ABSTRACT
The iconic Ganges River dolphin Platanista gangetica gangetica is endemic to the Indian subcontinent and has been classified as the most endangered cetacean due to sharp decline in the population size of this obligatory freshwater animal. The species is vulnerable to multiple anthropogenic activities such as habitat fragmentation caused by construction of structural barriers (dams and barrages) and dredging activities, reduced freshwater flow, huge siltation load, depletion of fish stock, use of vulnerable gears, and lack of public awareness. Geographical expansion of artisanal fishing, poaching for collection of their flesh (used as fish bait) and fat and oil (used as an ointment for joint pain and gout), injuries and mortalities due to entanglement with fishing gear are other threats for the species. In addition, they can bioaccumulate several hazardous and toxic chemical pollutants in their body tissues, which are detrimental for their sustenance. Due to the outbreak of novel coronavirus (2019—COVID) pandemic the positive and negative impacts have also been observed and discussed. The following precautionary measures should be undertaken for their conservation: ban fishing in the dolphin hotspot areas and sanctuaries;multispecies management along with law enforcement and sustainable fishing practices;dolphin-fishery interactions should be solved through fishing gear modifications (e.g., mesh size). © 2022 Elsevier Inc. All rights reserved
ABSTRACT
The purpose of the research was to investigate and identify the demographic risk factors behind the transmission of COVID-19 in Bangladesh based on spatial and statistical modeling. Number of COVID-19 confirmed cases per thousand population as the dependent variable and nine demographic explanatory variables were considered. Different spatial (i.e., Spatial Lag and Spatial Error Model) and non-spatial (Classic Model) regression techniques were employed in the research to detect the geographical relevance of potential risk factors affecting the transmission of COVID-19. Results indicate that population density was crucial for explaining the pattern of COVID-19 transmission in Bangladesh. Spatial Auto-correlation suggests that the spatial pattern of population density were significantly clustered at a confidence interval of 95%. Again, the regression analysis also shows that population density is an influential determinant for the propagation of COVID-19 in Bangladesh, with densely populated districts like Dhaka and Narayanganj also being among the worst affected areas. The findings of this research will help the government agencies and communities for effective and well-informed decision making in order to develop and implement strategies to contain the further spread of COVID-19 in Bangladesh. © 2021, Korean Spatial Information Society.