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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A nonparametric approach to modeling dependence among production parameters for energy cost estimation

Dependence existing among production parameters can significantly affect energy costs. For material removal processes, processing times and material amounts to be cut have positive dependence, and the dependence can affect energy costs by varying a peak electricity load. Existing methods to model the dependence of production parameters are based on parametric approaches that cannot accurately represent the dependence due to the rigid nature of parametric models. To address this issue, this study proposes a method to quantify dependence among manufacturing parameters through the application of the empirical copula to the dependence between the milling processing time and the amount of volume to be cut. The proposed method is illustrated by a case study of a manufacturing facility consisting of milling machines; a total of 27 scenarios are simulated for energy cost estimations. The case study clearly shows that the proposed method can capture the dependence between the milling parameters more accurately than a conventional dependence measure from parametric correlation models. Furthermore, the findings from this study would be useful to estimate energy costs in that the proposed method provides a better fit to real production data than conventional parametric approaches can.

42 ENGINEERING↗
DOE OSTI2025

Competition between roughness and strength for scale-dependent surfaces

Rocks famously have scale-dependent strength, yet the actual dependence is notoriously hard to measure or incorporate into any theoretical framework. Natural rough surfaces present an opportunity to solve the problem. Surfaces sliding in shear evolve as protrusions collide. These asperities can deform or break, thus creating a new surface shape. In particular, natural surfaces have roughness at all scales as well as scale-dependent strength. Based on a scaling analysis, we have previously suggested that the scale-dependent aspect ratio of steady-state surfaces should be proportional to the scale-dependent shear strain at yield. If true, scale-dependent strength could easily be inferred from natural surfaces. Thus, moving beyond the scaling argument to a rigorous treatment of scale-dependent strength for multiscale rough surfaces in shear is important. However, analytic frameworks for analyzing multiscale problems are challenging, as conventional continuum mechanics typically involves a single value for a material property across scales. Here, in this work, we build on the formalism of Persson (2001) that presents a method to compute contact area for rough surfaces with a prescribed topographic spectrum using a stochastic differential equation. The Persson formalism allows for plastic yield under normal loading of otherwise elastic materials and leaves open the possibility of scale-dependent yield stress. In this study, we pursue this route to develop a theory and numerical results for the yielding of a rough, elastoplastic surface with scale-dependent yield stress. Here, we examine surfaces for which the power spectrum of the topography 𝐶 and yield stress 𝑌 follow power laws as a function of scale 𝜆, such that 𝐶∼𝜆 −𝑚 and 𝑌∼𝜆 −𝑛 , respectively. In this formal treatment of the problem, we focus on surfaces in contact and the resulting yield and do not impose shear. Numerical solutions show that the deviation from the elastic scaling solution is bounded as expected by the prior 1D heuristic scaling argument that anticipates the Hurst exponent as 1−𝑛. We also show that the plasticity is expected to erode the contacts if 𝑚 is lower than 𝑛−3, which corresponds to a Hurst exponent lower than 1−𝑛/2. This result is rigorously sound for 2D, i.e., realistic surfaces, and quantitatively different than the prior scaling argument. The theory now permits a correspondingly quantitative approach to interpreting natural surfaces.

elasticity↗
DOE OSTI2021

Formative vs. Summative Dependence in Human Reliability Analysis

Dependence in human reliability analysis (HRA) is the concept that once an initial human error has occurred, subsequent human errors are more likely. The approach almost universally adopted in HRA was first introduced in the Technique for Human Error Rate Prediction (THERP). In THERP, calculated human error probabilities (HEPs) are adjusted for dependence in the final step of quantification. This final adjustment for dependence involves anchoring the HEP to a set of values corresponding to low through complete dependence. The effect is to increase the HEP. In this paper, we propose formative dependence, which occurs at the onset of quantification. We demonstrate that dependence should be considered earlier in the calculation process, because it is not actually necessary to calculate the HEP when it is subsequently overridden by the dependence anchors. By applying dependence first in the calculation, processing steps can be eliminated, making for more efficient analysis.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Physics augmented machine learning discovery of composition-dependent constitutive laws for 3D printed digital materials

