Multi-objective optimization shapes ecological variation
Abstract: Ecological systems contain a huge amount of quantitative variation between and within species and locations, which makes it difficult to obtain unambiguous verification of theoretical predictions. Ordinary experiments consider just a few explanatory factors and are prone to providing oversimplified answers because they ignore the complexity of the factors that underlie variation. We used multi-objective optimization (MO) for a mechanistic analysis of the potential ecological and evolutionary causes and consequences of variation in the life-history traits of a species of moth. Optimal life-history solutions were sought for environmental conditions where different life stages of the moth were subject to predation and other known fitness-reducing factors in a manner that was dependent on the duration of these life stages and on variable mortality rates. We found that multi-objective optimal solutions to these conditions that the moths regularly experience explained most of the life-history variation within this species. Our results demonstrate that variation can have a causal interpretation even for organisms under steady conditions. The results suggest that weather and species interactions can act as underlying causes of variation, and MO acts as a corresponding adaptive mechanism that maintains variation in the traits of organisms
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Edition
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Postprint version
- Language
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Englisch
- Notes
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IN COPYRIGHT http://rightsstatements.org/page/InC/1.0 rs
- Classification
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Tiere
- Event
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Veröffentlichung
- (where)
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Freiburg
- (who)
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Universität
- (when)
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2012
- Creator
- Contributor
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Hyytiälä Forestry Field Station, Department of Forest Sciences, University of Helsinki, Finland
Section of Ecology, Department of Biology, University of Turku, Finland
Albert-Ludwigs-Universität Freiburg
- DOI
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10.6094/UNIFR/13660
- URN
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urn:nbn:de:bsz:25-freidok-136605
- Rights
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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25.03.2025, 1:42 PM CET
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Kaitaniemi, Pekka
- Scheiner, Annette
- Klemola, Tero
- Ruohomäki, Kai
- Hyytiälä Forestry Field Station, Department of Forest Sciences, University of Helsinki, Finland
- Section of Ecology, Department of Biology, University of Turku, Finland
- Albert-Ludwigs-Universität Freiburg
- Universität
Time of origin
- 2012