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Relative influence of regional species richness vs local climate on local species richness in China's forests

Authors

  • Xiangping Wang,

    1. The Key Laboratory of Siliviculture and Conservation of the Ministry of Education, College of Forestry, Beijing Forestry Univ., CN-100083 Beijing, PR China.
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  • Zhiyao Tang,

    1. The Key Laboratory of Siliviculture and Conservation of the Ministry of Education, College of Forestry, Beijing Forestry Univ., CN-100083 Beijing, PR China.
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  • Zehao Shen,

    1. The Key Laboratory of Siliviculture and Conservation of the Ministry of Education, College of Forestry, Beijing Forestry Univ., CN-100083 Beijing, PR China.
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  • Chengyang Zheng,

    1. The Key Laboratory of Siliviculture and Conservation of the Ministry of Education, College of Forestry, Beijing Forestry Univ., CN-100083 Beijing, PR China.
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  • Juchun Luo,

    1. The Key Laboratory of Siliviculture and Conservation of the Ministry of Education, College of Forestry, Beijing Forestry Univ., CN-100083 Beijing, PR China.
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  • Jingyun Fang

    1. The Key Laboratory of Siliviculture and Conservation of the Ministry of Education, College of Forestry, Beijing Forestry Univ., CN-100083 Beijing, PR China.
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X. Wang, The Key Laboratory of Siliviculture and Conservation of the Ministry of Education, College of Forestry, Beijing Forestry Univ., CN-100083 Beijing, PR China. E-mail: wangxiangping@bjfu.edu.cn

Abstract

Disentangling the relative effects of local and regional processes on local species richness (LSR) is critical for understanding the mechanisms underlying large-scale biodiversity patterns. In this study we used 1098 forest plots from 41 mountains across China, together with regional flora data, to examine the relative influence of local climate vs regional species richness (RSR) on LSR patterns. Both RSR and LSR for woody species and all species combined decreased with increasing latitude, while richness of herbaceous species exhibited a hump-shaped pattern. The major climatic orrelates of species richness differed across spatial scales. At the regional scale, winter coldness was the best predictor of RSR patterns for both woody and herbaceous species. At the local scale, however, productivity-related climatic indices were the best predictors of LSR patterns. Local climate and RSR together explained 48, 54 and 23% of the variation in LSR, for overall, woody and herbaceous species, respectively. Both local climate and RSR independently influenced LSR in addition to their joint effects, suggesting that LSR patterns were shaped by local and regional processes together. Local climate and RSR affected LSR of woody species mainly through their joint effects, while there were few shared effects of climate and RSR on the LSR of herbaceous species. Our findings suggest that while geographic RSR patterns are mainly determined by winter coldness, the ecological processes driven by productivity may be critical to the filtering of regional flora into local communities. We also demonstrate that biogeographic region is not a good surrogate for regional richness, at least for our dataset. Consequently, whether biogeographic region can effectively reflect regional effects needs further examination.

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