Multi-material 3D printing, particularly through polymer jetting, enables the fabrication of digital materials by mixing distinct photopolymers at the micron scale within a single build to create a composite with tunable mechanical properties. Here, this work presents an integrated experimental and computational investigation into the composition-dependent mechanical behavior of 3D printed digital materials. We experimentally characterize five formulations, combining soft and rigid UV-cured polymers under uniaxial tension and torsion across three strain and twist rates. The results reveal nonlinear and rate-dependent responses that strongly depend on composition. To model this behavior, we develop a physics-augmented neural network (PANN) that combines a partially input convex neural network (pICNN) for learning the composition-dependent hyperelastic strain energy function with a quasi-linear viscoelastic (QLV) formulation for time-dependent response. The pICNN ensures convexity with respect to strain invariants while allowing non-convex dependence on composition. To enhance interpretability, we apply $L_0$ sparsification. For the time-dependent response, we introduce a multilayer perceptron (MLP) to predict viscoelastic relaxation parameters from composition. The proposed model accurately captures the nonlinear, rate-dependent behavior of 3D printed digital materials in both uniaxial tension and torsion, achieving high predictive accuracy for interpolated material compositions. This approach provides a scalable framework for automated, composition-aware constitutive model discovery for multi-material 3D printing.

Constitutive modeling↗
NASA NTRS1994

Theoretical investigation of wave-vector-dependent analytical and numerical formulations of the interband impact-ionization transition rate for electrons in bulk silicon and GaAs

The electron interband impact-ionization rate for both silicon and gallium arsenide is calculated using an ensemble Monte Carlo simulation with the expressed purpose of comparing different formulations of the interband ionization transition rate. Specifically, three different treatments of the transition rate are examined: the traditional Keldysh formula, a new k-dependent analytical formulation first derived by W. Quade, E. Scholl, and M. Rudan (1993), and a more exact, numerical method of Y. Wang and K. F. Brennan (1994). Although the completely numerical formulation contains no adjustable parameters and as such provides a very reliable result, it is highly computationally intensive. Alternatively, the Keldysh formular, although inherently simple and computationally efficient, fails to include the k dependence as well as the details of the energy band structure. The k-dependent analytical formulation of Quade and co-workers overcomes the limitations of both of these models but at the expense of some new parameterization. It is found that the k-dependent analytical method of Quade and co-workers produces very similar results to those obtained with the completely numerical model for some quantities. Specifically, both models predict that the effective threshold for impact ionization in GaAs and silicon is quite soft, that the majority of ionization events originate from the second conduction band in both materials, and that the transition rate is k dependent. Therefore, it is concluded that the k-dependent analytical model can qualitatively reproduce results similar to those obtained with the numerical model yet with far greater computational efficiency. Nevertheless, there exist some important drawbacks to the k-dependent analytical model of Quade and co-workers: These are that it does not accurately reproduce the quantum yield data for bulk silicon, it requires determination of a new parameter, related physically to the overlap intergrals of the Bloch state which can only be adjusted by comparison to experiment, and fails to account for any wave-vector dependence of the overlap integrals. As such the transition rate may be overestimated at those points for which 'near vertical,' small change in k, transitions occur.

Kolnik, Jan↗
NASA NTRS1994

Theoretical Investigation of Wave-Vector-Dependent Analytical and Numerical Formulations of the Interband Impact-Ionization Transition Rate for Electron in Bulk Silicon and GaAs

The electron interband impact-ionization rate for both silicon and gallium arsenide is calculated using an ensemble Monte Carlo simulation with the expressed purpose of comparing different formulations of the interband ionization transition rate. Specifically, three different treatments of the transition rate are examined: the traditional Keldysh formula, a new k-dependent analytical formulation first derived by W. Quade, E Scholl, and M. Rudan, and a more exact, numerical method of Y. Wang and K. F. Brennan. Although the completely numerical formulation contains no adjustable parameters and as such provides a very reliable result, it is highly computationally intensive. Alternatively, the Keldysh formula, although inherently simple and computationally efficient, fails to include the k dependence as well as the details of the energy band structure. The k-dependent analytical formulation of Quade and co-workers overcomes the limitations of both of these models but at the expense of some new parameterization. It is found that the k-dependent analytical method of Quade and co-workers produces very similar results to those obtained with (he completely numerical model for some quantities. Specifically, both models predict that the effective threshold for impact ionization in GaAs and silicon is quite soft, that the majority of ionization events originate from the second conduction band in both materials, and that the transition rate is k dependent. Therefore, it is concluded that the k-dependent analytical model can qualitatively reproduce results similar to those obtained with the numerical model yet with far greater computational efficiency. Nevertheless, there exist some important drawbacks to the k-dependent analytical model of Quade and co-workers: These are that it does not accurately reproduce the quantum yield data for bulk silicon, it requires determination of a new parameter, related physically to (he overlap integrals of the Bloch state which can only be adjusted by comparison to experiment, and fails to account for any wave-vector dependence of the overlap integrals. As such [he transition rate may be overestimated at those points for which "near vertical," small change in k, transitions occur.

