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At least 163 records · Page 9

Climate warming threatens the persistence of a community of disturbance-adapted native annual plants

With ongoing climate change, populations are expected to exhibit shifts in demographic performance that will alter where a species can persist. This presents unique challenges for managing plant populations and may require ongoing interventions, including in situ management or introduction into new locations. However, few studies have examined how climate change may affect plant demographic performance for a suite of species, or how effective management actions could be in mitigating climate change effects. Over the course of two experiments spanning 6 yr and four sites across a latitudinal gradient in the Pacific Northwest, United States, here we manipulated temperature, precipitation, and disturbance intensity, and quantified effects on the demography of eight native annual prairie species. Each year we planted seeds and monitored germination, survival, and reproduction. We found that disturbance strongly influenced demographic performance and that seven of the eight species had increasingly poor performance with warmer conditions. Across species and sites, we observed 11% recruitment (the proportion of seeds planted that survived to reproduction) following high disturbance, but just 3.9% and 2.3% under intermediate and low disturbance, respectively. Moreover, mean seed production following high disturbance was often more than tenfold greater than under intermediate and low disturbance. Importantly, most species exhibited precipitous declines in their population growth rates (λ) under warmer-than-ambient experimental conditions and may require more frequent disturbance intervention to sustain populations. Aristida oligantha, a C4 grass, was the only species to have λ increase with warmer conditions. These results suggest that rising temperatures may cause many native annual plant species to decline, highlighting the urgency for adaptive management practices that facilitate their restoration or introduction to newly suitable locations. Frequent and intense disturbances are critical to reduce competitors and promote native annuals’ persistence, but even such efforts may prove futile under future climate regimes.

54 ENVIRONMENTAL SCIENCES↗

Engineering integration in elementary science classrooms: Effects of disciplinary language scaffolds on English learners' content learning and engineering identity

Abstract Background Limited research examines the effects of integrated science and engineering (SE) instruction emphasizing disciplinary literacy and language activities on engineering identity and content understanding. Far fewer studies target English learners (ELs). Purpose The impact of an SE intervention on the development of science, engineering, and technology knowledge as well as engineering identity was examined. To address ELs' learning needs, the curricular design was built on a validated SE model by integrating (1) developmental, (2) language scaffolds, and (3) culturally based accommodations. Design/Method Separate analysis of variance examined the effects of the intervention on science, engineering, and technology knowledge as well as engineering identity. The relationship among engineering identity and content outcomes was also examined. ELs from kindergarten to second grade classrooms were randomly assigned to the integrated SE group or control group. Results Integrated SE instruction significantly increased ELs' science, engineering, and technology knowledge as well as a substantially developed engineering identity. Overall, ELs' engineering identity is associated with an increase in science, engineering, and technology content knowledge. However, second grade girls' identity development was not associated with learning measures. These correlations suggest the context of the engineering activity may have reinforced gendered stereotypes and reduced the effects for girls' engineering attitudes. Conclusions Integrated SE instruction emphasizing disciplinary literacy and cultural accommodations increases early elementary ELs' learning and engineering identity. Future studies should examine the unique effects of language scaffolds and cultural modifications on student learning and the impact of gender stereotypes on girls' engineering attitudes.

Aguirre‐Muñoz, Zenaida↗

Comparing the effect of virtual and in-person instruction on students’ performance in a design for additive manufacturing learning activity

The goal of this work is to compare the outcome of a design for additive manufacturing (DfAM) heuristics lesson conducted in a virtual learning environment to the same in an in-person learning environment. Prior work revealed that receiving DfAM heuristics at different points in the design process impacts the quality and novelty of designs produced afterward, but this work may have been limited by the solely virtual format. In this work, an identical experiment was performed in a face-to-face learning environment. Results indicate that neither learning format presents an advantage over the other when it comes to the quality of designs produced during the intervention. Participants across all experimental groups reported an increase in self-efficacy after the intervention, with improved performance on quiz-type questions. Furthermore, the novelty and variety of the designs produced by the in-person experimental groups were significantly lower than that of the virtual experimental groups. In addition to validating the effectiveness of virtual instruction as a teaching method, these results also support the authors’ hypothesis that the priming effect is stronger in an in-person classroom than in a virtual classroom.

