Let’s Do It for Real: Making the Ecosystem Service Concept Operational in Regional Planning for Climate Change Adaptation
Articolo
Data di Pubblicazione:
2024
Abstract:
The application of ecosystem service (ES) knowledge to planning processes and decision-making can lead to more effective climate change adaptation. Despite the increased attention given to the ES concept, its degree of integration and use in spatial planning processes are still below the expectations of those who are promoting this concept. Barriers hindering its operationalisation cover a span of aspects ranging from theoretical to procedural and methodological issues. Overall, there is a general lack of guidance on how and at what point ES knowledge should be integrated into planning processes. This study aims to promote the inclusion of ES knowledge into spatial planning practices and decision-making processes to enhance climate change adaptation. A replicable GIS-based methodology is proposed. First, the potential supply of ESs that can support climate change adaptation (ESCCAs) is defined, mapped, and quantified. Then, a need for an ESCCA supply is identified, and territorial capacities to respond to the expected climate change impacts on natural and socio-economic sectors are assessed. The methodology is applied to the Friuli Venezia Giulia Autonomous Region (Italy) as an illustrative case study. The results reveal that areas with similar geomorphological characteristics tend to respond similarly. Forest ecosystems, inland wetlands and specifically salt marshes can potentially supply a greater variety of ESCCAs. In the case study area, about 62% of the supplied ESCCAs can contribute to reducing the impacts in more than 50% of the impacted sectors. The territory of the study site generally shows good preparedness for expected impacts in most of the analysed sectors; less prepared areas are characterised by agricultural ecosystems. This reading approach based on land cover analyses can thus assist in developing policies to enhance different territorial capacities, ultimately leading to better and more sustainable decision-making.
Tipologia CRIS:
1.1 Articolo su Rivista
Keywords:
science-policy interface; adaptive planning; land cover analysis; decision-support tools
Elenco autori:
Longo, Alessandra; Zardo, Linda; Maragno, Denis; Musco, Francesco; Burkhard, Benjamin
Link alla scheda completa:
Link al Full Text:
Pubblicato in: