Abundance and survival rates of the Hawai’i Island associated spinner dolphin (Stenella longirostris) stock

Reliable population estimates are critical to implement effective management strategies. The Hawai’i Island spinner dolphin (Stenella longirostris) is a genetically distinct stock that displays a rigid daily behavioural pattern, foraging offshore at night and resting in sheltered bays during the day. Consequently, they are exposed to frequent human interactions and disturbance. We estimated population parameters of this spinner dolphin stock using a systematic sampling design and capture–recapture models. From September 2010 to August 2011, boat-based photo-identification surveys were undertaken monthly over 132 days (>1,150 hours of effort; >100,000 dorsal fin images) in the four main resting bays along the Kona Coast, Hawai’i Island. All images were graded according to photographic quality and distinctiveness. Over 32,000 images were included in the analyses, from which 607 distinctive individuals were catalogued and 214 were highly distinctive. Two independent estimates of the proportion of highly distinctive individuals in the population were not significantly different (p = 0.68). Individual heterogeneity and time variation in capture probabilities were strongly indicated for these data; therefore capture–recapture models allowing for these variations were used. The estimated annual apparent survival rate (product of true survival and permanent emigration) was 0.97 SE±0.05. Open and closed capture–recapture models for the highly distinctive individuals photographed at least once each month produced similar abundance estimates. An estimate of 221±4.3 SE highly distinctive spinner dolphins, resulted in a total abundance of 631±60.1 SE, (95% CI 524–761) spinner dolphins in the Hawai’i Island stock, which is lower than previous estimates. When this abundance estimate is considered alongside the rigid daily behavioural pattern, genetic distinctiveness, and the ease of human access to spinner dolphins in their preferred resting habitats, this Hawai’i Island stock is likely more vulnerable to negative impacts from human disturbance than previously believed

Embracing conservation success of recovering humpback whale populations: Evaluating the case for downlisting their conservation status in Australia

Optimism and hope in conservation biology are supported by examples of endangered species recovery, such as the population growth observed in humpback whales in several of the world's oceans. In Australia, monitoring data suggest rapid recovery for both east and west coast populations, which are now larger than 50% of their pre-whaling abundance. The measured growth rates exceed known species trends worldwide and have no indication of diminishing. Under Australian Commonwealth legislation and regulations, these populations should be considered for downlisting, as they are not eligible for listing as a threatened species against all statutory criteria. A change in conservation status will produce new challenges for the conservation and management of a recovered species, especially with the Australian economic landscape experiencing large-scale growth and development in recent years. More importantly, a recovered humpback whale population may bring a positive shift in the research goals and objectives throughout Australia by ensuring other endangered species an equal chance of recovery while delivering hope, optimism, and an opportunity to celebrate a conservation success

Passive acoustic monitoring of coastally associated Hawaiian spinner dolphins, Stenella longirostris, ground-truthed through visual surveys

Effective decision making to protect coastally associated dolphins relies on monitoring the presence of animals in areas that are critical to their survival. Hawaiian spinner dolphins forage at night and rest during the day in shallow bays. Due to their predictable presence, they are targeted by dolphin-tourism. In this study, comparisons of presence were made between passive acoustic monitoring (PAM) and vessel-based visual surveys in Hawaiian spinner dolphin resting bays. DSG-Ocean passive acoustic recording devices were deployed in four bays along the Kona Coast of Hawai'i Island between January 8, 2011 and August 30, 2012. The devices sampled at 80 kHz, making 30-s recordings every four minutes. Overall, dolphins were acoustically detected on 37.1% to 89.6% of recording days depending on the bay. Vessel-based visual surveys overlapped with the PAM surveys on 202 days across the four bays. No significant differences were found between visual and acoustic detections suggesting acoustic surveys can be used as a proxy for visual surveys. Given the need to monitor dolphin presence across sites, PAM is the most suitable and efficient tool for monitoring long-term presence/absence. Concomitant photo-identification surveys are necessary to address changes in abundance over time

Differential effects of human activity on Hawaiian spinner dolphins in their resting bays

