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At least 541 records · Page 30

Past and present disturbances generate spatial variation in seed predation

Seed survival is a key process for plant populations; variation in the activity and abundance of animals that consume seeds can lead to dramatic shifts in seed fate. Because granivores may respond to contemporary disturbance as well as to enduring changes in habitats caused by past disturbances, understanding seed fate requires studies capable of evaluating how past and present disturbances modify granivore communities, foraging activity, and ultimately, seed predation. Historic agricultural land use and contemporary canopy harvesting are widespread disturbances that could generate large-scale patterns of seed fate by modifying environmental characteristics that determine granivore identity and behavior. Here, to evaluate whether land-use history and canopy harvesting affect seed–animal interactions, we conducted an experiment distributed across 80,000 ha of longleaf pine woodlands that coupled large-scale canopy harvesting at seven 4-ha sites containing both post-agricultural land use and nonagricultural land use in South Carolina, United States. We deployed a total of 28,000 nail-tagged seeds and recovered the tags to quantify seed fate. Past agricultural land use and contemporary canopy harvesting interacted to affect the rate of seed predation. Seed predation rates in harvested sites depended on land-use history: Seed predation was 30% lower in post-agricultural plots than in nonagricultural plots. This interaction was driven by the differential effect of land-use history and canopy harvesting on rodent activity. Camera traps revealed that Sigmodon hispidus only foraged in harvested plots and was most active in nonagricultural plots. In harvested plots, seed removal increased with S. hispidus activity. In unharvested plots, seed removal increased with Sciurus niger activity, but S. niger was not affected by land-use history. In finding that land-use history and canopy harvesting determine the outcomes of seed–animal interactions, we show that understanding patterns of seed predation is contingent upon the interplay of disturbances in both the distant past and recent past. These results suggest that patterns of past land use and present land use may help reconcile the considerable variation in seed fate observed in ecological communities.

60 APPLIED LIFE SCIENCES↗

Internet-Based Approaches to Building Stakeholder Networks for Conservation and Natural Resource Management

Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing internet-based social networks, and use an existing traditional (survey-based) case study to illustrate in a familiar context the deviations in methods and results. Internet-based approaches to SNA offer a means to overcome institutional hurdles to conducting survey-based SNA, provide unique insight into an institution’s web presences, allow for easy snowballing (iterative process that incorporates new nodes in the network), and afford monitoring of social networks through time. The internet-based approaches differ in link definition: hyperlink is based on links on a website that redirect to a different website and relatedness links are based on a Google’s ‘‘relatedness’’ operator that identifies pages ‘‘similar’’ to a URL. All networks were initiated with the same start nodes [members of a conservation alliance for the Calumet region around Chicago (n = 130)], but the resulting networks vary drastically from one another. Interpretation of the resulting networks is highly contingent upon how the links were defined.

54 ENVIRONMENTAL SCIENCES↗

Efficacy of a Self-expanding Tract Sealant Device in the Reduction of Pneumothorax and Chest Tube Placement Rates After Percutaneous Lung Biopsy: A Matched Controlled Study Using Propensity Score Analysis

PurposeTo evaluate the use of a self-expanding tract sealant device (BioSentry™) on the rates of pneumothorax and chest tube insertion after percutaneous lung biopsy.Materials and MethodsIn this retrospective study, we compared 318 patients who received BioSentry™ during percutaneous lung biopsy (treated group) with 1956 patients who did not (control group). Patient-, lesion-, and procedure-specific variables, and pneumothorax and chest tube insertion rates were recorded. To adjust for potential selection bias, patients in the treated group were matched 1:1 to patients in the control group using propensity score matching based on the above-mentioned variables. Patients were considered a match if the absolute difference in their propensity scores was ≤equal to 0.02.ResultsBefore matching, the pneumothorax and chest tube rates were 24.5 and 13.1% in the control group, and 21.1 and 8.5% in the treated group, respectively. Using propensity scores, a match was found for 317 patients in the treatment group. Chi-square contingency matched pair analysis showed the treated group had significantly lower pneumothorax (20.8 vs. 32.8%; p = 0.001) and chest tube (8.2 vs. 20.8%; p < 0.0001) rates compared to the control group. Sub-analysis including only faculty who had >30 cases of both treatment and control cases demonstrated similar findings: the treated group had significantly lower pneumothorax (17.6 vs. 30.2%; p = 0.002) and chest tube (7.2 vs. 18%; p = 0.001) rates.ConclusionsThe self-expanding tract sealant device significantly reduced the pneumothorax rate, and more importantly, the chest tube placement rate after percutaneous lung biopsy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

