Lisamarie Windham-Myers’s research while affiliated with Geological Survey of Queensland and other places

Accurate accounting of greenhouse‐gas (GHG) emissions and removals is central to tracking progress toward climate mitigation and for monitoring potential climate‐change feedbacks. GHG budgeting and reporting can follow either the Intergovernmental Panel on Climate Change methodologies for National Greenhouse Gas Inventory (NGHGI) reporting or use atmospheric‐based “top‐down” (TD) inversions or process‐based “bottom‐up” (BU) approaches. To help understand and reconcile these approaches, the Second REgional Carbon Cycle Assessment and Processes study (RECCAP2) was established to quantify GHG emissions and removals for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), for ten‐land and five‐ocean regions for 2010–2019. Here, we present the results for the North American land region (Canada, the United States, Mexico, Central America and the Caribbean). For 2010–2019, the NGHGI reported total net‐GHG emissions of 7,270 TgCO2‐eq yr⁻¹ compared to TD estimates of 6,132 ± 1,846 TgCO2‐eq yr⁻¹ and BU estimates of 9,060 ± 898 TgCO2‐eq yr⁻¹. Reconciling differences between the NGHGI, TD and BU approaches depended on (a) accounting for lateral fluxes of CO2 along the land‐ocean‐aquatic continuum (LOAC) and trade, (b) correcting land‐use CO2 emissions for the loss‐of‐additional‐sink capacity (LASC), (c) avoiding double counting of inland water CH4 emissions, and (d) adjusting area estimates to match the NGHGI definition of the managed‐land proxy. Uncertainties remain from inland‐water CO2 evasion, the conversion of nitrogen fertilizers to N2O, and from less‐frequent NGHGI reporting from non‐Annex‐1 countries. The RECCAP2 framework plays a key role in reconciling independent GHG‐reporting methodologies to support policy commitments while providing insights into biogeochemical processes and responses to climate change.

The State of Bay–Delta Science (SBDS) is intended to inform science and policy audiences about the “state of the science” for topics relevant to management of the San Francisco Bay and Sacramento–San Joaquin Delta (“Bay–Delta”) system. When referencing the Bay–Delta system, we include the atmosphere, watershed, politics, and governance at a broad scale. Each SBDS edition has communicated new insights on a range of high-priority issues by synthesizing the current science and discussing progress on key research questions, knowledge gaps, and proposed future research. Collectively, these editions provide valuable summaries of the physical, biological, and social dimensions of the Bay–Delta. The first edition in 2008 provided a system-wide baseline on history, geography, water quality, ecosystem restoration, levee integrity, water supply, and public policy issues in the Bay–Delta (Healey et al. 2008). Eight years later, the second edition featured research on a dozen priority topics identified by senior scientists and managers working in the Bay–Delta (Healey et al. 2016), ranging from landscape change to migratory fishes to contaminants. Most recently, the third edition addressed research priorities identified in the 2017–2021 Science Action Agenda (DSC 2017), with a focus on the ecosystem services of primary producers (e.g., plants, algae, and their associated carbon) in the Bay–Delta (Larsen et al. 2023). Now, this fourth edition of SBDS focuses on governance and extreme events affecting the Bay–Delta: droughts, heatwaves, wildfires, and atmospheric rivers. The edition explores physical and ecological processes within the Bay–Delta that are responding to changes in large-scale forcing phenomena, primarily those associated with climate change, building on the rich long-term time-series data collected by regional and statewide monitoring programs.

