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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Determining circuit model parameters from operation data for PV system degradation analysis: $\mathrm{PVPRO}$

Physics-based circuit parameters like series and shunt resistance are essential to provide insights into the degradation status of photovoltaic (PV) arrays. However, calculating these parameters typically requires a full current-voltage characteristic (I-V curve), the acquisition of which involves specific measurement devices and costly methods. Thus, I-V curves of the PV system level are often not available. Here this paper proposes a methodology (PVPRO) to estimate these I-V curve parameters using only operation (string-level DC voltage and current) and weather data (irradiance and temperature). PVPRO first performs multi-stage data pre-processing to remove noisy data. Next, the time-series DC data are used to fit an equivalent circuit single-diode model (SDM) to estimate the circuit parameters by minimizing the differences between the measured and estimated values. In this way, the time evolutions of the SDM parameters are obtained. We evaluate PVPRO on synthetic datasets and find an excellent estimation of both SDM and the key I-V parameters (e.g., open-circuit voltage, short-circuit current, maximum power, etc.) with an average relative error of 0.55%. The performance, especially the extracted degradation rate of parameters, is robust to various measurement noises and the presence of faults. In addition, PVPRO is applied to a 271 kW PV field system. The relative error between the real and estimated operation voltage and current is less than 1%, suggesting that degradation trends are well captured. PVPRO represents a promising open-source tool to extract the time-series degradation trends of key PV parameters from routine operation data.

14 SOLAR ENERGY↗
DOE OSTI2021

Large-momentum effective theory

Since the parton model was introduced by Feynman more than 50 years ago, much has been learned about the partonic structure of the proton through a large body of high-energy experimental data and dedicated global fits. However, limited progress has been made in calculating partonic observables such as the parton distribution function (PDFs) from the fundamental theory of strong interactions, quantum chromodynamics (QCD). Recently some advocated for a formalism, large-momentum effective theory (LaMET), through which one can extract parton physics from the properties of the proton traveling at a moderate boost factor such as γ ~ 2 – 5 . The key observation behind this approach is that Lorentz symmetry allows the standard formalism of partons in terms of light-front operators to be replaced by an equivalent one with large-momentum states and time-independent operators of a universality class. With LaMET, the PDFs, generalized PDFs or generalized parton distributions, transverse-momentum-dependent PDFs, and light-front wave functions can all be extracted in principle from lattice simulations of QCD (or other nonperturbative methods) through standard effective field theory matching and running. Future lattice QCD calculations with exascale computational facilities could help one to understand the experimental data related to the hadronic structure, including those from the upcoming electron-ion colliders dedicated to exploring the partonic landscape of the proton. In this work, the progress made in the past few years in the development of the LaMET formalism and its applications is reviewed, with an emphasis on a demonstration of its effectiveness from initial lattice QCD simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems

In this work, we present Lift & Learn, a physics-informed method for learning low-dimensional models for large-scale dynamical systems. The method exploits knowledge of a system’s governing equations to identify a coordinate transformation in which the system dynamics have quadratic structure. This transformation is called a lifting map because it often adds auxiliary variables to the system state. The lifting map is applied to data obtained by evaluating a model for the original nonlinear system. This lifted data is projected onto its leading principal components, and low-dimensional linear and quadratic matrix operators are fit to the lifted reduced data using a least-squares operator inference procedure. Analysis of our method shows that the Lift & Learn models are able to capture the system physics in the lifted coordinates at least as accurately as traditional intrusive model reduction approaches. This preservation of system physics makes the Lift & Learn models robust to changes in inputs. Numerical experiments on the FitzHugh–Nagumo neuron activation model and the compressible Euler equations demonstrate the generalizability of our model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The 3D Lyman- α forest power spectrum from eBOSS DR16

