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At least 181 records · Page 10

Developing a Disaster-Ready Power Grid Agent Through Geophysically-Informed Fault Event Scenarios

Management of the nation’s power grid over the coming decades will need to factor multiple climate-driven threats to the power system that can be stressful or even detrimental to its operations. During disasters, grid operators suffer from cognitive overload where the electric grid is severely impacted by the weather, yet grid operators have limited awareness of these factors. Meanwhile, the electric grid is facing an explosion of data coming from a variety of sources which can enable the operator to evaluate the risks and develop mitigation strategies against hazardous events. In this work, we processed heterogeneous environmental and power grid data to learn and model grid behavior caused by extreme weather events. In this study, we focused on two weather-driven hazards, hurricanes and wildfires, which were analysed for the electric grid of Texas. We the used this data to train a Reinforcement Learning (RL) agent by analysing and predicting future behaviour of the grid during those hazard events. All these parts are incorporated in one framework to have a geophysically informed power simulators that can be used to train RL agents.

electic grid, reinforcement learning, climate adap↗

Increased Intracranial Pressure and Visual Impairment Associated with Long-Duration Spaceflight

Although humans have been flying in space since the 1960s, more recent missions have revealed a new suite of physiological adaptations and consequences of space flight. Notably, 60% of long-duration crewmembers (ISS/MIR) and >25% of short-duration (Shuttle) crewmembers have reported subjective degradation in vision (based on debrief comments) (Gibson 2011). Decreased near-visual acuity was demonstrated in 46% of ISS/Mir and 21% of Shuttle crewmembers, resulting in a shift of up to 1-2 diopters in their refractive correction. It is likely that the recently revealed ophthalmic changes have been present since the first days of human space flight, but have been overlooked or attributed to other causations. The reported changes in vision have occurred at various time points throughout missions, with ranging degrees of visual degradation. Although some cases resolved upon return to Earth, several astronauts have not regained preflight visual acuity, indicating that the damage may be permanent. While observing these changes over the years, without other overt symptomology and with the given age range of the flying population, this has largely been attributed to an expected hyperopic shift due to aging. However, the availability of onboard analysis techniques, including visual acuity assessments, retinal imagery, and ultrasounds of the eye and optic nerve tracts, along with more detailed post-flight techniques, has led to the recent recognition of a wider syndrome. Along with vision changes, findings include flattening of the globe, swelling of the optic disc (papilledema), choroidal folds in the retina, swelling of the optic nerve sheath, and visual field defects. It is widely hypothesized that this constellation of findings may be explained by an elevation of intracranial pressure (ICP). Out of the 60% of long-duration astronauts that have reported a subjective degradation in vision, a subset (currently 10 astronauts) have developed this syndrome. The National Aeronautics and Space Administration (NASA) has made it a high priority to understand this syndrome and provide mitigation techniques to protect crewmembers from visual impairment. While there are many possible factors that could contribute to intracranial hypertension associated with spaceflight, the relative contribution of these, as well as the processes by which eye damage occurs as a result of intracranial hypertension, are not fully understood. The observed pathophysiological phenomena are extremely complex and it is likely that multiple factors contribute to their incidence, rather than one simple mechanism. This paper will define and examine the findings in detail, and expound upon the potential contributing factors and their relative contribution to this syndrome.

Marshall-Bowman, Karina↗

The role of social support on midwestern farmers’ willingness to grow perennial bioenergy crops

The lack of farmers' willingness to grow perennial bioenergy crops (PBCs) presents a critical barrier to the emergence of cellulosic biofuel production. The willingness relies on a complex network of economic, environmental, and social drivers, among which the influence of social factors (e.g., the influence of neighborhood, community, and communication) is less understood. This study addresses this knowledge gap via a survey analysis of midwestern farmers. The survey data are analyzed through ordinary least square regression and structural equation model, which together investigate the individual and interactive impacts of multiple factors on farmers' decisions to adopt PBCs. Based on a farm-scale analysis, six statistically significant predictors of farmer willingness to grow PBCs are identified: perception of PBCs' environment benefits, education level, willingness to take risks, familiarity with PBCs, portion of peers already growing PBCs, and support of biorefineries locating in the local community. Among these, the latter three predictors are social support variables. It is found that familiarity with the crops is the most significant predictor of willingness; familiarity is also an important intermediate variable that mediates the influence of many other predictors. In addition, peer adoption can both directly and indirectly affect willingness via its influence on familiarity. Furthermore, these findings suggest that it is a pressing need to improve farmers’ knowledge of PBCs to promote the adoption of such crops.

