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<p>In the spatial management of marine resources, there are a variety of contexts in which it is valuable to estimate local, site-specific demographic rates, particularly harvest rates. For example, in the case of no-take marine reserves, estimating the fishing mortality rate (<i>F</i>) prior to reserve implementation can inform quantitative expectations for increases in the abundance of protected populations in the reserve. Additionally, estimating <i>F</i> after implementation could be used to detect poaching. Often the data available for these estimates are length-abundance survey data, such as from visual diver or camera surveys. One can estimate <i>F</i> by fitting models to population size-structure data; understanding how the accuracy of such estimates depends on sampling effort and fish life history can inform monitoring approaches. Here, we quantified the capacity of a state-space integral projection model (SS-IPM) to estimate local <i>F</i>, and how that depends on life history, the true value of <i>F</i>, and monitoring sampling design. We found that estimates of <i>F</i> were (a) more accurate for species with lower natural mortality rates and (b) less precise for higher values of <i>F</i>. Yet, with enough sampling effort, estimates of <i>F</i> were generally within 10% of the true value. In general, estimating local <i>F</i> reliably requires sampling ≥ 100 fish each year over at least 12–15&#xa0;years. We used empirical data from California to illustrate these general results, which could inform adaptive management plans for other marine reserves globally.</p>

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Quantifying local fishing mortality rates to inform monitoring design for marine reserves

  • 期刊论文

  • 发表日期：

    2025年5月22日

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  • Lauren Yamane,
  • Katherine A. Kaplan,
  • J. Wilson White,
  • Jennifer E. Caselle,
  • Daniel Malone,
  • Mark H. Carr,
  • Marissa L. Baskett,
  • Alan Hastings,
  • Louis W. Botsford

摘要

In the spatial management of marine resources, there are a variety of contexts in which it is valuable to estimate local, site-specific demographic rates, particularly harvest rates. For example, in the case of no-take marine reserves, estimating the fishing mortality rate (F) prior to reserve implementation can inform quantitative expectations for increases in the abundance of protected populations in the reserve. Additionally, estimating F after implementation could be used to detect poaching. Often the data available for these estimates are length-abundance survey data, such as from visual diver or camera surveys. One can estimate F by fitting models to population size-structure data; understanding how the accuracy of such estimates depends on sampling effort and fish life history can inform monitoring approaches. Here, we quantified the capacity of a state-space integral projection model (SS-IPM) to estimate local F, and how that depends on life history, the true value of F, and monitoring sampling design. We found that estimates of F were (a) more accurate for species with lower natural mortality rates and (b) less precise for higher values of F. Yet, with enough sampling effort, estimates of F were generally within 10% of the true value. In general, estimating local F reliably requires sampling ≥ 100 fish each year over at least 12–15 years. We used empirical data from California to illustrate these general results, which could inform adaptive management plans for other marine reserves globally.