Phenotypic plasticity and the leaf economics spectrum: plasticity is positively associated with specific leaf area
Data files
Jun 20, 2022 version files 78.38 KB
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README.rtf
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Stotz_et_al._Oikos_10.1111_oik.09342.xlsx
Abstract
Phenotypic plasticity is a key mechanism by which plants respond to changing or heterogeneous conditions. Efforts to predict phenotypic plasticity across plant species have mainly focused on environmental variability or abiotic conditions, i.e., site characteristics. However, the considerable variation in phenotypic plasticity within sites calls for alternative approaches. Different functional groups are thought to differ in their plasticity levels. Further, traits such as leaf specific area (SLA), leaf area (LA) and maximum photosynthetic rate (Amax) reflect central aspects of plant strategies. Lower values of SLA, LA and Amax are indicative of a resource-conservative strategy, which is thought to be associated with lower phenotypic plasticity. We used meta-analytical data to test whether plant functional group (herbs, woody deciduous and woody evergreens) and SLA, LA and Amax are associated with phenotypic plasticity in four trait types: biomass allocation, plant size, leaf morphology and physiology. We obtained data from 168 plant species and accounted for phylogenetic relationships in all analyses. We found a positive relationship between SLA and phenotypic plasticity in biomass allocation, leaf morphology and physiology, with differences across functional groups. In contrast, there was no evidence of greater plasticity in plant size in species with higher SLA; rather the opposite was true for woody evergreens. Amax and LA showed similar, but less consistent associations with phenotypic plasticity. Our results show the potential of building predictive frameworks for phenotypic plasticity based on easily measured plant functional characteristics. Results also provide insights into plant strategies and suggest the existence of potential compromises: resource-conservative, low-SLA species tend to be more stress-tolerant but may be less able to cope with variable conditions due to their generally lower phenotypic plasticity. Further studies are needed to explore the mechanisms and the potential implications of this association.
Methods
We used a subsample of Stotz et al. 2021 (Ecology Letters, doi.org/10.1111/ele.13827) dataset. Details on the study selection criteria are described in Stotz et al. 2021.
This dataset, includes only those species for which the authors measured and reported specific leaf area (SLA), leaf area (LA) or maximum photosynthetic capacity (Amax), and with available information on growth form and leaf habit.
Phenotypic plasticity of each trait was estimated as the absolute value of the effect size (Hedges' g) between the two most extreme treatments, as done in Stotz et al. 2021. Traits were classified into four trait types: biomass allocation, plant size, leaf morphology and physiology. When more than one trait per trait type was measured, we selected the most plastic trait (max plasticity). Alternatively, we also calculated average (pooled) plasticity of all traits within trait type.
Usage notes
Excel.