Given the realities of coal mine and coal bed methane
expansion in the (1) Identify reclamation targets using classification
analyses of pre-mine vegetation. We
review a number of existing classification methods along with existing and
original methods for finding the correct number of legitimate data clusters in
datasets. We demonstrate our analyses
using a large (> 800 site) dataset from a pre-mine steppe landscape in (2) Characterize target vegetation types. We recognize important or dominant species in
target communities to guide the creation of seed mixes. We also recognize the role of infrequent,
non-dominant species and the seral/climax character
of communities in creating realistic reclamation goals and time-frames.
(3) Model the environments of target vegetation types as a
guide for landscape engineering. We found that environmental data gathered ‘on
site' by consultants was generally much more precise than GIS layers or 10-30m DEMs. We utilized
two quantitative strategies to match vegetation types to their
environments. We used logistic
regression to express probabilities for the occurrence of specific vegetation
types given environmental responses. We also used classification and regression
tree analysis as a basis for simultaneously mapping optimal vegetation types
onto a post-mine surface. While useful,
the predictive power of both approaches were limited by the quality and types
of environmental data gathered.