ALBERT

Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scalpone, C. R., Jarvis, J. C., Vasslides, J. M., Testa, J. M., & Ganju, N. K. Simulated estuary-wide response of seagrass (Zostera marina) to future scenarios of temperature and sea level. Frontiers in Marine Science, 7, (2020): 539946, doi:10.3389/fmars.2020.539946.

Description: Seagrass communities are a vital component of estuarine ecosystems, but are threatened by projected sea level rise (SLR) and temperature increases with climate change. To understand these potential effects, we developed a spatially explicit model that represents seagrass (Zostera marina) habitat and estuary-wide productivity for Barnegat Bay-Little Egg Harbor (BB-LEH) in New Jersey, United States. Our modeling approach included an offline coupling of a numerical seagrass biomass model with the spatially variable environmental conditions from a hydrodynamic model to calculate above and belowground biomass at each grid cell of the hydrodynamic model domain. Once calibrated to represent present day seagrass habitat and estuary-wide annual productivity, we applied combinations of increasing air temperature and sea level following regionally specific climate change projections, enabling analysis of the individual and combined impacts of these variables on seagrass biomass and spatial coverage. Under the SLR scenarios, the current model domain boundaries were maintained, as the land surrounding BB-LEH is unlikely to shift significantly in the future. SLR caused habitat extent to decrease dramatically, pushing seagrass beds toward the coastline with increasing depth, with a 100% loss of habitat by the maximum SLR scenario. The dramatic loss of seagrass habitat under SLR was in part due to the assumption that surrounding land would not be inundated, as the model did not allow for habitat expansion outside the current boundaries of the bay. Temperature increases slightly elevated the rate of summer die-off and decreased habitat area only under the highest temperature increase scenarios. In combined scenarios, the effects of SLR far outweighed the effects of temperature increase. Sensitivity analysis of the model revealed the greatest sensitivity to changes in parameters affecting light limitation and seagrass mortality, but no sensitivity to changes in nutrient limitation constants. The high vulnerability of seagrass in the bay to SLR exceeded that demonstrated for other systems, highlighting the importance of site- and region-specific assessments of estuaries under climate change.

Description: This research was supported by the National Science Foundation Research Experience for Undergraduates Program (OCE-1659463), the Woods Hole Oceanographic Institution Summer Student Fellowship Program, the Barnegat Bay Partnership (through a US EPA Clean Water Act grant to Ocean County College; CE98212313), and the USGS Coastal and Marine Hazards/Resources Program. Although this project has been funded in part by the United States Environmental Protection Agency pursuant to a grant agreement with Ocean County College, it has not gone through the Agency’s publications review process and may not necessarily reflect the views of the Agency; therefore, no official endorsement should be assumed. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Estuaries and Coasts 39 (2016): 311-332, doi:10.1007/s12237-015-0011-y.

Description: Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review, we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.

Description: NKG, ALA, and RPS acknowledge support from the USGS Coastal and Marine Geology Program. DKR gratefully acknowledges support from NSF (OCE-1314642) and NIEHS (1P50-ES021923-01). MJB and JMPV gratefully acknowledge support from NOAA NOS NCCOS (NA05NOS4781201 and NA11NOS4780043). MJB and SJL gratefully acknowledge support from the Strategic Environmental Research and Development Program—Defense Coastal/Estuarine Research Program (RC-1413 and RC-2245).

Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ganju, N. K., Testa, J. M., Suttles, S. E., & Aretxabaleta, A. L. Spatiotemporal variability of light attenuation and net ecosystem metabolism in a back-barrier estuary. Ocean Science, 16(3), (2020): 593-614, doi:10.5194/os-16-593-2020.