Kolnik, Jan↗
NASA NTRS2017

Accounting for the Effects of Surface BRDF on Satellite Cloud and Trace-Gas Retrievals: A New Approach Based on Geometry-Dependent Lambertian-Equivalent Reflectivity Applied to OMI Algorithms

Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50% in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

Lambert-equivalent reflectivity↗
NASA NTRS2022

The Impact of Inclination-dependent Attenuation on Ultraviolet Star Formation Rate Tracers

We examine and quantify how hybrid (e.g., UV+IR) star formation rate (SFR) estimators and the AFUV–β relation depend on inclination for disk-dominated galaxies using spectral energy distribution modeling that utilizes the inclination-dependent attenuation curves described in Doore et al. We perform this analysis on a sample of 133 disk-dominated galaxies from the CANDELS fields and 18 disk galaxies from the Spitzer Infrared Nearby Galaxies Survey and Key Insights on Nearby Galaxies: A Far-Infrared Survey with Herschel samples. We find that both the hybrid SFR estimators and the AFUV–β relation present clear dependencies on inclination. To quantify this dependence in the hybrid SFR estimators, we derive an inclination and a far-UV–near-IR color-dependent parametric relation for converting observed UV and IR luminosities into SFRs. For the AFUV–β relation, we introduce an inclination-dependent component that accounts for the majority of the inclination dependence with the scatter of the relation increasing with inclination. We then compare both of these inclination-dependent relations to similar inclination-independent relations found in the literature. From this comparison, we find that the UV+IR correction factor and AFUV for our hybrid and AFUV–β relations, respectively, result in a reduction in the residual scatter of our sample by approximately a factor of 2. Therefore, we demonstrate that inclination must be considered in hybrid SFR estimators and the AFUV–β relation to produce more accurate SFR estimates in disk-dominated galaxies.

Keith Doore↗
DOE OSTI2023

A new method for detecting abrupt changes in the dependence among multivariate hydrological series based on moving cut total correlation

Knowledge of how to define and estimate the dependence among multivariate hydrological series is essential for detecting abrupt changes in the dependence. Here, in this paper, a new method (BMCTC) is proposed to detect all possible abrupt change points in the dependence among multivariate hydrological series. The total correlation estimated by the matrix-based Renyi's alpha-order entropy functional is firstly introduced to define and measure the dependence strength among multivariate hydrological series. Then, the moving cut total correlation (MCTC) sequence is built by the moving window technique, which is used to measure changes in the dependence strength among multivariate hydrological series. Finally, the Bernaola-Galvan algorithm is used to detect all change points of the MCTC sequence. Simulations are performed to compare the effectiveness of BMCTC with Pearson correlation (BMCPC) and Spearman correlation (BMCSC), Cramer-von Mises (CvM) and copula-based likelihood-ratio (CLR). The results show that all change points are detected by BMCTC regardless of the samples size, but wrong change points or no change points are detected by other methods in most cases. BMCTC is applied to detect change points in the dependence among annual runoff, precipitation and sediment discharge series in the Xiliugou and the Kuyehe River, China. It is found that the dependence among runoff, precipitation and sediment discharge changed abruptly in 1980 and 1996 in the Kuyehe River and in 1999 in the Xiliugou River. These changes are mainly caused by human activities such as construction of water conservancy projects and coal mining.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

On the quantification and efficient propagation of imprecise probabilities with copula dependence

