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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Classical Preoptimization Approach for ADAPT-VQE: Maximizing the Potential of High-Performance Computing Resources to Improve Quantum Simulation of Chemical Applications

The ADAPT-VQE algorithm is a promising method for generating a compact ansatz based on derivatives of the underlying cost function, and it yields accurate predictions of electronic energies for molecules. In this work, we report the implementation and performance of ADAPT-VQE with our recently developed sparse wave function circuit solver (SWCS) in terms of accuracy and efficiency for molecular systems with up to 52 spin orbitals. The SWCS can be tuned to balance computational cost and accuracy, which extends the application of ADAPT-VQE for molecular electronic structure calculations to larger basis sets and a larger number of qubits. Using this tunable feature of the SWCS, we propose an alternative optimization procedure for ADAPT-VQE to reduce the computational cost of the optimization. Furthermore, by preoptimizing a quantum simulation with a parametrized ansatz generated with ADAPT-VQE/SWCS, we aim to utilize the power of classical high-performance computing in order to minimize the work required on noisy intermediate-scale quantum hardware, which offers a promising path toward demonstrating quantum advantage for chemical applications.

ADAPT-VQE↗
DOE OSTI2024

Boundary-Aware Adversarial Learning Domain Adaption and Active Learning for Cross-Sensor Building Extraction

The use of convolutional neural networks (CNNs) for building extraction from remote sensing images has been widely studied and many public datasets have been made available for accelerating development of these CNN models. Yet adapting pretrained models at scale in real-world scenarios remains a challenging task. The main barrier is that certain new labels are still needed to compensate for domain shifting between the labeled data and new images that potentially cover new geographic locations or that are from a different sensor. In this article, we propose to add informatively labeled samples from a new image pool under the paradigm of active learning. To select the most useful samples based on model uncertainty, we first tackle the problem of uncalibrated uncertainty estimation due to distribution shifting by adapting feature extractors with boundary-based adversarial learning. Calibrated uncertainty is used as the query criterion in the active learning process, where the most uncertain samples are selected for annotation and included for model retraining. The proposed workflow was tested with three data pairs in which each workflow represents a scenario often encountered in real-world applications, including adapting pretrained models to new images collected with different sensors or to new geographic areas where appearances and types of buildings are very different. Compared to several baselines, including random sampling, temperature scaling (a well-known uncertainty calibration technique), different query strategies, and active domain adaptation methods, the proposed workflow shows that strategically querying a smaller set of samples for labeling achieves comparable or better building extraction performance. The proposed method reduces the number of labeled samples required to achieve sufficient model accuracy, thus significantly reducing hundreds of person-hours for labeled data creation. In addition, we include a few considerations when deploying this workflow in a GPU cluster that can be easily adapted to achieve operational building extraction model retraining.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Improving Deep Neural Networks’ Training for Image Classification With Nonlinear Conjugate Gradient-Style Adaptive Momentum

Momentum is crucial in stochastic gradient-based optimization algorithms for accelerating or improving training deep neural networks (DNNs). In deep learning practice, the momentum is usually weighted by a well-calibrated constant. However, tuning the hyperparameter for momentum can be a significant computational burden. In this article, we propose a novel adaptive momentum for improving DNNs training; this adaptive momentum, with no momentum-related hyperparame- ter required, is motivated by the nonlinear conjugate gradient (NCG) method. Stochastic gradient descent (SGD) with this new adaptive momentum eliminates the need for the momentum hyperparameter calibration, allows using a significantly larger learning rate, accelerates DNN training, and improves the final accuracy and robustness of the trained DNNs. For example, SGD with this adaptive momentum reduces classification errors for training ResNet110 for CIFAR10 and CIFAR100 from 5.25% to 4.64% and 23.75% to 20.03%, respectively. Furthermore, SGD, with the new adaptive momentum, also benefits adversarial training and, hence, improves the adversarial robustness of the trained DNNs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Improved Localization Precision and Angular Resolution of a Cylindrical, Time-Encoded Imaging System From Adaptive Detector Movements

