About

Alison Hoyt is an Assistant Professor of Earth System Science at Stanford University and a Center Fellow, by courtesy, at the Woods Institute for the Environment. Her work focuses on understanding how biogeochemical cycles respond to human impacts, with a particular emphasis on the most vulnerable and least understood carbon stocks in the tropics and the Arctic. She is dedicated to advancing knowledge in these critical areas of Earth system science, contributing to the broader understanding of environmental change and sustainability.

Research topics

• Environmental science
• Geology
• Ecology
• Computer Science
• Soil science
• Physical geography
• Chemistry
• Geography
• Environmental chemistry
• Oceanography
• Biology
• Database
• Agronomy
• Earth science
• Environmental engineering
• Environmental resource management
• Geomorphology
• Atmospheric sciences

Selected publications

• Africa dominates the long-term increase in global wetland CH4 emissions due to warmer and wetter conditions

  Zenodo (CERN European Organization for Nuclear Research) · 2026-03-04 · 1 citations

  otherOpen access

  Code and data repository associated with the manuscript under review: Africa dominates the long-term increase in global wetland CH4 emissions due to warmer and wetter conditions This release provides initial repository used for DOI generation via Zenodo.

  PublisherDOI

• The underappreciated importance of small wetlands in global methane emissions

  Nature Climate Change · 2026-04-08 · 1 citations

  article
  PublisherDOI

• Comment on essd-2025-753

  2026-04-07

  peer-reviewOpen access

  <strong class="journal-contentHeaderColor">Abstract.</strong> Soil radiocarbon (¹⁴C) measurements are crucial for understanding soil carbon cycling over timescales ranging from years to millennia. However, the global synthesis and comparison of radiocarbon data has been limited due to the variety of measurement methodologies and data formats. The International Soil Radiocarbon Database (ISRaD) is an open-access, community-driven archive designed to compile soil radiocarbon data and facilitate large-scale research on soil carbon dynamics. Here, we present ISRaD version 2 (v2), which has grown significantly since its initial release in 2020. It now contains data from 515 unique studies spanning 1,669 sites globally, with over 20,000 radiocarbon observations across multiple hierarchical levels, including bulk soil layers, soil fractions, laboratory incubations, interstitial carbon in soil pores, and in situ fluxes of CO₂ and CH₄. Major updates include expanded metadata structures to capture emerging measurement techniques and an improved soil fractionation template to better capture diverse methods. There has also been a substantial increase in data from underrepresented ecosystems, including urban and cultivated soils, as well as wetlands. Despite this growth, significant geographic and data-type gaps persist. Tropical and arid regions, soils deeper than 100 cm, and certain types of measurements, including incubation, interstitial, and flux, are severely undersampled. We discuss the scientific advances enabled by ISRaD v1 and the major updates to the database and data representation. We also explore future opportunities for ISRaD and the soil radiocarbon community. ISRaD v2 continues to serve as a living archive and dynamic platform for the soil radiocarbon research community. It supports synthesis efforts that are critical for predicting how soil carbon will respond to environmental and climatic changes.

  PublisherDOI

• The International Soil Radiocarbon Database (ISRaD) version 2: Synthesis, data gaps, and future directions of soil radiocarbon data

  2026-03-09

  articleOpen access

  Abstract. Soil radiocarbon (14C) measurements are crucial for understanding soil carbon cycling over timescales ranging from years to millennia. However, the global synthesis and comparison of radiocarbon data has been limited due to the variety of measurement methodologies and data formats. The International Soil Radiocarbon Database (ISRaD) is an open-access, community-driven archive designed to compile soil radiocarbon data and facilitate large-scale research on soil carbon dynamics. Here, we present ISRaD version 2 (v2), which has grown significantly since its initial release in 2020. It now contains data from 515 unique studies spanning 1,669 sites globally, with over 20,000 radiocarbon observations across multiple hierarchical levels, including bulk soil layers, soil fractions, laboratory incubations, interstitial carbon in soil pores, and in situ fluxes of CO2 and CH4. Major updates include expanded metadata structures to capture emerging measurement techniques and an improved soil fractionation template to better capture diverse methods. There has also been a substantial increase in data from underrepresented ecosystems, including urban and cultivated soils, as well as wetlands. Despite this growth, significant geographic and data-type gaps persist. Tropical and arid regions, soils deeper than 100 cm, and certain types of measurements, including incubation, interstitial, and flux, are severely undersampled. We discuss the scientific advances enabled by ISRaD v1 and the major updates to the database and data representation. We also explore future opportunities for ISRaD and the soil radiocarbon community. ISRaD v2 continues to serve as a living archive and dynamic platform for the soil radiocarbon research community. It supports synthesis efforts that are critical for predicting how soil carbon will respond to environmental and climatic changes.