The impact of positron range on PET resolution, evaluated with phantoms and PHITS Monte Carlo simulations for conventional and non-conventional radionuclides

The increasing interest and availability of non-standard positron-emitting radionuclides has heightened the relevance of radionuclide choice in the development and optimization of new positron emission tomography (PET) imaging procedures, both in preclinical research and clinical practice. Differences in achievable resolution arising from positron range can largely influence application suitability of each radionuclide, especially in small-ring preclinical PET where system blurring factors due to annihilation photon acollinearity and detector geometry are less significant. Here, some resolution degradation can be mitigated with appropriate range corrections implemented during image reconstruction, the quality of which is contingent on an accurate characterization of positron range.

43 PARTICLE ACCELERATORS↗

Determination of Gas-Phase Ion Structures of Locally Polar Homopolymers Through High-Resolution Ion Mobility Spectrometry–Mass Spectrometry

The strong synergy arising from coupling two orthogonal analytical techniques such as ion mobility and mass spectrometry can be used to separate complex mixtures and determine structural information of analytes in the gas phase. A tandem study is performed using two systems with different gases and pressures to ascertain gas-phase conformations of homopolymer ions. Aside from spherical and stretched configurations, intermediate configurations formed by a multiply charged globule and a “bead-on-a-string” appendix are confirmed for polyethylene-glycol (PEG), polycaprolactone (PCL), and polydimethylsiloxane (PDMS). These intermediate configurations are shown to be ubiquitous for all charge states and masses present. For each charge state, configurations evolve in two distinctive patterns: an inverse evolution which occurs as an elementary charge attached to the polymer leaves the larger globule and incorporates itself into the appendage, and a forward evolution which reduces the globule without relinquishing a charge while leaving the appendix relatively constant. Forward evolutions are confirmed to form self-similar family shapes that transcend charge states for all polymers. Identical structural changes occur at the same mass over charge regardless of the system, gas or pressure strongly suggesting that conformations are only contingent on number of charges and chain length, and start arranging once the ion is at least partially ejected from the droplet, supporting a charge extrusion mechanism. Configurational changes are smoother for PDMS which is attributed to the larger steric hindrance caused by protruding pendant groups. This study has implications in the study of the configurational space of more complex homopolymers and heteropolymers. .

74 ATOMIC AND MOLECULAR PHYSICS↗

A complete grain-level assessment of the stress-strain evolution and associated deformation response in polycrystalline alloys

Polycrystalline alloys are used pervasively across structural applications contingent upon extensive experimental testing. A statistically representative number of tests are required to expose the variability in the material's performance, as a result of non-uniform microstructures and associated micromechanical fields. In a more direct means of capturing this pertinent information, multi-modal experimental techniques are presented to measure and track the complete micromechanical state, evolving during loading, of each and every grain within the regions of interest. Specifically, a combination of high-energy X-ray diffraction microscopy and digital image correlation coupled with electron backscatter diffraction are conducted on a specimen for each of the alloys, Haynes 282 and Ti7Al. The results of the multi-modal analysis definitively demonstrate that the degree of heterogeneity increases with deformation level and is used to assess the number of grains necessary for a representative volume element description of the stress state for each of these materials. Moreover, higher resolution imaging is used for identification of the slip system activity and subsequently used to study slip transmission events. An accurate knowledge of the resolved shear stress in adjacent grains (grain interactions) is demonstrated to be a key descriptor of the slip transmission events.