We measure the three-dimensional power spectrum (P3D) of the transmitted flux in the Lyman-α (Ly α) forest using the complete extended Baryon Oscillation Spectroscopic Survey data release 16 (eBOSS DR16). This sample consists of ~205 000 quasar spectra in the redshift range 2 ≤ z ≤ 4 at an effective redshift z = 2.334. We propose a pair-count spectral estimator in configuration space, weighting each pair by exp( i k ∙ r), for wave vector k and pixel pair separation r, effectively measuring the anisotropic power spectrum without the need for fast Fourier transforms. This accounts for the window matrix in a tractable way, avoiding artefacts found in Fourier-transform based power spectrum estimators due to the sparse sampling transverse to the line of sight of Ly α skewers. We extensively test our pipeline on two sets of mocks: (i) idealized Gaussian random fields with a sparse sampling of Ly α skewers, and (ii) log-normal LyaCoLoRe mocks including realistic noise levels, the eBOSS survey geometry and contaminants. On eBOSS DR16 data, the Kaiser formula with a non-linear correction term obtained from hydrodynamic simulations yields a good fit to the power spectrum data in the range $(0.02 ≤ k ≤ 0.35)$ h Mpc -1 at the 1–2σ level with a covariance matrix derived from LyaCoLoRe mocks. We demonstrate a promising new approach for full-shape cosmological analyses of Ly α forest data from cosmological surveys such as eBOSS, the currently observing Dark Energy Spectroscopic Instrument and future surveys such as the Prime Focus Spectrograph, WEAVE-QSO, and 4MOST.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

IER-580 CED-3b: Experiment Execution Summary for the Pulsed-Neutron Die-Away Experiments (PNDA) with H 2 O

This report summarizes new experiments performed with H 2 O for IER-580, a testbed for pulsed-neutron die-away (PNDA) experiments at Lawrence Livermore National Laboratory (LLNL). The experiments will become high-quality benchmarksthat serve to optimize and validate thermal neutron scattering laws (TSLs) of H 2 O, which are high-priority nuclear data for the Department of Energy’s Nuclear Criticality Safety Program (NCSP). The report presents the details of the measurements conducted in October of 2023, including the experimental set-up (PNDA equipment and H 2 O targets) and all experimentally measured data. The report gives the fitted decay constants for the die-away curves of each target sample. It also provides the tabulated data for the die-away curves in the appendices.

42 ENGINEERING↗
DOE OSTI2021

Combining Spectroscopic Techniques to Determine the Optical Constants of Powdered Lactose

A method for deriving the optical constants (n/k) of organic powdered materials using pressed pellets in the mid-infrared spectral range is introduced that combines variable angle spectroscopic ellipsometry and transmission spectroscopy. The approach is applied to lactose, in which three different forms of pellets were pressed and measured: A pure lactose pellet and a mixed lactose/KBr pellet with a large analyte percentage were used for ellipsometric measurements, and a KBr transmission pellet with only a small analyte percentage were used for transmission measurements. The transmission data provide an initial set of oscillators and improve the spectral fitting of weak absorption features (k<0.01). Ellipsometric data for the pure and mixed pellets are then fit simultaneously to derive the final n/k values for lactose from 6000-400 cm-1. An alternative method just using the ellipsometric data from the mixed pellet and the transmission data is also presented and shows good agreement with the multi-sample analysis, providing a simpler method for powders that do not press easily into pure pellets. Finally, the derived optical constants are used to model the reflectance data, demonstrating a good match with the measured reflectance spectra if non-idealities are included.

Yokosuk, Michael O.↗
DOE OSTI2021

Main-sequence Scatter is Real: The Joint Dependence of Galaxy Clustering on Star Formation and Stellar Mass

We present new measurements of the clustering of stellar-mass-complete samples of ∼40,000 SDSS galaxies at z ∼ 0.03 as a joint function of stellar mass and specific star formation rate (sSFR). Our results confirm what Coil et al. find at z ∼ 0.7: galaxy clustering is a stronger function of sSFR at fixed stellar mass than of stellar mass at fixed sSFR. We also find that galaxies above the star-forming main sequence (SFMS) with higher sSFR are less clustered than galaxies below the SFMS with lower sSFR, at a given stellar mass. A similar trend is present for quiescent galaxies. This confirms that main-sequence scatter, and scatter within the quiescent sequence, is physically connected to the large-scale cosmic density field. We compare the resulting galaxy bias versus sSFR, and relative bias versus sSFR ratio, for different galaxy samples across 0 < z < 1.2 to mock galaxy catalogs based on the empirical galaxy evolution model of Behroozi et al. This model fits PRIMUS and DEEP2 clustering data well at intermediate redshift, but agreement with SDSS is not as strong. We show that increasing the correlation between galaxy SFR and halo accretion rate at z ∼ 0 in the model substantially improves agreement with SDSS data. Mock catalogs suggest that central galaxies contribute substantially to the dependence of clustering on sSFR at a given stellar mass and that the signal is not simply an effect of satellite galaxy fraction differences with sSFR. Our results are highly constraining for galaxy evolution models and show that the stellar-to-halo mass relation depends on sSFR.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Mapping Incidence and Prevalence Peak Data for SIR Modeling Applications

