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SPRUCE Measurements of Fine Root Production and Chemistry from Root Ingrowth Cores, Marcell Experimental Forest, Minnesota, 2022-2023

This dataset contains fine root production and tissue chemistry measurements from root ingrowth cores. Ingrowth cores were deployed in peat from June 28, 2022 to June 24, 2023 (2022-06-28 to 2023-06-24) inside SPRUCE Experiment plots at the Marcell Experimental Forest in northern Minnesota. The warming and elevated carbon dioxide (CO2) treatments in this dataset include +0 degrees Celsius (C) (+0 and +500 parts per million (ppm) elevated CO2), +4.5 degrees C (+0 and +500 ppm elevated CO2) and +9 degrees C (+0 and +500 ppm elevated CO2) for both hummocks and hollows, as well as +2.25 degrees C (+0 and +500 ppm) and +6.75 degrees C (+0 and +500 ppm) for hollows from minimum 10 cm depth from the peat surface. Measurements include root average diameter, root length, root biomass, and root tissue nitrogen (%N and δ15N) and carbon (%C and δ13C) concentration per plant functional type and microtopographical feature. Root length and biomass are standardized to 10 cm depth. These data were used to assess the warming and elevated CO2 response of fine roots across different peatland microtopographical features (hummocks and hollows) and plant functional types (shrub, spruce and larch). 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.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

Impact of Drought on Ecohydrology of Southern California Grassland and Shrubland

Abstract Through their rooting profiles and water demands, plants affect the distribution of water in the soil profile. Simultaneously, soil water content controls plant development and interactions within and between plant communities. These plant-soil water feedbacks might vary across plant communities with different rooting depths and species composition. In semiarid environments, understanding these differences will be essential to predict how ecosystems will respond to drought, which may become more frequent and severe with climate change. In this study, we tested how plant-soil water feedbacks responded to drought in two contrasting ecosystem types—grassland and shrubland—in the coastal foothills of southern California. During years 5–8 of an ongoing precipitation manipulation experiment, we measured changes in plant communities and soil moisture up to 2 m depth. We observed different water use patterns in grassland and shrubland communities with distinct plant functional types and water use strategies. Drought treatment did not affect perennial, deep-rooted shrubs because they could access deep soil water pools. However, mid-rooted shrubs were sensitive to drought and experienced decreased productivity and die-off. As a result, water content actually increased with drought at soil depths from 50–150 cm. In grassland, biomass production by annual species, including annual grasses and forbs, declined with drought, resulting in lower water uptake from the surface soil layer. An opportunistic “live fast, die young“ life strategy allowed these species to recover quickly once water availability increased. Our results show how drought interacts with plant community composition to affect the soil water balance of semiarid ecosystems, information that could be integrated into global scale models.

54 ENVIRONMENTAL SCIENCES↗

Satellite-Based Evidence for Shrub and Graminoid Tundra Expansion in Northern Quebec from 1986-2010

Global vegetation models predict rapid poleward migration of tundra and boreal forest vegetation in response to climate warming. Local plot and air-photo studies have documented recent changes in high-latitude vegetation composition and structure, consistent with warming trends. To bridge these two scales of inference, we analyzed a 24-year (1986-2010) Landsat time series in a latitudinal transect across the boreal forest-tundra biome boundary in northern Quebec province, Canada. This region has experienced rapid warming during both winter and summer months during the last forty years. Using a per-pixel (30 m) trend analysis, 30% of the observable (cloud-free) land area experienced a significant (p < 0.05) positive trend in the Normalized Difference Vegetation Index (NDVI). However, greening trends were not evenly split among cover types. Low shrub and graminoid tundra contributed preferentially to the greening trend, while forested areas were less likely to show significant trends in NDVI. These trends reflect increasing leaf area, rather than an increase in growing season length, because Landsat data were restricted to peak-summer conditions. The average NDVI trend (0.007/yr) corresponds to a leaf-area index (LAI) increase of ~0.6 based on the regional relationship between LAI and NDVI from the Moderate Resolution Spectroradiometer (MODIS). Across the entire transect, the area-averaged LAI increase was ~0.2 during 1986-2010. A higher area-averaged LAI change (~0.3) within the shrub-tundra portion of the transect represents a 20-60% relative increase in LAI during the last two decades. Our Landsat-based analysis subdivides the overall high-latitude greening trend into changes in peak-summer greenness by cover type. Different responses within and among shrub, graminoid, and tree-dominated cover types in this study indicate important fine-scale heterogeneity in vegetation growth. Although our findings are consistent with community shifts in low-biomass vegetation types over multi-decadal time scales, the response in tundra and forest ecosystems to recent warming was not uniform.

