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Evaluating landscape suitability for golden-headed lion tamarins (Leontopithecus chrysomelas) and Wied’s black tufted-ear marmosets (Callithrix kuhlii) in the Bahian Atlantic Forest

Authors:
  • Royal Zoological Society of Antwerp

Abstract and Figures

In southern Bahia, Brazil, rapid deforestation of the Atlantic Forest threatens a variety of endemic wildlife, including the Endangered golden-headed lion tamarin (GHLT; Leontopithecus chrysomelas) and the Near Threatened Wied’s black-tufted-ear marmoset (Wied’s marmoset; Callithrix kuhlii). Identifying high quality areas in the landscape is critical for mounting efficient conservation programs for these primates. We constructed ecological niche models (ENMs) for GHLTs and Wied’s marmosets using the presence-only algorithm Maxent to (1) locate suitable areas for each species, (2) examine the overlap in these areas, and (3) determine the amount of suitable habitat in protected areas. Our models indicate that 36% (10, 659 km2) of the study area is suitable for GHLTs and 53% (15, 642 km2) for Wied’s marmosets. Suitable areas were strongly defined by presence of neighboring forest cover for both species, as well as annual temperature range for GHLTs and distance from urban areas for Wied’s marmosets. Thirty-three percent of the landscape (9,809 km2) is overlapping suitable habitat. Given that the focal species form mixed-species groups, these areas of shared suitability may be key locations for preserving this important behavioral interaction. Protected areas contained 6% (651 km2) of all suitable habitat for GHLTs and 4% (682 km2) for Wied’s marmosets. All protected areas were suitable for the focal species, excepting Serra do Conduru, which had low suitability for GHLTs. Our results highlight that suitable habitat for GHLTs and Wied’s marmosets is limited and largely unprotected. Conservation action to protect additional suitable areas will be critical for their persistence.
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Research Article
Evaluating landscape suitability for golden-headed lion
tamarins (Leontopithecus chrysomelas) and Wied’s black
tufted-ear marmosets (Callithrix kuhlii) in the Bahian Atlantic
Forest
Cylita Guy1,*, Camila R. Cassano2, Leticia Cazarre2, Kristel M. De
Vleeschouwer3, Maria Cecília Martins Kierulff4, Leonardo G. Neves2,5,
Leonardo C. Oliveira6,7,8, Bruno Marchena R. Tardio9, Sara L. Zeigler10,
and Becky E. Raboy1
1 Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, M5S 3B2, Canada
2 Laboratório de Ecologia Aplicada à Conservação, Universidade Estadual de Santa Cruz, Ilhéus, BA, 45662-
900, Brazil
3 Centre for Research and Conservation, Royal Zoological Society of Antwerp, Koningin Astridplein 26, B-
2018, Antwerp, Belgium
4 Programa de Pós-Graduação em Biodiversidade Tropical. Centro Universitário Norte do Espírito Santo,
Universidade Federal do Espírito Santo. Bairro Litorâneo, Rodovia BR 101, km 60. São Mateus, ES, 29932-
540, Brazil.
5 Instituto de Estudos Socioambientais do Sul Bahia, Ilhéus, BA, 45652-180, Brazil
6 Faculdade de Formação de Professores, Universidade do Estado do Rio de Janeiro, São Gonçalo, RJ,
24435-005, Brazil
7 Bicho do Mato Instituto de Pesquisa, Belo Horizonte, MG, 30170-132, Brazil
8 Programa de pós-graduação em Ecologia e Conservação da Biodiversidade, Universidade Estadual de
Santa Cruz, UESC, Ilhéus, BA, 45662-900, Brazil
9 Ministry of Environment, Chico Mendes Institute of Biodiversity Conservation, Una, BA, 45690-000, Brazil
10 Department of Biological Sciences, Virginia Tech, Blacksburg, VA, 24061, USA
*Correspondence: cylita.guy@mail.utoronto.ca
Abstract
In southern Bahia, Brazil, rapid deforestation of the Atlantic Forest threatens a variety of endemic wildlife, including the
Endangered golden-headed lion tamarin (GHLT; Leontopithecus chrysomelas) and the Near Threatened Wied’s black-
tufted-ear marmoset (Wied’s marmoset; Callithrix kuhlii). Identifying high quality areas in the landscape is critical for
mounting efficient conservation programs for these primates. We constructed ecological niche models (ENMs) for GHLTs
and Wied’s marmosets using the presence-only algorithm Maxent to (1) locate suitable areas for each species, (2) examine
the overlap in these areas, and (3) determine the amount of suitable habitat in protected areas. Our models indicate that
36% (10, 659 km2) of the study area is suitable for GHLTs and 53% (15, 642 km2) for Wied’s marmosets. Suitable areas
were strongly defined by presence of neighboring forest cover for both species, as well as annual temperature range for
GHLTs and distance from urban areas for Wied’s marmosets. Thirty-three percent of the landscape (9,809 km2) is
overlapping suitable habitat. Given that the focal species form mixed-species groups, these areas of shared suitability
may be key locations for preserving this important behavioral interaction. Protected areas contained 6% (651 km2) of all
suitable habitat for GHLTs and 4% (682 km2) for Wied’s marmosets. All protected areas were suitable for the focal species,
excepting Serra do Conduru, which had low suitability for GHLTs. Our results highlight that suitable habitat for GHLTs and
Wied’s marmosets is limited and largely unprotected. Conservation action to protect additional suitable areas will be
critical for their persistence.
Keywords: ecological niche modeling, habitat suitability, primate conservation, Atlantic Forest
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Introduction
Habitat loss is a major driver of biodiversity decline in the tropics, where human population
growth and development cause high rates of habitat reduction [1]. The Atlantic Forest of Brazil,
home to over 8,000 endemic species, retains only 12% of its original forest cover in numerous
isolated patches [25]. In certain centers of endemism, estimated rates of habitat loss approach
and exceed 90% [5]. This habitat loss is driven by activities such as logging of forests for timber,
clearing of land for cattle pasture, and the intensification of traditional farming practices [6,7].
Further deforestation and fragmentation throughout the Atlantic Forest are likely [810] and
threaten many species. Strategies that emphasize landscape management, connectivity, and
protection of representative areas in future conservation efforts are critical and necessitate
identifying high quality areas of habitat essential for species persistence.
Two species threatened by continued deforestation are the Endangered golden-headed lion
tamarin (GHLT; Leontopithecus chrysomelas) and the Near Threatened Wied’s black tufted-ear
marmoset (Wied’s marmoset; Callithrix kuhlii; [11,12]). Both are cooperatively-breeding, small-
bodied arboreal primates in the family Callitrichidae. Endemic to the southern Bahia region of the
Atlantic forest (Fig 1), they share many of their ecological needs, require continuous forest cover
to maintain home ranges, and form non-random associations whereby both species travel, forage
and rest closely together for periods of up to several hours [1315]. In the west of their
distributions, remaining forest fragments are small and isolated [16]. In the east, forest cover is
still relatively well maintained and several protected areas exist, including national and state
parks, biological reserves, and numerous privately owned reserves. However, land use
intensification, conversion of shade cocoa to other forms of agriculture, and selective removal of
trees continue to degrade and eliminate habitat in the east [6,7]. Given the likelihood of future
Received: 11 March 2016; Accepted 1 May 2016; Published: 27 June 2016
Copyright: Cylita Guy, Camila R. Cassano, Leticia Cazarre, Kristel M. De Vleeschouwer, Maria Cecília Martins Kierulff,
Leonardo G. Neves, Leonardo C. Oliveira, Bruno Marchena R. Tardio, Sara L. Zeigler and Becky E. Raboy. This is an
open access paper. We use the Creative Commons Attribution 4.0 license
http://creativecommons.org/licenses/by/3.0/us/. The license permits any user to download, print out, extract,
archive, and distribute the article, so long as appropriate credit is given to the authors and source of the work. The
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in any scientific archive. Open Access authors retain the copyrights of their papers. Open access is a property of
individual works, not necessarily journals or publishers.
