Reconstructing population dynamics of a threatened marine mammal using multiple data sets

• Published in: Scientific reports Vol. 11; no. 1; p. 2702
• Main Authors: Hostetler, Jeffrey A, Martin, Julien, Kosempa, Michael, Edwards, Holly H, Rood, Kari A, Barton, Sheri L, Runge, Michael C
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 29.01.2021; Nature Publishing Group UK; Nature Portfolio
• Subjects: Abundance; Age composition; Animals; Aquatic mammals; Conservation status; Endangered Species; Environmental effects; Estimates; Female; Male; Marine mammals; Models, Biological; Population; Population Dynamics; Population growth; Trichechus; Trichechus manatus - physiology; Trichechus manatus latirostris
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-81478-z

Models of marine mammal population dynamics have been used extensively to predict abundance. A less common application of these models is to reconstruct historical population dynamics, filling in gaps in observation data by integrating information from multiple sources. We developed an integrated population model for the Florida manatee (Trichechus manatus latirostris) to reconstruct its population dynamics in the southwest region of the state over the past 20 years. Our model improved precision of key parameter estimates and permitted inference on poorly known parameters. Population growth was slow (averaging 1.02; 95% credible interval 1.01-1.03) but not steady, and an unusual mortality event in 2013 led to an estimated net loss of 332 (217-466) manatees. Our analyses showed that precise estimates of abundance could be derived from estimates of vital rates and a few input estimates of abundance, which may mean costly surveys to estimate abundance don't need to be conducted as frequently. Our study also shows that retrospective analyses can be useful to: (1) model the transient dynamics of age distribution; (2) assess and communicate the conservation status of wild populations; and (3) improve our understanding of environmental effects on population dynamics and thus enhance our ability to forecast.