09 BIOMASS FUELS↗

Data for The Role of Social Support on Midwestern Farmers’ Willingness to Grow Perennial Bioenergy Crops

The lack of farmers’ willingness to grow perennial bioenergy crops (PBCs) presents a critical barrier to the emergence of cellulosic biofuel production. The willingness relies on a complex network of economic, environmental, and social drivers, among which the influence of social factors (e.g., the influence of neighborhood, community, and communication) is less understood. This study addresses this knowledge gap via a survey analysis of midwestern farmers. The survey data are analyzed through ordinary least square regression and structural equation model, which together investigate the individual and interactive impacts of multiple factors on farmers’ decisions to adopt PBCs. Based on a farm-scale analysis, six statistically significant predictors of farmer willingness to grow PBCs are identified: perception of PBCs’ environment benefits, education level, willingness to take risks, familiarity with PBCs, portion of peers already growing PBCs, and support of biorefineries locating in the local community. Among these, the latter three predictors are social support variables. It is found that familiarity with the crops is the most significant predictor of willingness; familiarity is also an important intermediate variable that mediates the influence of many other predictors. In addition, peer adoption can both directly and indirectly affect willingness via its influence on familiarity. These findings suggest that it is a pressing need to improve farmers’ knowledge of PBCs to promote the adoption of such crops.

Economics↗

Geomechanical Simulation of Big Hill Strategic Petroleum Reserve - Calibration of Model Containing Shear Zone

A finite element numerical analysis model, that consists of a realistic mesh capturing the geometries of Big Hill (BH) Strategic Petroleum Reserve (SPR) site using the multi-mechanism deformation (MD) salt constitutive model and including data taken daily of the wellhead pressure and level of the oil-brine interface, has been upgraded. The upgraded model contains the shear zone to examine the interbed behavior in a realistic manner. The salt creep rate is not uniform in the salt dome, and creep test data for BH salt is limited. Therefore, a model calibration is necessary to simulate the geomechanical behavior of the salt dome. Cavern volumetric closures of SPR caverns calculated from sonar survey reports are used for the field baseline measurement. The structure factor, A 2 , and transient strain limit factor, K 0 , in the M-D constitutive model are used for model calibration. An A 2 value obtained experimentally from the BH salt and K 0 value of WIPP salt are used as the baseline values. To adjust the magnitude of A 2 and K 0 , multiplication factors A 2 F and K 0 F are defined, respectively. The A 2 F and K 0 F values of the salt dome and salt drawdown layer of elements surrounding each SPR cavern have been determined through a number of back fitting analyses. The trendlines of the predictions and sonar data match up well for BH 101, 103, 104, 106, 110, 111, 112, and 113. The prediction curves are close to the sonar data for BH 102 and 114. However, the prediction curves for BH 105, 107, 108, and 109 are not close to the sonar data. An inconsistency was found in the sonar data, i.e. the volume measured later is larger than that before in some time intervals, even if the leached volume is taken into account, for BH 101, 104, 106, 107, and 112. Project discussions are needed to determine possibilities on how to resolve the issues and determine the best path forward for future computer modeling attempts.

02 PETROLEUM↗

Geomechanical Simulation of Big Hill Strategic Petroleum Reserve (Model Calibration)

A finite element numerical analysis model has been constructed that consists of a realistic mesh capturing the geometries of Big Hill (BH) Strategic Petroleum Reserve (SPR) site using the multi-mechanism deformation (M-D) salt constitutive model and including data taken daily of the wellhead pressure and level of the oil-brine interface. The salt creep rate is not uniform in the salt dome, and creep test data for BH salt is limited. Therefore, a model calibration is necessary to simulate the geomechanical behavior of the salt dome. Cavern volumetric closures of SPR caverns calculated from sonar survey reports are used for the field baseline measurement. The structure factor, A 2 , and transient strain limit factor, K o , in the M-D constitutive model are used for model calibration. An A 2 value obtained experimentally from the BH salt and K o value of WIPP salt are used as the baseline values. To adjust the magnitude of A 2 and K o , multiplication factors A2F and KOF are defined, respectively. The A2F and KOF values of the salt dome and salt drawdown layer of elements surrounding each SPR cavern have been determined through a number of back fitting analyses. The trendlines of the predictions and sonar data match up well for BH 101, 103, 104, 106, 110, 111, and 113. The prediction curves are close to the sonar data for BH 102 and 114. However, the prediction curves for BH 105, 107, 108, 109, and 112 are not close to the sonar data. An inconsistency was found in the sonar data, i.e. the sonar measurements of cavern volumes increase with time, during some periods for BH 101, 104, 106, 107, and 112. A follow-up report in 2019 will provide a resolution for these issues.

