Climate change affects mountain forests by increasing the intensity and frequency of disturbances such as drought, insect and pathogen outbreaks, fire, wind and ice storms. As a result widespread tree mortality has been reported in recent decades. Most mountain forests support a rich community of organisms, so the loss or replacement of any tree species implies a change in species composition and a financial and economic cost. Understanding which species are lost and which are resilient to these environmental changes is crucial in order to take reasoned management decisions for mitigation. In addition, the presence of large numbers of dead trees and the replacement of dying native trees by exotic species have an impact on human inhabitants, tourists, and forest owners and can lead to local social conflicts over whether resources should be expended on maintaining traditional landscapes. To study the impact of climate change and forest management on the biodiversity of highland forests, we will quantify changes in species richness and composition of a wide range of terrestrial and freshwater organisms, along tree-dieback gradients of four highland conifers in European and Chinese mountains, using cutting-edge molecular technology. We will also measure changes in functional diversity for several focal groups recognized as regulators and indicators of key water and soil processes and ecosystem services. To study the perception of climate change by local populations and the socioeconomic impact of climate-induced mountain forest diebacks and tree replacement strategies on local communities we will carry out both qualitative and quantitative surveys in Europe and China. This project involves a multidisciplinary team of ecologists, sociologists, economists, geographers, forest entomologists, limnologists, mycologists, molecular biologists, forest managers and policy makers. We will work with stakeholders to disseminate the results of the project and facilitate the adoption of newly generated tools and indicators by policy makers.

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.