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Modeling the population dynamics of lemon sharks

BACKGROUND: Long-lived marine megavertebrates (e.g. sharks, turtles, mammals, and seabirds) are inherently vulnerable to anthropogenic mortality. Although some mathematical models have been applied successfully to manage these animals, more detailed treatments are often needed to assess potential dr...

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Autores principales: White, Easton R, Nagy, John D, Gruber, Samuel H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4289248/
https://www.ncbi.nlm.nih.gov/pubmed/25403640
http://dx.doi.org/10.1186/1745-6150-9-23
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author White, Easton R
Nagy, John D
Gruber, Samuel H
author_facet White, Easton R
Nagy, John D
Gruber, Samuel H
author_sort White, Easton R
collection PubMed
description BACKGROUND: Long-lived marine megavertebrates (e.g. sharks, turtles, mammals, and seabirds) are inherently vulnerable to anthropogenic mortality. Although some mathematical models have been applied successfully to manage these animals, more detailed treatments are often needed to assess potential drivers of population dynamics. In particular, factors such as age-structure, density-dependent feedbacks on reproduction, and demographic stochasticity are important for understanding population trends, but are often difficult to assess. Lemon sharks (Negaprion brevirostris) have a pelagic adult phase that makes them logistically difficult to study. However, juveniles use coastal nursery areas where their densities can be high. RESULTS: We use a stage-structured, Markov-chain stochastic model to describe lemon shark population dynamics from a 17-year longitudinal dataset at a coastal nursery area at Bimini, Bahamas. We found that the interaction between delayed breeding, density-dependence, and demographic stochasticity accounts for 33 to 49% of the variance in population size. CONCLUSIONS: Demographic stochasticity contributed all random effects in this model, suggesting that the existence of unmodeled environmental factors may be driving the majority of interannual population fluctuations. In addition, we are able to use our model to estimate the natural mortality rate of older age classes of lemon sharks that are difficult to study. Further, we use our model to examine what effect the length of a time series plays on deciphering ecological patterns. We find that—even with a relatively long time series—our sampling still misses important rare events. Our approach can be used more broadly to infer population dynamics of other large vertebrates in which age structure and demographic stochasticity are important. REVIEWERS: This article was reviewed by Yang Kuang, Christine Jacob, and Ollivier Hyrien.
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spelling pubmed-42892482015-01-11 Modeling the population dynamics of lemon sharks White, Easton R Nagy, John D Gruber, Samuel H Biol Direct Research BACKGROUND: Long-lived marine megavertebrates (e.g. sharks, turtles, mammals, and seabirds) are inherently vulnerable to anthropogenic mortality. Although some mathematical models have been applied successfully to manage these animals, more detailed treatments are often needed to assess potential drivers of population dynamics. In particular, factors such as age-structure, density-dependent feedbacks on reproduction, and demographic stochasticity are important for understanding population trends, but are often difficult to assess. Lemon sharks (Negaprion brevirostris) have a pelagic adult phase that makes them logistically difficult to study. However, juveniles use coastal nursery areas where their densities can be high. RESULTS: We use a stage-structured, Markov-chain stochastic model to describe lemon shark population dynamics from a 17-year longitudinal dataset at a coastal nursery area at Bimini, Bahamas. We found that the interaction between delayed breeding, density-dependence, and demographic stochasticity accounts for 33 to 49% of the variance in population size. CONCLUSIONS: Demographic stochasticity contributed all random effects in this model, suggesting that the existence of unmodeled environmental factors may be driving the majority of interannual population fluctuations. In addition, we are able to use our model to estimate the natural mortality rate of older age classes of lemon sharks that are difficult to study. Further, we use our model to examine what effect the length of a time series plays on deciphering ecological patterns. We find that—even with a relatively long time series—our sampling still misses important rare events. Our approach can be used more broadly to infer population dynamics of other large vertebrates in which age structure and demographic stochasticity are important. REVIEWERS: This article was reviewed by Yang Kuang, Christine Jacob, and Ollivier Hyrien. BioMed Central 2014-11-18 /pmc/articles/PMC4289248/ /pubmed/25403640 http://dx.doi.org/10.1186/1745-6150-9-23 Text en © White et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
White, Easton R
Nagy, John D
Gruber, Samuel H
Modeling the population dynamics of lemon sharks
title Modeling the population dynamics of lemon sharks
title_full Modeling the population dynamics of lemon sharks
title_fullStr Modeling the population dynamics of lemon sharks
title_full_unstemmed Modeling the population dynamics of lemon sharks
title_short Modeling the population dynamics of lemon sharks
title_sort modeling the population dynamics of lemon sharks
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4289248/
https://www.ncbi.nlm.nih.gov/pubmed/25403640
http://dx.doi.org/10.1186/1745-6150-9-23
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