02 PETROLEUM↗

Equivalent Fundamental-Mode Source Simulations for Spherical Uranium and Plutonium Systems [Abstract]

The equivalent fundamental-mode source refers to a “source” which is identically distributed in space, energy, and angle as that of a fundamental-mode fission source distribution. It has previously been shown that the system fixed source multiplication ($M_{fs}$) relates to the effective multiplication factor ($\kappa_{eff}$) as $M_{fs} = \frac{g^*}{1-k_{eff}}$ The term $\mathcal{g}$* therefore relates the system source distribution to the system equivalent fundamental-mode source. As previously shown, the $\mathcal{g}$* term is approximately 1 for deeply subcritical systems and then diverges as the system multiplication increases. For a system with a point source located in the center of an assembly (such a sphere), $\mathcal{g}$* will be greater than 1; this happens because there is a higher probability of induced fission when all of the starter neutrons originate from the center of the sphere. For a uniform source, $\mathcal{g}$* is less than 1, but does not diverge from 1 as dramatically as seen by a point source. One reason that $\mathcal{g}$* is an important parameter is that it is used in measurement methods to infer reactor kinetics parameters ($β_{eff}$ being one example). This work will discuss multiple ways to simulate $\mathcal{g}$* using MCNP®6.2, which include use of traditional methods versus a single input file method that was recently published. A discussion related to methods to simulate $M_{fs}$ will be presented. Spherical systems of Highly Enriched Uranium (HEU) will be compared with previous works. In addition, results of plutonium including multiple reflector materials will be investigated. Simulated systems will include both parametric studies as well as configurations used in recent experiments performed at the National Criticality Experiments Research Center (NCERC). These studies will include subtleties associated with system geometry that have not been previously shown. Last, this work will investigate the relationship between $\mathcal{g}$* and reactor kinetics parameters (such as $β_{eff}$).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Geomechanical Simulation of Bayou Choctaw Strategic Petroleum Reserve - Model Calibration.

A finite element numerical analysis model has been constructed that consists of a realistic mesh capturing the geometries of Bayou Choctaw (BC) Strategic Petroleum Reserve (SPR) site and multi - mechanism deformation ( M - D ) salt constitutive model using the daily data of actual wellhead pressure and oil - brine interface. The salt creep rate is not uniform in the salt dome, and the creep test data for BC salt is limited. Therefore, the model calibration is necessary to simulate the geomechanical behavior of the salt dome. The cavern volumetric closures of SPR caverns calculated from CAVEMAN are used for the field baseline measurement. The structure factor, A 2 , and transient strain limit factor, K 0 , in the M - D constitutive model are used for the calibration. The A 2 value obtained experimentally from the BC salt and K 0 value of Waste Isolation Pilot Plant (WIPP) salt are used for the baseline values. T o adjust the magnitude of A 2 and K 0 , multiplication factors A2F and K0F are defined, respectively. The A2F and K0F values of the salt dome and salt drawdown skins surrounding each SPR cavern have been determined through a number of back fitting analyses. The cavern volumetric closures calculated from this model correspond to the predictions from CAVEMAN for six SPR caverns. Therefore, this model is able to predict past and future geomechanical behaviors of the salt dome, caverns, caprock , and interbed layers. The geological concerns issued in the BC site will be explained from this model in a follow - up report .

58 GEOSCIENCES↗

Geomechanical Model Calibration Using Field Measurements for a Petroleum Reserve

A finite element numerical analysis model has been constructed that consists of a mesh that effectively captures the geometries of Bayou Choctaw (BC) Strategic Petroleum Reserve (SPR) site and multimechanism deformation (M-D) salt constitutive model using the daily data of actual wellhead pressure and oil–brine interface location. The salt creep rate is not uniform in the salt dome, and the creep test data for BC salt are limited. Therefore, the model calibration is necessary to simulate the geomechanical behavior of the salt dome. The cavern volumetric closures of SPR caverns calculated from CAVEMAN are used as the field baseline measurement. The structure factor, A 2 , and transient strain limit factor, K o , in the M-D constitutive model are used for the calibration. The value of A 2 , obtained experimentally from BC salt, and the value of K o , obtained from Waste Isolation Pilot Plant salt, are used for the baseline values. To adjust the magnitude of A 2 and K0, multiplication factors A 2 F and K o F are defined, respectively. The A 2 F and K0F values of the salt dome and salt drawdown skins surrounding each SPR cavern have been determined through a number of back analyses. The cavern volumetric closures calculated from this model correspond to the predictions from CAVEMAN for six SPR caverns. Therefore, this model is able to predict behaviors of the salt dome, caverns, caprock, and interbed layers. In conclusion, the geotechnical concerns associated with the BC site from this analysis will be explained in a follow-up paper.

