Integration of ecosystem services in spatial planning: A mixed methods approach

摘要

Land-use and land cover (LULC) changes are an important driver of global ecosystem change, with consequences in terms of biodiversity and the benefits humans get from nature, known as ecosystem services (ES). Spatial planning, a process dealing with the spatial expression of human activities in an integrated way, supported by instruments like Strategic Environmental Assessment, can play an important role in balancing those activities against their consequences. Although literature on ES is growing considerably, some of it covering the planning context, a coherent and integrated approach for practical application of the ES concept in spatial planning and decision-making is still needed, while knowledge gaps and challenges remain. This research aims at expanding current knowledge on the integration of ES in spatial planning. Through a mixed methods approach, firstly a profile of ES integration was drawn, based on a questionnaire survey and document analysis covering European to regional levels, using Portugal as example. Then, a set of relevant ES and drivers of change was identified through a participatory approach, with the Lisbon Metropolitan Area as case study. Subsequently, alternative scenarios of future LULC and ES changes driven by combined demographic and urban development patterns were explored. The profile revealed mismatches between ES integration as perceived by planning stakeholders and as found in planning documents, where integration (mainly implicit) needs improvement. The scenario exercise suggested that land take can be minimized through spatial planning, but effects on ES might be mixed. A conceptual framework for ES integration in spatial planning is proposed, based on the insights gained. Recommendations for further research and planning practice mainly concern broadening the range of stakeholders involved, the stages of stakeholder involvement and the scope of document analysis, as well as exploring more extreme scenario assumptions and adding ES demand to the supply analysis.