Global patterns and drivers of spatial autocorrelation in plant communities in protected areas

• Published in: Diversity and Distributions
• Main Authors: Peng, Yu, Xin, Jiaxun, Peng, Nanyi, Li, Yanyi, Huang, Jijiao, Zhang, Ruiqiang, Li, Chen, Wu, Yimeng, Gong, Bingzhang, Wang, Ronghui
• Other Authors: National Natural Science Foundation of China, National Key Research and Development Program of China
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2023
• Subjects: Arctic; Climate change
• Online Access: http://dx.doi.org/10.1111/ddi.13793; https://onlinelibrary.wiley.com/doi/pdf/10.1111/ddi.13793

Abstract Aim Stochastic and deterministic (biotic factors such as intraspecies competition or abiotic factors) processes affect the spatial patterns of ecological communities. These processes can be quantitatively assessed based on spatial autocorrelation (SAC) parameters. However, the global patterns of SAC and their differences across vegetation types remain unknown. We aimed to (1) quantitatively assess the SAC global pattern in plant communities and their variation from 1990 to 2020 and (2) identify the key drivers of SAC in plant communities in protected areas (PAs). Location Global. Time Period 1990–2020. Major Taxa Studied Terrestrial plants. Methods Using normalized difference vegetation index data extracted from remote sensing datasets, we calculated the SAC parameters, including the Nugget, Partial Sill (PSill), and Sill, in 147 samples from 49 PAs in 1990, 2000, 2010, and 2020. The random forest model was employed to identify the drivers among 10 annual and 120 monthly climatic variables. Results The SAC patterns of plant communities in global PAs differed across vegetation types. It reached the highest in grasslands and evergreen needleleaved forests, mainly explained by annual energy metrics, and the lowest in tropical evergreen rain forests around equator and boreal coniferous forests near the Arctic Circle. From 1990 to 2020, the Nugget, PSill, and Sill decreased by 92.36%, 58.36%, and 60.61%, respectively, indicating biological homogeneity. Monthly climatic variables explain SAC variations better than annual ones. Main Conclusions From 1990 to 2020, the SAC parameters decreased sharply across vegetation types, indicating an obvious biologically homogenous trend that was mainly driven by monthly climatic variation, vary across sites and vegetation types. Our results highlight the need to assess the SAC in different vegetation types separately to understand the shifts of global plant communities under climate change.