By Marta Pérez-Soba (DLO-Alterra) and Maria Luisa Paracchini (JRC).
Agriculture and forestry activities influence the availability and quality of Public Goods (PG) and Ecosystem Services (ES) supplied by farming and forest ecosystems through management activities. There is a large spatial variation across Europe in the nature and management of farming and forestry systems, their biogeographic conditions and their social, economic and institutional context. Spatial analysis can help improve our understanding of the nature of PG/ES provision, the positive and negative interactions between provision and management in different situations, as well as the demand for different PG/ES in different locations. However, many different methodological approaches and different sets of indicators are currently being used to assess individual PG/ES at national/regional level, which makes it difficult to make comparisons between different Members States.
PEGASUS is building a consistent mapping approach, to achieve a more comprehensive and more operational inventory and geospatial understanding of the occurrence, condition and interactions of PG/ES in the diverse forestry and farming systems in the EU. This will be achieved by critically reviewing existing inventories, methodological approaches and indicator datasets for mapping. On this basis, current mapping and data collation and comparison will be extended to enable a more comprehensive analysis of PG/ES distribution in the EU, including the identification of areas of high and low supply. The analysis of variations in governance, institutional and market drivers and influences upon PG/ES and their status will complete the picture. Feedback from the broad range of real-world case studies will help to refine the framework and make it more operational.
A crucial outcome of the spatial analysis (at EU-28 level and in the case studies) is to reveal the relevant spatial scales at which agriculture and forestry systems provide PG/ES. There are some PG/ES that are strongly influenced by land management activities wherever they occur (e.g. GHG emissions) whilst others are dependent on the local context; some are produced in the vicinity of the locations that benefit from them, whilst others are produced much farther afield. For example urban areas can be many kilometres away from their sources of clean water, which could be a forest located in a mountain area in the region. The novelty of the analysis compared to existing frameworks is to identify where changes in management and/or governance are needed in order to improve provision, or where systems already providing high levels of PG/ESS need to be maintained.
The first step in the work (review of relevant datasets and approaches available at EU level to categorise and map PG/ES) has just been finalised. We found indicators or proxies to map PG/ES relating to the supply of 16 out of the 19 beneficial outcomes identified in PEGASUS. Available indicators describe the ecosystem service itself, or the ecosystem function underpinning the service. Moreover, most of the indicators available describe the potential service – the capacity of the ecosystem to deliver a good or service, also called stocks or assets. Only in rare cases are there indicators and data available that allow the actual service (linked to the demand) to be mapped.
Many times the indicator is clear but relevant data are not available to measure it, and proxies need to be used. For example, the PG/ES “provision of habitat”, of which biodiversity is a key variable, cannot be described through one indicator only - there is no one-measure-fits-all. The lack of pan European monitoring data especially for agrobiodiversity (existing only for birds), implies the use of proxies (including pressures) in PEGASUS. Concerning management, a good number of indicators and maps are available for both agriculture and forestry (see Figure 1 for forestry), especially for agriculture where many data are regularly collected through EU wide agricultural surveys. The socio- economic descriptors for farming and forestry are sufficiently populated, though indicators are mostly available at coarse resolutions (NUTS2, NUTS0) and in this case the agricultural sector benefits from the fact that being subsidised, its economic aspects are much more closely monitored and modelled than forestry.
In the coming months we will develop an operational classification system of different types of relationships between farming/forestry management systems and PG/ES, taking into account the relevant spatial and temporal scales. Preliminary analysis will inform the case study work and the case studies will also be used to check the assumptions underpinning this classification system and refine it over the course of the project.