This policy brief shows how scenarios focused on biodiversity can map potential pathways to enhance ecosystem resilience.
This brief is based on findings of the PEATBOG project, illustrates a “win-win” between biodiversity-conservation and climate-change mitigation.
This brief is derived from the LinkTree project, which examined the genetic variation within forest tree populations in five European countries, and assessed how this variability and its management could help forests adapt to environmental changes.
This brief is based on the Ecocycles research results, treats of the importance of European policies (for example, the Common Agricultural Policy, the EU Strategy on Climate Adaptation) and actions in the context of the conservation of small mammals and other species which depend on them.
This brief builds on the conclusions from the CLIMIT project focusing on the conservation of threatened and vulnerable insects in the context of changing land use and climate.
This brief presents how the results from the TipTree, TIPPINGPOND and EC21C projects allow characterization of tipping points for two types of European ecosystems, forests and ponds.
This brief presents how the CONNECT, REGARDS, TALE and VITALprojects use optimization tools and participative approaches to quantify synergies and trade-offs between ecosystem services and identify policy options for their sustainable management.
This brief is based on the SPONFOREST BiodivERsA 2015-2016 research project presents information on how natural forest expansion can offer a cost-effective nature-based solution and climate mitigation measure.
This brief summarises the research showing that effectiveness of Marine Protected Areas (MPAs) depend on their management objectives, their level of protection, and the proximity to other areas with various human pressures.
This brief presents information on how soil biodiversity supports a wide range of ecosystem services, and influences crop properties beyond productivity, but that its benefits are often not well-known or underestimated.