Integrating ecosystem service bundles and socio-environmental conditions - A national scale analysis from Germany

被引:135
作者
Dittrich, Andreas [1 ]
Seppelt, Ralf [1 ,2 ]
Vaclavik, Tomas [1 ,3 ]
Cord, Anna F. [1 ]
机构
[1] UFZ Helmholtz Ctr Environm Res, Dept Computat Landscape Ecol, D-04318 Leipzig, Germany
[2] Martin Luther Univ Halle Wittenberg, Inst Geosci & Geog, D-06099 Halle, Saale, Germany
[3] Palacky Univ Olomouc, Dept Ecol & Environm Sci, Fac Sci, Olomouc 78371, Czech Republic
关键词
Hot spots; Landscape stratification; Self-organizing maps; Spatial analysis; Spatial clustering; Trade-offs; INTENSIFICATION; DEMAND;
D O I
10.1016/j.ecoser.2017.08.007
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Understanding the relationship and spatial distribution of multiple ecosystem services (ES) in the context of underlying socio-environmental conditions is an essential element of national ecosystem assessments. Here, we use Germany as an example to present a reproducible blueprint approach for mapping and analysing ecosystem service bundles (ESB) and associated socio-environmental gradients. We synthesized spatial indicators of eleven provisioning, regulating and cultural ES in Germany and used the method of self-organizing maps (SOM) to define and map ESBs. Likewise, we collated data from 18 covariates to delineate socio-environmental clusters (SEC). Finally, we used an overlap analysis to characterise the relationship between the spatial configuration of ESBs and co-occurring SECs. We identified and mapped eight types of ESBs that were characterized to varying degrees by provisioning, cultural and regulating/maintenance services. While ESBs dominated by provisioning ES were linked to regions with distinct environmental characteristics, cultural ESBs were associated with areas where environmental and socio-economic gradients had similar importance. Furthermore, spatial stratification of ESBs indicated hot spots where more detailed analysis is needed within national assessments. Our approach can serve as a blueprint for ESB analysis that can be reproduced in other geographical and environmental settings. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:273 / 282
页数:10
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