Department of Ecology, College of Urban and Environmental Sciences, Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, China.
Proc Biol Sci. 2011 Jul 22;278(1715):2122-32. doi: 10.1098/rspb.2010.1897. Epub 2010 Dec 8.
What determines large-scale patterns of species richness remains one of the most controversial issues in ecology. Using the distribution maps of 11 405 woody species in China, we compared the effects of habitat heterogeneity, human activities and different aspects of climate, particularly environmental energy, water-energy dynamics and winter frost, and explored how biogeographic affinities (tropical versus temperate) influence richness-climate relationships. We found that the species richness of trees, shrubs, lianas and all woody plants strongly correlated with each other, and more strongly correlated with the species richness of tropical affinity than with that of temperate affinity. The mean temperature of the coldest quarter was the strongest predictor of species richness, and its explanatory power for species richness was significantly higher for tropical affinity than for temperate affinity. These results suggest that the patterns of woody species richness mainly result from the increasing intensity of frost filtering for tropical species from the equator/lowlands towards the poles/highlands, and hence support the freezing-tolerance hypothesis. A model based on these results was developed, which explained 76-85% of species richness variation in China, and reasonably predicted the species richness of woody plants in North America and the Northern Hemisphere.
是什么决定了物种丰富度的大规模模式，这仍然是生态学中最具争议的问题之一。利用中国 11405 种木本植物的分布图谱，我们比较了生境异质性、人类活动以及气候的不同方面（特别是环境能量、水热动态和冬季霜期）对物种丰富度的影响，并探讨了生物地理亲缘关系（热带与温带）如何影响丰富度与气候的关系。我们发现，乔木、灌木、藤本和所有木本植物的物种丰富度彼此之间具有强烈的相关性，且与热带亲缘关系的物种丰富度的相关性强于与温带亲缘关系的相关性。最冷月均温是物种丰富度最强的预测因子，且其对热带亲缘关系的物种丰富度的解释能力明显高于温带亲缘关系。这些结果表明，木本物种丰富度的模式主要源于从赤道/低地向极地/高地的热带物种的霜期过滤强度增加，因此支持抗冻性假说。基于这些结果建立了一个模型，该模型解释了中国 76-85%的物种丰富度变化，并合理地预测了北美的木本植物和北半球的物种丰富度。
