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Summary Predictive relationships between plant traits and environmental factors can be derived at global and regional scales, informing efforts to reorient ecological models around functional traits. However, in a changing climate, the environmental variables used as predictors in such relationships are far from stationary. This could yield errors in trait–environment model predictions if timescale is not accounted for.Here, the timescale dependence of trait–environment relationships is investigated by regressingin situtrait measurements of specific leaf area, leaf nitrogen content, and wood density on local climate characteristics summarized across several increasingly long timescales.We identify contrasting responses of leaf and wood traits to climate timescale. Leaf traits are best predicted by recent climate timescales, while wood density is a longer term memory trait. The use of sub‐optimal climate timescales reduces the accuracy of the resulting trait–environment relationships.This study concludes that plant traits respond to climate conditions on the timescale of tissue lifespans rather than long‐term climate normals, even at large spatial scales where multiple ecological and physiological mechanisms drive trait change. Thus, determining trait–environment relationships with temporally relevant climate variables may be critical for predicting trait change in a nonstationary climate system.
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This content will become publicly available on October 16, 2026
commecometrics: an R package for trait-environment modelling at the community level
The R packagecommecometricsprovides an accessible, open-access framework for modelling trait–environment relationships using community-level trait data from modern and ancient species. Ecometrics links the trait distributions of communities to their local environmental variables, enabling the reconstruction of past conditions and the prediction of community responses under future climate change. Existing tools for functional trait analysis often lack palaeontological integration or are limited to specific taxa.commecometricsaddresses these gaps by offering a suite of functions to summarise trait distributions, construct ecometric models, visualise trait–environment relationships, assess model robustness and reconstruct environmental conditions. The package is designed for broad applicability across ecological and palaeoecological studies and includes tools for trait-based biodiversity analysis beyond ecometrics. Through a worked example using carnassial tooth relative blade length (RBL) in carnivoran mammals, we demonstrate the package’s capabilities for analysing trait–environment dynamics across space and time.
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- Award ID(s):
- 2334543
- PAR ID:
- 10686413
- Publisher / Repository:
- Pensoft
- Date Published:
- Journal Name:
- Biodiversity Data Journal
- Volume:
- 13
- ISSN:
- 1314-2836
- Format(s):
- Medium: X
- Associated Dataset(s):
- View Associated Dataset(s) >>
- Sponsoring Org:
- National Science Foundation
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