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The jaguar's spots are darker than they appear: assessing the global conservation status of the jaguar Panthera onca

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The IUCN Red List is widely used to guide conservation policy and practice. However, in most cases the evaluation of a species using IUCN Red List criteria takes into account only the global status of the species. Although subpopulations may be assessed using the IUCN categories and criteria, this rarely occurs, either because it is difficult to identify subpopulations or because of the effort involved. Using the jaguar Panthera onca as a model we illustrate that wide-ranging species that are assigned a particular category of threat based on the IUCN Red List criteria may display considerable heterogeneity within individual taxa in terms of the level of risk they face. Using the information available on the conservation status of the species, we evaluated the jaguar's current geographical range and its subpopulations. We identified the most threatened subpopulations, using the extent of occurrence, area of occupancy, population size and the level of threat to each subpopulation. The main outcome of this analysis was that although a large subpopulation persists in Amazonia, virtually all others are threatened because of their small size, isolation, deficient protection and the high human population density. Based on this approach, future conservation efforts can be prioritized for the most threatened subpopulations. Based on our findings we recommend that for future Red List assessments assessors consider the value of undertaking assessments at the subpopulation level. For the jaguar, sub-global assessments should be included on the Red List as a matter of urgency.
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The jaguar's spots are darker than they appear:
assessing the global conservation status of the jaguar
Panthera onca
J. ANTONIO DE LA TORRE,JOSÉ F. GONZÁLEZ-MAYA,HELIOT ZARZA
GERARDO CEBALLOS and R ODRIGO A. MEDELLÍN
Abstract The IUCN Red List is widely used to guide conser-
vation policy and practice. However, in most cases the
evaluation of a species using IUCN Red List criteria takes
into account only the global status of the species.
Although subpopulations may be assessed using the IUCN
categories and criteria, this rarely occurs, either because it is
difficult to identify subpopulations or because of the effort
involved. Using the jaguar Panthera onca as a model we il-
lustrate that wide-ranging species that are assigned a par-
ticular category of threat based on the IUCN Red List
criteria may display considerable heterogeneity within indi-
vidual taxa in terms of the level of risk they face. Using the
information available on the conservation status of the spe-
cies, we evaluated the jaguars current geographical range
and its subpopulations. We identified the most threatened
subpopulations, using the extent of occurrence, area of oc-
cupancy, population size and the level of threat to each sub-
population. The main outcome of this analysis was that
although a large subpopulation persists in Amazonia, virtu-
ally all others are threatened because of their small size, iso-
lation, deficient protection and the high human population
density. Based on this approach, future conservation efforts
can be prioritized for the most threatened subpopulations.
Based on our findings we recommend that for future Red
List assessments assessors consider the value of undertaking
assessments at the subpopulation level. For the jaguar, sub-
global assessments should be included on the Red List as a
matter of urgency.
Keywords Assessment, conservation, IUCN, jaguar,
Panthera onca, subpopulations, threats, threatened species
Introduction
Assessment of extinction risk is one of the most inform-
ative tools available to guide conservation policy and
practice (Mace et al., ). However, the specific facts
and processes that lead to listing, assessing or delisting spe-
cies are rarely available other than the schematic listings
within the IUCN Red List or other national protocols. The
IUCN Red List uses three categories of threat (Critically
Endangered, Endangered and Vulnerable), which are as-
signed on the basis of quantitative criteria to reflect varying
degrees of threats of extinction. Taxa that do not qualify as
threatened but may be close to qualifying are categorized as
Near Threatened, as are taxa that are likely to meet criteria
for a threatened category if ongoing conservation action
abates or ceases (IUCN, ).
In most cases, species evaluations are undertaken only at
the global level. Although IUCN Red List assessments may be
undertaken at the subpopulation level, following the proper
categories and criteria (IUCN Standards and Petitions
Subcommittee, ), these are often not implemented, usu-
ally because it is difficult to identify subpopulations or be-
cause of the effort involved. This is problematic, especially
for species with a wide distribution range, because the cat-
egorization does not necessarily reflect the status of the spe-
cies throughout its range (Wallace et al., ). There are
many species that have lost most of their habitat within
their geographical range but do not qualify within these
risk categories because they still maintain a wide range or a
single large population. This is the case for the jaguar
Panthera onca, the largest felid on the American continent.
Historically, the jaguar ranged across c. ,, km
from south-western USA to central Argentina (Seymour,
). However, since  its range has decreased to
c. ,, km
and it is now found only from northern
Mexico to northern Argentina, although it occasionally dis-
perses to the extreme south-western USA (Medellín et al.,
,; Sanderson et al., ). Previous efforts to evalu-
ate the jaguars conservation status at regional and contin-
ental scales have concluded that the species is declining
throughout much of its range (Swank & Teer, ;
Sanderson et al., ; Zeller, ; Medellín et al., ).
However, the jaguar is categorized as Near Threatened on
the IUCN Red List, the second lowest risk category, being
close to qualifying for the Vulnerable category under criteria
J. ANTONIO DE LA TORRE,JOSÉ F. GONZÁLEZ-MAYA*, GERARDO CEBALLOS and RODRIGO
A. MEDELLÍN (Corresponding author) Instituto de Ecología, Universidad
Nacional Autónoma de México, Ciudad Universitaria, 04318, México D.F.,
México. E-mail medellin@iecologia.unam.mx
HELIOT ZARZA Departamento de Ciencias Ambientales, Universidad Autónoma
Metropolitana Unidad Lerma, CP 52005 Lerma de Villada, México
*Also at: Proyecto de Conservación de Aguas y Tierras, Bogotá, Colombia
Received April . Revision requested  May .
Accepted September .
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Acd or Acda. The main reason the jaguar is not assigned a
higher risk category, such as Vulnerable or Endangered, is
its wide geographical range, along with the fact that it still
maintains a large subpopulation in the Amazon basin
(Caso et al., ).
Assessment of subpopulations can help to draw attention
to conservation priorities that may otherwise be obscured.
We thus undertook such an assessment of the jaguar, and
we present a methodology for identifying subpopulations
within the speciesrange, and assessing each subpopulation
against the IUCN Red List categories and criteria. We used
available information on the jaguars range and estimates of
density to assess the speciesconservation status throughout
its range. Additionally, we developed a threat evaluation sys-
tem to assess the level of threat for each subpopulation and
to allocate conservation priorities. Our aims were () to es-
timate the current geographical range of the species and its
subpopulations, () to estimate the size of the global popu-
lation and subpopulations of jaguars, and () to identify the
most threatened subpopulations throughout the jaguars
range. We illustrate that for wide-ranging species assigned
to a particular category of threat on the IUCN Red List
there may be considerable heterogeneity within the extinc-
tion risk for the taxon, and that assessments, especially for
species with a wide distribution range, should be based on
the level of threat for all subpopulations throughout the spe-
ciesrange. We hope this information will encourage asses-
sors to consider the value of undertaking assessments at the
subpopulation level.
Methods
Geographical range
To determine the jaguars current range we compiled the
most recent information on its distribution from all avail-
able sources. We included information from the Jaguar
Conservation Units (Sanderson et al., ; Zeller, ;
Rabinowitz & Zeller, ), and published population maps
for the range countries (Cavalcanti et al., ;Beisiegel
et al., ;deOliveiraetal.,;dePaulaetal.,;
Moraes, ; Carrillo-Percastegui & Maffei, ;Chávez
et al., ; de Azevedo et al., ;deThoisy,;
Díaz-Santos et al., ;Espinosaetal.,; Figueroa et al.,
;García-Anleuetal.,; González-Maya et al., ;
Hoogesteijn et al., ;Maffeietal.,;Moraetal.,;
Moreno et al., ; Payán Garrido et al., ). We mapped
polygons to define jaguar subpopulations at the continental
scale, delineatedbased on the information available for jaguar
distribution in each country. Because the information was
obtained from various sources, we recognized that criteria
for defining subpopulation polygons in each country were dis-
similar. For instance, subpopulations in Mexico and Brazil
were delineated with detailed maps, using expert knowledge.