McManus, K. M.↗

Seasonal Distribution of African Savanna Fires

Savannas consist of a continuous layer of grass interspersed with scattered trees or shrubs, and cover approx. 10 million square kilometers of tropical Africa. African savanna fires, almost all resulting from human activities, may produce as much as a third of the total global emissions from biomass burning. Little is known, however, about the frequency and location of these fires, and the area burned each year. Emissions from African savanna burning are known to be transported over the mid-Atlantic, south Pacific and Indian oceans; but to study fully the transport of regional savanna burning and the seasonality of the atmospheric circulation must be considered simultaneously. Here we describe the temporal and spatial distribution of savanna fires over the entire African continent, as determined from night-time satellite imagery. We find that, contrary to expectations, most fires are left to burn uncontrolled, so that there is no strong diurnal cycle in the fire frequency. The knowledge gained from this study regarding the distribution and variability of fires will aid monitoring of the climatically important trace gases emitted from burning biomass.

Cahoon, Donald R.↗

Aboveground carbon loss associated with the spread of ghost forests as sea levels rise

Coastal forests sequester and store more carbon than their terrestrial counterparts but are at greater risk of conversion due to sea level rise. Saltwater intrusion from sea level rise converts freshwater-dependent coastal forests to more salt-tolerant marshes, leaving 'ghost forests' of standing dead trees behind. Although recent research has investigated the drivers and rates of coastal forest decline, the associated changes in carbon storage across large extents have not been quantified. We mapped ghost forest spread across coastal North Carolina, USA, using repeat Light Detection and Ranging (LiDAR) surveys, multi-temporal satellite imagery, and field measurements of aboveground biomass to quantify changes in aboveground carbon. Between 2001 and 2014, 15% (167 km2) of unmanaged public land in the region changed from coastal forest to transition-ghost forest characterized by salt-tolerant shrubs and herbaceous plants. Salinity and proximity to the estuarine shoreline were significant drivers of these changes. This conversion resulted in a net aboveground carbon decline of 0.13 ± 0.01 TgC. Because saltwater intrusion precedes inundation and influences vegetation condition in advance of mature tree mortality, we suggest that aboveground carbon declines can be used to detect the leading edge of sea level rise. Aboveground carbon declines along the shoreline were offset by inland aboveground carbon gains associated with natural succession and forestry activities like planting (2.46 ± 0.25 TgC net aboveground carbon across study area). Our study highlights the combined effects of saltwater intrusion and land use on aboveground carbon dynamics of temperate coastal forests in North America. By quantifying the effects of multiple interacting disturbances, our measurement and mapping methods should be applicable to other coastal landscapes experiencing saltwater intrusion. As sea level rise increases the landward extent of inundation and saltwater exposure, investigations at these large scales are requisite for effective resource allocation for climate adaptation. In this changing environment, human intervention, whether through land preservation, restoration, or reforestation, may be necessary to prevent aboveground carbon loss.

ghost forests↗

Aeronet-based Microphysical and Optical Properties of Smoke-dominated Aerosol near Source Regions and Transported over Oceans, and Implications for Satellite Retrievals of Aerosol Optical Depth

Smoke aerosols from biomass burning are an important component of the global aerosol cycle. Analysis of Aerosol Robotic Network (AERONET) retrievals of size distribution and refractive index reveals variety between biomass burning aerosols in different global source regions, in terms of aerosol particle size and single scatter albedo (SSA). Case studies of smoke transported to coastal/island AERONET sites also mostly lie within the range of variability at near-source sites. Two broad families of aerosol properties are found, corresponding to sites dominated by boreal forest burning (larger, broader fine mode, with midvisible SSA 0.95), and those influenced by grass, shrub, or crop burning with additional forest contributions (smaller, narrower particles with SSA 0.88-0.9 in the midvisible). The strongest absorption is seen in southern African savanna at Mongu (Zambia), with average SSA 0.85 in the midvisible. These can serve as candidate sets of aerosol microphysicaloptical properties for use in satellite aerosol optical depth (AOD) retrieval algorithms. The models presently adopted by these algorithms over ocean are often insufficiently absorbing to represent these biomass burning aerosols. A corollary of this is an underestimate of AOD in smoke outflow regions, which has important consequences for applications of these satellite datasets.

