on a county level for the entire USA (including AK and HI where possible), considering all removal methods that are currently well-enough developed for us to estimate the likely costs in 2050. We anticipate that more than 1 Gt CO2e of removal will be available to the Nation. We will identify how much of each CO2 removal approach is available in specific regions of the Nation and provide cumulative costs and volumes (a supply curve) by region for 2050. We expect to complete this detailed analysis by late 2023.

Achieving more sustainable production of food, fiber and energy and reducing environmental burdens from agricultural systems is a global challenge. Meeting this challenge will create new opportunities for producers to provide a broader range of ecosystem services, including reducing greenhouse gas emissions (and sequestering more carbon) in their production systems. To meet these new objectives, land managers will need new decision tools and performance metrics. The COMET-Farm system was designed to fill this need by incorporating state-of-the-art greenhouse gas quantification methods into a web-based tool that can be used by farmers, ranchers, land managers and others. The system is capable of doing a full greenhouse gas assessment for CO2, CH4, and N2O, from all major on-farm emission sources (and CO2 removal into biomass and soil sinks), including land management of annual and perennial crops, pasture, range and agroforestry systems, as well as emissions from livestock and on-farm energy use. The system uses a fully spatial mapping and menu-driven graphical user interface (GUI) to facilitate data entry and evaluation of user-defined conservation practices. In this paper we provide an overview of the system and a description of the user interface and integrated databases in the system. We follow this with a brief description of the models and data requirements for the major emission source categories in the system. We illustrate the application of the system using examples of emission reductions from adoption of different conservation management practices and discuss how the tool can help meet needs for different policy-and market-driven greenhouse gas reduction efforts.

Conservation planners must assess a range of environmental, agronomic and economic impacts of implementing conservation practices on farms. While environmental impacts such as soil erosion control, improved soil quality, reduced nonpoint source pollution and a number of other sitespecific benefits are currently considered, conservation practices may also have significant climate benefits, through carbon sequestration and/or reduction of greenhouse gas (GHG) emissions. If conservation planners wish to incorporate greenhouse gas impacts in their planning process, they will need access to quick, easy-to-use tools to assess greenhouse gas impacts of conservation practices on farms. COMET-Planner (www.comet-planner.com) was developed to provide generalized estimates of GHG impacts of adoption of USDA National Resources Conservation Service (NRCS) conservation practice standards in a simple, web-based platform. Conservation scenarios were modeled in COMETFarm, a whole farm and ranch carbon and greenhouse gas accounting system based on USDA entityscale quantification methods, across a range of agricultural management, climate and soil types within Major Land Resource Areas (MLRA). Mean carbon sequestration and emission changes (CO2, N2O and CH4) associated with USDA-NRCS conservation practice adoption were estimated by MLRA. Results are provided to users via the web interface and a detailed methods report.

Liquid chromatography coupled to electrospray ionization-mass spectrometry (LC-ESI-MS) is a versatile and robust platform for metabolomic analysis. However, while ESI is a soft ionization technique, in-source phenomena including multimerization, nonproton cation adduction, and in-source fragmentation complicate interpretation of MS data. Here, we report chromatographic and mass spectrometric behavior of 904 authentic standards collected under conditions identical to a typical nontargeted profiling experiment. The data illustrate that the often high level of complexity in MS spectra is likely to result in misinterpretation during the annotation phase of the experiment and a large overestimation of the number of compounds detected. However, our analysis of this MS spectral library data indicates that in-source phenomena are not random but depend at least in part on chemical structure. These nonrandom patterns enabled predictions to be made as to which in-source signals are likely to be observed for a given compound. Using the authentic standard spectra as a training set, we modeled the in-source phenomena for all compounds in the Human Metabolome Database to generate a theoretical in-source spectrum and retention time library. A novel spectral similarity matching platform was developed to facilitate efficient spectral searching for nontargeted profiling applications. Taken together, this collection of experimental spectral data, predictive modeling, and informatic tools enables more efficient, reliable, and transparent metabolite annotation.

Phaeodactylum tricornutum is a widely used model organism for studying diatom biology. We created a P. tricornutum-specific literature database, or bibliome, that can be interactively annotated by users to improve the relevance and accuracy of search queries. A bibliome represents the current knowledge about a specific organism or biological process and is the foundation for genome-scale computation models. The bibliome of P. tricornutum was assembled from literature searches of ‘P. tricornutum’ (as topic) in two different existing databases, the Web of Knowledge and PubMed resulting in 2497 independent articles. We manually curated the bibliome for relevance to biochemical, physiological, and molecular biology studies. Literature that described the use of P. tricornutum as feed source and ecotoxicology studies were excluded from the bibliome. This process resulted in a final list of 1124 entries – 20% of which received additional classification in the form of notes or keywords. We present the bibliome in an HTML format that is easily searched and that can be customized according to the interests of individual researchers. This HTML tool can also easily be adapted for other algal species or specific research topics.