Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/26738
Title: How to fit nonlinear plant growth models and calculate growth rates: An update for ecologists
Contributor(s): Paine, C E Timothy  (author)orcid ; Marthews, Toby R (author); Vogt, Deborah R (author); Purves, Drew (author); Rees, Mark (author); Hector, Andy (author); Turnbull, Lindsay A (author)
Publication Date: 2012-04
Early Online Version: 2011-11-29
Open Access: Yes
DOI: 10.1111/j.2041-210X.2011.00155.xOpen Access Link
Handle Link: https://hdl.handle.net/1959.11/26738
Abstract: 1.Plant growth is a fundamental ecological process, integrating across scales from physiology to community dynamics and ecosystem properties. Recent improvements in plant growth modelling have allowed deeper understanding and more accurate predictions for a wide range of ecological issues, including competition among plants, plant-herbivore interactions and ecosystem functioning.2.One challenge in modelling plant growth is that, for a variety of reasons, relative growth rate (RGR) almost universally decreases with increasing size, although traditional calculations assume that RGR is constant. Nonlinear growth models are flexible enough to account for varying growth rates. 3.We demonstrate a variety of nonlinear models that are appropriate for modelling plant growth and, for each, show how to calculate function-derived growth rates, which allow unbiased comparisons among species at a common time or size. We show how to propagate uncertainty in estimated parameters to express uncertainty in growth rates. Fitting nonlinear models can be challenging, so we present extensive worked examples and practical recommendations, all implemented in R.4.The use of nonlinear models coupled with function-derived growth rates can facilitate the testing of novel hypotheses in population and community ecology. For example, the use of such techniques has allowed better understanding of the components of RGR, the costs of rapid growth and the linkage between host and parasite growth rates. We hope this contribution will demystify nonlinear modelling and persuade more ecologists to use these techniques.
Publication Type: Journal Article
Source of Publication: Methods in Ecology and Evolution, 3(2), p. 245-256
Publisher: Wiley-Blackwell Publishing Ltd
Place of Publication: United Kingdom
ISSN: 2041-210X
Field of Research (FOR): 060202 Community Ecology (excl. Invasive Species Ecology)
Socio-Economic Outcome Codes: 960806 Forest and Woodlands Flora, Fauna and Biodiversity
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

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