Design for additive manufacturing↗

A holistic framework integrating plant-microbe-mineral regulation of soil bioavailable nitrogen

Abstract Soil organic nitrogen (N) is a critical resource for plants and microbes, but the processes that govern its cycle are not well-described. To promote a holistic understanding of soil N dynamics, we need an integrated model that links soil organic matter (SOM) cycling to bioavailable N in both unmanaged and managed landscapes, including agroecosystems. We present a framework that unifies recent conceptual advances in our understanding of three critical steps in bioavailable N cycling: organic N (ON) depolymerization and solubilization; bioavailable N sorption and desorption on mineral surfaces; and microbial ON turnover including assimilation, mineralization, and the recycling of microbial products. Consideration of the balance between these processes provides insight into the sources, sinks, and flux rates of bioavailable N. By accounting for interactions among the biological, physical, and chemical controls over ON and its availability to plants and microbes, our conceptual model unifies complex mechanisms of ON transformation in a concrete conceptual framework that is amenable to experimental testing and translates into ideas for new management practices. This framework will allow researchers and practitioners to use common measurements of particulate organic matter (POM) and mineral-associated organic matter (MAOM) to design strategic organic N-cycle interventions that optimize ecosystem productivity and minimize environmental N loss.

Environmental Sciences & Ecology↗

Design and implementation of dynamic I/O control scheme for large scale distributed file systems

In this paper, we have analyzed the input/output (I/O) activities of Cori, which is a high-performance computing system at the National Energy Research Scientific Computing Center at Lawrence Berkeley National Laboratory. Our analysis results indicate that most users do not adjust storage configurations but rather use the default settings. In addition, owing to the interference from many applications running simultaneously, the performance varies based on the system status. To configure file systems autonomously in complex environments, we developed DCA-IO, a dynamic distributed file system configuration adjustment algorithm that utilizes the system log information to adjust storage configurations automatically. Our scheme aims to improve the application performance and avoid interference from other applications without user intervention. Moreover, DCA-IO uses the existing system logs and does not require code modifications, an additional library, or user intervention. To demonstrate the effectiveness of DCA-IO, we performed experiments using I/O kernels of real applications in both an isolated small-sized Lustre environment and Cori. Our experimental results shows that our scheme can improve the performance of HPC applications by up to 263% with the default Lustre configuration.

97 MATHEMATICS AND COMPUTING↗

Socio-Structural and Neighborhood Predictors of Incident Criminal Justice Involvement in a Population-Based Cohort of Young Black MSM and Transgender Women

Black men who have sex with men (MSM) and transgender women are disproportionately affected by criminal justice involvement (CJI) and HIV. This study recruited 618 young Black MSM and transgender women in Chicago, IL, using respondent-driven sampling between 2013 and 2014. Random effects logistic regression evaluated predictors of incident CJI over 18 months of follow-up. We report, controlling for respondent age, gender and sexual identity, spirituality (aOR 0.56, 95% CI 0.33-0.96), and presence of a mother figure (aOR 0.41, 95% CI 0.19-0.89) were protective against CJI. Economic hardship (financial or residential instability vs. neither aOR 2.23, 95% CI 1.10-4.51), two or more past episodes of CJI vs. none (aOR 2.66, 95% CI 1.40-5.66), and substance use (marijuana use vs. none aOR 2.79, 95% CI 1.23-6.34; other drug use vs. none aOR 4.49, 95% CI 1.66-12.16) were associated with CJI during follow-up. Research to identify and leverage resilience factors that can buffer the effects of socioeconomic marginalization may increase the effectiveness of interventions to address the socio-structural factors that increase the risk for CJI among Black MSM and transgender women. Given the intersection of incarceration, HIV and other STIs, and socio-structural stressors, criminal justice settings are important venues for interventions to reduce health inequities in these populations.

