Escaping the tyranny of the grid: a more realistic way of defining fishing opportunities

Branch, Trevor A.; Hilborn, Ray; Bogazzi, Eugenia

doi:10.1139/f04-232

Cited by 34 publications

(23 citation statements)

References 23 publications

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“…Other species' fates can be predicted by measuring their vulnerabilities to long-term depletion by the fishery relative to the key species. For the purposes of our approach, we define a "species" at the population level and a "fishery" as a group of fishermen using a particular type of gear to target a particular group of species in a particular region, with roughly uniform relative catch rates of the species (29).…”

Section: The Eventual Threat Index (T)mentioning

confidence: 99%

Predicting overfishing and extinction threats in multispecies fisheries

Burgess¹,

Polasky

Tilman

2013

Proc. Natl. Acad. Sci. U.S.A.

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Threats to species from commercial fishing are rarely identified until species have suffered large population declines, by which time remedial actions can have severe economic consequences, such as closure of fisheries. Many of the species most threatened by fishing are caught in multispecies fisheries, which can remain profitable even as populations of some species collapse. Here we show for multispecies fisheries that the biological and socioeconomic conditions that would eventually cause species to be severely depleted or even driven extinct can be identified decades before those species experience high harvest rates or marked population declines. Because fishing effort imposes a common source of mortality on all species in a fishery, the long-term impact of a fishery on a species is predicted by measuring its loss rate relative to that of species that influence the fishery's maximal effort. We tested our approach on eight Pacific tuna and billfish populations, four of which have been identified recently as in decline and threatened with overfishing. The severe depletion of all four populations could have been predicted in the 1950s, using our approach. Our results demonstrate that species threatened by human harvesting can be identified much earlier, providing time for adjustments in harvesting practices before consequences become severe and fishery closures or other socioeconomically disruptive interventions are required to protect species.early warning | preventative management | overharvesting | mechanistic | assessment

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Section: The Eventual Threat Index (T)mentioning

confidence: 99%

Predicting overfishing and extinction threats in multispecies fisheries

Burgess¹,

Polasky

Tilman

2013

Proc. Natl. Acad. Sci. U.S.A.

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“…The value of indices calculated from survey data has long been recognized by stock assessment scientists (16). In contrast, even subtle changes in fishing behavior by fleets can have dramatic influences on the composition of fisheries landings (17).…”

mentioning

confidence: 99%

Reanalyses of Gulf of Mexico fisheries data: Landings can be misleading in assessments of fisheries and fisheries ecosystems

Mutsert

Cowan

Essington

et al. 2008

Proc. Natl. Acad. Sci. U.S.A.

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We used two high profile articles as cases to demonstrate that use of fishery landings data can lead to faulty interpretations about the condition of fishery ecosystems. One case uses the mean trophic level index and its changes, and the other uses estimates of fishery collapses. In earlier analyses by other authors, marine ecosystems in the Gulf of Mexico (GOM) and U.S. Atlantic Ocean south of Chesapeake Bay were deemed to be severely overfished and the food webs badly deteriorated using these criteria. In our reanalyses, the low mean trophic level index for the GOM actually resulted from large catches of two groups of low trophic level species, menhaden and shrimp, and the mean trophic level was slowly increasing rather than decreasing. Commercial targeting and high landings of shrimps and menhaden, especially in the GOM, drove the index as previously calculated. Reanalyses of fishery collapses incorporating criteria that included targeting, variability in fishing effort, and market forces discovered many false cases of collapse based simply upon a decline of catches to 10% of previous maximum levels. Consequently, we suggest that the low mean trophic level index calculated in the earlier article for the GOM did not reflect the overall condition of the fishery ecosystem, and that the 10% rule for collapse should not be interpreted out of context in the GOM or elsewhere. In both cases, problems lay in the assumption that commercial landings data alone adequately reflect the fish populations and communities. landings data ͉ mean trophic level index

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“…As a result, patches could shift, split, and merge throughout a season time series. Because vessels in a commercial fishery move and position themselves to seek maximum profit, spatially flexible patches are more realistic than fixed strata (Branch et al, 2005). CPUE was the sum of all vessels' D. gahi catch within a patch divided by the number of vessels; i.e., day was the unit of effort.…”

Section: Cpue Peaks and Size Structurementioning

confidence: 99%