To the first order, the localization precision and angular resolution of a cylindrical, time-encoded imaging (c-TEI) system is governed by the geometry of the system. Improving either measure requires increasing the mask radius or decreasing the detector diameter, both of which are undesirable. Here, we propose an alternative option of repositioning the detector within the mask to increase the detector-to-mask distance in the direction of a source, thereby improving the localization precision and angular resolution in that direction. Since the detector-to-mask distance only increases for a small portion of the field of view (FOV), we propose implementing adaptive imaging where one leverages data collected during the measurement to optimize the system configuration. This article utilizes both simulations and experiments to set upper bounds on the potential gain from adaptive detector movements for one and two sources in the FOV. When only one source is present, adaptive detector movements can improve the localization precision and angular resolution by 20% for a source at 90 cm and by 32% for a far-field source. When two sources are present, adaptive detector movements can improve localization precision and angular resolution by up to 50% for sources that are ~10° apart (90 cm from the system). We experimentally verify these results through maximum likelihood estimation of the source position(s) and image reconstruction of point sources that are close together. As a demonstration of an adaptive imaging algorithm, we image a complex arrangement of special nuclear material at the Zero Power Physics Reactor facility at Idaho National Laboratory.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2019

Gene Regulation Shifts Shed Light on Fungal Adaption in Plant Biomass Decomposers

ABSTRACT Fungi dominate the recycling of carbon sequestered in woody biomass. This process of organic turnover was first evolved among “white rot” fungi that degrade lignin to access carbohydrates and later evolved multiple times toward more efficient strategies to selectively target carbohydrates—“brown rot.” The brown rot adaption was often explained by mechanisms to deploy reactive oxygen species (ROS) to oxidatively attack wood structures. However, its genetic basis remains unclear, especially in the context of gene contractions of conventional carbohydrate-active enzymes (CAZYs) relative to white rot ancestors. Here, we hypothesized that these apparent gains in brown rot efficiency despite gene losses were due, in part, to upregulation of the retained genes. We applied comparative transcriptomics to multiple species of both rot types grown across a wood wafer to create a gradient of progressive decay and to enable tracking temporal gene expression. Dozens of “decay-stage-dependent” ortho-genes were isolated, narrowing a pool of candidate genes with time-dependent regulation unique to brown rot fungi. A broad comparison of the expression timing of CAZY families indicated a temporal regulatory shift of lignocellulose-oxidizing genes toward early stages in brown rot compared to white rot, enabling the segregation of oxidative treatment ahead of hydrolysis. These key brown rot ROS-generating genes with iron ion binding functions were isolated. Moreover, transcription energy was shifted to be invested on the retained GHs in brown rot fungi to strengthen carbohydrate conversion. Collectively, these results support the hypothesis that gene regulation shifts played a pivotal role in brown rot adaptation. IMPORTANCE Fungi dominate the turnover of wood, Earth’s largest pool of aboveground terrestrial carbon. Fungi first evolved this capacity by degrading lignin to access and hydrolyze embedded carbohydrates (white rot). Multiple lineages, however, adapted faster reactive oxygen species (ROS) pretreatments to loosen lignocellulose and selectively extract sugars (brown rot). This brown rot “shortcut” often coincided with losses (>60%) of conventional lignocellulolytic genes, implying that ROS adaptations supplanted conventional pathways. We used comparative transcriptomics to further pursue brown rot adaptations, which illuminated the clear temporal expression shift of ROS genes, as well as the shift toward synthesizing more GHs in brown rot relative to white rot. These imply that gene regulatory shifts, not simply ROS innovations, were key to brown rot fungal evolution. These results not only reveal an important biological shift among these unique fungi, but they may also illuminate a trait that restricts brown rot fungi to certain ecological niches.

plant biomas↗
DOE OSTI2020

A Method for Dimensionally Adaptive Sparse Trigonometric Interpolation of Periodic Functions

