Biodiversité

COMMUNIQUE DE PRESSE - L’application de sciences participatives DRYRivERS montre déjà des premiers résultats ! Déployée à l’échelle internationale en 2022, elle enregistre en 1 an plus de 4000 contributions. Un ensemble de données en open-source, accessibles à tous via un simple site web. Un démarrage encourageant pour la préservation et la gestion de nos rivières, à l’échelle du globe.

Inclusiveness on all levels underpins SwafS. We need science education for all, gender equality in our organisations, ethics and integrity embedded in research, communication we can trust, open science and ultimately place citizens at the core to ensure excellent Research and Innovation to tackle the challenges of today for a better future. Europe can only thrive by matching the immense potential of science with the values, needs, and aspirations of society. Horizon Europe must strengthen efforts to tap into the vast potential citizens have to offer and ensure effective cooperation between science and society. This document reports on the Horizon 2020 Science with and for Society (SwafS), citizen science and citizen engagement project portfolio results.

Paris est l’une des capitales les plus boisées d’Europe. Si les platanes et les marronniers figurent en tête des essences représentées dans ses rues, la

In the French West Indies, more than 20 species of cetaceans have been observed over the last decades. The recognition of this hot spot of biodiversity of marine mammals observed in the French Exclusive Economic Zone of the West Indies motivated the French government to create in 2010 a marine protected area (MPA) dedicated to the conservation of marine mammals: the Agoa sanctuary. Threats that cetacean populations face are multiple but well-documented. Cetacean conservation can only be achieved if relevant and reliable data are available, starting by occurrence data. 

Time-lapse cameras facilitate remote and high-resolution monitoring of wild animal and plant communities, but the image data produced require further processing to be useful. Here we publish pipelines to process raw time-lapse imagery, resulting in count data (number of penguins per image) and ‘nearest neighbour distance’ measurements. The latter provide useful summaries of colony spatial structure (which can indicate phenological stage) and can be used to detect movement – metrics which could be valuable for a number of different monitoring scenarios, including image capture during aerial surveys. We present two alternative pathways for producing counts: (1) via the Zooniverse citizen science project Penguin Watch and (2) via a computer vision algorithm (Pengbot), and share a comparison of citizen science-, machine learning-, and expert- derived counts.