Bridging climate refuges for climate change adaptation: A spatio-temporal connectivity network approach

Abstract

Enhancing the spatio-temporal connectivity of dynamic landscapes is crucial for species to adapt to climate change. However, a spatio-temporal connectivity network approach considering climate change and species movement is often overlooked. Taking Tibetan wild ass on the Qinghai-Xizang Plateau as an example, we simulated species distribution under current (2019) and future scenarios (2100), constructed spatio-temporal connectivity networks, and assessed the spatio-temporal connectivity. The results show that under the current, SSP2-4.5 and SSP3-7.0 scenarios, the suitable habitats for Tibetan wild ass account for 21.11%, 21.34%, and 20.95% of the total area, respectively, which show more fragmentation in 2100. 78.35% of habitats which are predicted to be suitable under current conditions will remain suitable in the future, which can be regarded as stable climate refuges. With the increase in future emission intensity, the number percentage of auxiliary connectivity corridors increases from 27.65% to 33.57%. This indicates that more patches will function as temporary refuges and the auxiliary connectivity corridors will gradually weaken the dominance of direct connectivity corridors. Under different SSP-RCP scenarios, the internal spatio-temporal connectivity is the highest, accounting for 42%–43%. Compared with the spatio-temporal perspective, the purely spatial perspective overestimates network connectivity by about 28% considering all current and future patches, and underestimates network connectivity by 16%–21% when only considering all current or future patches. In this study, a new approach of spatio-temporal connectivity network is proposed to bridge climate refuges, which contributes to the long-term effectiveness of conservation networks for species’ adaptation to climate change.