estimated the number of individuals that can survive within these areas.
Materials andmethods
Study area
To study habitat requirements of the ChP (objective 1), our study area was a portion of the
Dry Chaco that covers 54,000 km2 (Fig.1). This area is representative of the Dry Chaco,
including both tropical and sub-tropical zones with large areas of continuous natural eco-
systems. To address how long the habitat of the species can last under current deforesta-
tion rates, the number of generations that can live in that time-frame, and the conservation
opportunities for the species within protected areas (objectives 2 and 3), our study area was
the entire Dry Chaco region (Fig.1A).
The Dry Chaco covers 787,000 km2 of land across Argentina, Bolivia and Paraguay,
with both arid and semi-arid conditions (Olson et al. 2001). Rain falls mainly between
October and May (550–800 mm) and rivers, ponds, and other water sources are scarce
(Morello etal. 2012). The vegetation is dominated by xerophytic deciduous and semide-
ciduous thorny forests of quebrachos (Schinopsis lorentzii and Aspidosperma quebracho-
blanco), that usually occur with other tree species, such as Ziziphus mistol (Morello etal.
2012). These quebracho dominated patches of forest alternate with forests patches domi-
nated by other species, e.g. Prosopis spp. (Morello etal. 2012). In the past, mature forest
canopy was greater than 20 m in height but at present, forests with this height are scarce
due to the long-established and intensive logging in the region (Cabrera 1976; Morello and
Saravia-Toledo 1959; Morello etal. 2012).
Most forests in the Dry Chaco where large trees remain have an average height of 12
m (henceforth primary forests), and forests that have lost their superior canopy stratum
have an average height of less than seven meters (henceforth secondary forests; Bonino and
Araujo 2005). Although most secondary forests are the result of intensive logging com-
bined with ranching, some of them may be natural in the region (Kunst etal. 2015; Morello
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and Saravia-Toledo 1959; Morello etal. 2005). Primary and secondary forests may share
species but they differ in their composition and diversity (López de Casenave etal. 1995;
Tálamo and Caziani 2003). In secondary forests, there is more sunlight, which favours
woody encroachment and a denser lower stratum (Morello and Saravia-Toledo 1959; López
de Casenave etal. 1995; Tálamo and Caziani 2003). These lower secondary forests have a
higher diversity of seedlings, fruits and seeds (López de Casenave etal. 1995; Tálamo and
Caziani 2003). The lower strata are characterised by shrubs and bushes, and the soil is
often covered by species of Bromelia and/or cacti (Morello etal. 2012). All forest patches
alternate with grasslands, wetlands, palm dominated areas, bushlands and areas dominated
by bare-soil where cacti may be present (Morello and Saravia-Toledo 1959; Cabrera 1976;
Morello etal. 2012).
The chacoan peccary
The chacoan peccary (ChP) is a species associated with the Dry Chaco forests and it is
not found in landscapes dominated by industrial agriculture (Altrichter and Boaglio 2004;
Núñez-Regueiro etal. 2015; Ferraz etal. 2016; Taber etal. 1993; Torres etal. 2018). It is
Fig. 1 Study areas. A The Dry Chaco region (grey), that covers portions of Argentina, Paraguay and
Bolivia. When focusing on habitat selection, our study area was a portion of the Argentine Dry Chaco (in
green). B Detail of the study area for the habitat selection analysis, that covered portions of Salta, Formosa
and Chaco provinces, in the Argentine Dry Chaco (in green). Orange points represent towns and small cit-
ies within the study area, violate lines are the main roads and in blue are the rivers
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adapted to the arid and semi-arid conditions of this region and can survive long periods
without surface water available (Sowls 1997). The ChP is omnivorous and its diet includes
cacti of different species, e.g. Opuntia spp. or Cleistocactus, bromelias, fruits, seedlings
and seeds, and it can even consume dead animals (Mayer and Brandt 1982; Taber etal.
1993). The species usually lives in groups with an average size of 4.5 individuals, although
there are reports of solitary individuals (Altrichter etal. 2016). Groups occupy fixed terri-
tories with an average home range of about 13 km2 and walk an average of 2 km/day within
these areas (Taber etal. 1993). Dispersal distances of a maximum of 4.6 km have been
recorded in the Paraguayan Chaco (Taber etal. 1993). The species can reproduce once a
year, its average litter-size in the wild is 1.7 (Altrichter etal. 2016; Taber etal. 1993), and
the generation time is estimated to be 5.26 years (Leus etal. 2016).
Habitat selection
Our objective was to evaluate the importance of primary and secondary forests as habitat
for the ChP. We also evaluated the effect of other vegetation types, such as grasslands, on
the habitat selection of this species. For this, we used single-season/single-species occu-
pancy modelling (MacKenzie etal. 2006). This method is based on maximum likelihood
and logistic regressions, and accounts for imperfect detection (SI 1.1; MacKenzie etal.
We designed our study based on the ecology of the ChP and on occupancy modelling
requirements (SI1.1). We divided the study area (Fig.1B) into square units of 6 × 6 km, and
we randomly selected non-adjacent units to survey (N = 93, Fig. SI1.2). With this design,
we minimised the probability of changes in occupancy status of the units during the sam-
pling period (SI1.1) while accounting for independence (SI1.1 and SI1.2; MacKenzie etal.
2006). Additionally, we used survey methods that reduce the probability of false-positives,
which is another requirement when using these occupancy models (SI1.1; MacKenzie etal.
2006). Our survey methods were camera-traps, locally-based monitoring, and/or interviews
with local hunters. Camino etal. (2020) evaluated these methods and demonstrated that
the chance of false-positives is very low. For each sampling occasion, we chose the sur-
vey method based on logistic restrictions (SI1.2; Camino etal. 2020). We describe survey
methods in detail in Supplementary Information (SI1.2; also see Camino etal. 2017, 2020).
