Argentine Shortfin Squid (Illex argentinus) Stock Assessment in the Southwest Atlantic Using Geostatistical Techniques

  • Author(s): Ke-Yang Chang, Chih-Shin Chen, Tsan-Yu Chiu, Wen-Bin Huang, and Tai-Sheng Chiu
  • DOI: 10.3319/TAO.2015.11.05.01(Oc)
  • Keywords: Illex argentines, Abundance, Geostatistics, Squid fishery
  • Citation: Chang, K. Y., C. S. Chen, T. Y. Chiu, W. B. Huang, and T. S. Chiu, 2016: Argentine shortfin squid (Illex argentinus) stock assessment in the Southwest Atlantic using geostatistical techniques. Terr. Atmos. Ocean. Sci., 27, 281-292, doi: 10.3319/TAO.2015.11.05.01(Oc)
Abstract

The spatial and temporal variation in Argentine shortfin squid Illex argentinus abundance distribution was examined over its fishing phase on the Patagonia Shelf and shelf break, Southwest Atlantic (SWA), using Taiwanese jigger’s fishery data. Geostatistical techniques were applied to characterize the spatial and temporal variability in the squid abundance and its relation to seawater temperature. The experimental semivariograms indicated that the abundance of Argentine shortfin squid was spatially structured in the SWA, with various abundance levels. The spherical models for all years, except 2010, explained most spatial information from the annual squid abundance distribution patterns. The linear regression analysis confirmed a negative relationship between the annual squid abundance and seawater temperature in the studied years. High squid abundance was estimated using Kriging interpolations along the 200-m isobath from 40°S to as far south as 50°S. The elliptical isopleth lines extended a longer distance from the 200-m isobath to the shelf side in high abundance years, such as 1999 and 2007. Scattered patches of low values were observed in the very low-abundance year of 2004. The integrated total squid biomass using Kriging interpolation upheld a healthy stock status in the SWA fishing ground. Our research showed that the geostatistical procedure is effective in describing the annual spatial pattern, and the parameters resulting from stationary modeling are valuable and useful in estimating the annual total biomass in the realized fishing ground.

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