Infectious disease modeling and forecasting have played a key role in helping assess and respond to epidemics and pandemics. Recent work has leveraged data on disease peak infection and peak hospital incidence to fit compartmental models for the purpose of forecasting and describing the dynamics of a disease outbreak. Incorporating these data can greatly stabilize a compartmental model fit on early observations, where slight perturbations in the data may lead to model fits that forecast wildly unrealistic peak infection. We introduce a new method for incorporating historic data on the value and time of peak incidence of hospitalization into the fit for a Susceptible-Infectious-Recovered (SIR) model by formulating the relationship between an SIR model’s starting parameters and peak incidence as a system of two equations that can be solved computationally. We demonstrate how to calculate SIR parameter estimates – which describe disease dynamics such as transmission and recovery rates – using this method, and determine that there is a noticeable loss in accuracy whenever prevalence data is misspecified as incidence data. To exhibit the modeling potential, we update the Dirichlet-Beta State Space modeling framework to use hospital incidence data, as this framework was previously formulated to incorporate only data on total infections. This approach is assessed for practicality in terms of accuracy and speed of computation via simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Investigation of Mass Transfer and Sorption in CO 2 /Brine/Rock Systems via In Situ FT-IR

CO 2 geological storage in deep saline formations is considered a promising method to mitigate anthropogenic CO 2 emissions and, thereby, minimize changes to the Earth’s atmosphere. A fundamental understanding of CO 2 mass transfer and sorption phenomena in brine-saturated reservoir formations is necessary to understand the long-term fate of injected CO 2 as it is subjected to different (physical, dissolution, and mineral) trapping mechanisms. In this work, we investigate CO 2 sorption in brine-saturated and dry Mt. Simon sandstone samples via in-situ Fourier Transform infrared spectroscopy (FT-IR) at elevated pressures, ranging from 0.3 MPa to 8.3 MPa, at a temperature of 50 ⁰C. The FT-IR spectra of bulk-phase CO 2 were simultaneously recorded under the same conditions. For bulk-phase CO 2 , we observed, in agreement with past studies, a doublet peak at 2361 cm -1 and 2336 cm -1 and another peak (ν 2 bending mode) at 667 cm -1 . With increasing pressure, the position of the peak at 667 cm -1 remains invariant, however, when crossing into the supercritical region the doublet peak degenerates onto a single peak at 2336 cm -1 with a barely visible shoulder at 2361 cm -1 . The bulk CO 2 data provide a perfect fit for Beer’s law for the whole range of pressure conditions. For the dry sample, the IR spectrum is experimentally indistinguishable from the bulk CO 2 spectrum, signifying that if physical adsorption occurs to any significant extent, the adsorbed CO 2 molecules are not substantially more rotationally constrained than the dense bulk CO 2 molecules. For the brine-saturated sample, we observe a strong band centered at 2342 cm -1 and a small companion peak at 2360-2361 cm -1 that degenerates into a barely visible shoulder peak at the higher pressures. The 2342 cm -1 band has been previously observed by other investigators for CO 2 dissolved in bulk water/brine as well during its adsorption on a variety of other wet natural porous media. We observe no peaks corresponding to bicarbonate or carbonate bulk species, which correlates well with the prior literature on similar low-pH aqueous solutions. The integrated peak area for the CO 2 sorbed in the brine-saturated sample correlates linearly with its solubility in the same bulk brine, as measured separately via a PVT-cell approach. Here, this validates the accuracy of both techniques, and the potential of the FT-IR method to be used in the study of mass transfer and adsorption in such systems. To that effect, a simple mathematical model is presented to analyze the FT-IR data to determine the CO 2 effective diffusivity in the brine-saturated sandstone sample.

