BIG_PICTURE

Finding pathways for humans to coexist with biodiversity in Europe requires significant levels of up-to-date knowledge on species status, distribution, relative abundance, and their interactions with humans and each other. This is because of the human-dominatednature of the landscape with its associated pressures and drivers, the manifold forms of direct and indirect interactions betweenhumans and biodiversity, and the resulting need for adaptive management. Effective conservation requires continental scalecoordination, which requires continental scale data. This can only be achieved if we avail of methods that (1) can target many speciesat the same time, and (2) can make use of data collected for many different purposes by a diversity of professional and citizenscientists. Digital camera traps are one such tool, the use of which has exploded in recent years. There are literally tens of millions ofimages of wildlife being produced each year across Europe. However, the state of data processing tools and data sharing proceduresare not yet developed to allow an efficient classification, storage, and sharing of this data. Camera traps are also used in a myriaddifferent ways, with different field sampling protocols used in different areas and dependent on the primary motivations of the usersand their target species. It is unclear to what extent data collected under different regimes can be compared. In order to make thisvast data resource more available for scientists and biodiversity managers this project proposes a set of four interlinkedworkpackages that will; (1) Explore legal, institutional, and social contraints on data sharing with a view to identify pathways thatfaciliate making data as open and available as possible. (2) Develop efficient and AI-enabled database structures that facilitate theefficient processing of raw data, the safe storage of the data, and export formats that conform to emerging data standards tofacilitate data sharing and comparative analysis. (3) An exploration of statistical analysis tools and procedures that find ways tomaximise the integration of data collected under different protocols into common analysis, essentially determining which data, onwhich species, can be used to determine which inferences. (4) A set of demonstration analyses that reveal the possibility and added-value that can be obtained when data is pooled across projects and countries. These illustrative analyses will cover a range ofbiodiversity policy areas, including One Health, Climate Change, Invasive Species, Natura 2000 site management, and conservationof Habitat Directive listed species.