In other cases we supplemented the Jaguar Conservation Unit
information with published maps of the jaguars range in each
of its range countries. Using all this information we generated
detailed geographical information system layers that repre-
sented the subpopulation polygons on a map. Although
most of this information has not been published in peer-
reviewed journals, it represents the latest knowledge of the
speciesrange based on assessments by experts working in
the jaguar range countries.
We defined the polygons using the IUCN definition: geo-
graphically or otherwise distinct groups in the global popu-
lation between which there is little demographic or genetic
exchange (typically one successful migrant individual or
gamete per year or less); a subpopulation may or may not
be restricted to a region (IUCN, ; IUCN Standards
and Petitions Subcommittee, ). As the taxonomic and
genetic research indicated little difference among jaguar
subpopulations (Larson, ; Eizirik et al., ; Ruiz-
Garcia et al., ) we defined the subpopulation polygons
as discrete units following these criteria: () we considered
only polygons ., km
, with the aim of including in
the analysis only regions where resident subpopulations oc-
curred; i.e. we considered only sites that could potentially
contain a subpopulation of at least resident jaguars, con-
sidering the lower density estimate throughout the species
distribution range (. jaguars per  km
; Paviolo et al.,
); and () we identified geographical, natural and an-
thropogenic barriers between the polygons, such as moun-
tain ranges that potentially divide the polygons (the upper
elevation limit of the species is , m; Caso et al., ),
and urban areas and large areas modified by human activ-
ities. We considered subpopulations to be independent if the
distance of habitat that was modified by human activities
between a polygon and its nearest neighbouring polygon
was . km. For this we used the GlobCover land-use clas-
sification (Arino et al., ). We reclassified the Natural
and Semi-natural Terrestrial Vegetation layers as natural
vegetationand the Cultivated and Terrestrial and
Management layers as intervened, according to the
GlobCover land-use classification (Arino et al., ). We
assumed the polygons included both the Jaguar
Conservation Units and the corridors under the scheme
proposed by Rabinowitz & Zeller ().
Using the subpopulation polygons we delineated an ap-
proximation of the jaguars current range at the continental
scale. We estimated the extent of jaguar occurrence using
the minimum convex polygon that enclosed the range of
each subpopulation (IUCN Standards and Petitions
Subcommittee, ; Joppa et al., ). Top-level predators
such as jaguars are particularly threatened in regions of high
human population density by direct persecution and habitat
loss (Woodroffe, ; Cardillo et al., ), and jaguar ex-
tinction can be predicted according to certain thresholds of
2 J. Antonio de la Torre et al.
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human population density (Woodroffe, ). Given these
two factors, we estimated the jaguars area of occupancy for
each polygon, using a grid of the human population density
in the Americas for the year  at a resolution of  arc-
seconds (c. km; Center for International Earth Science
Information Network et al., ). We defined two scenarios
of area of occupancy because threshold values of human
population density that predict the extinction of jaguars
are  people per km
(mean  people per km
;
Woodroffe, ). Our lower and upper estimates were de-
fined by obtaining the natural vegetation layers for each
polygon (Arino et al., ) and excluding the sites where
human density was . and . people per km
, respect-
ively. We calculated our lower and upper estimates of area of
occupancy at the reference scale of km
(×km grid
size), as suggested in the IUCN Red List Guidelines
(IUCN Standards and Petitions Subcommittee, ).
To estimate the jaguars range loss we contrasted our es-
timates of range and area of occupancy with the historical
distribution of the species, based on the maps of Patterson
et al. (). All geographical analyses were performed
using ArcGIS .(ESRI, Redlands, USA).
Subpopulations
For each subpopulation polygon we estimated the total area
covered, and we listed the biomes and ecoregions found
within the polygon (Olson et al., ). We compiled all
published estimates of jaguar density based on camera
traps, including those published in indexed journals, book
chapters and technical reports. In total we included  dens-
ity estimates from  studies from Mexico to Argentina, pub-
lished during . As the majority of camera trap
studies of the jaguar do not meet the requirements necessary
to produce unbiased density estimates, and probably over-
estimate densities (Tobler & Powell, ), we conservatively
corrected the estimate for each study using the inferior
interval of the density estimate (subtracting the standard
error from the density estimate reported). Each study was
categorized according to the biome and ecoregion using
the coordinates reported in the sources (Table ). For the
polygons for which there were no available density estimates
or estimates for a particular type of biome, we used the most
conservative density estimate reported for the nearest
polygon.
We defined a subpopulation as the estimated number of
individuals in each polygon, and used the term population
to refer to the sum of all subpopulations across the range
(IUCN, ; IUCN Standards and Petitions Subcommittee,
). We estimated the subpopulation size for each polygon
by extrapolating the density estimates to our layers of area of
occupancy. For each polygon we performed two estimates
of jaguar population size, based on our upper and lower
area of occupancy scenarios. For these estimates we assumed
that jaguar density declined linearly as the human population
density increased (Woodroffe, ). This implies that jaguar
densities across the polygons were estimated for each cell in
the area of occupancy maps using the linear regression for-
mula y=xm + b,whereyis the estimated jaguar density ad-
justed according to the human population density, xis the
human population density (Center for International Earth
Science Information Network et al., ), mis the constant
rate at which jaguar densities decline as the human popula-
tion density increases, and bis the jaguar density defined for
each biome in each polygon (Table ). We used the Raster
Calculator tool in ArcGIS .to estimate the jaguar density
adjusted according to the human population density for each
grid cell in the area of occupancy maps. Using the jaguar
density values of each grid cell we estimated the number of
jaguars for the biome or biomes contained in each polygon.
Importantly, jaguar density varies according to habitat
type, prey availability, degree of fragmentation, season,
and human disturbance. Also, density estimates based on
camera trapping could be skewed, depending on how the
methodology was used by various researchers throughout
the range of the species (Tobler & Powell, ). For these
reasons our estimates of subpopulation sizes should be in-
terpreted with caution because we are extrapolating from
the available information to vast areas. However, our ap-
proach was robust because we extrapolated jaguar densities
only for sites where the human population density was not
. (lower estimate) or . people per km
(upper estimate),
and assumed that jaguar densities were not homogeneous
across the biomes (i.e. jaguar densities were adjusted accord-
ing to the human population density across the polygon).
Assessment under the IUCN threat categories
Based on the extent of occurrence, area of occupancy and es-
timated population size, we assessed the conservation status
of each subpopulation using the IUCN criteria (IUCN
Standards and Petitions Subcommittee, ). We used this
evaluation to illustrate the risk of extinction of each subpopu-
lation independent of the conservation status of the other
subpopulations. To conduct the assessments we evaluated
each subpopulation against the five criteria: (A) declining
population, (B) geographical range size, (C) small population
size, (D) very restricted distribution, and (E) quantitative
analysis of extinction risk (IUCN, ). Each subpopulation
was categorized as Least Concern, Near Threatened,
Vulnerable, Endangered or Critically Endangered.
As there is little information available about the recent
decline of jaguars within the polygons, to apply Criterion
A we estimated the speciesarea of occupancy in the recent
past. For this we used the University of Maryland Land
Cover Classification, developed from a collection of satellite
The jaguars global conservation status 3
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TABLE 1 Densities (per  km
) of the jaguar Panthera onca in various biomes, used to extrapolate the population size of each subpopulation (Fig. ).