60 APPLIED LIFE SCIENCES↗

Development of a field-deployable qPCR assay for real-time pest monitoring in algal cultivation systems

Outdoor cultivation is commonly used to produce algal biomass for a variety of bioproducts including food, feed, fuel, pharmaceuticals, and nutraceuticals. Outdoor cultivation ponds are highly susceptible to pest pressures that may lead to periods of low productivity or even entire loss of the algal crop. Consequently, there is a need for rapid, real-time tracking of pests for early intervention to mitigate crop loss. In this work, we describe the development of a field deployable, low-cost qPCR assay for detecting both known and novel pests of a farmed eukaryotic alga species, Nannochloropsis sp. We performed a proximity guided metagenome deconvolution approach (ProxiMeta™) to discover novel pests that temporally correspond to periods of reduced pond productivity. This approach provided high-quality metagenome assemblies that were used to design qPCR probes to detect specific pests of interest. The portable qPCR assay, designed to be deployed at remote field locations, enables low-cost surveillance with a rapid (2 h) turn-around time. Frequent sampling allows for early detection and prompts intervention strategies to remedy infected ponds to minimize crop loss. The qPCR assay was used to successfully detect a known predatory bacterium within the order Bdellovibrionales both in the lab and at a remote field location. Furthermore, we assembled the genome of two novel, site-specific pests in the Saprospiraceae family and successfully designed qPCR probes that differentially detected their presence in two different pond locations. Ultimately, this assay has the potential to monitor multiple pests simultaneously and tailor targets to match likely pest infections that differ across geographical locations, helping to mitigate crop loss on a large scale.

59 BASIC BIOLOGICAL SCIENCES↗

Technologies and policies to decarbonize global industry: Review and assessment of mitigation drivers through 2070

Fully decarbonizing global industry is essential to achieving climate stabilization, and reaching net zero greenhouse gas emissions by 2050–2070 is necessary to limit global warming to 2 °C. This paper assembles and evaluates technical and policy interventions, both on the supply side and on the demand side. It identifies measures that, employed together, can achieve net zero industrial emissions in the required timeframe. Key supply-side technologies include energy efficiency (especially at the system level), carbon capture, electrification, and zero-carbon hydrogen as a heat source and chemical feedstock. There are also promising technologies specific to each of the three top-emitting industries: cement, iron & steel, and chemicals & plastics. These include cement admixtures and alternative chemistries, several technological routes for zero-carbon steelmaking, and novel chemical catalysts and separation technologies. Crucial demand-side approaches include material-efficient design, reductions in material waste, substituting low-carbon for high-carbon materials, and circular economy interventions (such as improving product longevity, reusability, ease of refurbishment, and recyclability). Strategic, well-designed policy can accelerate innovation and provide incentives for technology deployment. High-value policies include carbon pricing with border adjustments or other price signals; robust government support for research, development, and deployment; and energy efficiency or emissions standards. These core policies should be supported by labeling and government procurement of low-carbon products, data collection and disclosure requirements, and recycling incentives. In implementing these policies, care must be taken to ensure a just transition for displaced workers and affected communities. Similarly, decarbonization must complement the human and economic development of low- and middle-income countries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The sum is greater than the parts: exploiting microbial communities to achieve complex functions

We report multi-species microbial communities are ubiquitous in nature. The widespread prevalence of these communities is due to highly elaborated interactions among their members thereby accomplishing metabolic functions that are unattainable by individual members alone. Harnessing these communal capabilities is an emerging field in biotechnology. The rational intervention of microbial communities for the purpose of improved function has been facilitated in part by developments in multi-omics approaches, synthetic biology, and computational methods. Recent studies have demonstrated the benefits of rational interventions to human and animal health as well as agricultural productivity. Emergent technologies, such as in situ modification of complex microbial community and community metabolic modeling, represent an avenue to engineer sustainable microbial communities. In this opinion, we review relevant computational and experimental approaches to study and engineer microbial communities and discuss their potential for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗

The impact of behavioral and geographic heterogeneity on residential-sector carbon abatement costs

