Younjoo J. Lee

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models.

Abstract We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll‐a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed‐layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite‐derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low‐productivity seasons as well as in sea ice‐covered/deep‐water regions. Depth‐resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption‐based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll‐a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic‐relevant parameters.

β1 Integrin Is an Adhesion Protein for Sperm Binding to Eggs

We investigated the role of beta(1) integrin in mammalian fertilization and the mode of inhibition of fertilinbeta-derived polymers. We determined that polymers displaying the Glu-Cys-Asp peptide from the fertilinbeta disintegrin domain mediate inhibition of mammalian fertilization through a beta(1) integrin receptor on the egg surface. Inhibition of fertilization is a consequence of competition with sperm binding to the cell surface, not activation of an egg-signaling pathway. The presence of the beta(1) integrin on the egg surface increases the rate of sperm attachment but does not alter the total number of sperm that can attach or fuse to the egg. We conclude that the presence of beta(1) integrin enhances the initial adhesion of sperm to the egg plasma membrane and that subsequent attachment and fusion are mediated by additional egg and sperm proteins present in the beta(1) integrin complex. Therefore, the mechanisms by which sperm fertilize wild-type and beta(1) knockout eggs are different.

Role of Late Winter–Spring Wind Influencing Summer Hypoxia in Chesapeake Bay

We examined the processes influencing summer hypoxia in the mainstem portion of Chesapeake Bay. The analysis was based on the Chesapeake Bay Monitoring Program data collected between 1985 and 2007. Self-organizing map (SOM) analysis indicates that bottom water dissolved oxygen (DO) starts to be depleted in the upper mesohaline area during late spring, and hypoxia expands down-estuary by early summer. The seasonal hypoxia in the bay appears to be related to multiple variables, (e.g., river discharge, nutrient loading, stratification, phytoplankton biomass, and wind condition), but most of them are intercorrelated. The winter–spring Susquehanna River flow contributes to not only spring–summer buoyancy effects on estuarine circulation dynamics but also nutrient loading from the land-promoting phytoplankton growth. In addition, we found that summer hypoxia is significantly correlated with the late winter–spring (February–April) northeasterly–southwesterly (NE–SW) wind. Based on winter–spring (January–May) conditions, a predictive tool was developed to forecast summer (June–August) hypoxia using river discharge and NE–SW wind. We hypothesized that the late winter–spring wind pattern may affect the transport of spring bloom biomass to the western shoal or the deep channel of the bay that either alleviates or increases the summer hypoxic volume in the midbay region, respectively. To examine this hypothesis, residual flow fields were analyzed using a hydrodynamic ocean model (Regional Ocean Modeling System; ROMS) between 2000 and 2003, two hydrologically similar years but years with different wind conditions during the spring bloom period. Simulation model results suggest that relatively larger amounts of organic matter could be transported into the deep channel in 2003 (severe hypoxia; frequent northeasterly wind) than 2000 (moderate hypoxia; frequent southwesterly wind).

What drives interannual variability of hypoxia in Chesapeake Bay: Climate forcing versus nutrient loading?

Oxygen depletion in estuaries is a worldwide problem with detrimental effects on many organisms. Although nutrient loading has been stabilized for a number of these systems, seasonal hypoxia persists and displays large year-to-year variations, with larger hypoxic volumes in wetter years and smaller hypoxic volumes in drier years. Data analysis points to climate as a driver of interannual hypoxia variability, but nutrient inputs covary with freshwater flow. Here we report an oxygen budget analysis of Chesapeake Bay to quantify relative contributions of physical and biogeochemical processes. Vertical diffusive flux declines with river discharge, whereas longitudinal advective flux increases with river discharge, such that their total supply of oxygen to bottom water is relatively unchanged. However, water column respiration exhibits large interannual fluctuations and is correlated with primary production and hypoxic volume. Hence, the model results suggest that nutrient loading is the main mechanism driving interannual hypoxia variability in Chesapeake Bay.

Ecosystem model intercomparison of under-ice and total primary production in the Arctic Ocean

Previous observational studies have found increasing primary production (PP) in response to declining sea ice cover in the Arctic Ocean. In this study, under-ice PP was assessed based on three coupled ice-ocean-ecosystem models participating in the Forum for Arctic Modeling and Observational Synthesis (FAMOS) project. All models showed good agreement with under-ice measurements of surface chlorophyll-a concentration and vertically integrated PP rates during the main under-ice production period, from mid-May to September. Further, modeled 30-year (1980–2009) mean values and spatial patterns of sea ice concentration compared well with remote sensing data. Under-ice PP was higher in the Arctic shelf seas than in the Arctic Basin, but ratios of under-ice PP over total PP were spatially correlated with annual mean sea ice concentration, with higher ratios in higher ice concentration regions. Decreases in sea ice from 1980 to 2009 were correlated significantly with increases in total PP and decreases in the under-ice PP/total PP ratio for most of the Arctic, but nonsignificantly related to under-ice PP, especially in marginal ice zones. Total PP within the Arctic Circle increased at an annual rate of between 3.2 and 8.0 Tg C/yr from 1980 to 2009. This increase in total PP was due mainly to a PP increase in open water, including increases in both open water area and PP rate per unit area, and therefore much stronger than the changes in under-ice PP. All models suggested that, on a pan-Arctic scale, the fraction of under-ice PP declined with declining sea ice cover over the last three decades.

