Evaluating the effect of real-time closures on cod targeting

ICES Journal of Marine Science

Volumn 68, Issue 8, 2011, Pages 1647-1655

  Needle, Coby L ^a   Catarino, Rui ^a  

^a MARINE LABORATORY   (United Kingdom)

Author keywords

closed areas; cod; fleet dynamics; relative importance index; VMS data

Indexed keywords

CATCH COMPOSITION; CONSERVATION MANAGEMENT; ENVIRONMENTAL MONITORING; FISHING MORTALITY; GADOID; RESEARCH WORK; STATE ROLE;

SCOTLAND; UNITED KINGDOM;

EID: 80051969489     PISSN: 10543139     EISSN: 10959289     Source Type: Journal    
DOI: 10.1093/icesjms/fsr092     Document Type: Article

References (15)

1. Borchers, D. L., and Reid, D. G. 2008. Estimating the distribution of demersal fishing effort from VMS data using hidden Markov models. Technical Report 2008-1. CREEM, University of St Andrews. 23 pp.
2. Cleveland, W. S., Grosse, E., and Shyu, W. M. 1992. Local regression models. In Statistical Models in S, pp. 309-373. Ed. by J. M. Chambers, and T. J. Hastie. Wadsworth & Brooks/Cole, Pacific Grove. 624 pp.
3. Dinmore, T. A., Duplisea, D. E., Rackham, B. D., Maxwell, D. L., and Jennings, S. 2003. Impact of a large-scale area closure on patterns of fishing disturbance and the consequences for benthic communities. ICES Journal of Marine Science, 60: 371-380.
4. European Parliament. 2010. Real-time closures of fisheries. Note for the Directorate General for Internal Policies, Policy Department B: Structural and Cohesion Polices, Fisheries. IP/B/PECH/IC/2009-091, 15 June 2010. 56 pp. http://www.europarl.europa.eu/studies.
5. Gatt, I., and Reid, D. G. 2007. Scoping study for obtaining detailed data on the industry for fisheries management. Scottish Industry/Science Partnership (SISP) Report, 02/07. Marine Laboratory, Aberdeen. 18 pp.
6. Gellert, W., Gottwald, S., Hellwich, M., Kästner, H., and Küstner, H. 1989. The VNR Concise Encyclopedia of Mathematics, 2nd edn. Van Nostrand Reinhold, New York. 760 pp.
7. Gerritsen, H., and Lordan, C. 2011. Integrating vessel monitoring systems (VMS) data with daily catch data from logbooks to explore the spatial distribution of catch and effort at high resolution. ICES Journal of Marine Science, 68: 245-252.
8. Holmes, S. J., Bailey, N., Campbell, N., Catarino, R., Barratt, K., Gibb, A., and Fernandes, P. G. 2011. Using fishery-dependent data to inform the development and operation of a co-management initiative to reduce cod mortality and cut discards. ICES Journal of Marine Science, 68: 1679-1688.
9. Holmes, S. J., Campbell, N., Aires, C., Fernandes, P. G., Catarino, R., Bailey, N., and Barratt, K. 2009. Using VMS and fishery data in a real time closure scheme as a contribution to reducing cod mortality and discards. ICES Document CM 2009/M: 13. 27 pp.
10. Lee, J., South, A. B., and Jennings, S. 2010. Developing reliable, repeatable, and accessible methods to provide high-resolution estimates of fishing-effort distributions from vessel monitoring system (VMS) data. ICES Journal of Marine Science, 67: 1260-1271.
11. Murawski, S. A., Wigley, S. E., Fogarty, M. J., Rago, P. J., and Mountain, D. G. 2005. Effort distribution and catch patterns adjacent to temperate MPAs. ICES Journal of Marine Science, 62: 1150-1167.
12. R Development Core Team. 2008. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. http://www.R-project.org.
13. Venables, W. N., and Ripley, B. D. 2002. Modern Applied Statistics with S, 4th edn. Springer, New York. 512 pp.
14. Vermard, Y., Rivot, E., Mahévas, S., Marchal, P., and Gascual, D. 2010. Identifying fishing trip behaviour and estimating fishing effort from VMS data using Bayesian hidden Markov models. Ecological Modelling, 211: 1757-1769.
15. Zuur, A. F., Ieno, E. N., Walker, N., Saveliev, A. A., and Smith, G. M. 2009. Mixed Effects Models and Extensions in Ecology with R. Springer, Dordrecht. 574 pp.