02 PETROLEUM↗

SU-F-T-157: Physics Considerations Regarding Dosimetric Accuracy of Analytical Dose Calculations for Small Field Proton Therapy: A Monte Carlo Study

Purpose: To evaluate the accuracy of dose calculations by analytical dose calculation methods (ADC) for small field proton therapy in a gantry based passive scattering facility. Methods: 50 patients with intra-cranial disease were evaluated in the study. Treatment plans followed standard prescription and optimization procedures of proton stereotactic radiosurgery. Dose distributions calculated with the Monte Carlo (MC) toolkit TOPAS were used to represent delivered treatments. The MC dose was first adjusted using the output factor (OF) applied clinically. This factor is determined from the field size and the prescribed range. We then introduced a normalization factor to measure the difference in mean dose between the delivered dose (MC dose with OF) and the dose calculated by ADC for each beam. The normalization was determined by the mean dose of the center voxels of the target area. We compared delivered dose distributions and those calculated by ADC in terms of dose volume histogram parameters and beam range distributions. Results: The mean target dose for a whole treatment is generally within 5% comparing delivered dose (MC dose with OF) and ADC dose. However, the differences can be as great as 11% for shallow and small target treated with a thick range compensator. Applying the normalization factor to the MC dose with OF can reduce the mean dose difference to less than 3%. Considering range uncertainties, the generally applied margins (3.5% of the prescribed range + 1mm) to cover uncertainties in range might not be sufficient to guarantee tumor coverage. The range difference for R90 (90% distal dose falloff) is affected by multiple factors, such as the heterogeneity index. Conclusion: This study indicates insufficient accuracy calculating proton doses using ADC. Our results suggest that uncertainties of target doses are reduced using MC techniques, improving the dosimetric accuracy for proton stereotactic radiosurgery. The work was supported by NIH/NCI under CA U19 021239. CG was partially supported by the Chinese Scholarship Council (CSC) and the National Natural Science Foundation of China (Grant No. 11475087).

60 APPLIED LIFE SCIENCES↗

An Analysis of Terrestrial and Aquatic Environmental Controls of Riverine Dissolved Organic Carbon in the Conterminous United States

Riverine carbon cycling is an important, but insufficiently investigated component of the global carbon cycle. Analyses of environmental controls on riverine carbon cycling are critical for improved understanding of mechanisms regulating carbon processing and storage along the terrestrial-aquatic continuum. Here, we compile and analyze riverine dissolved organic carbon (DOC) concentration data from 1402 United States Geological Survey (USGS) gauge stations to examine the spatial variability and environmental controls of DOC concentrations in the United States (U.S.) surface waters. DOC concentrations exhibit high spatial variability, with an average of 6.42 ± 6.47 mg C/ L (Mean ± Standard Deviation). In general, high DOC concentrations occur in the Upper Mississippi River basin and the Southeastern U.S., while low concentrations are mainly distributed in the Western U.S. Single-factor analysis indicates that slope of drainage areas, wetlands, forests, percentage of first-order streams, and instream nutrients (such as nitrogen and phosphorus) pronouncedly influence DOC concentrations, but the explanatory power of each bivariate model is lower than 35%. Analyses based on the general multi-linear regression models suggest DOC concentrations are jointly impacted by multiple factors. Soil properties mainly show positive correlations with DOC concentrations; forest and shrub lands have positive correlations with DOC concentrations, but urban area and croplands demonstrate negative impacts; total instream phosphorus and dam density correlate positively with DOC concentrations. Notably, the relative importance of these environmental controls varies substantially across major U.S. water resource regions. In addition, DOC concentrations and environmental controls also show significant variability from small streams to large rivers, which may be caused by changing carbon sources and removal rates by river orders. In sum, our results reveal that general multi-linear regression analysis of twenty one terrestrial and aquatic environmental factors can partially explain (56%) the DOC concentration variation. In conclusion, this study highlights the complexity of the interactions among these environmental factors in determining DOC concentrations, thus calls for processes-based, non-linear methodologies to constrain uncertainties in riverine DOC cycling.