Polymeric ADAM protein mimics interrogate mammalian sperm-egg binding

ROMPing with the ADAMs family: The sperm‐surface display of egg adhesion proteins was investigated using multivalent polymer sperm mimics. Ruthenium‐catalyzed ring opening metathesis polymerization (ROMP) was used to synthesize heterovalent polymers.

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959–2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free versus ice-influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling.

Modeling Physical and Biogeochemical Controls on Dissolved Oxygen in Chesapeake Bay: Lessons Learned from Simple and Complex Approaches

We compared multiple modeling approaches in Chesapeake Bay to understand the processes controlling dissolved oxygen (O2) cycling and compare the advantages and disadvantages of the different models. Three numerical models were compared, including: (1) a 23-compartment biogeochemical model coupled to a regional scale, salt- and water-balance box model, (2) a simplified, four-term model formulation of O2 uptake and consumption coupled to a 3D-hydrodynamic model, and (3) a 23-compartment biogeochemical model coupled to a 3D-hydrodynamic model. All three models reproduced reasonable spatial and temporal patterns of dissolved O2, leading us to conclude that the model scale and approach one chooses to apply depends on the scientific questions motivating the study. From this analysis, we conclude the following: (1) Models of varying spatial and temporal scales and process resolution have a role in the scientific process. (2) There is still much room for improvement in our ability to simulate dissolved O2 dynamics in coastal ecosystems. (3) An ever-increasing diversity of models, three of which are presented here, will vastly improve our ability to discern physical versus biogeochemical controls on O2 and hypoxia in coastal ecosystems.

Toward predictive understanding of the rapidly evolving Arctic Ocean—An overview

Some of the most rapid climate changes on the planet are experienced in the Arctic. In particular, the Arctic has been warming at a quicker pace than any other place on Earth, what is recognized as Arctic Amplification (AA). This warming has been most visibly manifested through a declining perennial sea ice cover, increasing the potential for its transition from the permanent toward a seasonal coverage. Those changes also affect air-sea heat fluxes and amplify ice-albedo feedback, which strongly influences ocean’s absorption of solar radiation. In addition, they also alter the Arctic Ocean acoustical regime, as the thinning sea ice moves faster and deforms easier, while its reduced coverage allows increased momentum transfer from the atmosphere to the upper ocean. This talk will provide an updated overview of the recent changes and trends in the Arctic Ocean of relevance to acoustical oceanography. We will focus on the evolution of the upper ocean stratification and water masses, mesoscale processes, and their linkages to the changing regime of the sea ice cover from multi-year to first-year sea ice. Also, the latest advancements and outstanding challenges in modeling and prediction of Arctic climate change at sub-seasonal to interannual time scales will be discussed.Some of the most rapid climate changes on the planet are experienced in the Arctic. In particular, the Arctic has been warming at a quicker pace than any other place on Earth, what is recognized as Arctic Amplification (AA). This warming has been most visibly manifested through a declining perennial sea ice cover, increasing the potential for its transition from the permanent toward a seasonal coverage. Those changes also affect air-sea heat fluxes and amplify ice-albedo feedback, which strongly influences ocean’s absorption of solar radiation. In addition, they also alter the Arctic Ocean acoustical regime, as the thinning sea ice moves faster and deforms easier, while its reduced coverage allows increased momentum transfer from the atmosphere to the upper ocean. This talk will provide an updated overview of the recent changes and trends in the Arctic Ocean of relevance to acoustical oceanography. We will focus on the evolution of the upper ocean stratification and water masses, mesoscale processes, and ...

Effects of Model Resolution and Ocean Mixing on Forced Ice‐Ocean Physical and Biogeochemical Simulations Using Global and Regional System Models

The current coarse-resolution global Community Earth System Model (CESM) can reproduce major and large-scale patterns but is still missing some key biogeochemical features in the Arctic Ocean, e.g., low surface nutrients in the Canada Basin. We incorporated the CESM Version 1 ocean biogeochemical code into the Regional Arctic System Model (RASM) and coupled it with a sea-ice algal module to investigate model limitations. Four ice-ocean hindcast cases are compared with various observations: two in a global 18 (40 60 km in the Arctic) grid: G1deg and G1deg-OLD with/without new sea-ice processes incorporated; two on RASM’s 1/128 ( 9 km) grid R9km and R9km-NB with/without a subgrid scale brine rejection parameterization which improves ocean vertical mixing under sea ice. Higher-resolution and new sea-ice processes contributed to lower model errors in sea-ice extent, ice thickness, and ice algae. In the Bering Sea shelf, only higher resolution contributed to lower model errors in salinity, nitrate (NO3), and chlorophyll-a (Chl-a). In the Arctic Basin, model errors in mixed layer depth (MLD) were reduced 36% by brine rejection parameterization, 20% by new sea-ice processes, and 6% by higher resolution. The NO3 concentration biases were caused by both MLD bias and coarse resolution, because of excessive horizontal mixing of high NO3 from the Chukchi Sea into the Canada Basin in coarse resolution models. R9km showed improvements over G1deg on NO3, but not on Chl-a, likely due to light limitation under snow and ice cover in the Arctic Basin.