Cite this paper as: Guy, C., Cassano, C. R., Cazarre, L., De Vleeschouwer, K. M., Kierulff, M. C. M., Neves, L. G., Oliveira,
L. C., Tardio, B. M. R., Zeigler, S. L. and Raboy, B. E. 2016. Evaluating landscape suitability for Golden-headed lion
tamarins (Leontopithecus chrysomelas) and Wied’s black tufted-ear marmosets (Callithrix kuhlii) in the Bahian Atlantic
Forest. Tropical Conservation Science Vol. 9 (2): 735-757. Available online: www.tropicalconservationscience.org
Disclosure: Neither Tropical Conservation Science (TCS) or the reviewers participating in the peer review process have
an editorial influence or control over the content that is produced by the authors that publish in TCS.
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deforestation throughout the Atlantic forest [810], there is a need to locate and preserve
additional suitable areas for GHLTs and Wied’s marmosets.
Prior analyses to identify suitable areas in the landscape have relied on presence-absence
methods [16], a combination of population viability and landscape analysis [17], and a
prioritization of key habitat patches [18]. These studies addressed landscape suitability for GHLTs,
identifying a limited number of fragments capable of supporting self-sustaining populations in the
long term [17,18]. While prior approaches have identified landscape characteristics necessary for
the persistence of GHLTs, knowledge of local regions of suitability for both primates is needed.
Given the increasing isolation of forest fragments and land-use intensification in Southern Bahia,
we constructed Ecological Niche Models (ENMs) to identify regions of localized high quality
habitat for GHLT’s and Wied’s marmosets. Specifically, we used our ENMs to: (1) identify suitable
areas in the landscape for each species, (2) examine the overlap in suitable habitat for these two
species, and (3) determine the amount of suitable habitat in protected areas.
Methods
Study Area
We focused on the southern Bahia region of the Brazilian Atlantic Forest (Fig 1). The western
portion of this area contains highly fragmented, semi-deciduous tropical rainforest, while more
continuous coastal evergreen rainforest dominates the landscape in the east [17]. Remaining
forest can be broadly characterized as mature forest, regenerating secondary forest, or shade-
cocoa agroforest [16]. Shade-cocoa is an agroforestry system in which middle and understory
trees are removed and replaced with cocoa trees [19]. All three of these habitat types are used
by our focal species [14,20,21]. We defined our focal area by extending the proposed geographic
range for GHLTs (Raboy et al. unpublished data) to natural geographic barriers. Northern and
southern limits were demarcated by major waterways, Rio de Contas in the north and Rio
Jequitinhonha in the south. To the east, the study area extended to the Atlantic Ocean, while the
western limit was defined by the 700m elevation line, reflecting the altitudinal limit for GHLTs
[22]. Wied’s marmosets are believed to occupy most of this region [23] and possibly further
northwest, southwest, and south [11].
Species Occurrence Data
We gathered presence records for GHLTs and Wied’s marmosets from prior studies conducted by
the authors between 2005-2014 that made direct observations (by sightings or camera-trapping)
of naturally occurring populations. When datasets contained multiple observations of the same
social group tracked over time, we included only the first recorded observation. Occurrence
records were filtered using the spatial rarefaction tool in the SDMtoolbox extension [24] for
ArcGIS 10.1 [25]. Rarefaction distances were chosen to reflect the average minimum distance
between two conspecific groups, based on approximate home range radius (455m for GHLTs,
calculated based on Oliveira et al. [19]; and 265m for Wied’s marmoset, calculated based on
Raboy et al. [14] and Rylands [26]). Our final occurrence datasets contained 133 points for GHLTs
and 121 points for Wied’s marmosets, all converted to Corrego Alegre Universal Transverse
Mercator (UTM) Zone 24S.
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Fig. 1 Location of study area in southern Bahia, Brazil. A) Scale map of southern Bahia. Black rectangle indicates
the location of the study area. B) The study area. The shaded region is the landscape analyzed in this study.
Green represents forest, light grey deforested areas. Presence-points used to construct ENMs are also displayed.
Environmental Layers
We considered 24 environmental, climatic, and anthropogenic variables for inclusion in our
analysis (Appendix 1). From those we prioritized the most relevant to our study species on the
basis of expert opinion, further excluding variables due to high correlation (Pearson correlation
coefficient ≥ 0.75). Ultimately, six environmental variables were included in our final models:
distance to urban areas, neighboring forest cover, average annual temperature, elevation, annual
temperature range, and precipitation in the wettest quarter. All environmental variables were
resampled to a spatial resolution of 90 m, chosen to match the scale of our finest resolution
variable, which was elevation. All variables were converted to Corrego Alegre UTM Zone 24S.
Manipulations of environmental variables were performed in ArcGIS 10.1.
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We used a forest cover map, characterizing areas of non-forest and forest, previously generated
by Zeigler et al. [17], and further adapted it by performing a neighborhood analysis. This created
a map of average forest cover smoothed over a larger area, to get a broader sense of the amount
of forest bordering each pixel. Our neighborhood was defined as a circle with a radius of 1,753 m,
the average daily path length of GHLTs [21].
Spatial data on urban centers were obtained from the Biodiversity Corridors in the Atlantic Forest
of southern Bahia database [27]. We created a Euclidean distance surface map for urban areas.
Elevation data were available from NASA’s SRTM mission [28]. Climate data were obtained from
the BioClim global climate datasets developed by Hijmans et al. [29].
Ecological Niche Models (ENMs)
We used the presence-only algorithm Maxent to produce ENMs (version 3.3.3k, [3032]).
Ecological niche models use environmental data and species occurrence records to produce
probability surface maps that highlight the likelihood of species’ occurrence/suitable conditions
in a given area [33,34]. We optimized settings as recommended by Merow, Smith & Silander [35]
in order to reflect species-specific considerations. The regularization parameters (GHLTs β=1.8,
Wied’s marmoset β=3.4) were calculated following Warren & Seifert [36] using ENMTools (version
1.4.3, [37]). Hinge features (i.e. use of linear threshold functions) were excluded to reduce model
complexity and avoid redundancy with the linear features option [32,35]. Additionally, we
included a bias grid to account for varied sampling efforts throughout the region (Appendix 3).
Relative sampling weights were assigned based on the number of species occurrences, amount of
survey work, and number of long term tracking studies of our focal species in these areas.
Final ENMs were based on 100-subsampled replicates, constructed using 70% of species
occurrence records. The remaining 30% of records were used for model evaluation. Only the
logistic outputs, displaying suitability on a scale ranging from 0 (unsuitable) to 1 (suitable), were
considered [32].
Landscape Calculations and Protected Area Evaluation
Final ENMs for GHLTs and Wied’s marmosets were reclassified into suitable and unsuitable areas.
Chosen thresholds for species presence were based on a modified lowest presence threshold
approach (LPT, [38,39]). Due to isolation of habitat patches in the west, deforestation throughout
the region, and the nine-year period of occurrence data collection, we assumed that local
extinctions for either species were possible. To account for this, we used a 10% omission rate.