Description: Quantifying system-wide biogeochemical dynamics and ecosystem metabolism in estuaries is often attempted using a long-term continuous record at a single site or short-term records at multiple sites due to sampling limitations that preclude long-term monitoring. However, differences in the dominant primary producer at a given location (e.g., phytoplankton versus benthic producers) control diel variations in dissolved oxygen and associated ecosystem metabolism, and they may confound metabolic estimates that do not account for this variability. We hypothesize that even in shallow, well-mixed estuaries there is strong spatiotemporal variability in ecosystem metabolism due to benthic and water-column properties, as well as ensuing feedbacks to sediment resuspension, light attenuation, and primary production. We tested this hypothesis by measuring hydrodynamic properties, biogeochemical variables (fluorescent dissolved organic matter – fDOM, turbidity, chlorophyll a fluorescence, dissolved oxygen), and photosynthetically active radiation (PAR) over 1 year at 15 min intervals at paired channel (unvegetated) and shoal (vegetated by eelgrass) sites in Chincoteague Bay, Maryland–Virginia, USA, a shallow back-barrier estuary. Light attenuation (KdPAR) at all sites was dominated by turbidity from suspended sediment, with lower contributions from fDOM and chlorophyll a. However, there was significant seasonal variability in the resuspension–shear stress relationship on the vegetated shoals, but not in adjacent unvegetated channels. This indicated that KdPAR on the shoals was mediated by submerged aquatic vegetation (SAV) and possibly microphytobenthos presence in the summer, which reduced resuspension and therefore KdPAR. We also found that gross primary production (Pg) and KdPAR were significantly negatively correlated on the shoals and uncorrelated in the channels, indicating that Pg over the vegetated shoals is controlled by a feedback loop between benthic stabilization by SAV and/or microphytobenthos, sediment resuspension, and light availability. Metabolic estimates indicated substantial differences in net ecosystem metabolism between vegetated and unvegetated sites, with the former tending towards net autotrophy in the summer. Ongoing trends of SAV loss in this and other back-barrier estuaries suggest that these systems may also shift towards net heterotrophy, reducing their effectiveness as long-term carbon sinks. With regards to temporal variability, we found that varying sampling frequency between 15 min and 1 d resulted in comparable mean values of biogeochemical variables, but extreme values were missed by daily sampling. In fact, daily resampling minimized the variability between sites and falsely suggested spatial homogeneity in biogeochemistry, emphasizing the need for high-frequency sampling. This study confirms that properly quantifying ecosystem metabolism and associated biogeochemical variability requires characterization of the diverse estuarine environments, even in well-mixed systems, and demonstrates the deficiencies introduced by infrequent sampling to the interpretation of spatial variability.

Description: This study was funded by the USGS Coastal and Marine Geology Program and the Department of the Interior Hurricane Sandy Recovery program (GS2-2D).

Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 13 (2016): 2011-2028, doi:10.5194/bg-13-2011-2016.

Description: As three-dimensional (3-D) aquatic ecosystem models are used more frequently for operational water quality forecasts and ecological management decisions, it is important to understand the relative strengths and limitations of existing 3-D models of varying spatial resolution and biogeochemical complexity. To this end, 2-year simulations of the Chesapeake Bay from eight hydrodynamic-oxygen models have been statistically compared to each other and to historical monitoring data. Results show that although models have difficulty resolving the variables typically thought to be the main drivers of dissolved oxygen variability (stratification, nutrients, and chlorophyll), all eight models have significant skill in reproducing the mean and seasonal variability of dissolved oxygen. In addition, models with constant net respiration rates independent of nutrient supply and temperature reproduced observed dissolved oxygen concentrations about as well as much more complex, nutrient-dependent biogeochemical models. This finding has significant ramifications for short-term hypoxia forecasts in the Chesapeake Bay, which may be possible with very simple oxygen parameterizations, in contrast to the more complex full biogeochemical models required for scenario-based forecasting. However, models have difficulty simulating correct density and oxygen mixed layer depths, which are important ecologically in terms of habitat compression. Observations indicate a much stronger correlation between the depths of the top of the pycnocline and oxycline than between their maximum vertical gradients, highlighting the importance of the mixing depth in defining the region of aerobic habitat in the Chesapeake Bay when low-oxygen bottom waters are present. Improvement in hypoxia simulations will thus depend more on the ability of models to reproduce the correct mean and variability of the depth of the physically driven surface mixed layer than the precise magnitude of the vertical density gradient.

Description: This work was supported by the NOAA IOOS program as part of the Coastal Ocean Modeling Testbed.

Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Kalra, T. S., Ganju, N. K., & Testa, J. M. Development of a submerged aquatic vegetation growth model in the coupled ocean-atmosphere-wave-sediment transport (COAWST v3.4) model. Geoscientific Model Development, 13(11), (2020): 5211-5228, doi:10.5194/gmd-13-5211-2020.

