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WHEN TO STORE ENERGY IN A STOCHASTIC ENVIRONMENT

Authors

  • Barbara Fischer,

    1. Evolution and Ecology Program, International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria
    2. Department of Behavioural Ecology, Institute of Ecology and Evolution, University of Bern, Wohlenstrasse 50A, CH-3032 Hinterkappelen, Switzerland
    3. E-mail: barbara.fischer@bio.uio.no
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    • Present address: Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biology, University of Oslo, P.O. Box 1066 Blindern, N-0316 Oslo, Norway.

  • Ulf Dieckmann,

    1. Evolution and Ecology Program, International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria
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  • Barbara Taborsky

    1. Evolution and Ecology Program, International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria
    2. Department of Behavioural Ecology, Institute of Ecology and Evolution, University of Bern, Wohlenstrasse 50A, CH-3032 Hinterkappelen, Switzerland
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Abstract

The ability to store energy enables organisms to deal with temporarily harsh and uncertain conditions. Empirical studies have demonstrated that organisms adapted to fluctuating energy availability plastically adjust their storage strategies. So far, however, theoretical studies have investigated general storage strategies only in constant or deterministically varying environments. In this study, we analyze how the ability to store energy influences optimal energy allocation to storage, reproduction, and maintenance in environments in which energy availability varies stochastically. We find that allocation to storage is evolutionarily optimal when environmental energy availability is intermediate and energy stores are not yet too full. In environments with low variability and low predictability of energy availability, it is not optimal to store energy. As environments become more variable or more predictable, energy allocation to storage is increasingly favored. By varying environmental variability, environmental predictability, and the cost of survival, we obtain a variety of different optimal life-history strategies, from highly iteroparous to semelparous, which differ significantly in their storage patterns. Our results demonstrate that in a stochastically varying environment simultaneous allocation to reproduction, maintenance, and storage can be optimal, which contrasts with previous findings obtained for deterministic environments.

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