A Fuzzy Logic Based Method for Modeling the Spatial Distribution of Indicators of Decomposition in a High Mountain Environment. Issue 4 (1st November 2016)

• Record Type: Journal Article
• Authors: Hellwig, Niels; Anschlag, Kerstin; Broll, Gabriele
• Is Part Of: Arctic, antarctic, and alpine research. Volume 48:Issue 4(2016)
• Page Start: 623
• Page End: 635
• Publication Date: 2016-11-01
• Subjects: Polar regions -- Periodicals; Alpine regions -- Periodicals; Alpine regions; Cold Climate; Arctic Regions; Electronic journals; Periodicals; 570.998
• DOI: 10.1657/AAAR0015-073
• Languages: English
• ISSNs: 1523-0430

Abstract

ABSTRACT: Upscaling of sample data on indicators of decomposition to the landscape scale is often necessary for extensive ecological assessments. The amount of such data is mostly scarce even with high sampling efforts. Moreover, environmental conditions are very heterogeneous in high mountain regions. Therefore, the aim was to find a suitable technique for spatial modeling under these circumstances. A method combining decision tree analysis and the construction of fuzzy membership functions is introduced for a GIS-based mapping of decomposition indicating parameters. It is compared with an approach solely based on decision trees. Within a case study in the Italian Alps the spatial distribution of humus forms, classified by the occurrence of an OH (humified residues) horizon, is examined. There appears to be a strong relationship with elevation and a minor correlation with slope exposition. The fuzzy logic-based approach proves to be suitable for modeling the spatial distribution of indicators of decomposition. Mapping fuzzy values allows for the representation of small-scale variability and uncertainty of data due to a relatively low sample size in a very heterogeneous environment.