Coastal wetlands, including seagrass meadows, emergent marshes, mangroves, and temperate tidal swamps, can efficiently sequester and store large quantities of sediment organic carbon (SOC). However, SOC stocks may vary by ecosystem type and along environmental or climate gradients at different scales. Quantifying such variability is needed to improve blue carbon accounting, conservation effectiveness, and restoration planning. We analyzed SOC stocks in 1,284 sediment cores along >6,500 km of the Pacific coast of North America that included large environmental gradients and multiple ecosystem types. Tidal wetlands with woody vegetation (mangroves and swamps) had the highest mean stocks to 1 m depth (357 and 355 Mg ha⁻¹, respectively), 45% higher than marshes (245 Mg ha⁻¹), and more than 500% higher than seagrass (68 Mg ha⁻¹). Unvegetated tideflats, though not often considered a blue carbon ecosystem, had noteworthy stocks (148 Mg ha⁻¹). Stocks increased with tidal elevation and with fine (<63 μm) sediment content in several ecosystems. Stocks also varied by dominant plant species within individual ecosystem types. At larger scales, marsh stocks were lowest in the Sonoran Desert region of Mexico, and swamp stocks differed among climate zones; otherwise stocks showed little correlation with ecoregion or latitude. More variability in SOC occurred among ecosystem types, and at smaller spatial scales (such as individual estuaries), than across regional climate gradients. These patterns can inform coastal conservation and restoration priorities across scales where preserving stored carbon and enhancing sequestration helps avert greenhouse gas emissions and maintains other vital ecosystem services.

Tidal marshes are threatened coastal ecosystems known for their capacity to store large amounts of carbon in their water-logged soils. Accurate quantification and mapping of global tidal marshes soil organic carbon (SOC) stocks is of considerable value to conservation efforts. Here, we used training data from 3710 unique locations, landscape-level environmental drivers and a global tidal marsh extent map to produce a global, spatially explicit map of SOC storage in tidal marshes at 30 m resolution. Here we show the total global SOC stock to 1 m to be 1.44 Pg C, with a third of this value stored in the United States of America. On average, SOC in tidal marshes’ 0–30 and 30–100 cm soil layers are estimated at 83.1 Mg C ha⁻¹ (average predicted error 44.8 Mg C ha⁻¹) and 185.3 Mg C ha⁻¹ (average predicted error 105.7 Mg C ha⁻¹), respectively.

Tidal wetlands can be a substantial sink of greenhouse gases, which can be offset by variable methane (CH4) emissions under certain environmental conditions and anthropogenic interventions. Land managers and policymakers need maps of tidal wetland CH4 properties to make restoration decisions and inventory greenhouse gases. However, there is a mismatch in spatial scale between point-based sampling of porewater CH4 concentration and its predictors, and the coarser resolution mapping products used to upscale these data. We sampled porewater CH4 concentrations, salinity, sulfate (SO42−), ammonium (NH4+), and total Fe using a spatially stratified sampling at 27 tidal wetlands in the United States. We measured porewater CH4 concentrations across four orders of magnitude (0.05 to 852.9 μM). The relative contribution of spatial scale to variance in CH4 was highest between- and within-sites. Porewater CH4 concentration was best explained by SO42− concentration with segmented linear regression (p < 0.01, R2 = 0.54) indicating lesser sensitivity of CH4 to SO42− below 0.62 mM SO42−. Salinity was a significant proxy for CH4 concentration, because it was highly correlated with SO42− (p < 0.01, R2 = 0.909). However, salinity was less predictive of CH4 with segmented linear regression (p < 0.01, R2 = 0.319) relative to SO42−. Neither NH4+, total Fe, nor relative tidal elevation correlated significantly with porewater CH4; however, NH4+ was positively and significantly correlated with SO42− after detrending CH4 for its relationship with SO42− (p < 0.01, R2 = 0.194). Future sampling should focus on within- and between-site environmental gradients to accurately map CH4 variation. Mapping salinity at sub-watershed scales has some potential for mapping SO42−, and by proxy, constraining spatial variation in porewater CH4 concentrations. Additional work is needed to explain site-level deviations from the salinity-sulfate relationship and elucidate other predictors of methanogenesis. This work demonstrates a unique approach to remote team science and the potential to strengthen collaborative research networks.

Tropical cyclones (coastal storm events that include tropical depressions, tropical storms, and hurricanes) cause landscape-scale disturbances that can lead to impaired water quality and thus reduce water availability for use. Stakeholders and scientists at local and national scales have illustrated a need for understanding these risks to water quality. A regional and comprehensive understanding of the impacts of tropical storms and hurricanes on surface-water and groundwater quality—and thus water availability—is lacking for potentially impacted coastal and inland areas. As the U.S. Geological Survey considers development of tools to predict the extent to which water-quality impacts of hurricanes affect water availability, an assessment of the state of the science of hurricane impacts is needed, including a gap analysis and prioritization of data and science needs. This assessment focuses on the southeastern coastal States.

