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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Correlational selection and genetic architecture shape the evolution of the leaf economics spectrum in a perennial grass

The generality of the worldwide leaf economics spectrum (LES) has made it a pillar of trait-based ecological research. Yet, few studies have examined the processes shaping the evolution of the LES within species, in part, because most species occupy only a small portion of the LES. Here, to address this gap, we took advantage of the distinct leaf economics strategies present in different ecotypes of the phenotypically diverse perennial grass Panicum virgatum (switchgrass) to generate a genetic mapping population, which we planted in common gardens at three sites spanning 12 degrees of latitude in the central United States. With this genetic mapping population, we evaluated two potentially interacting causes of LES evolution: 1) genetic architecture, where multiple traits are influenced by either the same gene (pleiotropy) or by genes in close physical proximity (genetic linkage), and 2) correlational selection, where selection acts on traits in combination rather than in isolation. We found that shared genetic architecture influenced covariation between photosynthetic rate (A MASS ) and leaf nitrogen (N MASS ) and between A MASS and leaf mass per area (LMA). We also found that correlational selection favored the trait combinations predicted by the LES (e.g., high LMA with low N MASS or low LMA with high N MASS ) and disfavored other, mismatched trait combinations at two of the three sites. Together, these results demonstrate how the evolution of an integrated LES within species can arise from multiple evolutionary causes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Degradation and deforestation increase the sensitivity of the Amazon Forest to climate extremes

About 40% of the Brazilian Amazon has been deforested or suffered changes in forest structure through degradation (selective logging, fires, and fragmentation). The impact of forest degradation on the forest’s sensitivity to climate extremes has not been fully explored because of a lack of data and the complex interplay of forest structure and climate drivers. Here, we combined forest structure data from 545 airborne lidar transects (375 ha each) across the Brazilian Amazon with the Ecosystem Demography Model (ED2). We explore the forest’s functional response to near-present (1981–2019) climate extremes under observed forest structure from lidar ( Control ) and two forest structure change scenarios: (1) forest recovery by excluding all future deforestation and degradation ( Recovery ) and (2) expansion of selective logging and deforestation ( Degradation ). Using the Control simulation, we found a close and positive association between local forest aboveground biomass and the predicted gross primary productivity (GPP) and evapotranspiration (ET). Moreover, both GPP and ET respond negatively to extremes in vapor pressure deficit and downwelling shortwave irradiance in degraded forests in Eastern and Southern Amazon, indicating high sensitivity to droughts. Locally high-biomass forest patches showed little or no negative response of GPP and ET to extreme drought conditions whereas low-biomass forest patches in the same locations—typically degraded forest canopies—responded negatively to higher moisture stress. The results from the Recovery scenario showed similar results to simulations with observed structure; however, under the Degradation scenario, low-biomass forest patches became more abundant, resulting in more regions where GPP and ET are negatively impacted by hot drought conditions according to the ED2 model. Our results suggest that local forest structure is a critical determinant of an ecosystem’s response to climate variability, and that the loss of canopy trees in the Amazon through forest degradation could increase and expand forest vulnerability to droughts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Thermal stress in degraded forests in the Brazilian Amazon Arc of Deforestation

