Abundance and effect of health status on apparent survival of Guiana dolphins, Sotalia guianensis, in an open embayment in north‐eastern Brazil

Guiana dolphins (Sotalia guianensis) inhabit shallow waters of the tropical western Atlantic, an area that is now mostly occupied by cities and harbours. Demographic studies have been concentrated in sheltered areas of south/south‐eastern Brazil. This study investigated site fidelity and estimated population abundance and apparent survival of Guiana dolphins in Mucuripe Embayment (ME), on the north‐eastern Brazilian coast, through photo‐identification surveys and closed and open population mark–recapture models, from October 2009 to September 2011. Forty‐six Guiana dolphin groups were recorded (in groups of between one and eight dolphins, with a mean ± SD of 3.49 ± 2.33) in 27 out of 40 surveys. Twenty‐five animals were photo‐identified, with eight considered to have a ‘poor health’ status. The standardized site fidelity index (SSFI) was low (0.25). Using the program capture, the time and heterogeneity model (Mth) resulted in a total abundance estimate of 39, with a Coefficient of Variation (CV) of 21% (95% CI 35–80%). In program mark, model averaging resulted in a total abundance estimate of 33 (CV 32%, 95% CI 30–100%). Using a CV of 21%, the power to detect a decline of 50% during the study period was 0.44 and the power to detect a decline of 5% a year was 0.11. To detect these declines with a 0.90 power, 12 years of monitoring would be necessary. The annual adult apparent survival rate was low (0.71; CV 19%; 95% CI 0.40–0.90), and differed for dolphins in ‘good’ (0.64; CV 28%, 95% CI 0.27–0.89) and ‘poor’ (0.85; CV 22%; 95% CI: 0.23–0.99) health. The low abundance of Guiana dolphins in ME indicates that conservation actions should start immediately, such as creating a marine protected area, continuing awareness campaigns, using by‐catch reduction technologies, developing new regulations, and promoting law enforcement. Monitoring studies must continue with increased effort to reduce uncertainty in estimates and to improve the power to detect trends of decline.