Hawaiian spinner dolphins display predictable daily behavior, using shallow bays to rest during the daytime, bays that are also frequented by humans. All previous research on the potential response of Hawaiian spinner dolphins to human activity has been conducted visually, at the surface. In this study we take a different approach by using passive acoustic monitoring to analyze dolphin behavior and assess whether human activity affects the behavior of the animals. We used days (n=99) and hours (n=641) when dolphins were confirmed present in visual surveys between January 9, 2011 and August 15, 2012 and metrics generated from concomitant 30-second sound recordings (n=9615). Previous research found that the dolphins were predictably silent during rest and that acoustic activity matched general activity of the dolphins with higher acoustic activity before and after rest, and silence during rest. The daily pattern of dolphin whistle activity in Bay 2 and 4 (Kealakekua and Kauhako) matched what would be expected from this earlier work. However, in Bay 1 and 3 (Makako and Honaunau) there was no drop in dolphin whistle activity during rest. After assessing the relationship between time of day and dolphin acoustic activity, data on human presence were used to determine how variability in the dolphins’ acoustic activity might be explained by human activity (i.e. the number of vessels, kayaks and swimmer snorkelers present). Bay 2, the bay with the most human activity, showed no relationship between dolphin whistle activity and human presence (either vessels, kayaks, or swimmer/snorkelers). Although the relationships were weak, Bay 1 displayed a positive relationship between dolphin whistle activity and the number of vessels and swimmer/snorkelers present in the bay. Bay 4 also showed a positive relationship between dolphin whistle activity and the number of swimmer snorkelers. We also documented less sound being added to the soundscape with each additional vessel in Bay 2 when compared to Bay 1, a bay with dolphin-focused activities. We hypothesize it is not the magnitude of the activity but the focus of the activity that matters and suggest that the effect of human activity on spinner dolphin acoustic behavior should be explored in future studies. These results have implications for designing future studies as well as for ongoing efforts to protect Hawaiian spinner dolphins in their resting bays

Evaluating monitoring methods for cetaceans

With increasing human pressures on wildlife comes a responsibility to monitor them effectively, particularly in an environment of declining research funds. Scarce funding resources compromise the level and efficacy of monitoring possible to detect trends in abundance, highlighting the priority for developing cost-effective programs. A systematic and rigorous sampling regime was developed to estimate abundance of a small, genetically isolated spinner dolphin (Stenella longirostris) population exposed to high levels of human activities. Five monitoring scenarios to detect trends in abundance were evaluated by varying sampling effort, precision, power, and sampling interval. Scenario 1 consisted of monthly surveys, each of 12 days, used to obtain the initial two consecutive annual abundance estimates. Scenarios 2, 3, and 4 consisted of a reduced effort, while Scenario 5 doubled the effort of Scenario 1. Scenarios with the greatest effort (1 and 5) produced the most precise abundance estimates (CV = 0.09). Using a CV = 0.09 and power of 80%, it would take 9 years to detect a 5% annual change in abundance compared with 12 years at a power of 95%. Under this best-case monitoring scenario, if the trend was a decline, the population would have decreased by 37% and 46%, respectively, prior to detection of a significant decline: With the potential of a large decline in a small population prior to detection, the lower power level should be used to trigger a management intervention. The approach presented here is applicable across taxa for which individuals can be identified, including terrestrial and aquatic mammals, birds, and reptiles

Shark detection probability from aerial drone surveys within a temperate estuary

Drones are easy to operate over metres-to-kilometre scales, making them potentially useful to monitor species distributions and habitat use in shallow estuaries with widely varying environmental conditions. To investigate the utility of drones for surveying bonnethead sharks (Sphyrna tiburo) across estuarine environmental gradients, we deployed decoys, fashioned to mimic sharks, in the field. Decoys were placed in two flight areas (0.8 km2 each) in shallow (&lt;2 m) water near Beaufort, N.C., on five days during 2015–2016. Survey flights were conducted using a fixed-wing drone (senseFly eBee) equipped with a digital camera. Images were indexed for combinations of six environmental factors across flights. Images representative of all (N = 36) observed environmental combinations were sent to a group of 15 scientists who were asked to identify sharks in each image. Non-parametric rank-sum comparisons and regression tree analysis on resultant detection probabilities highlighted depth as having the largest, statistically reliable influence on detection probabilities, with decreasing detection probabilities at increased depth. Detection probabilities were higher during midday flights, with notable effects of wind speed and cloud presence also apparent. Our study highlights depth as a first-order factor constraining the temperate estuarine habitats over which drones may reliably quantify sharks (i.e., <0.75 m)

