Call for Experts: BiodivRestore Knowledge Hub
Join the BiodivRestore Knowledge Hub and shape the future of restoration!
Join the BiodivRestore Knowledge Hub and shape the future of restoration!
Imagine a Europe where biodiversity monitoring flows seamlessly across borders, providing a clear picture of the continent’s ecological health… To achieve this goal, Biodiversa+ is promoting the establishment of coordination hubs at different levels…
EU-funded BiodivScen projects highlight critical pathways for biodiversity conservation and restoration in Europe…
Invasive alien species are one of the top five drivers of biodiversity loss worldwide. To prevent the future introduction and spread of these species, we need to improve cooperation across Europe…
Biodiversa+ aims to promote and support transnational biodiversity monitoring, by building a transnational network of harmonised biodiversity monitoring schemes on specific priority topics. Soil biodiversity is one of them…
The second CO-OP4CBD call for experts is open. They are looking for expertise within the EU to enhance the implementation of the Convention on Biological Diversity (CBD). Share your knowledge and join a network of passionate professionals working towards impactful policy solutions…
As the continent’s largest network of protected areas, Natura 2000 sites play a critical role in the conservation of bird populations. But how can we manage these sites effectively in a changing climate? Take the survey…
The pilot examined and evaluated the current state of biodiversity monitoring governance, data management and interoperability, and data standards across participating countries and regions.
The pilot combines traditional morphological and DNA-based methods into a unified framework and develops standardised procedures for soil biodiversity assessment and reporting, in Europe and beyond.
This pilot is developing new methods to monitor invasive alien species, focusing on plants and insects. It uses image recognition techniques based on computer vision and deep learning.