Sex-Specific Patterns in Abundance, Temporary Emigration and Survival of Indo-Pacific Bottlenose Dolphins (Tursiops aduncus) in Coastal and Estuarine Waters

Abstract

Inherent difficulties in determining the sex of free-ranging, sexually monomorphic species often prevents a sex-specific focus on estimating abundance, movement patterns and survival rates. This study provides insights into sex-specific population parameters of Indo-Pacific bottlenose dolphins (Tursiops aduncus). Systematic, boat-based photo-identification surveys (n = 417) were conducted year-round from 2007 to 2013 in coastal and estuarine waters off Bunbury, Western Australia. Pollock's Robust Design was used to quantify population parameters for three datasets: (i) adults and juveniles combined, (ii) adult females and, (iii) adult males. For all datasets, abundance estimates varied seasonally, with general highs during summer and/or autumn, and lows during winter. Dolphins had seasonally structured temporary emigration rates with similar trends between sexes. The derived return rate (1-γ ') of temporary emigrants into the study area was highest from winter to spring, indicating that dolphins had a high probability of return into the study area during spring. We suggest that the return of dolphins into the study area and increase in abundance is influenced by the breeding season (summer/autumn). Prey availability is likely a main driver responsible for the movement of dolphins out of the study area during winter. Seasonal apparent survival rates were constant and high (0.98-0.99) for all datasets. High apparent survival rates suggest there is no permanent emigration from the study area. Our sex-specific modeling approach offers a comprehensive interpretation of the population dynamics of a top predator in a coastal and estuarine environment and acts as a model for future sex-based population studies on sexually monomorphic species.

Dolphin Prey Availability and Calorific Value in an Estuarine and Coastal Environment

“…However, the nutritional value of prey may be a more critical component of prey value and therefore an important component of any investigation into foraging ecology. In this study, a concomitant increase in abundance of prey was predicted to coincide with the increase in abundance of bottlenose dolphins during summer months off Bunbury, Western Australia (Smith et al, 2013;Sprogis et al, 2016a). The results of prey sampling indicated a higher abundance of prey in the summer seasons, however, the overall biomass and energy density of prey documented were higher in the winters, when fewer dolphins were present, but a time when dolphin mothers and calves remain in the area.…”

“…The population of bottlenose dolphins in the Bunbury region, approximately 180 km south of Perth, Western Australia, utilizes the Leschenault Estuary (Estuary), Koombana Bay (Bay), and the near shore coastal waters (Ocean) (Figure 1; Smith et al, 2013;Sprogis et al, 2016a).…”

“…Sampling days were spread across the sampling season. The summer season extended from January to mid-March corresponding to the period when dolphins are most abundant in the area, while the winter season extended from June through September when fewer dolphins are present (Smith et al, 2013;Sprogis et al, 2016a).…”

“…The abundance of dolphins fluctuates seasonally, with approximately double the population size in the summer vs. the winter months (Smith et al, 2013;Sprogis et al, 2016a). The seasonal high in abundance coincides with the peak in the breeding and calving season, in late summer/early autumn (Smith et al, 2016).…”

Evaluating monitoring methods for cetaceans

“…Although we have concentrated on the estimation of abundance and precision from different scenarios, survival and immigration/emigration have also been estimated using the data collected from this approach (Tyne et al 2014). Delphinid sighting data have also been collected systematically along transects to estimate abundance and other demographic parameters, such as temporary immigration/emigration (Smith et al 2013;Brown et al 2016;Sprogis et al 2016) using Pollock's Robust Design (Pollock et al 1990). The data from these studies could be used to estimate the power to detect change and evaluate alternative sampling strategies for monitoring in a similar manner to the current study by varying the number of transect cycles.…”