Measuring Multi-plot similarity with presence-absence data

Autor: Jurasinski, G. Beierkuhnlein, C., Jentsch, A., Rettenmaier, N., Retzer, V.
In:

Ecology

Jahr: 2007

Einordung:
Institut: Professur Landschaftsökologie und Standortkunde

Abstract:
The description and measurement of pattern in ecological systems is fundamental to ecology. Pattern diversity is an important level of spatial diversity and a possible way of measuring it is to calculate the similarity between a focal plot and its neighbors. Four measures have been suggested previously in the literature to address similarity between multiple plots: 1) the mean similarity coefficient, 2) the 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, different species patterns may result in the same value of the coefficient, making the explanation of the pattern difficult. Furthermore, additive and multiplicative partitioning exhibit strong edge effects, which restrict applicability. Thus, we propose a new multi-plot similarity measure (simMPn), which allows for the consideration of species identity on all compared plots. The principle is presented using a real data set from a Tundra ecosystem in Northern Sweden. In tests with simulated data, multi-plot similarity to neighbors performs best in the detection of gradients and hotspots. As investigations of pattern diversity rise in importance, multi-plot similarity may provide a valuable tool for investigating spatial pattern.

Ansprechpartner

Zur Publikation: Mitarbeiter, Projekte
Weitere Publikationen im Forschungsteilschwerpunkt