English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Da Rocha, J-M., Cerviño, S., and Gutiérrez, M-J. 2010. An endogenous bioeconomic optimization algorithm to evaluate recovery plans: an application to southern hake. – ICES Journal of Marine Science, 67: 1957–1962. Recovery plans were analysed by introducing social and economic behaviour and endogenous disinvestment decisions into bioeconomic models. Considering these endogenous constraints, a dynamic optimization problem was solved to find fishing mortality (F) trajectories that maximize discounted profits per vessel, subject to recovery of the stock to a spawning-stock biomass (SSB) target in 2015. The algorithm developed was used to assess the southern hake recovery plan. Three scenarios were analysed: (1) represents the current plan with an annual 10% reduction in F; (2) represents the optimum trajectory where profits must be positive all along and the SSB target is reached no later than 2015, and (3) represents the optimum trajectory allowing profits to be negative. The results from (3) indicate that if economic and social restrictions are not considered a prior condition, the optimum solution implies a fleet reduction in 2010 and 2011. Comparing (1) and (2), our results suggest that reducing F to 0.30 by 2010 achieves the recovery target in 2012, increases the net present profits by 7.7% relative to the current plan, and is compatible with maintaining the current fleet size.