The first step in occupancy modelling is to estimate the probability of detecting the focal
species (SI1.1, MacKenzie etal. 2006). Then, this method incorporates detection prob-
ability estimations into occupancy estimations to account for imperfect detection (SI1.1,
MacKenzie etal. 2006). Detection probability estimations are not the focus of our study,
we present the procedure, the covariates included in detection probability estimations, the
complete list of models and underlying hypotheses, and the correlation analysis between
covariates (Spearman’s rank correlation coefficient r > │0.4│), and the results of detection
probability models in Supplementary Information (SI1.2–SI1.5).
To test our hypotheses of habitat selection (SI1.6), we used occupancy modelling and
included as covariates: (i) the proportion of the sample unit covered with primary forest,
(ii) with secondary forest, (iii) with grasslands, (iv) with bushlands, and/or (v) with bare-
soil. Occupancy modelling requires that we model all heterogeneity in the landscape (SI
1.1; MacKenzie etal. 2006). Thus, we included as a covariate (vi) the distance to near-
est river; considering that riparian vegetation and soil structure differs from those of other
areas, and also, because there are more cattle near the rivers, further altering vegetation
characteristics (Cabrera 1976; Trigo etal. 2017). As the ChP is negatively affected by
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human presence (Altrichter 2005; Altrichter etal. 2016; Camino and Torres 2019; Taber
etal. 1993), we also included as covariates (vi) the Euclidian distance of the centre of the
unit to the nearest town or city, and (vii) to the nearest road; and (viii) the density of trails
and dirt-roads within sampling units. We also considered that the species may show time-
delayed responses to landscape transformation of between 10 and 25 years, as suggested by
Semper-Pascual etal. (2019). Accordingly, we measured the variables vi–viii for the years
1984/1985, 1994/1995, 2004/2005, and 2010, and included them as covariates (SI1.6).
We developed a land-cover map of the study area from satellite imagery which we
ground-truthed using a vegetation survey (details given in Camino etal. 2020). Our map
differentiated primary and secondary forests, natural grasslands, bushlands, deforested
areas and exotic pastures or crops (Camino etal. 2020). We also used satellite images to
digitalize locations of cities and towns, roads and rivers (Fig.1B; Camino etal. 2020). We
used ArcGIS 10.1 tools to digitalize features and calculate explanatory variables.
Before running the models, we did a correlation analysis between covariates (Spear-
man’s rank correlation coefficient r > │0.4│) and when two or more covariates were cor-
related, we excluded from our analysis the one that we considered of least ecological rele-
vance (correlation analysis results in SI1.4 & SI1.7). Then, we ran the models and selected
the model or group of models that best explained our data. We used the Akaike Informa-
tion Criterion corrected for small sample size and corrected by the overdispersion factor
(QAICc; Burnham and Anderson 2002). We considered that the models with explanatory
power were those within 2 QAICc values of the highest-ranking model (Arnold 2010;
Burnham and Anderson 2002). We estimated the overdispersion factor (c-hat) based upon
the global model (MacKenzie and Bailey 2004). Of the top model ranking model set we
eliminated models that included uninformative parameters determined by the 85% confi-
dence interval of the parameter estimate including zero (Arnold 2010). A variable had a
significant effect on our estimators when the 95% confidence interval of its coefficient in
the logistic regression average model did not include zero (Arnold 2010; MacKenzie etal.
To create, test and select models of occupancy accounting for imperfect detection, we
used the R-freeware with the packages unmarked, AICcmodavg and MuMIn (Fiske and
Chandler 2011; Bartoń 2015; Mazerolle 2015).
Habitat loss andsurvival oftheChP outsideprotected areas
To estimate the time that forests within the habitat of the species can last, and how many
generations are left before the species disappears outside protected areas, we assumed that
Fig. 2 Steps we followed for objectives 2 and 3 of this study. A Binary map that represents suitable/unsuit-
able habitat for Catagonus wagneri in the Wet and Dry Chaco regions prior to 2015 (Altrichter etal. 2016;
Ferraz etal. 2016). This map was developed by IUCN/SSC C. wagneri specialists using maximum entropy
algorithm, 177 confirmed presence records from the years 2000–2015, and six environmental variables.
Variables with explanatory power included isothermality, elevation, and land-cover. Areas were differen-
tiated as high, medium, low and no suitability for the species, and then classified as unsuitable/suitable
habitat of 1 km2 resolution. B Binary map that represents suitable/unsuitable habitat for the species in Dry
Chaco prior to 2015. C Binary map that represents suitable/unsuitable habitat for the species in Dry Chaco
in 2019 but does not consider the specie’s spatial requirements to survive, i.e. it still retains habitat patches
that are too small and/or isolated to conserve a herd of chacoan peccaries. D Binary map that represents
suitable/unsuitable habitat for C. wagneri in Dry Chaco in 2019. E Forest-cover in the Dry Chaco in 2019.
F Forest-cover and Protected Areas in the Dry Chaco in 2019. In blue are the values and estimations we
obtained or measured in these steps
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the rate of natural ecosystem-loss will remain constant, that deforestation in the Dry Chaco
follows a contagion pattern (Piquer-Rodríguez etal. 2018; Volante etal. 2016), and that
there is no loss of natural ecosystem-cover within protected areas that have strict biodiver-
sity conservation purposes (areas in categories I–IV of IUCN, National Parks, Provincial
Parks, and/or National Monuments). Additionally, we focused on habitat loss and did not
account for habitat degradation, effects of hunting, edge effects or demographic stochastic-
ity (Chase etal. 2020). Hence, our results represent the best-case scenario for the conserva-
tion of the ChP outside protected areas.
Our first step was to identify the areas with suitable habitat for the ChP in the Dry
Chaco, in June 2019 (Fig.2A–D). For this, we adapted an existing binary map of suit-
able/unsuitable habitat for the species before 2015 (A in Fig.2, Altrichter etal. 2016; Fer-
raz etal. 2016). ChP specialists developed this map using maximum entropy algorithm,
177 presence records and six environmental variables (elevation, land-cover, annual mean
temperature, mean diurnal range, isothermality, annual precipitation; Altrichter etal. 2016;
Ferraz etal. 2016). By adapting the binary map, we obtained a tool to identify all areas
with suitable habitat, irrespective of habitat quality. We used this information later to esti-
mate the time that habitat can last under current deforestation rates, as we explain in the
following paragraphs (Fig.2).
