The frequent rainfall during the low tide would erode and transport the surface sediment and microphytobenthos (MPB) in the intertidal flat. In order to quantify the rainfall effects on the erodibility of sediment and MPB at the salt marsh and mixed flat, a series of erosion experiments have been conducted with a Gust erosion microcosm system. Surface sediments were sampled for analyzing algal biomass (Chl-a) and primary production (PP) during three typical weather (without rain, rain, and post-rain) conditions. The results of erosion experiment, in both salt marsh and mixed flat, showed that the sediment erodibility under rain condition was higher than that under without rain condition, with increased total eroded mass by 37-86%. It indicated that the rainfall effects caused to significantly disturb the surface sediment. After the rainfall events, the removal of highly-erodible sediments resulted in the reduction in eroded mass. The MPB erodibility under rain condition was lower than that under without rain condition, with decreased total eroded Chl-a by 29%. At the mixed flat, the rainfall effects caused to significantly decrease biological activities of MPB (biomass and PP) associated with surface sediment. The surface Chl-a concentration under post-rain condition decreased by 73%, compared to that under rain condition. At the salt marsh, in contrast, the rainfall effects were barely shown when the biological activities of MPB were rather stable. This implied that the eroded MPB induced by rainfall was retained within the marsh system due to vegetation canopy.
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http://dx.doi.org/10.1016/j.envpol.2018.06.079 | DOI Listing |
Environ Sci Pollut Res Int
January 2025
ICAR-Central Inland Fisheries Research Institute, Barrackpore, Kolkata, 700120, West Bengal, India.
Nitrate, a highly reactive form of inorganic nitrogen, is commonly found in aquatic environments. Understanding the dynamics of nitrate-N concentration in rivers and its interactions with other water-quality parameters is crucial for effective freshwater ecosystem management. This study uses advanced machine learning models to analyse water quality parameters and predict nitrate-N concentrations in the lower stretch of the Ganga River from the observations of six annual periods (2017 to 2022).
View Article and Find Full Text PDFEvolution
January 2025
Centre for Ecological Sciences, Indian Institute of Science, Bengaluru, 560012, India.
Under current climate change patterns, rapidly changing environments can impose strong selection on traits. Costly traits that require heavy investment and strongly affect fitness may be particularly vulnerable to such changes. Despite organisms experiencing dynamic environments, our knowledge of costly trait response is limited as longitudinal studies across generations are rare.
View Article and Find Full Text PDFWater Sci Technol
January 2025
China Construction Fifth Engineering Division Co., Ltd, Changsha, Hunan 410004, China.
Road runoff underwent treatment using a filter filled with sludge from drinking water treatment plants to assess its capacity for removing dissolved organic matter (DOM). This evaluation utilized resin fractionation, gel permeation chromatography, three-dimensional excitation-emission matrix fluorescence spectroscopy, and UV-Visible spectroscopy. The filter demonstrated enhanced efficiency in removing dissolved organic carbon, achieving removal rates between 70 and 80%.
View Article and Find Full Text PDFNature
January 2025
School of Life Sciences, Hebei University, Baoding, China.
Extreme droughts generally decrease productivity in grassland ecosystems with negative consequences for nature's contribution to people. The extent to which this negative effect varies among grassland types and over time in response to multi-year extreme drought remains unclear. Here, using a coordinated distributed experiment that simulated four years of growing-season drought (around 66% rainfall reduction), we compared drought sensitivity within and among six representative grasslands spanning broad precipitation gradients in each of Eurasia and North America-two of the Northern Hemisphere's largest grass-dominated regions.
View Article and Find Full Text PDFSci Rep
January 2025
Centre for Earth, Ocean and Atmospheric Sciences, School of Physics, University of Hyderabad, Hyderabad, India.
We identified a set of bias-corrected and downscaled Coupled Model Intercomparison Project 6 (CMIP6) models capable of accurately simulating the observed mean Indian summer monsoon rainfall, extreme rain events (EREs) and their respective interannual variability. The future changes in EREs projected by these models for four climate change scenarios-Shared Socioeconomic Pathways (SSPs), 1-2.6, 2-4.
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