期刊
ECOLOGICAL INDICATORS
卷 130, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.ecolind.2021.108075
关键词
Climate diversity; Koppen-Geiger climate classification; Landscape; CMIP5; SHDI; SIDI
资金
- National Key Research and Development Program of China [2019YFC0507801]
- Second Tibetan Plateau Scientific Expedition and Research Program (STEP) [2019QZKK1003]
- National Natural Science Foundation of China [41890824]
- Strategic Priority Research Program of the Chinese Academy of Sciences [XDA20040301]
- CAS Interdisciplinary Innovation Team [JCTD-2019-04]
This study utilized Shannon's Diversity Index and Simpson's Diversity Index to analyze the changes in global climate heterogeneity and found a significant decrease in global climate heterogeneity, with temperature increase playing a more significant role in reducing it.
Variations in climate types are commonly used to describe changes in natural vegetation cover in response to global climate change. However, few attempts have been made to quantify the heterogeneous dynamics of climate types. In this study, based on the Coupled Model Intercomparison Project phase 5 (CMIP5) historical and representative concentration pathway (RCP) runs from 18 global climate models, we used Shannon's Diversity Index (SHDI) and Simpson's Diversity Index (SIDI) to characterise of global climate heterogeneity from a morphological perspective. Our results show that global climate heterogeneity calculated by the SHDI/SIDI indices decreased from 1901 to 2095 at a significance level of 0.01. As radiative forcing intensified from RCP 2.6 to 8.5, the SHDI/SIDI decreased significantly. Furthermore, we observed that the spatial distribution of global climate heterogeneity was significantly reduced, with a pronounced latitudinal trend. Sensitivity analysis indicated that the temperature increase played a more significant role in reducing global climate heterogeneity than precipitation under the three warming scenarios, which is possibly attributed to anthropogenic forcing. Our findings suggest that the dynamics of global climate heterogeneity can be an effective means of quantifying global biodiversity loss.
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