Biomagnification of Methylmercury in a Marine Plankton Ecosystem

Abstract

Methylmercury is greatly bioconcentrated and biomagnified in marine plankton ecosystems, and these communities form the basis of marine food webs. Therefore, the evaluation of the potential exposure of methylmercury to higher trophic levels, including humans, requires a better understanding of its distribution in the ocean and the factors that control its biomagnification. In this study, a coupled physical/ecological model is used to simulate the trophic transfer of monomethylmercury (MMHg) in a marine plankton ecosystem. The model includes phytoplankton, a microbial community, herbivorous zooplankton (HZ), and carnivorous zooplankton (CZ). The model captures both shorter food chains in oligotrophic regions, with small HZ feeding on small phytoplankton, and longer chains in higher nutrient conditions, with larger HZ feeding on larger phytoplankton and larger CZ feeding on larger HZ. In the model, trophic dilution occurs in the food webs that involve small zooplankton, as the grazing fluxes of small zooplankton are insufficient to accumulate more MMHg in themselves than in their prey. The model suggests that biomagnification is more prominent in large zooplankton and that the microbial community plays an important role in the trophic transfer of MMHg. Sensitivity analyses show that with increasing body size, the sensitivity of the trophic magnification ratio to grazing, mortality rates, and food assimilation efficiency (AE C ) increases, while the sensitivity to excretion rates decreases. More predation or a longer zooplankton lifespan may lead to more prominent biomagnification, especially for large species. Because lower AE C results in more predation, modeled ratios of MMHg concentrations between large plankton are doubled or even tripled when the AE C decreases from 50% to 10%. This suggests that the biomagnification of large zooplankton is particularly sensitive to food assimilation efficiency.

Methylmercury Induced Apoptosis of Human Neuroblastoma Cells Through the ROS Mediated Caspase and PARP/AIF Dependent Pathways

“…The researchers have never stopped studying the toxicity of MeHg. At present, a large number of population data and experimental studies have con rmed that MeHg can cause serious and irreversible nervous system damage (Harada, 1995;Wu et al, 2020). There are also in vitro studies showing that MeHg has a certain toxic effect on Neuro-2a, F3, C17.2, neural stem cells and other nerve cells, and can induce cell death through a variety of ways (Chang et al, 2013;Sato et al, 2020), but the mechanisms are still not very clear.…”

Assessing the spatial and temporal variability of MeHg biogeochemistry and bioaccumulation in the Mediterranean Sea with a coupled 3D model

“…The pool of dissolved gaseous mercury species (DGM, i.e., Hg 0 and DMHg) is assumed to be entirely in the dissolved phase. are parameterized as functions of particulate organic matter remineralization (Zhang et al, 2020(Zhang et al, , 2014a, which is read from the BFM model. The direct conversion of Hg II to DMHg is assumed to be negligible, due to the low rates observed in the only dataset available for this process (Lehnherr et al, 2011).…”

“…The gas-exchange flux of Hg 0 with the atmosphere (k vol {Hg w 0 -Hg atm 0 /K H ' }) is using the Nightingale's parameterization (Nightingale et al, 2000) for the rate constant k vol , (Eq. ( 9)), which depends on wind speed (u10, m/s) and on the ratio of Hg Current knowledge on dynamics and concentrations of DMHg in the ocean and in the atmosphere does not allow a detailed modelling representation (Baya et al, 2015;Coale et al, 2018;De Simone et al, 2014;Melaku Canu et al, 2015;Nerentorp Mastromonaco et al, 2017;Rosati et al, 2018;Zhang et al, 2020), and simulated variations of DMHg (Eq. 4) depend on photodegradation, production upon MMHg methylation and advective transport.…”

“…The bioaccumulation model simulates the MMHg uptake by the phytoplankton PFTs of the BFM model assuming that the uptake flux (Eq. ( 10), nmol(Hg) m -3 (w) d -1 ) decreases at high DOC concentrations, and increases proportionally to the phytoplankton Surface Area:Volume ratios, R SV_PFT (Schartup et al, 2018;Zhang et al, 2020). Furthermore, it considers the phytoplankton density (ρ =10 -12 g(w.w.) μm -3 (w.w.)), wet weight biomass (B w.w., PFT , in g(w.w.) m -3 (w)), and the water MMHg by adopting a carbon to Wet Weight conversion factors (Tab.…”

“…Here, we couple a model for Hg biogeochemistry (Canu et al, 2019;Rosati et al, 2020Rosati et al, , 2018Zhang et al, 2020) with the 3D transport biogeochemical model OGSTM-BFM (Lazzari et al, 2021(Lazzari et al, , 2010Salon et al, 2019) to investigate spatial and temporal variability of MeHg dynamics in the Mediterranean Sea. The coupled model (Fig.…”