This paper addresses the problem of quantification and propagation of uncertainties associated with dependence modeling when data for characterizing probability models are limited. Practically, the system inputs are often assumed to be mutually independent or correlated by a multivariate Gaussian distribution. However, this subjective assumption may introduce bias in the response estimate if the real dependence structure deviates from this assumption. In this work, we overcome this limitation by introducing a flexible copula dependence model to capture complex dependencies. Here, a hierarchical Bayesian multimodel approach is proposed to quantify uncertainty in dependence model-form and model parameters that result from small data sets. This approach begins by identifying, through Bayesian multimodel inference, a set of candidate marginal models and their corresponding model probabilities, and then estimating the uncertainty in the copula-based dependence structure, which is conditional on the marginals and their parameters. The overall uncertainties integrating marginals and copulas are probabilistically represented by an ensemble of multivariate candidate densities. A novel importance sampling reweighting approach is proposed to efficiently propagate the overall uncertainties through a computational model. Through an example studying the influence of constituent properties on the out-of-plane properties of transversely isotropic E-glass fiber composites, we show that the composite property with copula-based dependence model converges to the true estimate as data set size increases, while an independence or arbitrary Gaussian correlation assumption leads to a biased estimate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Full time-dependent SOLPS-ITER simulation of the SPARC tokamak: actuator design for particle and divertor condition control *

Abstract This paper presents the application of full time-dependent SOLPS-ITER simulations for actuator design in the SPARC tokamak. This study employs both the EIRENE module, a neutral solver, and the B2.5 plasma module in a time-dependent mode. This is in contrast to most SOLPS simulations, which focus on steady-state solutions, where the neutral distribution is evolved without any time limit or for a time step of 1 ⋅ 10 − 3 second, which is several orders of magnitude larger than the fluid plasma time step. The time-dependent EIRENE was tested with a fixed B2.5 background and compared with a simple conductance based model in a simplified pump chamber geometry. This comparison aimed to verify the reliability of the neutral relaxation timescale derived from the time-dependent EIRENE. Subsequently, a full time-dependent simulation was performed in a realistic geometry, with the Monte-Carlo neutral time step synchronized with the plasma fluid time step. The numerical setup of the code, including relative time steps and the size of the census data used to store Monte-Carlo particle information is considered. The full-time dependent simulations are then applied to inform the design of the SPARC louver structure, which affects divertor plasma parameters by regulating the neutral conductance from the divertor to the pump. The response of the plasma and neutral parameters was captured on a timescale that enables the design of the actuator to consider time-dependent control capability. It was found that changing the louver opacity has an equivalent effect as varying the gas throughput via puff actuation. Therefore, equivalent divertor plasma conditions can be obtained from both actuators, while the neutral pressure distribution in the pump and divertor differs for each actuator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Validation of time-dependent shift using the pulsed sphere benchmarks

The detailed behavior of neutrons in a rapidly changing time-dependent physical system is a challenging computational physics problem, particularly when using Monte Carlo methods on heterogeneous high-performance computing architectures. A small number of algorithms and code implementations have been shown to be performant for time-independent (fixed source and k-eigenvalue) Monte Carlo, and there are existing simulation tools that successfully solve the time-dependent Monte Carlo problem on smaller computing platforms. To bridge this gap, a time-dependent version of ORNL’s Shift code has been recently developed. Shift’s history-based algorithm on CPUs, and its event-based algorithm on GPUs, have both been observed to scale well to very large numbers of processors, which motivated the extension of this code to solve time-dependent problems. The validation of this new capability requires a comparison with time-dependent neutron experiments. Lawrence Livermore National Laboratory’s (LLNL) pulsed sphere benchmark experiments were simulated in Shift to validate both the time-independent as well as new time-dependent features recently incorporated into Shift. A suite of pulsed-sphere models was simulated using Shift and compared to the available experimental data and simulations with MCNP. Overall results indicate that Shift accurately simulates the pulsed sphere benchmarks, and that the new time-dependent modifications of Shift are working as intended. Validated exascale neutron transport codes are essential for a wide variety of future multiphysics applications.