AERONET↗

Effects of Rapid Permafrost Thaw on CO2 and CH4 Fluxes in a Warmer and Wetter Future (Final Technical Report)

When ice-rich permafrost thaws, the ground subsides, creating thermokarst landscapes with dramatically different soil conditions and carbon fluxes than the original ecosystem. Roughly 20% of the northern permafrost region is susceptible to thermokarst formation (Olefeldt et al., 2016). Thermokarst formation is often rapid; tens of meters of permafrost can thaw within a few years (Schuur et al., 2015). In topographically low areas, thermokarst thaw converts boreal forest or tundra dry shrub ecosystems into sedge or Sphagnum moss wetlands (Olefeldt et al., 2016). While this type of landscape transformation releases carbon stored in permafrost into the atmosphere, on longer time scales, it facilitates sequestration of atmospheric carbon in plant biomass because permafrost thaw releases plant-available nutrients and wetlands are highly productive (M. C. Jones et al., 2017). However, wetlands also generate methane, which is a potent greenhouse gas. Methane emissions from thermokarst wetlands can cause these carbon-sequestering systems to have a positive global warming potential (Johansson et al., 2006; Turetsky et al., 2007). Our project objective was to improve Earth System and environmental predictability by advancing understanding of how CO 2 and CH 4 flux in permafrost thaw-induced wetlands (thermokarst) will change in the future as temperatures and climate conditions shift. Northern latitudes are expected to get warmer and wetter (IPCC 2013), and initiation and expansion of thermokarst thaw is expected to increase (Jorgenson et al. 2006; Zhang et al. 2017). Given these expected changes, our work sought to address three broad questions: Q1) How will northern latitude CO2 and CH4 emissions respond to warming temperatures? Q2) What is the impact of precipitation on permafrost thaw and carbon emissions? Q3) How do CO2 and CH4 emissions change as wetlands age after permafrost thaw? To answer these questions, we took both a modeling and measurement approach. Modeling work was conducted with DOE’s Energy Exascale Earth System Model (E3SM) land model (ELM). Empirical work took place in two primary locations. The first was a thermokarst site near Fairbanks, AK. The site is part of the Bonanza Creek Long Term Ecological Research program and is well instrumented (Neumann et al., 2019). The second was an isolated thawing permafrost wetland located on Kenai Peninsula — Brown’s Lake bog (B. M. Jones et al., 2016) — where the current climate is representative of what is expected at higher latitudes in the future. This site provides an ideal opportunity to test our hypotheses about how thermokarst wetland dynamics will respond to future environmental conditions. In addition, the project collaborated with researchers asking similar questions who were collecting measurements in high latitude post-glacial lakes located in collaborators tackling similar questions in Sweden (Stordalen Mire) (Emerson et al., 2021). Project efforts directly aligned with the stated goal of the funding opportunity announcement (FOA), which was “to improve the understanding and representation of terrestrial ecosystems in ways that advance Earth system model parameterizations and capabilities... thereby improving the quality of Earth and environmental model projections and providing the scientific foundation needed to support DOE’s science and energy missions.” Specifically, the project improved sophistication and accuracy of the Energy Exascale Earth System Model (E3SM), which is being developed primarily at DOE National Laboratories to support scientific research and decision-making.