Understanding thermal stress in tropical forests has taken on new urgency in light of accelerating climate change and expansion of deforestation and forest degradation. Degraded tropical forests in particular may be approaching critical temperature thresholds even more rapidly than intact forests, with implications for tree survival and ecosystem recovery. We investigate thermal stress in degraded tropical forests within the Brazilian Amazon Arc of Deforestation. Using land surface temperature data from the ECOsystem Spaceborne Thermal Radiometer Experiment on the international Space Station (ECOSTRESS), we compared canopy temperatures of intact, selectively logged, and burned forests in Feliz Natal, Mato Grosso, Brazil. Upper canopy temperatures in previously burned forests were 4.1% higher (mean = 36.5 °C) and 50.9% more variable compared to intact and logged forests, which showed remarkably similar temperature distributions (means of 34.9 °C and 35.1 °C, respectively). Modeled leaf temperature distributions based on canopy temperature measurements from one of the warmest days in a 2 year dry season record indicated that 87% of leaves in the warmest burned forest patches exceeded the temperature threshold where respiration surpasses photosynthesis, compared to approximately 72%–74% in intact and logged forests, respectively, in the same time period. After controlling for environmental factors, burned forests were predicted to be 2.6 °C warmer on average [1.39 °C–3.96 °C, 95% credible interval] than intact forests across a 5–40 m canopy height range. Burned forests showed modest thermal recovery over time, with temperatures decreasing by approximately 1.2 °C over a 30 year recovery period. In contrast, logged forests showed minimal thermal differences from intact forests (−0.353 on average, [−1.125–0.274, 95% credible interval]) and negligible change (0.15 °C) over the same timeframe. While the absolute probabilities of exceeding damaging thermal thresholds remain low across all forest types under current climate conditions, the probability of leaves exceeding temperatures that cause permanent leaf damage was ten times higher in burned forests, with implications for the future of burned forest regeneration in water-limited regions of the Amazon basin. In particular, the combination of higher mean temperatures, greater temperature variability, and more frequent exposure to damaging thermal thresholds implies that burned tropical forests will experience substantially higher mortality rates and slower biomass recovery compared to intact and selectively logged forests, especially in water-limited regions where trees cannot rely on evaporative cooling to moderate canopy temperatures.

Brazilian Amazon Arc of Deforestation↗
DOE OSTI2025

Deep-learning-based canopy height model generation from sub-meter resolution panchromatic satellite imagery

Canopy height models (CHMs) with sufficient resolution to distinguish individual trees are useful for a variety of applications. However, standard techniques to acquire such data, such as airborne lidar surveying, are often prohibitively expensive. Deep learning techniques for generating CHMs from high-resolution imagery are an attractive option to reduce costs. To date, success with these methods has been demonstrated using multichannel aerial photography and specialized satellite data products derived from multiple sensors, neither of which is commonly available at temporal resolutions finer than one year. Here we demonstrate a method to generate sub-meter resolution CHMs in three forests in California using a more abundant data source: sub-meter resolution, panchromatic satellite imagery from a single sensor. We show that phenology and species composition play important roles in model transferability; when trained using imagery from a single conifer forest in autumn, the model performs well on autumn imagery from a second conifer forest several hundred kilometers distant with no re-training. With modest additions to the training dataset, the same model generates minimally biased estimates of canopy height in both conifer and deciduous forests during multiple seasons. Because the model operates on satellite data with global coverage and a relatively short return interval, we propose its suitability to extrapolate tree-level canopy height data to remote regions and conduct high-temporal resolution monitoring of forest structure. We furthermore demonstrate the workflow’s applicability to fire modeling by conducting simulations in forests populated by trees measured using both this approach and airborne lidar surveying. We find minimal differences in fire behavior relative to a baseline case in which only statistical distributions of tree height and crown area are known. This result underscores the value of forest structural information derived from our workflow for improving the fidelity of wildland fire simulations, among other ecological applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Volatiles from the necrophagous fly Cochliomyia macellaria (Diptera: Calliphoridae) as indicators of Salmonella exposure

Blow flies (Diptera: Calliphoridae) are crucial in forensic investigations due to their association with both living and dead humans and other animals. Additionally, their interactions with various resources and potential as vectors of pathogens of humans and other animals, thus, make them potential tools for biosurveillance. This study investigated the potential of monitoring volatile organic compounds (VOCs) emitted by blow flies exposed to Salmonella as a method for pathogen surveillance. Adult blow flies ( Cochliomyia macellaria ) were exposed, or not, to Salmonella enterica . Following exposure, VOCs released by the blow flies were collected and analyzed using gas chromatography-mass spectrometry (GC-MS). Results indicate a treatment by time interaction (P < 0.01). Indicator species analysis identified a single compound significantly associated with S. enterica exposure (P = 0.02), Nonane, 2,2,4,4,6,8,8-heptamethyl, potentially indicating an immune system response. Given a compound indicating exposure was detected, future research should determine if more replicates could detect more differences after Salmonella ingestion. This research highlights the potential of blow flies as biosurveillance tools and the potential value of volatiles for assessing their exposure to pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Towards rational control of seed oil composition: dissecting cellular organization and flux control of lipid metabolism

