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 a...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-07-01
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| Series: | Journal of Advanced Research |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090123221002010 |
| _version_ | 1818545981014147072 |
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| author | Zeeshan Ahmad Shujaul Mulk Khan Sue Page Saad Alamri Mohamed Hashem |
| author_facet | Zeeshan Ahmad Shujaul Mulk Khan Sue Page Saad Alamri Mohamed Hashem |
| author_sort | Zeeshan Ahmad |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-12T07:47:02Z |
| format | Article |
| id | doaj.art-cc09885fe6864310afb8bb4318ac6775 |
| institution | Directory Open Access Journal |
| issn | 2090-1232 |
| language | English |
| last_indexed | 2024-12-12T07:47:02Z |
| publishDate | 2022-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Advanced Research |
| spelling | doaj.art-cc09885fe6864310afb8bb4318ac67752022-12-22T00:32:33ZengElsevierJournal of Advanced Research2090-12322022-07-0139119133Plants predict the mineral mines – A methodological approach to use indicator plant species for the discovery of mining sitesZeeshan Ahmad0Shujaul Mulk Khan1Sue Page2Saad Alamri3Mohamed Hashem4Department of Plant Sciences, Quaid-i-Azam University Islamabad, PakistanDepartment of Plant Sciences, Quaid-i-Azam University Islamabad, Pakistan; Corresponding author.Department of Geography, University of Leicester, UKKing Khalid University, College of Science, Department of Biology, Abha 61413, Saudi ArabiaKing Khalid University, College of Science, Department of Biology, Abha 61413, Saudi Arabia; Assiut University, Faculty of Science, Botany and Microbiology Department, Assiut, 71516, EgyptIntroduction: 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.http://www.sciencedirect.com/science/article/pii/S2090123221002010Mine zonesMines’ indicatorsMicrohabitatIndicator species analysisCanonical correspondence analysisStructural equation model |
| spellingShingle | Zeeshan Ahmad Shujaul Mulk Khan Sue Page Saad Alamri Mohamed Hashem Plants predict the mineral mines – A methodological approach to use indicator plant species for the discovery of mining sites Journal of Advanced Research Mine zones Mines’ indicators Microhabitat Indicator species analysis Canonical correspondence analysis Structural equation model |
| title | Plants predict the mineral mines – A methodological approach to use indicator plant species for the discovery of mining sites |
| title_full | Plants predict the mineral mines – A methodological approach to use indicator plant species for the discovery of mining sites |
| title_fullStr | Plants predict the mineral mines – A methodological approach to use indicator plant species for the discovery of mining sites |
| title_full_unstemmed | Plants predict the mineral mines – A methodological approach to use indicator plant species for the discovery of mining sites |
| title_short | Plants predict the mineral mines – A methodological approach to use indicator plant species for the discovery of mining sites |
| title_sort | plants predict the mineral mines a methodological approach to use indicator plant species for the discovery of mining sites |
| topic | Mine zones Mines’ indicators Microhabitat Indicator species analysis Canonical correspondence analysis Structural equation model |
| url | http://www.sciencedirect.com/science/article/pii/S2090123221002010 |
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