群落/生态系统功能多样性研究方法及展望

功能多样性是指影响群落/生态系统功能的物种性状值和范围，是解释和预测生态系统结构和功能的有效手段之一，可将植物个体尺度与群落尺度和生态系统尺度的相关生态学问题联系起来。虽已发展出多种功能多样性定量化研究方法，但不同方法结果差异较大，难以进行多研究间的比较研究。比较探讨各功能多样性研究方法的优缺点有利于拓展功能多样性内涵，也有助于功能生态学的应用与发展。回顾了当前10种功能多样性的定量化研究方法，并指出选取合适功能多样性方法的关键在于，应考虑选取群落/生态系统中的哪些物种、哪些功能性状、选取的功能性状数目、以及如何对功能性状权重等。对比发现，功能分散性指数和Rao二次熵系数的研究方法在众多方法中优势明显，具有较高的应用潜力；标准化功能多样性的研究方法在未来仍需进一步完善。利用功能多样性指数预测群落/生态系统过程和功能当前仍多侧重于理论研究，野外实证研究较为缺乏，是功能生态学未来研究的重点和难点之一。

Community/Ecosystem Functional Diversity: measurements and development

Functional diversity is a component of biodiversity reflecting the value and range of functional traits of species in a community or ecosystem. It can be used effectively to measure, explain and predict ecosystem function. Although many quantitative methods of functional diversity have been developed, the results of these methods are quite inconsistent and it is difficult to conduct a comparative study among them. Comparing and discussing the advantages and disadvantages of the main quantitative methods of functional diversity could be beneficial to expand the connotation of functional diversity and to promote its application and development. In this study, we reviewed 10 quantifying research methods of the functional diversity and examined in which way the functional diversity could be employed to explain and predict the effects of organisms on ecosystem functions, thereby providing a mechanistic link between the individual and the community/ecosystem scale. The key to develop effective methods for measuring functional diversity is to consider which species, what and how many traits should be used and weighted, among other considerations. By comparing the advantages and disadvantages of the 10 methods, we suggested that the measurement of functional diversity should meet the following criteria:(1) It can basically represent the functional diversity characteristics of the community/ecosystem; (2) It can calculate the qualitative, semi-quantitative and quantitative type of functional trait data; (3) It has no strict limitation for the trait data, e.g., the missing value and non-monotonous data should be allowed in the dataset; (4) Multiple functional traits data can be considered or calculated simultaneously; (5) The influence of species weight in the community/ecosystem can be considered; (6) Different communities/ecosystems can be compared by the method; (7) The intraspecific variance of functional traits can be considered; (8) The calculation is simple, easy to understand, and practical. Among the 10 functional diversity measurements, the functional dispersion index and the Rao''s quadratic entropy coefficient have great potential to be applied, although they currently have some theoretical issues. The standardization of calculation method of functional diversity clearly needs further improvement in the future. Although new theories have been developed to predict ecosystem function with functional diversity, due to the methodological limitations, the application of functional diversity to study the structure and function of community/ecosystem (such as the research on the relationships between functional diversity and ecosystem productivity, stability, and resources dynamic) is still insufficient, and more field and experimental confirmation in this aspect are also urgently needed.