Geology topics

Julie Shahan

Publications and source records attributed to Julie Shahan.

4 recordsLinked to original sources

USGS2024

Methane fluxes in tidal marshes of the conterminous United States

Methane (CH 4 ) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre-industrial times. Wetlands account for a large share of global CH 4 emissions, yet the magnitude and factors controlling CH 4 fluxes in tidal wetlands remain uncertain. We synthesized CH 4 flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH 4 emissions. This effort included creating an open-source database of chamber-based GHG fluxes ( https://doi.org/10.25573/serc.14227085 ). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH 4 m −2 year −1 , with a median of 3.9 g CH 4 m −2 year −1 , and only 25% of sites exceeding 18 g CH 4 m −2 year −1 . The highest fluxes were observed at fresh-oligohaline sites with daily maximum temperature normals (MATmax) above 25.6°C. These were followed by frequently inundated low and mid-fresh-oligohaline marshes with MATmax ≤25.6°C, and mesohaline sites with MATmax >19°C. Quantile regressions of paired chamber CH 4 flux and porewater biogeochemistry revealed that the 90th percentile of fluxes fell below 5 ± 3 nmol m −2 s −1 at sulfate concentrations >4.7 ± 0.6 mM, porewater salinity >21 ± 2 psu, or surface water salinity >15 ± 3 psu. Across sites, salinity was the dominant predictor of annual CH 4 fluxes, while within sites, temperature, gross primary productivity (GPP), and tidal height controlled variability at diel and seasonal scales. At the diel scale, GPP preceded temperature in importance for predicting CH 4 flux changes, while the opposite was observed at the seasonal scale. Water levels influenced the timing and pathway of diel CH 4 fluxes, with pulsed releases of stored CH 4 at low to rising tide. This study provides data and methods to improve tidal marsh CH 4 emission estimates, support blue carbon assessments, and refine national and global GHG inventories.

conterminous United States↗

USGS2023

On the relationship between aquatic CO2 concentration and ecosystem fluxes in some of the world’s key wetland types

To understand patterns in CO 2 partial pressure (P CO2 ) over time in wetlands’ surface water and porewater, we examined the relationship between P CO2 and land–atmosphere flux of CO 2 at the ecosystem scale at 22 Northern Hemisphere wetland sites synthesized through an open call. Sites spanned 6 major wetland types (tidal, alpine, fen, bog, marsh, and prairie pothole/karst), 7 Köppen climates, and 16 different years. Ecosystem respiration (R eco ) and gross primary production (GPP), components of vertical CO 2 flux, were compared to P CO2 , a component of lateral CO 2 flux, to determine if photosynthetic rates and soil respiration consistently influence wetland surface and porewater CO 2 concentrations across wetlands. Similar to drivers of primary productivity at the ecosystem scale, P CO2 was strongly positively correlated with air temperature (T air ) at most sites. Monthly average P CO2 tended to peak towards the middle of the year and was more strongly related to R eco than GPP. Our results suggest R eco may be related to biologically driven P CO2 in wetlands, but the relationship is site-specific and could be an artifact of differently timed seasonal cycles or other factors. Higher levels of discharge do not consistently alter the relationship between R eco and temperature normalized P CO2 . This work synthesizes relevant data and identifies key knowledge gaps in drivers of wetland respiration.

Wetlands↗

USGS2022

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 CH 4 budgets. However, these ecosystems' greenhouse gas monitoring and predictions are challenging due to spatial heterogeneity and tidal flooding. We utilized eddy covariance and chamber measurements to quantify fluxes of CO 2 and CH 4 at a restored tidal saltmarsh across spatial and temporal scales. Eddy covariance data revealed that the site was a strong net sink for CO 2 (−387 g C-CO 2 m −2 yr −1 , SD = 46) and a small net source of CH 4 (0.7 g C-CH 4 m −2 yr −1 , SD = 0.4). After partitioning net ecosystem exchange of CO 2 into gross primary production and ecosystem respiration, we found that high net uptake of CO 2 was due to low respiration emissions rather than high photosynthetic rates. We also found that respiration rates varied between land covers with increased respiration in mudflats compared to vegetated areas. Daytime soil chamber measurements revealed that the greatest CO 2 emission was from higher elevation mudflat soils (0.5 μmol m −2 s −1 , SE = 1.3) and CH 4 emission was greatest from lower elevation Spartina foliosa soils (1.6 nmol m −2 s −1 , SD = 8.2). Overall, these results highlight the importance of the relationships between wetland plant community and elevation, and inundation for CO 2 and CH 4 fluxes. Future research should include the use of high-resolution imagery, automated chambers, and a focus on quantifying carbon exported in tidal waters.

California↗

USGS2021

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 signals by tidal flooding. However, understanding plant phenology is necessary to gain insight into aboveground biomass, photosynthetic activity, and carbon sequestration. In this study we use a modeling approach to estimate plant greenness throughout a year in tidal wet-lands located within the San Francisco Bay Area, USA. We used variables such as EVI history, temperature, and elevation to predict plant greenness on a 14-day timestep. We found this ap-proach accurately estimated plant greenness, with larger error observed within more dynamic restored wetlands, particularly at early post-restoration stages. We also found modeled EVI can be used as an input variable into greenhouse gas models, allowing for an estimate of carbon se-questration and gross primary production. Our strategy can be further developed in future re-search by assessing restoration and management effects on wetland phenological dynamics and through incorporating the entire Sentinel-2 time-series once it becomes available within Google Earth Engine.

California↗