Host-parasite communities compose networks of interacting individuals of different species. These communities are constantly coevolving, i.e. reciprocal selective pressures. Coevolution produces ecological changes, such as dynamic...
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Información proyecto OUTCOME
Duración del proyecto: 34 meses
Fecha Inicio: 2024-03-13
Fecha Fin: 2027-01-31
Fecha límite de participación
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Descripción del proyecto
Host-parasite communities compose networks of interacting individuals of different species. These communities are constantly coevolving, i.e. reciprocal selective pressures. Coevolution produces ecological changes, such as dynamics in demographies or in the distribution of interactions. Such ecological changes may feedback to drive further evolution in the communities. However, coevolutionary research usually focuses on isolated host-parasite pairs, assuming that the ecological effects can be ignored. Similarly, ecological studies argue that coevolution is not fast enough to affect ecological processes. Hence, the reciprocal effect, or eco-evolutionary feedback, is generally ignored by both evolutionary and ecological studies when evaluating host-parasite interactions. These assumptions possibly lead us to inaccurate understanding of the processes driving host-parasite communities and ecosystem dynamics in general. I aim to infer and predict coevolutionary outcomes in communities of several host and parasite species from host-parasite interaction networks and demographic histories. I will develop a unique combination of coevolutionary footprints in whole-genome sequences with dynamic network analysis (i.e. the network changes the distribution of interactions according to selected genotypes over time). I will use theoretical models and simulated data to link population genetics with interaction establishment and specificity at the ecological community level. Using the theoretical models, I will finally build statistical inference tools to infer and predict changes in real-world ecosystems based on empirical genome and network data. OUTCOME brings together studies on genomic coevolution (Prof Tellier, TUM), eco-evolutionary dynamics in empirical communities (Dr Möst, UIBK), and communities as complex networks (Dr Llopis-Belenguer). It will result in an enriching two-way transfer of knowledge and a complete development of the candidate as an independent researcher.