No. Jaguar subpopulation
Biome
1
ReferencesMBF DBF GSS FGS MGS TCF D M
1 Mexican Pacific 1.8 1.5 0.65 0.65 0.65 Núñez-Pérez (2011); de la Torre & Medellín (2011); Gutiérrez-González et al. (2012)
2 Sierra de Tamaulipas 0.75 0.75 0.65 Gutiérrez-González et al., (2012); Chávez et al. (2016)
3 Gulf of Mexico 1.8 1.5 0.65 de la Torre & Medellín (2011); Chávez et al. (2016)
4 Selva Maya 1.8 1.5 0.65 0.65 Núñez-Pérez (2011); de la Torre & Medellín (2011); Chávez et al. (2016)
5 Maya Mountains 5.75 4 0.65 0.65 Silver et al. (2004)
6 Honduras Caribbean 1.55 1 1 Mora et al. (2016)
7 Honduran Mosquitia 1.55 1 1 1 Mora et al. (2016)
8 Indio-Maíz Tortuguero 1.5 1 1 Díaz-Santos et al. (2016)
9 Talamanca 1.34 González-Maya et al. (2016)
10 Osa Peninsula 4 0.65 Salom-Pérez et al. (2007)
11 Central Panama 2 0.65 Moreno et al. (2016)
12 Biogeographic Choco 1.5 1.5 0.65 0.65 Moreno et al. (2016)
13 Paramillo-San Lucas 1.5 1.5
14 Sierra Nevada de Santa Marta 1.5 1 0.65 0.65 0.65
15 Serrania de Perija-Catatumbo 1.5 1.5 0.65 0.65
16 Santa Helena-Guayas 1.5 1.5 0.65 0.65
17 Amazonia
2
1 1 1 1 0.65 0.65 0.65 Maffei et al. (2004); Soisalo & Cavalcanti (2006); de Oliveira et al. (2012); Tobler et al. (2013)
18 Maranhão-Babaçu 0.67 Moraes (2012)
19 Nascentes Parnaíba 0.67 0.67 0.67
20 Boquerião da Onça 0.5 0.5 0.5 De Paula et al. (2012)
21 Serra da Capivara 0.2 De Paula et al. (2012)
22 Chapada Diamantina 0.3 0.3 0.3 De Paula et al. (2012)
23 Araguaia 0.67 0.67 Moraes (2012)
24 Goiás & Tocantins 0.67 0.67 Moraes (2012)
25 Sertão Veredas Peruaçu 0.67 0.67 0.67 0.67 de Oliveira et al. (2012)
26 Mato Grosso 1 1 1 de Oliveira et al. (2012)
27 Chapada dos Guimarães 0.69 0.69 Moraes (2012)
28 Emas 0.69 Sollmann et al. (2011)
29 Espinhaço de Minas 0.69 0.69 Moraes (2012)
30 Sooretama 0.33 0.33 Paviolo et al. (2008)
31 Mantiqueira-Rio Doce 0.33 Paviolo et al. (2008)
32 Pontal do Paranapanema 0.33 0.33 Paviolo et al. (2008)
33 Serra do Mar 0.33 0.33 0.33 Paviolo et al. (2008)
34 Iguaçu 0.33 0.33 Paviolo et al. (2008)
MBF, Moist Broadleaf Forest; DBF, Dry Broadleaf Forest; GSS, Grasslands, Savannahs, Scrublands; FGS, Flooded Grasslands and Savannahs; MGS, Montane Grassland and Scrublands; TCF, Tropical Coniferous
Forest; D, Deserts; M, Mangroves.
For the Amazonia subpopulation polygon we used the most conservative density estimate of jaguar per  km
(de Oliveira et al., ) for most of the biomes because most of this vast area has never been surveyed
for jaguars, and thus there is considerable uncertainty in the extrapolation for this area. However, density estimates for the Moist Broadleaf Forest biome are.jaguars per  km
(de Oliveira et al., ; Tobler
et al., ), for the Dry Broadleaf Forest biome .. jaguars per  km
(Maffei et al., ), and for the Flooded Grasslands and Savannahs biome .jaguars per  km
(Soisalo & Cavalcanti, ).
4 J. Antonio de la Torre et al.
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images acquired during  (Hansen et al., ,
), and a grid of the human population density in the
American continent for the year  at a resolution of 
arc-seconds (Center for International Earth Science
Information Network et al., ). In a similar way we de-
fined two scenarios for our estimation of area of occupancy
in the recent past. Our lower and upper estimates were de-
fined by obtaining the natural vegetation layers in each
polygon from the University of Maryland Land Cover
Classification and excluding the sites where human density
was . and . people per km
, respectively, in .We
rescaled the maps of area of occupancy in the recent past at
the reference scale of km
, and we estimated the percent-
age of range reduction for each polygon based on the esti-
mates of the area of occupancy at present and in the
recent past (IUCN Standards and Petitions Subcommittee,
). We set the generation time at years, based on ap-
proximate age of maturity (years for females and years
for males) plus half the length of the reproductive lifespan
(years; Eizirik et al., ; Quigley & Crawshaw, ),
and thus past and future declines were estimated for a max-
imum period of  years.
Criterion B was applied using our estimates of the extent
of occurrence and area of occupancy of jaguars in each poly-
gon. Criteria C and D were applied using the mean of our
estimates of population size in each polygon and using the
patterns of jaguar occurrence within the polygon according
to our estimate of the area of occupancy. Criteria C and D
were applied using the number of mature individuals, de-
fined as the number of individuals known, estimated or in-
ferred to be capable of reproduction (IUCN Standards and
Petitions Subcommittee, ). Given that most studies of
jaguar density report data on adult individuals only, we as-
sume that our estimations of jaguar subpopulation size in-
clude only mature individuals.
Criterion E was applied using a population viability ana-
lysis in VORTEX v. ..(Lacy & Pollak, ). To assess
the subpopulations under this criterion we estimated the
probability of extinction of each subpopulation based on
their estimated population size and for time intervals of 
years (three generations),  years (five generations) and 
years. As most of the demographic parameters for jaguars
are unknown, our generic model was based on the para-
meters used by Eizirik et al. () to model the viability
of jaguar populations (Table ). We did not include cata-
strophes in our model, and we used  iterations in each
subpopulation model.
Level of threat for jaguar subpopulations
To assess the level of threat for each subpopulation we devel-
oped a threat evaluation system, which was applied inde-
pendently to each polygon. This system was based on five
criteria: extent of habitat, degree of human disturbance, via-
bility of the populations, isolation from the other subpopu-
lations, and level of protection. Extent of habitat was based
on the percentage of natural habitat contained in each poly-
gon, calculated based on the remaining areas with natural
vegetation in each polygon (Arino et al., ). As the hunt-
ing pressure on large carnivores and their prey species is
likely to be higher in areas of high human population dens-
ity (Woodroffe, ; Dupain et al., ; Espinosa et al.,
; Fa et al., ; Ziegler et al., ), we measured the de-
gree of human disturbance using a human population dens-
ity grid (Center for International Earth Science Information
Network et al., ) and by calculating the mean human
density in each polygon. To estimate the viability of the po-
pulations, we used our estimates of population size for each
polygon and the criteria defined by Eizirik et al. ().
Subpopulations with , individuals were considered to
be non-viable, subpopulations with  individuals
were considered to be viable in the medium term (
years, with % probability), and those with .
TABLE 2 Demographic parameters used in our base model in VORTEX to evaluate jaguar subpopulations under criterion E of the IUCN Red
List.
Parameters Values in the base model
Inbreeding depression 3.4 lethal equivalents per individual, & 1.57 recessive lethal alleles
Extinction definition No individuals of one or both sexes
Reproduction system Polygynous
First age of reproduction 3 years for females & 4 years for males
Maximum breeding age 10 years
Sex ratio at birth 0.5
Adult males in the breeding pool 90%
% of adult females breeding Reproduction is density dependent, according to the formula
((50 × [1 ((N/K)
2
)]) + (30 × [(N/K)
2
])) × (N/(0.50 + N))
Number of offspring per female per brood 14 litters; 5% of females produce litter of 1 cub, 40% produce litter of 2, 30%
produce litter of 3 and 25% produce litter of 4
Mortality of females 34% aged 01 years, 17% aged 12, 19% aged 23, and 20% adults
Mortality of males 34% aged 01 years, 17% aged 12, 35% aged 23, 30% aged 34, and 30% adults
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individuals were considered to be viable in the long term
( years, with % probability; Eizirik et al., ).
