Evolution of flowering decisions in a stochastic, density-dependent environment

C. J.E. Metcalf; K. E. Rose; D. Z. Childs; A. W. Sheppard; P. J. Grubb; M. Rees

doi:10.1073/pnas.0800777105

Evolution of flowering decisions in a stochastic, density-dependent environment

C. J.E. Metcalf, K. E. Rose, D. Z. Childs, A. W. Sheppard, P. J. Grubb, M. Rees

Research output: Contribution to journal › Article › peer-review

46 Scopus citations

Abstract

Demography is central to both ecology and evolution, and characterizing the feedback between ecology and evolution is critical for understanding organisms' life histories and how these might evolve through time. Here, we show how, by combining a range of theoretical approaches with the statistical analysis of individually structured databases, accurate prediction of life history decisions is possible in natural density-regulated populations undergoing large fluctuations in demographic rates from year to year. Our predictions are remarkably accurate and statistically well defined. In addition, we show that the predicted trait values are evolutionarily and convergence stable and that protected polymorphisms are possible.

Original language	English (US)
Pages (from-to)	10466-10470
Number of pages	5
Journal	Proceedings of the National Academy of Sciences of the United States of America
Volume	105
Issue number	30
DOIs	https://doi.org/10.1073/pnas.0800777105
State	Published - Jul 29 2008
Externally published	Yes

All Science Journal Classification (ASJC) codes

General

Keywords

Adaptive dynamics
Carduus nutans
Carlina vulgaris
Coexistence
Relative nonlinearity of competition

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title = "Evolution of flowering decisions in a stochastic, density-dependent environment",

abstract = "Demography is central to both ecology and evolution, and characterizing the feedback between ecology and evolution is critical for understanding organisms' life histories and how these might evolve through time. Here, we show how, by combining a range of theoretical approaches with the statistical analysis of individually structured databases, accurate prediction of life history decisions is possible in natural density-regulated populations undergoing large fluctuations in demographic rates from year to year. Our predictions are remarkably accurate and statistically well defined. In addition, we show that the predicted trait values are evolutionarily and convergence stable and that protected polymorphisms are possible.",

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T1 - Evolution of flowering decisions in a stochastic, density-dependent environment

AU - Metcalf, C. J.E.

AU - Rose, K. E.

AU - Childs, D. Z.

AU - Sheppard, A. W.

AU - Grubb, P. J.

AU - Rees, M.

PY - 2008/7/29

Y1 - 2008/7/29

N2 - Demography is central to both ecology and evolution, and characterizing the feedback between ecology and evolution is critical for understanding organisms' life histories and how these might evolve through time. Here, we show how, by combining a range of theoretical approaches with the statistical analysis of individually structured databases, accurate prediction of life history decisions is possible in natural density-regulated populations undergoing large fluctuations in demographic rates from year to year. Our predictions are remarkably accurate and statistically well defined. In addition, we show that the predicted trait values are evolutionarily and convergence stable and that protected polymorphisms are possible.

AB - Demography is central to both ecology and evolution, and characterizing the feedback between ecology and evolution is critical for understanding organisms' life histories and how these might evolve through time. Here, we show how, by combining a range of theoretical approaches with the statistical analysis of individually structured databases, accurate prediction of life history decisions is possible in natural density-regulated populations undergoing large fluctuations in demographic rates from year to year. Our predictions are remarkably accurate and statistically well defined. In addition, we show that the predicted trait values are evolutionarily and convergence stable and that protected polymorphisms are possible.

KW - Adaptive dynamics

KW - Carduus nutans

KW - Carlina vulgaris

KW - Coexistence

KW - Relative nonlinearity of competition

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Evolution of flowering decisions in a stochastic, density-dependent environment

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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