Status and Solutions for the World’s Unassessed Fisheries
By C. Costello, D. Ovando, Ray Hilborn, S. Gaines, O. Deschenes, S. Lester. Science, 2012
797 citations recorded by the source corpus.
Subfields: Global and Planetary Change, Nature and Landscape Conservation
View Paper: https://www.semanticscholar.org/paper/329f49019c9076ad0966a29a2d1f9e4c0d632904
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In Global and Planetary Change
In Nature and Landscape Conservation
Citations in the corpus
- Fast versus slow growing tuna species: age, growth, and implications for population dynamics and fisheries management (2017, background): “In a global context where the current exploitation status for the large majority of fish species is unknown or poorly known (Costello et al. 2012), exploitation scenarios using knowledge of fish life histories and their relative sensitivities to fishing pressure provide a starting framework to…”
- Effects of biological, economic and management factors on tuna and billfish stock status (2017, background): “As a result, an estimated 28-33% of the large well-assessed fisheries of the 69 world are overfished (Branch et al. 2011; FAO 2014), while many smaller unassessed fisheries 70 in poorer countries are likely in worse shape (Costello et al. 2012).”
- The art of ecosystem-based fishery management (2014, background): “Detailed stock assessments are currently possible for only a small fraction of exploited fish populations (Costello et al. 2012), and most of these are concentrated in the developed world.”
- Reflections on the success of traditional fisheries management (2014, background): “In addition, they are poorly studied, and their available catch data [on which the Costello et al. (2012) paper depends] are generally believed to be unreliable and almost certainly underestimated (Mills et al.”
- Ghosts of the coast: global extinction risk and conservation of sawfishes (2016, background): “Moreover, fisheries management capacity is lacking in much of the world, and – where it does exist – it has been focused on the most commercially valuable fish populations (Costello et al., 2012).”
- Improving estimates of population status and trend with superensemble models (2017, methodology): “…categories to match the simulated data set, removes the maximum catch predictor because the absolute catch in the simulated data set is arbitrary, and does not implement the bias correction needed in Costello et al. (2012) because we do not derive estimates of median status across multiple stocks.”
- 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, methodology): “This has renewed interest in simple stock-reduction analysis (SRA, Kimura and Tagart, 1982) that uses available catch trends and life history data to provide estimates of exploitation and sustainable catch limits (e.g. Dick and MacCall, 2011; Costello et al., 2012; Martell and Froese, 2013; Thorson ”