About

Dr. Jared L. Wilmoth leads the Soil Chemical Interfaces (W-SCI) research group within the Department of Environmental Science and Technology at the University of Maryland, College Park. His research focuses on understanding the mechanistic connections between environmental soil systems, their biogeochemical cycles, and the Earth's climate. Current work examines how soil redox conditions and climate-driven perturbations interact in various soil environments, utilizing high-resolution chemical and biomolecular characterization techniques. The research investigates critical abiotic and biotic pathways across mineral, microbial, organic matter, and rhizosphere interfaces, aiming to elucidate their roles over different spatiotemporal scales. The overarching goal is to better understand these processes' relationship with global carbon cycling and environmental sustainability through collaborative, interdisciplinary approaches.

Research topics

• Geology
• Oceanography
• Soil science
• Environmental science
• Ecology
• Atmospheric sciences
• Remote sensing
• Geomorphology
• Geography

Selected publications

• Soil Extractable Lead (Pb) Levels Associated With Increased Soil Carbon Content in Mid‐Atlantic Turfgrass Soils

  Journal of Geophysical Research Biogeosciences · 2025-10-01

  articleOpen access

  Abstract The effects of multiple global change factors on soil carbon (C) stocks are difficult to capture in short‐term experiments, but urbanization and other localized characteristics impose long‐term, gradual increases in temperature, carbon dioxide and ozone with observable in situ effects. We conducted an observational study in 62 golf courses at varying distances from urbanized areas in the temperate, mesic, mid‐Atlantic U.S., measuring soil carbon stocks in minimally managed areas where cool‐season turfgrasses had grown without disturbance for at least 25 years. In 2009–2010, soils were sampled to 30 cm depth and site and management variables were recorded. Total and permanganate oxidizable soil carbon were quantified and potential explanatory factors were explored using multiple regression analysis. Extractable soil lead (Pb) was strongly and positively correlated with total soil C (Pb incremental R 2 = 30.3%) above a threshold of ca. 4 mg/kg soil extracted. Increasing minimum daily temperature in February and cation exchange capacity were also positively correlated with total soil carbon (incremental R 2 = 2.8% for each factor). These findings suggest that atmospherically deposited Pb atoms chemically associated with and stabilized soil carbon in these soils. Large quantities of Pb were deposited atmospherically over the last century. If the effects observed here are widespread (i.e., in other regions and ecosystems), legacy Pb may impact soil carbon at a scale relevant to global carbon cycle modeling and uncertainty. Further exploration of Pb effects on soil C mineralization is urgently needed to improve quantitative models and our understanding of soil C dynamics.

  PublisherDOI

• A New Coupled Biogeochemical Modeling Approach Provides Accurate Predictions of Methane and Carbon Dioxide Fluxes Across Diverse Tidal Wetlands

  Journal of Geophysical Research Biogeosciences · 2024-10-01 · 6 citations

  articleOpen access

  Abstract Tidal wetlands provide valuable ecosystem services, including storing large amounts of carbon. However, the net exchanges of carbon dioxide (CO 2 ) and methane (CH 4 ) 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 CO 2 and CH 4 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 CO 2 and CH 4 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 (R eco ) modules explained, on average, 73% of the variation in CO 2 exchange with low model error (normalized root mean square error (nRMSE) <1). The CH 4 module also explained the majority of variance in CH 4 emissions in validation sites ( R 2 = 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 R eco , (c) heterogeneous sulfate availability and methylotrophic methanogenesis impacts on surface CH 4 emissions, and (d) CH 4 responses to non‐periodic changes in salinity.