Analyses of monetary and emissions savings from residential efficiency upgrades usually neglect behavioral differences between consumers. Variations in behavior are frequently large: 13% of the U.S. population sets thermostats for cooling at 20 °C (68 °F) or lower and 15% at 25.5 °C (78 °F) or higher. Efficiency analyses should account for behavioral heterogeneity as well as variations in climate and housing characteristics. We model energy and economic savings of efficiency upgrades for U.S. single-family detached houses, accounting for differences in thermostat settings, climate zone, fuel prices, and home characteristics. We consider five efficiency interventions: wall insulation, attic insulation, air sealing, high-efficiency furnaces, and high-efficiency air conditioners. Energy and economic savings vary widely by consumer; the average net present value for wall insulation is $3,020 United States Dollar (USD), but considering heterogeneity, it has a 10th percentile value of -$231 and 90th percentile value of $5,000. Neglecting heterogeneity, technology upgrades can be prioritized from lower to higher carbon abatement costs: air conditioners, wall insulation, furnace, air sealing, and attic insulation. Accounting for heterogeneity reorders this prioritization, and consumer-specific conditions affect mitigation costs such that technologies are mixed in with one another and are no longer arranged one after another. These results indicate that interventions to improve efficiency should consider differences between consumers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Computational design and engineering of an Escherichia coli strain producing the nonstandard amino acid para -aminophenylalanine

Introducing heterologous pathways into host cells constitutes a promising strategy for synthesizing nonstandard amino acids (nsAAs) to enable the production of proteins with expanded chemistries. However, this strategy has proven challenging, as the expression of heterologous pathways can disrupt cellular homeostasis of the host cell. Here, we sought to optimize the heterologous production of the nsAA para -aminophenylalanine (pAF) in Escherichia coli . First, we incorporated a heterologous pAF biosynthesis pathway into a genome-scale model of E. coli metabolism and computationally identified metabolic interventions in the host’s native metabolism to improve pAF production. Next, we explored different approaches of imposing these flux interventions experimentally and found that the upregulation of flux in the chorismate biosynthesis pathway through the elimination of feedback inhibition mechanisms could significantly raise pAF titers (~20-fold) while maintaining a reasonable pAF production-growth rate trade-off. Overall, this study provides a promising strategy for the biosynthesis of nsAAs in engineered cells.

59 BASIC BIOLOGICAL SCIENCES↗

Bundling measures for food systems transformation: a global, multimodel assessment

Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.

Sundiang, Marina [Cornell Univ., Ithaca, NY (Unite↗

Optimizing quantification of MK6240 tau PET in unimpaired older adults

Accurate measurement of Alzheimer's disease (AD) pathology in older adults without significant clinical impairment is critical to assessing intervention strategies aimed at slowing AD-related cognitive decline. The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (POINTER) is a 2-year randomized controlled trial to evaluate the effect of multicomponent risk reduction strategies in older adults (60-79 years) who are cognitively unimpaired but at increased risk for cognitive decline/dementia due to factors such as cardiovascular disease and family history. The POINTER Imaging ancillary study is collecting tau-PET ([ 18 F]MK6240), beta-amyloid (Aβ)-PET ([ 18 F]florbetaben [FBB]) and MRI data to evaluate neuroimaging biomarkers of AD and cerebrovascular pathophysiology in this at-risk sample. Here 481 participants (70.0±5.0; 66% F) with baseline MK6240, FBB and structural MRI scans were included. PET scans were coregistered to the structural MRI which was used to create FreeSurfer-defined reference regions and target regions of interest (ROIs). We also created off-target signal (OTS) ROIs to examine the magnitude and distribution of MK6240 OTS across the brain as well as relationships between OTS and age, sex, and race. OTS was unimodally distributed, highly correlated across OTS ROIs and related to younger age and sex but not race. Aiming to identify an optimal processing approach for MK6240 that would reduce the influence of OTS, we compared our previously validated MRI-guided standard PET processing and 6 alternative approaches. The alternate approaches included combinations of reference region erosion and meningeal OTS masking before spatial smoothing as well as partial volume correction. To compare processing approaches we examined relationships between target ROIs (entorhinal cortex (ERC), hippocampus or a temporal meta-ROI (MetaROI)) SUVR and age, sex, race, Aβ and a general cognitive status measure, the Modified Telephone Interview for Cognitive Status (TICSm). Overall, the processing approaches performed similarly, and none showed a meaningful improvement over standard processing. Across processing approaches we observed previously reported relationships with MK6240 target ROIs including positive associations with age, an Aβ+> Aβ- effect and negative associations with cognition. In sum, we demonstrated that different methods for minimizing effects of OTS, which is highly correlated across the brain within subject, produced no substantive change in our performance metrics. This is likely because OTS contaminates both reference and target regions and this contamination largely cancels out in SUVR data. Caution should be used when efforts to reduce OTS focus on target or reference regions in isolation as this may exacerbate OTS contamination in SUVR data.