  PublisherOA PDFDOI

• Supplementary material to "The International Soil Radiocarbon Database (ISRaD) version 2: Synthesis, data gaps, and future directions of soil radiocarbon data"

  2026-03-09

  articleOpen access
  PublisherDOI

• Monitoring water level dynamics in neotropical peatlands with earth observation data

  Remote Sensing of Environment · 2026-03-03

  articleOpen access

  Intact tropical peatlands are globally important carbon stores, yet their hydrology remains poorly understood due to limited accessibility and sparse field measurements. In this study, we evaluate the potential of L-band Synthetic Aperture Radar (SAR) backscatter to monitor above-ground water level variation across diverse lowland peatland ecosystems in Colombia and Peru. Using vegetation structure metrics from GEDI with ancillary remote sensing data, we assess the sensitivity of L-band HH (L-HH) backscatter to water level changes. We observed significant linear correlations between water level and L-HH backscatter in white-sand ecosystems, palm swamp peatlands (open and forested) and seasonally flooded forests. Pole forest peatland water levels showed no correlation with L-HH backscatter. To predict these regressions, we developed ecosystem-specific multiple linear regression models using L-band HV backscatter, NDVI, and GEDI metrics, achieving strong predictive performance (R 2 = 0.8–0.94). We further tested the temporal robustness of these relationships by predicting water levels across different years. Our results demonstrate the potential of combining L-band SAR with vegetation metrics derived from spaceborne data for regional monitoring of peatland hydrology. This provides a methodological pathway for integrating tropical peatland dynamics into carbon cycle models. • L-band SAR HH backscatter correlates with water level in tropical peatland sites. • Vegetation structure controls L-band SAR sensitivity to hydrological changes. • Ecosystems with low vegetation density show strong monitoring potential. • Palm swamps and flooded forests exhibit good monitoring potential with L-band SAR. • Our approach supports the integration of peatland hydrology into carbon cycle models.

  PublisherDOI

• Insights Into the Persistence and Vulnerability of Tropical Peat Carbon Stocks From a Long‐Term Field Decomposition Experiment

  Global Biogeochemical Cycles · 2026-01-01

  articleOpen accessSenior author

  Abstract Tropical peatlands contain around one‐sixth of the global peat carbon stock. Decomposition is a key determinant of tropical peat persistence, but there is a scarcity of data on decomposition in tropical peatlands. To further understand decomposition in tropical peatlands, we conducted an 8‐year field experiment in a primary peat swamp forest in Brunei. We tracked mass loss and the organic matter composition of Shorea albida wood buried at multiple depths over 8 years, including blocks buried with and without termite exclusion mesh. The proportion of time wood blocks spent above the water table explained the majority of the variation in wood decomposition over time. Carbon loss from wood that spent &lt;1% of the time under the water table was 32.1%–86.5% higher on average than from wood that spent 30%–100% of the time under the water table. We estimate that termites enhanced wood decomposition by ∼2% per year. Despite significant decomposition, we did not observe a strong shift in wood organic matter composition. To contextualize our results, we synthesized past work on wood decomposition across tropical peatlands. We found that burial in waterlogged peat soils slows decomposition across tropical peatlands and that decomposition is also strongly influenced by peatland trophic status. Overall, our results affirm that waterlogging is the key to tropical peat persistence. Our study highlights the vulnerability of tropical peat carbon stocks to lowered water tables by either drainage or prolonged dry spells, as well as the promise of peatland rewetting to mitigate carbon losses from disturbed peatlands.

