Summary
Predicting ecosystems response to ongoing environmental shifts is a major challenge in ecology and evolution, which is tightly linked with the eco-evolutionary feedback loop. However, we lack studies that thoroughly examine the whole loop of ecology to evolution and back. Moreover, there is a dire need for comprehensive studies on the mechanisms involved in this feedback that integrate different biological levels. With DYNAMICTRIO, we will perform an in-depth and multilevel analysis of the eco-evolutionary process, by combining experimental evolution and theoretical modelling of a tri-trophic system composed of plants (Arabidopsis thaliana), herbivores (Tetranychus urticae), and predators (Amblyseius swirskii). First, we will quantify the impact of ecosystem productivity and environmental stress on ecological dynamics (aim 1). Second, we will address how the interplay between ecosystem stability and population dynamics determine (trait and genomic) evolution (aim 2). Third, we will examine how the evolution of direct and indirect interactions affect species evolution and ecosystem resilience (aim 3). Finally, using the huge body of experimental data produced, we will examine how population dynamics, system stability, and interspecific interactions shape the genotype to phenotype to fitness map of each population. This will allow us to incorporate the ecology-evolution feedback loop into fitness landscape models (aim 4). By building on the combination of powerful empirical and theoretical approaches, which I have been developing throughout my career, DYNAMICTRIO provides an extensive, multidisciplinary understanding of the mechanisms underlying eco-evolutionary dynamics. The long-term goal of DYNAMICTRIO is the development of statistical and theoretical tools that properly integrate the different components of the eco-evolutionary loop and generate the much-needed predictions on how a broad range of ecosystems persist in a fast-changing world.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101042392 |
| Start date: | 01-10-2022 |
| End date: | 30-09-2027 |
| Total budget - Public funding: | 2 083 871,00 Euro - 2 083 871,00 Euro |
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Original description
Predicting ecosystems response to ongoing environmental shifts is a major challenge in ecology and evolution, which is tightly linked with the eco-evolutionary feedback loop. However, we lack studies that thoroughly examine the whole loop of ecology to evolution and back. Moreover, there is a dire need for comprehensive studies on the mechanisms involved in this feedback that integrate different biological levels. With DYNAMICTRIO, we will perform an in-depth and multilevel analysis of the eco-evolutionary process, by combining experimental evolution and theoretical modelling of a tri-trophic system composed of plants (Arabidopsis thaliana), herbivores (Tetranychus urticae), and predators (Amblyseius swirskii). First, we will quantify the impact of ecosystem productivity and environmental stress on ecological dynamics (aim 1). Second, we will address how the interplay between ecosystem stability and population dynamics determine (trait and genomic) evolution (aim 2). Third, we will examine how the evolution of direct and indirect interactions affect species evolution and ecosystem resilience (aim 3). Finally, using the huge body of experimental data produced, we will examine how population dynamics, system stability, and interspecific interactions shape the genotype to phenotype to fitness map of each population. This will allow us to incorporate the ecology-evolution feedback loop into fitness landscape models (aim 4). By building on the combination of powerful empirical and theoretical approaches, which I have been developing throughout my career, DYNAMICTRIO provides an extensive, multidisciplinary understanding of the mechanisms underlying eco-evolutionary dynamics. The long-term goal of DYNAMICTRIO is the development of statistical and theoretical tools that properly integrate the different components of the eco-evolutionary loop and generate the much-needed predictions on how a broad range of ecosystems persist in a fast-changing world.Status
SIGNEDCall topic
ERC-2021-STGUpdate Date
09-02-2023
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