Time series modeling of coastal fishery landings on the Southwestern Atlantic shelf: Influence of environmental drivers

Abstract

Time-series modeling of fisheries provides insights into stock tendencies and enablesshort-term forecasting of landings, aiding decision makers in establishing management priorities. The Rio de la Plata Estuary and its maritime front sustain valuablefisheries for Argentina and Uruguay, with striped weakfish (Cynoscion guatucupa),whitemouth croaker (Micropogonias furnieri), and Argentine hake (Merluccius hubbsi)historically representing highest catches. However, their landings have declined inrecent decades. To support resource management, we investigated the effectivenessof Autoregressive Integrated Moving Average (ARIMA) models in capturing fisherylanding dynamics and providing reliable short-term predictions. The best modelsexhibited a good fit and accurately captured the overall trends of landings. Residualvariability unaccounted for by the model was analyzed in relation to time-laggedenvironmental conditions. A wavelet coherence analysis was employed to examinethe effect of the most significant variables on landings. Results revealed that environmental conditions affect differentially landings of each species as a result of their particular ecological traits. Turbidity and salinity affected mainly M. furnieri, whichinhabits the innermost part of the estuary. Additionally, C. guatucupa, inhabiting theouter estuary and coastal region, exhibited a stronger association with river runoffcompared to M. hubbsi, which inhabits the continental shelf. This study provides thefirst evidence of ARIMA models' reliability in representing the temporal evolution ofcatch in these fisheries, offering valuable tools for short-term landings forecastingand facilitating sustainable management. Wavelet analysis findings will also contribute to enhancing our comprehension of trends in the correlation between environmental conditions and commercial landings.