With 10% omission, 90% of all occurrences were assumed to fall into suitable habitat
(LPT10%,GHLT=0.3, LPT10%,Weid’s= 0.41) (Fig 2). Additionally, within suitable regions, we distinguished
highly suitable’ areas from moderately suitable areas using a more stringent 40% omission
threshold, given that some metapopulations may be persisting in suboptimal habitat (LPT40%,GHLT=
0.67, LPT40%,Wied’s= 0.55) (Fig 2). The amount of moderately and highly suitable habitat for GHLTs
and Wied’s marmosets, as well as overlapping moderately and highly suitable habitat, was
measured on maps reclassified based on LPT thresholds.
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Fig. 2 Suitability values associated with species’ occurrence points from logistic ENM outputs. Vertical lines
represent suitability thresholds based on a modified LPT assuming 10% omission rate (solid line) and 40%
omission rate (dashed line). Above these values, habitat is assumed to be suitable and highly suitable,
respectively, for species. Suitability value histograms are labeled with respective species names and LPT
values.
We evaluated the suitability of protected areas in the study region with IUCN classifications I-III
(large natural areas set aside to preserve biodiversity or ecological processes [40]). This included
four areas: Una Biological Reserve, Una Wildlife Refuge, Serra das Lontras National Park, and Serra
do Conduru State Park. Additionally, we assessed a cluster of privately owned reserves belonging
to the company Veracel, which have served as recent reintroduction sites for GHLTs.
Finally, using the raw logistic Maxent outputs, we calculated the average suitability of habitat
inside protected areas for GHLTs and Wied’s marmosets using all raster pixel values inside reserve
boundaries. To examine differences in average suitability, confidence intervals based on standard
deviation were compared among protected areas. Using reclassified LPT maps, we also measured
the amount of suitable habitat and overlapping suitable habitat for each species within protected
area boundaries.
Table 1 Amounts and percentages of suitable habitat in the landscape and protected areas for GHLTs and
Wied’s marmosets.
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Suitability
Category
Amount of Habitat (km2) and Percentage of Landscape
Amount Under
Protection
Landscape2
Protected Areas3
GHLT
WM
Overlap
GHLT
WM
Overlap
GHLT
WM
Moderately
Suitable
9,115 (31%)
10,667 (36%)
4995 (17%)
336 (47%)
194 (27%)
170 (24%)
3%
2%
Highly
Suitable
1,544 (5%)
4,975 (17%)
1474 (5%)
316 (44%)
488 (68%)
313 (43%)
20%
9%
Suitable1
10,659 (36%)
15,642 (53%)
9809 (33%)
651 (90%)
682 (95%)
634 (88%)
6%
4%
1Suitable = combined moderately and highly suitable habitat
2Percentages based on total study area
3Percentages based on combined area of all protected areas in the landscape
Results
Landscape Patterns of Suitability
Ecological niche models had Area Under the Curve (AUC) values of 0.872 0.024SD) for GHLTs
and 0.782 (± 0.032SD) for Wied’s marmosets. The minimum training presence logistic threshold
for ENMs was 0.147 (± 0.026SD) for GHLTs and 0.302 0.035SD) for Wied’s marmosets. Based
on percent contribution (PC), the environmental variables that contributed most to the final
models for GHLTs were neighboring forest cover (PC=72.6%) and annual temperature range
(PC=10.9%) (Appendix 2). Response curves indicated that suitability of habitat increased with
increasing neighboring forest cover and decreased at low values of annual temperature range
(Appendix 4). The environmental variables that contributed most to final models for Wied’s
marmosets were neighboring forest cover (PC=70.2%) and distance to urban areas (PC=17.8%)
(Appendix 2). Response curves suggested that the most suitable areas were those with more
neighboring forest cover located farther away from urban areas (Appendix 5).
Reclassified models based on modified LTP-thresholds indicated differing amounts of suitable
habitat in the landscape for the two primate species (Fig 3, Table 1). Thirty-six percent of the
study area (10,659 km2) was suitable for GHLTs, of which 14% (5% of the study area, 1,544 km2)
was highly suitable habitat. Suitability scores associated with GHLT presence points took on a wide
range of values (Fig 2). Models for Weid’s marmosets indicated that 53% of the study area (15,642
km2) was suitable for the species, of which 31% (17% of the study area, 4,975 km2) was highly
suitable habitat. The distribution of suitability scores for Weid’s marmosets’ presence points was
narrower than that for GHLTs (Fig 2).
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Fig. 3 Reclassified ENMs for GHLTs and Wied’s marmosets. Maps display areas classified as both
moderately suitable and highly suitable. Forest cover is displayed in green for reference.
Presence of GHLTs and Wied’s marmosets was most strongly defined by neighboring forest cover.
The majority of suitable areas for both species were confined to the eastern part of the study
area, within remaining regions of continuous forest cover. Additional suitable areas for GHLTs and
Wied’s marmosets were also identified in the west, in some of the larger remaining forest
fragments. The largest dissimilarities in suitable habitat were the northeast and southwest regions
of the study area. Here, large portions of habitat were suitable for Wied’s marmosets, but not for
GHLTs (Fig 3). Despite dissimilarities in suitable regions for both species, 33% percent of the study
area (9,809 km2) was overlapping suitable habitat (Fig 4). Of this, 15% was overlapping highly
suitable habitat (5% of the study area, 1,474 km2).
Table 2 Amount and percentages of protected areas considered suitable for GHLTs and Wied’s
marmosets. The amount of overlapping suitable habitat inside the boundaries of each protected
area is also reported.
Suitability of Protected Areas
Protected Area
Amount of Protected Area (km2)
Moderately Suitable
Highly Suitable
GHLT
WM
Overlap
GHLT
WM
Overlap
Una Biological Reserve
39 (21%)
12 (6%)
10 (6%)
145 (79%)
172 (93%)
143 (77%)
Una Wildlife Refuge
95 (41%)
62 (26%)
60 (26%)
121 (52%)
151 (64%)
120 (51%)
Serra das Lontras
National Park
123 (74%)
69 (42%)
68 (41%)
40 (24%)
83 (50%)
40 (25%)
Serra do Conduru
State Park
49 (52%)
36 (38%)
17 (19%)
0
58 (62%)
0
Veracel
Reintroduction Sites
30 (72%)
17 (39%)
15 (34%)
9 (22%)
25 (60%)
9 (22%)
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Protected areas preserved suitable habitat for both GHLTs and Wied’s marmosets (Fig 4). There
were high amounts of moderately and highly suitable habitat for both species in Una Biological
Reserve, Una Wildlife Refuge, Serra das Lontras National Park, and the reintroduction sites (Table
2). These conservation units also contained large amounts of overlapping suitable habitat (Fig 4).
In contrast, Serra do Conduru State Park contained considerably less suitable habitat for GHLTs
than for Wied’s marmosets.
Fig. 4 Overlapping suitable habitat in the study area for GHLTs and Wied’s marmosets. Areas of
overlap represent combined moderately and highly suitable classes. Protected areas are
indicated. Forest cover is displayed in green.
Average suitability measures for each protected area indicated that all of these areas were
suitable for both species (i.e., average suitability and confidence intervals fell above or overlapped
with the minimum suitability threshold) (Fig 5). Average suitability scores of protected areas
ranged between 0.29 (±0.18SD) and 0.73 (±0.08SD) for GHLTs. Average suitability scores of
protected areas for Wied’s marmosets ranged between 0.43 (±0.12SD) and 0.67 (±0.07SD). Serra
do Conduru State Park had a much lower average suitability for GHLTs than the other protected
areas. Average suitability scores within protected areas were similar between species for all
reserves, except Serra do Conduru, where average suitability was lower for GHLTs (based on
confidence intervals).
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Although well represented in protected areas, only 3% of all moderately suitable and 20% of all
highly suitable habitat in the study area was protected for GHLTs (Table 1). For Wied’s marmosets
2% of moderately suitable and 9% of highly suitable habitat was protected (Table 1). Considering
total suitability (moderately and highly suitable habitat combined), protected areas contained
only 6% of suitable GHLT habitat and 4% of suitable Wied’s marmoset habitat (Table 1).
Discussion
Species Distribution
Our models demonstrate that suitable habitat for GHLTs and Wied’s marmosets is limited and
mostly unprotected. Model predictions were largely consistent with expectations based on the
ecological needs of these sympatric arboreal primates. Neighboring forest cover was the strongest
contributing variable to models, and the most suitable habitat for both species was located in the
largest block of contiguous forest in the study area. This is the only fragment thought capable of
supporting a genetically viable, self-sustaining population of GHLTs under high-risk scenarios [17].
For both species, comparatively less suitable habitat was identified in the western region of the
study area. Here, high rates of habitat conversion have resulted in relatively small, isolated forest
fragments surrounded by cattle pasture. The likelihood of extinction is thought to increase in such
fragments, which are often not considered large enough to support viable primate populations in
the long-term [17,41,42]. Moreover, dispersal between fragments, at least for GHLTs, is thought
to be unlikely and infrequent [16].
Within the otherwise suitable eastern forest block, there was an absence of suitable habitat for
GHLTs in the northeast corner. This region, in and around Serra do Conduru State Park (Figure 4),
was noted as a lacuna by Pinto and Rylands [43] in their 1991-93 survey. Disagreement exists
about whether it is a natural gap in the GHLT distribution or a result of more recent anthropogenic
changes [43]. It has been a long-standing enigma for lion tamarin biologists, as the region contains
forest types thought to be good habitat for GHLTs [15,1921,44]. Additionally, researchers
recently identified a high density of Aechmea and Hohenbergia bromeliads in this region [45],
known to be important resources for GHLTs [21,46,47]. However, despite seemingly ideal habitat,
our models indicate GHLT presence may be limited in the northeast by certain climatic factors. On
the basis of variable response curves (Fig S2), we suggest that high levels of precipitation and/or
low variability in annual temperature range might explain the absence of GHLTs, although the
reasons why are unclear. These climatic factors could be interacting to limit the diversity of animal
prey or another critical resource used by this species. Further research to understand the
limitations imposed by climatic conditions on GHLTs in this region is needed.
Our models identify several areas in the highly fragmented southwestern region as suitable for
Wied’s marmosets. This may be contrary to expectation for an arboreal species, but Wied’s
marmosets exhibit a high degree of ecological and behavioral plasticity [14,26,48]. In fact, they
have been observed to colonize urban environments, suggesting an ability to rapidly adapt to
changing conditions [48]. The flexibility of Wied’s marmosets can be partially attributed to
specialized dentition that enables them to extract exudates from trees [14,26,49]. This feeding
behavior ensures continued access to stable sources of carbohydrates [49]. Moreover, marmosets
have smaller home ranges (average 38.9 ha, range 34-39 ha; Raboy et al. [14]) than GHLTs
(average 83 ha, range 22-197 ha; Oliveira et al. [44]). Wied’s marmosets may therefore be better
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able to maintain the social integrity of their groups in smaller forest patches without suffering
social Allee effects. Thus, gummivory and range size are both socioecological factors that may
explain why Wied’s marmosets are found in smaller, fragmented areas of forest.
Fig. 5 Average suitability of protected areas for GHLTs and Wied’s marmosets. Average suitability for the entire landscape is
included for reference on the far right. Values were calculated from raw logistic ENM outputs. Error bars represent standard
deviation. Horizontal lines represent suitability thresholds for GHLTs and Wied’s marmosets based on a modified LPT assuming
10% omission rate. Above this value, habitat is assumed to be suitable for species.
Protected Areas and Conservation Prospects
Given a growing need for accountability in management decisions, it is important to validate
locations of existing reserves. Our models indicate existing protected areas contain large amounts
of moderately and highly suitable habitat for GHLTs and Wied’s marmosets, with one exception.
Serra do Conduru contained minimal suitable habitat for GHLTs. Additionally, our models
indicated that the recent reintroduction sites for GHLTs in the southern part of their distribution
contained large amounts of moderately and highly suitable habitat for the species. These sites
were originally selected on a presumed ability to sustain viable populations and lack of native
GHLTs (MCM Kierulff, personal observation). Further assessing these areas for suitability based
on environmental and climatic conditions indicates that populations may do well in these areas.
Given concerns about future deforestation in southern Bahia [10], conservation actions to protect
as much of the region’s suitable habitat as possible would be beneficial for the preservation of
GHLTs and Wied’s marmosets. Although protected areas contained suitable regions for both
species, only 6% of all suitable habitat for GHLTs and 4% for Wied’s marmosets is currently
protected in the study area. Given the congruence in suitable areas for GHLTs and Wied’s
marmosets, targeting the regions of overlapping suitable habitat identified in our maps would be
an effective way to achieve protection for both primates and other arboreal frugi-faunivore guild
members. Moreover, protecting regions of overlapping suitable habitat may help preserve the
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unique behavioral associations between GHLTs and Wied’s marmosets. Prior work suggests these
mixed species associations [14,15,26] provide benefits in terms of increased foraging efficiency
[13] and predator surveillance [15]. Given the likely survival benefits of forming associations,
protecting areas of shared suitability could promote continued interaction and thus facilitate each
species’ persistence. Currently, only 6% of overlapping suitable habitat in the study area is
protected.
Limitations and Future Directions
Although neighboring forest cover was the strongest contributing variable in our final models
(Appendix 2), this variable did not distinguish among forest types, which vary in this region.
Abundant forest cover in the eastern portion of the study area is composed of shade-cocoa,
secondary and mature forests [16], which differ in canopy cover and resources [19,20].
Additionally, these forest types are under different deforestation pressures. While the removal of
late secondary and mature forest is largely limited by the Brazilian forest code (Federal Law No.
12651, of May 25, 2012) and “Lei da Mata Atlântica” (Federal Law No. 11.428, of December 22,
2006), tree removal in shade-cocoa agroforest is likely to be authorized (Federal Law No. 12651
of May 25, 2012 and INEMA Ordinance No. 10225 of August 18, 2015). Differences in
deforestation and variance in canopy cover and resources are important factors that impact the
suitability of habitat for GHLTs and Wied’s marmosets. Unfortunately, a reliable map detailing
different forest cover types does not exist for our study area. Eventual inclusion of such a map
would aid conservation planning. This may be especially important for GHLTs, given their different
responses to, and risk in, different forest types [15,21,50].
Determining the role rainfall or other correlated climatic variables may play in limiting GHLTs in
the northeast will be an important avenue of future research. Given the relatively well-preserved
status of forest in this region and the existence of a protected area, arguments could be made to
consider this area for future reintroductions. We stress the need for thorough evaluation to
understand the trophic impacts of high rainfall and low temperature variability on GHLTs or key
plant and animal species they rely on, before management action occurs. Furthermore, given the
threat of climate change, understanding how rainfall, temperature variation, and other climatic
variables may change in the future is a key consideration for management. Recent work indicates
that climatically suitable habitat for GHLTs, particularly in the western portion of their range, will
greatly decrease under current climate change scenarios [51]. Although the Meyer et al. [51] work
did not consider Wied’s marmosets, climate change will likely impact them as well. Additionally,
changes to climate may interact synergistically with deforestation [52] to further threaten both
species, highlighting the need to understand the effects of changing climatic conditions on the
distribution of suitable habitat in the landscape.