The initial adjustment we made to the binary map was changing its extension to cover
the Dry Chaco (originally, it also covered the Humid Chaco region; Fig.2A, B). For this,
we used a layer of the Dry Chaco created by WWF (available at www. monit oreod esmon
te. com. ar). Then, we identified the areas that were suitable for the species in the origi-
nal binary map but had subsequently lost their natural ecosystems and thus, their vegeta-
tion-cover (Fig.2B, C). We created a layer with the areas that lost their vegetation-cover
(transformed areas hereafter) by merging the layers created by REDAF, FAUBA, LARS &
INTA (available at, for the period 1976–2012) and by Guyrá
Paraguay (available at http:// www. guyra. org. py for the period 2013–2018). Guyrá mapped
deforestation while we also focused on the loss of other ecosystems. For this reason, and
also because deforestation continued after 2018, we found transformed areas that did not
appear in the merged layer. We digitalized these transformed areas using satellite images
(Landsat 8, bands 6, 5 & 3; 1:500.000 scale), and incorporated these areas to the trans-
formed areas-layer.
The loss of natural ecosystems was mainly due to advance of industrial agriculture
(Vallejos etal. 2015). Because the ChP does not occupy areas dominated by industrial agri-
culture (Altrichter and Boaglio 2004; Núñez-Regueiro etal. 2015; Ferraz etal. 2016; Taber
etal. 1993; Torres etal. 2018), we changed the category of transformed areas from suitable
to unsuitable (Fig.2). Subsequently, we eliminated all habitat patches that remained too
small and isolated to sustain a group of ChPs (Fig.2C, D). This is, habitat patches that cov-
ered less than the average home range of the species (13.02 km2; Taber etal. 1993) and that
were also separated from other habitat patches by distances greater than what individuals
walk under normal circumstances (Euclidian distance between patches larger than 5 km;
Taber etal. 1993). From the resulting map, we estimated the area covered with suitable
habitat, the area transformed into industrial agriculture, and the percentages these areas
represent for the Dry Chaco region (Fig.2).
Following map adaptation, we estimated the number of years that the identified suitable
habitat would remain if current deforestation trends continue. We focused on deforesta-
tion because deforestation rates in this region are among the highest of the world (Kue-
mmerle etal. 2017), and the ChP does not occupy territories with reduced or no forest-
cover (Altrichter and Boaglio 2004; Taber etal. 1993). Thus, if forests disappear from a
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suitable area, then this area will become unsuitable even if other natural ecosystems remain
(Altrichter and Boaglio 2004; Taber etal. 1993). Based on the results of the first section of
this study (sections ‘Habitat selection’ and ‘Habitat selection’), we did not differentiate for-
ests by height or by their distance to the rivers—because we found that this peccary selects
both high and low forests, and does not seem to select forests based on their distance to the
rivers. Thus, we used information from the first section of our study, measures of forest-
cover and estimations of deforestation rates to estimate the number of years habitat will
remain under current deforestation rates.
We measured forest-cover in suitable and unsuitable areas of the Dry Chaco. For this,
we first uploaded a layer of the Dry Chaco region in Keyhole Markup Language (kml)
to www. globa lfore stwat ch. org with setup in land cover-tree cover, canopy density > 30%
(threshold of recent studies, e.g. De la Sancha etal. 2021). We obtained a raster represent-
ing forest-cover in the region in 2019, transformed it to vector format and overlapped it
with our suitable/unsuitable binary map (Fig.2). As we assumed no deforestation in pro-
tected areas of strict conservation, we masked these areas, i.e. clipped protected areas out
of the forest-cover layer (using a layer from WDPA; UNEP-WCMC, IUCN 2020) (Fig.2).
Then, we measured forest-cover in suitable and unsuitable portions of the Dry Chaco that
occur outside protected areas (Fig.2).
To calculate the number of years that forests will last within the habitat of the ChP out-
side protected areas, we used Eq.1 (Fig.2). We downloaded the average annual deforesta-
tion rates for the Dry Chaco limits from global forest watch (z in Eq.1).
where (j) is the number of years that forest-cover will remain in suitable areas of the Dry
Chaco; (x) is the area covered with forest within suitable habitat; (a) is the area covered
with forest in protected areas of suitable habitat; (y) is the area covered with forest in the
portions of the Dry Chaco that are unsuitable for the ChP; (z) is the average annual defor-
estation rate of the last decade in the Dry Chaco.
We were able to use this method without spatially explicit modelling because defor-
estation in the Dry Chaco follows a contagion pattern, which means that areas surrounding
industrial agriculture have higher probability of losing their natural vegetation-cover com-
pared to other areas (Piquer-Rodríguez etal. 2018, Volante etal. 2016).
Finally, we estimated the number of generations that the ChP can survive outside pro-
tected areas under current deforestation rates. For this, we divided the number of years that
forest-cover will last within environmentally suitable habitat (j in Eq.1) by the generation
time of the species (5.26 years; Leus etal. 2016).
Conservation oftheChP inprotected areas
First, we identified the protected areas that had suitable habitat for the ChP and those that
are functionally connected (Fig.2). We considered that two or more protected areas were
connected when the Euclidian distance between them was equal or less than the maxi-
mum distance travelled by individuals under normal circumstances (less than 5 km, Taber
etal. 1993). We labelled each connected pair or group of protected areas a ‘conservation
nucleus’, and differentiated them from disconnected, isolated, protected areas (Fig.2). We
then measured the area covered with suitable habitat and with forest in each conservation
nucleus and isolated protected area (Fig.2).
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Second, we estimated the number of individuals that each conservation nucleus and iso-
lated protected area can sustain. To do that, we multiplied the area covered with suitable
habitat in each conservation nucleus and isolated protected area by the average density of
the species. We used 0.3 individuals/km2 as average density based on estimations for the
Argentinean (0.16 individuals/km2, Altrichter 2005) and Paraguayan Chaco (0.43 individu-
als/km2, Taber etal. 1993). We also calculated the number of groups that these individuals
represent by dividing the number of individuals by the average group size (4.5 individuals;
Altrichter etal. 2016).
