The approach first seeks to summarize the overall variability for
each data table by identifying a subset of variables within each
table that best explain patterns in the data. This information is
then combined with practical knowledge of laboratory tests and
ecosystem functioning to determine indicators that are sensitive
and easy to measure by local land managers and technicians.