OUTCOME · ecO-evolUTionary dynamics in COMmunitiEs

ecO-evolUTionary dynamics in COMmunitiEs

Ecological communities are composed of a vast number of interacting species. Individuals of different species interact for feeding, survival or many other services, like protection or transport. Such interactions form ecological networks. The network structure, or distribution of interactions between different species in a community, is seldom random and several measurable patterns may emerge. Two frequently detected patterns are modularity and nestedness. An ecological network is modular when it is composed of subsets or modules of species that interact more frequently among themselves than with other members of the community. An ecological network is nested when interacting partners of specialist species are subsets of the interacting partners of generalist species. At the same time, interactions between individuals of different species favour coevolution, that is reciprocal adaptation between interacting species. In addition, ecological (e.g., assembly of the network structure) and evolutionary (e.g., coevolution) processes can produce reciprocal effects. Eco-evolutionary feedback occurs when evolution of a trait impacts ecological processes (or vice versa), which feeds back to drive further evolution (or ecological dynamics) in a continuous cycle. Ultimately, ecological interactions are affected by the genetic architecture at the coevolving loci (i.e., gene or genes at a given position in a chromosome that produce traits under coevolution) of the interacting species. Matching-allele (MA) and Gene-for-gene (GFG) are common genetic architecture models to describe coevolutionary dynamics. Under a MA coevolutionary model, when a species is able to interact with a new species, it loses its ability to interact with its former interacting species. This process favours specialist species. Under a GFG coevolutionary model, a species can expand its range of interacting species without losing its ability to interact with its former interacting species. This scenario promotes generalists. Coevolving processes at the loci level are expected to spread knock-on effects at different ecological levels. For example, when interspecific interactions are driven by MA model, ecological networks will have modular structures. When a GFG model sets the interspecific interactions, ecological networks will be nested. Additionally, network structures are expected to feed back into coevolution, thus favouring specialists or generalists depending on the network structure. Parasites are tightly dependent on their hosts, despite parasite species in an ecological community usually differ in their specialisation degree for hosts. Therefore, host-parasite communities represent suitable models for studying the relationship between coevolutionary models and the structure of host-parasite networks. The overall objective of OUTCOME is to accurately model, infer and predict eco-evolutionary changes in ecological communities of many interacting species. This objective is ambitious since it aims to jointly study different processes driving ecological communities. Specifically, this project overcomes some limitations of eco-evolutionary research because it studies coevolution in communities with many interactions (coevolution is usually studied between species pairs) and considers that interaction networks may change due to coevolution (network structure is usually studied as a fixed property). Finally, it focuses on host-parasite interactions, a key component of ecological communities under constant coevolutionary pressures, that will allow us to understand the dynamic functioning of ecosystems better.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз