Besides allowing maps of a taxon’s distribution to be created, Edaphobase offers basic descriptive analyses of its data through the “EdaphoStat” function accessible from the “Tools” Menu. Please allow pop-ups in your browser to access this tool.
EdaphoStat is a pilot project for automated assessment tools of data-warehouse data and represents work in progress. The main feature of this tool currently concentrates on the species level, allowing autecological preferences of individual species to be evaluated. The tool examines the data basis for a chosen species and then, from this, calculates ecological niche width and optima for user-selected habitat parameters. It offers:
Bar charts – of a species’ occurrence frequency along a habitat gradient (both categorical variables such as habitat or soil types as well as numerical variables such as soil parameters are possible).
Regressions – of a species’ occurrence (either presence or abundance data) along a quantitative habitat parameter, so-called “response curves”. The type of regression can be chosen from a list and more are being planned.
Niche-space diagrams – (2-D scatterplots) of one or two species’ occurrence(s) in relation to two quantitative habitat parameters. Contour (density) lines can be added for enhanced visualisation.
A further analysis function in this tool is EdaphoClass, which predicts the site-specific species composition of soil organism communities. After selecting a set of habitat conditions (such as habitat type and soil pH or organic material), this function searches the database for all species (of the selected taxonomic major group) found under these conditions and delivers a histogram of the species ordered according to their occurrence frequency (based on all sites with these conditions where the major group was recorded).
Details on the use of this data-assessment tool can be found under “Help” in the EdaphoStat window.
This pilot project for database assessment tools was developed by the Institute for Environmental Biology and Chemodynamics of the RWTH Aachen University, in particular by:
Dipl. Gyml. Jonas Hausen (ⴕ) and Dr. Björn Scholz-Starke
and lead by
Dr. Martina Roß-Nickoll and Dr. Richard Ottermanns.