The importance of network spatial structure as a driver of eco‐evolutionary dynamics
Investigating eco‐evolutionary responses of populations to environmental changes requires a solid understanding of the spatial context in which they evolve. While the interplay between local adaptation and dispersal in guiding evolutionary outcomes has been studied extensively, it is often in a cont...
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crwiley:10.1111/ecog.06933 2024-09-15T17:56:30+00:00 The importance of network spatial structure as a driver of eco‐evolutionary dynamics Lamarins, Amaïa Prévost, Etienne Carlson, Stephanie M. Buoro, Mathieu 2023 http://dx.doi.org/10.1111/ecog.06933 https://onlinelibrary.wiley.com/doi/pdf/10.1111/ecog.06933 en eng Wiley http://creativecommons.org/licenses/by/3.0/ Ecography volume 2024, issue 1 ISSN 0906-7590 1600-0587 journal-article 2023 crwiley https://doi.org/10.1111/ecog.06933 2024-08-01T04:20:29Z Investigating eco‐evolutionary responses of populations to environmental changes requires a solid understanding of the spatial context in which they evolve. While the interplay between local adaptation and dispersal in guiding evolutionary outcomes has been studied extensively, it is often in a context of divergent selection and simplified spatial structure. Alternatively, we used a spatially‐explicit demo‐genetic agent‐based model to simulate a complex network of interconnected populations of Atlantic salmon facing a perturbation shifting their genetic composition to create diversity among populations. Our model allowed us to track emerging demographic, phenotypic, and evolutionary changes from the individual to the metapopulation in a single, spatially realistic framework. We analyzed the influence of the spatial structure of genetic diversity and populations on the evolutionary dynamics under convergent selection (toward a common optimum). Our simulations showed adaptation and demographic recovery of local populations was enhanced by dispersal between initially diverse populations, providing general support for the adaptation network theory. This was particularly true for increased dispersal rates and a random spatial genetic structure. Importantly, our spatially realistic model emphasized that the evolutionary and demographic trajectories of local populations are context‐dependent and can be heavily influenced by the spatial configuration of populations linked by dispersal. Overall, the adaptive capacity of the network depended on the ‘opportunity for adaptation' provided by immigration patterns that emerged from the connectivity structures of the scenarios tested. We highlight the importance of spatial diversity and population structure for the ability of species to respond to environmental change, with implications for management and conservation of spatially structured populations. Article in Journal/Newspaper Atlantic salmon Wiley Online Library Ecography |
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English |
description |
Investigating eco‐evolutionary responses of populations to environmental changes requires a solid understanding of the spatial context in which they evolve. While the interplay between local adaptation and dispersal in guiding evolutionary outcomes has been studied extensively, it is often in a context of divergent selection and simplified spatial structure. Alternatively, we used a spatially‐explicit demo‐genetic agent‐based model to simulate a complex network of interconnected populations of Atlantic salmon facing a perturbation shifting their genetic composition to create diversity among populations. Our model allowed us to track emerging demographic, phenotypic, and evolutionary changes from the individual to the metapopulation in a single, spatially realistic framework. We analyzed the influence of the spatial structure of genetic diversity and populations on the evolutionary dynamics under convergent selection (toward a common optimum). Our simulations showed adaptation and demographic recovery of local populations was enhanced by dispersal between initially diverse populations, providing general support for the adaptation network theory. This was particularly true for increased dispersal rates and a random spatial genetic structure. Importantly, our spatially realistic model emphasized that the evolutionary and demographic trajectories of local populations are context‐dependent and can be heavily influenced by the spatial configuration of populations linked by dispersal. Overall, the adaptive capacity of the network depended on the ‘opportunity for adaptation' provided by immigration patterns that emerged from the connectivity structures of the scenarios tested. We highlight the importance of spatial diversity and population structure for the ability of species to respond to environmental change, with implications for management and conservation of spatially structured populations. |
format |
Article in Journal/Newspaper |
author |
Lamarins, Amaïa Prévost, Etienne Carlson, Stephanie M. Buoro, Mathieu |
spellingShingle |
Lamarins, Amaïa Prévost, Etienne Carlson, Stephanie M. Buoro, Mathieu The importance of network spatial structure as a driver of eco‐evolutionary dynamics |
author_facet |
Lamarins, Amaïa Prévost, Etienne Carlson, Stephanie M. Buoro, Mathieu |
author_sort |
Lamarins, Amaïa |
title |
The importance of network spatial structure as a driver of eco‐evolutionary dynamics |
title_short |
The importance of network spatial structure as a driver of eco‐evolutionary dynamics |
title_full |
The importance of network spatial structure as a driver of eco‐evolutionary dynamics |
title_fullStr |
The importance of network spatial structure as a driver of eco‐evolutionary dynamics |
title_full_unstemmed |
The importance of network spatial structure as a driver of eco‐evolutionary dynamics |
title_sort |
importance of network spatial structure as a driver of eco‐evolutionary dynamics |
publisher |
Wiley |
publishDate |
2023 |
url |
http://dx.doi.org/10.1111/ecog.06933 https://onlinelibrary.wiley.com/doi/pdf/10.1111/ecog.06933 |
genre |
Atlantic salmon |
genre_facet |
Atlantic salmon |
op_source |
Ecography volume 2024, issue 1 ISSN 0906-7590 1600-0587 |
op_rights |
http://creativecommons.org/licenses/by/3.0/ |
op_doi |
https://doi.org/10.1111/ecog.06933 |
container_title |
Ecography |
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1810432697382731776 |