Photo-Identification Methods Reveal Seasonal and Long-Term Site-Fidelity of Risso’s Dolphins (<i>Grampus griseus</i>) in Shallow Waters (Cardigan Bay, Wales)

A photo-identification study on Risso’s dolphins was carried out off BardseyIslandinWales(July to September, 1997-2007). Their local abundance was estimated using two different analytical techniques: (1) mark-recapture of well-marked dolphins using a ‘closed-population’ model;and (2) a census technique based on the total number of identified individual dolphins sighted over the study period. The mark-recapture estimates of 121 (left sides;64 - 178 95% CI;CV 0.24) and 145 dolphins (right sides;78 - 213 95% CI;CV 0.24) closely matched the census technique estimates (population size of 90 - 151). It was found that the dolphins showed a degree of long-term and seasonal site-fidelity. A first long-distance match was made for Risso’s dolphins (319 km) betweenBardseyIslandandCornwall, confirming they can be wide-ranging animals. This study demonstrates that the combination of systematic and opportunistic photo-ID studies has complementary value as a population assessment tool in generating the first local abundance estimate for Risso’s dolphins inUKwaters. From the conservation perspective, these studies confirm the regular presence of Risso’s dolphins in these waters and the presence of calves shows breeding.BardseyIslandmay be part of a network of localities that are important habitats to this species where it may take advantage of prey abundance in shallow waters. As such, results of this study may provide assistance to include the Risso’s dolphin in future regional conservation strategies including the envisaged marine protected areas.

Individual Minke Whale Recognition Using Deep Learning Convolutional Neural Networks

The only known predictable aggregation of dwarf minke whales (Balaenoptera acutorostrata subsp.) occurs in the Australian offshore waters of the northern Great Barrier Reef in May-August each year. The identification of individual whales is required for research on the whales’ population characteristics and for monitoring the potential impacts of tourism activities, including commercial swims with the whales. At present, it is not cost-effective for researchers to manually process and analyze the tens of thousands of underwater images collated after each observation/tourist season, and a large data base of historical non-identified imagery exists. This study reports the first proof of concept for recognizing individual dwarf minke whales using the Deep Learning Convolutional Neural Networks (CNN).The “off-the-shelf” Image net-trained VGG16 CNN was used as the feature-encoder of the perpixel sematic segmentation Automatic Minke Whale Recognizer (AMWR). The most frequently photographed whale in a sample of 76 individual whales (MW1020) was identified in 179 images out of the total 1320 images provid-ed. Training and image augmentation procedures were developed to compen-sate for the small number of available images. The trained AMWR achieved 93% prediction accuracy on the testing subset of 36 positive/MW1020 and 228 negative/not-MW1020 images, where each negative image contained at least one of the other 75 whales. Furthermore on the test subset, AMWR achieved 74% precision, 80% recall, and 4% false-positive rate, making the presented approach comparable or better to other state-of-the-art individual animal recognition results.

Site Fidelity and Residency of Tursiops truncatus off the Aragua Coast,Venezuela-First Records of Long Residency

This study represents the first comprehensive analysis of the residency patterns of a coastal population of bottlenose dolphin off the coast of Aragua,Venezuela,over a multi-year period.Using photo-identification,the most recent study(2019-2020)identified 56 individuals with the time between encounters from one to 344 days between the first and last sighting.Site Fidelity(SF)and Residence(RES)indices were calculated and Agglomerative Hierarchical Clustering(AHC)modeling was performed,with three patterns of residence obtained:resident(25%),semi-resident(17.86%)and transient(57.14%).These results were contrasted with remodeled data from a previous study(2006-2007),showing similar patterns:resident(24.44%),semi-resident(28.89%)and transient(46.67%).Importantly,two individuals were found to have been resident over the extended period.A breeding female sighted for the first time in 2004 and again in 2020(16 years)and the other from 2005 to 2020(15 years).This region is an important area for marine mammals,known to support a resident reproductive population over many years,as well seabirds,sea turtles,whale sharks and fishermen.We recommend that consideration be given to designating the waters as a Marine Protected Area to safeguard the existing population and provide benefit to the surrounding marine environment.

Combining spawn egg counts,individual photo-ID and genetic fingerprinting to estimate the population size and sex ratio of an endangered amphibian

According to the International Union for Conservation of Nature Red List,41%of the world’s amphibian species are threatened with extinction,making them more threatened than any other vertebrate group nowadays.Given the global amphibian crisis,comprehensive understanding of demographics and population trends of declining and threatened species is essential for effective management and conservation strategies.Counting egg spawns is widely used to assess population abundance in pond breeding anurans.However,it is unknown how such counts translate into robust population size estimations.We monitored the breeding activity of the Natterjack toad(Epidalea calamita),combining egg string counts and individual photo-identification with Capture-Mark-Recapture population size and operational sex ratio estimation.Male Natterjack toads were identified by the pattern of natural markings with repeated ID of the same individual confirmed for 10%of the samples using genetic fingerprinting.We identified 647 unique individuals within a closed study population at Caherdaniel,Co Kerry.Population estimates derived from egg string counts estimated a breeding population of 368 females(95%CI 353–384)and Capture-Mark-Recapture estimated a breeding population of 1698 males(95%CI 1000–2397).The female:male sex ratio was conservatively estimated at 1:5(95%CI 1:3–1:6)where 62%±6%of females were assumed to spawn.These substantially departed from any priori assumption of 1:1 which could have underestimated the breeding population by up to 72%.Where amphibian absolute population size estimation is necessary,methods should include empirical survey data on operational sex ratios and not rely on assumptions or those derived from the literature which may be highly population and/or context-dependent.