Third, we identified protected areas and conservation nuclei that can sustain ChP popu-
lations in the long-term. We defined long-term as populations that can keep a 98% gene
diversity and a zero probability of extinction for the next 100 years (Leus etal. 2016). For
the ChP, 1300 is the minimum number of individuals required to sustain viable populations
in the long-term (Leus etal. 2016). ChP specialists estimated 1300 as the minimum viable
population size using population viability analysis—particularly Monte Carlo simulations
and Vortex (www. vorte x10. org)—(Altrichter et al. 2016; Leus et al. 2016). We
assumed no human-caused threats in protected areas and conservation nuclei—otherwise
the minimum viable population size would not be 1300 (Leus etal. 2016).
Fourth, we determined the total number of individuals and groups that can survive in
the long-term in protected areas and conservation nuclei. For this, we summed the num-
ber of individuals that can live in each of these areas and nuclei (estimated in the second
step of this process). This sum is the number of individuals that can be conserved in pro-
tected areas in the long-term if surrounding forests disappear. As in step two, we estimated
the number of groups these individuals represent by dividing the total number by average
group size (4.5 individuals; Altirchter etal. 2016).
For all our analysis, we used tools from QGIS 3.4, ArcGIS 10.3, Matrix Green and pro-
jections WGS84/UTM 20 S. We had three main sources of information with different spa-
tial resolution: Landsat images (30–60 m), the forest-cover layer from Global Forest Watch
(479 m) and the binary map of suitable habitat for the ChP (1000 m). We chose to work at
the lowest spatial resolution (1000 m), so for all the forest-cover area calculations we did
not consider polygons smaller than 1 km2 (Supplementary Information SI2.1).
Habitat selection
Occupancy models with high explanatory power included both secondary and primary
forest as covariates, as well as the distance of the unit to the nearest road in the 1980’s
(Table1). However, only the availability of primary and secondary forest in the sampling
unit showed significant effects on occupancy probability (Table2, Fig.3).
Habitat loss andsurvival oftheChP
In June 2019, suitable habitat for the ChP covered 364,003 km2 (Fig.4A, and Supplementary
Information Table SI2.2). Seventy-seven percent of the suitable habitat of the species was cov-
ered by forests (both primary and secondary forests, 280,901 km2; Fig.4B and Supplementary
Information Table SI2.3), and 79% of these forests occurred outside protected areas (221,001
km2, Fig.4B, Supplementary Information SI2.2 and SI2.3). Under current deforestation rates
Biodiversity and Conservation
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(8800 km2/year, Table SI2.2), the habitat of the ChP outside protected areas will have disap-
peared by 2051, or 32 years after June 2019 (Supplementary Information Equation S2.1 and
Table SI2.2). Six generations of ChP could persist within this time-frame.
Conservation oftheChP inprotected areas
Of the forests of the Dry Chaco that remained in June 2019, only 21% occurred within pro-
tected areas that prohibit natural resources extraction (59,900 km2, Fig.3B, Supplementary
Information Tables SI2.2–2.4). In Northern Paraguay and Bolivia, there is a group of pro-
tected areas that are functionally connected, and can sustain viable populations of chacoan
peccaries in the long-term (Fig.4B, Supplementary Information Tables SI2.3 and SI2.4). This
is a conservation nucleus of 47,633 km2 that can sustain 14,290 ChP individuals, and approxi-
mately 3175 groups (Supplementary Information SI2.4). This conservation nucleus represents
1.3% of the suitable habitat available for the ChP in 2019 (Supplementary Information Tables
SI2.3 and SI2.4). The rest of the protected areas in the Dry Chaco are too small and/or lack the
connectivity needed to sustain viable populations if surrounding, unprotected habitat disap-
pears (Fig.4; Supplementary Information SI2.3 and 2.4).
Table 1 Occupancy models for the chacoan peccary (Catagonus wagneri), ranked by their Akaike Informa-
tion Criteria corrected by model weights (QAIC)
We only present models with high explanatory power (deltaQAICc lower than 2). c-hat = 1.87. In all cases,
detection probability (p) was incorporated in the models (detection probability models in Supplementary
Information 1). Primary Forest: area of the sample unit covered with forests of media height of > 7 m; Sec-
ondary Forest: area of the sample unit covered with forests of media height 7 m; dis_road 80: Euclidean
distance of the centre of the sample unit to the nearest road in the 1980’s
Models with substantial weight K QAICc Delta_QAICc QAICcWt
Ψ(Primary_Forest, Secondary_Forest) 5 172.87 0 0.14
Ψ(Secondary_Forest) 4 173.6 0.73 0.1
Ψ(Primary_Forest, Secondary_Forest, dis_road80) 6 174.8 1.93 0.06
Table 2 Parameters included
in the average occupancy
model of the chacoan peccary
(Catagonus wagneri), and their
beta estimates in the logistic
(*) Significant effect of the variable on the occupancy probability
Estimate SE 95% Confidence
Inferior Superior
Secondary Forest 0.70 0.54 0.30 1.73 *
Primary forest 0.28 0.34 0.04 1.12 *
Dis_Road80 − 0.02 0.05 − 0.66 0.32
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Fig. 3 Probability of a sample unit being occupied (occupancy; Ψ) by the chacoan peccary (Catagonus
wagneri) vs the proportion of the sample unit covered by (A) primary and (B) secondary forest
Biodiversity and Conservation
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Habitat selection
Our study shows that besides occupying primary forests, the ChP can use secondary for-
ests. This result has great management implications as it shows that human use of the forest
does not necessarily lead to the disappearance of the ChP. Contrary to what happens when
natural ecosystems are completely transformed to human-dominated agricultural systems,
well-managed forests may be favourable for the conservation of the ChP. Thus, initiatives
focused on the conservation of primary, well-preserved forests should continue, increase
and combine with the restoration of degraded and deforested areas. Additionally, working
with local communities and producers to promote the sustainable use of forests can be an
effective conservation strategy for the ChP. Also, working on ecological restoration with
local communities can be highly effective (Erbaugh etal. 2020).