Degree of isolation was defined using the minimum dis-
tances to the four nearest polygons, and distances were es-
timated using the Proximity tools of ArcGIS .. The level
of protection of each subpopulation was determined by the
percentage of protected area within the speciesrange in
each polygon; this percentage was estimated using the
World Database on Protected Areas (UNEP-WCMC &
IUCN, ). We overlaid our estimation of the species
range on the terrestrial protected areas of the American con-
tinent and estimated the percentage protected in each poly-
gon. We included in this analysis the protected areas
recognized by national governments, areas designated
under regional and international conventions, privately pro-
tected areas, and territories conserved by indigenous people
and communities, all of which met the IUCN and
Convention on Biological Diversity definitions of protected
areas (UNEP-WCMC & IUCN, ).
We scored the level of threat for each subpopulation ac-
cording to each of the five criteria. The highest level of threat
for each criterion was assigned a score of , a medium level
of threat was assigned a score of , and the lowest level was
assigned a score of ; therefore, each population could get a
maximum score of  and a minimum score of  (Table ).
Subpopulations with a final score of $ (equivalent to hav-
ing more than three criteria with the highest threat score)
were defined as having a high level of threat, those with a
final score of  (equivalent to having more than one cri-
terion with the highest threat score) were defined as having a
medium level of threat, and those with a final score of #
(equivalent to having only one criterion with the maximum
score) were defined as having a low level of threat.
Results
Current geographical range and level of protection
According to our estimates the jaguars geographical range
is c. ,, km
(Table ). Jaguars are still found in 
countries across the continent, from northern Mexico to
northern Argentina; they have disappeared from El
Salvador and Uruguay and are practically extinct in the
USA (Fig. ). Using the area covered by the subpopulation
polygons we estimate that the jaguars geographical range
has contracted by % in the last century. However, using
our estimation of the area of occupancy, the situation is
even worse; the area of occupancy is c. ,, km
and
jaguar range may have decreased by % in the last century.
Circa .% of the speciesgeographical range is protected.
Brazil has the largest proportion of area protected (%of
the jaguars range), followed by Venezuela (%), Peru (%),
Bolivia (%) and Colombia (%). We identified 
subpopulation polygons of ,,, km
. One
subpopulation, in Amazonia, covers % of the species
global range (Table ). This means that jaguars have
declined by c. % throughout their range outside
Amazonia.
Population size We estimated the global population of
jaguars to be c. , individuals (Fig. ; Table ). The
largest subpopulation, in Amazonia, comprises c. ,
individuals; the mean estimated population of the
remaining  subpopulations is  ±SD . The
Amazonian subpopulation represents c. .% of the total
jaguar population, leaving only .% in the rest of the
range.
Assessment of subpopulations using IUCN criteria Based
on our assessment of the subpopulations using IUCN
criteria, jaguars are threatened virtually everywhere except
in Amazonia (Fig. ;Table). According to our assessment,
and using the precautionary principle,  subpopulations
should be categorized as Critically Endangered, and eight as
Endangered. Only the Amazonian subpopulation maintains
the status of Least Concern. Most subpopulations qualified
for one of the threat categories under at least three criteria
(C, D and E).
TABLE 3 IUCN Red List criteria used to evaluate the level of threat in each jaguar subpopulation polygon.
Criterion Unit
Threshold*
Maximum (4) Medium (3) Low (2)
A. Habitat availability % of natural habitats within the polygon ,50 $50 & ,75 $75
B. Degree of human perturbation Mean human population density within
the polygon
$500 $100 & ,500 ,100
C. Viability of the population Population size ,300 $300 & #650 .650
D. Isolation Mean minimum distance to the nearest
four polygons (km)
.200 .100 & #199 $50 & #100
E. Protection % of area protected within the polygon ,25 $25 & #50 .50
*We defined three thresholds for the five criteria according to the level of threat (see text for details). The higher the total score assigned to a subpopulation,
the greater the level of threat.
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TABLE 4 Jaguar subpopulations (Fig. ), with the area of the subpopulation polygon, the extent of occurrence (EOO) in each polygon, lower
and upper estimates of the area of occupancy (AOO) in each polygon, and lower and upper estimates of the subpopulation size (no. of
mature individuals).
No.
Jaguar
subpopulation
Area of subpopu-
lation polygon
(km
2
)
EOO, km
2
(Minimum
Convex
Polygon)
Lower esti-
mate of
AOO (km
2
)
Upper esti-
mate of
AOO (km
2
)
Lower estimate of
jaguar subpopula-
tion size
1
Upper estimate of
jaguar subpopula-
tion size
2
1 Mexican Pacific 195,848 1,274,871 117,964 151,000 852 1,179
2 Sierra de
Tamaulipas
54,447 94,043 36,860 43,048 149 218
3 Gulf of Mexico 9,059 13,804 3,436 7,016 26 52
4 Selva Maya 88,923 182,895 80,016 83,308 764 1,079
5 Maya Mountains 17,856 28,246 7,248 9,556 217 332
6 Honduras
Caribbean
6,333 9,999 1,532 2,284 9 16
7 Honduran
Mosquitia
26,502 39,294 19,124 23,764 188 231
8 Indio-Maíz
Tortuguero
26,766 43,303 13,132 18,332 101 152
9 Talamanca 15,141 17,887 7,712 11,484 25 69
10 Osa Peninsula 2,241 3,305 0 1,788 0 21
11 Central Panama 5,129 7,809 2,532 2,932 26 35
12 Biogeographic
Choco
159,175 278,753 89,164 105,244 697 1,035
13 Paramillo-San
Lucas
38,186 38,342 19,728 32,732 70 214
14 Sierra Nevada de
Santa Marta
8,662 8,765 0 3,832 0 25
15 Serrania de
Perija-Catatumbo
43,367 52,370 21,552 29,340 106 198
16 Santa
Helena-Guayas
10,592 10,866 1,324 4,240 5 13
17 Amazonia 6,691,521 9,874,482 6,244,810 6,289,556 56,223 58,183
18 Maranhão-Babaçu 22,414 22,522 7,140 19,652 10 45
19 Nascentes Parnaíba 148,027 162,275 118,360 118,360 491 491
20 Boquerião da Onça 12,327 15,239 10,564 10,600 10 13
21 Serra da Capivara 81,466 103,542 52,704 57,080 132 169
22 Chapada
Diamantina
25,110 30,076 14,496 16,188 21 24
23 Araguaia 122,212 143,080 103,832 103,832 531 566
24 Goiás &
Tocantins
124,726 141,670 88,976 90,444 315 349
25 Sertão Veredas
Peruaçu
138,305 162,923 72,528 76,396 202 239
26 Mato Grosso 112,103 146,001 91,696 91,696 762 782
27 Chapada dos
Guimarães
44,246 48,245 24,512 24,536 72 80
28 Emas 15,169 15,182 9,212 9,212 30 31
29 Espinhaço de Minas 29,599 32,261 17,684 21,592 59 81
30 Sooretama 4,974 5,006 232 1,796 0 1
31 Mantiqueira-Rio
Doce
5,249 5,285 1,204 1,804 2 3
32 Pontal do
Paranapanema
34,888 44,925 13,636 16,444 12 16
33 Serra do Mar 56,400 116,227 16,012 26,968 23 45
34 Iguaçu 46,011 56,705 15,100 24,080 26 43
Critical human density =  persons km
Critical human density =  persons km
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Level of threat to subpopulations According to our
evaluation most of the subpopulations faced a high level
of threat (Fig. ;Table ). We identified  subpopulations
with scores that exceeded the threshold for a high level of
threat, and  exceeded the threshold for a medium level
of threat. Only the Amazonia, Araguaia and Selva Maya
subpopulations scored as having a low level of threat.