Tidal wetlands provide valuable ecosystem services, including storing large amounts of carbon. However, the net exchanges of carbon dioxide (CO2) and methane (CH4) in tidal wetlands are highly uncertain. While several biogeochemical models can operate in tidal wetlands, they have yet to be parameterized and validated against high‐frequency, ecosystem‐scale CO2 and CH4 flux measurements across diverse sites. We paired the Cohort Marsh Equilibrium Model (CMEM) with a version of the PEPRMT model called PEPRMT‐Tidal, which considers the effects of water table height, sulfate, and nitrate availability on CO2 and CH4 emissions. Using a model‐data fusion approach, we parameterized the model with three sites and validated it with two independent sites, with representation from the three marine coasts of North America. Gross primary productivity (GPP) and ecosystem respiration (Reco) modules explained, on average, 73% of the variation in CO2 exchange with low model error (normalized root mean square error (nRMSE) <1). The CH4 module also explained the majority of variance in CH4 emissions in validation sites (R² = 0.54; nRMSE = 1.15). The PEPRMT‐Tidal‐CMEM model coupling is a key advance toward constraining estimates of greenhouse gas emissions across diverse North American tidal wetlands. Further analyses of model error and case studies during changing salinity conditions guide future modeling efforts regarding four main processes: (a) the influence of salinity and nitrate on GPP, (b) the influence of laterally transported dissolved inorganic C on Reco, (c) heterogeneous sulfate availability and methylotrophic methanogenesis impacts on surface CH4 emissions, and (d) CH4 responses to non‐periodic changes in salinity.

Coastal wetlands are hotspots of carbon sequestration, and their conservation and restoration can help to mitigate climate change. However, there remains uncertainty on when and where coastal wetland restoration can most effectively act as natural climate solutions (NCS). Here, we synthesize current understanding to illustrate the requirements for coastal wetland restoration to benefit climate, and discuss potential paths forward that address key uncertainties impeding implementation. To be effective as NCS, coastal wetland restoration projects will accrue climate cooling benefits that would not occur without management action (additionality), will be implementable (feasibility) and will persist over management-relevant timeframes (permanence). Several issues add uncertainty to understanding if these minimum requirements are met. First, coastal wetlands serve as both a landscape source and sink of carbon for other habitats, increasing uncertainty in additionality. Second, coastal wetlands can potentially migrate outside of project footprints as they respond to sea-level rise, increasing uncertainty in permanence. To address these first two issues, a system-wide approach may be necessary, rather than basing cooling benefits only on changes that occur within project boundaries. Third, the need for NCS to function over management-relevant decadal timescales means methane responses may be necessary to include in coastal wetland restoration planning and monitoring. Finally, there is uncertainty on how much data are required to justify restoration action. We summarize the minimum data required to make a binary decision on whether there is a net cooling benefit from a management action, noting that these data are more readily available than the data required to quantify the magnitude of cooling benefits for carbon crediting purposes. By reducing uncertainty, coastal wetland restoration can be implemented at the scale required to significantly contribute to addressing the current climate crisis.

Methane (CH4) 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 CH4 emissions, yet the magnitude and factors controlling CH4 fluxes in tidal wetlands remain uncertain. We synthesized CH4 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 CH4 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 CH4 m⁻² year⁻¹, with a median of 3.9 g CH4 m⁻² year⁻¹, and only 25% of sites exceeding 18 g CH4 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 CH4 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 CH4 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 CH4 flux changes, while the opposite was observed at the seasonal scale. Water levels influenced the timing and pathway of diel CH4 fluxes, with pulsed releases of stored CH4 at low to rising tide. This study provides data and methods to improve tidal marsh CH4 emission estimates, support blue carbon assessments, and refine national and global GHG inventories.