Aim:We test a new species distribution modelling (SDM) framework, while comparing results to more common distribution modelling techniques. This framework allows for the combination of presence-only (PO) and presence-absence (PA) data and accounts for imperfect detection and spatial bias in presence data. The new framework tested here is based on a Poisson point process model, which allows for predictions of population size. We compared these estimates to those provided by experts on the species.
Species and Location: Presence data on Baird's tapir (Tapirus bairdii) throughout its range from southern México to northern Colombia were used in this research, primarily from the years 2000 to 2016. Methods: Four SDM frameworks are compared as follows: (1) Maxent, (2) a presenceonly (PO) SDM based on a Poisson point process model (PPM), (3) a presence-absence (PA) SDM also based on a PPM and (4) an Integrated framework which combines the previous two models. Model averaging was used to produce a single set of coefficient estimates and predictive maps for each model framework. A hotspot analysis (Gi*) was used to identify habitat cores from the predicted intensity of the Integrated model framework.
Results: Important variables to model the distribution of Baird's tapir included land cover, human pressure and topography. Accounting for spatial bias in the presence data affected which variables were important in the model. Maxent and the Integrated model produced predictive maps with similar patterns and were considered to be more in agreement with expert knowledge compared to the PO and PA models.Main conclusions: Total abundance as predicted by the model was higher than expert opinion on the species, but local density estimates from our model were similar to available independent assessments. We suggest that these results warrant further validation and testing through collection of independent test data, development of more precise predictor layers and improvements to the model framework.
The reproductive season of white-tailed deer (Odocoileus virginianus) has been hypothesized to be aseasonal south of about 14°–18°N latitude, where annual variation in day length is low. We tested this idea by using camera-trap data (1,336 photographed individuals identified by age and sex) collected during 2011–2017 in the dry tropical forest of Santa Rosa National Park, northwest Costa Rica, where wet and dry seasons are well-defined. We identified variation in monthly occurrence of spotted deer fawns, as well as the status of antler growth of male deer, specifically related to the very seasonal environment of the region. Year-round reproduction likely occurs, but the rainfall pattern in the area greatly influences the relative frequency of reproductive indicators, with most births occurring during the dry season, and a second peak occurring toward the latter part of the wet season. We speculate that food resources are the major influence on reproductive patterns, and that variation in types and timing of food resource availability likely account for the variation in reproductive patterns.
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