Shrub Willow Biomass Production Ranking Across Three Harvests in New York and Minnesota
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We report that TUMME is a program for assembling and solving master equations for gas-phase chemical kinetics based on chemically significant eigenmodes. TUMME has interfaces to the Gaussian, Polyrate, and/or MSTor output files that allow the master equation code to obtain the microcanonical flux coefficients needed for the coefficient matrix of the master equation. The flux coefficients for reactions with barriers can be calculated by multi-structural variational transition state theory with small-curvature tunneling (MS-VTST/SCT) or by simpler approximations to this such as conventional transition state theory without tunneling (also called RRKM theory). The flux coefficients for barrierless reactions are provided by a hard-sphere model. TUMME is written in double precision with Python 3; quadruple and octuple precision are also available for some subtasks in C++. The Python code can run in serial or parallel (MP or MPI), and the C++ code can run on a single processor or on multiple processors with OpenMP.
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Abstract Global declines in insect populations have important implications for biodiversity and food security. To offset these declines, habitat restoration and enhancement in agricultural landscapes could mutually safeguard insect populations and their pollination services for crop production. The expansion of utility-scale solar energy development in agricultural landscapes presents an opportunity for the dual use of the land for energy production and biodiversity conservation through the establishment of grasses and forbs planted among and between the photovoltaic solar arrays (‘solar-pollinator habitat’). We conducted a longitudinal field study across 5 years (2018–2022) to understand how insect communities responded to newly established habitat on solar energy facilities in agricultural landscapes by evaluating (1) temporal changes in flowering plant abundance and diversity; (2) temporal changes in insect abundance and diversity; and (3) the pollination services of solar-pollinator habitat by comparing pollinator visitation to agricultural fields near solar-pollinator habitat with other agricultural field locations. We found increases over time for all habitat and biodiversity metrics: floral rank, flowering plant species richness, insect group diversity, native bee abundance, and total insect abundance, with the most noticeable temporal increases in native bee abundance. We also found positive effects of proximity to solar-pollinator habitat on bee visitation to nearby soybean ( Glycine max ) fields. Bee visitation to soybean flowers adjacent to solar-pollinator habitat were comparable to bee visitation to soybeans adjacent to grassland areas enrolled in the Conservation Reserve Program, and greater than bee visitation to soybean field interior and roadside soybean flowers. Our observations highlight the relatively rapid (<4 year) insect community responses to grassland restoration activities and provide support for solar-pollinator habitat as a feasible conservation practice to safeguard biodiversity and increase food security in agricultural landscapes.
The functional diversity of a community can influence ecosystem functioning and reflects assembly processes. The large number of disparate metrics used to quantify functional diversity reflects the range of attributes underlying this concept, generally summarized as functional richness, functional evenness, and functional divergence. However, in practice, we know very little about which attributes drive which ecosystem functions, due to a lack of field-based tests. Here we test the association between eight leading functional diversity metrics (Rao’s Q, FD, FDis, FEve, FDiv, convex hull volume, and species and functional group richness) that emphasize different attributes of functional diversity, plus 11 extensions of these existing metrics that incorporate heterogeneous species abundances and trait variation. We assess the relationships among these metrics and compare their performances for predicting three key ecosystem functions (above- and belowground biomass and light capture) within a long-term grassland biodiversity experiment. Many metrics were highly correlated, although unique information was captured in FEve, FDiv, and dendrogram-based measures (FD) that were adjusted by abundance. FD adjusted by abundance outperformed all other metrics in predicting both above- and belowground biomass, although several others also performed well (e.g. Rao’s Q, FDis, FDiv). More generally, trait-based richness metrics and hybrid metrics incorporating multiple diversity attributes outperformed evenness metrics and single-attribute metrics, results that were not changed when combinations of metrics were explored. For light capture, species richness alone was the best predictor, suggesting that traits for canopy architecture would be necessary to improve predictions. Our study provides a comprehensive test linking different attributes of functional diversity with ecosystem function for a grassland system.
This data set contains measurements of methane (CH4) transport by plants (both ground-layer and trees) and diffusion, as well as whole-plot emissions, taken in September 2018 and June 2019 in S1 Bog outside of the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experimental enclosures. Additionally, CH4 and carbon dioxide (CO2) stable isotope data in porewater and atmospheric emissions were taken in July 2017 in the SPRUCE enclosures to explore the relative magnitude of CH4 oxidation. Episodic ebullition rates for S1 Bog are taken from Gill et al. (2017). Methane transport is an important component of many ecosystem models of peatlands. The results were compared to two methane models that have been developed for the SPRUCE project, ELM-SPRUCE (Earth Land Model) and TECO_SPRUCE (Terrestrial ECOsystem model). This dataset contains six data files in comma separate (.csv) format. Additional metadata are provided: six data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.
This data set contains observations of photosynthetically active radiation (PAR), precipitation, soil temperature, soil volumetric water content, air temperature, relative humidity, and normalized water table depth that are summarized on a daily, weekly, monthly, and annual basis for each of the SPRUCE plots. Observations span 2015-2024. This dataset draws on several datasets (Hanson et al. 2016; Hanson et al. 2020; and Warren, unpublished data) and compiles these environmental observations into useful formats for data analysis. These environmental metrics can be used to understand the environmental conditions inside SPRUCE environmental chambers throughout the durations of the experiment and can be paired with other data for modeling and analysis. R code used to generate these files is provided as part of the data package. This dataset contains four data files in comma separate (.csv) format and a compressed folder (*.zip) containing three R (*.r) scripts. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. User note: Users must cite the original dataset/s along with this dataset when publishing any analyses using this dataset. Details on the dataset used to compile each variable are available in the header row of the files and in the user guide.