  PublisherDOI

• Tree stem methane emissions are regulated by site‐level biogeochemistry over species identity in Amazon floodplain forests

  New Phytologist · 2026-04-16

  articleOpen access

  Summary Tree stems in Amazonian floodplains emit substantial methane (CH 4 ), yet controls on emission variability remain unclear. Emissions span orders of magnitude between várzea (nutrient‐rich) and igapó (nutrient‐poor) forests and among trees, suggesting controls beyond flooding. We tested whether site‐level biogeochemistry better explains stem CH 4 variability than species identity by measuring emissions from two co‐occurring species with contrasting wood densities – Eschweilera coriacea and Hevea spruceana – across várzea and igapó forests. Emissions were paired with porewater chemistry (electrical conductivity, dissolved oxygen, dissolved CH 4 , and dissolved organic carbon), methane production potential (MPP), and root biomass. Stem CH 4 emissions were significantly higher in várzea than in igapó, independent of species or stem height. Várzea porewaters displayed higher conductivity, dissolved CH 4 and MPP, near‐neutral pH, and lower oxygen, with fine roots concentrated in the 0‐ to 50‐cm soil layer, indicating a shallow CH 4 supply zone. Basal stem emissions in várzea correlated with shallow porewater chemistry and fine‐root biomass, whereas relationships in igapó were weak. These findings show that Amazonian floodplain stem CH 4 emissions are governed by shallow site‐level biogeochemistry, rather than species identity alone and should be incorporated into basin‐scale CH 4 budgets and process models to capture spatial variability.

  PublisherDOI

• Global natural wetland methane emissions (2000–2025)

  2026-03-12

  articleOpen access

  Abstract. Wetlands are the largest natural source of atmospheric methane (CH4), yet comprehensive global budgets are typically delayed by several years, preventing a timely understanding of CH4 sources, sinks, and their trends. To reduce this delay, we present a model emulator-driven framework and accompanying workflow that enable timely, continuous emission updates and applying the framework to a global dataset of natural vegetated wetland CH4 emissions to extend the most recent Global Methane Budget (GMB; Saunois et al., 2025) record through 2025 at monthly 1°x1° resolution. We developed a machine-learning emulator to reconstruct spatially explicit monthly emission fields (global R2 =0.65 ± 0.003 (mean ± 95 % CI, hereafter) and RMSE=5.49 ± 0.12 ×10-3 Tg CH4/year in test data which is ~30 % of the total data). The emulator is trained on 35 GMB model estimates (22 process-based model estimates and 13 atmospheric inversion estimates) paired with 10 ensemble realizations of 11 gridded climate predictor variables from atmospheric reanalyses. While the global mean predicted wetland CH4 emissions for 2021–2025 (157.83 ± 2.38 Tg CH4/year) are only marginally higher (~0.05 Tg CH4/year) than the 2000–2020 baseline, this stability masks a significant hemispheric redistribution of emissions. We detect a surge in Northern Hemisphere emissions in 2021–2025, with mid- and high-latitudes increasing by 0.76 ± 0.07 (z-score: 2.21) and 0.35 ± 0.03 Tg/year (z-score:1.01), respectively, while the tropics and Southern Hemisphere extratropics show offsetting negative trends (-0.95 ± 0.19 and -0.11 ± 0.02 Tg/year with z-scores of -2.81 and -0.34, respectively). The predicted emissions capture the low emissions in 2023 in South America linked to El Niño-related drought, as reported by recent studies (Ciais et al., 2026; Quinn et al., 2025). Post-2020 growth rates of emission anomalies are a magnitude higher than that in 2000–2025, suggesting an intensification of emission variability. Furthermore, we identify a distinct seasonal amplification of global emission growth peaking in late boreal summer. This new dataset and operational framework bridge the gap between latest updated budgets and low-latency monitoring, providing a scalable capacity to frequently update global emission estimates and critical early warnings of regional wetland feedback loops. The data are publicly available at https://doi.org/10.5281/zenodo.18870108 (Li et al., 2026).

  PublisherOA PDFDOI

• Supplementary material to "Global natural wetland methane emissions (2000–2025)"

  2026-03-12

  articleOpen access
  PublisherDOI

Frequent coauthors

• Laure Gandois

  Centre de Recherche sur la Biodiversité et l'Environnement

  95 shared

• Charles F. Harvey

  Massachusetts Institute of Technology

  70 shared

• Susan Trumbore

  46 shared

• Sebastian Döetterl

  Board of the Swiss Federal Institutes of Technology

  43 shared

• Shane Stoner

  ETH Zurich

  38 shared

• Ale×ander R. Cobb

  Singapore-MIT Alliance for Research and Technology

  37 shared

• Carlos A. Sierra

  36 shared

• Sophie F. von Fromm

  Max Planck Institute for Biogeochemistry

  33 shared

Labs

• Terrestrial Carbon Cycle GroupPI

  Research Group