Building on 150 Years of Knowledge : The Freshwater Isopod Asellus aquaticus as an Integrative Eco-Evolutionary Model System
Lafuente, E., Lürig, M. D., Rövekamp, M., Matthews, B., Buser, C., Vorburger, C., & Räsänen, K. (2021). Building on 150 Years of Knowledge : The Freshwater Isopod Asellus aquaticus as an Integrative Eco-Evolutionary Model System. Frontiers in Ecology and Evolution, 9, Article 748212. https://doi.org/10.3389/fevo.2021.748212
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Frontiers in Ecology and EvolutionAuthors
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2021Copyright
© 2021 the Authors
Interactions between organisms and their environments are central to how biological diversity arises and how natural populations and ecosystems respond to environmental change. These interactions involve processes by which phenotypes are affected by or respond to external conditions (e.g., via phenotypic plasticity or natural selection) as well as processes by which organisms reciprocally interact with the environment (e.g., via eco-evolutionary feedbacks). Organism-environment interactions can be highly dynamic and operate on different hierarchical levels, from genes and phenotypes to populations, communities, and ecosystems. Therefore, the study of organism-environment interactions requires integrative approaches and model systems that are suitable for studies across different hierarchical levels. Here, we introduce the freshwater isopod Asellus aquaticus, a keystone species and an emerging invertebrate model system, as a prime candidate to address fundamental questions in ecology and evolution, and the interfaces therein. We review relevant fields of research that have used A. aquaticus and draft a set of specific scientific questions that can be answered using this species. Specifically, we propose that studies on A. aquaticus can help understanding (i) the influence of host-microbiome interactions on organismal and ecosystem function, (ii) the relevance of biotic interactions in ecosystem processes, and (iii) how ecological conditions and evolutionary forces facilitate phenotypic diversification.
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ML received financial support from the Swiss National Science Foundation through an Early Postdoc. Mobility Grant with the No. P2EZP3_191804 and from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement No. 898932.License
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