Investigation of the behavioral plasticity of Wied’s marmosets is another valuable research area.
Wied’s marmosets have been observed to be adept at living in urban areas [48] and are often
found in degraded habitat [23]. We caution that these observations do not mean this species does
not need high quality forest. Despite the apparent ecological flexibility of Wied’s marmosets,
response curves (Appendix 5) indicate that the more suitable areas are those with more forest
cover, farther away from urban areas. This suggests that natural habitat is ideal where available.
It will be useful to compare differences in the behavior of groups living across a spectrum of
habitat types (i.e., mature forest, degraded forest, urban areas) to understand this species
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capacity for rapid adaptation and the impacts of habitat on their behavior. This information may
aid in future management action for this species.
Fig. 6 Study species and landscape. A) Golden-headed lion tamarin. Photo by Kris D´Août. B) Shade-cocoa
agroforest. Note the lack of midstory trees. Photo by Leonardo Oliveira. C) Wied’s black-tufted ear marmoset.
Photo by Kris D´Août. D&E) Fragmented forests typical of the region. Photos by Becky Raboy.
Implications for Conservation
The ENMs we produced for the endangered GHLT and near-threatened Wied’s marmoset are a
broad approach to understanding habitat suitability and degree of protection in the landscape for
these species (Fig 6). This work is a step towards integrating multi-species assessments of
suitability into conservation planning for the region. Our studies reveal spatial patterns of
suitability useful for developing or enhancing management programs. In particular, many of the
unprotected areas of suitable habit for focal species were also regions of overlapping suitable
habitat, potentially ideal future conservation targets. Importantly, protecting shared areas of
suitability may also help to preserve the beneficial behavioral association between GHLTs and
Wied’s marmosets. We urge future researchers to make use of techniques considered here and
to consider fine-scale habitat variation and population viability analyses among multiple species
to further identify areas of importance for Bahian biodiversity.
Acknowledgments
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We thank Marie-Josee Fortin, Christopher Searcy, Resit Akçakaya, and Kevin Shoemaker for advice
and feedback during model building. Additionally, we appreciate Christopher Searcy and John
Ratcliffe’s reviews of earlier versions of the manuscript. Financial support was provided by an
NSERC Discovery Grant to Becky Raboy and additional travel support from NSF RCN grant DEB-
1146198. In addition, all authors thank respective funding sources and institutional support, as
well as individuals who assisted with the original collection and/or processing of data used in the
present analysis (see Appendix 6). Author Contributions, CG and BER designed study. BER, CRC,
LC, KMV, MCMK LGN, LCO, BMRT, SLZ provided data for analysis. CG performed analyses. CG and
BER wrote the first draft of the manuscript, and CRC, KMV, MCMK, LGN, LCO, BMRT, SLZ
contributed to subsequent writing.
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Appendix 1: Environmental Variables Originally Evaluated
Table A1 The environmental, climatic, and anthropogenic variables originally considered for
inclusion in the analysis with their data sources. Variables included in final models are bolded.
Environmental Variable
Source
Annual Mean Temperature
WorldClim Global Climate Database1
Mean Diurnal Range
WorldClim Global Climate Database1
Isothermality
WorldClim Global Climate Database1
Temperature Seasonality
WorldClim Global Climate Database1
Max Temperature of Warmest Month
WorldClim Global Climate Database1
Min Temperature of Coldest Month
WorldClim Global Climate Database1
Temperature Annual Range
WorldClim Global Climate Database1
Mean Temperature of Wettest
Quarter*
WorldClim Global Climate Database1
Mean Temperature of Driest Quarter
WorldClim Global Climate Database1
Mean Temperature of Warmest
Quarter
WorldClim Global Climate Database1
Mean Temperature of Coldest Quarter
WorldClim Global Climate Database1
Annual Precipitation
WorldClim Global Climate Database1
Precipitation of Wettest Month
WorldClim Global Climate Database1
Precipitation of Driest Month
WorldClim Global Climate Database1
Precipitation Seasonality
WorldClim Global Climate Database1
Precipitation of Wettest Quarter
WorldClim Global Climate Database1
Precipitation of Driest Quarter
WorldClim Global Climate Database1
Precipitation of Warmest Quarter
WorldClim Global Climate Database1
Precipitation of Coldest Quarter
WorldClim Global Climate Database1
Neighboring Forest Cover
Sara L. Zeigler2
Distance to Urban Areas
Biodiversity Corridors in the Atlantic Forest of
Southern Bahia database3
Distance to Waterways
Biodiversity Corridors in the Atlantic Forest of
Southern Bahia database3
Distance to Roadways
Biodiversity Corridors in the Atlantic Forest of
Southern Bahia database3
Elevation
NASA’s SRTM Mission4
1 Hijimans et al. [29]
2 Zeigler et al. [17]
3 Prado et al. [27]
4 Jarvis et al. [28]
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Appendix 2: Percent Contribution of Environmental Variables
Table A2 Percent Contribution of environmental variables to final Maxent models for GHLTs and
Wied’s marmosets.
Environmental Variable
Percent Contribution
GHLT
WM
Forest Cover
72.6%
70.2%
Annual Temperature Range
10.9%
3.3%
Distance to Urban Areas
7.7%
17.8%
Average Annual Temperature
5.8%
1.2%
Precipitation in the Wettest Quarter
2%
4.4%
Elevation
1%
3.1%
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Appendix 3: Bias Grid
Fig. A3 Bias grid used in analyses. The map delineates three levels of sampling effort for the
study region.
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Appendix 4: Response Curves for GHLT Models
Fig. A4 Response curves for environmental variables in GHLT models. A) Marginal response
curves for environmental variables based on full models B) Response curves for environmental
variables based on a Maxent model built using only that variable.
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Appendix 5: Response Curves for Wied’s Marmoset Models
Fig. A5 Response curves for environmental variables in Wied’s marmoset models. A) Marginal
response curves for environmental variables based on full models. B) Response curves for
environmental variables based on a Maxent model built using only that variable.