Previous studies suggested both that the ChP mainly selects primary forests (Altrichter
and Boaglio 2004; Taber etal. 1993; Torres etal. 2018) and that the species may also use
and select secondary forests (Ferraz etal. 2016; Torres etal. 2018). Our study is the first to
highlight the importance of both primary and secondary forests as the habitat for the ChP.
Yet, it is important to keep in mind that primary and secondary forests may have different
roles in the ecology and survival of the ChP. The species may use these habitats differently,
Fig. 4 In the Dry Chaco, in June 2019. A Suitable and unsuitable areas for the chacoan peccary (Catagonus
wagneri) and all protected areas (from WDPA 2019). B Forest-cover in suitable and unsuitable areas and
protected areas that are National Parks, Provincial Reserves, National Monuments and/or in IUCN catego-
ries I–IV—differentiating protected areas that are functionally connected for the species from isolated pro-
tected areas
Biodiversity and Conservation
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and the abundance and/or breeding success of the species may differ in each type of forest.
Finally, other forest characteristics may be relevant for the habitat selection of this species
besides forest-height, such as canopy density and abundance of ground cover vegetation,
among others.
Primary forests are well-preserved ecosystems (Morello and Saravia-Toledo 1959;
Morello etal. 2005) to which the ChP adapted throughout its evolution (Sowls 1997; Gas-
parini etal. 2013). Therefore, our results showing that the species selects primary forests
are not surprising. Additionally, our findings support previous research (Altrichter and
Boaglio 2004; Taber etal. 1993; Torres etal.2018). On the contrary, the selection of sec-
ondary forests by the ChP was less predictable. First, because previous evidence was not
conclusive (Altrichter and Boaglio 2004; Ferraz etal. 2016; Torres etal. 2018). Second,
because most secondary forests of the Dry Chaco are the result of human disturbances
(Kunst etal. 2015; Morello and Saravia-Toledo 1959; Morello etal. 2005) and habitat spe-
cialists, such as the ChP, may have more difficulty in adapting to use human-modified envi-
ronments (Brown 1984).
We suggest three hypotheses to explain why the ChP selects secondary forests in addi-
tion to primary forests. First, secondary, low-height, forests have high seedling, fruit and
seed diversity (López de Casenave etal. 1995; Tálamo and Caziani 2003), and the soil
is usually covered with cacti (Morello etal. 2012). These are important sources of food
for the ChP (Camino and Torres 2019). Consequently, secondary forests may have high
food diversity and availability for the species. Second, the ChP may also use these for-
ests to hide from predators or hunters given their usually dense understory (Morello and
Saravia-Toledo 1959; López de Casenave etal. 1995; Tálamo and Caziani 2003). A third
hypothesis is that the ChP’s selection of secondary forests could be a consequence of com-
petitive exclusion out of better habitats, such as primary forests (Hardin 1960; Johnson
and Bronstein 2019). The exclusion could be due to indirect or direct competition with the
other peccary species that also inhabit the Dry Chaco (Tayassu pecari and Pecari tajacu).
It could be also the result of competition with domestic livestock that roam freely in the
forests (Camino etal. 2018).
Habitat loss, survival andconservation opportunities oftheChP,
insideandoutsideprotected areas
According to our study, the ChP is highly threatened by habitat loss and fragmentation
in the Dry Chaco. Comparing our results to previous research (Ferraz et al. 2016), we
find that in the last decade the species lost one quarter of its habitat due to the advance of
industrial agriculture. Our results suggest that under current deforestation rates, the spe-
cies will have disappeared outside protected areas before the year 2051. In this time-frame,
only six generations of ChP can survive. Moreover, when focusing on protected areas, we
found that these are insufficient to conserve the species and that there is only one group of
protected areas that is large enough to sustain viable populations of ChP. Most protected
areas are too small and disconnected to sustain viable populations. Consequently, our study
shows that if deforestation continues at the current rates, in 30 years from now, chacoan
peccaries will exist only in one group of protected areas in Paraguay and Bolivia with an
area of 47,633 km2. This area covers 1.3% of the current suitable habitat for the species.
This means that by 2051, the species will likely have disappeared from at least 98.7% of its
distribution range.
Biodiversity and Conservation
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Our estimates represent the more optimistic scenario for the ChP under current trends
of deforestation and habitat loss. First, because we assumed no human-driven threats to
the ChP within protected areas and this may not be completely true. Our maps show that
deforestation may reach these areas despite the ban on natural resource extraction, e.g. Tin-
funque in Paraguay (category II according to IUCN; Fig.3; UNEP-WCMC, IUCN 2020).
Additionally, there may be hunting within protected areas, as described by Saldivar-Bel-
lassai etal. (2021) for the Defensores de Chaco National Park (IUCN category II; UNEP-
WCMC, IUCN 2020). According to our results, Defensores del Chaco is part of the only
conservation nucleus with chances of conserving the species in the long-term. Yet, this
result is true only if we assume no hunting within these protected areas.
Second, outside protected areas we focused on habitat loss and did not consider the
impacts of hunting. However, hunting pressure on this species is high outside protected
areas (Altrichter and Boaglio 2004; Camino etal. 2018; Cuéllar and Noss 2014; Saldivar-
Bellassai etal. 2021) and negatively impacts populations (Leus etal. 2016; Taber etal.
1993). Furthermore, deforestation increases forest-edges and access-points to the forest
and thus, hunting and habitat loss have synergistic negative effects for the conservation of
the ChP (Romero-Muñoz etal. 2020). Third, we did not account for the fact that smaller
habitat patches may have decreased dispersal rate, demographic stochasticity, edge effects,
among others (Chase etal. 2020). Thus, habitat fragments probably contain fewer individu-
als than what we would expect from density estimations (Chase etal. 2020).
