Real-time (co)evolution in a multitrophic community under current and future climates
EvolCommunity aims to experimentally evolve multitrophic species in varying climate conditions to understand their coevolution and responses to climate change, using advanced genetic tools.
Projectdetails
Introduction
In nature, organisms live in communities and form complex trophic interactions. Understanding how multitrophic communities evolve and respond to environmental changes is a fundamental and pressing challenge in the face of global change. While research in evolutionary biology revealed that a warming climate can drive adaptive evolution of individual organisms in the community, studies from community ecology showed that a warming climate can alter trophic interactions and community structure, which in turn changes the (co)evolutionary trajectory of interacting species.
Importance of Integration
Thus, integrating evolutionary and ecological responses is crucial to understand the climate responses of individual species and communities. However, methodological challenges have hampered empirical studies until now.
Project Overview
EvolCommunity will address these challenges by experimentally evolving populations of three interacting species (aphid, duckweed, and daphnia) in their native communities using outdoor mesocosms with different climate conditions.
Research Objectives
We will quantify how warming shapes the function and evolution of the multitrophic community in real-time. The specific objectives include:
- Manipulating climate-driven plant evolution to determine whether plant evolution alters the community’s response to climate change.
- Assessing whether the interacting species coevolve in the community by quantifying the reciprocal selection imposed from their evolutionary changes.
- Investigating the molecular mechanisms underlying (co)evolution using state-of-the-art genetic tools.
Methodological Approach
Using a combination of experimental evolution, community manipulation, and cutting-edge genetic and analytic tools, EvolCommunity will push the research boundaries of evolutionary ecology by revealing the mechanisms and processes of community evolution at work.
Expected Outcomes
The outcomes will open new research avenues in evolutionary ecology by establishing a new methodological framework that integrates evolutionary biology and community ecology in natural communities.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.998.383 |
Totale projectbegroting | € 1.998.383 |
Tijdlijn
Startdatum | 1-2-2024 |
Einddatum | 31-1-2029 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- JOHANNES GUTENBERG-UNIVERSITAT MAINZpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
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Spatio-Seasonal Eco-Evolutionary DynamicsEcoEvoMove aims to develop new eco-evolutionary theories and empirical methods to predict how wild populations can adapt to extreme seasonal climate changes and avoid extinction. | ERC Advanced... | € 2.499.752 | 2024 | Details |
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Coevolutionary Consequences of Biodiversity Change
This project investigates how climate change alters plant-microbe interactions and coevolutionary dynamics, revealing impacts on biodiversity and ecosystem functioning over 35 years.
Feedback between population dynamics and evolution of interactions in a tri-trophic system
DYNAMICTRIO aims to analyze eco-evolutionary dynamics in a tri-trophic system to develop tools for predicting ecosystem responses to environmental changes.
Using thermal limits to understand community response to climate warming
This project aims to predict the thermal vulnerability of multi-trophic lake communities to climate change by integrating species interactions, acclimation, and food web dynamics through experimental and modeling approaches.
Spatio-Seasonal Eco-Evolutionary Dynamics
EcoEvoMove aims to develop new eco-evolutionary theories and empirical methods to predict how wild populations can adapt to extreme seasonal climate changes and avoid extinction.
Mapping vast functional landscapes with single-species resolution: a new approach for precision engineering of microbial consortia
ECOPROSPECTOR aims to optimize microbial community composition for enhanced starch hydrolysis using machine learning and evolutionary theories, bridging ecology and biotechnology.