Let the concept of trait be functional!

TLDR

The concept of a trait, originally a surrogate of organismal performance used by evolutionists, has expanded to community and ecosystem ecology, yet remains poorly defined and confusing across disciplines. The study aims to provide an unambiguous definition of plant functional traits, propose a hierarchical performance paradigm, and present an integrative framework linking trait changes to organismal performance and higher‑level processes. Functional traits are defined as morpho‑physio‑phenological characteristics that influence fitness through growth, reproduction, and survival, and the authors propose integration functions—functional response and effect algorithms—to translate trait changes into organismal performance and ecosystem processes.

Abstract

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.