Historical hypothesis in explaining spatial patterns of species richness

doi:10.3724/SP.J.1003.2009.09143

Abstract

Abstract:

Spatial patterns of biodiversity are results of contemporary climate, disturbance, and geological history. In this paper, we review the historical hypothesis which explains historical importance in shaping biodiversity patterns, focusing on the recent development in its studies on mechanisms, parameter selection, and relative importance of historical factors versus contemporary climate. Based on literature research, we conclude that, (1) the historical events significantly affect the present patterns of biodiversity, and that these effects are masked by the strong collinearity between historical processes and contemporary climate; (2) historical processes are more significant in influencing distributional patterns of species with small ranges (or endemic species) than those of wide-spread species; (3) measurement of historical processes is a challenge in testing historical hypothesis, as the surrogates currently used are strongly collinear with contemporary climates. Phylogenetic analysis may be help assess the importance of historical hypothesis in controlling spatial patterns of biodiversity.

Key words: species richness, regional process, geological history, contemporary climate

Zhiyao Tang, Zhiheng Wang, Jingyun Fang. Historical hypothesis in explaining spatial patterns of species richness[J]. Biodiv Sci, 2009, 17(6): 635-643.

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URL: https://www.biodiversity-science.net/EN/10.3724/SP.J.1003.2009.09143

https://www.biodiversity-science.net/EN/Y2009/V17/I6/635

Figures/Tables 3

Fig. 1 Factors influencing biodiversity patterns at different scales (after Harrison & Cornell, 2008)

Fig. 2 The comparison of current and fossil tree genera in different regions of the Northern Hemisphere (revised from Ricklefs, 2005)

Fig. 3 The relative effects of biogeographic regions and contemporary climate on the patterns of woody plant richness in China. a, b, c represent the variance explained by the pure effect of climate, joint effect of climate and regional effect, pure effect of regional effect; d represents the unexplained variance (after Wang, 2008).

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