Abstract
Plant species represent the hierarchical expression of vegetation as it is affected by different ecological, environmental factors and pollution variables. This study assesses the impact of a different hidden treasure or factors on angiosperm plants in the marble waste polluted environment. Quadrat quantitative ecological techniques were adapted for sampling of vegetation. Size of the quadrats was kept 1 × 1m, 5 × 5m and 10 × 10m for herbs, shrubs and tree species, respectively. Soil physicochemical properties were carried out using standard protocols. All the collected data were put in MS Excel for analysis in PCORD, CANOCO, STATA and SPSS software's. The degrees of relationship among variables and with abundant plants were measured using Pearson correlation and regression analysis. The structural relationship between environmental variables and abundant angiosperms was determined through Structural Equation Modeling to examine the admired dignity of diverse environmental factors. A total of one hundred two plant species belong to ninety-five genera and forty-eight families were reported from a marble waste polluted environment. Cluster Analysis via Jaccard distance measurement and ward linkage methods gave rise to three plant communities i.e. (i) Populus alba-Arundo donax-Erigeron canadensis plants community, (ii) Morus alba- Rosa webbiana- Centaurium tenuiflorum plants community and (iii) Dalbergia sissoo- Dodonaea viscosa- Panicum antidotale plants community. Among all the measured environmental variables, the dominant plants of the first plant community comprehend positive and significant relationships with soil pH, potassium and negative plus significant relationship with electrical conductivity and organic matter. The abundant plants of 2nd plant community were under the influence of higher potassium concentration and lower soil pH as compared to other communities. Third community exhibits a negative and significant relationship with soil pH in conjunction with higher electrical conductivity in the region. The aforementioned techniques could be used to find out the relationship between plant species distribution and microclimatic variables.
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