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Cui, Diyang
Wang, Dongdong
Climate change is driving biodiversity redistribution on Earth, undermining the effectiveness of protected areas (PAs) in conserving global biodiversity. Managing the consequences of biodiversity redistribution and promoting effective conservation necessitates a better understanding of climate shift patterns and species’ ability to track changing climates. Recent studies assessing the effects of climate change on biodiversity have increasingly used velocity metrics to represent climate shifts over space and time. Velocity based on a single climate variable or climate space identified using statistically combined multivariate indices may not be related to biomes or ecosystems and lacks the potential to conduct risk evaluation for biodiversity. The widely used Köppen–Geiger classification scheme provides an effective way to characterize bioclimatic conditions by incorporating multiple climatic indicators and biological information, thus can be a new direction for developing velocity metrics and supporting the development of species distribution models (SDMs). To identify research gaps, this dissertation research first reviews recent detection and assessment studies on past and future projected climate zone changes. Previous studies have shown that accelerated global warming since the 1980s has resulted in changes in climate zones that have been observed over 5% of the global land area. Tropical and arid climate zones are expected to expand into mid and high latitudes, while polar climates are shifting poleward and upward, leading to significant area shrinkage. Given the need for improved historical and future global climate maps with long-term temporal coverage and accurate depiction of fine-grained bioclimatic conditions in climate change studies, the study creates a set of 1 km Köppen-Geiger climate classification maps (KGClim) for six historical periods in 1979–2013 and four future periods in 2020–2099 under RCP2.6, 4.5, 6.0, and 8.5. The new maps offer higher classification accuracy than existing datasets and demonstrate the ability to capture recent and future projected changes in distribution of climate zones. Using the new KGClim dataset, this dissertation calculates the velocity of climate zone shifts to assess exposure risks of global PAs and examines the spatial patterns of near-, mid- and long-term climate shifts projected based on different emission pathways. Based on the findings, under RCP8.5, 38% of global protected land could undergo climate zone shifts at accelerating rates for the remainder of this century. Furthermore, global protected lands are experiencing novel (8% of global protected land) and disappearing (7%) climates, shifts of climates outside current PA networks (8%), and transition to human-dominated land use (6%). The fine-scale velocity metrics reveal spatiotemporal patterns of climate shifts and biodiversity redistribution, which can inform adaptive conservation planning to address the ongoing biodiversity crisis and achieve future conservation goals.