My research focuses on understanding spatial patterns of nutrients and pCO2 in large lakes and oceans. I am interested in how biology and physics mediate these patterns to understand how the climate and ecosystems change over time. This work can lead to efficient managment efforts in large lakes and reduce uncertainty in the global carbon budget. Tools I use to tackle these problems include: computer models, satellite data, and in-situ observations.
The ocean serves an important ecosystem service by reducing the impact of human derived carbon dioxide emissions. Quantifying the CO2 flux across the air-sea interface requires time-dependent maps of surface ocean pCO2. However, observations are sparse in space and time, making global flux estimates difficult. Various techniques have been developed to create time-dependent maps of pCO2 with a global coverage. However, the methods do not agree on the range of variability. This projects aims to create a testbed where these methods can be evaluated. The testbed is created using three independent coupled ocean-atmosphere large ensemble models sampled at observation locations. We use this testbed to statistically evaluate how well different gap-filling approaches are able to reconstruct the spatial pattern of pCO2 in different climate states This work is important to reducing uncertainty in the global carbon budget and assessing whether the goals of the UNFCCC Paris agreement are being achieved.
The shunt of photosynthetically derived particulate organic carbon (POC) out of the surface ocean is an integral component of the “biological pump.” POC raining through the deep ocean is remineralized back to dissolved inorganic carbon though microbial respiration. Accurately modeling POC flux is critical for understanding the “biological pump” and its impacts on air-sea CO2 exchange and, ultimately, long-term ocean carbon sequestration. Yet commonly used parameterizations have not been tested quantitatively against global data sets using identical modeling frameworks. We use a single one-dimensional physical-biogeochemical modeling framework to assess three common POC flux parameterizations in capturing POC flux observations from moored sediment traps and thorium-234 depletion. This work has implications for understanding how the climate and ecosystem services will change in the future.
The Great Lakes are a treasured natural resource that contain over 80% of North America's surface freshwater. Tributary nutrient loads degrade Great Lakes coastal ecosystems and services they provide, including drinking water, fisheries, and recreation. In Lake Michigan, open-lake total phosphorus concentrations are below Great Lakes Water Quality agreement (GLWQA) target concentrations but are elevated in the coastal zone. A realistic three-dimensional hydrodynamic model of Lake Michigan was developed to simulate the redistribution of tributary-derived phosphorus loads in the lake. In spring along most of the shoreline, riverine phosphorus is trapped in coastal plumes that eventually spread offshore in summer. Ths simulation is used in tandem with time-invariant maps of ecosystem services to calculate stress due to excesive nutrient concentrations.Load magnitudes, in-lake physics, and the spatial distribution of ecosystem services all contribute to coastal service impacts. The quantitative framework is applicable to a wide range of pollutants and waterbodies and has the potential to increase the efficiency of coastal management.