ABSTRACT: Species distribution models are a key component for understanding a species’ potential occurrence, specifically in vastly undersampled landscapes. The current species distribution data for the Assamese macaque Macaca assamensis are outdated, but suggest a patchy distribution in moist broadleaved forests in South and Southeast Asia. Therefore, in this study, we used a species distribution model to explore the potential climatic niche of this species and assess its distribution and potential barriers in 12 South and Southeast Asian countries. We combined primary and secondary species occurrence records from different countries. We applied Classification and Regression Tree (CART), TreeNet (boosting), RandomForest (bagging) and Maximum Entropy (MaxEnt) machine-learning algorithms with elevation as well as 19 bioclimatic variables for the first ensemble predictions ever completed for this species. Our results suggested that the predicted distribution of the Assamese macaque is strongly associated with precipitation of warmest quarter (BIO18), temperature annual range (BIO7) and temperature seasonality (BIO4). Our prediction shows a continuous potential climatic niche of the species from east of the Kaligandaki River in Nepal to Lao People’s Democratic Republic. There are also potential niche patches in Bhutan, Southeast China, Thailand and Cambodia, while Pakistan and Afghanistan have no potential niche for the species. We believe that our workflow presents a new conservation-oriented open access research template to progress empirical primate conservation worldwide.
KEY WORDS: Assamese macaque · Potential distribution niche · Machine learning · Ensemble model prediction · Open access data
Full text in pdf format Supplementary material | Cite this article as: Regmi GR, Huettmann F, Suwal MK, Nijman V and others (2018) First open access ensemble climate envelope predictions of Assamese macaque Macaca assamensis in Asia: a new role model and assessment of endangered species. Endang Species Res 36:149-160. https://doi.org/10.3354/esr00888
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