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https://hdl.handle.net/1959.11/18832
Title: | Improved estimation of intrinsic growth rmax for long-lived species: integrating matrix models and allometry | Contributor(s): | Dillingham, Peter (author); Moore, Jeffrey E (author); Fletcher, David (author); Cortes, Enric (author); Curtis, K Alexandra (author); James, Kelsey C (author); Lewison, Rebecca L (author) | Publication Date: | 2016 | DOI: | 10.1890/14-1990 | Handle Link: | https://hdl.handle.net/1959.11/18832 | Abstract: | Intrinsic population growth rate (r max) is an important parameter for many ecological applications, such as population risk assessment and harvest management. However, r max can be a diffi cult parameter to estimate, particularly for long-lived species, for which appropriate life table data or abundance time series are typically not obtainable. We describe a method for improving estimates of r max for long-lived species by integrating life-history theory (allometric models) and population-specific demographic data (life table models). Broad allometric relationships, such as those between life history traits and body size, have long been recognized by ecologists. These relationships are useful for deriving theoretical expectations for r max , but r max for real populations may vary from simple allometric estimators for "archetypical" species of a given taxa or body mass. Meanwhile, life table approaches can provide population-specific estimates of r max from empirical data, but these may have poor precision from imprecise and missing vital rate parameter estimates. Our method borrows strength from both approaches to provide estimates that are consistent with both life-history theory and population-specific empirical data, and are likely to be more robust than estimates provided by either method alone. Our method uses an allometric constant: the product of r max and the associated generation time for a stable-age population growing at this rate. We conducted a meta-analysis to estimate the mean and variance of this allometric constant across well-studied populations from three vertebrate taxa (birds, mammals, and elasmobranchs) and found that the mean was approximately 1.0 for each taxon. We used these as informative Bayesian priors that determine how much to "shrink" imprecise vital rate estimates for a data-limited population toward the allometric expectation. The approach ultimately provides estimates of r max (and other vital rates) that reflect a balance of information from the individual studied population, theoretical expectation, and meta-analysis of other populations. We applied the method specifically to an archetypical petrel (representing the genus 'Procellaria') and to white sharks ('Carcharodon carcharias') in the context of estimating sustainable fishery bycatch limits. | Publication Type: | Journal Article | Source of Publication: | Ecological Applications, 26(1), p. 322-333 | Publisher: | John Wiley & Sons, Inc | Place of Publication: | United States of America | ISSN: | 1939-5582 1051-0761 |
Fields of Research (FoR) 2008: | 010401 Applied Statistics 060207 Population Ecology 050202 Conservation and Biodiversity |
Fields of Research (FoR) 2020: | 490501 Applied statistics 310307 Population ecology 410401 Conservation and biodiversity |
Socio-Economic Objective (SEO) 2008: | 960609 Sustainability Indicators 970101 Expanding Knowledge in the Mathematical Sciences 970105 Expanding Knowledge in the Environmental Sciences |
Socio-Economic Objective (SEO) 2020: | 190209 Sustainability indicators 280118 Expanding knowledge in the mathematical sciences 280111 Expanding knowledge in the environmental sciences |
Peer Reviewed: | Yes | HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
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Appears in Collections: | Journal Article |
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