36 MATERIALS SCIENCE↗

Merging a mechanistic enzymatic model of soil heterotrophic respiration into an ecosystem model in two AmeriFlux sites of northeastern USA

Heterotrophic respiration (Rh), microbial processing of soil organic matter to carbon dioxide (CO 2 ), is a major, yet highly uncertain, carbon (C) flux from terrestrial systems to the atmosphere. Temperature sensitivity of Rh is often represented with a simple Q 10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed as a way to disentangle the confounding factors of apparent temperature sensitivity of Rh and improve the performance of ecosystem models and ESMs. The objective of this work was to insert into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh and evaluate the model performance in terms of soil and ecosystem respiration. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen, soluble C substrates, and extracellular enzymes to the enzymatic reaction site. Here, we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration). We used high-frequency soil flux data from automated soil chambers and landscape-scale ecosystem fluxes from eddy covariance towers at two AmeriFlux sites (Harvard Forest, MA and Howland Forest, ME) in the northeastern USA to estimate parameters, validate the merged model, and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal and inter-annual dynamics of soil respiration (Soil R) compared to the FöBAAR-only model for the Harvard Forest, where higher frequency and duration of drying events significantly regulate substrate supply to heterotrophs. However, DAMM-FöBAAR showed improvement over FöBAAR-only at the boreal transition Howland Forest only in unusually dry years. The frequency of synoptic-scale dry periods is lower at Howland, resulting in only brief water limitation of Rh in some years. At both sites, the declining trend of soil R during drying events was captured by the DAMM-FöBAAR model; however, model performance was also contingent on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the model-data mismatch. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than the wide variety of empirical functions that are commonly used, and these DAMM functions could be readily incorporated into other ecosystem models and ESMs.

54 ENVIRONMENTAL SCIENCES↗

H 2 -optimal transactive control of electric power regulation from fast-acting demand response in the presence of high renewables

Here, this paper presents an H 2 -optimal power regulation scheme for balancing authorities to provide regulation services using both generation and load resources in the presence of a significant amount of intermittent renewable generation. The optimal controller is designed to minimize the loss of total economic surplus due to deviations from the schedule because of generation contingencies. The results show that the optimal controller outperforms the conventional ACE control policy by (1) providing faster return to the schedule under varying demand response levels, (2) reducing the cost of using reserve units for regulation services, and (3) minimizing deviations from the global surplus-maximizing schedule.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Integration of optimal operational dispatch and controller determined dynamics for microgrid survivability

We present that the reliability and resilience of the electrical power grids are essential to industry, economy and society. Microgrids that are able to island from the bulk electrical grid are one technology that may vastly improve electrical power service to customer loads. To achieve these improvements, an islanded microgrid should be able to operate through the loss of one of its generators without shedding electrical load. The loss of one generator will typically result in significant additional loads, including transient overloads, being placed on the remaining generators. There is also the possibility of additional generator tripping during these processes (i.e. cascading failures), which would likely result in the collapse of the microgrid. The novelty of our work consists in incorporating dynamic models of generator controllers into a microgrid optimal dispatch formulation with the ultimate goal to avoid operational failures and ensure the “survivability” of all-inverter microgrids to generator loss and transient overloads. The integration of generator and controller dynamics into the optimal dispatch formulation significantly increases the computational complexity. As we develop algorithms to restore speed of the optimization, our method can be readily implemented into a new operational strategy capable of an unprecedented level of reliability against generator contingencies. In addition, we quantitatively illustrate the effect of the survivability constraints on the microgrid operating costs and how the related trade-off between capital and operating costs should be taken into account at the design stage. Finally, the methods developed here also apply to the dispatch of off-grid microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Multi-Model Framework for Assessing Long- and Short-Term Climate Influences on the Electric Grid

