BioacAI doctoral network workshop in Czech Republic

From May 6th to May 10th, 2024, PhD student Yasmine Benhamadi and CNRS scientist Vincent Lostanlen have attended the first internal workshop of the BioacAI doctoral network. The Czech University of Life Sciences in Prague hosted the event in its University Forest Establishment, an ancient castle in the town of Kostelec nad Černými lesy. Yasmine… Continue reading BioacAI doctoral network workshop in Czech Republic

11 juin 2024 : colloque “Capteurs acoustiques en environnement” à Nantes

Le son, en tant que vecteur d’information, est une aubaine pour les sciences naturelles. À l’heure des smartphones et de l’Internet des objets, il devient possible de décrire dans le détail les propriétés acoustiques d’un environnement, que celui-ci soit naturel ou industrialisé. Des algorithmes d’intelligence artificielle (IA) sont alors requis pour traiter automatiquement les données massives ainsi… Continue reading 11 juin 2024 : colloque “Capteurs acoustiques en environnement” à Nantes

PhD offer: Developmental robotics of birdsong

The Neurocybernetic team of ETIS Lab (CNRS, CY Cergy-Paris University, ENSEA) is seeking applicants for a fully funded PhD place providing an exciting opportunity to pursue a postgraduate research in the fields of bio/neuro-inspired robotics, ethology, neuroscience.Webpage: This PhD is funded by the French ANR, under the 4 years’ project “Nirvana” on sensorimotor integration of… Continue reading PhD offer: Developmental robotics of birdsong

8 février 2024 : “Les sens artificiels” au Stereolux

Le jeudi 8 février 2024 à 18h30 au Stereolux, dans le cadre de la Nuit blanche des chercheur-e-s de Nantes université. L’intelligence artificielle (IA) révolutionne notre compréhension du vivant en utilisant les sens humains. Elle permet une analyse poussée de la parole, des signaux sonores et de la bioacoustique. En médecine, les sens peuvent être reproduits pour améliorer les… Continue reading 8 février 2024 : “Les sens artificiels” au Stereolux

Efficient Evaluation Algorithms for Sound Event Detection @ DCASE

Our article presents an algorithm for pairwise intersection of intervals by performing binary search within sorted onset and offset times. Computational benchmarks on the BirdVox-full-night dataset confirms that our algorithm is significantly faster than exhaustive search. Moreover, we explain how to use this list of intersecting prediction-reference pairs for the purpose of SED evaluation.

Automated acoustic monitoring captures timing and intensity of bird migration @ J. Applied Ecology

Monitoring small, mobile organisms is crucial for science and conservation, but is technically challenging. Migratory birds are prime examples, often undertaking nocturnal movements of thousands of kilometres over inaccessible and inhospitable geography. Acoustic technology could facilitate widespread monitoring of nocturnal bird migration with minimal human effort. Acoustics complements existing monitoring methods by providing information about individual behaviour and species identities, something generally not possible with tools such as radar. However, the need for expert humans to review audio and identify vocalizations is a challenge to application and development of acoustic technologies. Here, we describe an automated acoustic monitoring pipeline that combines acoustic sensors with machine listening software (BirdVoxDetect). We monitor 4 months of autumn migration in the northeastern United States with five acoustic sensors, extracting nightly estimates of nocturnal calling activity of 14 migratory species with distinctive flight calls. We examine the ability of acoustics to inform two important facets of bird migration: (1) the quantity of migrating birds aloft and (2) the migration timing of individual species. We validate these data with contemporaneous observations from Doppler radars and a large community of citizen scientists, from which we derive independent measures of migration passage and timing. Together, acoustic and weather data produced accurate estimates of the number of actively migrating birds detected with radar. A model combining acoustic data, weather and seasonal timing explained 75% of variation in radar-derived migration intensity. This model outperformed models that lacked acoustic data. Including acoustics in the model decreased prediction error by 33%. A model with only acoustic information outperformed a model comprising weather and date (57% vs. 48% variation explained, respectively). Acoustics also successfully measured migration phenology: species-specific timing estimated by acoustic sensors explained 71% of variation in timing derived from citizen science observations. Our results demonstrate that cost-effective acoustic sensors can monitor bird migration at species resolution at the landscape scale and should be an integral part of management toolkits. Acoustic monitoring presents distinct advantages over radar and human observation, especially in inaccessible and inhospitable locations, and requires significantly less expense. Managers should consider using acoustic tools for monitoring avian movements and identifying and understanding dangerous situations for birds. These recommendations apply to a variety of conservation and policy applications, including mitigating the impacts of light pollution, siting energy infrastructure (e.g. wind turbines) and reducing collisions with structures and aircraft.

Timing of dawn chorus in songbirds along an anthropization gradient @ ICCB

On the basis of a field survey conducted on a breeding bird community (37 species) in spring 2022 in France, we disentangle the relative influence of such factors of the timing of bird chorus both at the species and community levels. Human activities are thus not only driving temporal changes in different bird species but also promote a change in the temporal structure of the chorus at the whole community.