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The development of species distribution models (SDMs) can help conservation efforts by generating potential distributions and identifying areas of high environmental suitability for protection. Our study presents a rigorously derived distribution and habitat map for lowland tapir in South America. We also describe the potential habitat suitability of various geographical regions and habitat loss, inside and outside of protected areas network. Two different SDM approaches, MAXENT and ENFA, produced relative different Habitat Suitability Maps for the lowland tapir. While MAXENT was efficient at identifying areas as suitable or unsuitable, it was less efficient (when compared to the results by ENFA) at identifying the gradient of habitat suitability. MAXENT is a more multifaceted technique that establishes more complex relationships between dependent and independent variables. Our results demonstrate that for at least one species, the lowland tapir, the use of a simple consensual approach (average of ENFA and MAXENT models outputs) better reflected its current distribution patterns. The Brazilian ecoregions have the highest habitat loss for the tapir. Cerrado and Atlantic Forest account for nearly half (48.19%) of the total area lost. The Amazon region contains the largest area under protection, and the most extensive remaining habitat for the tapir, but also showed high levels of habitat loss outside protected areas, which increases the importance of support for proper management.
The text was edited, mostly for the sake of clarity and some of the reviewers’ questions were answered.
Lowland Tapir location points (n=500) used for modeling (Raw Data)
Table S1: Lowland Tapir location points (n=500) used for modeling (Raw Data).
Fig S1: MAXENT bias grid, according procedures outlined by Elith, Kearney & Phillips (2010). The bias grid was used to down-weight the importance of presence records from areas with more intense sampling. The weighting surface was calculated based on the number of presence records within an area around any given cell (weighted by a Gaussian kernel with a standard deviation of 100km).
Fig S2: Response-curves of the variables in the MAXENT Tapirus terrestris distribution model. Mean Temperature of Coldest Quarter (MTCQ); Annual Mean Temperature (AMT);Annual Precipitation (AP). These curves show how each environmental variable affects the MAXENT prediction when all environmental variables are used to build the model.
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