Climate change influences many aspects of the electric grid, but prior work and industry practices often ignore the potential effects of changing climate, or they only consider a single effect or individual effects in isolation. Challenges vary with each grid and include adapting to long-term trends such as changing temperature and precipitation or shorter-term events such as drought or storms that could increase in frequency or intensity. Here we present a multi-model framework designed to analyze the effects of long and short-term climate impacts in combination. This framework couples capacity expansion and production cost models with hydrologic models and future climate scenario data to analyze alternative climate and energy futures at high spatial, temporal, and process resolutions. Furthermore, we constructed and evaluated the results of a suite of simulated scenarios exploring climate impacts on capacity investment and stress-tested the resulting future infrastructures using hourly dispatch modeling under alternative drought and load conditions. We demonstrate the approach through a case study of the U.S. Western Interconnection, where climate impacts depend on interactions between temperature-induced load, water availability for hydropower, technology competitiveness, and demand flexibility. Changes in 2038 generating capacity range from -8.5-16.6 GW, and changes in 2038 transmission capacity range from -1-2 GW. Capacity increases are driven by higher load from higher temperatures, while capacity reductions can be achieved in scenarios with higher future hydropower availability and increased demand flexibility. Scenarios requiring additional capacity cost an additional $\$5$-$\$17$ billion (discounted) from 2018 to 2038; however, scenarios with capacity reductions cost $\$1$-$\$18$ billion less. Stress tests on four 2038 infrastructures demonstrated that the identified systems were able to serve at least 99.999% of load and 99.96% of reserves. However, drought and unexpected high-load conditions can result in reduced capacity to respond to contingency events we did not model. Although these results are system and scenario specific, they highlight the importance of considering multiple climate change impacts simultaneously in long-term planning efforts and demonstrate a multi-model, multiscale approach that can be flexibly applied to any system and set of climate change concerns.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distributed Control of Inverter-Based Lossy Microgrids for Power Sharing and Frequency Regulation Under Voltage Constraints

This paper presents a new distributed control framework to coordinate inverter-interfaced distributed energy resources (DERs) in island microgrids. We show that under bounded load uncertainties, the proposed control method can steer the microgrid to a desired steady state with synchronized inverter frequency across the network and proportional sharing of both active and reactive powers among the inverters. We also show that such convergence can be achieved while respecting constraints on voltage magnitude and branch angle differences. The controller is robust under various contingency scenarios, including loss of communication links and failures of DERs. The proposed controller is applicable to lossy mesh microgrids with heterogeneous R/X distribution lines and reasonable parameter variations. Simulations based on various microgrid operation scenarios are also provided to show the effectiveness of the proposed control method.

Microgrid Control, Droop Control, Frequency Synchr↗

Intracellular calcium is a rheostat for the STING signaling pathway

Highlights: • BAPTA-AM treatment inhibits the STING translocation and its downstream signaling. • Ionomycin treatment suppresses the STING translocation and signaling through the influx of extracellular calcium. • Knockout of DRP1, the mitochondrial fission mediator, hinders the ionomycin-mediated inhibition of STING activity. • DRP1 regulates ionomycin-induced elevation of intracellular calcium levels. Stimulator of IFN genes (STING) is essential for the DNA-sensing innate immune pathway. Recently, evidence is emerging that suggests STING also plays important roles in autoimmunity, cancer therapy, and senescence. Although a multitude of post-translational modifications that regulate the STING pathway have been discovered, the cellular events that guide STING translocation remain unclear. Here, we show, paradoxically, that both BAPTA-AM-mediated calcium depletion and ionomycin-induced calcium elevation suppress STING translocation and STING-mediated IFN-β production. We demonstrate that the mitochondria fission mediator DRP1 is crucial for ionomycin-induced inhibition of IFN-β production. Furthermore, knockout of DRP1 suppressed ionomycin-induced increases in calcium as well as mitochondrial fragmentation. Collectively, our findings reveal that the induction of STING signaling is contingent on a fine-tuning of intracellular calcium levels.

