Multivariate statistical analysis of bioavailability of heavy metals and mineral characterization in selected species of coastal flora

Abstract

Abstract This study presents a thorough investigation into the concentration of heavy metals and mineral composition within four distinct coastal flora species: Cyperus conglomeratus, Halopyrum mucronatum, Sericostem pauciflorum, and Salvadora persica. Employing rigorous statistical methodologies such as Pearson coefficient correlation, principal component analysis (PCA), analysis of variance (ANOVA), and interclass correlation (ICC), we aimed to elucidate the bioavailability of heavy metals, minerals, and relevant physical characteristics. The analysis focused on essential elements including copper (Cu), iron (Fe), manganese (Mn), zinc (Zn), magnesium (Mg2+), calcium (Ca2+), sodium (Na+), potassium (K+), and chloride (Cl–), all of which are known to play pivotal roles in the ecological dynamics of coastal ecosystems. Through PCA, we discerned distinctive patterns within PC1 to PC4, collectively explaining an impressive 99.65% of the variance observed in heavy metal composition across the studied flora species. These results underscore the profound influence of environmental factors on the mineral composition of coastal flora, offering critical insights into the ecological processes shaping these vital ecosystems. Furthermore, significant correlations among mineral contents in H. mucronatum; K+ with content of Na+ (r = 0.989) and Mg2+ (r = 0.984); as revealed by ICC analyses, contributed to a nuanced understanding of variations in electrical conductivity (EC), pH levels, and ash content among the diverse coastal flora species. By shedding light on heavy metal and mineral dynamics in coastal flora, this study not only advances our scientific understanding but also provides a foundation for the development of targeted environmental monitoring and management strategies aimed at promoting the ecological sustainability and resilience of coastal ecosystems in the face of ongoing environmental challenges.

Keywords

• Heavy metals
• Mineral composition
• Coastal flora
• Principal component analysis (PCA)
• Bioavailability
• Environmental monitoring