Using decision trees to predict benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea.
In this article a concept is described in order to predict and map the occurrence of benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea. The approach consists of two work steps: (1) geostatistical analysis of abiotic measurement data and (2) calculation of benthic provinces by means of Classification and Regression Trees (CART) and GIS-techniques. From bottom water measurements on salinity, temperature, silicate and nutrients as well as from punctual data on grain size ranges (0-20, 20-63, 63-2,000 mu) raster maps were calculated by use of geostatistical methods. At first the autocorrelation structure was examined and modelled with help of variogram analysis. The resulting variogram models were then used to calculate raster maps by applying ordinary kriging procedures. After intersecting these raster maps with punctual data on eight benthic communities a decision tree was derived to predict the occurrence of these communities within the study area. Since such a CART tree corresponds to a hierarchically ordered set of decision rules it was applied to the geostatistically estimated raster data to predict benthic habitats within and near the EEZ.
Landscape Ecology, Institute for Environmental Science, University of Vechta, Vechta, Germany. rpesch@iuw.uni-vechta.de
Roland
R
Pesch
Hendrik
H
Pehlke
Kerstin
K
Jerosch
Winfried
W
Schröder
Michael
M
Schlüter
D000818:Animals; D003663:Decision Trees; D017753:Ecosystem; D040362:Geographic Information Systems; D019015:Geologic Sediments; D005858:Germany; D008386:Marine Biology; D009659:North Sea; D012621:Seasons; D012623:Seawater