Global Ecology and Conservation (Aug 2024)
Using an ensemble modeling to predict the potential distribution and habitat suitability of caracal (Caracal caracal) in southwestern Iran
Abstract
Anthropogenic activities and climate change are degrading wildlife habitats, making it crucial to assess suitability of remaining habitat for effective conservation and management of threatened wildlife. This study aimed to determine the variables influencing habitat selection and spatial distribution of caracal (Caracal caracal) in southwestern Iran from 2019 to 2020. Ensembles of Small Models (ESM) were used based on eight species distribution models that included a combination of statistical and machine learning methods (GLM, CTA, FDA, GBM, ANN, MARS, RF, and MaxEnt). The outputs of two ensemble models were hybridized by simple averaging. In ESM 1, distance to water resources was used as a representative of environmental variables and in ESM 2, annual precipitation was used as a representative of bioclimatic variables. In both ESMs, these variables were combined with ecological variables such as the distribution of wild goat (Capra aegagrus) and livestock. The average importance of the model variables for ESM 1 and ESM 2 showed that the distribution of wild goat and livestock were the most important factors in predicting suitable habitat for caracals, respectively. Habitat suitability was higher close to the distribution of wild goat and livestock, near water sources and during periods of higher precipitation. Probabilistic predictions of caracal presence based on the hybridization of ESM 1 and ESM 2 suggest that only 1.3 % (206 ha) of the study area was highly suitable habitat, while 58.4 % (9570 ha) was unsuitable. Based on the ensemble of binary presence-absence maps, caracals were certainly absent in 76.2 % (12,490 ha) of the area, while their presence was uncertain in 21.6 % (3536 ha). The presence of caracals was certain in 2.2 % (363 ha) of the study area. Awareness of the habitat and distribution of caracal can help to make better decisions towards conservation and management and also reduce its conflict with humans.