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Dryad

Assessing the vulnerability of plant functional trait strategies to climate change

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Mar 31, 2022 version files 514.70 MB

Abstract

Aim: Our ability to understand how species may respond to changing climate conditions is hampered by a lack of high-quality data on the adaptive capacity of species. Plant functional traits are linked to many aspects of species life history and adaptation to environment, with different combinations of trait values reflecting alternate strategies for adapting to varied conditions. If the realised climate limits of species can be partially explained by plant functional trait combinations, then a new approach of using trait combinations to predict the expected climate limits of species trait combinations may offer considerable benefits.

Location: Australia.

Time period: Current and future.

Methods: Using trait data for leaf size, seed mass and plant height for 6,747 Australian native species from 27 plant families, we model the expected climate limits of trait combinations and use future climate scenarios to estimate climate change impacts based on plant functional trait strategies.

Results: Functional trait combinations were a significant predictor of species climate niche metrics with potentially meaningful relationships with two rainfall variables (R2 = 0.36 & 0.45) and three temperature variables (R2 = 0.21, 0.28, 0.30). Using this method, the proportion of species exposed to conditions across their range that are beyond the expected climate limits of their trait strategies will increase under climate change.

Main conclusions: Our new approach, called Trait Strategy Vulnerability, includes three new metrics. For example, the Climate Change Vulnerability (CCV) metric identified a small but important proportion of species (4.3%) that will on average be exposed to conditions beyond their expected limits for summer temperature in the future. These potentially vulnerable species could be high priority targets for deeper assessment of adaptive capacity at the genomic or physiological level. Our methods can be applied to any suite of co-occurring plants globally.