This data set contains metadata associated with peat core samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2025. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored in the SPRUCE archive and may be available for further analysis by request. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B05LW. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR.
This data set contains metadata associated with shrub-layer vegetation samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2025. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored in the SPRUCE archive and may be available for further analysis by request. See below under 7 Sample Access. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B069L. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR.
Corn (Zea mays L.) is grown across vast acreages producing massive quantities of stover making corn a desirable cellulosic bioenergy feedstock. Nitrous oxide (N 2 O) is a potent greenhouse gas (GHG) so small changes in direct soil N 2 O emissions may have substantial influence on global warming potential (GWP) from the agricultural sector. Harvesting stover alters soil properties such as soil moisture, oxygen availability, temperature, and substrate availability (C and N). Thus, harvesting stover might reduce soil N 2 O emissions by reducing substrate and by warming and drying the soil. The goal of the study was to determine how harvesting corn stover altered soil N 2 O emissions. Therefore, soil N 2 O emissions were measured for four crop-years (planting to planting) in two independent studies, one in a field managed without tillage (NT1995) and the other was in a field tilled annually with a chisel plow (Chisel). In this study, each field was in a corn–soybean (Glycine max L. [Merr.]) rotation, with (i) corn grain (Grain) only, (ii) grain plus about 50% of the stover harvested (Grain+Moderate), and (iii) grain plus harvesting as much stover as possible (Grain+Aggressive) treatments. Cumulative soil N 2 O emissions did not differ among treatments in either field during any of the crop-years monitored. Flux events occurred corresponding to fertilizer applications and to spring freeze-thaw events. Cumulative fertilizer stimulated emissions tended to be greater for corn than soybean because of N-fertilizer application. These results are valuable to modelers for enhancing estimates of the N 2 O component of the stover management C-footprint.
Are there advantages to states that adopt the most recent model building energy codes other than saving energy? For example, can the construction activity and energy savings associated with code-compliant housing units become significant sources of job creation for states if new building energy codes are adopted to cover residential construction?, The U.S. Department of Energy (DOE) Building Energy Codes Program (BECP) asked Pacific Northwest National Laboratory (PNNL) to research and ascertain whether jobs would be created in individual states based on their adoption of model building energy codes. Each state in the country is dealing with high levels of unemployment, so job creation has become a top priority. Many programs have been created to combat unemployment with various degrees of failure and success. At the same time, many states still have not yet adopted the most current versions of the International Energy Conservation Code (IECC) model building energy code, when doing so could be a very effective tool in creating jobs to assist states in recovering from this economic downturn.
This project analyzed combined condensing water heaters or boilers and hydronic air coils to provide high efficiency domestic hot water and forced air space heating. Called 'Combi' systems, they provided similar space and water heating performance less expensively than installing two condensing appliances. The system's installed costs were cheaper than installing a condensing furnace and either a condensing tankless or condensing storage water heater. However, combi costs must mature and be reduced before they are competitive with a condensing furnace and power vented water heater (EF of 0.60). Better insulation and tighter envelopes are reducing space heating loads for new and existing homes. For many homes, decreased space heating loads make it possible for both space and domestic water heating loads to be provided with a single heating plant. These systems can also eliminate safety issues associated with natural draft appliances through the use of one common sealed combustion vent.
This stormwater management plan focuses on the cantonment and training areas of the Arden Hills Army Training Site (AHATS). The plan relates the site stormwater to the regulatory framework, and it summarizes best management practices to aide site managers in promoting clean site runoff. It includes documentation for a newly developed, detailed model of stormwater flow retention for the entire AHATS property and adjacent upgradient areas. The model relies on established modeling codes integrated in a U.S. Department of Defense-sponsored software tool, the Watershed Modeling System (WMS), and it can be updated with data on changes in land use or with monitoring data.
The Local Energy Matters project advanced solar deployment in the City of Duluth, MN- a cold-climate community of 86,000. At the beginning of the project, Duluth had 254.57 kW installed solar capacity with an average cost of 5.04 USD/watt installed in 2014. The project worked with cross-sector stakeholders to benchmark the current market, implement best practices for solar deployment and soft cost reduction, develop pilot deployment programs in residential rooftop, community solar, and commercial/industrial sectors, work with the City of Duluth to determine appropriate sites for utility scale developments, and demonstrate solar pus storage. Over the three years of the project, Duluth’s installed residential and commercial solar capacity grew by 344% to 875.9 kW with an additional 702 kW solar garden capacity subscribed by Duluth residents, businesses, and institutions. Installation costs dropped 48% over this timeframe to 4.08 USD/watt installed (exclusive of solar garden construction). This report documents the process used to identify levers for increased solar installation and cost reductions in a nascent cold-climate solar market.
This report describes the methodology and results of a state cost-effectiveness analysis of ASHRAE Standard 90.1-2016. Moving to the Standard 90.1-2016 edition from Standard 90.1-2013 is found to be cost-effective for the state. Annual energy cost savings, added construction costs, and life-cycle costs are all described and presented here for various building types and climate zones.