Among the growing stock of research in ecosystem and landscape functions and services (de Groot et al., 2010; TEEB, 2010), their spatial determination is not fully understood and operationalized, still requiring the development of methods and tools to quantify and map different services across the landscape. To support sustainable land use decision-making the analysis of spatial heterogeneity and patterns of the diverse functions and services across a given landscape should be able to explore and identify potential spatial synergies, i.e. 'multiple win locations' or multifunctional 'hotspots' (Gimona and van der Horst, 2007). Methodologies used for identifying, assessing and mapping landscape functions and services are diverse and frequently inconsistent (Baral et al., 2012) and notwithstanding the examples from available literature, evident methodological gaps are still present. This paper presents a probabilistic approach to landscape services spatial modelling and assessment based on geostatistical simulations, providing a flexible and generally applicable tool to support mapping and decision making. Of operational value is the fact that several services can be treated and mapped simultaneously. Using spatial data, complemented with information from governmental databases or management strategies, the methodology has been adopted for ecological habitat and recreational landscape services in the case study area of Märkische Schweiz nature park in North-East Germany. It consists of i) observations of landscape services at random points within a regular reference grid; ii) indicator coding and variogram analysis; and iii) kriging of single and multiple indicators via sequential simulations; and iv) probabilistic mapping of landscape services. In addition, the spatial characteristics were assessed at a radius of 125 and 250 m to assess the effect of neighbourhood size on the spatial scale of landscape service. The method provides new insights about the relevance of spatial abundance of landscape elements or management practices related services for the multiple services composition and interrelation of a region. Its application can contribute to a more holistic picture of effects of landscape management and thus may support better policy effectiveness.
Mapping landscape services, competition and synergies. A case study using sequential geostatistical simulations in a rural landscape in Germany.
Fabrizio Ungaro;
2013
Abstract
Among the growing stock of research in ecosystem and landscape functions and services (de Groot et al., 2010; TEEB, 2010), their spatial determination is not fully understood and operationalized, still requiring the development of methods and tools to quantify and map different services across the landscape. To support sustainable land use decision-making the analysis of spatial heterogeneity and patterns of the diverse functions and services across a given landscape should be able to explore and identify potential spatial synergies, i.e. 'multiple win locations' or multifunctional 'hotspots' (Gimona and van der Horst, 2007). Methodologies used for identifying, assessing and mapping landscape functions and services are diverse and frequently inconsistent (Baral et al., 2012) and notwithstanding the examples from available literature, evident methodological gaps are still present. This paper presents a probabilistic approach to landscape services spatial modelling and assessment based on geostatistical simulations, providing a flexible and generally applicable tool to support mapping and decision making. Of operational value is the fact that several services can be treated and mapped simultaneously. Using spatial data, complemented with information from governmental databases or management strategies, the methodology has been adopted for ecological habitat and recreational landscape services in the case study area of Märkische Schweiz nature park in North-East Germany. It consists of i) observations of landscape services at random points within a regular reference grid; ii) indicator coding and variogram analysis; and iii) kriging of single and multiple indicators via sequential simulations; and iv) probabilistic mapping of landscape services. In addition, the spatial characteristics were assessed at a radius of 125 and 250 m to assess the effect of neighbourhood size on the spatial scale of landscape service. The method provides new insights about the relevance of spatial abundance of landscape elements or management practices related services for the multiple services composition and interrelation of a region. Its application can contribute to a more holistic picture of effects of landscape management and thus may support better policy effectiveness.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
