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

Ahmad, Zeeshan; Mulk Khan, Shujaul; Page, Sue; Alamri, Saad; Hashem, Mohamed

Ahmad, Zeeshan; Mulk Khan, Shujaul; Page, Sue; Alamri, Saad; Hashem, Mohamed.

Afiliación

Ahmad Z; Department of Plant Sciences, Quaid-i-Azam University Islamabad, Pakistan.
Mulk Khan S; Department of Plant Sciences, Quaid-i-Azam University Islamabad, Pakistan. Electronic address: shujaqau@gmail.com.
Page S; Department of Geography, University of Leicester, UK.
Alamri S; King Khalid University, College of Science, Department of Biology, Abha 61413, Saudi Arabia.
Hashem M; King Khalid University, College of Science, Department of Biology, Abha 61413, Saudi Arabia; Assiut University, Faculty of Science, Botany and Microbiology Department, Assiut, 71516, Egypt.

J Adv Res ; 39: 119-133, 2022 07.

Article en En | MEDLINE | ID: mdl-35777902

Asunto(s)

Carbonato de Calcio; Minerales; Movimiento Celular; Carbón Mineral; Ligamiento Genético; Humanos

Palabras clave

Canonical correspondence analysis; Indicator species analysis; Microhabitat; Mine zones; Mines' indicators; Structural equation model

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Carbonato de Calcio / Minerales Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Adv Res Año: 2022 Tipo del documento: Article País de afiliación: Pakistán Pais de publicación: Egipto

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