Abstract
Introduction Methods combining data from spatially limited, independently conducted surveys indicate a preliminary recovery for coastal shark species along the Atlantic. However, anthropogenic climate change is expected to shift distributions and alter migration timing for these highly migratory species, potentially affecting survey catchability and interpretation of abundance indices. Methods Vector autoregressive spatiotemporal (VAST) models were applied to data from six fishery-independent surveys of six coastal shark stocks to generate area-weighted indices of abundance. Area-weighted indices, trends in density over space and time, and analysis of density anomalies were used to evaluate changes in a stock’s spatial distribution across the U.S. southeast Atlantic. In addition to VAST, generalized linear mixed models were used to generate indices of abundance for each survey, which served as inputs to two previously implemented reconciliation methods in coastal shark stock assessments: dynamic factor analysis (DFA) and Bayesian hierarchical analysis (Conn). Results The index standardization methods, particularly VAST and Conn, largely agreed with one another and appeared robust to spatial patterns. Only two of the six shark stocks showed increasing trends by the end of the time series, with indices for multiple species plateauing or declining. Positive trends in density and increased variability in density anomalies in the VAST models across the northern extent of the surveyed spatial domain suggests a potential northward expansion or a timing discrepancy between migration onset and sampling efforts for multiple species. Discussion Overall, the VAST models provided evidence of spatial changes that could impact each survey’s catchability, thus complicating the interpretation of abundance trends. These findings underscore the importance of accounting for spatiotemporal dynamics in future stock assessments and fisheries management strategies.