Katherine EO Todd-Brown
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View article: Synthesis of a National Soil Dataset Across Productive Land in Mexico: The Importance of Making Existing Data Accessible
Synthesis of a National Soil Dataset Across Productive Land in Mexico: The Importance of Making Existing Data Accessible Open
The lack of soil data is a complication that most soil scientists will encounter throughout their career; this critical aspect is exacerbated due to the excessive cost of soil surveying. Consequently, it is essential to develop strategies …
View article: Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands
Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands Open
Decomposition is the transformation of dead organic matter into its inorganic constituents. In most biomes, decomposition rates can be accurately predicted with simple mathematical models, but these models have long under‐predicted decompo…
View article: Sustainability Nexus AID: soil health
Sustainability Nexus AID: soil health Open
The Sustainability Nexus Analytics, Informatics, and Data (AID) Programme of the United Nations University (UNU), aims to provide information, data, computational, and analytical tools to support the sustainable management and long-term se…
View article: Open Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement
Open Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement Open
Soil spectroscopy is a widely used method for estimating soil properties that are important to environmental and agricultural monitoring. However, a bottleneck to its more widespread adoption is the need for establishing large reference da…
View article: Cohort Marsh Equilibrium Model (CMEM): History, Mathematics, and Implementation
Cohort Marsh Equilibrium Model (CMEM): History, Mathematics, and Implementation Open
Marsh accretion models predict the resiliency of coastal wetlands and their ability to store carbon in the face of accelerating sea level rise. Most existing marsh accretion models are derived from two parent models: the Marsh Equilibrium …
View article: Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction
Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction Open
Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biologic…
View article: Upscaling Soil Organic Carbon Measurements at the Continental Scale Using Multivariate Clustering Analysis and Machine Learning
Upscaling Soil Organic Carbon Measurements at the Continental Scale Using Multivariate Clustering Analysis and Machine Learning Open
Estimates of soil organic carbon (SOC) stocks are essential for many environmental applications. However, significant inconsistencies exist in SOC stock estimates for the U.S. across current SOC maps. We propose a framework that combines u…
View article: The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy
The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy Open
Quantifying carbon fluxes into and out of coastal soils is critical to meeting greenhouse gas reduction and coastal resiliency goals. Numerous ‘blue carbon’ studies have generated, or benefitted from, synthetic datasets. However, the commu…
View article: Open Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement
Open Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement Open
Soil spectroscopy is a widely used method for estimating soil properties that are important to environmental and agricultural monitoring. However, a bottleneck to its more widespread adoption is the need for establishing large reference da…
View article: An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter
An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter Open
Diffuse reflectance spectroscopy has been extensively employed to deliver timely and cost-effective predictions of a number of soil properties. However, although several soil spectral laboratories have been established worldwide, the disti…
View article: Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning
Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning Open
Estimates of soil organic carbon (SOC) stocks are essential for many environmental applications. However, significant inconsistencies exist in SOC stock estimates for the U.S. across current SOC maps. We propose an upscaling framework that…
View article: Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning
Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning Open
Data Description: To improve SOC estimation in the United States, we upscaled site-based SOC measurements to the continental scale using multivariate geographic clustering (MGC) approach coupled with machine learning models. First, we used…
View article: Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning
Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning Open
Data Description: To improve SOC estimation in the United States, we upscaled site-based SOC measurements to the continental scale using multivariate geographic clustering (MGC) approach coupled with machine learning models. First, we used…
View article: Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning
Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning Open
Data Description: To improve SOC estimation in the United States, we upscaled site-based SOC measurements to the continental scale using multivariate geographic clustering (MGC) approach coupled with machine learning models. First, we used…