Affiliation:
1. Department of Earth System Science Stanford University Stanford CA 94305 USA
2. Department of Ecology, Evolution, & Marine Biology University of California, Santa Barbara Santa Barbara CA 93106 USA
Abstract
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 regressing in situ trait 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.
Funder
Division of Environmental Biology
National Aeronautics and Space Administration
National Science Foundation
Cited by
2 articles.
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