58 GEOSCIENCES↗
DOE OSTI2026

Determination of nuclear PDFs using Markov chain Monte Carlo methods

Global QCD analyses of nuclear parton distribution functions (nPDFs) have traditionally relied on the Hessian method for uncertainty estimation. However, the inherent Gaussian approximation and reliance on local curvature often prove insufficient for nPDF fits, which are frequently characterized by limited data constraints and non-Gaussian likelihoods. In this paper, we present the first nPDF determination based on Markov Chain Monte Carlo (MCMC) techniques, implemented within the nCTEQ framework using an adaptive Metropolis-Hastings algorithm. The MCMC approach enables a direct mapping of the posterior distribution and reveals a highly nontrivial parameter-space structure, including multiple modes and pronounced non-Gaussian behavior, particularly for the valence PDFs. We perform the first single-nucleus global analysis of lead PDFs using exclusively lead data and compare it to a multi-nuclei fit employing a standard analytic A dependence. The inclusion of lighter nuclei reduces quark uncertainties and modifies the shape of the lead PDFs, while leaving the gluon distribution largely unaffected. A complementary Hessian analysis exposes systematic limitations of the Gaussian approximation. Our results demonstrate that MCMC methods provide a more reliable framework for uncertainty quantification in nPDF determinations.

Derakhshanian, N. [Institute of Nuclear Physics Po↗
DOE OSTI2020

Blinding multiprobe cosmological experiments

ABSTRACT The goal of blinding is to hide an experiment’s critical results – here the inferred cosmological parameters – until all decisions affecting its analysis have been finalized. This is especially important in the current era of precision cosmology, when the results of any new experiment are closely scrutinized for consistency or tension with previous results. In analyses that combine multiple observational probes, like the combination of galaxy clustering and weak lensing in the Dark Energy Survey (DES), it is challenging to blind the results while retaining the ability to check for (in)consistency between different parts of the data. We propose a simple new blinding transformation, which works by modifying the summary statistics that are input to parameter estimation, such as two-point correlation functions. The transformation shifts the measured statistics to new values that are consistent with (blindly) shifted cosmological parameters while preserving internal (in)consistency. We apply the blinding transformation to simulated data for the projected DES Year 3 galaxy clustering and weak lensing analysis, demonstrating that practical blinding is achieved without significant perturbation of internal-consistency checks, as measured here by degradation of the χ2 between the data and best-fitting model. Our blinding method’s performance is expected to improve as experiments evolve to higher precision and accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

High pressure raman spectroscopy and X-ray diffraction of K2Ca(CO3)2 bütschliite: multiple pressure-induced phase transitions in a double carbonate

Abstract The crystal structure and bonding environment of K 2 Ca(CO 3 ) 2 bütschliite were probed under isothermal compression via Raman spectroscopy to 95 GPa and single crystal and powder X-ray diffraction to 12 and 68 GPa, respectively. A second order Birch-Murnaghan equation of state fit to the X-ray data yields a bulk modulus, $${K}_{0}=46.9$$ K 0 = 46.9 GPa with an imposed value of $${K}_{0}^{\prime}= 4$$ K 0 ′ = 4 for the ambient pressure phase. Compression of bütschliite is highly anisotropic, with contraction along the c -axis accounting for most of the volume change. Bütschliite undergoes a phase transition to a monoclinic C 2/ m structure at around 6 GPa, mirroring polymorphism within isostructural borates. A fit to the compression data of the monoclinic phase yields $${V}_{0}=322.2$$ V 0 = 322.2 Å 3 $$,$$ , $${K}_{0}=24.8$$ K 0 = 24.8 GPa and $${K}_{0}^{\prime}=4.0$$ K 0 ′ = 4.0 using a third order fit; the ability to access different compression mechanisms gives rise to a more compressible material than the low-pressure phase. In particular, compression of the C 2/ m phase involves interlayer displacement and twisting of the [CO 3 ] units, and an increase in coordination number of the K + ion. Three more phase transitions, at ~ 28, 34, and 37 GPa occur based on the Raman spectra and powder diffraction data: these give rise to new [CO 3 ] bonding environments within the structure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Extended Modeling of DOE Sealed Canisters with Updated Chemistry Models

