Using thermal limits to understand community response to climate warming

Introduction

When will communities reach their upper thermal limits (i.e., their climate countdown)? A key challenge for ecology and conservation is to understand the biological processes driving community thermal limits and assess how fast warming actually pushes communities to these limits, thereby increasing their vulnerability.

Current Limitations

The difference between upper thermal limit and habitat temperature is widely used to predict thermal vulnerability. Yet, existing models are mostly limited to single species and neglect key processes such as species interactions.

Research Objectives

To predict the thermal vulnerability of multi-trophic communities, we need to scale up thermal limits from species to community. This can only be done by answering four key questions:

1. How do species interactions impact individual thermal limits?
2. How do acclimation and evolution influence community thermal limits?
3. How do temperature impacts on food web structure and community composition influence community thermal limits?
4. How does spatial heterogeneity in warming rates affect community vulnerability?

Proposed Approach

To address these four key research questions, I propose a novel integrative approach combining:

• Semi-natural aquatic experiments
• Temperature-dependent community models
• Analyses of 200 lake food webs
• Climatic projections

This ambitious research programme will evaluate how the evolutionary dynamics of each species, their interactions, and food web structure collectively contribute to defining community thermal limits. It will predict the climate countdown of lake communities and test if the latter informs of biodiversity losses induced by climate warming.

Expected Outcomes

This project will provide unprecedented insights on community thermal vulnerability by linking ecophysiology with community ecology. By uncovering the mechanisms of community thermal limits, it will contribute to understanding how communities respond to climate change and provide a new means of predicting the future of biodiversity.