Beneath the Surface: Comparative Diversity, Abundance, and Bio-Indicative Capabilities of Nematode Community Structure in Natural and Disturbed Habitats

Abstract

This present study underscores the significance of soil nematodes as indicators of ecological health, particularly in areas affected by human activities like mining. Soil nematodes, classified into five trophic groups, play vital roles in nutrient cycling and provide insights into soil food web dynamics. Various nematode community indices, including the maturity index (MI) and trophic diversity index (TDI), are crucial for assessing soil food web diversity. Nematodes exhibit adaptability across diverse soil environments, from pristine to highly disturbed habitats, making them responsive indicators of environmental changes. Understanding nematode community structure enhances their potential as global indicators for assessing food resource availability and habitat characterization. This study compares three different zones based on anthropogenic disturbances in the coal mining region of Sonebhadra, Uttar Pradesh, representing undisturbed, moderately disturbed, and intensely disturbed sites. By analyzing nematode communities and trophic group abundance, the study assesses soil ecosystems across these zones. Human activities, especially mining, significantly impact soil nematode diversity and ecosystem health. Transition from natural forests to mining sites leads to shifts in nematode communities and species diversity, with intermediate disturbance fostering increased species diversity. Maturity index values reflect ecosystem maturity, with undisturbed and moderately disturbed zones indicating structured ecosystems, while highly disturbed zones represent degraded conditions. Faunal profiles mirror these findings, indicating shifts in decomposition pathways. This study highlights the potential of nematodes as indicators for environmental monitoring and quality assessment in coal mine areas. Further research on individual nematode species can inform biodiversity modeling and contribute to more effective ecological restoration efforts.