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Spatially varying coefficients improve discrete choice models for tuna purse seine fisheries in the Western–Central Pacific



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  • Journal Title:
    ICES Journal of Marine Science
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    The discrete choice model (DCM) is commonly used to analyze fishing behavior and model fishing location choices based on choice attributes such as expected revenue, cost, and previous effort. However, traditional or mixed DCMs treat parameters among each fishing location as independent and fail to account for spatial autocorrelation among fishing grounds. To address this limitation, we extend traditional DCM by incorporating spatial autocorrelation and spatially varying coefficients (SVCs) to account for latent processes linked to environmental conditions, referred to as spatial DCM. We first develop a diffusion-taxis movement simulation model to simulate fishing vessel behavior, where spatial preferences are influenced by tuna density and oceanographic indices such as the El Niño-Southern Oscillation (ENSO). ENSO is incorporated in the simulation as a time-varying climate index that is multiplied by an SVC, modeling how fishermen adapt fishing strategies in response to regional oceanographic conditions. The simulation testing shows the spatial DCM effectively estimates the spatial preference generated by the movement simulation model through the incorporation of SVCs. Finally, we suggest that spatial DCM can be a useful tool to analyze and forecast fishing behavior for tuna purse seine fisheries in the Western and Central Pacific Ocean (WCPO). The application results showed that the spatial DCM can identify baseline fishing preferences, seasonal spatial variations, and spatially varying responses to environmental conditions beyond the utility predicted from covariates such as expected catch (previous year catch value) and cost (previous year effort and distance to port). Specifically, by incorporating SVCs, the spatial DCM reveals that El Niño events enhance fishing activity in the western WCPO (Papua New Guinea and Federated States of Micronesia), while La Niña events increase fishing activity in the eastern WCPO (Kiribati), presumably representing how fishers adapt to changes in tuna distribution and catch efficiency driven by shifts in oceanographic conditions associated with climate events. We therefore conclude that the spatial DCM is a useful approach to account for spatial autocorrelation and latent oceanographic influences.
  • Source:
    ICES Journal of Marine Science, 82(7)
  • DOI:
  • ISSN:
    1054-3139 ; 1095-9289
  • Format:
    pdf
  • Publisher:
    Oxford University Press (OUP)
  • Document Type:
    Journal Article
  • License:
  • Rights Information:
    CC BY
  • Compliance:
    Submitted
  • Main Document Checksum:
    urn:sha-512:cdda9ccb93a950c839da28bee653556955fd98aa12af148009657cee283400326418e4f30931aee2aeab94dea1f50f4751e70e490e95d4ce578c28f84119edff
  • Download URL:
  • File Type:
    Filetype[PDF - 465.89 KB ]
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