54 ENVIRONMENTAL SCIENCES↗

Regional Feedstock Partnership Biomass Quality Assessment Final Report

The United States (U.S.) Department of Energy (DOE) developed the Billion-Ton Vision to enable production of one-billion tons of sustainable, reliable biomass for the bioenergy industry by 2030 (Perlack et al., 2005). The Sun Grant Regional Feedstock Partnership (RFP) was organized to fill information gaps and validate biomass yield assumptions related to the Billion-Ton Study (Owens, 2018; Owens, Karlen, and Lacey, 2016). Along with the more than 130 scientific publications generated from these studies, yield and sustainability data from the RFP field trials not only validated the Billion-Ton estimates, but were critical in developing both the U.S. Billion-Ton Update report in 2011 and the 2016 Billion-Ton Report (DOE, 2011; 2016). The intention of this biomass quality assessment report is to build on these initial successes from the RFP field trials by focusing on variability in biomass quality data necessary to evaluate conversion performance. This report contains a summary of chemical quality results from samples collected as part of the RFP field trials. This report focuses on assessment of the impact of experimental agronomic designs on biomass properties followed by analyses of the impact of environmental and production variables on biomass properties. Datasets include species and other genetic variables, fertilizer treatments, harvest information, and yield, as well as other publicly available data such as precipitation, temperature, soil properties, and drought. The key outcomes from this chemical quality focused assessment have included: • Complete evaluation of the impacts of agronomic designs, genetics, and environmental conditions on chemical properties for Miscanthus, switchgrass, sorghum, energycane, mixed perennial grasses, and shrub willow short-rotation feedstocks • Over 30 peer review publications and technical reports focused on variability in quality data • Development of spatial and temporal environmental quality prediction maps for Miscanthus and switchgrass feedstocks allowing for comprehensive evaluation of variability in feedstock chemical quality across U.S. regions and over multiple harvest years

09 BIOMASS FUELS↗

Resistance, Resilience, and Recovery of Dryland Soil Bacterial Communities Across Multiple Disturbances

Dryland ecosystems are sensitive to perturbations and generally slow to recover post disturbance. The microorganisms residing in dryland soils are especially important as they contribute to soil structure and nutrient cycling. Disturbance can have particularly strong effects on dryland soil structure and function, yet the natural resistance and recovery of the microbial components of dryland soils has not been well documented. In this study, the recovery of surface soil bacterial communities from multiple physical and environmental disturbances is assessed. Samples were collected from three field sites in the vicinity of Moab, UT, United States, 6 to 7 years after physical and climate disturbance manipulations had been terminated, allowing for the assessment of community recovery. Additionally, samples were collected in a transect that included three habitat patches: the canopy zone soils under the dominant shrubs, the interspace soils that are colonized by biological soil crusts, and edge soils at the plot borders. Field site and habitat patch were significant factors structuring the bacterial communities, illustrating that sites and habitats harbored unique soil microbiomes. Across the different sites and disturbance treatments, there was evidence of significant bacterial community recovery, as bacterial biomass and diversity were not significantly different than control plots. There was, however, a small number of 16S rRNA gene amplicon sequence variants that distinguished particular treatments, suggesting that legacy effects of the disturbances still remained. Taken together, these data suggest that dryland bacterial communities may possess a previously unappreciated potential to recover within years of the original disturbance.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site-level Applications of the CLM-Microbe Model

Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for the realistic projections of soil carbon (C) and climate dynamics. The CLM-Microbe model builds upon the CLM4.5 and explicitly represents two major soil microbial groups, fungi and bacteria. Based on the compiled time-series data of fungal (FBC) and bacterial (BBC) biomass C from nine biomes, we parameterized and validated the CLM-Microbe model, and further conducted sensitivity analysis and uncertainty analysis for simulating C cycling. The model performance was evaluated with mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) for relative change in FBC and BBC. The CLM-Microbe model is able to reasonably capture the seasonal dynamics of FBC and BBC across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland, with MAE < 0.49 for FBC and <0.36 for BBC and RMSE <0.52 FBC and <0.39 for BBC, while R2 values are relatively smaller in some biomes (e.g., shrub) due to small sample sizes. We found good consistencies between simulated and observed FBC (R 2 =0.70, P<0.001) and BBC (R 2 =0.26, P<0.05) on average across biomes, but the model is not able to fully capture the large variation in observed FBC and BBC. Sensitivity analysis shows the most critical parameters are turnover rate, carbon-to-nitrogen ratio of fungi and bacteria, and microbial assimilation efficiency. This study confirms that the explicit representation of soil microbial mechanisms enhances model performance in simulating C variables such as heterotrophic respiration and soil organic C density. The further application of the CLM-Microbe model would deepen our understanding of microbial contributions to the global C cycle.

