Let the concept of trait be functional!
Let the concept of trait be functional!
复制标题
DOI：
10.1111/j.2007.0030-1299.15559.x
复制
发表时间：
2007-05-01
期刊：
影响因子：
3.4
通讯作者：
Garnier, Eric
中科院分区：
文献类型：
--
作者：
Violle, Cyrille;Navas, Marie-Laure;Garnier, Eric
在其最简单的定义中，性状是生物体性能的替代品，这个术语的含义已经被进化论者使用了很长时间。在过去的三十年里，社区和生态系统生态学的发展已经迫使性状的概念超越了这些最初的界限，基于性状的方法现在被广泛用于从生物体到生态系统的研究。尽管有一些试图固定的术语，特别是在植物生态学，目前有一个高度混乱的使用，不仅是术语“性状”本身，而且在它所指的基本概念。因此，我们给植物性状的明确定义，特别强调功能性状。提出了一个层次的观点，将“性能范式”扩展到植物生态学。“功能性状”被定义为形态-生理-物候性状，其通过对个体表现的三个组成部分-生长、繁殖和存活的影响而间接影响适合度。最后，我们提出了一个综合框架，解释如何在特质值的变化，由于环境的变化转化为有机体的性能，以及这些变化可能会影响过程中更高的组织水平。我们认为，这可以通过开发“集成功能”，可以分为功能响应（社区水平）和效果（生态系统水平）算法来实现。
In its simplest definition, a trait is a surrogate of organismal performance, and this meaning of the term has been used by evolutionists for a long time. Over the last three decades, developments in community and ecosystem ecology have forced the concept of trait beyond these original boundaries, and trait-based approaches are now widely used in studies ranging from the level of organisms to that of ecosystems. Despite some attempts to fix the terminology, especially in plant ecology, there is currently a high degree of confusion in the use, not only of the term "trait" itself, but also in the underlying concepts it refers to. We therefore give an unambiguous definition of plant trait, with a particular emphasis on functional trait. A hierarchical perspective is proposed, extending the "performance paradigm" to plant ecology. "Functional traits" are defined as morpho-physio-phenological traits which impact fitness indirectly via their effects on growth, reproduction and survival, the three components of individual performance. We finally present an integrative framework explaining how changes in trait values due to environmental variations are translated into organismal performance, and how these changes may influence processes at higher organizational levels. We argue that this can be achieved by developing "integration functions" which can be grouped into functional response (community level) and effect (ecosystem level) algorithms.