Banca de DEFESA: SAMUEL GAUDIOSO ALBUQUERQUE CARVALHO MELO

INFLUENCE OF CLIMATE VARIABLES ON ARTISANAL FISHING IN PECEM-CEARÁ

CPUE; Artisanal Fishery Productivity; Cross Correlation

The phenomenon of climate change has intensified global interest in the impacts of global warming across various sectors, including artisanal fishing, particularly in vulnerable regions such as the Pecém district in the municipality of São Gonçalo do Amarante, Ceará. Climate alterations, particularly the rise in global temperatures and changes in precipitation patterns, directly affect fishery 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, utilizing a series of precipitation, sea surface temperature, and wind speed data from 2019 to 2022. These data were obtained from reliable sources such as the Fundação Cearense de Meteorologia e Recursos Hídricos (Funceme), the National Institute of Meteorology (INMET), and the ERA-Interim reanalysis. Additionally, specific data on fishing activity were provided by the Fish Landing Monitoring Project (PMDP) and the Fishery Spatialization Project (PEP), both coordinated by Petrobras. The statistical analysis included descriptive statistics methods, catch per unit effort (CPUE) calculations, 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 those 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 greater than 5%, failing to reject 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 exhibited the highest negative correlation, especially with a four-month lag in total production. This finding is particularly relevant for species such as camurim, which showed greater sensitivity to changes in sea surface temperature, evidencing a damaging 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 fishery management. The use of robust meteorological data, such as those from the ERA-Interim, combined with rigorous statistical methods, can provide valuable insights into the sustainability and efficiency of fishing in regions vulnerable to the impacts of climate change.