54 ENVIRONMENTAL SCIENCES↗

Optimizing Carbon Cycle Parameters Drastically Improves Terrestrial Biosphere Model Underestimates of Dryland Mean Net CO 2 Flux and its Inter-Annual Variability

Drylands occupy ~40% of the land surface and are thought to dominate global carbon (C) cycle inter-annual variability (IAV). Therefore, it is imperative that global terrestrial biosphere models (TBMs), which form the land component of IPCC earth system models, are able to accurately simulate dryland vegetation and biogeochemical processes. However, compared to more mesic ecosystems, TBMs have not been widely tested or optimized using in situ dryland CO 2 fluxes. Here, for this work, we address this gap using a Bayesian data assimilation system and 89 site-years of daily net ecosystem exchange (NEE) data from 12 southwest US Ameriflux sites to optimize the C cycle parameters of the ORCHIDEE TBM. The sites span high elevation forest ecosystems, which are a mean sink of C, and low elevation shrub and grass ecosystems that are either a mean C sink or “pivot” between an annual C sink and source. We find that using the default (prior) model parameters drastically underestimates both the mean annual NEE at the forested mean C sink sites and the NEE IAV across all sites. Our analysis demonstrated that optimizing phenology parameters are particularly useful in improving the model's ability to capture both the magnitude and sign of the NEE IAV. At the forest sites, optimizing C allocation, respiration, and biomass and soil C turnover parameters reduces the underestimate in simulated mean annual NEE. Our study demonstrates that all TBMs need to be calibrated for dryland ecosystems before they are used to determine dryland contributions to global C cycle variability and long-term carbon-climate feedbacks.

59 BASIC BIOLOGICAL SCIENCES↗

The red edge in arid region vegetation: 340-1060 nm spectra

The remote sensing study of vegetated regions of the world has typically been focused on the use of broad-band vegetation indices such as NDVI. Various modifications of these indices have been developed in attempts to minimize the effect of soil background, e.g., SAVI, or to reduce the effect of the atmosphere, e.g., ARVI. Most of these indices depend on the so-called 'red edge,' the sharp transition between the strong absorption of chlorophyll pigment in visible wavelengths and the strong scattering in the near-infrared from the cellular structure of leaves. These broadband indices tend to become highly inaccurate as the green canopy cover becomes sparse. The advent of high spectral resolution remote sensing instrument such as the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) has allowed the detection of narrow spectral features in vegetation and there are reports of detection of the red edge even for pixels with very low levels of green vegetation cover by Vane et al. and Elvidge et al., and to characterize algal biomass in coastal areas. Spectral mixing approaches similar to those of Smith et al. can be extended into the high spectral resolution domain allowing for the analysis of more endmembers, and potentially, discrimination between material with narrow spectral differences. Vegetation in arid regions tends to be sparse, often with small leaves such as the creosote bush. Many types of arid region vegetation spend much of the year with their leaves in a senescent state, i.e., yellow, with lowered chlorophyll pigmentation. The sparseness of the leaves of many arid region plants has the dual effect of lowering the green leaf area which can be observed and of allowing more of the sub-shrub soil to be visible which further complicates the spectrum of a region covered with arid region vegetation. Elvidge examined the spectral characteristics of dry plant materials showing significant differences in the region of the red edge and the diagnostic ligno-cellulose absorptions at 2090 nm and 2300 nm. Ray et al. detected absorption at 2100 nm in AVIRIS spectra of an abandoned field known to be covered by a great deal of dead plant litter. In order to better study arid region vegetation remote sensing data, it is necessary to better characterize the reflectance spectra of in situ, living, arid region plants.