Description: The coupled biophysical interactions between submerged aquatic vegetation (SAV), hydrodynamics (currents and waves), sediment dynamics, and nutrient cycling have long been of interest in estuarine environments. Recent observational studies have addressed feedbacks between SAV meadows and their role in modifying current velocity, sedimentation, and nutrient cycling. To represent these dynamic processes in a numerical model, the presence of SAV and its effect on hydrodynamics (currents and waves) and sediment dynamics was incorporated into the open-source Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. In this study, we extend the COAWST modeling framework to account for dynamic changes of SAV and associated epiphyte biomass. Modeled SAV biomass is represented as a function of temperature, light, and nutrient availability. The modeled SAV community exchanges nutrients, detritus, dissolved inorganic carbon, and dissolved oxygen with the water-column biogeochemistry model. The dynamic simulation of SAV biomass allows the plants to both respond to and cause changes in the water column and sediment bed properties, hydrodynamics, and sediment transport (i.e., a two-way feedback). We demonstrate the behavior of these modeled processes through application to an idealized domain and then apply the model to a eutrophic harbor where SAV dieback is a result of anthropogenic nitrate loading and eutrophication. These cases demonstrate an advance in the deterministic modeling of coupled biophysical processes and will further our understanding of future ecosystem change.

Description: This is University of Maryland Center for Environmental Contribution no. 5909.

Description: Quantifying system-wide biogeochemical dynamics and ecosystem metabolism in estuaries is often attempted using a long-term continuous record at a single site or short-term records at multiple sites due to sampling limitations that preclude long-term monitoring. However, differences in the dominant primary producer at a given location (e.g., phytoplankton versus benthic producers) control diel variations in dissolved oxygen and associated ecosystem metabolism, and they may confound metabolic estimates that do not account for this variability. We hypothesize that even in shallow, well-mixed estuaries there is strong spatiotemporal variability in ecosystem metabolism due to benthic and water-column properties, as well as ensuing feedbacks to sediment resuspension, light attenuation, and primary production. We tested this hypothesis by measuring hydrodynamic properties, biogeochemical variables (fluorescent dissolved organic matter – fDOM, turbidity, chlorophyll a fluorescence, dissolved oxygen), and photosynthetically active radiation (PAR) over 1 year at 15 min intervals at paired channel (unvegetated) and shoal (vegetated by eelgrass) sites in Chincoteague Bay, Maryland–Virginia, USA, a shallow back-barrier estuary. Light attenuation (KdPAR) at all sites was dominated by turbidity from suspended sediment, with lower contributions from fDOM and chlorophyll a. However, there was significant seasonal variability in the resuspension–shear stress relationship on the vegetated shoals, but not in adjacent unvegetated channels. This indicated that KdPAR on the shoals was mediated by submerged aquatic vegetation (SAV) and possibly microphytobenthos presence in the summer, which reduced resuspension and therefore KdPAR. We also found that gross primary production (Pg) and KdPAR were significantly negatively correlated on the shoals and uncorrelated in the channels, indicating that Pg over the vegetated shoals is controlled by a feedback loop between benthic stabilization by SAV and/or microphytobenthos, sediment resuspension, and light availability. Metabolic estimates indicated substantial differences in net ecosystem metabolism between vegetated and unvegetated sites, with the former tending towards net autotrophy in the summer. Ongoing trends of SAV loss in this and other back-barrier estuaries suggest that these systems may also shift towards net heterotrophy, reducing their effectiveness as long-term carbon sinks. With regards to temporal variability, we found that varying sampling frequency between 15 min and 1 d resulted in comparable mean values of biogeochemical variables, but extreme values were missed by daily sampling. In fact, daily resampling minimized the variability between sites and falsely suggested spatial homogeneity in biogeochemistry, emphasizing the need for high-frequency sampling. This study confirms that properly quantifying ecosystem metabolism and associated biogeochemical variability requires characterization of the diverse estuarine environments, even in well-mixed systems, and demonstrates the deficiencies introduced by infrequent sampling to the interpretation of spatial variability.