A GIS-based method for the reconstruction of the late eighteenth century forest vegetation in the Prignitz region (NE Germany) View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-02

AUTHORS

Monika Wulf, Hendrik Rujner

ABSTRACT

Our goal was to reconstruct the late eighteenth century forest vegetation of the Prignitz region (NE Germany) at a scale of 1:50,000. We also wanted to relate the historical forest vegetation to the actual and potential natural vegetation. For these purposes, we selected 15 woody species and transferred relevant data found in historical records from various sources together with the recent localities of (very) old individuals belonging to these woody species into ArcView GIS. Following multi-step data processing including the generation of a point density layer using a moving window with kernel estimation and derivation of vegetation units applying Boolean algebra rules together with information on site conditions, we derived 17 forest communities corresponding to the potential natural vegetation. We were able to reconstruct the historical forest vegetation for 90% of the forest area ca. 1780. Only two of the 17 forest communities covered large parts of the forested area. The oak forest with Agrostis capillaris covered about 44% of the total forest area, and alder forests on fenland made up about 37%. Oak-hornbeam forests with Stellaria holostea comprised slightly less than 6% of the forest area, while all other forest communities comprised less than 1%. The historical forest vegetation is more similar to the potential forest vegetation and quite different from the actual forest vegetation because coniferous tree species currently cover approximately two-thirds of the actual forest area. The most beneficial result of this study is the map of high-resolution historical vegetation units that may serve as the basis for various further studies, e.g., modelling long-term changes in biodiversity at the landscape scale. More... »

PAGES

153-168

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10980-010-9555-1

DOI

http://dx.doi.org/10.1007/s10980-010-9555-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1012864092


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