Our results confirm that the ChP is threatened with extinction, as categorised by IUCN
(EN, Altrichter etal. 2015). Even with an overestimation of the time and number of gen-
erations left before the species disappears in the wild—except maybe from a group of pro-
tected areas, our results suggest that the time window for acting is small. Effective conser-
vation actions focused on this species and its habitat are urgent.
Final comments
The accelerated rates of deforestation and natural ecosystem loss of the Dry Chaco are
probably threatening many species besides the ChP. Based on our results, we consider
that it is highly probable that the Dry Chaco is undergoing a defaunation process, as sug-
gested by other authors (Periago etal. 2015). Our results on the ChP also support pre-
vious research showing that protected areas are insufficient to conserve wildlife species,
particularly large vertebrates, in the Dry Chaco (Matteucci and Camino 2012; Nori etal.
2016; Saura et al. 2019). The creation and implementation of new protected areas and
wildlife corridors could be an adequate conservation strategy for this and other species.
Also, ecological restoration and reforestation may be effective strategies for recovering lost
and degraded forests in the Dry Chaco (Basualdo etal. 2019) and thus, for conserving the
ChP. The design and implementation of protected areas, wildlife corridors, programmes of
ecological restoration and reforestation, and any conservation strategy, must consider that
a large proportion of the remaining natural ecosystems of the Dry Chaco are indigenous
lands (Garnett etal. 2018). Moreover, it is probable that small-scale farmers also have rel-
evant roles in the conservation of natural ecosystems of this region (Camino etal. 2016,
2018; Eriksson 2021).
As the natural ecosystems of the Dry Chaco are inhabited by indigenous and small-scale
farmers (Altrichter and Boaglio 2004; Camino etal. 2018), top-down conservation initia-
tives may not be optimal for the region (Erbaugh etal. 2020; Piquer-Rodríguez etal. 2018).
We recommend that scientists, decision-makers and other stakeholders work horizontally
Biodiversity and Conservation
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with local communities to design and implement initiatives. Horizontal work has been
shown to increase local legitimacy and thus, effectiveness of conservation initiatives both
in the short and long-term (Adger etal. 2005; Brondizio and Tourneau 2016; Mistry and
Berardi 2016). According to our results, the ChP can use well-managed forests and thus, all
conservation initiatives should contribute to strengthen local communities, fair commerce
and environmental justice in order to achieve inclusive sustainable management of natural
ecosystems. In addition, planning land use and setting limits to deforestation and advance-
ment of industrial agriculture, as well as creating forest management plans, is of uttermost
importance for the conservation of the ChP in particular, and biodiversity in general.
Supplementary Information The online version contains supplementary material available at https:// doi.
org/ 10. 1007/ s10531- 021- 02337-x.
Acknowledgements We thank financial support of the Rufford Foundation, the EDGE of Existence Pro-
gramme of the Zoological Society of London, the Agencia de Promoción de Ciencia y Técnica de la Argen-
tina and el Ministerio de Trabajo y Seguridad Social de la Nación. We thank local indigenous and criollo
people for their participation of this research, and the support of Red Agroforestal Chaco, Marisa Pizzi,
Horacio Córdoba, Ines Quilici, Hugo Hernando Correa and Ezequiel Pintos. We also thank the information
provided by Guyra Paraguay, Katia Ferraz and IUCN that although referenced, was extremely useful. We
thank Paul Barnes and Claudia Grey of the Zoological Society of London for their careful reading of our
manuscript, and their thoughtful and constructive comments and also, for revising our English. Finally, we
thank the anonymous reviewers that greatly contributed to improve our manuscript.
Authors’ contributions MC: Conceived the study, Designed the study; MC, PAV-A, RT, SC: Data gathering;
MC, JT, PAV-A, SC, RT: Data analysis; MC, SC, SC, SDM, MA: Interpretation of results; MC, PAV-A, SC:
Manuscript draft. All authors revised the manuscript carefully and critically, and approved this version to be
sent to this journal.
Funding Our sources of funding were the Rufford Foundation (Grant No. 1 & 2), the EDGE of Existence
Programme of the Zoological Society of London, the Agencia de Promoción de Ciencia y Técnica de la
Argentina (Grant No. 01000100101289), and el Ministerio de Trabajo y Seguridad Social de la Nación. The
authors of this manuscript have no direct financial benefits that could result from publication.
Data availability The data that support the findings of this study are available from the corresponding
author, upon reasonable request.
Code availability Not applicable.
Conflict of interest The authors declare that they have no actual or potential conflict of interest influencing
their research.
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Authors and Aliations
MicaelaCamino1,2 · JereyThompson3,4· PabloArriagaVelasco‑Aceves1·
SebastiánCirignoli5· RiccardoTiddi1· SaraCortez1· SilviaD.Matteucci6·
1 Proyecto Quimilero, CP1430BuenosAires, Argentina
2 EDGE ofExistence – Zoological Society ofLondon, London, UK
Biodiversity and Conservation
1 3
3 Guyra Paraguay, Asunción, Paraguay
4 Consejo Nacional de Ciencia y Tecnología (CONACYT), Dr. Justo Prieto N° 223 &,
Tte. 1º Teófilo del Puerto, Asunción, Paraguay
5 Centro de Investigaciones del Bosque Atlántico (CeIBA), PuertoIguazú, Misiones, Argentina
6 Consejo Nacional de Investigaciones Científicas y Técnicas, BuenosAires, Argentina
7 Environmental Studies Prescott College, Prescott, AZ, USA
Agricultural expansion is the primary cause of forest loss and fragmentation. It threatens the conservation of its biodiversity as well as the capability to provide ecosystem services. Land-use policies, such as zonation programs, have been traditionally used as a tool for promoting a sustainable natural resource management; however, we still lack standardized methodologies that can be applied world-widely to achieve this purpose. In the current context of rampant deforestation over the tropical forests, there is an urgent need of identifying policies that steer agricultural land-use change into a reduced pressure on forests. This study focuses on the outcomes of the first territorial planning law in the Province of Formosa (Argentina) located within the Chaco region, one of the world’s deforestation hotspots. The research questions were: a) How did agriculture expand in Formosa before, during and after the enactment of the territorial planning law? b) Did the introduction of the law affect the spatial distribution of land-use change?; and c) How did the sanction of the law affect forest loss and forest fragmentation? Landsat imagery was used to map land-use change, and to calculate the cover loss and cover loss rate considering the zoning and physiognomic classification of the law. The forest fragmentation was evaluated in terms of the forest loss spatial configuration, classified as perforation or shrinkage, forest edge generation, patch size distribution, and patch isolation. The territorial planning law effect over agricultural expansion was tested using a difference in difference model. After the law was passed, a reduced land-use pressure was observed for the forest within the conservation designated zone; however, the forest presented the highest cover loss rates among the physiognomic categories of the law. Land-use change within the conservation designated zone was predominantly made according to a perforation spatial configuration, which promoted the forest edge generation. Formosa is experiencing an early fragmentation process as the isolation between patches decreased and its size distribution changed towards a less large-patch-centered pattern. Overall, the territorial planning law in Formosa succeeded in the relief of land-use pressure on forest, but highlighted the need of incorporating spatial configuration guidelines for long-term forest conservation. The case of Formosa case could be useful in the design of future sustainable natural resource management policies and implies the importance of early natural resource planning.
