Model data for benthic oxygen flux on the East China Sea shelf

The pelagic component (BYESbio24), which was based on a physical-biogeochemical ROMS-CoSiNE model customized for Bohai Sea, Yellow Sea and East China Sea (Zhou et al., 2017; Zhou et al., 2020), was coupled with the benthic component (TOCMAIN; Zhang & Wirtz, 2017; Zhang et al., 2021) to quantify oxygen flux across the sediment-water interface on the East China Sea shelf. Sediment oxygen consumption (SOC) is decomposed into three components: porewater advective flux, molecular diffusive flux and bioturbation diffusive flux. Advective flux is caused by porewater flows in permeable sediments, while diffusive flux is induced by molecular movements and bioturbation in both permeable and impermeable sediments. The uploaded model outputs are in matrix format that is readable by MATLAB. The data are confined within [122 - 127ºE] and [27 - 32ºE]. The mesh grids in terms of longitude and latitude can be found in variables ‘xgrid’ and ‘ygrid’, respectively. Daily-averaged gridded data are presented spanning from 2009 to 2014. Macrobenthos biomass is stored in the variable ‘gbiomass’ in units of gC/m2. Bioturbation coefficient is stored in the variable ‘gbioturb’ in units of cm2/day. Molecular diffusive benthic oxygen flux is stored in the variable ‘gmoldiff’ in units of mmol/m2/day. Bioturbation diffusive benthic oxygen flux is stored in the variable ‘gbiodiff’ in units of mmol/m2/day. Porewater advective benthic oxygen flux is stored in the variable ‘gporeadv’ in units of mmol/m2/day. Total benthic oxygen flux, or the SOC, is stored in the variable ‘gSOC’ in units of mmol/m2/day. Water oxygen consumption (WOC) below the pycnocline is stored in the variable ‘gWOC’ in units of mmol/m2/day. Contribution of SOC to the total local oxygen consumption (SOC + WOC) is stored in the variable ‘gSOCpercent’. References:Zhang, W., & Wirtz, K. (2017). Mutual Dependence Between Sedimentary Organic Carbon and Infaunal Macrobenthos Resolved by Mechanistic Modeling. Journal of Geophysical Research: Biogeosciences, 122(10), 2509-2526. doi: 10.1002/2017JG003909Zhang, W., Neumann, A., Daewel, U., Wirtz, K., van Beusekom, J. E. E., Eisele, A., . . . Schrum, C. (2021). Quantifying importance of macrobenthos for benthic-pelagic coupling in a temperate coastal shelf sea. Journal of Geophysical Research: Oceans, 126, e2020JC016995. doi: 10.1029/2020JC016995.Zhou, F., Chai, F., Huang, D., Xue, H., Chen, J., Xiu, P., . . . Wang, K. (2017). Investigation of hypoxia off the Changjiang Estuary using a coupled model of ROMS-CoSiNE. Progress in Oceanography, 159, 237-254. doi: 10.1016/j.pocean.2017.10.008Zhou, F., Chai, F., Huang, D., Wells, M., Ma, X., Meng, Q., . . . Li, H. (2020). Coupling and Decoupling of High Biomass Phytoplankton Production and Hypoxia in a Highly Dynamic Coastal System: The Changjiang (Yangtze River) Estuary. Frontiers in Marine Science, 7, 259. doi: 10.3389/fmars.2020.00259

本数据集包含基于物理-生物地球化学模型ROMS-CoSiNE（Zhou et al., 2017; Zhou et al., 2020）针对渤海、黄海和东海（Zhou et al., 2017; Zhou et al., 2020）进行定制开发的浮游组分（BYESbio24），并与底栖组分（TOCMAIN；Zhang & Wirtz, 2017; Zhang et al., 2021）耦合，以量化东海大陆架上沉积物-水界面的氧气通量。沉积物氧气消耗（SOC）分解为三个组成部分：孔隙水对流通量、分子扩散通量和生物扰动扩散通量。对流通量由渗透性沉积物中的孔隙水流引起，而扩散通量则由分子运动和生物扰动在渗透性和非渗透性沉积物中引起。上传的模型输出以矩阵格式呈现，可由MATLAB读取。数据范围限定在[122 - 127ºE]和[27 - 32ºE]。经纬度网格数据分别存储在变量‘xgrid’和‘ygrid’中。从2009年至2014年的每日平均网格数据予以展示。大型底栖生物量存储在变量‘gbiomass’中，单位为gC/m²。生物扰动系数存储在变量‘gbioturb’中，单位为cm²/day。分子扩散底栖氧气通量存储在变量‘gmoldiff’中，单位为mmol/m²/day。生物扰动扩散底栖氧气通量存储在变量‘gbiodiff’中，单位为mmol/m²/day。孔隙水对流底栖氧气通量存储在变量‘gporeadv’中，单位为mmol/m²/day。总底栖氧气通量，或SOC，存储在变量‘gSOC’中，单位为mmol/m²/day。水氧气消耗（WOC）在跃层以下的贡献存储在变量‘gWOC’中，单位为mmol/m²/day。SOC对当地总氧气消耗（SOC + WOC）的贡献存储在变量‘gSOCpercent’中。参考文献：Zhang, W., & Wirtz, K. (2017). Mutual Dependence Between Sedimentary Organic Carbon and Infaunal Macrobenthos Resolved by Mechanistic Modeling. Journal of Geophysical Research: Biogeosciences, 122(10), 2509-2526. doi: 10.1002/2017JG003909Zhang, W., Neumann, A., Daewel, U., Wirtz, K., van Beusekom, J. E. E., Eisele, A., . . . Schrum, C. (2021). Quantifying importance of macrobenthos for benthic-pelagic coupling in a temperate coastal shelf sea. Journal of Geophysical Research: Oceans, 126, e2020JC016995. doi: 10.1029/2020JC016995.Zhou, F., Chai, F., Huang, D., Xue, H., Chen, J., Xiu, P., . . . Wang, K. (2017). Investigation of hypoxia off the Changjiang Estuary using a coupled model of ROMS-CoSiNE. Progress in Oceanography, 159, 237-254. doi: 10.1016/j.pocean.2017.10.008Zhou, F., Chai, F., Huang, D., Wells, M., Ma, X., Meng, Q., . . . Li, H. (2020). Coupling and Decoupling of High Biomass Phytoplankton Production and Hypoxia in a Highly Dynamic Coastal System: The Changjiang (Yangtze River) Estuary. Frontiers in Marine Science, 7, 259. doi: 10.3389/fmars.2020.00259