Public Comment on USDA Greenhouse Gas Technical Assistance Provider and Third-Party Verifier Program
The USDA recently requested public input on implementation of a program for third-parties to verify greenhouse gas emissions. The goal of the program is to “facilitate farmer, rancher, and private forest landowner participation in voluntary carbon markets.” Because the soil microbiome plays a significant role in GHG emissions in agriculture, and because we have the expertise in evaluating microbiome-driven emissions, Trace Genomics issued a public comment. The full text is below and may also be accessed here.
As the USDA works to develop regulations to implement the Greenhouse Gas (GHG) Technical Assistance Provider and Third-Party Verifier Program (the Program), they should consider solutions that go beyond traditional soil carbon diagnostics or direct measurements of chemical emissions. These methods are subject to obstacles such as high variability between analytics laboratories and difficulty scaling. Over the past decade, technology for analyzing the soil microbiome has improved significantly while at the same time becoming cheaper. Additionally, access to microbiome data has greatly increased as a result of non-academic labs offering services that include basic bioinformatic analysis. As a result, providers utilizing advances in DNA sequencing technology are able to precisely measure changes in greenhouse gas emissions in agricultural settings at scale.
Soil microbes are known to produce the GHGs methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2) (1). Considering the difficulty of measuring these gasses directly on a fine scale (2), soil microbiome analysis could be a more labor- and cost-efficient alternative to improve geospatial understanding and management of GHG emissions. Metagenomics, or sequencing all DNA in a sample, is a scalable, high-throughput, and rapid tool that can be used to analyze the species composition as well as the biological functional capacity of a soil sample (3). By examining the metagenome, different genetic pathways can be measured, including those that impact production of GHG such as methanogenesis, ammonia oxidation, nitrification, denitrification, and nitrate reduction.
In order to accurately investigate functional genes contributing to GHG production, not all DNA-based assays are created equal. Methods should be used that quantify functional genes directly, such as metagenomics or targeted assays such as qPCR. On the other hand, microbiome analysis based on amplicon sequencing uses marker genes such as 16S rDNA (bacteria, archaea) and ITS (fungi). These data only reveal the taxonomic makeup of an environment. While there are bioinformatic methods for predicting functions based on amplicon datasets, they are not nearly as robust as measuring functional genes directly (4).
Access to soil microbiome data has collateral benefits to producers and landowners for nutrient and pathogen management, including informing practices to reduce GHG emissions. In addition to data on their overall soil health and potential for GHG emissions, metagenomics provides a comprehensive test for the presence and prevalence of soil-borne pathogens (5). Unlike targeted assays that search for a single gene or pathogen, metagenomics has the capacity to use one test for any pathogen with a reference genome. Data on functional genes (such as those responsible for N2O production) are not only beneficial for GHG monitoring, but they can also be used by growers and agronomists when creating a fertility management plan. By optimizing nitrogen fertilizer input alongside other management products like nitrogen stabilizers, growers can reduce N2O emissions as well as nitrogen leaching and runoff into waterways. Similarly, genetic pathways impacting phosphorus cycling can be measured and used to optimize phosphorus inputs.
Growers have been increasingly turning to regenerative agriculture (RegenAg) practices such as reduced tillage and cover cropping to reduce their carbon footprint and improve soil health, however there are technical and institutional barriers to adoption of these practices (6). Recently, metagenomics has been incorporated into soil health evaluations and used to monitor the effectiveness of RegenAg practices. A proponent of RegenAg, the Soil Health Institute (SHI) is a nonprofit organization that brings together academic, industry, and government researchers in a cross-discipline effort to understand soil health (7).
Trace Genomics performs comprehensive soil testing by analyzing soil biology, chemistry, and carbon. Since 2015, Trace has amassed a database of soil samples covering a wide geographical area and developed tools to predict the potential for GHG emission from microbial functional profiles. Many of these samples had soil carbon analyzed and could be incorporated into a soil carbon monitoring network. Moving forward, soil samples analyzed using metagenomics can and should be incorporated into GHG emission monitoring strategies and to monitor biodiversity and soil health and resilience.
You may browse all posted comments issued in response to this request here.
References
- https://journals.asm.org/doi/10.1128/mbio.00800-22
- https://link.springer.com/chapter/10.1007/978-3-030-55396-8_2
- https://www.soilsa.com/pdf-163080-92536?filename=Metagenomics%20approaches.pdf
- https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-020-00815-y
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9280627/
- https://www.mdpi.com/2071-1050/15/3/2338
- https://soilhealthinstitute.org/about-us/vision-values/
About the author: Dr. Tuesday Simmons is the Science Communication Manager at Trace Genomics. She earned her Ph.D. in Microbiology from the University of California, Berkeley, studying the root microbiome of cereal crops.
