Application of a combined model simulation to determine ecological corridors for western black-crested gibbons in the Hengduan Mountains, China

Abstract Habitat fragmentation is a critical contributor to biodiversity degradation and species extinction, as illustrated by the severely fragmented habitat of the western black-crested gibbon (Nomascus concolor), a critically endangered species in the Hengduan Mountains, China. An integrated simulation model, including the random forest algorithm (RFA), empirical bayesian kriging regression (EBKR), and the least-cost path model (LCP), is introduced to determine ecological corridors for western black-crested gibbons in the Hengduan Mountains. In this study, we identified habitat variables and movement behaviors of western black-crested gibbons through RFA and then proposed EBKR, which is combined with LCP to determine potential corridors. Model simulation results suggest that the western black-crested gibbons' habitat is mostly dependent on forests with an altitude of about 2,000 m and a 20° slope, areas undisturbed by human activities. Two land use and cover classes predominate inside the corridors, tree cover and mostly natural vegetation, corresponding to 67.55% and 18.54% of total land use, respectively. A total of nine corridors were planned in Hengduan Mountains via LCP. The shortest corridor, which has recently been incorporated into national park planning, is 7.40 km, and is a route that has no need for bridge construction. The longest corridor is 95.74 km and would require construction of three bridges. Mobility of western black-crested gibbons can increase by 39.49% using our simulated corridors. The planned corridor is an optimized route for western black-crested gibbons in the Hengduan Mountains, and provides the best opportunities for security, food, and survival. The proposed integrated model is an efficient method for designing and estimating habitat suitability using competitively predictive performance and simultaneously quantifying model uncertainties.