Situação da pesca artesanal em Pecém-CE (2019-2022): implicações climáticas sobre a captura e atividade pesqueira

Abstract

The phenomenon of climate change has intensified global interest in the impacts of global warming on various sectors, including artisanal fishing, especially in vulnerable regions such as the district of Pecém, in the municipality of São Gonçalo do Amarante, Ceará. Climate changes, particularly rising global temperatures and shifts in precipitation patterns, directly affect fishing productivity. Analyzing these variables within the specific context of artisanal fishing in coastal areas is essential. This study aims to explore the relationship between meteorological variables and fishing activity in Pecém, using data series on precipitation, sea surface temperature, and wind speed from 2019 to 2022. These data were obtained from reliable sources such as the Ceará Foundation for Meteorology and Water Resources (FUNCEME), the National Institute of Meteorology (INMET), and the ERA-Interim reanalysis. Additionally, specific fishing activity data were provided by the Fisheries Landing Monitoring Project (PMDP) and the Fisheries Spatialization Project (PEP), both coordinated by Petrobras. The statistical analysis included descriptive statistics, calculations of catch per unit effort (CPUE), simple and cross correlations, Taylor diagrams, bias calculations, root mean square error (RMSE), and the Wilcoxon test. One of the main findings of this study was the observation of an inverse relationship between CPUE and fishing activity, with higher monthly CPUE averages recorded between November and March and lower averages between April and October. This pattern suggests that meteorological conditions directly influence fishing efficiency at different times of the year. The strong correlation between precipitation data obtained from the ERA-Interim reanalysis and the data observed by FUNCEME validated the use of these reanalysis data in the study. The bias and RMSE calculations, along with the Taylor diagram, corroborated the adequacy of the reanalysis data. At the same time, the Wilcoxon test indicated a p-value above 5%, not rejecting the null hypothesis and confirming the validity of the data used. The influence of meteorological variables on total production and CPUE was observed. Sea surface temperature showed the highest negative correlation, particularly with a four-month lag in relation to total production. This finding is particularly relevant for species such as the camurim, which showed greater sensitivity to changes in sea surface temperature, evidencing a detrimental relationship between fishing activity and CPUE, with a four-month lag. In summary, this study highlights the importance of meteorological variables in artisanal fishing in Pecém, pointing to the need for adaptive policies that consider these variables in fisheries management. The use of robust meteorological data, such as those from ERA-Interim, combined with rigorous statistical methods, can provide valuable insights for the sustainability and efficiency of fishing in regions vulnerable to the impacts of climate change.