Literature DB >> 30209223

Nonlinear averaging of thermal experience predicts population growth rates in a thermally variable environment.

Joey R Bernhardt1, Jennifer M Sunday2,3, Patrick L Thompson2, Mary I O'Connor2.   

Abstract

As thermal regimes change worldwide, projections of future population and species persistence often require estimates of how population growth rates depend on temperature. These projections rarely account for how temporal variation in temperature can systematically modify growth rates relative to projections based on constant temperatures. Here, we tested the hypothesis that time-averaged population growth rates in fluctuating thermal environments differ from growth rates in constant conditions as a consequence of Jensen's inequality, and that the thermal performance curves (TPCs) describing population growth in fluctuating environments can be predicted quantitatively based on TPCs generated in constant laboratory conditions. With experimental populations of the green alga Tetraselmis tetrahele, we show that nonlinear averaging techniques accurately predicted increased as well as decreased population growth rates in fluctuating thermal regimes relative to constant thermal regimes. We extrapolate from these results to project critical temperatures for population growth and persistence of 89 phytoplankton species in naturally variable thermal environments. These results advance our ability to predict population dynamics in the context of global change.
© 2018 The Author(s).

Keywords:  Jensen's inequality; phytoplankton; population growth; scale transition theory; thermal variability

Mesh:

Year:  2018        PMID: 30209223      PMCID: PMC6158538          DOI: 10.1098/rspb.2018.1076

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


  25 in total

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Journal:  Proc Biol Sci       Date:  2018-09-12       Impact factor: 5.349

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  17 in total

1.  Nonlinear averaging of thermal experience predicts population growth rates in a thermally variable environment.

Authors:  Joey R Bernhardt; Jennifer M Sunday; Patrick L Thompson; Mary I O'Connor
Journal:  Proc Biol Sci       Date:  2018-09-12       Impact factor: 5.349

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