The ecosystem services are natural assets and services, which are used by humans directly or indirectly over their respective lifetimes (MEA, 2005). Several authors and organizations describe these goods of nature in different ways. Some authors use ecological concepts as the basis for categorization (Norberg, 1999), others concentrate on different human needs (Wallace, 2007), however the most common categories are based on some functional distinction (MEA, 2005; de Groot, 2006; Hein et al., 2006). Authors representing this latter group usually mention the following classification: provisioning, regulating, supporting and cultural services. The provisioning services like water, wood or timber are used directly by people. The regulating services are climate regulation, water purification and other similar processes. The cultural services are for example education, recreation potential and spiritual inspiration. The supporting services ensure the clear functioning of the three groups, for example soil formation and photosynthesis (MEA, 2005).
The methodology of valuing ecosystem services is an effective decision support tool, because this highlights the natural, social and economic values of the goods and services of the living system for decision-making and planning. Despite the availability of a wide range of valuation methods (Chen et al., 2009; Kiss et al., 2012), there are still unresolved issues (de Groot et al., 2010). Its important elements are revealing the spatial characterization and the dynamics of the landscape and ecosystem services, for which there are effective methods among the dynamically developing GIS analysis tools. This usually does not create a comprehensive inventory of all the ecosystem services, but analysis several selected services in detail, primarily in context with the potentials and land use changes (Willemen et al., 2008). One of the most promising methods of ecosystem services valuation is the assessment matrix, a great advantage of the method is that it can be aggregated at the landscape-level (Burkhard et al., 2009).
The major account of the processing and analysis of the historical maps is that allows of understanding of the past human land use, the long-term landscape changes and the dynamics of the landscape. The knowledge of the past also contributes to the exploration of the main driving forces and use them to anticipate the future changes (Swetnam et al., 2011). Modeling of future land use change is proved to be a very efficient method among many types of landscape change analysis (Pontius et al., 2001; Goldstein et al., 2004; Kline et al., 2007), and a frequent tool in climate change analysis (IPCC, 2007), land use planning (Xiang & Clarke, 2003), conservation planning (Osvaldo et al., 2000) and recently it has been increasingly used in the assessment of the ecosystem services (MEA, 2005). The evaluation of the ecosystem services and the modeling of the future land use changes have an increasing role in regional politics. The consistency between these two topics would be a very important step forward (Estoque et al., 2012).
In this study we describe an assessment framework of ecosystem services analysis in a pilot area of Southwest-Hungary called Nagyberek, used to be the largest swampy bay of Lake Balaton. The method using GIS analysis of historic maps and recent land cover dataset explores the main land use types. It concentrates also on those driving forces which are directly influenced by the land use of the area. We plan three future land use scenarios based on the main driving forces, with the help of the CLUE-S (Verburg et al., 2002), the integrated land use modeling tool. We select and assess a certain part of the ecosystem services according to the Burkhard’s study (2009), their trends, with the help of the assessment matrix.
Nagy, Gergő Gábor; Magyar, Veronika; Jombach, Sándor; Kollányi, László; and Duray, Balázs
"Assessment Matrix Based Evaluation of Ecosystem Services in Relation to Land Use Change Scenarios,"
Proceedings of the Fábos Conference on Landscape and Greenway Planning: Vol. 4
, Article 20.
Available at: https://scholarworks.umass.edu/fabos/vol4/iss1/20
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