Mapping and Assessment of Ecosystems Services under the Proposed MAES European Common Framework: Methodological Challenges and Opportunities

The EU Biodiversity Strategy for 2020 was a driving force behind spatially explicit quantifications of Ecosystem Services (ES) in Europe. In Portugal, the MAES initiative (ptMAES-Mapping and Assessment of Ecosystem and their Services) was conducted in 2014 to address Target 2 (Action 5) of the Strategy, namely mapping and assessing ecosystems, ecosystems' condition (EC), and ES. In this study covering the NUTS II Alentejo region, EC was assessed and mapped based on four indicators (soil organic matter, plant and bird diversity, and ecological value of plant communities) and five ES were assessed and mapped (soil protection, carbon sequestration, and fiber/crop/livestock production). Assessments were performed under a multi-tiered approach, ranging from spatialization of statistical data to analytical modeling, based on the most detailed land-use/land-cover cartography available. In this paper, we detail the methodological and analytical framework applied in ptMAES and present its main outcomes. Our goal is to (1) discuss the main methodological challenges encountered to inform future MAES initiatives in Portugal and other member states; and (2) further explore the outcomes of ptMAES by looking into spatial relationships between EC and ES supply. We highlight the advantages of the proposed analytical framework and identify constraints that, among others, limited the number of ES and EC indicators analyzed. We also show that MAES can provide useful insights to landscape planning at the regional scale, for instance, red-flagging areas where ES supply may be unsustainable over time.

Automated summary

The EU Biodiversity Strategy for 2020 led to spatially explicit quantifications of Ecosystem Services in Europe. In Portugal, the MAES initiative aimed to address this strategy by evaluating ecosystems and their services. The study in the Alentejo region detailed methodological and analytical frameworks and highlighted the potential of MAES for landscape planning.