Ecosystem services across Europe. D4.2 Current and future natural capital and ecosystem services

The EU Biodiversity Strategy for 2030 aims to put biodiversity on the path to recovery by 2030. A key component of the Strategy is the development of a coherent Trans-European Nature Network (TEN-N), to increase the coherence of the existing network of Natura 2000 sites and other nationally designated protected areas by addressing gaps in the coverage of priority habitats and species. The NaturaConnect project supports the design of a TEN-N, amongst others by designing and developing a future-proof blueprint through spatial conservation prioritisation. In this context, it is key to consider multifunctionality, that is, to ensure that the TEN-N addresses not just ecological representativeness but also the ability of nature to meet societal needs or demands through the provisioning of ecosystem services (ES).

The present deliverable of NaturaConnect (D4.2) provides a set of ES layers aligned with present and potential future land and climate conditions, designed for use in spatial conservation prioritisation. We generated layers for a selection of regulating and cultural ES, with a focus on climate change mitigation (carbon storage and sequestration) and adaptation (e.g., improving soil retention considering expected increases in the magnitude and frequency of heavy rainfall events), food security (crop pollination, pest control), as well as the capacity of nature to improve people’s mental and physical health by offering opportunities for recreation and experiencing nature. We quantified all ES based on common input data with regard to land systems and climate, to ensure compatibility. Where possible and relevant, we considered ES supply, demand and flow separately.

We quantified carbon storage and sequestration according to a book-keeping approach, assigning typical values of the amounts of carbon stored (MgC/ha) and sequestred (MgC/ha/yr) to each land system. We considered only the supply of carbon storage and sequestration, reasoning that the demand for this service is global and considerably larger than the supply. The amounts of carbon stored and sequestered are based on values from the scientific literature and existing datasets which indicate how much carbon is stored and sequestered per land system, and how this would change if the land system underwent a transition (e.g. from forest to cropland). Output maps revealed that forests and wetlands, especially in northern Europe, are characterised by the highest carbon storage and sequestration rates. Croplands are characterised by negative sequestration rates, hence act as sources of emission.

We quantified the supply of soil retention based on the ability of vegetation to prevent soil erosion induced by heavy rainfall events, using the universal soil loss equation (RUSLE) to assess soil erosion. Specifically, we quantified the soil retention service (t/ha/yr) based on how much soil loss is prevented by the current vegetation cover, defined per land system, as compared to a counterfactual situation without vegetation. We also quantified the potential additional prevention of soil loss (t/ha/yr) if the vegetation were restored from its current state to a maximum cover. We defined soil retention demand based on the amount of soil loss to be prevented in order to ensure that losses would not exceed the natural soil formation rate. Output maps revealed hotspots of actual and potential additional soil retention demand, supply and flow mainly in mountainous regions, reflecting the key role of terrain slope in determining erodibility as well as the importance of vegetation for reducing it.

We modelled the supply of crop pollination based on the potential of pollinator habitat to provide pollinators and the demand based on the presence of nearby cropland in need of pollination. Using observational data from scientific literature and existing databases, we first established a quantitative relationship that estimates wild pollinator abundance in pollinator-dependent cropland (n/m ² ) based on various ecologically relevant covariates, including the proportion of pollinator habitat within 3 km from the cropland cell. We used this relationship to map pollinator abundance in croplands across Europe, which we subsequently attributed to the cells with pollinator habitat (i.e., the service-providing units) within 3 km from each focal cropland cell, to facilitate application of the model results in spatial conservation prioritisation. Output maps reveal high pollinator abundance values for habitat cells located in areas dominated by cropland, as these habitat cells serve multiple cropland cells, and low values when multiple habitat cells surround a single cropland cell.

To assess forest recreational potential , we developed a spatial model based on people’s preferences for forests with different structural characteristics, expressed through the willingness-to-travel (WTT) indicator. Using data from a large-scale visual choice experiment conducted in 12 European countries, we estimated WTT as a function of forest management classes, combined with spatial data on canopy height and tree species diversity. The result is the first Europe-wide map of forest recreational potential, revealing particularly high values in regions with taller, more diverse, and structurally complex forests.

We modelled landscape recreational potential based on the recreational opportunities associated with the land systems surrounding each grid cell. We quantify supply based on the number and diversity of land systems that provide recreational opportunities within a given distance from each focal grid cell, and the demand based on the number of potential beneficiaries within a certain distance. Well-supplied areas encompass, among others, the western Iberian peninsula (Portugal) and the Pyrenees, the Auvergne, Rhone-Alpes, and the Provence-Alpes-Cote d’Azur in France, Ireland, Scotland, the Alps and Dinarides as well as the Baltics (Estonia, Latvia), and large parts of the Scandinavian Peninsula and Finland. Demand is particularly high for the European megacities and the various conurbations and metropolitan areas.

Finally, we modelled nine regulating and five cultural species-based ecosystem services provided by terrestrial vertebrate species, including, among others, carrion removal, control of pest species (bark beetles, mosquitoes) and evolutionary heritage. For each service, we modelled supply based on the number of specific vertebrate species able to provide a certain service and demand based on the land system in a grid cell assumed to be in need of the service. Resulting maps show distinct patterns for the different ES, revealing the richness of provider species in areas with demand for each service.

The ES layers described in this report were primarily developed to support broad-scale spatial conservation or restoration prioritisation efforts, i.e., efforts to identify and rank planning units (in this case grid cells) based on features considered in need of conservation or restoration. In the NaturaConnect project, the ES layers will be used together with layers of other relevant variables, such as biodiversity features, habitat connectivity and the costs of conservation, to identify pan-European conservation priorities. Beyond NaturaConnect, we expect our layers to be useful in particular for national and sub-national governmental and non-state authorities responsible for land planning, as our maps can help in identifying sites where ES supply or flow are high (indicating a need for conservation) or where demand is high yet supply is low (indicating a need for restoration). This way, we expect the layers and underlying code to be useful for informing land management and conservation planning also beyond the project.