Road-ready and final disposition packaging configurations for the advanced test reactor (ATR) fuel currently specifies storage within helium backfilled DOE sealed standard canisters. The aluminum cladding of the ATR fuel contains an oxyhydroxide layer of boehmite/bayerite that generates hydrogen when subjected to irradiation. Understanding the effect of this hydrogen buildup over time to important for long term storage considerations. Previous modeling efforts have built a coupled CFD-chemical model to simulate the temperature gas phase concentrations within the DOE sealed standard canisters. These models have coupled the temperature conditions to both the gas phase radiolysis chemistry and the surface chemistry associated with the oxyhydroxide layer. The previous iteration of the model utilized constant G-values for the hydrogen generation a 50-year period. This new iteration of the model utilizes new experimental data to update the hydrogen generation rate, as well as increase the simulated time to a 200-year period. Given the half-life assumed for the primary Cs-137 isotope responsible for gamma radiation in the ATR spent fuel, the 200-year period decreases the decay heat and dose rate of the spent fuel by a factor of 100, which combined with the updated chemistry substantially decreases new hydrogen generation. Continued experimental work has identified trends for aluminum surrogate samples with oxyhydroxide layers for tests done at higher dose rates. At low initial doses a fast generation rate of hydrogen occurs which starts to roll over to a lower generation as the total dose applied increase. A small-scale chemical model was built to replicate as mini-canister surrogate system at SRNL as well as for the smaller capsule tests performed at INL. A variety of chemical models to capture this effect were tested, and a back reaction of H radical absorbing onto the surface, or inhibition of the reaction by significant H 2 cover gas were both able to fit both the mini-canister and the small capsule test data. Both kinetic fits were used to generate data from the new 200-year simulation. As additional experiments continue, the kinetic fits may be adjusted to adapt to new data. However, updated data shows that hydrogen atmosphere has little effect on actual generation data, so the model was reverted to use a star-stepped G-value for low-dose and high-dose regions. For the undried fuel case, the three models differ significantly with an end concentration of 1% for back reaction, 4.2% for inhibition, and 13.1% for constant G-value for the nominal scenario. For the dried fuel case, the nominal cases showed end concentrations of 0.23% for back reaction, 1.9% for inhibition, and 4.2% for const G-value for the nominal scenario. For the constant G-value case that is less conservative than the other two, the pressure for undried fuel increases to 1.94 atm over 200 years for the nominal case and 2.11 atm for the high decay heat case. The total hydrogen concentration after 200 years is 4.92% for the low decay heat case and 27.4% for the high decay heat case for undried fuel and is 1.4% and 9.6% for low and high decay heat fuel for the dried fuel case. If small amount of residual air is present, the potential for nitric acid formation of 595, 1568, and 2816 ppm for the lower, nominal, and upper fuel decay heat can occur. At long-term timeframes no significant shift in major species present occurs, so no appreciable amount of oxygen is present in the system. The continued rate of hydrogen generation in the canister occurs at an increase of 0.04% by mole over the final 10 years. Increasing the model range out to 1000 years continues to drop the hydrogen generation rate through decreasing dose rate.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A Likely Magnetic Activity Cycle for the Exoplanet Host M Dwarf GJ 3512

Current radial velocity data from specialized instruments contain a large amount of information that may pass unnoticed if their analysis is not accurate. The joint use of Bayesian inference tools and frequency analysis has been shown as effective in revealing exoplanets but they have been used less frequently to investigate stellar activity. We intend to use radial velocity data of the exoplanet host star GJ 3512 to investigate its magnetic activity. Our study includes the analysis of the photometric data available. The main objectives of our work are to constrain the orbital parameters of the exoplanets in the system, to determine the current level of activity of the star and to derive an activity cycle length for it. An adaptive importance sampling method was used to determine the parameters of the exoplanets orbit. Generalized Lomb–Scargle periodograms were constructed with both radial velocity curve and photometric data. A careful analysis of the harmonic frequencies was conducted in each periodogram. Our fit to multiple Keplerian orbits constrained the orbital parameters of two giant gas planets orbiting the star GJ 3512. The host star showed an increase of its magnetic activity during the last observing campaign. The accurate fit of the radial velocity curve data to the multi-Keplerian orbit permitted to reveal the star rotation in the residuals of the best fit and estimate an activity cycle length of ~14 yr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Local models for scatter estimation and descattering in polyenergetic X-ray tomography