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Appendix 6: Individual author acknowledgements for data contributions
For data points and spatial processing from our previous studies (used herein) we thank: BER -
Jim Dietz, Saturnino De Sousa, Paulo Cruz, José Renato, Daniel Batista, Gilvan Gomes Mota,
Gilvânio Gomes Mota, and Jiomário dos Santos Souza. Funding was provided by The World
Wildlife Fund, Durrell Wildlife Conservation Trust, the Lion Tamarins of Brazil Fund, the Tulsa
Zoo, and Sigma Xi; BER and LGN- Nayara Cardoso and Gabriel Santos. Funding was provided by
the Association of Zoos and Aquariums/Disney Worldwide Conservation Fund, the Critical
Ecosystem Partnership Fund, the International Primatological Society, and the Lion Tamarins of
Brazil Fund; BMRT - Tatiana Alves Fona e Franco, Paulo César Pires Diniz da Cruz, Ivan dos Santos
Leão, Weilton Rocha dos Santos, Antônio Hugo Ferreira da Silva, Netonias Rocha dos Santos,
Leandro da Silva Oliveira, Felipe Souza Gudinho, Nereyda Falconi Lopez, Anna Carolina Cornélio
Henriques, Letícia Leite Ferraço, Janete G. Abrão-Oliveira, Danilo Barbosa Mendonça. Funding
was provided by Instituto Chico Mendes de Conservação da Biodiversidade; CRC- Rubens Vieira
Lopes, Eduardo Mariano Neto, Sirleide Batista dos Santos, Ana Paula Silva and the owners and
employees of the farms where studies were developed. Funding was provided by the European
Union, the Brazilian Ministry of the Environment, Seeds of Change, Fundação de Amparo à
Pesquisa do Estado da Bahia and Fundação de Amparo à Pesquisa do Estado de São Paulo; KMV-
Saturnino De Souza, Paulo Cruz, Josinei da Silva Santos, Antonio Ribeiro Santos Jr, José Alves das
Neves Filho and the Ribeiro and Ozawa families. Funding was provided by the Flemish Ministry
of Economy, Science and Innovation (Belgium), Conselho Nacional de Pesquisa, Scott
Neotropical Fund of the Cleveland Metroparks Zoo, Lion Tamarins of Brazil Fund, National
Lottery of Belgium, Primate Action Fund, Zoological Society of London; LC- Gabriel Santos,
Leonardo Neves and Priscila Suscke. Funding was provided by Petrobras, SAVE Brasil, BirdLife
International, Global Conservation Fund/Conservation International-Brazil; LCO- Fábio Falcão,
Paula Pedreira dos Reis, Lilian Catenacci, Jiomário dos Santos Souza, Edimalvan da Purificação,
and to the owners and their employees of the farms, Almada, Santa Rita, Riachuelo and São
José, the private reserves (RPPNs) Ararauna and Serra do Teimoso and the rural settlement
Bem-te-vi Funding was provided by University of Maryland Biology Department, Seeds of
Change, Lion Tamarins of Brazil Fund, the Wildlife Conservation Society, International
Foundation of Science, the Rufford Small Grants Foundation, Idea Wild, the University of
Maryland Ann G. Wylie Dissertation Fund, Drs. Wayne T. and Mary T. Hockmeyer Doctoral
Fellowship, and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -
CAPES/Fulbright; MCMK- Veracel Celulose S.A., Gabriel Rodrigues dos Santos, and Programa
Nacional de Pós-Doutorado/ Coordenação de Aperfeiçoamento de Pessoal de Nível Superior;
SLZ- Douglas Morton and Alessandro Coelho Marques. Funding was provided by the Explorer’s
Club, Washington Group Exploration and Field Research Grant. The Instituto de Estudos
Socioambientais do Sul Bahia (IESB) provided major institutional support for several of these
projects.
... Lion tamarins (Callitrichidae: Leontopithecus spp.) are small arboreal primates (weighing between 586 g and 653 g) which live in small social groups of an average of seven individuals per group. Leontopithecus chrysomelas are endemic to the southern Atlantic Forest of Bahia, Brazil (Kierulff et al., 2002;Rylands, 1993;De Vleeschouwer et al., 2011) where they live in a highly fragmented area (Guy et al., 2016). ...
... Eggs from Ascarididae, Trichridae, Strongyloididae and coccidian oocysts were reported only in groups from inside the natural reserve. Human disturbed environments, such as cabruca and small patches of disconnected forest, tend to have lower biodiversity than REBIO (Al-Shorbaji et al., 2016;Guy et al., 2016;Costa et al., 2020). Furthermore, the management differences of the environment are essential to determine the establishment and reproduction of the parasites (Grundmann et al., 1976;Bongers & Ferris, 1999;Nunn et al., 2003). ...
... However, parasitological studies can shed light on host health status and vulnerability to parasitic infections in threatened species such as the L. chrysomelas. From the point of view of conservation, the finding of Acanthocephalan eggs may represent a risk for populations of golden-headed lion tamarins in the wild that already may face stress factors such as predation, hunting and human contact Guy et al., 2016;Oliveira et al., 2011). Monteiro et al. (2010) also stated that Acanthocephalan infection results in a significant reduction in tamarin health, which can potentially lead to their death. ...
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We performed coproparasitological testing of free-living golden-headed lion tamarins, Leontopithecus chrysomelas, using the Hoffmann-Pons-Janner method. In total, we collected 118 samples from ten groups: four living in Federal Protected Area and six living in Non-Protected Areas of cocoa farms. Eggs from parasites of the Acanthocephala phylum and Spiruridae, Ancylostomatidae, Ascarididae and Oxyuridae families were identified, as well as the genus Strongyloides (Nematode: Strongyloididae) and phylum Apicomplexa. This is the first description of infection with coccidian, Trichuridae family and Strongyloides spp. in L. chrysomelas. A total of 48% (n= 57) of the animals were infected and the highest prevalence (37.2±SD 8.72, n = 44) was for Acanthocephalidae, followed by Spiruridae (8.5±SD 5.03, n = 10). There was no difference in parasite prevalence by age classes or sex. However, we found higher diversity and prevalence of parasites in animals living in the Federal Protected Area. These results suggest that intestinal parasites may be influenced by environmental factors, such as the management of the areas where the animals live, in addition to the feeding behavior of L. chrysomelas and distinct transmission strategies of parasites. The combination of ecological and demographic data combined with parasitological studies may contribute to conservation programs for this species.
... To the east, the population of GHLTs in Una Biological Reserve represents an important genetic population (e.g., no evidence for a recent genetic bottleneck was found in our study). The REBIO Una and surrounding forests have been considered a potential source population for the conservation of GHLTs because of the likelihood that the population will maintain genetic diversity over time [Holst et al., 2006;Zeigler et al., 2010], and that they are located in a climatically suitable region for GHLT persistence [Meyer et al., 2014;Guy et al., 2016]. However, the maintenance of a viable population of GHLTs in the REBIO Una can be compromised if the process of deforestation in its surroundings continues [Zeigler et al., 2013]. ...
... Recent research has shown that the situation for GHLTs has worsened especially in the western portion of its geographic distribution Zeigler et al., 2010;Meyer et al., 2014]. Only 36% of the habitat within the GHLT distribution area (and study area) is suitable for the species' persistence [Guy et al., 2016]. To the east, rapid loss of their natural habitat, the conversion of cabruca to other agricultural crops or pastures threaten GHLTs [Pinto and Rylands, 1997;Holst et al., 2006;Raboy et al., 2010]. ...
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This study evaluated the genetic structure of wild populations of the endangered primate, Leontopithecus chrysomelas. We tested the assumption that populations of L. chrysomelas, given their larger population size and higher degree of habitat continuity, would have higher genetic diversity and less genetic structuring than other lion tamarins. We used eleven microsatellites and 122 hair samples from different locations to assess their genetic diversity, genetic structure, and to make inferences about the isolation-by-distance. The overall expected heterozygosity (0.51 ± 0.03) and the average number of alleles (3.6 ± 0.2) was relatively low, as is the case in other endangered lion tamarins. Genetic clustering analyses indicated two main clusters, whereas the statistical analyses based on genotype similarities and Fst suggested further substructure. A Mantel test showed that only 34% of this genetic differentiation was explained by the linear distance. In addition to linear distance, structural differences in the landscape, physical barriers, and behavioral factors may be causing significant genetic structuring. Overall, this study suggests that these populations have a relatively low genetic diversity and a relatively high population genetic structure, putting in question whether the presence of agro-forest systems (known locally as cabruca) is enough to fully reestablish functional landscape connectivity.
... However, a group of C. kuhlii with 13 individuals was also found in native forests and cocoa plantations in southern Bahia (Tisovec et al. 2014). C. penicillata is known for its aggressive invasive behavior (Teixeira et al. 2015) while C. kuhlii has a limited and sensitive geographical distribution, not acting as a good colonizer (Guy et al. 2016). The study area, although within the distribution of C. penicillata, has been proposed as an overlapping area for C. kuhlii (Neves 2008). ...
