Modeling biodiversity patterns from tropical, temperate and boreal forests

宏观生态学是一门新兴的生态学学科，旨在寻找一组关于物种共存和生物多样性分布的一般模式，并了解自然界中观察到的这些模式背后的规则。这个课题从来没有像现在这样令人激动。最近在宏观生态学的几个方面取得的进展极大地激发了辩论，并大大推进了这一领域。这些进展包括生物多样性中性理论的发展，重新关注将群落生态学与功能性状联系起来，寻找物种组合中的系统发育（进化）足迹，以及应用统计力学建模生物多样性模式。基于这些进展，我建议开发和测试模型来解释和预测从热带，温带到寒带森林的全球生物多样性模式。本文的工作将有助于：（1）放宽中性理论，引入物种间的出生率和死亡率差异，使中性理论更符合实际;（2）理解系统发育的意义通过发展基于遗传学的生物多样性指数和属种模型，促进生物多样性的（进化）足迹，以及（3）整合群落生态学，自我生态学和生理学，以了解功能性状的权衡对生物多样性维持的重要性。从这项研究中发展的理论和模型应该提高我们的解释和预测宏观生态格局的能力，从而建立我们的保护和管理景观生物多样性的能力。

Macroecology is a newly emerging ecological discipline aiming to search for a parsimonious set of general patterns with respect to species coexistence and biodiversity distribution and to understand the rules that underlie those patterns observed in nature. This subject has never been so exciting as it is now. The recent progress on several fronts of macroecology has greatly stimulated the debate and has substantially advanced the area. This progress includes the development of the neutral theory of biodiversity, the renewed interest in connecting community ecology to functional traits, the search for phylogenetic (evolutionary) footprints in species assemblages, and application of statistical mechanics to modeling biodiversity patterns. Based on these advances, I propose to develop and test models to explain and predict global biodiversity patterns from tropical, temperate to boreal forests. The proposed work will contribute to (1) relaxing the neutral theory by incorporating differential birth and death rates among species so that to make the neutral theory more realistic, (2) understanding the significance of phylogenetic (evolutionary) footprints in promoting biodiversity through developing phylogenetically-based biodiversity indices and genus-species models, and (3) integrating community ecology, autoecology and physiology for understanding the importance of tradeoff in functional traits to biodiversity maintenance. Theories and models developed from this study should enhance our ability to explain and predict macrecological patterns and thus build our capacity of conserving and managing biodiversity in landscapes.