Abstract

Abundance estimates corrected for changes in detection are needed to assess population trends. We used transect-count surveys andN-mixture models to estimate green turtleChelonia mydasand hawksbill turtleEretmochelys imbricatadetection and total abundance at foraging grounds in Bonaire during 2003-2018, and we used these total abundance estimates to fit a Bayesian state-space logistic model and make abundance predictions for 2019-2030. During 2019-2022, we also recorded distance categories to estimate detection and total abundance using distance sampling andN-mixture models. In the present study, we focus on distance sampling to estimate observer detectability and total abundance, and to determine if total abundance increased, declined, or did not change during 2019-2022 and when compared with 2003-2018 estimates and 2019-2030 predictions. Detectability averaged 0.53 (SE = 0.02) for green turtles and 0.51 (SE = 0.06) for hawksbill turtles. Density (ind. km-2) and population size (individuals in the 4 km2survey region) averaged 72.1 (SE = 17.3) and 288 (SE = 69) for green turtles and 21.8 (SE = 4.6) and 87 (SE = 18) for hawksbill turtles. Green turtle total abundance did not change during 2019-2022 (p > 0.05) but remained low when compared with 2003-2018 estimates and 2019-2030 predictions. Hawksbill turtle total abundance declined between 2020 and 2021(z= 2.15, p = 0.03) and increased between 2021 and 2022(z= -3.04, p = 0.002), but 2019-2022 estimates were similar to 2003-2018 estimates and 2019-2030 predictions. Our methodology can be used to monitor sea turtle populations at coastal foraging grounds in the Caribbean.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call