Most of the subpopulations with the highest levels of
threat were in the southern portion of the speciesrange
in Brazil and Argentina (n = ). Additionally, three
subpopulations in northern South America had high levels
of threat: in Santa Helena-Guayas in Ecuador, and in
Paramillo San Lucas and Sierra Nevada de Santa Marta in
Colombia. In Central America the subpopulations with
the highest levels of threat were in Central Panama and
the Honduras Caribbean. In Mexico the subpopulation
with the highest level of threat was the Sierra de
Tamaulipas (Table ).
Discussion
Our results support and provide greater robustness to prior
assessments of range loss and population decline of jaguars
at the continental scale (Sanderson et al., ; Zeller, ).
Jaguars have been extirpated from more than half of their
original range in the last  years, and the most recent as-
sessments of the regional and continental conservation
FIG. 1 (a) Locations (grey
shaded areas) of the  known
jaguar Panthera onca
subpopulations identified
(Table ); (b) , Mexican
Pacific; , Sierra de
Tamaulipas; , Gulf of Mexico;
, Selva Maya; (c) ,Maya
Mountains; , Honduras
Caribbean; , Honduran
Mosquitia; , Indio
Maíz-Tortuguero; ,
Talamanca; , Osa Peninsula;
, Central Panama; (d) ,
Biogeographic Choco; ,
Paramillo-San Lucas; , Sierra
Nevada de Santa Marta; ,
Serrania de Perija-Catatumbo;
, Santa Elena Guayas; (e) ,
Amazonia; (f) ,
Maranhão-Babaçu; ,
Nascentes Parnaíba; ,
Boquerião da Onça; , Serra
da Capivara; , Chapada
Diamantina; , Araguaia; ,
Goiás and Tocantins; ,
Sertão Veredas Peruaçu; ,
Mato Grosso; , Chapada dos
Guimarães; , Emas; ,
Espinhaço de Minas; ,
Sooretama; ,
Mantiqueira-Rio Doce; ,
Pontal do Paranapanema; ,
Serra do Mar; , Iguaçu.
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status of the species have concluded that the jaguar con-
tinues to decline in much of its current range (Swank &
Teer, ; Medellín et al., ,; Sanderson et al.,
; Zeller, ; Caso et al., ). Our use of subpopula-
tion polygons to estimate range loss is similar to the ap-
proach of Sanderson et al. (;% range loss).
However, we included areas in the current range of the
species where its occurrence was previously unknown
(Sanderson et al., ; Zeller, ), and for the first time
we assessed the speciesstatus across its historical range,
c. ,, km
(Patterson et al., ). Our estimates of
the decline in the jaguars range and population are there-
fore more accurate than previous approaches because our
analysis was based on the most recent information on jaguar
FIG. 2 Jaguar densities across
the speciesrange according to
our lower (a, b, c & d) and
upper (e, f, g & h) estimates of
subpopulation sizes. Density
estimates were extrapolated
only for sites where the human
population density was #
people km
(for our lower
estimate) or # people km
(for our upper estimate), and
jaguar densities were adjusted
according to the human
population density.
The jaguars global conservation status 9
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distribution and on a more precise historical range of the
species. Our estimate of the jaguars global area of occu-
pancy yields a worse scenario than previous assessments
had projected; according to our analyses jaguars have al-
ready disappeared from c. % of their historical range
and the majority of subpopulations are Endangered or
Critically Endangered.
Our global estimate of the jaguar population could be
questioned as it is based on the extrapolation of localized
density estimates to extensive areas, ignoring local conditions
such as fragmentation, prey availability and varying levels of
threat. However, our approach and estimate are realistic and
conservative because we extrapolated jaguar densities only for
sites where human population density did not exceed the
threshold at which jaguar extirpation was predicted
(Woodroffe, ), and because we assumed that jaguar
density decreased with increasing human population density.
Furthermore, there are other estimates of local population
sizes that suggest that our approach is reasonable (Tobler
et al., ;Chávezetal.,;deThoisy,;DiBitetti
et al., ; Díaz-Santos et al., ; Espinosa et al., ;
Figueroa et al., ; García-Anleu et al., ).
Amazonia is the only remaining stronghold for the spe-
cies, and several studies have highlighted the importance of
this region for jaguar conservation (Sanderson et al., ;
Sollmann et al., ; de Oliveira et al., ; Tobler et al.,
). Even this subpopulation is likely to be affected in the
coming decades by deforestation and other threats because
the region is rapidly being transformed by human activity
(Rosa et al., ,; Coe et al., ; Morton et al., ).
Ochoa-Quintero et al. () predicted that by  only
% of the landscapes in the Amazon will be able to sustain
at least % of the focal species of mammals and birds, includ-
ing the jaguar, as a result of habitat fragmentation.
Assessments of the conservation status of a species should
not be based on, or affected significantly by, the existence of a
single large subpopulation. Rather, conservation plans should
be based on an integrated assessment of the species over its
entire range (Ceballos & Ehrlich, ; Wallace et al.,
). Data based on only one subpopulation is likely to result
in a biased assessment and the risk that all other subpopula-
tions will become extinct. As most of the jaguar subpopula-
tions are threatened and subspecific categorization has been
rejected, we propose that jaguar conservation assessments
should include not only one global category but should con-
sider subpopulations/sub-global assessments. Data on only
the range size of this species has biased the assessment, and
conservation resources have not been allocated specifically
for threatened subpopulations, given the speciesglobal
Near Threatened, rather than threatened, status. In addition,
FIG. 3 Conservation status of jaguar subpopulations according to the IUCN Red List criteria (Table ) (a) throughout the species
range, (b) in Mexico, (c) in Central America, (d) in northern South America, and (e) in southern Amazonia; and level of vulnerability
of the subpopulations according to the levels of threat (Table ) (f) throughout the speciesrange, (g) in Mexico, (h) in Central
America, (i) in northern South America, and (j) in southern Amazonia.
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TABLE 5 Categorization of each jaguar subpopulation (Fig. ) based on evaluation against each of the IUCN Red List criteria, and the cat-
egory assigned under the most precautionary principle.
No.
Jaguar
subpopulation
IUCN criteria
IUCN Red List
category*
assigned
A. Population
size reduction
B. Geographical
range
C. Small popu-
lation size &
decline
D. Very small or
restricted
population
E. Quantitative
analysis
1 Mexican Pacific EN C2a(i) VU D1 EN
2 Sierra de Tamaulipas CR C2a(ii) EN D VU E CR
3 Gulf of Mexico VU A2a+4c VU B1ab(i) CR C2a(ii) CR D EN E; CR E CR
4 Selva Maya EN C2a(ii) VU D1 VU E EN
5 Maya Mountains VU A4c CR C2a(ii); EN
C2a(ii)
EN D1;VU D1 VU E EN
6 Honduras Caribbean VU A2a+4c VU B1ab(i)
+2ab(ii)
CR C2a(i) CR D CR E CR
7 Honduran
Mosquitia
VU A4c CR C2a(ii) EN D VU E CR
8 Indio-Maíz
Tortuguero
CR C2a(ii) EN D VU E CR
9 Talamanca VU B1ab(i) CR C2a(ii) CR D; EN D1 EN E; CR E CR
10 Osa Peninsula VU A4c EN B1ab(i);
VU B2ab(ii)
CR C2a(ii) CR D CR E CR
11 Central Panama VU B1ab(i) CR C2a(ii) CR D EN E; CR E CR
12 Biogeographic
Choco
EN C2a(ii) VU D1 VU E EN
13 Paramillo-San Lucas CR C2a(ii) EN D VU E; EN E CR
14 Sierra Nevada de
Santa Marta
VU B1ab(i) CR C2a(ii) CR D CR E CR
15 Serrania de
Perija-Catatumbo
VU A4c CR C2a(ii) EN D VU E CR
16 Santa
Helena-Guayas
VU A4c VU B1ab(i) CR C2a(i) CR D CR E CR
17 Amazonia LC
18 Maranhão-Babaçu VU A4c CR C2a(ii) CR D EN E; CR E CR
19 Nascentes Parnaíba EN C2a(ii) VU D1 VU E EN
20 Boquerião da Onça VU B1ab(i) CR C2a(ii) CR D CR E CR
21 Serra da Capivara VU A4c CR C2a(i) EN D VU E CR
22 Chapada
Diamantina
CR C2a(i) CR D CR E CR
23 Araguaia EN C2a(ii) VU D1 VU E EN
24 Goiás &
Tocantins
VU A4c EN C2a(i) VU D1 VU E EN
25 Sertão Veredas
Peruaçu
VU A2a+4c CR C2a(i) EN D VU E CR
26 Mato Grosso EN C2a(i) VU D1 VU E EN
27 Chapada dos
Guimarães
VU A2a+4c CR C2a(i) EN D EN E CR
28 Emas VU A4c VU B1ab(i) CR C2a(i) CR D EN E CR
29 Espinhaço de Minas CR C2a(i) EN D EN E CR
30 Sooretama VU A2a+4c VU B1ab(i)
+2ab(ii)
CR C2a(i) CR D CR E CR
31 Mantiqueira-Rio
Doce
VU A4c VU B1ab(i)
+2ab(ii)
CR C2a(i) CR D CR E CR
32 Pontal do
Paranapanema
VU A4c CR C2a(i) CR D CR E CR
33 Serra do Mar CR C2a(i) CR D EN E; CR E CR
34 Iguaçu VU A4c CR C2a(i) CR D EN E; CR E CR
*VU, Vulnerable; EN, Endangered; CR, Critically Endangered
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decline is accelerating in most subpopulations, and the causes
of decline are still present, and therefore it is likely the jaguar
will become more threatened in most of its range. The main
threats to the species throughout its range are hunting, deple-
tion of prey, and habitat loss and fragmentation (Sanderson
et al., ;Casoetal.,;Haagetal.,).