We present a method for dimensionally adaptive sparse trigonometric interpolation of multidimensional periodic functions belonging to a smoothness class of finite order. This method targets applications where periodicity must be preserved and the precise anisotropy is not known a priori. To the authors' knowledge, this is the first instance of a dimensionally adaptive sparse interpolation algorithm that uses a trigonometric interpolation basis. The motivating application behind this work is the adaptive approximation of a multi-input model for a molecular potential energy surface (PES) where each input represents an angle of rotation. Our method is based on an anisotropic quasi-optimal estimate for the decay rate of the Fourier coefficients of the model; a least-squares fit to the coefficients of the interpolant is used to estimate the anisotropy. Thus, our adaptive approximation strategy begins with a coarse isotropic interpolant, which is gradually refined using the estimated anisotropic rates. The procedure takes several iterations where ever-more accurate interpolants are used to generate ever-improving anisotropy rates. We present several numerical examples of our algorithm where the adaptive procedure successfully recovers the theoretical “best” convergence rate, including an application to a periodic PES approximation. An open-source implementation of our algorithm resides in the Tasmanian UQ library developed at Oak Ridge National Laboratory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Comparative genomics reveals the high diversity and adaptation strategies of Polaromonas from polar environments

Abstract Background Bacteria from the genus Polaromonas are dominant phylotypes found in a variety of low-temperature environments in polar regions. The diversity and biogeographic distribution of Polaromonas have been largely expanded on the basis of 16 S rRNA gene amplicon sequencing. However, the evolution and cold adaptation mechanisms of Polaromonas from polar regions are poorly understood at the genomic level. Results A total of 202 genomes of the genus Polaromonas were analyzed, and 121 different species were delineated on the basis of average nucleotide identity (ANI) and phylogenomic placements. Remarkably, 8 genomes recovered from polar environments clustered into a separate clade (‘polar group’ hereafter). The genome size, coding density and coding sequences (CDSs) of the polar group were significantly different from those of other nonpolar Polaromonas . Furthermore, the enrichment of genes involved in carbohydrate and peptide metabolism was evident in the polar group. In addition, genes encoding proteins related to betaine synthesis and transport were increased in the genomes from the polar group. Phylogenomic analysis revealed that two different evolutionary scenarios may explain the adaptation of Polaromonas to cold environments in polar regions. Conclusions The global distribution of the genus Polaromonas highlights its strong adaptability in both polar and nonpolar environments. Species delineation significantly expands our understanding of the diversity of the Polaromonas genus on a global scale. In this study, a polar-specific clade was found, which may represent a specific ecotype well adapted to polar environments. Collectively, genomic insight into the metabolic diversity, evolution and adaptation of the genus Polaromonas at the genome level provides a genetic basis for understanding the potential response mechanisms of Polaromonas to global warming in polar regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Adaptation Actions for a Changing Arctic: Perspectives from the Bering-Chukchi-Beaufort Region

In May 2013, the Arctic Council requested the Arctic Monitoring and Assessment Programme (AMAP) to “produce information to assist local decision-makers and stakeholders in three pilot regions in developing adaptation tools and strategies to better deal with climate change and other pertinent environmental stressors” (AMAP, 2017). Adaptation Actions for a Changing Arctic (AACA) is the response to that request: an assessment of climate and integrated social and environmental frameworks or models that can inform adaptation actions in the face of Arctic change. Three Arctic regions were chosen by AMAP for pilot assessments to be conducted simultaneously. This report is an assessment for the Bering-Chukchi-Beaufort (BCB) region. It focuses on the challenges that residents have experienced and the adaptations they have implemented in response to the rapid changes of recent decades – in climate, landscape, wildlife, and social, economic, and health systems. It also looks to the future and analyzes the strengths and deficiencies in societies’ and individuals’ abilities to adapt, so that decision-makers may better understand where assistance is needed or where alternatives must be developed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deep Sequencing of MHC-Adapted Viral Lines Reveals Complex Recombinational Exchanges With Endogenous Retroviruses Leading to High-Frequency Variants