Palmer, Camille J.↗
NASA NTRS1972

Experimental investigation of the visual field dependency in the erect and supine positions

The increasing utilization of simulators in many fields, in addition to aeronautics and space, requires the efficient use of these devices. It seemed that personnel highly influenced by the visual scene would make desirable subjects, particularly for those simulators without sufficient motion cues. In order to evaluate this concept, some measure of the degree of influence of the visual field on the subject in necessary. As part of this undertaking, 37 male and female subjects, including eight test pilots, were tested for their visual field dependency or independency. A version of Witkin's rod and frame apparatus was used for the tests. The results showed that nearly all the test subjects exhibited some degree of field dependency, the degree varying from very high field dependency to nearly zero field dependency in a normal distribution. The results for the test pilots were scattered throughout a range similar to the results for the bulk of male subjects. The few female subjects exhibited a higher field dependency than the male subjects. The male subjects exhibited a greater field dependency in the supine position than in the erect position, whereas the field dependency of the female subjects changed only slightly.

Lichtenstein, J. H.↗
NASA NTRS1994

Interplanetary magnetic field dependency of stable Sun-aligned polar cap arcs

This is the first analysis, using a statistically significant data set, of the morphological dependence of the presence, orientation, and motion of stable sun-aligned polar cap arcs upon the vector interplanetary magnetic field (IMF). For the one winter season analyzed we had 1392 all-sky 630.0-nm images of 2-min resolution containing a total of 150 polar cap arcs, all with corresponding values of the IMF as measured by International Monitoring Platform (IMP) 8 or International Sun Earth Explorer (ISEE) 2. After demonstrating an unbiased data set with smooth normal distributions of events versus the dimensions of time, space, and IMF component, we examine IMF dependencies of the properties of the optical arcs. A well-defined dependence for B(sub z) is found for the presence/absence of stable Sun-aligned polar cap arcs. Consistent with previous statistical studies, the probability of observing polar cap aurora steadily increases for larger positive values of B(sub z), and linearly decreases when B(sub z) becomes more negative. The probability of observing Sun-aligned arcs within the polar cap is determined to vary sharply as a function of the arc location; arcs were observed 40% of the time on the dawnside and only 10% on the duskside. This implies an overall probability of at least 40% for the whole polar cap. 20% of the arcs were observed during 'southward IMF conditions,' but in fact under closer inspection were found to have been formed under northward IMF conditions; these 'residual' positive B(sub z) arcs ha d a delayed residence time in the polar cap of about what would be expected after a north to south transition of B(sub z). A firm dependence on B(sub y) is also found for both the orientation and the dawn-dusk direction of motion of the arcs. All the arcs are Sun-aligned to a first approximation, but present deviations from this orientation, depending primarily upon the location of the arc in corrected geomagnetic (CG) coordinates. The arcs populating the 06-12 and the 12-18 quadrants of the CG coordinate system point toward the cusp. The B(sub y) dependency of the arc alignment is consistent with a cusp displacement in local time according to the sign of B(sub y). We found that the arc direction of motion depended both on B(sub y) and the arc location within the polar cap. For a given value of B(sub y) two well-defined regions (or cells) exist. Within each cell the arcs move in the same direction toward the boundary between the cells. The arcs located in the duskside move dawnward; those in the dawnside move duskward. The relative size of these dusk and dawn regions (or cells) are controlled by the magnitude of B(sub y). This persistent dusk-dawn motion fo the polar cap arcs is interpreted in terms of newly open flux tubes entering the polar cap and exerting a displacement of the convective cells and the polar cap arcs that are embedded within them.

Valladares, C. E.↗
NASA NTRS2000

Angular and Energy Dependence of Proton Upset in Optocouplers

Proton upset effects in optocouplers were reported by LaBel, et al. that showed an unexpected increase in cross section for incident angles above 80 degrees. Although it appeared that the angular dependence was related to direct ionization from protons, the angular dependence was weaker than expected from basic geometrical arguments using a shallow charge collection depth. Later work showed that the angular dependence of proton upset observed in the earlier studies at a single energy could be explained by considering the distribution of proton recoil energies along with the assumption of a deeper charge collection depth, which was consistent with upset tests from heavy ions. However, an experimental test of the underlying assumptions in the latter work has yet to be done. Protons in space not only arrive over a wide range of incident angles, but also involve a distribution of proton energies. It is necessary to understand both the angular dependence and the dependence of proton upset on energy in order to determine how optocouplers will respond in space. If the angular dependence only occurs for extreme angles of incidence, it will have little impact on the overall cross section because of the narrow acceptance angle. The present work examines mechanisms for proton upset in optocouplers in more detail, investigating the energy dependence and the effects of different load conditions. A model for proton upset is developed, along with a laboratory screening method to determine whether direct ionization is significant for specific device types.

