Abstract
Managing ecosystems to effectively preserve function and services requires reliable tools that can infer changes in the stability and dynamics of a system. Conceptually, functional diversity (FD) appears as a sensitive and viable monitoring metric stemming from suggestions that FD is a universally important measure of biodiversity and has a mechanistic influence on ecological processes. It is however unclear whether changes in FD consistently occur prior to state responses or vice versa, with no current work on the temporal relationship between FD and state to support a transition towards trait-based indicators. There is consequently a knowledge gap regarding when functioning changes relative to biodiversity change and where FD change falls in that sequence. We therefore examine the lagged relationship between planktonic FD and abundance-based metrics of system state (e.g. biomass) across five highly monitored lake communities using both correlation and cutting edge non-linear empirical dynamic modelling approaches. Overall, phytoplankton and zooplankton FD display synchrony with lake state but each lake is idiosyncratic in the strength of relationship. It is therefore unlikely that changes in plankton FD are identifiable before changes in more easily collected abundance metrics. These results highlight the power of empirical dynamic modelling in disentangling time lagged relationships in complex multivariate ecosystems, but suggest that FD cannot be generically viable as an early indicator. Individual lakes therefore require consideration of their specific context and any interpretation of FD across systems requires caution. However, FD still retains value as an alternative state measure or a trait representation of biodiversity when considered at the system level.
Original language | English |
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Pages (from-to) | 686-701 |
Number of pages | 16 |
Journal | Global Change Biology |
Volume | 29 |
Issue number | 3 |
Early online date | 12 Nov 2022 |
DOIs | |
Publication status | Published - 12 Nov 2022 |
Bibliographical note
Funding Information:DAO received funding from the GW4+ FRESH Centre for Doctoral Training in Freshwater Biosciences and Sustainability (NE/R011524/1). We thank Tamar Zohary for the long‐term phytoplankton dataset from Lake Kinneret, and Heidrun Feuchtmayr for providing data from Windermere; monitoring at this site is currently supported by Natural Environment Research Council award number NE/R016429/1 as part of the UK‐SCAPE program delivering National Capability. We also thank the field and laboratory teams who have collected all of the data used in this study. We also declare we have no competing interests and thank the two anonymous reviewers for comments to improve the clarity of the manuscript.
Publisher Copyright:
© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.