Experimental evolution (serial passage) of Friend virus complex (FVC) in mice demonstrates phenotypic adaptation to specific host major histocompatibility complex (MHC) genotypes. These evolved viral lines show increased fitness and virulence in their host-genotype-of-passage, but display fitness and virulence tradeoffs when infecting unfamiliar host MHC genotypes. Here, we deep sequence these viral lines in an attempt to discover the genetic basis of FVC adaptation. The principal prediction for genotype-specific adaptation is that unique mutations would rise to high frequency in viral lines adapted to each host MHC genotype. This prediction was not supported by our sequencing data as most observed high-frequency variants were present in each of our independently evolved viral lines. However, using a multi-variate approach to measure divergence between viral populations, we show that populations of replicate evolved viral lines from the same MHC congenic mouse strain were more similar to one another than to lines derived from different MHC congenic mouse strains, suggesting that MHC genotype does predictably act on viral evolution in our model. Sequence analysis also revealed rampant recombination with endogenous murine leukemia virus sequences (EnMuLVs) that are encoded within the BALB/c mouse genome. The highest frequency variants in all six lines contained a 12 bp insertion from a recombinant EnMuLV source, suggesting such recombinants were either being favored by selection or were contained in a recombinational hotspot. Interestingly, they did not reach fixation, as if they are low fitness. The amount of background mutations linked to FVC/EnMuLV variable sites indicated that FVC/EnMuLV recombinants had not reached mutation selection equilibrium and thus, that EnMuLV sequences are likely continuously introgressing into the replicating viral population. These discoveries raise the question: is the expression of EnMuLV sequences in mouse splenocytes that permit recombination with exogenous FVC a pathogen or host adaptation?

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Adaptive Evolution of Sphingobium hydrophobicum C1 T in Electronic Waste Contaminated River Sediment

Electronic waste (e-waste) has caused a severe worldwide pollution problem. Despite increasing isolation of degradative microorganisms from e-waste contaminated environments, the mechanisms underlying their adaptive evolution in such habitats remain unclear. Sphingomonads generally have xenobiotic-degrading ability and may play important roles in bioremediation. Sphingobium hydrophobicum C1 T , characterized with superior cell surface hydrophobicity, was recently isolated from e-waste contaminated river sediment. To dissect the mechanisms driving its adaptive evolution, we evaluated its stress resistance, sequenced its genome and performed comparative genomic analysis with 19 other Sphingobium strains. Strain C1 T can feed on several kinds of e-waste-derived xenobiotics, exhibits a great resistance to heavy metals and possesses a high colonization ability. It harbors abundant genes involved in environmental adaptation, some of which are intrinsic prior to experiencing e-waste contamination. The extensive genomic variations between strain C1 T and other Sphingobium strains, numerous C1 T -unique genes, massive mobile elements and frequent genome rearrangements reflect a high genome plasticity. Positive selection, gene duplication, and especially horizontal gene transfer drive the adaptive evolution of strain C1 T . Moreover, presence of type IV secretion systems may allow strain C1 T to be a source of beneficial genes for surrounding microorganisms. This study provides new insights into the adaptive evolution of sphingomonads, and potentially guides bioremediation strategies.

comparative genomics↗
NASA NTRS2002

Sensorimotor aspects of high-speed artificial gravity: III. Sensorimotor adaptation

As a countermeasure to the debilitating physiological effects of weightlessness, astronauts could live continuously in an artificial gravity environment created by slow rotation of an entire spacecraft or be exposed to brief daily "doses" in a short radius centrifuge housed within a non-rotating spacecraft. A potential drawback to both approaches is that head movements made during rotation may be disorienting and nauseogenic. These side effects are more severe at higher rotation rates, especially upon first exposure. Head movements during rotation generate aberrant vestibular stimulation and Coriolis force perturbations of the head-neck motor system. This article reviews our progress toward distinguishing vestibular and motor factors in side effects of rotation, and presents new data concerning the rates of rotation up to which adaptation is possible. We have studied subjects pointing to targets during constant velocity rotation, because these movements generate Coriolis motor perturbations of the arm but do not involve unusual vestibular stimulation. Initially, reaching paths and endpoints are deviated in the direction of the transient lateral Coriolis forces generated. With practice, subjects soon move in straighter paths and land on target once more. If sight of the arm is permitted, adaptation is more rapid than in darkness. Initial arm movement trajectory and endpoint deviations are proportional to Coriolis force magnitude over a range of rotation speeds from 5 to 20 rpm, and there is rapid, complete motor adaptation at all speeds. These new results indicate that motor adaptation to high rotation rates is possible. Coriolis force perturbations of head movements also occur in a rotating environment but adaptation gradually develops over the course of many head movements.

