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Reynolds Functional Groups: a trait-based pathway from patterns to predictions
by
Kruk, Carla
, Huszar, Vera L
, Devercelli Melina
in
Aquatic ecosystems
/ Clustering
/ Diagnostic systems
/ Ecological function
/ Ecologists
/ Ecology
/ Environmental gradient
/ Environmental requirements
/ Freshwater
/ Freshwater ecology
/ Freshwater ecosystems
/ Functional groups
/ Inland water environment
/ Phytoplankton
/ Plankton
/ Species
/ Species classification
/ Tolerances
/ Tolerances (dimensional)
2021
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Reynolds Functional Groups: a trait-based pathway from patterns to predictions
by
Kruk, Carla
, Huszar, Vera L
, Devercelli Melina
in
Aquatic ecosystems
/ Clustering
/ Diagnostic systems
/ Ecological function
/ Ecologists
/ Ecology
/ Environmental gradient
/ Environmental requirements
/ Freshwater
/ Freshwater ecology
/ Freshwater ecosystems
/ Functional groups
/ Inland water environment
/ Phytoplankton
/ Plankton
/ Species
/ Species classification
/ Tolerances
/ Tolerances (dimensional)
2021
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Do you wish to request the book?
Reynolds Functional Groups: a trait-based pathway from patterns to predictions
by
Kruk, Carla
, Huszar, Vera L
, Devercelli Melina
in
Aquatic ecosystems
/ Clustering
/ Diagnostic systems
/ Ecological function
/ Ecologists
/ Ecology
/ Environmental gradient
/ Environmental requirements
/ Freshwater
/ Freshwater ecology
/ Freshwater ecosystems
/ Functional groups
/ Inland water environment
/ Phytoplankton
/ Plankton
/ Species
/ Species classification
/ Tolerances
/ Tolerances (dimensional)
2021
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Reynolds Functional Groups: a trait-based pathway from patterns to predictions
Journal Article
Reynolds Functional Groups: a trait-based pathway from patterns to predictions
2021
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Overview
Reynolds Functional Groups (RFG) were designed to represent the diversity of phytoplankton assemblages of freshwater ecosystems and are among the most enduring legacies of C. S. Reynolds to freshwater phytoplankton ecologists. The RFG concept summarises a rich base of knowledge, clustering species according to functional criteria. RFG allow researchers to organise information, understand community and ecosystem functioning, and identify future outcomes, also contributing to construct hypotheses and define community assembly. This approach represents the environmental requirements, tolerances and sensitivities of species, organizing them into diagnostic environmental axes representing the habitat template of phytoplankton communities. In this contribution, we highlight the importance of this trait-based approach for phytoplankton ecology, and summarise its history and usage for phytoplankton species classifications and prediction based on environmental gradients. We present some of the applications of the approach, to describe patterns, explain mechanisms and predict new situations. We hope that this review will contribute both to describe the trajectory and practice of RFG and to encourage its use in addressing new ecological questions and in generating new avenues of research.
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