Ray, Terrill W.↗

AIS spectra of desert shrub canopies

Airborne Imaging Spectrometer (AIS) data were collected 30 August 1985 from a desert shrub community in central Oregon. Spectra from artificial targets placed on the test site and from bare soil, big sagebrush (Artemesia tridentata wyomingensis), silver sagebrush (Artemesia cana bolander), and exposed volcanic rocks were studied. Spectral data from grating position 3 (tree mode) were selected from 25 ground positions for analysis by Principal Factor Analysis (PFA). In this grating position, as many as six factors were identified as significant in contributing to spectral structure. Channels 74 through 84 (tree mode) best characterized between-class differences. Other channels were identified as nondiscriminating and as associated with such errors as excessive atmospheric absorption and grating positin changes. The test site was relatively simple with the two species (A. tridentata and A. cana) representing nearly 95% of biomass and with only two mineral backgrounds, a montmorillonitic soil and volcanic rocks. If, as in this study, six factors of spectral structure can be extracted from a single grating position from data acquired over a simple vegetation community, then AIS data must be considered rich in information-gathering potential.

Murray, R.↗

Coupling Remote Sensing With a Process Model for the Simulation of Rangeland Carbon Dynamics

Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring carbon (C) fluxes in rangelands are challenging due to the considerable spatial and temporal variability tied to rangeland C dynamics as well as limited data availability. We developed the Rangeland Carbon Tracking and Management (RCTM) system to track long-term changes in SOC and ecosystem C fluxes by leveraging remote sensing inputs and environmental variable data sets with algorithms representing terrestrial C-cycle processes. Bayesian calibration was conducted using quality-controlled C flux data sets obtained from 61 Ameriflux and NEON flux tower sites from Western and Midwestern US rangelands to parameterize the model according to dominant vegetation classes (perennial and/or annual grass, grass-shrub mixture, and grass-tree mixture). The resulting RCTM system produced higher model accuracy for estimating annual cumulative gross primary productivity (GPP) (R 2 > 0.6, RMSE <390 g C m -2 ) relative to net ecosystem exchange of CO 2 (NEE) (R 2 > 0.4, RMSE <180 g C m -2 ). Model performance in estimating rangeland C fluxes varied by season and vegetation type. The RCTM captured the spatial variability of SOC stocks with R 2 = 0.6 when validated against SOC measurements across 13 NEON sites. Model simulations indicated slightly enhanced SOC stocks for the flux tower sites during the past decade, which is mainly driven by an increase in precipitation. Future efforts to refine the RCTM system will benefit from long-term network-based monitoring of vegetation biomass, C fluxes, and SOC stocks.

54 ENVIRONMENTAL SCIENCES↗

Nonadditive gene expression is correlated with nonadditive phenotypic expression in interspecific triploid hybrids of willow ( Salix spp.)

Many studies have highlighted the complex and diverse basis for heterosis in inbred crops. Despite the lack of a consensus model, it is vital that we turn our attention to understanding heterosis in undomesticated, heterozygous, and polyploid species, such as willow (Salix spp.). Shrub willow is a dedicated energy crop bred to be fast-growing and high yielding on marginal land without competing with food crops. A trend in willow breeding is the consistent pattern of heterosis in triploids produced from crosses between diploid and tetraploid species. Here, we test whether differentially expressed genes are associated with heterosis in triploid families derived from diploid Salix purpurea, diploid Salix viminalis, and tetraploid Salix miyabeana parents. Three biological replicates of shoot tips from all family progeny and parents were collected after 12 weeks in the greenhouse and RNA extracted for RNA-Seq analysis. This study provides evidence that nonadditive patterns of gene expression are correlated with nonadditive phenotypic expression in interspecific triploid hybrids of willow. Expression-level dominance was most correlated with heterosis for biomass yield traits and was highly enriched for processes involved in starch and sucrose metabolism. In addition, there was a global dosage effect of parent alleles in triploid hybrids, with expression proportional to copy number variation. Importantly, differentially expressed genes between family parents were most predictive of heterosis for both field and greenhouse collected traits. Altogether, these data will be used to progress models of heterosis to complement the growing genomic resources available for the improvement of heterozygous perennial bioenergy crops.