Non-NASA Center↗
NASA NTRS2002

Context-specific adaptation of saccade gain

Previous studies established that vestibular reflexes can have two adapted states (e.g., gain) simultaneously, and that a context cue (e.g., vertical eye position) can switch between the two states. The present study examined this phenomenon of context-specific adaptationfor horizontal saccades, using a variety of contexts. Our overall goal was to assess the efficacy of different context cues in switching between adapted states. A standard double-step paradigm was used to adapt saccade gain. In each experiment, we asked for a simultaneous gain decrease in one context and gain increase in another context, and then determined if a change in the context would invoke switching between the adapted states. Horizontal eye position worked well as a context cue: saccades with the eyes deviated to the right could be made to have higher gains while saccades with the eyes deviated to the left could be made to have lower gains. Vertical eye position was less effective. This suggests that the more closely related a context cue is to the response being adapted, the more effective it is. Roll tilt of the head, and upright versus supine orientations, were somewhat effective in context switching; these paradigms contain orientation of gravity with respect to the head as part of the context.

NASA Discipline Neuroscience↗
NASA NTRS2000

Effects of adaptation of vestibulo-ocular reflex function on manual target localization

The goal of the present study was to determine if adaptive modulation of vestibulo-ocular reflex (VOR) function is associated with commensurate alterations in manual target localization. To measure the effects of adapted VOR on manual responses we developed the Vestibular-Contingent Pointing Test (VCP). In the VCP test, subjects pointed to a remembered target following passive whole body rotation in the dark. In the first experiment, subjects performed VCP before and after wearing 0.5X minifying lenses that adaptively attenuate horizontal VOR gain. Results showed that adaptive reduction in horizontal VOR gain was accompanied by a commensurate change in VCP performance. In the second experiment, bilaterally labyrinthine deficient (LD) subjects were tested to confirm that vestibular cues were central to the spatial coding of both eye and hand movements during VCP. LD subjects performed significantly worse than normal subjects. These results demonstrate that adaptive change in VOR can lead to alterations in manual target localization.

NASA Center JSC↗
NASA NTRS1996

A low, adaptive dose of gamma-rays reduced the number and altered the spectrum of S1- mutants in human-hamster hybrid AL cells

We examined the effects of a low, adaptive dose of 137Cs-gamma-irradiation (0.04 Gy) on the number and kinds of mutants induced in AL human-hamster hybrid cells by a later challenge dose of 4 Gy. The yield of S1- mutants was significantly less (by 53%) after exposure to both the adaptive and challenge doses compared to the challenge dose alone. The yield of hprt- mutants was similarly decreased. Incubation with cycloheximide (CX) or 3-aminobenzamide largely negated the decrease in mutant yield. The adaptive dose did not perturb the cell cycle, was not cytotoxic, and did not of itself increase the mutant yield above background. The adaptive dose did, however, alter the spectrum of S1- mutants from populations exposed only to the adaptive dose, as well as affecting the spectrum of S1- mutants generated by the challenge dose. The major change in both cases was a significant increase in the proportion of complex mutations compared to small mutations and simple deletions.

Non-NASA Center↗
NASA NTRS2014

Complexity and Pilot Workload Metrics for the Evaluation of Adaptive Flight Controls on a Full Scale Piloted Aircraft

Flight research has shown the effectiveness of adaptive flight controls for improving aircraft safety and performance in the presence of uncertainties. The National Aeronautics and Space Administration's (NASA)'s Integrated Resilient Aircraft Control (IRAC) project designed and conducted a series of flight experiments to study the impact of variations in adaptive controller design complexity on performance and handling qualities. A novel complexity metric was devised to compare the degrees of simplicity achieved in three variations of a model reference adaptive controller (MRAC) for NASA's F-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Full-Scale Advanced Systems Testbed (Gen-2A) aircraft. The complexity measures of these controllers are also compared to that of an earlier MRAC design for NASA's Intelligent Flight Control System (IFCS) project and flown on a highly modified F-15 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois). Pilot comments during the IRAC research flights pointed to the importance of workload on handling qualities ratings for failure and damage scenarios. Modifications to existing pilot aggressiveness and duty cycle metrics are presented and applied to the IRAC controllers. Finally, while adaptive controllers may alleviate the effects of failures or damage on an aircraft's handling qualities, they also have the potential to introduce annoying changes to the flight dynamics or to the operation of aircraft systems. A nuisance rating scale is presented for the categorization of nuisance side-effects of adaptive controllers.