Johnston, A. H.↗
NASA NTRS2020

Assessment of Temperature-Dependent Regression Model Terms of a RUAG Six-Component Block-Type Balance

A metric called the percent contribution was applied to regression models of temperature-dependent calibration data of a RUAG six-component block-type balance in order to assess the influence of temperature-dependent regression model terms on the balance load prediction. Regression models were examined that are needed if either the Iterative or the Non-Iterative Method is used for the load prediction. Computed values of the percent contribution confirmed that the cross-product term defined by a primary load and the temperature difference is the most influential temperature-dependent term of the regression model of a primary output that the Iterative Method needs. Similarly, the analysis showed that the cross-product term defined by a primary output and the temperature difference is the most influential temperature-dependent term of the regression model of a primary load that the Non-Iterative Method needs. Computed results support conclusions that were reported in an earlier theoretical study. This study asserted that the cross-product term defined by a primary load or output and the temperature difference models the temperature-dependent shift of the gage sensitivity. The influence of other temperature-dependent terms used in the regression models of the calibration data of RUAG's balance was negligible. This observation may be explained by the fact that RUAG's block-type balances have highly linear characteristics. Overall, the percent contribution has proven itself to be a reliable and easy-to-implement metric that may also be used for the assessment of the influence of temperature-dependent regression model terms on the load prediction of a six-component strain-gage balance.

Ulbrich, N.↗
DOE OSTI2022

Defining and Measuring Forest Dependence in the United States: Operationalization and Sensitivity Analysis

This manuscript helps bridge a gap between theoretical work that advocates for a broad view of forest dependence, and empirical work that has focused narrowly on economic measures. Background: Forest dependence has been widely recognized as a valuable concept for understanding human communities’ well-being and vulnerability to shocks and changes. Past theoretical literature has highlighted the importance of recognizing various types of dependence—environmental, economic, and social—yet past empirical literature on the topic in the United States has almost exclusively relied on measures of economic dependence such as employment and earnings from the traditional forest products sector. Objective and Methods: As a first step to bridge the gap between the theoretical and empirical, we reviewed the existing, publicly available, reliable, wall-to-wall data sources to identify alternate proxy measures for forest dependence. Data availability made the analysis feasible only at the county level—the administrative subdivisions of the state—or higher. Results and Conclusions: We created environmental, economic, and social criteria based on threshold levels of the following proxy variables: forest area, earnings, employment, and indigenous population. Using these criteria, we identified 524 counties to be potentially forest-dependent of 3140 total counties in the United States. The largest concentration was in the Pacific Northwest and Southeast regions, and a higher proportion were non-metro counties than metro. Varying the threshold levels significantly changes the number of counties identified but does not alter the overall geographic trends.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Predicting responses to climate change using a joint species, spatially dependent physiologically guided abundance model

Abstract Predicting the effects of warming temperatures on the abundance and distribution of organisms under future climate scenarios often requires extrapolating species–environment correlations to climatic conditions not currently experienced by a species, which can result in unrealistic predictions. For poikilotherms, incorporating species' thermal physiology to inform extrapolations under novel thermal conditions can result in more realistic predictions. Furthermore, models that incorporate species and spatial dependencies may improve predictions by capturing correlations present in ecological data that are not accounted for by predictor variables. Here, we present a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming. The jsPGA model uses a basis function approach to capture both species and spatial dependencies. We apply the jsPGA model to predict the response of eight fish species to projected climate warming in thousands of lakes in Minnesota, USA. By the end of the century, the cold‐adapted species was predicted to have high probabilities of extirpation across its current range—with 10% of lakes currently inhabited by this species having an extirpation probability >0.90. The remaining species had varying levels of predicted changes in abundance, reflecting differences in their thermal physiology. Though the model did not identify many strong species dependencies, the variation in estimated spatial dependence across species suggested that accounting for both dependencies was important for predicting the abundance of these fishes. The jsPGA model provides a new tool for predicting changes in the abundance, distribution, and extirpation probability of poikilotherms under novel thermal conditions.

54 ENVIRONMENTAL SCIENCES↗