60 APPLIED LIFE SCIENCES↗

Constrained or unconstrained? Neural-network-based equation discovery from data

Throughout many fields, practitioners often rely on differential equations to model systems. Yet, for many applications, the theoretical derivation of such equations and/or the accurate resolution of their solutions may be intractable. Instead, recently developed methods, including those based on parameter estimation, operator subset selection, and neural networks, allow for the data-driven discovery of both ordinary and partial differential equations (PDEs), on a spectrum of interpretability. The success of these strategies is often contingent upon the correct identification of representative equations from noisy observations of state variables and, as importantly and intertwined with that, the mathematical strategies utilized to enforce those equations. Specifically, the latter has been commonly addressed via unconstrained optimization strategies. Representing the PDE as a neural network, we propose to discover the PDE (or the associated operator) by solving a constrained optimization problem and using an intermediate state representation similar to a physics-informed neural network (PINN). The objective function of this constrained optimization problem promotes matching the data, while the constraints require that the discovered PDE is satisfied at a number of spatial collocation points. We present a penalty method and a widely used trust-region barrier method to solve this constrained optimization problem, and we compare these methods on numerical examples. Our results on several example problems demonstrate that the latter constrained method outperforms the penalty method, particularly for higher noise levels or fewer collocation points. This work motivates further exploration into using sophisticated constrained optimization methods in scientific machine learning, as opposed to their commonly used, penalty-method or unconstrained counterparts. For both of these methods, we solve these discovered neural network PDEs with classical methods, such as finite difference methods, as opposed to PINNs-type methods relying on automatic differentiation. Here, we briefly highlight how simultaneously fitting the data while discovering the PDE improves the robustness to noise and other small, yet crucial, implementation details.

Data-driven discovery↗

Computational diagnostics and characterization of combustion recession in diesel sprays

While low-temperature combustion (LTC) strategies have been found to mitigate nitrogen oxides and particulate matter emissions in diesel engines, studies have also associated LTC with an increase in unburnt hydrocarbons. With more recent studies on diesel after end-of-injection (AEOI), combustion recession is identified as a phenomenon where at near nozzle region, high-temperature ignition (HTI) combustion can propagate back to the nozzle tip consuming the unburnt hydrocarbons AEOI. Current literature has suggested that combustion recession is controlled by auto-ignition. However, high-fidelity simulations and detailed analysis of such a mechanism are missing. In this study, comprehensive Large Eddy Simulations of a reacting spray at “Spray A” conditions are performed, where detailed analysis of combustion recession concerning flame morphology and propagation modes are included. In particular, this study demonstrated for the first time that while combustion recession is mainly auto-ignition dominated (consistent with the literature), a cool flame was found to deflagrate towards the richer regions of the mixture, promoting mixing and increasing the mixture temperature. This leads to HTI kernels, which then grow and develop as deflagrative waves, therefore sustaining the combustion recession process. The study also detailed the extinction mechanism of combustion: the entrainment wave will overlean the near-nozzle mixtures, rendering it unable to support HTI, which leads to the extinction of the upstream flame AEOI in lower reactivity mixtures. Combustion recession is also observed to be contingent on the chemical and diffusion processes, even at low scalar dissipation rates. Finally, a new criterion for combustion recession based on chemical explosive mode is proposed and validated with previous combustion recession index to quantify the extent of HTI in near-nozzle mixtures AEOI. The newly developed metric combined with a previous experimentally-based metric can provide simple but valuable measurements of the degree and propensity of the upstream flame AEOI.

