MEPS 381:287-296 (2009)  -  doi:10.3354/meps07942

Identifying fish nurseries using density and persistence measures

Francesco Colloca1,*, Valerio Bartolino1, Giovanna Jona Lasinio2, Luigi Maiorano1, Paolo Sartor3, Giandomenico Ardizzone1

1Department of Animal and Human Biology, Sapienza University of Rome, V.le dell’Università, 32, 00185 Rome, Italy
2Department of Statistics, Probability and Applied Statistics, Sapienza University of Rome, P.le Aldo Moro 5, 00185 Rome, Italy
3Interuniversitary Centre of Marine Biology, V.le Nazario Sauro 4, 57128 Livorno, Italy

ABSTRACT: We propose a 3-step methodological approach to identify and classify fish nurseries for fisheries management purposes. We applied our approach to juvenile European hake Merluccius merluccius in the central Mediterranean Sea. Time series of trawl-survey fish-density data were used to map juvenile hake distribution with Bayesian kriging, while geostatistical aggregation curves were used to find density hot-spots. Persistence measures were adopted to identify nurseries on the basis of their spatio-temporal persistence. We found that areas with a high density of juvenile hake showed a high temporal persistence on both a seasonal and annual basis, with the most persistent nursery areas covering about 5% of the study areas while including about 39% of hake recruitment (averaged over 10 yr). We believe the persistence of these areas is indirect evidence of their importance to the productivity of the population, with many potentially important implications for fisheries management. The approach that we developed to identify hake nurseries can be applied to different species and life stages to improve knowledge of the role of habitat for populations and communities.

KEY WORDS: Nurseries · Merluccius merluccius · Mediterranean Sea · Bayesian kriging · Geostatistical aggregation curves · Persistence measure

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Cite this article as: Colloca F, Bartolino V, Lasinio GJ, Maiorano L, Sartor P, Ardizzone G (2009) Identifying fish nurseries using density and persistence measures. Mar Ecol Prog Ser 381:287-296

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