Karst as an abiotic driver of François’ langur distribution, with predictions for biological communities on karst under climate change

Mary E Blair,Zhijin Liu,Tuan A Nguyen,Tao Meng,Minh D Le,Ned Horning,Hoang M Thach,Ming Xu,Peter J Galante,Eleanor J Sterling

doi:10.21425/f5fbg51838

Abstract

Ecological niche models (ENMs) can project changes in species’ distributions under climate change and thus inform conservation efforts and further our understanding of patterns of change. Predictions of species’ distribution shifts under climate change in topographically and geologically complex landscapes, such as karst landforms, should be improved by better integration of non-climate abiotic variables, such as karst geology or habitat structure, into model projections. We built ENMs for one of the limestone langurs, a group of leaf monkeys adapted to forests on the Sino-Vietnamese limestone karst landform. We collected occurrence localities for François’ leaf monkeys (Trachypithecus francoisi) and thinned them to avoid sampling bias. We included as environmental parameters a global dataset for karst geology and 19 bioclimatic variables derived from monthly temperature and precipitation at 30 arc-second resolution. ENMs including karst geology and climatic variables outperformed and differed spatially from climate-only models. Across six future-climate scenario projections, the optimal karst+climate model differed from the best climate-only model and predicted more spatial overlap with karst in the future, a contraction in total area of suitable habitat by the 2070s, and a small loss in the amount of suitable habitat in existing conservation areas. This study shows the importance of considering other abiotic factors beyond climate in projections of suitable habitat under climate change for species in complex landscapes. Because our results show that karst and climate interact to explain the distribution of a karst-adapted species, the results also suggest that, under climate change, these interactions are likely to produce altered networks of species into novel biological communities. Finally, our results support the need for conservation of limestone habitats and cross-border collaboration to maintain refuges and movement connectivity for endangered species in the face of climate change.

Highlights

Climate change is likely to cause shifts in biological communities as novel climates appear, major biomes are redistributed, and annual temperatures increase (Parmesan and Yohe 2003, Corlett 2012, IPCC 2013)
We compiled information on T. francoisi recorded presence in four other nature reserves in Guizhou and Chongqin Provinces but could not find precise occurrence locality information for these areas. We held back this information in model training and discuss in our results whether the Ecological niche models (ENMs) built on the occurrence locality data predicted potential T. francoisi presence in these four reserves
We note that 88% of the T. francoisi localities are within 20 km of the original global carbonate rock outcrop dataset (Fig. 1 and see Appendix S1)

Summary

Introduction

Climate change is likely to cause shifts in biological communities as novel climates appear, major biomes are redistributed, and annual temperatures increase (Parmesan and Yohe 2003, Corlett 2012, IPCC 2013). Climate change is expected to shift species’ distributions and increase the likelihood of local and global extinctions (Parmesan et al 1999, Pounds et al 1999) as areas suitable for species’ survival contract or expand (Huntley et al 2008, Thomas 2010). Are microclimate conditions explicitly captured in existing models of species’ distribution shifts under past or future climate change (Franklin 2013, Keppel et al 2017). Predictions of redistributions of species under climate change could be improved by better integration of microclimate information or non-climate abiotic variables, such as geology, solar radiation, soil depth, topography and habitat structure, that likely interact to produce varied microclimate conditions Predictions of redistributions of species under climate change could be improved by better integration of microclimate information or non-climate abiotic variables, such as geology, solar radiation, soil depth, topography and habitat structure, that likely interact to produce varied microclimate conditions (e.g. Brown and Yoder 2015, Keppel et al 2017, Suggitt et al 2018)

Methods

Results

Conclusion