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

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 climateonly 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 Highlights• Climate change may result in shifts in species' distributions, leading to changes in biological communities and increasing the likelihood of local and global extinctions.• High endemic biodiversity coincides with known and unknown biogeomorphological feedbacks and interactions in topographically and geologically complex landscapes like karst landforms, which can complicate predictions of species' distribution shifts under climate change.• We built and projected distribution models for Trachypithecus francoisi, a leaf monkey adapted to forests on the Sino-Vietnamese limestone karst landform, to show that models combining karst geology and climate as drivers outperformed models built only with climate data, with differing projections for distribution shifts under future climate change.• Including karst geology or other non-climate abiotic variables that approximate microclimate heterogeneity will be important for distribution shift predictions for other species in karst landforms and other complex landscapes.• Urgent, cross-border collaborations are likely needed for the conservation of the endangered biodiversity of the Sino-Vietnamese Karst Landform in the face of climate change.

Modeling the Distribution of the Southern Yellow-Cheeked Gibbon (Nomascus Gabriellae) Using Maxent

“…Chu Yang Sin National Park, Bidoup -Nui Ba National Park, and Phuoc Binh National Park landscape (Viet Nam): The adjacent protected areas form a relatively intact and continuous forest region of about 200,000 ha. As a large population of the Southern yellow-cheeked gibbon has been recorded in this landscape [1,29,30], it should be a priority for any species conservation initiative.…”

Species distribution modeling to inform transboundary species conservation and management under climate change: promise and pitfalls

“…Vegetation cover, microclimate, water surface coverage, and geology (e.g. Blair et al 2022b, Ngo et al 2022, Tan et al 2022 can all improve a model's predictive ability so long as they are relevant to the species' biology. These types of variables may present challenges to 13 climate change projections because of data limitations, restrictions, or lack of interoperability in some areas.…”

“…For example, microclimate data may be quite important for many species but relevant datasets may be challenging to obtain depending on the extent and resolution required. However, a study in this issue shows that variables that approximate microclimate reflect essential characteristics that result in predictions that are likely as informative as using microclimate itself for model training (Blair et al 2022b this issue). Another study in this issue pointed out the need for more long-term ecological research to better understand microclimate and fine-scale habitat preferences and improve model projections for the purpose of adaptive conservation management plans (Blair et al 2022a this issue).…”

The influence of scale-dependent geodiversity on species distribution models in a biodiversity hotspot

“…Our approach addresses the need to incorporate environmental filtering at broader scales surrounding species occurrence points, and scale-dependency in species-environment relationships. As geodiversity variables reflect the availability of microclimates or landscape variability, they hold promise for improving SDMs and providing a more comprehensive understanding of species-environment relationships [ 3 , 13 , 30 ].…”