Abstract
Coastal fisheries are typically characterized by species-rich catch compositions and limited management resources, which typically leads to notably data-poor situations for stock assessment. Some parsimonious stock assessment approaches rely on cost-efficient size composition data, but these also require estimates of life history parameters associated with natural mortality, growth, and maturity. These parameters are unavailable for most exploited stocks. Here, we present a novel approach that uses a local estimate of maximum length and statistical relationships between key life history parameters to build multivariate probability distributions that can be used to parameterize stock assessment models in the absence of speciesspecific life history data. We tested this approach on three fish species for which empirical length-at-age and maturity data were available (from Hawaii and Guam) and calculated probability distributions of spawning potential ratios (SPR) at different exploitation rates. The life history parameter and SPR probability distributions generated from our data-limited analytical approach compared well with those obtained from bootstrap analyses of the empirical life history data. This work provides a useful new tool that can greatly assist fishery stock assessment scientists and managers in data-poor situations, typical of most of the world’s fisheries.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1874-1884 |
| Number of pages | 11 |
| Journal | Canadian Journal of Fisheries and Aquatic Sciences |
| Volume | 73 |
| Issue number | 12 |
| DOIs | |
| State | Published - Aug 16 2016 |
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ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Aquatic Science
Cite this
A stepwise stochastic simulation approach to estimate life history parameters for data-poor fisheries. / Nadon, Marc O.; Ault, Jerald S.
In: Canadian Journal of Fisheries and Aquatic Sciences, Vol. 73, No. 12, 16.08.2016, p. 1874-1884.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A stepwise stochastic simulation approach to estimate life history parameters for data-poor fisheries
AU - Nadon, Marc O.
AU - Ault, Jerald S
PY - 2016/8/16
Y1 - 2016/8/16
N2 - Coastal fisheries are typically characterized by species-rich catch compositions and limited management resources, which typically leads to notably data-poor situations for stock assessment. Some parsimonious stock assessment approaches rely on cost-efficient size composition data, but these also require estimates of life history parameters associated with natural mortality, growth, and maturity. These parameters are unavailable for most exploited stocks. Here, we present a novel approach that uses a local estimate of maximum length and statistical relationships between key life history parameters to build multivariate probability distributions that can be used to parameterize stock assessment models in the absence of speciesspecific life history data. We tested this approach on three fish species for which empirical length-at-age and maturity data were available (from Hawaii and Guam) and calculated probability distributions of spawning potential ratios (SPR) at different exploitation rates. The life history parameter and SPR probability distributions generated from our data-limited analytical approach compared well with those obtained from bootstrap analyses of the empirical life history data. This work provides a useful new tool that can greatly assist fishery stock assessment scientists and managers in data-poor situations, typical of most of the world’s fisheries.
AB - Coastal fisheries are typically characterized by species-rich catch compositions and limited management resources, which typically leads to notably data-poor situations for stock assessment. Some parsimonious stock assessment approaches rely on cost-efficient size composition data, but these also require estimates of life history parameters associated with natural mortality, growth, and maturity. These parameters are unavailable for most exploited stocks. Here, we present a novel approach that uses a local estimate of maximum length and statistical relationships between key life history parameters to build multivariate probability distributions that can be used to parameterize stock assessment models in the absence of speciesspecific life history data. We tested this approach on three fish species for which empirical length-at-age and maturity data were available (from Hawaii and Guam) and calculated probability distributions of spawning potential ratios (SPR) at different exploitation rates. The life history parameter and SPR probability distributions generated from our data-limited analytical approach compared well with those obtained from bootstrap analyses of the empirical life history data. This work provides a useful new tool that can greatly assist fishery stock assessment scientists and managers in data-poor situations, typical of most of the world’s fisheries.
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U2 - 10.1139/cjfas-2015-0303
DO - 10.1139/cjfas-2015-0303
M3 - Article
AN - SCOPUS:84994908799
VL - 73
SP - 1874
EP - 1884
JO - Canadian Journal of Fisheries and Aquatic Sciences
JF - Canadian Journal of Fisheries and Aquatic Sciences
SN - 0706-652X
IS - 12
ER -