Zooming the macroscope: medium-resolution remote sensing as a framework for the assessment of a small-scale fishery

Abstract

Abstract Amoroso, R. O., Parma, A. M., Orensanz, J. M., and Gagliardini, D. A. 2011. Zooming the macroscope: medium-resolution remote sensing as a framework for the assessment of a small-scale fishery. – ICES Journal of Marine Science, 68: 696–706. Management of small-scale fisheries targeting sedentary stocks requires integration of information about processes operating and observable at different spatial and temporal scales. An integrated approach was developed with a scallop (Aequipecten tehuelchus) fishery in a small, semi-enclosed Patagonian basin as a demonstration case. Medium-resolution (30 m2) satellite (Landsat) data, used to identify circulation patterns, were combined with information from fishery surveys and recruitment experiments to link oceanographic processes with population dynamics. A frontal system splits San José Gulf (northern Argentine Patagonia) into two oceanographic domains (East and West) with distinct hydrographic regimes. In the West Domain, where circulation is highly advective and governed by turbulent vorticial fluxes, larval settlement on artificial collectors was insignificant over five reproductive seasons and no important scallop grounds were ever found. In the East Domain, where the main fishing grounds are, spat abundance varied between sites and years, but was always significant. Growth rates displayed strong clinal variation within the East Domain, decreasing clockwise away from the entrance to the Gulf and reflecting inferred circulation and gradual nutrient extinction. A physical mechanism capable of dispersing larvae over long distances towards the north, into the adjacent San Matias Gulf, was identified from Landsat images. The large-scale patterns of variation in growth, distribution, and recruitment of the Tehuelche scallop stock could not have been interpreted without an integrative approach to data assemblage and analysis, including satellite remote sensing.