Based on our evaluation of threats, conservation efforts for
the most threatened subpopulations should be prioritized.
Identification and implementation of corridors to maintain
connectivity should be a priority in the polygons that have
the highest degree of isolation and the lowest population
sizes (Rabinowitz & Zeller, ); for example, subpopulations
in the Atlantic Forest in Brazil and Argentina are threatened
not only by their isolation and low numbers but also by low
genetic diversity, lack of gene flow, and small effective popu-
lation sizes (Haag et al., ). Another priority is to plan re-
serves throughout the jaguars range to ensure the long-term
connectivity and conservation of most subpopulations. In
most of the subpopulation polygons ,% of the area is pro-
tected. Vast areas of high-quality habitat are required to en-
sure the viability of a jaguar population over the long term
(Quigley & Crawshaw, ; Ceballos et al., ; Sanderson
TABLE 6 The  jaguar subpopulations (Fig. ), with values for each of the five criteria used to evaluate the level of threat to each
subpopulation.
No. Jaguar subpopulation
% natural
cover
Human popula-
tion density
(km
²)
Mean no.
of jaguars
Mean distance to four
nearest subpopulation
polygons (km)
% pro-
tected
Total
score
Level of
threat
1 Mexican Pacific 86.08 488.3 1,016 161.00 8.87 14 Medium
2 Sierra de Tamaulipas 93.75 1033.1 184 858.00 16.73 18 High
3 Gulf of Mexico 79.25 263.6 39 301.00 66.47 15 Medium
4 Selva Maya 95.32 216.8 922 131.00 50.67 12 Low
5 Maya Mountains 90.10 884.5 275 183.83 49.74 16 Medium
6 Honduras Caribbean 45.78 1096.1 13 240.00 29.59 19 High
7 Honduran Mosquitia 85.90 116.6 210 284.00 87.46 15 Medium
8 Indio-Maíz
Tortuguero
74.69 408.5 127 160.00 63.79 14 Medium
9 Talamanca 81.24 572.0 47 99.00 48.16 15 Medium
10 Osa Peninsula 69.94 307.7 11 206.00 63.53 16 Medium
11 Central Panama 73.03 1687.5 31 186.00 57.96 16 Medium
12 Biogeographic Choco 74.17 928.4 866 86.00 11.62 15 Medium
13 Paramillo-San Lucas 72.06 521.0 142 138.00 9.16 18 High
14 Sierra Nevada de
Santa Marta
75.61 1451.2 13 228.00 38.87 17 High
15 Serrania de
Perija-Catatumbo
65.51 1151.8 152 100.00 25.28 16 Medium
16 Santa Helena-Guayas 51.66 4544.6 9 534.00 2.10 19 High
17 Amazonia 93.02 83.6 57,203 51.00 42.75 11 Low
18 Maranhão-Babaçu 70.72 392.0 28 366.00 20.95 18 High
19 Nascentes Parnaíba 61.13 53.1 491 59.00 19.58 14 Medium
20 Boquerião da Onça 68.81 155.6 12 63.00 5.88 18 Medium
21 Serra da Capivara 60.66 106.8 151 294.00 20.30 16 Medium
22 Chapada Diamantina 54.70 195.3 23 141.00 17.05 17 High
23 Araguaia 76.93 27.8 549 69.00 35.33 12 Low
24 Goiás & Tocantins 55.54 132.5 332 89.00 10.01 15 Medium
25 Sertão Veredas
Peruaçu
35.87 151.0 221 101.63 12.96 18 High
26 Mato Grosso 78.57 29.6 772 329.00 13.94 14 Medium
27 Chapada dos
Guimarães
42.51 380.7 76 166.00 10.90 18 High
28 Emas 42.39 58.9 31 235.00 10.79 18 High
29 Espinhaço de Minas 58.70 209.1 70 225.00 7.49 18 High
30 Sooretama 44.41 744.9 1 297.53 15.10 20 High
31 Mantiqueira-Rio
Doce
51.64 2024.6 3 225.11 7.90 19 High
32 Pontal do
Paranapanema
25.26 220.5 14 298.00 29.24 18 High
33 Serra do Mar 77.36 5757.6 34 307.24 44.02 17 High
34 Iguaçu 59.12 771.1 35 338.00 14.37 19 High
12 J. Antonio de la Torre et al.
Oryx
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et al., ); however, few regions where the species currently
ranges maintain protected areas that are large enough to en-
sure the protection of at least  jaguars, to guarantee popu-
lation viability over the next  years (Eizirik et al., ).
Furthermore, many protected areas throughout the species
range have limited or no real protection. The jaguar is consid-
ered to be an umbrella, charismatic, and symbol or flag species
in many conservation programmes throughout Latin America
(Medellín et al., ,; Sanderson et al., ; Rabinowitz
&Zeller,), and ensuring the protection of areas large en-
ough to maintain viable populations of jaguars offers a unique
opportunity to ensure protection of the biodiversity with
which jaguars coexist (Thornton et al., ). In areas that
are threatened by high human densities and risk of habitat
loss, sustainable development policies should be implemented
to ensure the conservation of jaguar habitat and the well-being
of human communities that coexist with this felid.
Our analysis is the first to provide a global population es-
timate for the jaguar. It also establishes a basis for determin-
ing geographical conservation priorities for this iconic
umbrella species based on the vulnerability of its individual
populations. More detailed information is needed about the
areas occupied by the species across its range. Additional
density estimates for more biomes and ecoregions would
also help to improve the definition of subpopulations, and
more accurate estimates of the distances that jaguars can tra-
vel between fragmented landscapes would indicate where
conservation efforts should be allocated. The sub-global as-
sessments should be included under the IUCN Red List as a
matter of urgency; we believe that consideration of our ana-
lysis, and further research, would result in a robust regional
conservation strategy that could be designed and implemen-
ted by local conservation leaders across the speciesrange.
Acknowledgements
We thank all local jaguar scientists, from Argentina to
Mexico, for their effective, devoted work to protect this spe-
cies, and their collaborative disposition, and Thomas
A. Gavin, Professor Emeritus, Cornell University, for help
with editing the English of this article. We appreciate the
helpful comments of two anonymous reviewers. This
paper constitutes a partial fulfilment of the Graduate
Programme in Biological Sciences of the National
Autonomous University of Mexico (UNAM) for J.A. de la
Torre, who also acknowledges the support of the National
Council of Science and Technology and UNAM.
