Annual Review of Ecology Evolution and Systematics · 2008 · 1.3K citations · 168 references
Life SciencesBiologyEcologyCommunity EcologyEcosystem EcologyMarine EcologyFreshwater Community EcologyFreshwater Ecosystem EcologyMarine Community EcologyPhytoplankton EcologyPhytoplankton Community DynamicsPhytoplankton Community StructurePhytoplankton DynamicsPhytoplankton Functional TraitsTrait Variation Across Environmental GradientsTrait-based Community StructureTrait-based Ecological ModelsTrait-based Ecology
Trait‑based approaches are increasingly applied in ecology, and phytoplankton communities—rich model systems—serve as ideal platforms to study key ecological axes such as light, nutrients, enemies, morphology, temperature, and reproduction, where trait trade‑offs and environmental differences shape community structure. The authors aim to summarize core components of trait‑based approaches, review their historical and potential applications to phytoplankton community ecology, and outline future challenges and directions. They describe mathematical techniques for integrating traits into growth and fitness measures and predicting how community structure varies along environmental gradients.
Trait-based approaches are increasingly used in ecology. Phytoplankton communities, with a rich history as model systems in community ecology, are ideally suited for applying and further developing these concepts. Here we summarize the essential components of trait-based approaches and review their historical and potential application to illuminating phytoplankton community ecology. Major ecological axes relevant to phytoplankton include light and nutrient acquisition and use, natural enemy interactions, morphological variation, temperature sensitivity, and modes of reproduction. Trade-offs between these traits play key roles in determining community structure. Freshwater and marine environments may select for a different suite of traits owing to their different physical and chemical properties. We describe mathematical techniques for integrating traits into measures of growth and fitness and predicting how community structure varies along environmental gradients. Finally, we outline challenges and future directions for the application of trait-based approaches to phytoplankton ecology.
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