Simulating population dynamics of sea turtles in a high survival world
Abstract Globally, nest counts for many sea turtles now routinely exceed pre-conservation levels but also exhibit increased inter-annual variability. Mixed trend interpretations support population growth constraints but differ regarding why. Here we used a closed-loop population simulator to report...
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-10482-4 |
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| author | Michael D. Arendt Jeffrey A. Schwenter |
| author_facet | Michael D. Arendt Jeffrey A. Schwenter |
| author_sort | Michael D. Arendt |
| collection | DOAJ |
| description | Abstract Globally, nest counts for many sea turtles now routinely exceed pre-conservation levels but also exhibit increased inter-annual variability. Mixed trend interpretations support population growth constraints but differ regarding why. Here we used a closed-loop population simulator to report generalized patterns of demographic change under assumptions of random variability that tended both above and below the null model scenario of no change over decades. Random changes in nine life history parameters spanning sea turtle hatching to eventual sexual maturity from 1950 through 2018 provided context for comparison with three decades of published nesting data for a globally important loggerhead sea turtle (Caretta caretta) population through 2018. Six demographic metrics (nests, mature abundance, immature abundance, mature sex ratio, immature sex ratio, and neritic survival equivalent [NSE]) computed from simulations better predicted each other than their respective prediction by any of the annual simulator inputs. Irrespective of maturity status, abundance fluctuated widely and inversely to age group sex ratio. The ratio of older (ages 20–29) to younger (ages 10–19) individuals provided the best lagged (21 years) prediction of annual nest counts. Our novel findings substantiate demographic metrics for monitoring, plus forecast a future annual nest count oscillation even with high survival (0.93). |
| format | Article |
| id | doaj-art-b16591dd9d1341b0b0bd0f366a0de3d9 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-b16591dd9d1341b0b0bd0f366a0de3d92025-08-20T03:05:26ZengNature PortfolioScientific Reports2045-23222025-07-0115111110.1038/s41598-025-10482-4Simulating population dynamics of sea turtles in a high survival worldMichael D. Arendt0Jeffrey A. Schwenter1Marine Resources Division, South Carolina Department of Natural ResourcesMarine Resources Division, South Carolina Department of Natural ResourcesAbstract Globally, nest counts for many sea turtles now routinely exceed pre-conservation levels but also exhibit increased inter-annual variability. Mixed trend interpretations support population growth constraints but differ regarding why. Here we used a closed-loop population simulator to report generalized patterns of demographic change under assumptions of random variability that tended both above and below the null model scenario of no change over decades. Random changes in nine life history parameters spanning sea turtle hatching to eventual sexual maturity from 1950 through 2018 provided context for comparison with three decades of published nesting data for a globally important loggerhead sea turtle (Caretta caretta) population through 2018. Six demographic metrics (nests, mature abundance, immature abundance, mature sex ratio, immature sex ratio, and neritic survival equivalent [NSE]) computed from simulations better predicted each other than their respective prediction by any of the annual simulator inputs. Irrespective of maturity status, abundance fluctuated widely and inversely to age group sex ratio. The ratio of older (ages 20–29) to younger (ages 10–19) individuals provided the best lagged (21 years) prediction of annual nest counts. Our novel findings substantiate demographic metrics for monitoring, plus forecast a future annual nest count oscillation even with high survival (0.93).https://doi.org/10.1038/s41598-025-10482-4 |
| spellingShingle | Michael D. Arendt Jeffrey A. Schwenter Simulating population dynamics of sea turtles in a high survival world Scientific Reports |
| title | Simulating population dynamics of sea turtles in a high survival world |
| title_full | Simulating population dynamics of sea turtles in a high survival world |
| title_fullStr | Simulating population dynamics of sea turtles in a high survival world |
| title_full_unstemmed | Simulating population dynamics of sea turtles in a high survival world |
| title_short | Simulating population dynamics of sea turtles in a high survival world |
| title_sort | simulating population dynamics of sea turtles in a high survival world |
| url | https://doi.org/10.1038/s41598-025-10482-4 |
| work_keys_str_mv | AT michaeldarendt simulatingpopulationdynamicsofseaturtlesinahighsurvivalworld AT jeffreyaschwenter simulatingpopulationdynamicsofseaturtlesinahighsurvivalworld |