Incorporating trait-based functional diversity metrics into conventional EIAs enables practitioners to better predict habitat fragmentation risks, and design targeted mitigation strategies.
Environmental Impact Assessments (EIAs) for hydroelectric projects traditionally rely on species richness, often failing to capture shifts in ecosystem functioning and leaving communities uncertain about ecological risks. To demonstrate how IA practice can achieve real effectiveness rather than “more of the same,” this study presents a case study from the Madi River, Nepal, experiencing rapid hydroelectric expansion, where functional diversity metrics were integrated into baseline assessment and monitoring. Fish were sampled across 11 sampling sites in four seasons. A total of 26 fish species were recorded. Only 14 species with adequate abundance (greater than five individuals) were included in the functional analysis. Six functional traits related to feeding and locomotion were used to calculate five functional diversity indices. Results showed distinct seasonal variation. FRic picked in summer (0.71), likely driven by increased habitat heterogeneity and resource availability during high discharge, and it became lowest in autumn (0.01). In contrast, FEve was found to be highest in autumn (0.89), indicating a more even distribution of species in trait space. This study provides the first comprehensive seasonal assessment of functional diversity in the Himalayan River. Incorporating trait-based functional diversity metrics into conventional EIAs enables practitioners to better predict habitat fragmentation risks, design targeted mitigation strategies such as species-specific fishways and environmental flows, and provide transparent evidence to address community
Indira Sharma Bhandari is an assistant professor in the Department of Zoology at Tri-chandra Multiple Campus, Kathmandu.