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Twelve fundamental life histories evolving through allocation-dependent fecundity and survival
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics. Evolution and Ecology Program, International Institute for Applied Systems Analysis, Laxenburg, Austria.
2018 (English)In: Ecology and Evolution, ISSN 2045-7758, E-ISSN 2045-7758, Vol. 8, no 6, p. 3172-3186Article in journal (Refereed) Published
Abstract [en]

An organism's life history is closely interlinked with its allocation of energy between growth and reproduction at different life stages. Theoretical models have established that diminishing returns from reproductive investment promote strategies with simultaneous investment into growth and reproduction (indeterminate growth) over strategies with distinct phases of growth and reproduction (determinate growth). We extend this traditional, binary classification by showing that allocation-dependent fecundity and mortality rates allow for a large diversity of optimal allocation schedules. By analyzing a model of organisms that allocate energy between growth and reproduction, we find twelve types of optimal allocation schedules, differing qualitatively in how reproductive allocation increases with body mass. These twelve optimal allocation schedules include types with different combinations of continuous and discontinuous increase in reproduction allocation, in which phases of continuous increase can be decelerating or accelerating. We furthermore investigate how this variation influences growth curves and the expected maximum life span and body size. Our study thus reveals new links between eco-physiological constraints and life-history evolution and underscores how allocation-dependent fitness components may underlie biological diversity.

Place, publisher, year, edition, pages
John Wiley & Sons, 2018. Vol. 8, no 6, p. 3172-3186
Keywords [en]
determinate growth, dynamic programming, indeterminate growth, marginal value theorem, productive allocation
National Category
Ecology Evolutionary Biology
Identifiers
URN: urn:nbn:se:umu:diva-146801DOI: 10.1002/ece3.3730ISI: 000428522100011PubMedID: 29607016OAI: oai:DiVA.org:umu-146801DiVA, id: diva2:1201865
Available from: 2018-04-26 Created: 2018-04-26 Last updated: 2018-06-09Bibliographically approved

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Brännström, Åke

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  • apa
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  • de-DE
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Output format
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