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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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Leaf mass per area: An investigation into the application of the ubiquitous functional trait from a paleobotanical perspective
Abstract PremiseLeaf mass per area (LMA) is a widely used functional trait in both neobotanical and paleobotanical research that provides a window into how plants interact with their environment. Paleobotanists have used site‐level measures of LMA as a proxy for climate, biome, deciduousness, and community‐scale plant strategy, yet many of these relationships have not been grounded in modern data. In this study, we evaluated LMA from the paleobotanical perspective, seeking to add modern context to paleobotanical interpretations and discover what a combined modern and fossil data set can tell us about how LMA can be best applied toward interpreting plant communities. MethodsWe built a modern data set by pulling plant trait data from the TRY database, and a fossil data set by compiling data from studies that have used the petiole‐width proxy for LMA. We then investigated the relationships of species‐mean, site‐mean, and site‐distribution LMA with different climatic, phylogenetic, and physiognomic variables. ResultsWe found that LMA distributions are correlated with climate, site taxonomic composition, and deciduousness. However, the relative contributions of these factors are not distinctive, and ultimately, LMA distributions cannot accurately reconstruct the biome or climate of an individual site. ConclusionsThe correlations that make up the leaf economics spectrum are stronger than the correlations between LMA and climate, phylogeny, morphospace, or depositional environment. Fossil LMA should be understood as the culmination of the influences of these variables rather than as a predictor.
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- Award ID(s):
- 1924390
- PAR ID:
- 10567859
- Publisher / Repository:
- American Journal of Botany
- Date Published:
- Journal Name:
- American Journal of Botany
- Volume:
- 111
- Issue:
- 10
- ISSN:
- 0002-9122
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1002/ajb2.16419
