Experimental evolution of dispersal: Unifying theory, experiments and natural systems
Dispersal is a central life history trait that affects the ecological and evolutionary dynamics of populations and communities. The recent use of experimental evolution for the study of dispersal is a promising avenue for demonstrating valuable proofs of concept, bringing insight into alternative di...
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Veröffentlicht in: | The Journal of animal ecology 2023-06, Vol.92 (6), p.1113-1123 |
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Hauptverfasser: | , , , , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Dispersal is a central life history trait that affects the ecological and evolutionary dynamics of populations and communities. The recent use of experimental evolution for the study of dispersal is a promising avenue for demonstrating valuable proofs of concept, bringing insight into alternative dispersal strategies and trade‐offs, and testing the repeatability of evolutionary outcomes.
Practical constraints restrict experimental evolution studies of dispersal to a set of typically small, short‐lived organisms reared in artificial laboratory conditions. Here, we argue that despite these restrictions, inferences from these studies can reinforce links between theoretical predictions and empirical observations and advance our understanding of the eco‐evolutionary consequences of dispersal.
We illustrate how applying an integrative framework of theory, experimental evolution and natural systems can improve our understanding of dispersal evolution under more complex and realistic biological scenarios, such as the role of biotic interactions and complex dispersal syndromes.
In this concepts piece, we discuss how the use of experimental evolution has improved the study of dispersal. We highlight the potential advantages and limits of such an approach, and discuss how a better integration of evolution experiments with theory and data from natural systems can further improve our understanding of dispersal evolution under more realistic biological scenarios. |
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ISSN: | 0021-8790 1365-2656 1365-2656 |
DOI: | 10.1111/1365-2656.13930 |