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Lehrstuhl für Biogeografie

Prof. Dr. Carl Beierkuhnlein

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Retzer, V*; Jurasinski, G: Detecting spatial pattern by using multi-plot similarity indices - a novel approach
Vortrag, 37. Jahrestagung der GFÖ, Marburg: 10.09.2007 - 14.09.2007


The analysis of the spatial organization of diversity is a central topic to ecology. This has been called pattern diversity by Scheiner (1992). Often similarity indices are used to describe spatial pattern. However, a focal plot has typically more than only a single neighbour. Thus pattern diversity should be addressed by calculating the similarity of one focal plot to its multiple neighbours. Four approaches to the determination of similarity among multiple plots have been previously suggested in the literature: 1) mean similarity coefficient, 2) standard deviation of the similarity coefficient, 3) additive and 4) multiplicative partitioning. These, however, suffer from serious drawbacks. Because they do not take species identity into account, similar values may result from different species pattern. This makes the explanation of the pattern difficult. Furthermore, additive and multiplicative partitioning exhibit strong edge effects which restrict applicability. Therefore, we propose a new multi-plot similarity measure to neighbours (simMPn) which considers species identity. In tests with real and simulated data multi-plot similarity to neighbours performs best in the detection of gradients and hotspots. In the light of the increasing importance of spatial issues in ecology multi-plot similarity may provide a valuable tool to investigate pattern diversity.

Scheiner S.M. (1992) Measuring pattern diversity. Ecology 73 (5):1860-1867.

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