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Spatial overlap between the leafscale gulper shark and the black scabbardfish off Portugal

Published online by Cambridge University Press:  19 December 2013

Nuno Veiga ,
Teresa Moura  and
Ivone Figueiredo
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Abstract

Information about the spatial distribution of bycatch species and their spatial overlap with the target species is essential for fisheries management. The present study used fishery-dependent data (vessel monitoring systems, logbooks and official daily landings) to study the spatial distribution and overlap between black scabbardfish Aphanopus carbo and leafscale gulper shark Centrophorus squamosus taken by the longline fishery operating off mainland Portugal. The geostatistical method kriging was applied to estimate the distribution of the leafscale gulper shark in relation to black scabbardfish and thus assess the impact of the fishery on the leafscale gulper shark. Results indicate that in fishing grounds where the black scabbardfish is more abundant, the relative occurrence of deepwater sharks is reduced. These findings have implications for alternative management measures to be adopted in this particular fishery, particularly where it concerns the minimization of deepwater shark bycatch.

Keywords

Spatial distributionSpatial overlapBycatchDeep-sea fishCentrophorus squamosusAphanopus carboNortheast Atlantic Ocean
Type
Research Article
Information
Aquatic Living Resources , Volume 26 , Issue 4 , October 2013 , pp. 343 - 353
Copyright
© EDP Sciences, IFREMER, IRD 2013