Ab initio calculation of the neutron-proton mass difference

The existence and stability of atoms rely on the fact that neutrons are more massive than protons. The measured mass difference is only 0.14\% of the average of the two masses. A slightly smaller or larger value would have led to a dramatically different universe. Here, we show that this difference results from the competition between electromagnetic and mass isospin breaking effects. We performed lattice quantum-chromodynamics and quantum-electrodynamics computations with four nondegenerate Wilson fermion flavors and computed the neutron-proton mass-splitting with an accuracy of $300$ kilo-electron volts, which is greater than $0$ by $5$ standard deviations. We also determine the splittings in the $\Sigma$, $\Xi$, $D$ and $\Xi_{cc}$ isospin multiplets, exceeding in some cases the precision of experimental measurements.Comment: 57 pages, 15 figures, 6 tables, revised versio

The role of beach state and the timing of pre-storm surveys in determining the accuracy of storm impact assessments

Dune erosion principally occurs when water level exceeds the elevation of the beach and predicting erosion is progressively becoming more important for management as coastal populations increase, sea level rises, and storms become more powerful. This study assesses storm impacts using a simple model from Stockdon et al. (2007) configured with oceanographic information from the ADCIRC + SWAN model and frequently collected beach profiles. We applied that model to barrier islands in North Carolina including: Core Banks with a more dissipative beach morphology and Shackleford Banks and Onslow Beach with intermediate beach morphologies. The study periods captured 10 events where wave collision with the dunes and/or overwash were either predicted or observed, including large multiple-day events caused by hurricanes and smaller events caused by onshore winds and high tide. Comparing model output with a time series of beach photographs shows the predictive power and sensitivity of the model was consistently high at the Core Banks Site with its wide and low-gradient beach, high-elevation dunes (2.58 m), and high resistance to overwash. Model predictive power and sensitivity was lowest at the Shackleford Banks Site because frequent and large changes to beach slope and intermediate dune elevation (0.54–1.25 m) caused small variations of modeled total water level to either overpredict or underpredict storm impacts. In addition, storm impacts were always overpredicted during hurricanes at the Shackleford Banks Site, which was likely due to storm waves decreasing the beach slope from what was measured prior to the event and used as model input. Like Shackleford Banks, the beach slope of the Onslow Beach Site was steep and variable, but the low-elevation dunes (0.24–0.28 m) made resistance to overwash low and the predictive power and sensitivity of the model higher than at the Shackleford Banks Site. Results suggest that storm impacts and the associated potential for dune erosion is predicted more accurately at beaches where the threshold for overwash is high or low because total water level during most events will commonly fall short of or exceed the overwash threshold, respectively. The accuracy of predicting the storm impact regime is sensitive to beach slope. The slope of intermediate beaches is more variable than dissipative beaches and requires frequent measurement if it is to be represented accurately in the model, but this can be impractical and costly even using the latest drone-surveying methods. To maximize the accuracy of predicting storm impacts, intermediate beach morphology should be constrained by surveying at seasonal or yearly time scales and used as input to numerical models that estimate beach slope over short time scales (hours during an event or daily), configured with the latest wave and water-level forecasts

Spatio-temporal genetic tagging of a cosmopolitan planktivorous shark provides insight to gene flow, temporal variation and site-specific re-encounters

Migratory movements in response to seasonal resources often influence population structure and dynamics. Yet in mobile marine predators, population genetic consequences of such repetitious behaviour remain inaccessible without comprehensive sampling strategies. Temporal genetic sampling of seasonally recurring aggregations of planktivorous basking sharks, Cetorhinus maximus, in the Northeast Atlantic (NEA) affords an opportunity to resolve individual re-encounters at key sites with population connectivity and patterns of relatedness. Genetic tagging (19 microsatellites) revealed 18% of re-sampled individuals in the NEA demonstrated inter/multi-annual site-specific re-encounters. High genetic connectivity and migration between aggregation sites indicate the Irish Sea as an important movement corridor, with a contemporary effective population estimate (Ne) of 382 (CI = 241–830). We contrast the prevailing view of high gene flow across oceanic regions with evidence of population structure within the NEA, with early-season sharks off southwest Ireland possibly representing genetically distinct migrants. Finally, we found basking sharks surfacing together in the NEA are on average more related than expected by chance, suggesting a genetic consequence of, or a potential mechanism maintaining, site-specific re-encounters. Long-term temporal genetic monitoring is paramount in determining future viability of cosmopolitan marine species, identifying genetic units for conservation management, and for understanding aggregation structure and dynamics