Md. Mofizul Hoque, Subodh Chandra Pal, Sudipto Mandal, Aznarul Islam
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引用次数: 0
Abstract
Mollusc habitat suitability (MHS) analysis is significant nowadays due to increasing anthropogenic interventions both structural (dam, barrage, weir, bridge) and non-structural (pollution and environmental damage), which lead to the degradation of their population and habitat. The present work has assessed the MHS using the habitat suitability index (HSI) model with the help of habitat water quality (CWQ) and habitat substrate-suspended solids (CSS) indices in the spatiotemporal dimension. This study exhibits that the CWQ, CSS and HSI are comparatively worse in the monsoon than in the other seasons due to higher velocity and water temperature, and they are in better condition in 2022–23 than in 2014–15 in the study area. Besides, HSI reveals that the MHS lies under good to excellent categories in pre-monsoon and excellent in post-monsoon seasons in the Damodar River and is high at station 5 in spatial dynamics due to favourable conditions (lower velocity and temperature) that exist in these seasons and station. The ANOVA indicates a significant spatiotemporal variation in the mollusc habitat quality variables in the study area. The hierarchical cluster analysis (HCA) portrays a complex clustering; however, locations Ids. 6, 7, 8 and 9 are found to be clustered, implying that more or less similar mollusc habitat quality lies in these locations. The principal component analysis (PCA) infers that all the studied variables are major factors playing a significant role in controlling mollusc habitat suitability. This study will be highly useful for maintaining and conserving aquatic biodiversity and the ecological services provided by rivers. It is vital to mitigate pollution and restore rivers.
期刊介绍:
Environmental Monitoring and Assessment emphasizes technical developments and data arising from environmental monitoring and assessment, the use of scientific principles in the design of monitoring systems at the local, regional and global scales, and the use of monitoring data in assessing the consequences of natural resource management actions and pollution risks to man and the environment.