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References

Augustin, N.H., Trenkel, V.M., Wood, S.N., Lorance, P., 2013, Space-time modelling for blue ling using soap film smoothers. Environmetrics 24, 109–119. CrossRefGoogle Scholar
Bivand R.S., Pebesma E.J., Gómez-Rubio V., 2008, Applied spatial data analysis with R. New York, Springer.
Bonfil R., 1994, Overview of world elasmobranch fisheries. FAO Fisheries Technical Paper, Rome, No. 341.
Bordalo-Machado, P., Fernandes, A. C., Figueiredo, I., Moura, O., Reis, S., Pestana, G., Gordo, L.S., 2009, The black scabbardfish (Aphanopus carbo, Lowe 1839) fisheries from Portuguese mainland and Madeira Island. Scient. Mar. 73, 63–76. CrossRefGoogle Scholar
Bordalo-Machado P., Figueiredo I., 2007, Extraction and classification of longline fishing trips from vessel monitoring systems data with sequential recording gaps. 5th International Symposium, Spatial Data Quality 2007. Int. Soc. Photogram. Rem. Sens. Arch. 36–2C43.
Bordalo-Machado, P., Figueiredo, I., 2009, The fishery for the black scabbardfish (Aphanopus carbo, Lowe 1839) in the Portuguese continental slope. Rev. Fish Biol. Fish. 19, 49–67. CrossRefGoogle Scholar
Bordalo-Machado P., Sousa R.T., Matos J.G., 2007, A software toolkit to analyse vessel monitoring system data from longline fisheries. In: Nishida T., Kailola P.J., Caton A. (Eds.), GIS/Spatial analysis in fishery and aquatic sciences. Japan, Fishery-Aquatic GIS Research Group Saitama, Vol. 3, pp. 259–274.
Breiman, L., 2001, Random forests, Machine Learnings 45, 5–32. CrossRefGoogle Scholar
Bridger J.P., 1978, New deep-water trawling grounds to the west of Britain. Lowestoft, MAFF Directorate of Fisheries Research, Laboratory Leaflet No. 41.
Brodeur, R.D., Suchman, C.L., Reese, D.C, Miller, T.W., Daly, E.A., 2008, Spatial overlap and trophic interactions between fish and large jellyfish in the Northern California Current. Mar. Biol. 154, 649–59. CrossRefGoogle Scholar
Broennimann, O., Treier, U.A., Müller-Schärer, H., Thuiller, W., Peterson, A.T., Guisan, A., 2007, Evidence of climatic niche shift during biological invasion. Ecol. Lett. 10, 701–709. CrossRefGoogle ScholarPubMed
Broennimann, O., Fitzpatrick, M.C., Pearman, P.B., Petitpierre, B., Pellissier, L., Yoccoz, N.G., Thuiller, W., Fortin, M.-J., Randin, C., Zimmermann, N.E., Graham, C.H., Guisan, A., 2012, Measuring ecological niche overlap from occurrence and spatial environmental data. Glob. Ecol. Biogeogr. 21, 481–487. CrossRefGoogle Scholar
Castro J.I., Woodley C.M., Brudek R.L., 1999, A preliminary evaluation of the status of shark species. FAO Fisheries Technical Papers, Rome, No. 380.
Chase J.M., Leibold M.A., 2003, Ecological niche: linking classical and contemporary approaches. The University of Chicago Press.
Clarke, M.W., Connolly, P.L., Bracken, J.J., 2001, Aspects of reproduction of the deep-water sharks Centroscymnus coelolepis and Centrophorus squamosus from west of Ireland and Scotland. J. Mar. Biol. Assoc. UK 81, 1019–1029. CrossRefGoogle Scholar
Compagno L., Dando M., Fowler S., 2005, Sharks of the World. London, Harper Collins Publishers, Collins Field Guide.
Cressie N., 1993, Statistics for Spatial Data. Revised edition, New-York, Wiley. Wiley Series in Probability and Mathematical Statistics.
Ehrich, S., 1983, On the ocurrence of some fish species at the slopes of the Rockall Trough. Arch. Fish. 33, 105–212. Google Scholar
Eastwood, P.D., Meaden, G.J., Carpentier, A., Rogers, S.I., 2003, Estimating limits to the spatial extent and suitability of sole (Solea solea) nursery grounds in the Dover Strait. J. Sea Res. 50, 151–165. CrossRefGoogle Scholar
Etterson, J.R., Shaw, R.G., 2001, Constraint to adaptive evolution in response to global warming. Science 294, 151–154. CrossRefGoogle ScholarPubMed
Figueiredo, I., Machado, P.B., Gordo, L.S., 2005, Deep-water shark fisheries off the Portuguese continental coast. J. Northwest Atl. Fish. Sci. 35, 291–298. CrossRefGoogle Scholar
Fitzpatrick, M.C., Weltzin, J.F., Sanders, N.J., Dunn, R.R., 2007, The biogeography of prediction error: why does the introduced range of the fire ant over-predict its native range? Global Ecol. Biogeogr. 16, 24–33. Google Scholar
Friedman, J.H., 2001, Greedy function approximation: a gradient boosting machine. Ann. Stat. 29, 1189–1232. CrossRefGoogle Scholar
Garcia, V.B., Lucifora, L.O., Myers, R.A., 2008, The importance of habitat and life history to extinction risk in sharks, skates, rays and chimaeras. Proc. R. Soc. B 275, 83–89. CrossRefGoogle ScholarPubMed
