A novel length-based empirical estimation method of spawning potential ratio (SPR), and tests of its performance, for small-scale, data-poor fisheries

By Adrian R. Hordyk, K. Ono, S. Valencia, N. Loneragan, J. Prince. 2015

396 citations recorded by the source corpus.

Subfields: Aquatic Science, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/0ab9026be399e3e00b963c69f045736836cfd0be

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In Aquatic Science

In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

Research Priorities to Support Effective Manta and Devil Ray Conservation (2018, background): “, 2016a) and the length based spawning potential ratio (Hordyk et al., 2015) to evaluate the status of mobulid populations.”
An evaluation of an iterative harvest strategy for data-poor fisheries using the length-based spawning potential ratio assessment methodology (2015, methodology): “The M/k ratio is a major determinant of the shape of the unfished size composition in populations under equilibrium (Hordyk et al., 2014a,b; Prince et al., 2014), and the biological parameters for the MSE were based on three species that covered a range of M/k ratios (Table 1): (i) Pacific mackerel…”
Revisiting the concept of Beverton -Holt life-history invariants with the aim of informing data-poor fisheries assessment (2015, background): “…“borrowing” knowledge from well-studied species to apply to related, unstudied species and populations, and when applied together with the assessment technique described by Hordyk et al. (2015b), could make simple forms of size-based assessment possible for many currently unassessable fish stocks.”
Some explorations of the life history ratios to describe length composition, spawning-per-recruit, and the spawning potential ratio (2015, methodology): “link between the life history ratios, the expected equilibrium size composition, and SPR, this study provides the potential to develop a cost-effective technique to assess data-poor fisheries using length frequency data; an idea that is further developed in an accompanying paper (Hordyk et al., 2015”
A simple length-structured model based on life history ratios and incorporating size-dependent selectivity: application to spawning potential ratios for data-poor stocks (2016, methodology): “325 Four sets of equilibrium size distributions, representing the four different life history 326 types (Table 1), were generated with both the LB-SPR model (Hordyk et al. 2015b, 2015c) 327 and the GTG LB-SPR model.”
On the pile‐up effect and priors for Linf and M/K: response to a comment by Hordyk et al. on “A new approach for estimating stock status from length frequency data” (2018, background): “Note that LBSPR gives estimates of spawning potential ratio (SPR), where values below 0.2 ( 0.5 B/Bmsy) indicate depletion and values above 0.4 ( 1.0 B/ Bmsy) indicate good stock status.”