60 APPLIED LIFE SCIENCES↗

Identifying mitigation strategies for $\mathrm{COVID}$-$\mathrm{19}$ superspreading on flights using models that account for passenger movement

Despite commercial airlines mandating masks, there have been multiple documented events of COVID-19 superspreading on flights. Conventional models do not adequately explain superspreading patterns on flights, with infection spread wider than expected from proximity based on passenger seating. An important reason for this is that models typically do not consider the movement of passengers during the flight, boarding, or deplaning. Understanding the risks for each of these aspects could provide insight into effective mitigation measures. We modeled infection risk from seating and fine-grained movement patterns – boarding, deplaning, and inflight movement. We estimated infection model parameters from a prior superspreading event. We validated the model and the impact of interventions using available data from three flights, including cabin layout and seat locations of infected and uninfected passengers, to suggest interventions to mitigate COVID-19 superspreading events during air travel. Specifically, we studied: 1) London to Hanoi with 201 passengers, including 13 secondary infections among passengers; 2) Singapore to Hangzhou with 321 passengers, including 12 to 14 secondary infections; 3) a non-superspreading event on a private jet in Japan with 9 passengers and no secondary infections. Here our results show that the inclusion of passenger movement better explains the infection spread patterns than conventional models do. We also found that FFP2/N95 mask usage would have reduced infection by 95–100%, while cloth masks would have reduced it by only 40–80%. Results indicate that leaving the middle seat vacant is effective in reducing infection, and the effectiveness increases when combined with good quality masks. However, with a good mask, the risk is quite low even without the middle seats being empty. Our results suggest the need for more stringent guidelines to reduce aviation-related superspreading events of COVID-19.

54 ENVIRONMENTAL SCIENCES↗

A modeling framework for designing and evaluating curbside traffic management policies at Dallas-Fort Worth International Airport

Emerging mobility technologies are changing the transportation system landscape. This is especially evident at airports, such as the Dallas-Fort Worth International Airport (DFW). Without careful analysis, these changes could lead to inefficient and costly airport operations. This paper presents a modeling framework that integrates travel mode encoding, demand projection, and microsimulation to enable airports to develop, simulate, and evaluate curbside traffic managements policies and measure their impact. Here, the framework is utilized to analyze several traffic scenarios and policies for DFW: a baseline scenario which represents DFW traffic pattern as observed in 2018 and projected to 2045, a transit network company (TNC) electrification policy, a TNC queuing policy, a policy that increased transit ridership, a bus-only policy which considers the use of only buses inside DFW, an autonomous vehicle (AV) policy which investigates the impact of autonomous vehicle (AV) adoption on airport operations, and an example COVID-19 scenario which models the impact of the COVID19 pandemic. The simulations’ results demonstrate that: increasing the DFW transit ridership postpones the need for airport curbside expansion the most; encouraging shared-mobility with the bus-only policy produces the most savings in curbside congestion delays; automation and electrification for all passenger vehicle trips to/from DFW generates the most saving in fuel consumption and emissions; and uncontrolled AV adoption incurs the highest increase in fuel consumption, delay, and emissions and could require immediate airport capacity extension. Without policy intervention or investment in additional infrastructure capacity, these results predict the current operations would face significant congestion on high demand days starting as early as 2028. While derived in close partnership with DFW, the methodology presented here can be generalized to any airport.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Sixty days of head-down tilt bed rest with or without artificial gravity do not affect the neuromuscular secretome