Gerritsen, H., 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 J. Mar. Sci. 68, 245–252. CrossRefGoogle Scholar
Guisan, A., Thuiller, W., 2005, Predicting species distribution: offering more than simple habitat models. Ecol. Lett. 8, 993–1009. CrossRefGoogle Scholar
ICES, 2011, Report of the Working Group for North-east Atlantic Continental Slope Survey (WGNEACS), 14–16 June 2011, ICES HQ, Copenhagen, ICES CM 2011/SSGESST:15.
ICES, 2012, Report of the Working Group on the Biology and Assessment of Deep-sea Fisheries Resources (WGDEEP), 28 March–5 April, Copenhagen, ICES CM 2012/ACOM:17.
Jump, A.S., Peñuelas, J., 2005, Running to stand still: adaptation and the response of plants to rapid climate change. Ecol. Lett. 8, 1010–1020. CrossRefGoogle Scholar
Kelly, C.J., Clarke, M., Connolly, P.L., 1997, Catch and discards from a deep-water trawl survey in 1996. Fish. Leaf. 175, 1–16. Ir. Marine Institute, Dublin. Google Scholar
Large, P.A., Diez, G., Drewery, J., Laurans, M., Pilling, G.M., Reid, D.G., Reinert, J., South, A.B., Vinnichenko, V.I., 2010, Spatial and temporal distribution of spawning aggregations of blue ling (Molva dypterygia) west and northwest of the British Isles. ICES J. Mar. Sci. 67, 494–501. CrossRefGoogle Scholar
Lewison, R.L., Soykan, C.U., Franklin, J., 2009, Mapping the bycatch seascape: multispecies and multi-scale spatial patterns of fisheries bycatch. Ecol. Appl. 19, 920–930. CrossRefGoogle ScholarPubMed
Machete, M., Morato, T., Menezes, G., 2011, Experimental fisheries for black scabbardfish (Aphanopus carbo) in the Azores, Northeast Atlantic. ICES J. Mar. Sci. 68, 302–308. CrossRefGoogle Scholar
Maxwell, D.L., Stelzenmuller, V., Eastwood, P.D., Rogers, S.I., 2009, Modelling the spatial distribution of plaice (Pleuronectes platessa), sole (Solea solea) and thornback ray (Raja clavata) in UK waters for marine management and planning. J. Sea Res. 61, 258–267. CrossRefGoogle Scholar
McCullagh P., Nedler J., 1989, Generalized linear models, 2nd edition. Boca Raton, FL, Chapman and Hall/CRC.
Medley, K.A., 2010, Niche shifts during the global invasion of the Asian tiger mosquito, Aedes albopictus Skuse (Culicidae), revealed by reciprocal distribution models. Global Ecol. Biogeogr. 19, 122–133. CrossRefGoogle Scholar
Pajuelo, J.G., Gonzalez, J.A., Santana, J.I., 2010, Bycatch and incidental catch of the black scabbardfish (Aphanopus spp.) fishery off the Canary Islands. Fish. Res. 106, 448–453. CrossRefGoogle Scholar
Pebesma, E.J., 2004, Multivariable geostatistics in S: the gstat package. Comput. Geosci. 30, 683–691. CrossRefGoogle Scholar
Philips, S.J., Anderson, R.P., Schapire, R.E., 2006, Maximum entropy modeling of species geographic distributions. Ecol. Model. 190, 231–259. CrossRefGoogle Scholar
Pittman, S.J., Christensen, J.D., Caldow, C., Menza, C., Monaco, M.E., 2007, Predictive mapping of fish species richness across shallow-water seascapes in the Caribbean. Ecol. Model. 204, 9–21. CrossRefGoogle Scholar
Pratt H.L, Casey J.G., 1990, Shark reproductive strategies as a limiting factor in directed fisheries, with a review of Holden’s method of estimating growth parameters. In: Pratt Jr H.L., Gruber S.H., Taniuchi T. (Eds.). Elasmobranchs as living resources: advances in the biology, ecology, systematics and the status of the fisheries. NOAA Technical Report NMFS, No. 90, pp 97–109.
R Development Core Team, 2012, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org/.
Simpfendorfer, C.A., Kyne, P.M., 2009, Limited potential to recover from overfishing raises concerns for deep-sea sharks, rays and chimaeras. Environ. Conserv. 36, 97–103. CrossRefGoogle Scholar
Sims, M., Cox, T., Lewison, R., 2008, Modelling spatial patterns in fisheries bycatch: improving bycatch maps to aid fisheries management. Ecol. Appl. 18, 649–661. CrossRefGoogle Scholar
STECF, 2002, Report of the subgroup on resource status (SGRST) of the scientific, technical and economic committee for fisheries (STECF). Brussels elasmobranchs fisheries.
Steiner, F.M., Schlick-Steiner, B.C., VanDerWal, J., Reuther, K.D., Christian, E., Stauffer, C., Suarez, A.V., Williams, S.E., Crozier, R.H., 2008, Combined modeling of distribution and niche in invasion biology: a case study of two invasive Tetramorium and species. Divers. Distrib. 14, 347–357. CrossRefGoogle Scholar
Stelzenmüller, V., Maynou, F., Ehrich, S., Zauke, G.P., 2004, Spatial analysis of twaite shad, Alosa fallax (Lacepède 1803), in the Southern North Sea: application of non-linear geostatistics as a tool to search for special areas of conservation. Int. Rev. Hydrobiol. 89, 337–351. CrossRefGoogle Scholar