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Coupling Satellite Data with Species Distribution and Connectivity Models

AutorInnen: 
Rödder, D., Nekum, S., Cord, A.F., Engler, J.O.
Erscheinungsjahr: 
2016
Vollständiger Titel: 
Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species
Autor/-innen des ZFMK: 
Org. Einordnung: 
Publiziert in: 
Environmental Management
Publikationstyp: 
Zeitschriftenaufsatz
DOI Name: 
10.1007/s00267-016-0698-y
Keywords: 
Connectivity conservation, Fragmentation thresholds, Habitat directive, Habitat fragmentation, Remote sensing
Bibliographische Angaben: 
Rödder, D., Nekum, S., Cord, A.F., Engler, J.O. (2016): Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species. - Environmental Management 58 (1): 130-143.
Abstract: 

Climate change and anthropogenic habitat fragmentation are considered major threats for global biodiversity. As a direct consequence, connectivity is increasingly disrupted in many species, which might have serious consequences that could ultimately lead to the extinction of populations. Although a large number of reserves and conservation sites are designated and protected by law, potential habitats acting as inter-population connectivity corridors are, however, mostly ignored in the common practice of environmental planning. In most cases, this is mainly caused by a lack of quantitative measures of functional connectivity available for the planning process. In this study, we highlight the use of fine-scale potential connectivity models (PCMs) derived from multispectral satellite data for the quantification of spatially explicit habitat corridors for matrix-sensitive species of conservation concern. This framework couples a species distribution model with a connectivity model in a two-step framework, where suitability maps from step 1 are transformed into maps of landscape resistance in step 2 filtered by fragmentation thresholds. We illustrate the approach using the sand lizard (Lacerta agilis L.) in the metropolitan area of Cologne, Germany, as a case study. Our model proved to be well suited to identify connected as well as completely isolated populations within the study area. Furthermore, due to its fine resolution, the PCM was also able to detect small linear structures known to be important for sand lizards’ inter-population connectivity such as railroad embankments. We discuss the applicability and possible implementation of PCMs to overcome shortcomings in the common practice of environmental impact assessments.
 

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