Data from: Temporally and spatially partitioned behaviours of spinner dolphins: implications for resilience to human disturbance

Selective forces shape the evolution of wildlife behavioural strategies and influence the spatial and temporal partitioning of behavioural activities to maximize individual fitness. Globally, wildlife is increasingly exposed to human activities which may affect their behavioural activities. The ability of wildlife to compensate for the effects of human activities may have implications for their resilience to disturbance. Resilience theory suggests that behavioural systems which are constrained in their repertoires are less resilient to disturbance than flexible systems. Using behavioural time-series data, we show that spinner dolphins (Stenella longirostris) spatially and temporally partition their behavioural activities on a daily basis. Specifically, spinner dolphins were never observed foraging during daytime, where resting was the predominant activity. Travelling and socializing probabilities were higher in early mornings and late afternoons when dolphins were returning from or preparing for nocturnal feeding trips, respectively. The constrained nature of spinner dolphin behaviours suggests they are less resilient to human disturbance than other cetaceans. These dolphins experience the highest exposure rates to human activities ever reported for any cetaceans. Over the last 30 years human activities have increased significantly in Hawaii, but the spinner dolphins still inhabit these bays. Recent abundance estimates (2011 and 2012) however, are lower than all previous estimates (1979–1981, 1989–1992 and 2003), indicating a possible long-term impact. Quantification of the spatial and temporal partitioning of wildlife behavioural schedules provides critical insight for conservation measures that aim to mitigate the effects of human disturbance

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

An integrated data management and video system for sampling aquatic benthos

Remote video systems can be expensive, slow to deploy and the data recorded may not be available until the system has been retrieved. To overcome these issues a rapid, non-destructive and cost-effective remote video and data management system was developed to record benthic habitats in Shark Bay, Western Australia. This system comprises a downward oriented video camera, linked to a laptop computer, attached to the apex of a stainless steel pyramid to film a 1 m2 area of benthos. The video image of the substratum, spatial coordinates, depth and temperature are recorded in a database at the time of deployment. A web interface was developed to manage the database and examine the video images to determine the percent cover of seagrass, sponge type (conical or non-conical) and the total number of sponges in the quadrat. Using this system, a total of 1,380 video quadrats were collected from a study area of approximately 248 km2, ranging in water depth from 2 to 16 m. An average of 16.4 (±1.3 SE) samples was recorded every hour during 15 days. This system could be modified to quantify substratum components at a greater taxonomic resolution or to record details of the mobile fauna

Data from: The importance of spinner dolphin (Stenella longirostris) resting habitat: implications for management

Linking key ecological characteristics with animal behaviour is essential for identifying and protecting important habitats that support life functions. Spinner dolphins display a predictable diurnal behavioural pattern where they forage offshore at night and return to sheltered bays during daytime to rest. These bays, which are also subject to considerable use by humans, have long been recognized as key habitats for this species although the extent to which dolphins rely on specific characteristics of these habitats for rest has not been quantified. An integration of boat-based and land-based group focal follow sampling regimes and three gradient boosting generalized additive models were developed to identify habitat features that contribute to the occurrence of resting spinner dolphins in coastal waters off Hawai'i Island. Two ‘in-bay’ models used data collected within bays, and a third ‘coastal’ model (near-shore, outside of bays) used data collected both inside and outside of bays. The coastal model identified that spinner dolphins were unlikely to rest outside sheltered bays. In-bay models showed that dolphins rested throughout daylight hours within bays with a peak resting period between 10.00 h to 14.00 h. The models also identified bottom-substrate-type as an important predictor of rest. Pseudo R2 values of 0·61 and 0·70 for the in-bay models and 0·66 for the coastal model showed that these models provided a good fit to the behavioural data for the occurrence of resting spinner dolphins. Synthesis and application. To date, studies evaluating spinner dolphin resting habitat have focussed on areas inside bays only. Here, we combined data collected inside and outside bays, and illustrate that should resting spinner dolphins be displaced from resting bays, they are unlikely to engage in resting behaviour elsewhere. Results provide further information on the importance of bays as important habitat for resting spinner dolphins. To mitigate the disturbance from human interactions during important rest periods, we recommend that management keep the spinner dolphin resting areas free from human activities. Our quantitative approach where models explicitly link behaviour with habitat characteristics is applicable to identify important habitats for protection of other taxa

The importance of spinner dolphin (Stenella longirostris) resting habitat: Implications for management

The combined boat-based and land-based group focal follow data to determine the resting behaviour of spinner dolphins across a range of available habitats, inside four bays and along open coastline adjacent to the bays

Challenges of collecting blow from small cetaceans

We trialed the collection of blow samples using a waterproof electric multirotor (quadcopter) drone from two free‐ranging dolphin species, the abundant and approachable bottlenose dolphin (Tursiops aduncus) and the less common and boat shy humpback dolphin (Sousa sahulensis). This drone was fast, maneuverable, and quiet compared to other drones commonly used in studies of cetaceans and relative to their hearing thresholds. We were successful in collecting blow samples from four individual dolphins (three bottlenose dolphins and one humpback dolphin) in two groups. The success of obtaining samples was dependent on the individual dolphin's activity. We were successful in sampling when dolphins were resting and socializing but found that socializing dolphins were not predictable in their surfacing and direction and therefore do not recommend drone sampling socializing dolphins. The suitability and preference of the sampling technique over biopsy sampling is highly dependent on the dolphin activity. We also attempted to extract DNA from the blow samples with the aim of assessing the feasibility of using blow sampling by drone for population genetic studies. We were unsuccessful in extracting DNA and recommend that others attempting to sample dolphin blow with a drone should prioritize collecting a larger volume of blow that may yield adequate concentrations of DNA to be amplified. Blow sample volume could potentially be increased by sampling with more absorbent materials

Number of photographic identification surveys, hours in each bay, spinner dolphin encounters in four resting bays along the Kona Coast of Hawai’i Island from September 2010 to August 2011.

<p>Number of photographic identification surveys, hours in each bay, spinner dolphin encounters in four resting bays along the Kona Coast of Hawai’i Island from September 2010 to August 2011.</p

Highly distinctive (<i>D1</i>) population abundance estimates calculated from open and closed mark recapture models.

<p>Highly distinctive (<i>D1</i>) population abundance estimates calculated from open and closed mark recapture models.</p

The combination of bays in which individual spinner dolphins have been sighted from September 2010 to August 2011.

<p>A = Kauhako Bay, B = Honaunau Bay, C = Kealakekua Bay and D = Makako Bay.</p

Map of the study area illustrating the locations of the four spinner dolphin resting bays, Kauhako Bay, Honaunau Bay, Kealakekua Bay and Makako Bay, along the Kona Coast of Hawai’i Island in relation to the other island regions in the Main Hawaiian Islands (inset).

<p>Map of the study area illustrating the locations of the four spinner dolphin resting bays, Kauhako Bay, Honaunau Bay, Kealakekua Bay and Makako Bay, along the Kona Coast of Hawai’i Island in relation to the other island regions in the Main Hawaiian Islands (inset).</p