Analysis of blood cell can reveal a measurable amount of physiological changes in fish more rapidly than any physiological assessment parameters (Rowan, 2007). It can also respond to changes in other tissues due to exposure of environmental stressors (i.e., temperature, salinity, overcrowding, and water quality) (Ruas et al., 2008). Therefore, examining blood cells has been considered a valuable approach for analyzing the health status of fish and enhancing our understanding of the relationship of blood characteristics with the habitat and adaptability of a species to an environment (Fazio et al., 2012; Shahjahan et al., 2018; De et al., 2019; Islam et al., 2019). Thus, the use of blood indicators in fisheries research is growing rapidly as it is very important in toxicological research, environmental monitoring and predicting of fish health conditions (Barcellos et al., 2004).

The global concern over trace and heavy metal contamination in aquatic environments necessitates the development of effective remediation strategies. Using aquatic plants for heavy metal removal is a relatively economical and sustainable technology worldwide. This study involved collecting sediment and aquatic plant samples (Acanthus ilicifolius, Typha elephantina, and Cynodon dactylon) from a highly urbanized estuary to analyze metal concentrations in sediment, assess ecological risks, and explore the phytoremediation potential. Trace and heavy metals were detected using Energy Dispersive X-ray Fluorescence Spectroscopy (EDXRF). The sediment metal concentrations were found in decreasing order of Fe, Ti, Mn, Rb, Zr, Zn, Sr, Cu, Co, and As. Fe, Sr, and As concentrations were below certified values, whereas Cu, Zn, and Rb exceeded them. Cumulatively, the pollution load index (PLI) values were close to 1 (0.845), indicating that the study area is likely experiencing metal pollution. The Contamination Factor (CF) values, ranging from 1 to 3, indicated a moderate degree of sediment pollution for Ti, Mn, Cu, Zn, and Rb. The Enrichment Factor (EF) values similarly showed moderate enrichment for these metals, with Cu exhibiting the highest degree of enrichment. Ecological risk assessment highlighted the only metal, Cu, as posing the greatest risk among the studied metals. In terms of phytoremediation potential, the bioconcentration factor (BCF) followed the decreasing order of C. dactylon > A. ilicifolius > T. elephantina for most metals, with low BCF values (<1) indicating low accumulator potential. However, the translocation factor (TF) values for Zn (1.464) and Rb (1.299) in A. ilicifolius species were greater than 1, indicating low accumulation potential but hyper-metabolizing capabilities, allowing the plant to accumulate metals in its aerial parts, making it effective for phytostabilization.

Fisheries and Aquatic Sciences

Purpose: This study aimed to investigate the presence, morpho-polymer characteristics, and potential ecological impacts of microplastics (MPs) in sediment samples from two popular tourist beaches along the northern Bay of Bengal. MP contamination is a rising issue in Bangladesh coastal waters, given its dense population, extensive plastic manufacturing, and a lack of waste processing facilities. Materials and methods: Sediment samples were collected from two tourist beaches. Microplastics were identified, quantified, and categorized by type, size, shape, and color. Statistical analyses were performed to compare microplastic abundance between the two sites. Polymer composition was analyzed using Fourier-transform infrared spectroscopy (FTIR). Multivariate analyses were used to identify potential sources of contamination. Results and discussion: Microplastic abundance ranged from 55.83 ± 10.10 to 116.67 ± 11.27 items kg⁻¹ at Patenga beach and 60.00 ± 6.61 to 135.83 ± 12.58 items kg⁻¹ at Parki beach. Fibers dominated Patenga beach (68.71%), while foam was prevalent at Parki beach (48.97%). Most microplastics were < 0.5 mm, filamentous, and transparent (Patenga) or white (Parki). Polyethylene (33.33%) was the most common polymer. Morpho-polymer characteristics and statistical analyses indicated the sources of MPs were linked to tourism, industrial waste, river discharge, and fishing activities. Conclusions: This study revealed moderate microplastic pollution at the study beaches, offering baseline data for the northeastern Bay of Bengal. The findings highlighted that targeted waste management policies are urgently needed to reduce coastal microplastic contamination.

