TY - JOUR

T1 - Bayesian Belief Network-based assessment of nutrient regulating ecosystem services in Northern Germany

AU - Bicking, Sabine

AU - Burkhard, Benjamin

AU - Kruse, Marion

AU - Müller, Felix

N1 - Funding Information: The work of M.K. was financially supported by the project SECOS (03F0666A), funded by the German Federal Ministry for Education and Research. The ESMERALDA project has received funding from the European Union Horizon 2020 research and innovation programme under Grant Agreement No 642007. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank BayesFusion, LLC for the provision of software (GeNIe 2.2; http://www.bayesfusion.com/). Besides, we want to thank Angie Faust for double-checking the English language.

PY - 2019/4/30

Y1 - 2019/4/30

N2 - 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.

AB - 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.

KW - Bayes Theorem

KW - Ecosystem

KW - Geography

KW - Germany

KW - Lakes

KW - Nitrogen/analysis

KW - Phosphorus/analysis

KW - Probability

UR - http://www.scopus.com/inward/record.url?scp=85065388662&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0216053

DO - 10.1371/journal.pone.0216053

M3 - Article

C2 - 31039186

VL - 14

JO - PLOS ONE

JF - PLOS ONE

SN - 1932-6203

IS - 4

M1 - e0216053

ER -