Bicking, S.; Burkhard, B.; Kruse M.; Müller, F.: Bayesian Belief Network-based assessment of nutrient regulating ecosystem services in Northern Germany. In: PLoS ONE 14 (2019), Nr. 4. DOI: https://doi.org/10.1371/journal.pone.0216053
Zusammenfassung: | |
This study aims to assess the potential supply of the ecosystem service (ES) nutrient regulation on two spatial scales, the federal German state of Schleswig-Holstein (regional) and the Bornhöved Lakes District (local), exemplarily for the nutrient nitrogen. The methodology was developed using the ES matrix approach, which can be applied to evaluate and map ES at different geospatial units such as land use/land cover classes. A Bayesian Belief Network (BBN) was constructed in order to include additional spatial information on environmental characteristics in the assessment. The integration of additional data, which describes site-specific characteristics such as soil type and slope, resulted in shifted probability distributions for the nutrient regulation ES potential. The focal objective of the study was of methodological nature: to test the application of a BBN as an integrative modelling approach combining the information from the ES matrix with additional data sets. In the process, both study areas were assessed with a regional differentiation with regard to the predominant landscape types. For both study areas, regional differences could be detected. Furthermore, the results indicate a spatial mismatch between ES demand and supply of the nutrient regulation potential. Land management and agricultural practices seem not to be in harmony with the spatial patterns of the environmental characteristics in the study areas. The assessment on the local scale, which comprised higher resolution input data, emphasized these circumstances even more clearly. | |
Lizenzbestimmungen: | CC BY 4.0 Unported |
Publikationstyp: | Article |
Publikationsstatus: | publishedVersion |
Erstveröffentlichung: | 2019 |
Die Publikation erscheint in Sammlung(en): | Naturwissenschaftliche Fakultät |
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