Optimality approaches linking fire-related plant traits and ecosystem responses to climate change

Shen, Y. (2025) Optimality approaches linking fire-related plant traits and ecosystem responses to climate change. PhD thesis, University of Reading. doi: 10.48683/1926.00127880

Abstract/Summary

Fire is a fundamental ecological and evolutionary process that shapes the structure, function, and resilience of ecosystems worldwide. Yet, global fire models typically treat vegetation as passive fuel, neglecting plant adaptive strategies and their feedbacks on fire behaviour and recovery following fire. This thesis advances a predictive, trait-based understanding of fire by integrating global plant trait data, remote sensing, and eco-evolutionary optimality (EEO) theory into a unified framework linking environmental drivers, fire regimes, plant traits, and ecosystem outcomes. A novel EEO-based classification of global pyroclimates has been developed, which shows that the seasonal dynamics of fuel accumulation and drying, captured through gross primary production (GPP) and vapour pressure deficit (VPD), provide a simple yet mechanistic basis for distinguishing fire behaviour across biomes (Chapter 4). Fire behaviour is shown to act as a selective filter on plant strategies. The abundance of resprouting woody species across Europe and Australia, for example, is strongly related to fire return time, intensity, and type, with resprouters most common under frequent, intense crown fires (Chapter 2). Key flammability-related traits of woody plants, including specific leaf area (SLA), leaf dry matter content (LDMC), and leaf C:N ratio, vary systematically across pyroclimates (Chapter 5). In a global analysis of more than 10,000 fires, post-fire recovery of photosynthetic activity as measured using solar-induced chlorophyll fluorescence (SIF) is shown to be related to plant traits, such as pre-fire productivity and the abundance of resprouting, as well as fire characteristics and post-fire climate conditions (Chapter 3). These findings demonstrate a coherent causal chain: environmental drivers shape fire regimes, fire acts as an evolutionary filter on plant traits, and traits determine post-fire ecosystem function and resilience. This thesis provides both empirical evidence and a theoretical framework for integrating trait–fire relationships into Earth system models, providing insights on moving beyond empirical parameterisation toward simplified, mechanistic representations. By grounding fire ecology in biophysical constraints and eco-evolutionary principles, this research enhances our ability to predict vegetation– fire feedbacks and informs management strategies in an era of intensifying global fire activity.

Item Type	Thesis (PhD)
URI	https://centaur.reading.ac.uk/id/eprint/127880
Identification Number/DOI	10.48683/1926.00127880
Divisions	Science > School of Archaeology, Geography and Environmental Science
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