  PublisherOA PDFDOI

• Early‐season biomass and weather enable robust cereal rye cover crop biomass predictions

  Agricultural & Environmental Letters · 2024-02-13 · 6 citations

  articleOpen access

  Abstract Farmers need accurate estimates of winter cover crop biomass to make informed decisions on termination timing or to estimate potential release of nitrogen from cover crop residues to subsequent cash crops. Utilizing data from an extensive experiment across 11 states from 2016 to 2020, this study explores the most reliable predictors for determining cereal rye cover crop biomass at the time of termination. Our findings demonstrate a strong relationship between early‐season and late‐season cover crop biomass. Employing a random forest model, we predicted late‐season cereal rye biomass with a margin of error of approximately 1,000 kg ha −1 based on early‐season biomass, growing degree days, cereal rye planting and termination dates, photosynthetically active radiation, precipitation, and site coordinates as predictors. Our results suggest that similar modeling approaches could be combined with remotely sensed early‐season biomass estimations to improve the accuracy of predicting winter cover crop biomass at termination for decision support tools. Core Ideas Cereal rye winter cover crop biomass modeled on data from 35 site‐years. We found a strong relationship between early and late‐season biomass. Random forest model with early‐season biomass and weather data performed well. Similar approach could improve decision support tools for cover crop management.

  PublisherOA PDFDOI

• U.S. cereal rye winter cover crop growth database

  Scientific Data · 2024-02-13 · 14 citations

  articleOpen access

  Abstract Winter cover crop performance metrics (i.e., vegetative biomass quantity and quality) affect ecosystem services provisions, but they vary widely due to differences in agronomic practices, soil properties, and climate. Cereal rye (S ecale cereale ) is the most common winter cover crop in the United States due to its winter hardiness, low seed cost, and high biomass production. We compiled data on cereal rye winter cover crop performance metrics, agronomic practices, and soil properties across the eastern half of the United States. The dataset includes a total of 5,695 cereal rye biomass observations across 208 site-years between 2001–2022 and encompasses a wide range of agronomic, soils, and climate conditions. Cereal rye biomass values had a mean of 3,428 kg ha −1 , a median of 2,458 kg ha −1 , and a standard deviation of 3,163 kg ha −1 . The data can be used for empirical analyses, to calibrate, validate, and evaluate process-based models, and to develop decision support tools for management and policy decisions.

  PublisherOA PDFDOI

• Methane fluxes in tidal marshes of the conterminous United States

  Global Change Biology · 2024-09-01 · 25 citations

  articleOpen access

  Abstract 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.

  PublisherOA PDFDOI

• Soil‐Judging Roundup in the Wild West

  CSA News · 2023-06-27

  articleSenior author
  PublisherDOI

• Application and evaluation of a subaqueous soil‐landscape conceptual model in the West River subestuary, Maryland

  Soil Science Society of America Journal · 2022-10-18 · 1 citations

  articleOpen accessSenior author

  Abstract A soil‐landscape conceptual model developed in the Rhode River subestuary of Maryland was applied to create a soil survey for the adjacent West River subestuary. The survey for the West River subestuary was completed before samples were collected there to evaluate the soil‐landscape conceptual model used to generate the soil survey. The West River subestuary was then sampled along transects that crossed soil map units to compare observed soil taxa with predicted soil taxa. Observed transect samples were classified and scored based on their similarity to predicted taxa in soil map units. These data were resampled via a bootstrapping method to determine if the predictions of the West River subestuary soil survey were significantly different from random predictions. Significant information was provided by the survey, and therefore by the soil‐landscape conceptual model used to generate it.

  PublisherOA PDFDOI

• A subaqueous soil‐landscape conceptual model to guide soil survey in Chesapeake Bay subestuaries

  Soil Science Society of America Journal · 2021 · 11 citations

  Senior authorCorresponding
  • Geology
  • Soil science
  • Geomorphology

  Abstract RhodeRiver, a subestuary on the western shore of Chesapeake Bay, contains a diverse array of subaqueous soils that range from submerged paleosols to fine‐textured fluid soils and organic soils. A subaqueous soil survey was completed for the Rhode River subestuary by collecting bathymetric data, delineating landforms, and sampling and describing soils across the submerged landscape. Soil map units were developed by correlating soil properties and taxonomic classification with delineated landforms, resulting in the development of seven proposed soil series corresponding to new soil map units. Geologic maps and other supporting information about the dominant factors of soil formation in this landscape were used with the soil survey of Rhode River to develop a conceptual subaqueous soil‐landscape model of soil genesis to explain the origin and distribution of soils in Rhode River. This is the first time that a subaqueous soil‐landscape model has been developed for the flooded river valley geomorphic setting of Chesapeake Bay, and it will assist subaqueous soil surveys in other western shore Chesapeake Bay subestuaries and similar environmental settings where upland environments have been or are currently submerging.

