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Spatio-temporal modelling of zero-inflated deep-sea shrimp data by Tweedie generalized additive

Author

Listed:
  • Simona Arcuti

    (University of Bari "Aldo Moro" - Italy)

  • Crescenza Calculli

    (University of Bari "Aldo Moro" - Italy)

  • Alessio Pollice

    (University of Bari "Aldo Moro" - Italy)

  • Gianfranco D’Onghia

    (University of Bari "Aldo Moro" - Italy)

Abstract

In theMediterrean Sea the population features of demersal resources fluctuate over spatial and temporal scales due to the variability of abiotic and biotic factors as well as to human activities. The two shrimps Parapenaeus longirostris and Aristaeomorpha foliacea are among the most important deep-sea demersal resources in the North-Western Ionian Sea. Their changes in terms of density, biomass andmedian length induced by anthropogenic and environmental variables (fishing effort, sea surface temperature, precipitations, Winter North Atlantic Oscillation (NAO) and Annual MediterraneanOscillation (MO) indices) were investigated. Biological data were collected during trawl surveys carried out from 1995 to 2006 as part of the international program MEDITS (International Bottom Trawl Survey in the Mediterranean). Generalized AdditiveModels were used to evaluate the spatio-temporal variation of both species, together with the possible nonlinear effects of biotic and abiotic factors. Density and biomass were assumed to be distributed according to a member of the Tweedie family in order to account for zero-inflation in the relative data. Spacetime interaction was consideredwithin a non-separablemodel with smooth spatio-temporal component based on tensor product splines. The results show significant spatio-temporal and depth effects in the three population parameters of these resources. Winter NAO index significantly influenced the density, biomass and length of P. longirostris. Sea surface temperature significantly influenced the size of this species and the three population features of A. foliacea. The size of this shrimp resulted also influenced negatively by fishing effort and positively by the MO index.

Suggested Citation

  • Simona Arcuti & Crescenza Calculli & Alessio Pollice & Gianfranco D’Onghia, 2013. "Spatio-temporal modelling of zero-inflated deep-sea shrimp data by Tweedie generalized additive," Statistica, Department of Statistics, University of Bologna, vol. 73(1), pages 87-101.
    • Handle: RePEc:bot:rivsta:v:73:y:2013:i:1:p:87-101
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    Cited by:

    1. Khalin, Andrey A. & Postnikov, Eugene B., 2020. "A wavelet-based approach to revealing the Tweedie distribution type in sparse data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    2. Maé Guinet & Guillaume Adeux & Stéphane Cordeau & Emeric Courson & Romain Nandillon & Yaoyun Zhang & Nicolas Munier-Jolain, 2023. "Fostering temporal crop diversification to reduce pesticide use," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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