Scaling up phenotypic plasticity with hierarchical population models |
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Authors: | Eelke Jongejans Heidrun Huber Hans de Kroon |
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Institution: | (1) Department of Experimental Plant Ecology, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands;(2) Nature Conservation and Plant Ecology Group, Wageningen University, Droevendaalsesteeg 3a, 6708 PB Wageningen, The Netherlands |
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Abstract: | Individuals respond to different environments by developing different phenotypes, which is generally seen as a mechanism through
which individuals can buffer adverse environmental conditions and increase their fitness. To understand the consequences of
phenotypic plasticity it is necessary to study how changing a particular trait of an individual affects either its survival,
growth, reproduction or a combination of these demographic vital rates (i.e. fitness components). Integrating vital rate changes
due to phenotypic plasticity into models of population dynamics allows detailed study of how phenotypic changes scale up to
higher levels of integration and forms an excellent tool to distinguish those plastic trait changes that really matter at
the population level. A modeling approach also facilitates studying systems that are even more complex: traits and vital rates
often co-vary or trade-off with other traits that may show plastic responses over environmental gradients. Here we review
recent developments in the literature on population models that attempt to include phenotypic plasticity with a range of evolutionary
assumptions and modeling techniques. We present in detail a model framework in which environmental impacts on population dynamics
can be followed analytically through direct and indirect pathways that importantly incorporate phenotypic plasticity, trait-trait
and trait-vital rate relationships. We illustrate this framework with two case studies: the population-level consequences
of phenotypic responses to nutrient enrichment of plant species occurring in nutrient-poor habitats and of responses to changes
in flooding regimes due to climate change. We conclude with exciting prospects for further development of this framework:
selection analyses, modeling advances and the inclusion of spatial dynamics by considering dispersal traits as well. |
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