... Tufted-ear marmosets, although known for their ecological flexibility, require resources from native habitats to adapt to a heterogeneous landscape. Patches of a better-quality forest within the rubber landscape and pioneer vegetation in the rubber inter-rows are necessary for longterm survival of the populations (Guy et al. 2016). ...
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With the loss and fragmentation of tropical forests, the survival of primates depends on their ability to adapt to human-introduced modifications in their habitat. Marmosets are known for their ecological and behavioral plasticity and have been registered in various agricultural landscapes. Our goal was to describe the ecology of tufted-ear marmosets (Callithrix sp.) in a rubber/forest landscape, monitoring their use of habitat and diet. We followed two groups using radio telemetry and visual observations for nine months at the Michelin plantation Ltd. in Bahia, Brazil. Both groups used mainly pioneer forest and rubber with pioneer vegetation more than expected according to availability, even though they explored all types of vegetation. Rubber monocultures act as corridors for marmoset locomotion among more suitable habitats. Feeding, gummivory and socialization were mainly performed in the pioneer forest (with or without rubber), in which most sleeping sites and food sources were found. Groups of marmosets can incorporate agroforest matrixes to their area of use and activity patterns. Maintenance of marmosets in fragmented landscapes might be favored by their diet flexibility, with the use of resources such as gum and fruit, including exotic plants. Although known for their ecological flexibility, marmosets do require certain resources to be present in native habitat to adapt to agricultural landscapes. Patches of forest within a rubber landscape and pioneer vegetation in the rubber inter-rows should be considered to maintain populations of Callithrix in rubber landscapes.
... We anticipate that the conservation practices here suggested, namely installing passages in more sites across the road network and the monitoring process, might have a positive spillover effect in other sections of BR-101 as well as in other road networks in Brazil. For example, BR-101 also fragments the habitat of two other threatened arboreal primates within the Atlantic Forest, the golden-headed lion tamarin (Leontopithecus chrysomelas) and Wied's marmoset (Callithrix kuhlii), and is known to hinder inter-population gene flow and to reduce habitat suitability for these species (Guy et al., 2016;. These measures could also benefit other endangered forest-dwelling species occurring in the region, including threatened mammals as the maned sloth (Bradypus torquatus), and birds, including Salvadori's antwren (Myrmotherula minor) and the banded cotinga (Cotinga maculata). ...
... We anticipate that the conservation practices here suggested, namely installing passages in more sites across the road network and the monitoring process, might have a positive spillover effect in other sections of BR-101 as well as in other road networks in Brazil. For example, BR-101 also fragments the habitat of two other threatened arboreal primates within the Atlantic Forest, the golden-headed lion tamarin (Leontopithecus chrysomelas) and Wied's marmoset (Callithrix kuhlii), and is known to hinder inter-population gene flow and to reduce habitat suitability for these species (Guy et al., 2016;. These measures could also benefit other endangered forest-dwelling species occurring in the region, including threatened mammals as the maned sloth (Bradypus torquatus), and birds, including Salvadori's antwren (Myrmotherula minor) and the banded cotinga (Cotinga maculata). ...
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Roads have a myriad of negative effects on biodiversity, ultimately threatening the persistence of populations. In this Perspective we call attention to an extreme example , where the entire current geographic range of the endangered golden lion tama-rin (Leontopithecus rosalia, GLT) is bisected by a major highway that is being widened to four lanes. We believe that the planned mitigation actions are not enough to reduce the expected increase of barrier effects and road mortality. These impacts may lead to a sequence of cascading effects that could jeopardize the conservation actions that prevented the extinction of GLTs three decades ago. We identify specific road sections along the highway and accompanying paved roads in the region that if equipped with tailored over passages would greatly reduce the road Fernando Ascensão and Bernardo B. Niebuhr shared first authorship.
... They maintain large home ranges ) but their groups are relatively small, ranging from 3 to 13 individuals (BER and JMD, unpublished data). There are a growing number of studies on L. chrysomelas, particularly focused on habitat use (de Almeida Rocha et al. 2015;Catenacci et al. 2016;De Vleeschouwer and Oliveira 2017), the effects of ongoing habitat fragmentation Zeigler et al. 2013;Guy et al. 2016), and disease ecology (Bueno et al. 2015;Aitken et al. 2016). However, little is known about the relationship between group composition and reproductive success. ...
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Cooperative breeding is a system where helper individuals care for breeding individuals’ offspring. As a result, social environment is likely to play a key role in regulating reproductive success. In primates, cooperative breeding is only found in the family Callitrichidae. Callitrichid males typically provide more infant care than non-breeding females, and in many callitrichid species, the presence of multiple males has been linked to infant survival. Leontopithecus chrysomelas (the golden-headed lion tamarin) is an endangered callitrichid found in the Atlantic Forest of Brazil. We used long-term data for wild L. chrysomelas to assess the influence of social group composition on reproductive success. Our survival model found that infant survival was negatively associated with group size, but this cost was mitigated by the presence of multiple adult males vs a single adult male. We also found that infants raised in groups with multiple adult males exhibited faster growth rates and higher adult weights than infants raised with a single adult male. This study adds novel evidence for the positive influence of adult males on callitrichid reproduction, demonstrating that adult males influence infant growth, as well as survival, in wild populations of cooperatively breeding primates. We suggest that social group composition, particularly the presence of adult males, be considered in future conservation strategies given its importance for reproductive success. Significance statement In cooperatively breeding species, group members care for breeding individuals’ offspring. Due to this care, group composition may have a strong influence on infant success. In cooperatively breeding primates, males often provide more infant care than females. We investigated the influence of group composition on infant success in a cooperatively breeding primate, the golden-headed lion tamarin. Using long-term field data, we found that infant survival decreased as group size increased. However, this effect was reduced when multiple adult males were present in the group compared to a single male. We also found that infants grew faster and reached larger adult weights in the presence of multiple adult males compared to a single male. Our results demonstrate the importance of group composition for cooperative breeders and provide new evidence for the positive influence of adult males on cooperatively breeding primate infants.
... region in the Brazilian Atlantic Forest. The EMS use both environmental data and species occurrence data to create probability surface maps that depict the likelihood of occurrence of a certain species in a given area. These maps take into account the suitable conditions for the species as well as the probability of finding the species in the area.Guy et al. (2016) concluded that only 36 % of the study area was suitable for L. chrysomelas. This percentage amounts for a total of 10,659 Km 2 . Moreover, they found that 33% of the studied area can harbour suitable conditions for both species. In addition, their results showed that only 6% of the study areas identified as suitable areas were currently ...
Thesis
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The Atlantic Forest of Brazil is the second largest rainforest of south America and one the World´s biodiversity hotspots. However, it is highly fragmented and deteriorated due to intense deforestation that started around the time of colonization, and continued during the industrialization and urban development that followed. It is home to many plant and animal species among which we find the lion tamarins (Leontopithecus spp.). The lion tamarins are a genus of " New World Primates " which comprises four species: the golden lion tamarin (L. rosalia), the golden-headed lion tamarin (L. chrysomelas), the black lion tamarin (L. chrysopygus) and, the black-faced lion tamarin (L. caissara). The former three species are listed as Endangered by the IUCN, meanwhile L. caissara is listed as Critically endangered. Thus, all four species are subject to conservation projects to increase their numbers in the wild and to mitigate the effects of habitat fragmentation on them. Moreover, a " Population and Habitat Viability Assessment " (PHVA) has been organized three times, with the aim of proposing new conservation actions to preserve these species. Thus, the aim of this paper is to review which actions have been implemented since the last PHVA (2005) and what is still needed to be done to preserve the four species. I conclude that despite all the efforts, the species are still in risk and is still necessary to actively work in-situ improving their habitats. Furthermore, it is also of great importance to keep on conducting basic research to better understand which are the requirements of all four species. Finally, it is necessary to engage local communities in hands-on conservation, as well as, applying a multidisciplinary approach that encompasses knowledge from the social sciences and the scientific community.
