Ellen Stuart-Haëntjens - California Water Science Center
Science and Products
Creating a Model to Predict Future Carbon Levels in Tidally-driven Marshes
Tidal marshes are important ecosystems in the San Francisco-Bay Delta. They remove carbon from the atmosphere, they build up soils that buffer our communities from sea level rise, they provide critical habitat and food resources for a diversity of species, and they reduce excessive nutrients which have a negative impact on water quality. As a result of land-use change and urbanization, the San...
Combining eddy covariance and chamber methods to better constrain CO2 and CH4 fluxes across a heterogeneous restored tidal wetland
Tidal wetlands play an important role in global carbon cycling by storing carbon in sediment at millennial time scales, transporting dissolved carbon into coastal waters, and contributing significantly to global CH4 budgets. However, these ecosystems' greenhouse gas monitoring and predictions are challenging due to spatial heterogeneity and tidal flooding. We utilized eddy covariance and chamber m
Carbon flux, storage, and wildlife co-benefits in a restoring estuary
Tidal marsh restorations may result in transitional mudflat habitats depending on hydrological and geomorphological conditions. Compared to tidal marsh, mudflats are thought to have limited value for carbon sequestration, carbon storage, and foraging benefits for salmon. We evaluated greenhouse gas exchange, sediment carbon storage, and invertebrate production at restoration and reference tidal ma
The potential of satellite remote sensing time series to uncover wetland phenology under unique challenges of tidal setting
While growth history of vegetation within upland systems is well studied, plant phenology within coastal tidal systems is less understood. Landscape-scale, satellite-derived indicators of plant greenness may not adequately represent seasonality of vegetation biomass and productivity within tidal wetlands due to limitations of cloud cover, satellite temporal frequency and attenu-ation of plant sign
FLUXNET-CH4: A global, multi-ecosystem database and analysis of methane seasonality from freshwater wetlands
Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux mea
Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors
A reporting format for leaf-level gas exchange data and metadata
Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of t
Science and Products
- Science
Creating a Model to Predict Future Carbon Levels in Tidally-driven Marshes
Tidal marshes are important ecosystems in the San Francisco-Bay Delta. They remove carbon from the atmosphere, they build up soils that buffer our communities from sea level rise, they provide critical habitat and food resources for a diversity of species, and they reduce excessive nutrients which have a negative impact on water quality. As a result of land-use change and urbanization, the San... - Publications
Combining eddy covariance and chamber methods to better constrain CO2 and CH4 fluxes across a heterogeneous restored tidal wetland
Tidal wetlands play an important role in global carbon cycling by storing carbon in sediment at millennial time scales, transporting dissolved carbon into coastal waters, and contributing significantly to global CH4 budgets. However, these ecosystems' greenhouse gas monitoring and predictions are challenging due to spatial heterogeneity and tidal flooding. We utilized eddy covariance and chamber mCarbon flux, storage, and wildlife co-benefits in a restoring estuary
Tidal marsh restorations may result in transitional mudflat habitats depending on hydrological and geomorphological conditions. Compared to tidal marsh, mudflats are thought to have limited value for carbon sequestration, carbon storage, and foraging benefits for salmon. We evaluated greenhouse gas exchange, sediment carbon storage, and invertebrate production at restoration and reference tidal maThe potential of satellite remote sensing time series to uncover wetland phenology under unique challenges of tidal setting
While growth history of vegetation within upland systems is well studied, plant phenology within coastal tidal systems is less understood. Landscape-scale, satellite-derived indicators of plant greenness may not adequately represent seasonality of vegetation biomass and productivity within tidal wetlands due to limitations of cloud cover, satellite temporal frequency and attenu-ation of plant signFLUXNET-CH4: A global, multi-ecosystem database and analysis of methane seasonality from freshwater wetlands
Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux meaGap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictorsA reporting format for leaf-level gas exchange data and metadata
Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of t