54 ENVIRONMENTAL SCIENCES↗

Neutronic design and fuel cycle analysis of a fluoride salt-cooled High Temperature Reactor (FHR)

The Fluoride salt-cooled High temperature Reactor (FHR) is a new Gen IV reactor concept that can operate under near atmospheric pressure circumstances and further enhance the inherent safety. In this study, an FHR core design with 165 megawatts of thermal output (MWth) is proposed. The reactor core employs tri-structural-isotropic (TRISO) particle fuel within prismatic graphite blocks as the basic fuel form, FLiBe (2 {sup 7}LiF-BeF{sub 2}) as the primary coolant, and a three-batch fuel cycle scheme. Sensitivity analyses on various parameters were performed to optimize the cycle length and neutronic parameters. The fuel cycle of this core design was evaluated in detail from 4 aspects: cycle length, power peaking factor (PPF), discharge burnup, and temperature coefficient. It was found that larger fuel channel pitch (FCP) would have a relatively harder neutron spectrum, and yield relatively longer cycle length, lower, better fuel temperature coefficient (FTC), and moderator temperature coefficient (MTC). In addition, burnable poison (BP), Er{sub 2}O{sub 3}, can effectively reduce PPF, hold down the multiplication factor, and more importantly it can improve the MTC. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A nodal transport method for coupled fast-thermal reactor analysis

We report that for efficient core analyses of coupled fast-thermal reactors, a new deterministic method has been developed based on the variational nodal transport method of VARIANT. A new multigroup cross section generation procedure was devised by combining Monte Carlo lattice calculations for thermal assemblies and the two-step procedure of the MC 2 -3 code for fast assemblies. To reduce assembly homogenization errors in nodal transport calculations, a new nodal equivalence method was developed based on the partial current discontinuity factor (PCDF) and incorporated in VARIANT. A practical procedure to calculate PCDFs with fixed source supercell calculations was also devised. The performance of the proposed method was investigated using a test problem derived from the versatile coupled test reactor (VCTR) design. The new procedure produced multigroup cross sections accurately for all assemblies. VARIANT transport calculations with PCDFs produced accurate multiplication factor and power distribution compared to reference Serpent-2 Monte Carlo solutions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Customer enrollment and participation in building demand management programs: A review of key factors

Increasing the efficiency and flexibility of electricity demand is necessary for ensuring a cost-effective and reliable transition to zero-carbon electricity systems. Such demand-side management (DSM) resources have been procured by utilities for decades via energy efficiency and demand response programs; however, the key drivers of program enrollment and customer participation levels remain poorly understood — even as governments and grid planners seek to scale up the deployment of DSM assets to meet climate targets. Here we systematically review the evidence on multiple factors that may influence customer enrollment and participation in building DSM programs, focusing primarily on residential and commercial buildings. We examine the contexts in which relationships between DSM factors and outcomes are most often explored and with which methods; we also score the strength, direction, and internal consistency of each factor's reported impact on the enrollment and participation outcomes. We find that studies most commonly assess the effects of economic incentives for load flexibility on program participation levels, often using simulation-based methods in lieu of measured data. Few studies focus on program enrollment outcomes or regulatory drivers of either enrollment or participation, and gaps are also evident in the coverage of emerging DSM opportunities like load electrification. Removal of structural barriers (e.g., the lack of controls infrastructure) and the use of third party services (e.g., load aggregators) are the factors with the largest positive impacts on DSM outcomes, but no single factor emerges as clearly most impactful. For a given factor, the range of reported impacts typically varies widely across the relevant studies reviewed. Our findings provide a snapshot of the state of knowledge about building DSM and customer decision-making, and they expose key gaps in understanding that must be filled if building DSM is to expand as a critical resource for operating clean power grids.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Roles of genetic and microenvironmental factors in cancer epithelial-to-mesenchymal transition and therapeutic implication

Epithelial-to-mesenchymal transition (EMT) is a process in which epithelial cells lose their cell-cell contacts resulting in the formation of mesenchymal cells with migratory properties. Increasing evidence indicate EMT plays a key role in the invasion, metastasis and therapeutic resistance of cancer and maintenance of the phenotype of cancer stem cells (CSCs), which makes the prognosis of patients worse. The progression of cancer from epithelial tissue towards a malignant phenotype is driven by multiple factors that remodel the tissue architecture. This review summarizes and analyzes current studies of genetic and microenvironmental factors in inducing and maintaining cancer EMT and therapeutic implications. This will enable a better understanding of the contribution of EMT-associated factors to cancer progression and highlights that genetic factors and tumor microenvironment responsible for EMT could be used as attractive targets for therapeutic intervention.