59 BASIC BIOLOGICAL SCIENCES↗

Life Cycle Emissions and Health Cost Impacts of Producing Ethanol and Electricity from Willow and Switchgrass in the Riparian Buffers of Mid-Atlantic United States

The United States (US Mid-Atlantic Region (MAR) has the potential to grow a variety of perennial feedstocks such as switchgrass and shrub willow to increase domestic energy production. These cellulosic feedstocks have also shown improved ecosystem services, such as soil carbon sequestration, nitrate leaching reduction, and flood mitigation along rivers and streams as partially harvested riparian buffers. To examine the effects on greenhouse gases (GHGs) and criteria air pollutants (CAPs) from using these feedstocks to produce ethanol or electricity, we conducted a comprehensive life cycle assessment (LCA) and estimated the impact on human health costs when land use is changed from corn production for ethanol. Results indicate up to 54% reduced GHG per hectare from using willow and switchgrass feedstock sources to produce ethanol instead of corn. However, there was a trade-off in terms of CAP emission, as grass-based energy emitted more NO x and SO x compared to the corn ethanol pathway, except for SO X emissions from willow-based electricity. Electricity from cellulosic biomass had higher particulate matter (PM) emission compared to that from corn ethanol. Estimates for health cost to society ranged from $2498 ha –1 for electricity from switchgrass to a net benefit of $448 ha –1 for ethanol production from willow, depending on varying biomass yield under different market scenarios. Although using cellulosic feedstocks to produce bioenergy has great potential to reduce GHG emissions, CAP control measures are needed to manage CAP-induced health costs.

Bioenergy↗

Invertebrate and Plant Community Diversity of an Illinois Corn–Soybean Field with Integrated Shrub Willow Bioenergy Buffers

Perennial bioenergy crop production within intensively managed agricultural landscapes has the potential to improve the sustainability, resiliency, and diversity of these landscapes. Perennial crops are ideal because of their high production potential on marginal lands relative to grain crops (e.g., corn and soybean) and their ability to provide additional ecosystem service benefits. When agricultural landscapes are designed to target specific services, determining the non-targeted services of perennial bioenergy crops can further promote their adoption. This 3-year study addresses this proposition by evaluating the canopy invertebrates and understory plant (non-target crop) communities using bee bowls and point measurement of ground coverage, respectively, within a grain field integrated with shrub willow buffer systems designed for nutrient loss reduction. Greater plant diversity and richness were observed under willow than under grain, resembling that of the surrounding riparian community with more perennial, native species. However, the same relationship did not hold true for invertebrates, with seasonality having a significant influence resulting in similar communities observed in willow and grain plots. The presence of unique plant and invertebrate species in both willow and grain crops as well as foraging pollinators on both crop and non-target crop species highlights the importance of habitat heterogeneity for supporting biodiversity and the potential benefits of buffer bioenergy landscape designs.

09 BIOMASS FUELS↗

Impact of landscape design on the greenhouse gas emissions of shrub willow bioenergy buffers in a US Midwest corn-production landscape

Previous studies have evaluated the economics and ecosystem services of perennial bioenergy crops when replacing grain crops on marginal (environmentally critical and/or underproductive) lands. This study used life-cycle analysis (LCA) to investigate the greenhouse gas (GHG) emissions of perennial crops when grown in targeted landscape positions and their impact in reducing nitrogen leaching. Specifically, LCA was performed to evaluate the GHG emissions of growing shrub willow on marginal lands in the Indian Creek watershed in Illinois to assess the sustainability of strategically planted willow buffer strips. Willow was grown as a short-rotation woody crop with a 21-year rotation under three scenarios including a business-as-usual (BAU) field-scale production with nitrogen fertilizer application and two unfertilized subfield buffer scenarios – landscape single subfield (LSSF) or landscape multiple subfields (LMSF) – grown alongside cornfields to reduce nitrate leaching. Each scenario also considers three field sizes, 2.0, 10.1, and 40.5 ha. The average annual GHG emissions from willow production and depot transportation were 0.32–0.77 Mg-CO 2 e ha-1 with the lowest emissions for the LSSF scenario and highest for the BAU. The GHG emissions for the LSSF and BAU scenarios are independent of field size, whereas LMSF emissions increase with increasing field size, 0.41 Mg-CO 2 e ha-1 at 2.0 ha and 0.76 Mg-CO 2 e ha-1 at 40.5 ha. Emission results were most sensitive to the willow yield, followed by fertilizer application rate (BAU only), harvest fuel consumption, and transportation distance.

09 BIOMASS FUELS↗