Knowledge of an animal’s home range is a crucial component in making informed management decisions. However, many home range studies are limited by study area size, and therefore may underestimate the size of the home range. In many cases, individuals have been shown to travel outside of the study area and utilize a larger area than estimated by the study design. In this study, data collected by multiple research groups studying bottlenose dolphins on the east coast of Florida were combined to determine how home range estimates increased with increasing study area size. Home range analyses utilized photo-identification data collected from 6 study areas throughout the St Johns River (SJR; Jacksonville, FL, USA) and adjacent waterways, extending a total of 253 km to the southern end of Mosquito Lagoon in the Indian River Lagoon Estuarine System. Univariate kernel density estimates (KDEs) were computed for individuals with 10 or more sightings (n = 20). Kernels were calculated for the primary study area (SJR) first, then additional kernels were calculated by combining the SJR and the next adjacent waterway; this continued in an additive fashion until all study areas were included. The 95% and 50% KDEs calculated for the SJR alone ranged from 21 to 35 km and 4 to 19 km, respectively. The 95% and 50% KDEs calculated for all combined study areas ranged from 116 to 217 km and 9 to 70 km, respectively. This study illustrates the degree to which home range may be underestimated by the use of limited study areas and demonstrates the benefits of conducting collaborative science.

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Common bottlenose dolphins (Tursiops truncatus truncatus) inhabiting the Indian River Lagoon (IRL) estuarine system along the east coast of Florida are impacted by anthropogenic activities and have had multiple unexplained mortality events. Given this, managers need precise estimates of demographic and abundance parameters. Mark-recapture photo-identification boat-based surveys following a Robust Design were used to estimate abundance, adult survival, and temporary emigration for the IRL estuarine system stock of bottlenose dolphins. Models allowed for temporary emigration and included a parameter (time since first capture) to assess evidence for transient individuals. Surveys (n = 135) were conducted along predetermined contour and transect lines throughout the entire IRL (2016–2017). The best fitting model allowed survival to differ for residents and transients and to vary by primary period, detection to vary by secondary session, and did not include temporary emigration. Dolphin abundance was estimated from 981 (95% CI: 882–1,090) in winter to 1,078 (95% CI: 968–1,201) in summer with a mean of 1,032 (95% CI: 969–1,098). Model averaged seasonal survival rate for marked residents was 0.85–1.00. Capture probability was 0.20 to 0.42 during secondary sessions and the transient rate was estimated as 0.06 to 0.07. This study is the first Robust Design mark-recapture survey to estimate abundance for IRL dolphins and provides population estimates to improve future survey design, as well as an example of data simulation to validate and optimize sampling design. Transients likely included individuals with home ranges extending north of the IRL requiring further assessment of stock delineation. Results were similar to prior abundance estimates from line-transect aerial surveys suggesting population stability over the last decade. These results will enable managers to evaluate the impact of fisheries-related takes and provide baseline demographic parameters for the IRL dolphin population which contends with anthropogenic impacts and repeated mortality events.