Highlights: • Long-term bed rest with/without artificial gravity does not affect the neuromuscular secretome. • Serum concentrations of markers of muscle wasting are not affected by bed rest/artificial gravity. • C-terminal Agrin Fragment serum concentrations are not affected by bed rest/artificial gravity. • Human centrifugation during bed rest does not have a negative impact on the neuromuscular secretome. Artificial gravity is a potential countermeasure to attenuate effects of weightlessness during long-term spaceflight, including losses of muscle mass and function, possibly to some extent attributable to disturbed neuromuscular interaction. The 60-day AGBRESA bed-rest study was conducted with 24 participants (16 men, 8 women; 33 ± 9 years; 175 ± 9 cm; 74 ± 10 kg; 8 control group, 8 continuous (cAG) and 8 intermittent (iAG) centrifugation) to assess the impact of bed rest with or without daily 30-min continuous/intermittent centrifugation with 1G at the centre of mass. Fasting blood samples were collected before and on day 6, 20, 40 and 57 during 6° head-down tilt bed rest. Concentrations of circulating markers of muscle wasting (GDF-8/myostatin; slow skeletal muscle troponin T; prostaglandin E2), neurotrophic factors (BDNF; GDNF) and C-terminal Agrin Fragment (CAF) were determined by ELISAs. Creatine kinase activity was assessed by colorimetric enzyme assay. Repeated-measures ANOVAs were conducted with TIME as within-subject, and INTERVENTION and SEX as between-subject factors. The analyses revealed no significant effect of bed rest or sex on any of the parameters. Continuous or intermittent artificial gravity is a safe intervention that does not have a negative impact of the neuromuscular secretome.

60 APPLIED LIFE SCIENCES↗

Pilot plant reliability metrics for grinding and fast pyrolysis of woody residues

Here we report on the effects of loblolly pine residue variability on material throughput, pilot plant uptime, operator intervention, product yield, and product quality for grinding, fast pyrolysis, and hydrotreating operations. Preprocessing throughput using a hammer mill varied between 31-48% of nameplate capacity (5 tons/hr). Grinder overloads in the size reduction step were more prevalent for lower ash and higher moisture materials. Fast pyrolysis throughput varied between 57-72% of nameplate capacity (20 kg/hr) and bio-oil yields varied between 46-53% (feedstock carbon to oil, dry basis). During fast pyrolysis operations, downtime was caused by bridging in the feed and char removal systems and plugging in the condensation system. Cohesion of feedstock and char leading to system plugging was less frequent for higher ash feedstocks, and differences in condenser plugging behavior between high and low ash feedstocks were observed. The catalyst stability of the bio-oil stabilization step was strongly dependent on the sulfur content in the bio-oil, which was higher for the high-ash residue oils. Lower moisture content in the starting biomass was consistent with lower sulfur content in bio-oil. Yields and properties of hydrotreated fuel products showed minimal deference among the bio-oils.

Klinger, Jordan↗

Cycles-L: A Coupled, 3-D, Land Surface, Hydrologic, and Agroecosystem Landscape Model

Managing landscapes to increase agricultural productivity and environmental stewardship can be informed by spatially-distributed models that operate at spatial and temporal scales that are intervention-relevant. This paper presents Cycles-L, a landscape-scale agroecosystem and hydrologic modeling system, using as a test case a watershed in Pennsylvania. Cycles-L emerges from melding the landscape and hydrology structure of Flux-PIHM, a 3-D land surface hydrologic model, with the agroecosystem processes in the Cycles model. Consequently, Cycles-L can simulate processes affected by topography, soil heterogeneity, and management practices, owing to its physically-based hydrology that can simulate horizontal and vertical transport of solutes with water. The model was tested at a 730-ha experimental watershed within the Mahantango Creek watershed. Cycles-L simulated well stream water and mineral nitrogen discharge (Nash-Sutcliffe coefficient 0.55 and 0.60, respectively) and grain yield (root mean square error 1.2 Mg ha -1 ). Cycles-L outputs are as good or better than those obtained with the uncoupled Flux-PIHM (water discharge) and Cycles (grain yield) models. Modeled spatial patterns of nitrogen fluxes like denitrification illustrate the combined control of crop management and topography. For example, denitrification is almost twice as high when simulated with Cycles-L than when simulated with Cycles 1-D. Due to its spatial and temporal resolution, Cycles-L fills a gap in the availability of models that operate at a scale relevant to evaluate interventions in the landscape. Cycles-L can become a central component in tools for climate change scenario analysis, precision agriculture, precision conservation, and artificial intelligence-based decision support systems.

54 ENVIRONMENTAL SCIENCES↗