Words: Jonian Dolphin Conservation
Photo-identification is a non-invasive technique for the identification of cetaceans, mostly used for “capturing and marking” single individuals of different species. The list of cetacean species that have been studied using photo-identification includes several species of baleen whales, as well as many species of large and small odontocetes (toothed whales).
The photo-identification method can be used to study their behaviour, migrations patterns, size and structure of populations. All these data are collected by our team during the “Researcher for a Day” program, with the valuable contribution of tourists, students and visitors. Subsequently, the data is processed by our researchers and shared through scientific publications and awareness reports.
In our particular geographical research area –the Gulf of Taranto, Northern Ionian Sea -this method is applied to different species: sperm whales, short-beaked common dolphins, bottlenose dolphins and Risso’s dolphins. For bottlenose, Risso’s and short-beaked common dolphins, their dorsal fin is the distinctive feature. Characterized by different shapes and colouration patterns, their dorsal fins allow us to identify each individual of these species that occur in the Gulf of Taranto.
As for the large sperm whales, we observe their flukes, which usually emerge just before a long and deep dive, related to hunting behaviour. Their flukes are characterized by unique marks, which allow us to identify each single sperm whale encountered.
These studies and observations, conducted thanks to the support of many people, confirmed the regular presence of apex predators in the marine food chain in an area like the Gulf of Taranto, which is highly impacted by anthropic activities. These animals are a fundamental indicator of the health of the Ionian Sea. Therefore, they have crucial management implications, as they contribute to guide local administrations towards more effective protective measures to preserve the biological diversity and the integrity of habitats.
Support the Jonian Dolphin Conservation by adopting a cetacean
If you want to support the conservation efforts of our team, the Jonian Dolphin Conservation, you can do it in many ways. One of them, it’s through the adoption of the dolphins and sperm whales that we have observed and catalogued:
https://www.joniandolphin.it/wordpress/2017/adozioni/?lang=en
And there’s more..
Furthermore, two new scientific publications have been produced as a result of the work Jonian Dolphin Conservation have been undertaking. You can read them both here:
Convolutional Neural Networks for Risso’s Dolphins Identification
Abstract:
Photo-identification is one of the best practices to estimate the abundance of cetaceans and, as such, it can help to obtain the biological information necessary to decision-making and actions to preserve the marine environment and its biodiversity. The Risso’s dolphin is one of the least-known cetacean species on a global scale, and the distinctive scars on its dorsal fin proved to be extremely useful to photo-identify single individuals. The main novelty of this paper is the development of a new method based on deep learning, called Neural Network Pool (NNPool), and specifically devoted to the photo-identification of Risso’s dolphins. This new method also includes the unique function of recognizing unknown vs known dolphins in large datasets with no interaction by the user. Moreover, the new version of DolFin catalogue, collecting Risso’s dolphins data and photos acquired between 2013-2018 in the Northern Ionian Sea (Central-eastern Mediterranean Sea), is presented and used here to carry out the experiments. Results have been validated using a further data set, containing new images of Risso’s dolphins from the Northern Ionian Sea and the Azores, acquired in 2019. The performance of the NNPool appears satisfying and increases proportionally to the number of images available, thus highlighting the importance of building large-scale data set for the application at hand.
Combined Color Semantics and Deep Learning for the Automatic Detection of Dolphin Dorsal Fins
Abstract:
Photo-identification is a widely used non-invasive technique in biological studies for understanding if a specimen has been seen multiple times only relying on specific unique visual characteristics. This information is essential to infer knowledge about the spatial distribution, site fidelity, abundance or habitat use of a species. Today there is a large demand for algorithms that can help domain experts in the analysis of large image datasets. For this reason, it is straightforward that the problem of identify and crop the relevant portion of an image is not negligible in any photo-identification pipeline. This paper approaches the problem of automatically cropping cetaceans images with a hybrid technique based on domain analysis and deep learning. Domain knowledge is applied for proposing relevant regions with the aim of highlighting the dorsal fins, then a binary classification of fin vs. no-fin is performed by a convolutional neural network. Results obtained on real images demonstrate the feasibility of the proposed approach in the automated process of large datasets of Risso’s dolphins photos, enabling its use on more complex large scale studies. Moreover, the results of this study suggest to extend this methodology to biological investigations of different species.