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As habitat for the golden-headed lion tamarin (GHLT; Leontopithecus chrysomelas) in Brazil's Atlantic forest becomes smaller and more fragmented, remaining large forest patches may be critical to the persistence of the species. The objectives of our study were to identify the forest patch size that could support a viable population of GHLTs under a range of risk scenarios and to locate patches meeting these size requirements. We found the self-sustaining minimum viable population (MVP) size of GHLTs using the simulation program Vortex under a baseline model and under several anthropogenic disturbance models. We multiplied the MVP size determined in each model scenario by low, medium, and high GHLT population densities to estimate a minimum area requirement. We then used a forest cover map derived through a supervised classification of 2004-2008 Landsat 5TM imagery to locate forest patches meeting the range of minimum area requirements. We found that the MVP size of GHLTs is 70-960 individuals, requiring a forest patch size of 700-18,113 ha depending on the risk level or scenario considered. We found one forest patch that could support a genetically viable, self-sustaining population of GHLTs under the highest level of risk. However, only one federally protected reserve known to currently support GHLTs exists within the range of the species while continuing deforestation, land conversion, and construction projects are real and major threats to the remaining GHLT habitat. Research into the quality and occupancy of the largest patches highlighted here as well as additional protection of habitat needs to be a priority for GHLT conservation. © Zeigler, Sara L., William F. Fagan, Ruth DeFries, and Becky E. Raboy.
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Ecological and behavioral plasticity allow marmosets, genus Callithrix, to adapt and succeed in urban areas. This research assess proximity and relationships between Wied's marmoset Callithrix kuhlii, domestic animals and residents of Ilheus, Bahia, Brazil. We collected data on the species' urban ecology and biology, since it has been little studied so far. Tools for data gathering included semi-structured interviews, direct observations and GPS-mapping. There were sightings within the three major districts of Ilheus, with 37% of positive questionnaires (n = 359) for marmoset sighting at least weekly. Therefore, marmosets were considered common in this city. Most records and frequent sightings were associated with secondary forest fragments, backyards with fruit trees and mangroves. Marmosets travel among urban fragments using electrical and phone wires and crossing roads. There is a relatively small number of accidents when compared to the number of sightings, with electrocution as the most common. Visitation of marmosets to households, attracted by food provisioning, was considered frequent. People feel pity for the marmosets and lure them to their houses through food, but offered items are not always suitable. Marmoset exploration of uncommon habitats, such as mangroves, might be driven by a lack of larger forest fragments within the city.
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The Atlantic Forest is a global hotspot of biodiversity that may be on the verge of ecological collapse. Current changes in forest legislation have increased the debate concerning policy impacts on land-use and the consequences for biodiversity conservation and ecosystem services provision. This paper evaluates the impact of three environmental policy options (National Forest Act from 1965-NFA65, Business as Usual-BAU, National Forest Act from 2012-NFA12) on land-use patterns and ecosystem services in the southern Atlantic Forest. InVEST (the Integrated Valuation of Environmental Services and Tradeoffs tool) was used to model ecosystem services. Synergies and tradeoffs between commodities, erosion regulation, carbon storage and habitat for biodiversity were assessed with the Spearman Correlation Test. The NFA65 produced the largest gains for forest ecosystem services, while BAU favored commodities expansion. The NFA12 approaches the baseline, contributing less to the provision of ecosystem services and biodiversity conservation.
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The intensification of agricultural activity can have profound impacts on biodiversity. We evaluated the influence of the landscape's percentage of forest cover and shaded cocoa plantations on the community of zoochorous bromeliads in southern Bahia, Brazil. We selected two contrasting landscapes, one dominated by Atlantic tropical rainforest and the other by traditional cocoa plantations. In each landscape we sampled three forest fragments and three areas of cocoa plantation, where we conducted a survey of epiphytic bromeliads of the genera Aechmea and Hohenbergia in eight plots of 400 m 2 in each area. The number of trees differed between landscapes and habitats, and was higher in forest fragments than in shade cocoa plantations, but the number of phorophytes was similar between landscapes and habitats. Highest richness of Aechmea and Hohenbergia species was found in forest fragments in landscapes where forests are predominant. Contrary to expectations, the richness in the other areas was relatively low, and extremely low in the landscape dominated by cocoa plantations, ranging from zero to four species per fragment. Bromeliad abundance was not different among landscapes and habitats, but the shade cocoa plantations located in predominant agroforest landscape showed the higher number of stands. Moreover, the species found in the cocoa plantations were more drought-tolerant species. These results suggest that the conservation of species of these genera depends on factors such as the conservation status of each forest fragment and the microclimatic alterations in the habitats, and not only on the percentage of forest in the landscape per se.
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The golden-headed lion tamarin, Leontopithecus chrysomelas, was formerly thought to range below 300–400 m above sea level, because of changes in forest physiognomy and lack of resources at higher elevations. We document four cases (from two studies) of L. chrysomelas ranging above 500 m, and investigate the behavior of two groups that ranged from 100 to 700 m. We discuss the possibilities that 1) resources may be more abundant at higher elevations than previously thought, 2) a shift may have occurred in the species elevation-use patterns in response to forest loss and degradation at lower elevations, and that 3) golden-headed lion tamarins require low elevations for access to resources but use higher altitudes to travel between lower lying areas. Understanding exactly how L. chrysomelas uses higher elevations and the limits of its upper ranging patterns has significant conservation implications for this endangered species. Even without being able to definitively ascertain that golden-headed lion tamarins are able to settle in stable home ranges at higher elevations with adequate resources for breeding and survival, they certainly move through these habitats. We suggest, therefore, that slopes and ridge-tops should be taken into account as corridors to be preserved for gene flow in the otherwise highly fragmented L. chrysomelas metapopulation.
Chapter
The effect of forest fragmentation on arboreal species can be measured and quantified at various scales using a variety of technical approaches. Multidisciplinary studies or networks of studies that integrate information across scales and fields of expertise provide the most comprehensive understanding of fragmentation. We illustrate the use of a multifaceted approach to assess the threats, and conservation status, of golden-headed lion tamarins (Leontopithecus chrysomelas, GHLTs), an endangered primate residing in a highly complex landscape of Southern Bahia, Brazil. Most remaining habitat is in the hands of private landowners. In the west, the cattle industry has contributed to the severe fragmentation of forests and led to small and extremely isolated fragments. Local GHLT extinctions are occurring quickly. In the east, declining market prices of cocoa and the rapid spread of a fungal disease have devastated cocoa production, and once rather contiguous expanses of shade-cocoa forests are rapidly being converted to unsuitable habitat. GHLTs have been studied at the population level, with increasingly more information being generated on their behavior, ecology, demographics, habitat, genetics, and health. GHLTs (and their landscapes) have also been studied at broader levels, yielding vital information regarding habitat change and fragmentation trends over time, predictors of the presence and absence, and viability and threat analysis via simulation modeling. Collectively, this information is giving rise to a more integrated sense of the mechanisms by which anthropogenic pressures are affecting GHLTs. Additional factors regarding the rich history of GHLT conservation efforts are discussed in this chapter. In an environment as spatially and temporally dynamic as Southern Bahia, a conservation management approach involving evaluation, adaptation, synthesis, and prioritization is critical towards developing efficient conservation action plans sensitive to the continuously changing socioeconomic context.
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