Author contributions
JAT and RAM conceptualized and designed the study. JAT
compiled the information on the jaguar subpopulations,
conducted the assessment using the IUCN Red List
guidelines, and drafted the article. RAM and JFGM also
wrote sections of the article. JFGM and HZ compiled the in-
formation on jaguar distribution and analysed the spatial in-
formation. RAM and GC reviewed the data, reviewed the
article critically and directed the revisions.
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Biographical sketches
J. ANTONIO DE LA TORRE is interested in carnivore ecology, be-
haviour and conservation; he has studied jaguars in southern
Mexico for the past  years. J OSÉ F. GONZALEZ-MAYA is inter-
ested in functional ecology and the conservation of mammals, with
a particular focus on Colombia and Costa Rica. HELIOT ZARZA
works on research projects involving spatial analysis and conserva-
tion of carnivores. GERARDO CEBALLOS and R ODRIGO
A. MEDELLÍN have studied the ecology and conservation of mam-
mals in Mexico for more than  years. All the authors have guided
the conservation and management plans for jaguars in Mexico and
other countries.
16 J. Antonio de la Torre et al.
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... T he jaguar (Panthera onca) has been considered as Near Threatened for a quarter century 1 . Although several subpopulations have already been recognized as endangered or critically endangered [1][2][3][4] , some stability is still assumed within the Amazon and Pantanal biomes [1][2][3]5 . The Pantanal is a biodiversity/ ecosystem services hotspot 6,7 and was declared a National Heritage Site by the Brazilian Constitution of 1988 and a Biosphere Reserve by UNESCO in 2000 7,8 . ...
... T he jaguar (Panthera onca) has been considered as Near Threatened for a quarter century 1 . Although several subpopulations have already been recognized as endangered or critically endangered [1][2][3][4] , some stability is still assumed within the Amazon and Pantanal biomes [1][2][3]5 . The Pantanal is a biodiversity/ ecosystem services hotspot 6,7 and was declared a National Heritage Site by the Brazilian Constitution of 1988 and a Biosphere Reserve by UNESCO in 2000 7,8 . ...
... Fire occurrences increased with drought conditions from 2019 to 2020 (Figs. 1,2). Notably, the 2020 Pantanal fires exhibited the highest mean intensity of the period (352.3 ...
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The Pantanal wetland harbours the second largest population of jaguars in the world. Alongside climate and land-use changes, the recent mega-fires in the Pantanal may pose a threat to the jaguars' long-term survival. To put these growing threats into perspective, we addressed the reach and intensity of fires that have affected jaguar conservation in the Pantanal ecoregion over the last 16 years. The 2020 fires were the most severe in the annual series, burned 31% of the Pantanal and affected 45% of the estimated jaguar population (87% of these in Brazil); 79% of the home range areas, and 54% of the protected areas within home ranges. Fires consumed core habitats and injured several jaguars, the Pantanal's apex predator. Displacement, hunger, dehydration, territorial defence, and lower fecundity are among the impacts that may affect the abundance of the species. These impacts are likely to affect other less mobile species and, therefore, the ecological stability of the region. A solution to prevent the recurrence of mega-fires lies in combating the anthropogenic causes that intensify drought conditions, such as implementing actions to protect springs, increasing the number and area of protected areas, regulating fire use, and allocating fire brigades before dry seasons.
... Due to habitat loss, depletion of the prey base, and retaliation for livestock depredation, its historical range has decreased by 54% . Although it is almost endangered globally (NT) (IUCN 2022), most subpopulations are Critically Endangered (CR) or Endangered (EN) (De La Torre et al. 2018). At the cultural level this feline represents the main symbol of sacredness in the cosmology of many indigenous peoples (Benson and Coe 1972;Castaño-Uribe 2016;Morales and Morales 2021;Reichel-Dolmatoff 1978). ...
... In the southern sector of the Sierra Nevada de Santa Marta ecoregion (SNSM), Colombia, the Arhuaco people have cohabited with big cats that prey on their livestock since the time of colonization, when domestic animals were introduced in the region (Castaño-Uribe et al. 2019). This ecoregion is a priority for jaguar conservation because it is one of the few areas in the Colombian Caribbean with sufficient viable habitat for this species and where the present subpopulation is Critically Endangered (De La Torre et al. 2018). Based on that and considering that the cosmovision can strongly influence the attitude towards biodiversity conservation in indigenous contexts (Dickson 2018), research was conducted for the present study in Arhuaco communities. ...
... However, regions of Panamá, and in particular the Azuero Peninsula, have been dramatically altered due to habitat loss and fragmentation and would likely be insufficient to provide connectivity for large mammals throughout their range . Currently, jaguars are classified as Endangered in Panamá (Ministerio de Ambiente de Panamá (MINAM, 2016) with a critically endangered subpopulation in Central Panamá (De la Torre et al., 2017), while pumas are listed as Vulnerable in Panamá (MINAM, 2016). Further, the persistence of viable populations of large felids is dependent on prey availability, in particular ungulates, in tropical rainforests (Weckel et al., 2006). ...
... However, habitat use of collared peccaries was expected to be higher near human settlement due to a high tolerance of anthropogenic disturbance (Mandujano & Reyna-Hurtado, 2019;Thornton et al., 2020). (2) Jaguars are known to utilize habitats closer to water in many areas (e.g., De la Torre et al., 2017;Figel et al., 2019;Nowell and Jackson, 1996;Sollmann et al., 2012). Hence, we hypothesized jaguars to occupy habitat close to water and pumas would be more likely to occupy habitat farther from water than jaguars to potentially avoid competition. ...
Article
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Background and Research Aims Wildlife research in Panamá has focused primarily on protected areas along the Central Cordillera, where much of the remaining mature rainforest habitat is located. Information on large felid and prey habitat use in isolated habitats in Panamá is therefore limited. Here, we estimated occupancy and detection probabilities, as affected by habitat and anthropogenic influences, for 2 felid species (jaguars [ Panthera onca] and pumas [ Puma concolor]), and 2 prey species (white-lipped peccaries [ Tayassu pecari] and collared peccaries [ Pecari tajacu]). Methods Camera trap surveys were conducted during 2014–2015 at Cerro Hoya National Park (CHNP), an isolated remnant of tropical rainforest habitat, and Darién National Park (DNP), a large tract of continuous rainforest habitat. We used single-season, single-species occupancy modeling to estimate probabilities of detection and habitat use of our focal species. Results Three of the 4 focal species were detected at both sites, excluding white-lipped peccary at CHNP. Detection of jaguars and white-lipped peccaries at DNP was highest in February, while detection of collared peccaries at DNP and pumas at CHNP was highest in May and April, respectively. Peccary habitat use was uniform across sites and unaffected by habitat covariates. Both felids preferred habitat further away from anthropogenic disturbance, and jaguars preferred habitat at higher elevations than pumas. Conclusion We further confirm the presence of jaguars and likely local extirpation of white-lipped peccaries in CHNP. Temporal variations influenced detections of focal species. Habitat use of felids was negatively affected by anthropogenic disturbance and elevation. Implications for Conservation Habitat fragmentation and human activities negatively influenced habitat use of felids at both study areas. Given that CHNP serves as one of the last remnants of forest habitat outside the Central Cordillera, we recommend that CHNP be considered a top priority area for wildlife conservation in Panamá.
... Unfortunately, these trends are widespread in deforestation frontiers (Gibson et al. 2011, Barlow et al. 2016. The declines we detected in most species' core areas often contrast with their generally low-threat global conservation status (Supplementary material Appendix 1 Table A3), highlighting the importance of conducting such assessments at the regional level (de la Torre et al. 2018). Given the varied and key ecological roles of larger mammals, their disappearance can disturb ecosystem functioning, including seed dispersal, carbon storage and nutrient cycling (Dirzo et al. 2014, Periago et al. 2014. ...
