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Advancing environmentally explicit structured population models of plants
Stockholm Univ, Dept Ecol Environm & Plant Sci, SE-10691 Stockholm, Sweden..
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics. Duke Univ, Dept Biol, Box 90338, Durham, NC 27708 USA..
Stockholm Univ, Dept Ecol Environm & Plant Sci, SE-10691 Stockholm, Sweden..
Univ So Denmark, Dept Biol, Campusvej 55, DK-5230 Odense M, Denmark.;Univ So Denmark, Max Planck Odense Ctr Biodemog Aging, Campusvej 55, DK-5230 Odense M, Denmark..
2016 (English)In: Journal of Ecology, ISSN 0022-0477, E-ISSN 1365-2745, Vol. 104, no 2, 292-305 p.Article in journal (Refereed) PublishedText
Abstract [en]

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.

Place, publisher, year, edition, pages
2016. Vol. 104, no 2, 292-305 p.
Keyword [en]
demography, distribution, environmental change, environmental drivers, environmental stochasticity, non-stationary environments, plant population and community dynamics, stage-structured models, vital rates
National Category
Botany Ecology
URN: urn:nbn:se:uu:diva-282301DOI: 10.1111/1365-2745.12523ISI: 000370959800003OAI: oai:DiVA.org:uu-282301DiVA: diva2:916876
Swedish Research Council
Available from: 2016-04-05 Created: 2016-04-05 Last updated: 2016-04-05Bibliographically approved

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