Applying seasonal time series modeling to forecast marine fishery landings for six species in the Colombian Pacific Ocean

Abstract

Marine fisheries are keystone components of the industrial and social development of countries. Management of marine resources requires forecasting skills to support best decisions for the sustainability of fishery resources and food security under different environmental, social and political scenarios. In this study, we aimed at forecasting the landings of six marine fish species in the Colombian Pacific Ocean (CPO) from 2020 to 2024, using monthly time series from 2012 to 2020 provided by SEPEC (Servicio Estadístico Pesquero Colombiano), the Colombian governmental authority in charge of aquaculture and fisheries. These forecasts consisted of building, fitting and evaluating SARIMA models (Seasonal Autoregressive Integrated Moving Average), since all of the time series were non-stationary. We focused on evaluating the average percent change of landings between the historical and the forecast periods exclusively on peak landing months. The main results suggested that the landings of the Yellowfin tuna (Thunnus albacores) will decrease by 14% until 2024, those of the Skipjack tuna (Katsunowus pelamis) by 20% until 2022, and those of the Spotted snapper (Lutjanus peru) by 28% until 2023. The forecast landings of the Cachema weakfish (Cynoscion phoxocephalus) and the Red snapper (Lutjanus peru) showed constant increases until 2024, by 1.5 and 0.85 tons per year on average respectively, and those of the Pink grouper (Hyporthodus acanthistius) showed no trends until 2024. These results are the first approach to a multi-species forecast of marine fishery landings in the Colombian Pacific Ocean using a SARIMA model, and their implications must be carefully interpreted for decision making towards the sustainability of fishery resources.