Plant functional traits differ in adaptability and are predicted to be differentially affected by climate change

Ahrens, Collin, Western Sydney University, https://orcid.org/0000-0002-0614-9928

Andrew, Margaret, Murdoch University

Mazanec, Richard, Department of Agriculture and Food Western Australia

Ruthrof, Katinka, Department of Agriculture and Food Western Australia

Challis, Anthea, Western Sydney University

Hardy, Giles, Murdoch University

Byrne, Margaret, Department of Agriculture and Food Western Australia

Tissue, David T., Western Sydney University

Rymer, Paul, Western Sydney University

c.ahrens@westernsydney.edu.au

Published Nov 25, 2019 on Dryad. https://doi.org/10.5061/dryad.nk98sf7pv

Cite this dataset

Ahrens, Collin et al. (2019). Plant functional traits differ in adaptability and are predicted to be differentially affected by climate change [Dataset]. Dryad. https://doi.org/10.5061/dryad.nk98sf7pv

Abstract

1. Climate change is testing the resilience of forests worldwide pushing physiological tolerance to climatic extremes. Plant functional traits have been shown to be adapted to climate, and have evolved patterns of trait correlations (similar patterns of distribution) and coordinations (mechanistic trade-off). We predicted that traits would differentiate between populations associated with climatic gradients, suggestive of adaptive variation, and correlated traits would adapt to future climate scenarios in similar ways. 2. We measured genetically determined trait variation and described patterns of correlation for seven traits: photochemical reflectance index (PRI), normalized difference vegetation index (NDVI), leaf size (LS), specific leaf area (SLA), δ¹³C (integrated water use efficiency, WUE), nitrogen concentration (N_CONC), and wood density (WD). All measures were conducted in an experimental plantation on 960 trees sourced from 12 populations of a key forest canopy species in southwestern Australia. 3. Significant differences were found between populations for all traits. Narrow-sense heritability was significant for five traits (0.15 to 0.21), indicating that natural selection can drive differentiation; however, SLA (0.08) and PRI (0.11) were not significantly heritable. Generalised additive models predicted trait values across the landscape for current and future climatic conditions (>90% variance). The percent change differed markedly among traits between current and future predictions (differing as little as 1.5% (δ13C) or as much as 30% (PRI)). Some trait correlations were predicted to break down in the future (SLA:N_CONC, δ¹³C:PRI, and N_CONC:WD). 4. Synthesis: Our results suggest that traits have contrasting genotypic patterns and will be subjected to different climate selection pressures, which may lower the working optimum for functional traits. Further, traits are independently associated with different climate factors, indicating that some trait correlations may be disrupted in the future. Genetic constraints and trait correlations may limit the ability for functional traits to adapt to climate change.