Upgrading from M version 0.2: An application-based method for practical estimation, evaluation and uncertainty characterization of natural mortality
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Upgrading from M version 0.2: An application-based method for practical estimation, evaluation and uncertainty characterization of natural mortality

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  • Journal Title:
    Fisheries Research
  • Personal Author:
  • NOAA Program & Office:
    NOAA General Documents
  • Description:
    Natural morality (M) is a notoriously difficult population parameter to estimate, yet it is also one of the most important measures of life history that sets, as Beverton and Holt called it, "the course of events". Stock assessments that include this parameter often show great sensitivity to its value, reflecting the need to characetrize the uncertainty inherent in its estimation. Direct measurement of natural mortality is often limited to resource intensive tag-recapture studies. Indirect measures are more often used, and are built on life history theory, relating natural mortality to traits such as age, size, maturity and reproductive condition (or just assuming 0.2). The Natural Mortality Tool attempts to accumulate several empirical estimators of M into one application. Users simply input life history values to obtain estimates of natural mortality. These estimates can be taken individually or can be combined into a weighted density function that can be used to develop an M prior that integrates uncertainty across several estimates. Comparing estimators can also reveal inconsistencies in life history values that may lead to further refining of basic biological understanding. Two examples are used to demonstrate tool functionality and highlight general recommendations on implementation. Making these estimators and the development of uncertainty in estimating natural mortality more widely available hopefully supports transparent and defensible decision-making on the treatment of this important population parameter.
  • Keywords:
  • Source:
    Fisheries Research, 256, 106493
  • DOI:
  • ISSN:
    0165-7836
  • Format:
    PDF
  • Publisher:
    Elsevier BV
  • Document Type:
    Journal Article
  • Rights Information:
    Accepted Manuscript
  • Compliance:
    Library
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