806 B. Moraes et al.


TABLE 1 Results of the species distribution models for the three studied primates, number of location records included in the models (N), results of the statistical tests used to evaluate model discrimination ability (area under the receiver operator curve; AUC) for training and test datasets and the per cent contribution of the different environmental variables.


Species (N)


Alouatta belzebul (66) 0.91 Sapajus flavius (33)


0.98 Sapajus libidinosus (77) 0.88


AUC train AUC test 0.87


0.97 0.82


Environmental variables contribution (%)1 Bio2 Bio3 Bio8 Bio11 Bio12 Bio15 Bio18 Slope Eco Geom 21.30 6.41


0.69 7.78 0.15 1.65 37.46 4.48 0.06


3.97 10.76 7.97 0.36


0.43 3.68 13.75 3.08


3.30 9.10


45.42 35.41


6.95 60.52 15.19


1Bio2, mean diurnal range (mean of the difference of the monthly maximum and minimum temperatures over 1 year); Bio3, isothermality; Bio8, mean tem- perature of wettest quarter; Bio11, mean temperature of coldest quarter; Bio12, annual precipitation; Bio15, precipitation seasonality; Bio18, precipitation of warmest quarter; Eco, ecoregion; Geom, geomorphology.


predicted current and future suitable areas for each species by overlaying in ArcGIS the outputs of our models with maps of Brazilian protected areas (ICMBio, 2017; MMA, 2018b), priority areas for biodiversity conservation (MMA, 2018a) and forest cover (IBGE, 2017). To identify protected areas and priority areas that will retain climatic suitability in the future, we overlapped areas that were predicted to be suitable under both present and future conditions with ex- isting protected areas and priority areas.Weoverlapped pri- ority areas and protected areas with our modelled suitable areas to identify relevant locations for the expansion or cre- ation of protected areas. We also identified protected areas that are likely to be under threat because of hunting and other anthropogenic impacts by overlapping model outputs with a human settlement map (IBGE, 2017). To categorize the degree of protection of the areas pre-


dicted by our models to be suitable for the target species, we considered the following categories: high protection status (protected areas of integral protection, where human settlement is not permitted, but certain activities such as sci- entific research and ecotourism are); medium protection status (areas under permanent protection in which sustain- able use of natural resources and human occupation are per- mitted); low protection status (protected areas in which human settlement and development are permitted as well sustainable use of natural resources); and unprotected (areas not formally protected). Areas defined by the Brazilian government as priority


areas for biodiversity conservation are areas where conser- vation efforts should be directed for the planning and imple- mentation of actions such as the creation of protected areas, licensing, inspection, and promotion of sustainable use. We considered areas occupied by forests as those with trees .5 m tall, including areas of dense, open, seasonal and mixed ombrophilous forest, as well as forested savannah, forested campinarana and mangroves (IBGE, 2017). We de- fined human settlements as areas characterized by urban use, structured by buildings and road systems, where non- agricultural artificial surfaces predominate (IBGE, 2017). This category includes cities, towns, roads, services and transport, power grids, communication infrastructure and


associated land, areas occupied by industrial and commer- cial complexes, buildings (which may in some cases be located in periurban areas), Indigenous villages and mining areas.


Results


We found 223 occurrence records for the three target spe- cies, 176 of which were retained after validation. These com- prised 66 records of A. belzebul, 33 of S. flavius and 77 of S. libidinosus (Supplementary Table 3). All species distribution models were able to discriminate


between true presence and pseudo-absences (AUCtest range: 0.82–0.97; Table 1) and performed better than null models because they fell outside the range of AUC values gener- ated from 100 null models (AUCtrain range: 0.61–0.80). Geomorphology, annual precipitation and ecoregion were the main environmental variables affecting habitat suitabil- ity for the target species (Table 1). The model considering current conditions predicted suitable areas of 671, 47,184 and 1,059,360 km2 for A. belzebul,S. flavius and S. libidi- nosus, respectively (Table 2, Fig. 2). Our future models con- sidering climate change predicted a reduction in the areas suitable for all species (Table 2, Fig. 3). Gap analysis showed that only 24, 8 and 9% of the areas


predicted to be suitable under current climatic conditions for A. belzebul, S. flavius and S. libidinosus, respectively, fall within existing protected areas (Table 3, Fig. 4), and 72%of these areas are of low protection status. Approximately 88% of the areas predicted to be suitable are unprotected. In our models, we overlapped areas predicted to be suit-


able for the occurrence of the three target species with gov- ernment priority areas and forest cover layers. We found that 27% of the suitable areas for all three target species to- gether fall within government priority areas for conserva- tion (10% in the Amazon forest, 10% in the Cerrado, 6% in the Caatinga and 1% in the Atlantic Forest). Only 24% of the suitable areas are currently forested (17%inthe Amazon forest, 4% in the Caatinga, 2.5% in the Cerrado and 0.5% in the Atlantic Forest; Table 3). Binary maps of


Oryx, 2020, 54(6), 803–813 © The Author(s), 2020. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605319001388


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