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Advancing environmentally explicit structured population models of plants

Publication ,  Journal Article
Ehrlén, J; Morris, WF; von Euler, T; Dahlgren, JP
Published in: Journal of Ecology
March 1, 2016

The relationship between the performance of individuals and the surrounding environment is fundamental in ecology and evolutionary biology. Assessing how abiotic and biotic environmental factors influence demographic processes is necessary to understand and predict population dynamics, as well as species distributions and abundances. We searched the literature for studies that have linked abiotic and biotic environmental factors to vital rates and, using structured demographic models, population growth rates of plants. We found 136 studies that had examined the environmental drivers of plant demography. The number of studies has been increasing rapidly in recent years. Based on the reviewed studies, we identify and discuss several major gaps in our knowledge of environmentally driven demography of plants. We argue that some drivers may have been underexplored and that the full potential of spatially and temporally replicated studies may not have been realized. We also stress the need to employ relevant statistical methods and experiments to correctly identify drivers. Moreover, assessments of the relationship between drivers and vital rates need to consider interactive, nonlinear and indirect effects, as well as effects of intraspecific density dependence. Synthesis. Much progress has already been made by using structured population models to link the performance of individuals to the surrounding environment. However, by improving the design and analyses of future studies, we can substantially increase our ability to predict changes in plant population dynamics, abundances and distributions in response to changes in specific environmental drivers. Future environmentally explicit demographic models should also address how genetic changes prompted by selection imposed by environmental changes will alter population trajectories in the face of continued environmental change and investigate the reciprocal feedback between plants and their biotic drivers. Much progress has been made by using structured population models to link the performance of individuals to the surrounding environment. By improving the design and analyses of future studies, environmentally explicit demographic models can increase our ability to address how changes in environmental drivers will influence abundances and distributions, as well as the evolutionary dynamics of populations.

Duke Scholars

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Published In

Journal of Ecology

DOI

EISSN

1365-2745

ISSN

0022-0477

Publication Date

March 1, 2016

Volume

104

Issue

2

Start / End Page

292 / 305

Related Subject Headings

  • Ecology
  • 3103 Ecology
  • 07 Agricultural and Veterinary Sciences
  • 06 Biological Sciences
  • 05 Environmental Sciences
 

Citation

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Ehrlén, J., Morris, W. F., von Euler, T., & Dahlgren, J. P. (2016). Advancing environmentally explicit structured population models of plants. Journal of Ecology, 104(2), 292–305. https://doi.org/10.1111/1365-2745.12523
Ehrlén, J., W. F. Morris, T. von Euler, and J. P. Dahlgren. “Advancing environmentally explicit structured population models of plants.” Journal of Ecology 104, no. 2 (March 1, 2016): 292–305. https://doi.org/10.1111/1365-2745.12523.
Ehrlén J, Morris WF, von Euler T, Dahlgren JP. Advancing environmentally explicit structured population models of plants. Journal of Ecology. 2016 Mar 1;104(2):292–305.
Ehrlén, J., et al. “Advancing environmentally explicit structured population models of plants.” Journal of Ecology, vol. 104, no. 2, Mar. 2016, pp. 292–305. Scopus, doi:10.1111/1365-2745.12523.
Ehrlén J, Morris WF, von Euler T, Dahlgren JP. Advancing environmentally explicit structured population models of plants. Journal of Ecology. 2016 Mar 1;104(2):292–305.
Journal cover image

Published In

Journal of Ecology

DOI

EISSN

1365-2745

ISSN

0022-0477

Publication Date

March 1, 2016

Volume

104

Issue

2

Start / End Page

292 / 305

Related Subject Headings

  • Ecology
  • 3103 Ecology
  • 07 Agricultural and Veterinary Sciences
  • 06 Biological Sciences
  • 05 Environmental Sciences