CEMA↗

Scale and the representation of human agency in the modeling of agroecosystems

Human agency is an essential determinant of the dynamics of agroecosystems. However, the manner in which agency is represented within different approaches to agroecosystem modeling is largely contingent on the scales of analysis and the conceptualization of the system of interest. While appropriate at times, narrow conceptualizations of agroecosystems can preclude consideration for how agency manifests at different scales, thereby marginalizing processes, feedbacks, and constraints that would otherwise affect model results. Modifications to the existing modeling toolkit may therefore enable more holistic representations of human agency. Model integration can assist with the development of multi-scale agroecosystem modeling frameworks that capture different aspects of agency. In addition, expanding the use of socioeconomic scenarios and stakeholder participation can assist in explicitly defining context-dependent elements of scale and agency. Finally, such approaches, however, should be accompanied by greater recognition of the meta agency of model users and the need for more critical evaluation of model selection and application.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Progressing quality control in environmental impact assessment beyond legislative compliance: An evaluation of the IEMA EIA Quality Mark certification scheme

The effectiveness of Environmental Impact Assessment (EIA) systems is contingent on a number of control mechanisms: procedural; judicial; evaluative; public and government agency; professional; and development aid agency. If we assume that procedural and judicial controls are guaranteed in developed EIA systems, then progressing effectiveness towards an acceptable level depends on improving the performance of other control mechanisms over time. These other control mechanisms are either absent, or are typically centrally controlled, requiring public finances; this we argue is an unpopular model in times of greater Government austerity. Here we evaluate a market-based mechanism for improving the performance of evaluative and professional control mechanisms, the UK Institute of Environmental Management and Assessments' EIA Quality Mark. We do this by defining dimensions of effectiveness for the purposes of our evaluation, and by identifying international examples of the approaches taken to delivering the other control measures to validate the approach taken in the EIA Quality Mark. We then evaluate the EIA Quality Mark, when used in combination with legal procedures and an active judiciary, against the effectiveness dimensions and use time-series analysis of registrant data to examine its ability to progress practice. We conclude that the EIA Quality Mark has merit as a model for a market-based mechanism, and may prove a more financially palatable approach for delivering effective EIA in mature systems in countries that lack centralised agency oversight. It may, therefore, be of particular interest to some Member States of the European Union for ensuring forthcoming certification requirements stemming from recent amendments to the EIA Directive. - Highlights: • Quality control mechanisms in EIA are identified. • Effectiveness of EIA is conceptualised for evaluation purposes. • The UK IEMA EIA Quality Mark is introduced as a market-based mechanism. • The EIA Quality Mark is found to progress quality in many, but not all, areas.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Fragmentary provisions for uncertainty disclosure and consideration in EA legislation, regulations and guidelines and the need for improvement

The consideration and disclosure of uncertainties is fundamental to a credible EA process, but little is known about the nature and type of requirements and guidance available to proponents, practitioners and decision makers about how to deal with uncertainties. This paper examines the provisions for considering and disclosing uncertainties in EA. Methods are based on a comparative review of uncertainty provisions in EA legislation, regulations and guidance documents under Canadian federal, provincial and territorial jurisdictions. Results show 10 types of provisions applied at different stages of the EA process with considerable jurisdictional variability and incoherence. The most common provision was that decision makers can request that project proponents provide more information, followed by the preparation of contingency plans, and that practitioners document their assumptions about data reliability. Most of these provisions were found in guidelines, versus legislation or regulations; and most addressed impact management, with very few provisions for addressing uncertainty during EA review and decision making. Current practices of uncertainty (non)disclosure and (non)consideration in EA can be explained, in part, by the superficial nature and limited extent of the requirements and guidance made available to EA practitioners, proponents, and decision makers. The existing requirements placed on proponents and practitioners to disclose and consider uncertainties are necessary, but insufficient. Stronger, more coherent and transparent requirements for those tasked with EA review and decision making to consider uncertainty information when disclosed, and the development of practical guidance on how to do so, are needed. - Highlights: •Uncertainty disclosure requirements in EA are examined. •Practitioners are often suggested to disclose uncertainties in their EAs. •Most provisions for uncertainty disclosure in EA are non-mandatory, guidelines. •There are few provisions for decision makers to consider uncertainty when disclosed. •Stronger, more coherent and transparent requirements are needed.

54 ENVIRONMENTAL SCIENCES↗