Plants predict the mineral mines - A methodological approach to use indicator plant species for the discovery of mining sites.

INTRODUCTION

There has been limited research conducted on the identifications/methodological approaches of using plant species as indicators of the presence of economically, important mineral resources.

OBJECTIVES

This study set out to answer the following questions (1) Do specific plant species and species assemblages indicate the presence of mineral deposits? and (2) if yes, then what sort of ecological, experimental, and statistical procedures could be employed to identify such indicators?

METHODS

Keeping in mind these questions, the vegetation of subtropical mineral mines sites in northern Pakistan were evaluated using Indicator Species Analysis (ISA), Canonical Correspondence Analysis (CCA) and Structural Equation Modeling (SEM).

RESULTS

A total of 105 plant species belonging to 95 genera and 43 families were recorded from the three mining regions. CA and TWCA classified all the stations and plants into three major mining zones, corresponding to the presence of marble, coal, and chromite, based on Jaccard distance and Ward's linkage methods. This comprehended the following indicator species: Ficuscarica, Isodonrugosus and Ajugaparviflora (marble indicators); Oleaferruginea, Gymnosporiaroyleana and Diclipterabupleuroides (coal indicators); and Acacianilotica, Rhazyastricta and Aristidaadscensionis (chromite indicators) based on calculated Indicator Values (IV). These indicators were reconfirmed by CCA and SEM analysis.

CONCLUSION

It was concluded that ISA is one of the best techniques for the identification/selection of plant indicator species, followed by reconfirmation via CCA and SEM analysis. In addition to establishing a robust approach to identifying plant indicator species, our results could have application in mineral prospecting and detection.