Expanded distribution and predicted suitable habitat for the critically endangered yellow-tailed woolly monkey (Lagothrix flavicauda) in Peru

The Tropical Andes Biodiversity Hotspot holds a remarkable number of species at risk of extinction due to anthropogenic habitat loss, hunting and climate change. One of these species, the Critically Endangered yellow-tailed woolly monkey (Lagothrix flavicauda), was recently sighted in Junín region, 206 kilometres south of its previously known distribution. The range extension, combined with continued habitat loss, calls for a re-evaluation of the species' distribution and available suitable habitat. Here, we present novel data from surveys at 53 sites in the regions of Junín, Cerro de Pasco, Ayacucho and Cusco. We encountered L. flavicauda at 9 sites, all in Junín, and the congeneric L. l. tschudii at 20 sites, but never in sympatry. Using these new localities along with all previous geographic localities for the species, we made predictive Species Distribution Models based on Ecological Niche Modelling using a generalized linear model and maximum entropy. Each model incorporated bioclimatic variables, forest cover, vegetation measurements, and elevation as predictor variables. Model evaluation showed >80% accuracy for all measures. Precipitation was the strongest predicter of species presence. Habitat suitability maps illustrate potential corridors for gene flow between the southern and northern populations, although much of this area is inhabited by L. l. tschudii. An analysis of the current protected area (PA) network showed ~47% of remaining suitable habitat is unprotected. With this, we suggest priority areas for new protected areas or expansions to existing reserves that would conserve potential corridors between L. flavicauda populations. Further surveys and characterization of the distribution in intermediate areas, combined with studies on genetic flow, are still needed to protect this species.Funding provided by: Boston UniversityCrossref Funder Registry ID: http://dx.doi.org/10.13039/100007161Award Number:Presence data was collected through a literature search of all L. flavicauda localities since 2010. Prediction results are from 1) a generalized linear model produced in R and 2) MaxEnt Programming Software (v. 3.4.4)