Distinct responses and range shifts of lizards populations across an elevational gradient under climate change
Jiang, Zhong-wen et al. (2023), Distinct responses and range shifts of lizards populations across an elevational gradient under climate change , Dryad, Dataset, https://doi.org/10.5061/dryad.1zcrjdfwx
Ongoing climate change has profoundly affected global biodiversity, but its impacts on populations across elevations remain understudied. Using a mechanistic niche model incorporating species traits, we predicted ecophysiological responses (activity times, oxygen consumption and evaporative water loss) for lizard populations at high-elevation (< 3600 m asl) and extra-high-elevation (> 3600 m asl) under recent (1970–2000) and future (2081–2100) climates. Compared with their high-elevation counterparts, lizards from extra-high-elevations are predicted to experience a greater increase in activity time and oxygen consumption but a similar increase in evaporative water loss. By integrating these ecophysiological traits into a hybrid species distribution model (HSDM), we were able to make the following predictions under two warming scenarios (SSP1-2.6, SSP5-8.5). By 2081–2100, we predict that lizards at both high- and extra-high-elevations will shift upslope; lizards at extra-high-elevations will gain more and lose less habitat than will their high-elevation congeners. We therefore advocate the conservation of high-elevation species in the context of climate change, especially for those populations living close to their lower elevational range limits. In addition, by comparing the results from HSDM and traditional species distribution models, we highlight the importance of considering intraspecific variation and local adaptation in physiological traits along elevational gradients when forecasting species' future distributions under climate change.
The Second Tibetan Plateau Scientific Expedition and Research Program (STEP), Award: 2019QZKK0501
Joint Grant from Chinese Academy of Sciences-People's Government of Qinghai Province on Sanjiangyuan National Park, Award: LHZX-2020-01
The Strategic Priority Research Program of the Chinese Academy of Sciences, Award: XDB31000000