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Context The Dry Chaco spans more than 87 million hectares across Argentina, Bolivia, and Paraguay. This unique forest system has experienced extensive loss and fragmentation due to land-use change, with different land-use histories in the three countries. This forest loss has altered landscape connectivity for the Dry Chaco’s associated biota. Objectives We compared patterns of deforestation-induced fragmentation and concomitant changes in structural landscape connectivity between 2000 and 2019 in the three countries to identify consistent patterns that might facilitate biome-wide conservation. Methods We quantified forest cover in the Dry Chaco of Argentina, Bolivia, and Paraguay for the years 2000 and 2019 at 30 m resolution. We analyzed structural connectivity at three scales. Then, we identified and visualized the most important stepping stones per country per year. Results Between 2000 and 2019, the overall extent of Dry Chaco forest cover decreased by 20.2% (9.5 million ha). All three counties experienced substantial reductions, with Paraguay undergoing the greatest loss and fragmentation relative to 2000. Most of the overall network metrics decreased from 2000 to 2019 for Paraguay and Bolivia, but Argentina experienced increased coalescence distance and average nodal connectance. Dispersal-level metrics showed clustering threshold distances between 1000 and 2000 m for each country in both years. Conclusions The large number of forest fragments and distances between them suggest that some mammals characteristic of the biome may be experiencing negative impacts from this fragmentation. Contemporary and future challenges of uncoordinated national conservation and management policies, land speculation, and increased human infrastructure will accelerate the rate of deforestation.
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The main paradigm for protection of biodiversity, focusing on maintaining or restoring conditions where humans leave no or little impact, risks overlooking anthropogenic landscapes harboring a rich native biodiversity. An example is northern European agricultural landscapes with traditionally managed semi-natural grasslands harboring an exceptional local richness of many taxa, such as plants, fungi and insects. During the last century these grasslands have declined by more than 95%, i.e. in the same magnitude as other, internationally more recognized declines of natural habitats. In this study, data from the Swedish Red List was used to calculate tentative extinction rates for vascular plants, insects (Lepidoptera, Coleoptera, Hymenoptera) and fungi, given a scenario where such landscapes would vanish. Conservative estimates suggest that abandonment of traditional management in these landscapes would result in elevated extinction rates in all these taxa, between two and three orders of magnitude higher than global background extinction rates. It is suggested that the species richness in these landscapes reflects a species pool from Pleistocene herbivore-structured environments, which, after the extinction of the Pleistocene megafauna, was rescued by the introduction of pre-historic agriculture. Maintaining traditionally managed agricultural landscapes is of paramount importance to prevent species loss. There is no inherent conflict between preservation of anthropogenic landscapes and remaining ‘wild’ areas, but valuating also anthropogenic landscapes is essential for biodiversity conservation.
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Forest restoration occupies centre stage in global conversations about carbon removal and biodiversity conservation, but recent research rarely acknowledges social dimensions or environmental justice implications related to its implementation. We find that 294.5 million people live on tropical forest restoration opportunity land in the Global South, including 12% of the total population in low-income countries. Forest landscape restoration that prioritizes local communities by affording them rights to manage and restore forests provides a promising option to align global agendas for climate mitigation, conservation, environmental justice and sustainable development. An analysis of the overlap between tropical forest restoration, human populations, development and national policies for community forest ownership shows that 294.5 million people live within forest restoration opportunity land in the Global South.
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Although habitat loss is the predominant factor leading to biodiversity loss in the Anthropocene1,2, exactly how this loss manifests—and at which scales—remains a central debate3,4,5,6. The ‘passive sampling’ hypothesis suggests that species are lost in proportion to their abundance and distribution in the natural habitat7,8, whereas the ‘ecosystem decay’ hypothesis suggests that ecological processes change in smaller and more-isolated habitats such that more species are lost than would have been expected simply through loss of habitat alone9,10. Generalizable tests of these hypotheses have been limited by heterogeneous sampling designs and a narrow focus on estimates of species richness that are strongly dependent on scale. Here we analyse 123 studies of assemblage-level abundances of focal taxa taken from multiple habitat fragments of varying size to evaluate the influence of passive sampling and ecosystem decay on biodiversity loss. We found overall support for the ecosystem decay hypothesis. Across all studies, ecosystems and taxa, biodiversity estimates from smaller habitat fragments—when controlled for sampling effort—contain fewer individuals, fewer species and less-even communities than expected from a sample of larger fragments. However, the diversity loss due to ecosystem decay in some studies (for example, those in which habitat loss took place more than 100 years ago) was less than expected from the overall pattern, as a result of compositional turnover by species that were not originally present in the intact habitats. We conclude that the incorporation of non-passive effects of habitat loss on biodiversity change will improve biodiversity scenarios under future land use, and planning for habitat protection and restoration.