The health of subtropical transboundary coastal rivers is closely linked to phytoplankton diversity, seasonal fluctuations, and community structure. This study presents the first comprehensive multivariate assessment of phytoplankton diversity and environmental drivers in the Dakatia River. Canonical Correspondence Analysis (CCA), Analysis of Similarity (ANOSIM), and Similarity Percentage (SIMPER) were applied across eight geo‐referenced stations under varying anthropogenic pressures to establish a baseline data for this cage‐culture–intensive river system. The analysis revealed distinct spatial and seasonal variations in phytoplankton diversity and taxonomic composition, highlighting shifts in community assemblages and the influence of physicochemical factors on these dynamics. A total of 37 genera were identified across six major classes: Bacillariophyceae (36.50%), Chlorophyceae (25.91%), Cyanophyceae (17.00%), Euglenophyceae (13.20%), Ulvophyceae (5.06%), and Zygnematophyceae (2.31%). Phytoplankton abundance was highest in winter (16,958.33 ± 6418.75 cells L ⁻¹ ), followed by the monsoon (14,572.92 ± 2982.90 cells L ⁻¹ ) and summer (13,739.60 ± 1857.76 cells L ⁻¹ ). The Shannon–Wiener diversity index, species evenness, and species richness exhibited seasonal fluctuations, ranging from 2.14 ± 0.22 to 2.47 ± 0.15, 0.65 ± 0.07 to 0.75 ± 0.07, and 2.67 ± 0.55 to 4.29 ± 0.38, respectively, reflecting a moderate level of phytoplankton diversity in a dynamic and complex river ecosystem. Cluster analysis delineated five distinct phytoplankton communities at a 50% similarity threshold. ANOSIM results indicated significant seasonal dissimilarity ( p < 0.001), while no significant spatial dissimilarity ( p > 0.05) was observed. SIMPER analysis identified Melosira sp. as the primary contributor to interseasonal dissimilarities, followed by Oscillatoria sp. and Gomphosphaeria sp. Pearson's correlation and CCA highlighted ammonia, temperature, salinity, nitrate, and phosphate as key environmental drivers shaping phytoplankton abundance, diversity, and community composition. These findings have provided critical insights for ecosystem management, biodiversity conservation, and sustainable water resource governance.

Objective: This study examined the composition, diversity, and assemblage of zooplankton in relation to environmental factors in the coastal Dakatia River, Bangladesh, across wet and dry seasons. Methods: Zooplankton samples were collected seasonally (monsoon and winter) from each station, alongside measurements of environmental parameters. Population density, diversity indices, assemblage patterns, and environmental drivers of the zooplankton community were analyzed. Results: A total of 25 zooplankton genera were recorded, dominated by Rotifera (36%), followed by Copepoda (26.49%), Cladocera (21.25%), and crustacean nauplii (16.26%). Zooplankton density varied significantly ( p < 0.05) between the seasons, with the highest mean (144.88 ± 22.94 ind./L) during the winter (dry) and the lowest (120.25 ± 14.04 ind./L) in the monsoon (wet) season. Diversity indices indicated moderate diversity, ecological stability, habitat suitability, and generally low dominance of taxa. Cluster analysis delineated five and four major assemblage clusters during monsoon and winter, respectively, at 70% similarity. Analysis of similarity confirmed significant ( p < 0.05) spatial and temporal variation among the stations and between the seasons, while similarity percentage analysis identified Keratella sp., Brachionus sp., Bosminopsis sp., crustacean nauplii, Cyclops sp., and Lecane sp. as the most influential contributors to community dissimilarity. Environmental parameters varied significantly across seasons ( p < 0.05). Among them, pH exerted the greatest effect during the monsoon, while canonical correspondence analysis further revealed that pH in the monsoon and nitrate in the winter were the primary drivers structuring zooplankton assemblages. Conclusion: These findings reveal moderate zooplankton diversity and community stability, providing key indicators of ecological integrity and productivity in tropical river ecosystems.