60 APPLIED LIFE SCIENCES↗

A Markov Decision Process Framework for Optimal Airport Reconfiguration

The airport runway configuration is defined as a combination set of runways for arrivals and departures used at a point during operation of the airport. An optimal configuration of these runways depends on a number of factors, including traffic demand, wind magnitude and direction, other adverse weather conditions, and noise restrictions, among others. Based on the current state of these factors and predictions of traffic demand and weather conditions, runway configuration changes are made and coordinated between tower controller, other air traffic control facilities, pilots, and ground personnel. Reconfigurations can be quite disruptive to airport operations; minimizing their frequency and scheduling them well in advance is essential for mitigating some of the added workload for controllers and pilots. Unfortunately, deciding on an appropriate time to change is challenging for human decision makers. Not only do multiple factors need to be evaluated, but the uncertainty in their forecasts must also be considered. Previous optimization methods, such as mixed linear integer programming, have been proposed. Although these methods can reason over a large set of variables, they do not systematically handle the uncertainty associated with weather movement, traffic demands, and other variables. In this work, we introduce a Markov Decision Process (MDP)-based decision making framework which can reason effectively over the inherent uncertainties and make optimal decisions on if/when to change the airport configuration. In a prototype implementation, we present a single runway with three aircraft and utilize knowledge of the forecasted wind speed and direction to determine whether to keep or change the current runway configuration. Our aim through this work is to present a framework for airport reconfiguration which can be scalable to additional aircraft, multiple runways, and various input parameters. This technique will optimize the airport reconfiguration procedure by providing a proactive approach, optimizing not just at the next optimal opportunity for a reconfiguration based on varying atmospheric and traffic conditions in the terminal airspace, but also anticipating future necessary reconfigurations. This will eliminate the inefficiencies of frequent changes currently associated with runway reconfiguration procedures.

runway reconfiguration↗

Influence of the atmosphere on remotely sensed data

Factors which influence the effects of the atmosphere on the data of remote sensing are examined. A radiative-transfer model is considered and effects of varied optical thickness of the atmosphere are investigated. Effects of varied surface albedo are discussed along with the effects of the sun angle, the effects of the scan angle, and questions regarding the atmospheric effects on the recognition performance. It is found that a multiplicative factor involving the sun angle alone is not sufficient for the correction of space data.

Turner, R. E.↗

Climate change reshapes the drivers of false spring risk across European trees

Temperate and boreal forests are shaped by late spring freezing events after budburst, which are also known as false springs. Research has generated conflicting results on whether or not these events will change with climate change, potentially because---to date---no study has compared the myriad climatic and geographic factors that contribute to a plant's risk of a false spring. We assessed and compared the strength of the effects of mean spring temperature, distance from the coast, elevation and the North Atlantic Oscillation (NAO) using PEP725 leafout data for six temperate, decidious tree species across 11,648 sites in Central Europe and how these predictors shifted with climate change. Across species before recent warming, mean spring temperature and distance from the coast were the strongest predictors, with higher mean spring temperatures associated with decreased risk in false springs (–7.64% per 2°C increase) and sites further from the coast experiencing an increased risk (5.32% per 150km from the coast). Elevation (2.23% per 200m increase in elevation) and NAO index (1.91% per 0.3 increase) also increased false spring risk. With climate change, elevation and distance from coast---i.e., the geographic factors---remain relatively stable, while climatic factors shifted in magnitude for mean spring temperature (down to -2.84% in risk per 2°C), and in direction, with positive NAO phases leading to lower risk (-9.15% per 0.3). The residual effects of climate change---unexplained by the climatic and geographic factors already included in the model---magnified the species-level variation in risk, with risk increasing among early-leafout species (i.e., Aesculus hippocastanum, Alnus glutinosa and Betula pendula) but a decline or no change in risk among late-leafout species (i.e., Fagus sylvatica, Fraxinus excelsior and Quercus robur). Our results show that climate change has reshaped the major drivers of false spring risk and highlight how considering multiple factors can yield a better understanding of the complexities of climate change.

Climate change↗