pilot workload metrics↗
NASA NTRS2014

Hurricane Sandy and Adaptation Pathways in New York: Lessons from a First-Responder City

Two central issues of climate change have become increasingly evident: Climate change will significantly affect cities; and rapid global urbanization will increase dramatically the number of individuals, amount of critical infrastructure, and means of economic production that are exposed and vulnerable to dynamic climate risks. Simultaneously, cities in many settings have begun to emerge as early adopters of climate change action strategies including greenhouse gas mitigation and adaptation. The objective of this paper is to examine and analyze how officials of one city - the City of New York - have integrated a flexible adaptation pathways approach into the municipality's climate action strategy. This approach has been connected with the City's ongoing response to Hurricane Sandy, which struck in the October 2012 and resulted in damages worth more than US$19 billion. A case study narrative methodology utilizing the Wise et al. conceptual framework (see this volume) is used to evaluate the effectiveness of the flexible adaptation pathways approach in New York City. The paper finds that Hurricane Sandy serves as a ''tipping point'' leading to transformative adaptation due to the explicit inclusion of increasing climate change risks in the rebuilding effort. The potential for transferability of the approach to cities varying in size and development stage is discussed, with elements useful across cities including the overall concept of flexible adaptation pathways, the inclusion of the full metropolitan region in the planning process, and the co-generation of climate-risk information by stakeholders and scientists.

adaptation pathways↗
NASA NTRSDate not supplied

Verification of Viscous Goal-Based Anisotropic Mesh Adaptation

Adaptive unstructured mesh techniques have a limited, but growing impact on production analysis workflows where the control of discretization error is critical to obtaining reliable simulation results. Recent progress has matured a number of independent implementations of flow solvers, anisotropic metric construction methods, and anisotropic mesh adaptation mechanics. A key ingredient for the broader acceptance of unstructured mesh adaptation is the verification of these implementations. Anisotropic metric construction methods are evaluated with analytically defined primal fields and the corresponding entropy variables as adjoint fields. This allows the comparison of different metric formulations and different implementations of the same formulation without the complications of a flow and adjoint solution method. The convergence of the output associated with the entropy variable adjoint is studied for mesh adaptation to these fields and a manufactured solution. Mesh adapted drag output is studied for two simple wings in compressible laminar flow to show fine-mesh convergence of multiple metric construction methods to less than a single drag count. The documentation of these verification exercises helps to prepare these goal-based methods for routine use in more complex simulations for production workflows.

mesh adaptation↗
NASA NTRS2021

Agricultural Breadbaskets Shift Poleward Given Adaptive Farmer Behavior Under Climate Change

Modern food production is spatially concentrated in global “breadbaskets”. A major unresolved question is whether these peak production regions will shift poleward as the climate warms, allowing some recovery of potential climaterelated losses. While agricultural impacts studies to date have focused on currently cultivated land, the Global Gridded Crop Model Intercomparison Project (GGCMI) Phase 2 experiment allows us to assess changes in both yields and the location of peak productivity regions under warming. We examine crop responses under projected end-of-century warming using 7 process-based models simulating 5 major crops (maize, rice, soybeans, and spring and winter wheat) with a variety of adaptation strategies. We find that in no-adaptation cases, when planting date and cultivar choices are held fixed, regions of peak production remain stationary and yield losses can be severe, since growing seasons contract strongly with warming. When adaptations in management practices are allowed (cultivars that retain growing season length under warming and modified planting dates), peak productivity zones shift poleward and yield losses are largely recovered. While most growing-zone shifts are ultimately limited by geography, breadbaskets studied here move poleward over 600 km on average by end of the century under RCP8.5. These results suggest that agricultural impacts assessments can be strongly biased if restricted in spatial area or in the scope of adaptive behavior considered. Accurate evaluation of food security under climate change requires global modeling and careful treatment of adaptation strategies.

adaptation↗