  PublisherDOI

• Changing the hierarchical placement of soil moisture regimes in Soil Taxonomy

  Soil Science Society of America Journal · 2021-01-09 · 5 citations

  articleOpen access

  Abstract Soil moisture and temperature are incorporated into Soil Taxonomy through the broad classes of moisture and temperature regimes. Although both are important variables in soil formation and land use, soil temperature regime (STR) is typically applied at the family level, whereas soil moisture regime (SMR) is applied at the suborder level. In this paper, we are questioning whether moving SMR to the family level will create a classification system that is more efficient and provide more information to the user at higher categories. The pros and cons of moving ustic, xeric, and udic SMRs from suborder to family category are discussed. To explore this potential change, we used Shannon diversity (Δ H ) as an index of the information gain moving from order to suborder when classifying a soil. The analysis indicated a relatively small Δ H for most of the country considering current suborder classes. The proposed group of suborders, characterized by diagnostic horizons instead of SMR, conveyed a considerably larger Δ H supporting a substantial gain in information if the change was incorporated into Soil Taxonomy. The proposed change also has the potential to reduce the number of subgroup taxa by nearly 50%, without losing any of the current information within each taxa. Counterarguments for the change are that SMRs have soil genesis connotations and provide a way to group similar soils on broad‐scale maps. A change in the hierarchy of SMRs within Soil Taxonomy could deemphasize the relevance of soil moisture to soil genesis, morphology, and ecology.

  PublisherOA PDFDOI

• Vegetation and hydrology stratification as proxies to estimate methane emission from tidal marshes

  Biogeochemistry · 2021 · 25 citations

  • Environmental science
  • Atmospheric sciences
  • Ecology

  Abstract Direct measurement of methane emissions is cost-prohibitive for greenhouse gas offset projects, necessitating the development of alternative accounting methods such as proxies. Salinity is a useful proxy for tidal marsh CH 4 emissions when comparing across a wide range of salinity regimes but does not adequately explain variation in brackish and freshwater regimes, where variation in emissions is large. We sought to improve upon the salinity proxy in a marsh complex on Deal Island Peninsula, Maryland, USA by comparing emissions from four strata differing in hydrology and plant community composition. Mean CH 4 chamber-collected emissions measured as mg CH 4 m −2 h −1 ranked as S. alterniflora (1.2 ± 0.3) ≫ High-elevation J. roemerianus (0.4 ± 0.06) > Low-elevation J. roemerianus (0.3 ± 0.07) = S. patens (0.1 ± 0.01). Sulfate depletion generally reflected the same pattern with significantly greater depletion in the S. alterniflora stratum (61 ± 4%) than in the S. patens stratum (1 ± 9%) with the J. roemerianus strata falling in between. We attribute the high CH 4 emissions in the S. alterniflora stratum to sulfate depletion likely driven by limited connectivity to tidal waters. Low CH 4 emissions in the S. patens stratum are attributed to lower water levels, higher levels of ferric iron, and shallow rooting depth. Moderate CH 4 emissions from the J. roemerianus strata were likely due to plant traits that favor CH 4 oxidation over CH 4 production. Hydrology and plant community composition have significant potential as proxies to estimate CH 4 emissions at the site scale.

  PublisherOA PDFDOI

Frequent coauthors

• Martin C. Rabenhorst

  University of Maryland, College Park

  13 shared

• Katherine Johnson

  National Institute of Standards and Technology

  12 shared

• Peter J. A. Kleinman

  Agricultural Research Service

  12 shared

• Michael Paolisso

  University of Maryland, College Park

  11 shared

• Lisa A. Wainger

  ORCID

  10 shared

• J. Patrick Megonigal

  Smithsonian Environmental Research Center

  10 shared

• David E. Ruppert

  9 shared

• Anna McMurray

  Wildlife Conservation Society

  9 shared

Labs

• Soil Chemical Interfaces LabPI

Awards & honors

• Ernest F. Hollings Scholar