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

Journal of Advanced Research

Sue Page¹  Saad Alamri²  Shujaul Mulk Khan³  Zeeshan Ahmad³  Mohamed Hashem⁴ 

[1] Corresponding author.;Department of Geography, University of Leicester, UK;Department of Plant Sciences, Quaid-i-Azam University Islamabad, Pakistan;King Khalid University, College of Science, Department of Biology, Abha 61413, Saudi Arabia;

关键词: Mine zones;    Mines’ indicators;    Microhabitat;    Indicator species analysis;    Canonical correspondence analysis;    Structural equation model;   

DOI  :  

来源: DOAJ

【 摘 要 】

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: Ficus carica, Isodon rugosus and Ajuga parviflora (marble indicators); Olea ferruginea, Gymnosporia royleana and Dicliptera bupleuroides (coal indicators); and Acacia nilotica, Rhazya stricta and Aristida adscensionis (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.

【 授权许可】

Unknown