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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 km2 Gran Chaco region, a global deforestation hotspot cov-ering parts of Argentina, Bolivia and Paraguay. This provides three key insights. First, we find that the footprints of habitat destruction and hunting pressure expanded con-siderably 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, cumula-tive increase of co-occurring threats across 465 000 km2), 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 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.
... The jaguar has experienced a 55% retraction in its global distribution and most of the species' subpopulations are isolated and highly threatened (de la Torre et al. 2018). Despite being a species with great movement capacities, both its occurrence and its movements are negatively affected by the decrease in forest cover and the increase in anthropogenic land uses and infrastructure development Espinosa et al. 2018;Jędrzejewski et al. 2018;Thompson et al. 2020Thompson et al. , 2021Cerqueira et al. 2021). ...
Article
Context Habitat loss is a major factor influencing declines in landscape connectivity for many species, but forest patch configuration and changes in matrix permeability can also represent important drivers. An evaluation of which of these factors are predominant is key to guiding landscape planning at a regional scale. Objectives We aimed to quantify the loss of jaguar (Panthera onca) habitat connectivity and to analyse the drivers behind this process in the Atlantic Forest. Methods We analysed trends in jaguar habitat connectivity between 1973 and 2015 in the Upper Paraná Atlantic Forest and the three countries that comprise the eco-region (Argentina, Brazil, and Paraguay). We used graph-based indices and jaguar movement data to evaluate changes in forest area, forest patch configuration and matrix permeability. Results Jaguar habitat connectivity decreased throughout the entire period, with a loss of up to 93% of connectivity. Changes in forest patch configuration and forest area loss were the main drivers of this trend, but the effect of decreased matrix permeability was also significant. These processes together largely increased the negative effect of forest area declines on jaguar habitat connectivity. Connectivity trends for the three countries in the study area were negative, with the highest forest decline in Paraguay and Brazil compared to Argentina. Conclusions Analysing landscape dynamics using metrics that go beyond measuring net forest area is key when assessing landscape connectivity for jaguars. Future studies evaluating landscape connectivity should incorporate habitat patch configuration and matrix permeability in addition to forest loss, aspects that should also be considered when undertaking habitat restoration measures.
... The jaguar has experienced a 55% retraction in its global distribution and most of the species' subpopulations are isolated and highly threatened (de la Torre et al. 2018). Despite being a species with great movement capacities, both its occurrence and its movements are negatively affected by the decrease in forest cover and the increase in anthropogenic land uses and infrastructure development Espinosa et al. 2018;Jędrzejewski et al. 2018;Thompson et al. 2020Thompson et al. , 2021Cerqueira et al. 2021). ...
Article
Full-text available
ContextHabitat loss is a major factor influencing declines in landscape connectivity for many species, but forest patch configuration and changes in matrix permeability can also represent important drivers. An evaluation of which of these factors are predominant is key to guiding landscape planning at a regional scale.Objectives We aimed to quantify the loss of jaguar (Panthera onca) habitat connectivity and to analyse the drivers behind this process in the Atlantic Forest.Methods We analysed trends in jaguar habitat connectivity between 1973 and 2015 in the Upper Paraná Atlantic Forest and the three countries that comprise the eco-region (Argentina, Brazil, and Paraguay). We used graph-based indices and jaguar movement data to evaluate changes in forest area, forest patch configuration and matrix permeability.ResultsJaguar habitat connectivity decreased throughout the entire period, with a loss of up to 93% of connectivity. Changes in forest patch configuration and forest area loss were the main drivers of this trend, but the effect of decreased matrix permeability was also significant. These processes together largely increased the negative effect of forest area declines on jaguar habitat connectivity. Connectivity trends for the three countries in the study area were negative, with the highest forest decline in Paraguay and Brazil compared to Argentina.Conclusions Analysing landscape dynamics using metrics that go beyond measuring net forest area is key when assessing landscape connectivity for jaguars. Future studies evaluating landscape connectivity should incorporate habitat patch configuration and matrix permeability in addition to forest loss, aspects that should also be considered when undertaking habitat restoration measures.
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We conducted research to understand online trade in jaguar parts and develop tools of utility for jaguars and other species. Our research took place to identify potential trade across 31 online platforms in Spanish, Portuguese, English, Dutch, French, Chinese, and Vietnamese. We identified 230 posts from between 2009 and 2019. We screened the images of animal parts shown in search results to verify if from jaguar; 71 posts on 12 different platforms in four languages were accompanied by images identified as definitely jaguar, including a total of 125 jaguar parts (50.7% posts in Spanish, 25.4% Portuguese, 22.5% Chinese and 1.4% French). Search effort varied among languages due to staff availability. Standardizing for effort across languages by dividing number of posts advertising jaguars by search time and number of individual searches completed via term/platform combinations changed the proportions the rankings of posts adjusted for effort were led by Portuguese, Chinese, and Spanish. Teeth were the most common part; 156 posts offered at least 367 teeth and from these, 95 were assessed as definitely jaguar; 71 of which could be linked to a location, with the majority offered for sale from Mexico, China, Bolivia, and Brazil (26.8, 25.4, 16.9, and 12.7% respectively). The second most traded item, skins and derivative items were only identified from Latin America: Brazil (7), followed by Peru (6), Bolivia (3), Mexico (2 and 1 skin piece), and Nicaragua and Venezuela (1 each). Whether by number of posts or pieces, the most commonly parts were: teeth, skins/pieces of skins, heads, and bodies. Our research took place within a longer-term project to assist law enforcement in host countries to better identify potential illegal trade and presents a snapshot of online jaguar trade and methods that also may have utility for many species traded online.
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We conducted the first long-term and large-scale study of demographic characteristics and reproductive behavior in a wild jaguar (Panthera onca) population. Data were collected through a combination of direct observations and camera trapping on a study area that operates both as a cattle ranch and ecotourism destination. Jaguars exhibited two birth peaks: April/May and October/November, that are the end and the beginning of the wet season in the Pantanal, respectively. The average litter size was 1.43 ± 0.65. Single cubs made up a total of 65.7% of the births, and we found a slight predominance of females (1.15:1 ratio) in litters. The mean age at independence was 17.6 ± 0.98 months, with sex-biased dispersal, with all males (n = 27) leaving the natal home range and 63.6% of females exhibiting philopatry. The interbirth intervals were 21.8 ± 3.2 months and the mean age at first parturition was 31.8 ± 4.2 months. Our results estimated a lifetime reproductive success for female jaguars of 8.13 cubs. Our observations also indicate that female jaguars can display mating behavior during cub rearing or pregnancy, representing 41.4% of the consorts and copulations recorded. We speculate that this behavior has evolved as a defense against infanticide and physical harm to the female. To our knowledge, this is the first time that such behavior is described for this species. All aggressive interactions between females involved the presence of cubs, following the offspring–defense hypothesis, that lead to territoriality among females in mammals, regardless of food availability. In the face of growing threats to this apex predator, this work unveils several aspects of its natural history, representing a baseline for comparison with future research and providing critical information for population viability analysis and conservation planning in the long term.
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Effective transboundary corridors play a crucial role in jaguar Panthera onca conservation. Local residents reported jaguar sightings along the Baritú–Tariquía Biological Corridor, which prompted us to carry out this camera-trap survey. We surveyed an area of 1,243 km ² across the corridor to confirm jaguar presence. We used 50 single camera stations, with cameras placed c. 5 km apart. We placed the cameras along trails, streams and mountain ridges. We recorded jaguars at seven sites across the Corridor; at least three different individuals were identified. These records confirm the presence of the jaguar in the Baritú–Tariquía Biological Corridor between Argentina and Bolivia, a trans-frontier area of the Austral Yungas facing multiple threats but hosting one of the southernmost jaguar populations. Conservation efforts in border regions can promote collaboration and synergies between agencies and other conservation stakeholders, with important implications for wide-ranging predators such as jaguars and their habitats.
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