Aim: Determining the mechanisms by which climate change and human activities affect patterns of ecological specialization in different genetic units of the same species is crucial for developing local or regionally-based conservation solutions. This study uses species distribution models and genetic analysis to 1) identify evidence of intraspecific differences in the population size and distribution of the three extant lineages (Sichuan/Gansu (SG), Qinling (QL), and Shennongjia (SNJ)) of Sichuan snub-nosed monkeys; and 2) determine why some lineages have lower population numbers, a smaller geographical distribution, and are more threatened with extinction.

Location: China

Methods: We used n-dimensional hypervolume modeling and Genotype–Environment Association (GEA) models to compare the climatic niches of three snub-nosed monkey lineages, SDMs to reconstruct the historical, current, and future distributions of each lineage, and SMC++ to calculate their effective population sizes.

Results: We found evidence of: 1) climatic niche differentiation among the SG, QL, and SNJ lineages of Sichuan snub-nosed monkeys; 2) geographical isolation combined with a decrease in population size during the LGM resulted in ecological specialization among these three lineages; and 3) a decline in climatic suitability and anthropogenically-driven land conversion, combined with small population size and a narrow distributional range, indicate that the SNJ lineage is at a greater risk of extinction than the SG and QL lineages.

Main conclusions: We demonstrate that during the LGM a reduction in habitat suitability driven by climate change, in concert with decreasing population size resulted in the geographical isolation of the three Sichuan snub-nosed monkey subpopulations, leading to lineage differences in ecological specialization. GEA models and hypervolume models demonstrated that the three lineages occupy different ecological niches. Based on lineage-level models, the SNJ and QL lineages should be the immediate focus of conservation efforts due to their small effective population size and expected future reductions in available suitable habitat. The modeling approach used here is robust and can be applied effectively to examine the biogeography, recent evolutionary history, and effective population size of other endangered animal taxa.