We propose a new modeling approach for scatter estimation and descattering in polyenergetic X-ray computed tomography (CT) based on fitting models to local neighborhoods of a training set. X-ray CT is widely used in medical and industrial applications. X-ray scatter, if not accounted for during reconstruction, creates a loss of contrast in CT reconstructions and introduces severe artifacts including cupping, shading, and streaks. Even when these qualitative artifacts are not apparent, scatter can pose a major obstacle in obtaining quantitatively accurate reconstructions. Our approach to estimating scatter is, first, to generate a training set of 2D radiographs with and without scatter using particle transport simulation software. To estimate scatter for a new radiograph, we adaptively fit a scatter model to a small subset of the training data containing the radiographs most similar to it. We compared local and global (fit on full data sets) versions of several X-ray scatter models, including two from the recent literature, as well as a recent deep learning-based scatter model, in the context of descattering and quantitative density reconstruction of simulated, spherically symmetrical, single-material objects comprising shells of various densities. Our results show that, when applied locally, even simple models provide state-of-the-art descattering, reducing the error in density reconstruction due to scatter by more than half.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Monte Carlo Global QCD Analyses of the Pion Parton Distribution Functions

As the lightest hadron, the pion presents itself as a dichotomy. While being the pseudo Goldstone boson associated with chiral symmetry breaking, it is simultaneously regarded as the lightest pseudoscalar meson typically composed of constituent quark and antiquark. As the chiral symmetry shares the same global symmetry as QCD, studying the pion and its internal structure is key in understanding one of the four fundamental forces of nature, namely the quantum chromodynamic strong interaction. We study the pion's parton distribution functions (PDFs), which are universal quantities that describe the structure of the pion in terms of its constituent quarks, antiquarks, and gluons. Our goal is to discover what the available data reveal for these universal quantities, namely the PDFs. Through the use of factorization theorems and perturbative QCD, we use Monte Carlo (MC) methods to extract the PDFs from the available Drell-Yan (DY) and leading neutron (LN) data. While the DY process involves two hadrons colliding, the LN electroproduction involves an electron beam incident on a target nucleon. We can constrain well the pion PDFs at large momentum fraction using DY data, and at low momentum fraction using LN data. We also use threshold resummation in the DY process to gather predictable higher order terms associated with the soft gluon radiation because their contributions to the cross section are nontrivial. In this dissertation, we parametrize the pion PDFs and fit those parameters to the available data. We make use of Bayesian inference and use MC techniques to sample the parameter space. Three sets of results are presented. We first extract the pion PDFs by fitting the DY and LN data. Then, we include transverse momentum dependent DY data in conjunction with the DY and LN data to extract the pion PDFs. Finally, we apply various methods of threshold resummation to the DY cross section and extract pion PDFs. The pion PDFs presented here are the first global QCD analyses performed as well as the first MC extracted pion PDFs, which are at the forefront of the pion PDF community.

Barry, Patrick↗
DOE OSTI2023

Spatial Bayesian models project shifts in suitable habitat for Pacific Northwest tree species under climate change

Abstract We developed spatial Bayesian hierarchical models to assess potential climate change impacts on suitable habitat for five important tree species in the Pacific northwestern United States (California, Oregon, and Washington). Individual‐species models were fit with presence–absence data from forest inventory field plots and spatial relationships were specified through a conditional autoregressive model. This modeling approach allowed us to visualize uncertainty in response curves, map current and future prediction uncertainty, and provide interval estimates for change. Upward elevational or northward latitudinal shifts in climatically suitable habitat were projected for all species. Climate change impacts were the most damaging for noble fir ( Abies procera ), for which 79%–100% of the current range was projected to become climatically unsuitable by the 2080s. Although coastal Douglas‐fir ( Pseudotsuga menziesii var. menziesii ) has been projected by others to gain habitat in Canada, within our study area we projected a net loss of climatically suitable habitat (ca. 8000–31,400 km 2 ) under three of four future climate scenarios. A net loss in habitat was also projected for Oregon white oak ( Quercus garryana ) under three of four scenarios, with 40%–60% of the current range becoming unsuitable. Although there was no net loss of habitat for forest land blue oak under any scenario, other factors like competition may inhibit blue oak ( Quercus douglasii ) and white oak from occupying areas projected to increase in climatic suitability. Additionally, between 13% and 32% of blue oak's current range was projected to become unsuitable; some of these areas aligned with dieback following the 2012–2015 California drought, which our data set predates. Unlike the other four species, we projected a 17%–25% increase in climatically suitable habitat for California black oak ( Quercus kelloggii ), although 1%–20% of the current range was still projected to become unsuitable. Our findings indicate that, although some species will face more pressure in tracking climatically suitable habitat than others, climate change will impact the location of suitable habitat for many species.

Kralicek, Karin↗