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Habitat destruction and overexploitation are the main threats to biodiversity and where they co-occur, their combined impact is often larger than their individual one. Yet, detailed knowledge of the spatial footprints of these threats is lacking, including where they overlap and how they change over time. These knowledge gaps are real barriers for effective conservation planning. Here, we develop a novel approach to reconstruct the individual and combined footprints of both threats over time. We combine satellite-based land-cover change maps, habitat suitability models and hunting pressure models to demonstrate our approach for the community of larger mammals (48 species > 1 kg) across the 1.1 million km 2 Gran Chaco region, a global deforestation hotspot covering parts of Argentina, Bolivia and Paraguay. This provides three key insights. First, we find that the footprints of habitat destruction and hunting pressure expanded considerably between 1985 and 2015, across ~40% of the entire Chaco-twice the area affected by deforestation. Second, both threats increasingly acted together within the ranges of larger mammals in the Chaco (17% increase on average, ± 20% SD, cumulative increase of co-occurring threats across 465 000 km 2), suggesting large synergistic effects. Conversely, core areas of high-quality habitats declined on average by 38%. Third, we identified remaining priority areas for conservation in the northern and central Chaco, many of which are outside the protected area network. We also identify hotspots of high threat impacts in central Paraguay and northern Argentina, providing Research 2 a spatial template for threat-specific conservation action. Overall, our findings suggest increasing synergistic effects between habitat destruction and hunting pressure in the Chaco, a situation likely common in many tropical deforestation frontiers. Our work highlights how threats can be traced in space and time to understand their individual and combined impact, even in situations where data are sparse.
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Field information is essential for developing conservation actions, but standard methods for surveying wildlife are often inefficient in large, remote areas. Without efficient methods, surveying is difficult or even impossible. Consequently, some of the most threatened species and regions remain un- or under-surveyed, e.g. South American Chaco. Survey methods based on local ecological knowledge (LEK-methods) could be useful for surveying these areas and species. However, LEK-methods may be inaccurate and are rarely evaluated or compared to standard-methods. This is the first large-scale study evaluating the performance of two LEK-methods, and comparing it with the performance of standard-methods, for detecting three species of large terrestrial mammals. We used a locally-based survey (LBS) and interviews as LEK-methods, and transect and camera trapping as standard survey methods. We estimated the probability of detecting each species with each method, of having false-presences and their cost. We also quantitatively analysed the ability of LBS to build local capacity, focusing on conservation, research and working skills. We found that compared to standard-methods, LEK-methods increase detection probabilities of three species while providing accurate information. LBSs are more expensive than interviews but improve local capacities, raising the chances of successful implementation of community-based conservation programmes. Interviews are optimal for rapid assessments and can be useful for wildlife monitoring. Before using LEK-methods, we recommend pilot studies to determine estimators´ variability. Overall, this study shows that LEK-based methods can be efficient and accurate for detecting large mammals in remote areas. Furthermore, LEK-methods can help develop legitimate conservation initiatives.
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The human impact on life on Earth has increased sharply since the 1970s, driven by the demands of a growing population with rising average per capita income. Nature is currently supplying more materials than ever before, but this has come at the high cost of unprecedented global declines in the extent and integrity of ecosystems, distinctness of local ecological communities, abundance and number of wild species, and the number of local domesticated varieties. Such changes reduce vital benefits that people receive from nature and threaten the quality of life of future generations. Both the benefits of an expanding economy and the costs of reducing nature's benefits are unequally distributed. The fabric of life on which we all depend-nature and its contributions to people-is unravelling rapidly. Despite the severity of the threats and lack of enough progress in tackling them to date, opportunities exist to change future trajectories through transformative action. Such action must begin immediately, however, and address the root economic, social, and technological causes of nature's deterioration.
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Connectivity of protected areas (PAs) is needed to ensure the long-term persistence of biodiversity and ecosystem service delivery. The Convention on Biological Diversity agreed in 2010 to have 17% of land covered by well-connected PA systems by 2020 (Aichi Target 11). We here globally assess, for all countries, the trends in terrestrial PA connectivity every other year from 2010 to 2018 using the ProtConn indicator, which quantifies how well the PA systems are designed to support connectivity. The percentage of protected connected land (ProtConn) has increased globally from 6.5% in 2010 to 7.7% in 2018. Oceania experienced the largest recent increase in PA connectivity, whereas Asia is the only content with a lower ProtConn in 2018 than in 2010. Globally, the relative increase in the percentage of protected connected land (ProtConn) is nearly twice that of the percentage of land under protection (PA coverage), due to clear improvements in the design of PA systems for connectivity in many regions. The connectivity of the PA networks has become more dependent on the permeability of the unprotected landscape matrix in between PAs and on the coordinated management of adjacent PAs with different designations and of transboundary PA linkages. The relatively slow recent increase in PA connectivity globally (2016–2018) raises doubt as to whether connectivity targets will be met by 2020, and suggests that considerable further action is required to promote better-connected PA systems globally, including the expansion of the PA systems to cover key areas for connectivity in many countries and regions.
Overexploitation is a frequently cited driver of species extinction. Throughout the Neotropics, balancing traditional practices and the needs of local people with protection of rare or declining species is challenging, especially given low capacity for control by authorities. We conducted interviews with wildlife professionals and residents, along with a camera-based field survey of wildlife occurrence, to gain insight into recent population trends, relative abundance, and drivers of harvest for large mammals in the northern Dry Chaco of Paraguay including but not limited to, Defensores del Chaco National Park. Although the endangered Chacoan peccary (Catagonus wagneri) was preferred regardless of hunter motivation, harvests of all species appeared largely opportunistic, and limited to immediate family use due to a lack of market forces, and constraints on refrigeration capacity in the region. This pattern may soon change given rapid deforestation, and an associated and growing road network providing greater access both to wildlife resources and commercial bushmeat markets. Notably, public perception of abundance and trends for Chacoan peccary differed from professional opinions—likely due in part to greater use of areas along roads by C. wagneri compared to other, relatively more abundant species. This discordance may pose future challenges if harvest restrictions become a conservation necessity, especially during a process of essentially self-imposed voluntary limitations.