Plant lipids represent a fascinating field of scientific study, in part due to a stark dichotomy in the limited fatty acid (FA) composition of cellular membrane lipids vs the huge diversity of FAs that can accumulate in triacylglycerols (TAGs), the main component of seed storage oils. With few exceptions, the strict chemical, structural, and biophysical roles imposed on membrane lipids since the dawn of life have constrained their FA composition to predominantly lengths of 16–18 carbons and containing 0–3 methylene-interrupted carbon-carbon double bonds in cis-configuration. However, over 450 “unusual” FA structures can be found in seed oils of different plants, and we are just beginning to understand the metabolic mechanisms required to produce and maintain this dichotomy. Here we review the current state of plant lipid research, specifically addressing the knowledge gaps in membrane and storage lipid synthesis from 3 angles: pathway fluxes including newly discovered TAG remodeling, key acyltransferase substrate selectivities, and the possible roles of “metabolons.”

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Complete replacement of Arabidopsis oil-producing enzymes with heterologous diacylglycerol acyltransferases

Acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1) and phospholipid:diacylglycerol acyltransferase 1 (PDAT1) share responsibility for triacylglycerol (TAG) biosynthesis, and their selectivities control TAG fatty acid (FA) compositions. For rational metabolic engineering of seed oils, replacing endogenous TAG biosynthesis with exogenous enzymes containing different substrate FA selectivities is desirable; however, the dgat1-1/pdat1-2 double mutant is pollen lethal. Here, we evaluated the ability of 3 DGAT1s, from phylogenetically diverse plants with distinct TAG assembly processes, to completely replace endogenous TAG biosynthesis in Arabidopsis ( Arabidopsis thaliana ). We transformed dgat1-1 mutant plants with expression constructs for DGAT1 s from Camelina sativa , Physaria fendleri , and castor ( Ricinus communis ). Transgene expression was properly “contextualized” by using a previously determined minimum necessary expression unit containing the promoter/5′ UTR and first intron of native AtDGAT1 ; both of these DNA elements are essential for pollen expression. Next, we crossed homozygous lines with a DGAT1/DGAT1/PDAT1/pdat1-2 parent. C. sativa and P. fendleri DGAT1s restored the FA compositions and transcriptional differences of dgat1-1 to near wild-type and rescued the dgat1-1/pdat1-2 pollen lethality. R. communis DGAT1 was active in dgat1-1 seeds but produced unique oil profiles and alterations in the expression of lipid metabolic genes; it also failed to rescue dgat1-1/pdat1-2 lethality. This study confirms that the promoter and first intron of AtDGAT1 can modulate the expression of foreign DGAT1 genes to fit the correct spatiotemporal profile necessary for completely replacing endogenous TAG biosynthesis. Furthermore, it demonstrates an additional layer of unexpected enzyme incompatibility between oilseed lineages, which may complicate bioengineering approaches that seek to replace essential genes with orthologs.

McGuire, Sean T. [Washington State Univ., Pullman,↗
DOE OSTI2025

PII interactions with the acetyl-CoA carboxylase subunits BADC and BCCP co-regulate lipid and nitrogen metabolism in Arabidopsis

In plants, the initiation of fatty acid synthesis is catalyzed by acetyl-CoA carboxylase (ACCase), which produces malonyl-CoA. The heteromeric form of ACCase (htACCase) is a holoenzyme consisting of biotin carboxylase and carboxyltransferase sub-complexes, both of which are subject to extensive regulation. Biotin carboxylase activity is controlled in part by the presence of the catalytic biotin carboxyl carrier proteins (BCCP1/2) and/or the non-catalytic, non-biotinylated, biotin/lipoyl attachment domain-containing proteins (BADC1/2/3) that associate with backbone biotin carboxylase (BC) protein. However, the mechanisms regulating BADC and BCCP interactions with BC and, consequently, ACCase activity in planta , remain unclear. Here, we demonstrate that the Arabidopsis ( Arabidopsis thaliana ) regulatory protein PII modulates htACCase activity through independent interactions with BADC and BCCP proteins in a selective manner. Analysis of badc1 badc2 and badc1 badc3 mutant lines and the respective pii triple mutants revealed that changes in seed oil and protein accumulation of badc double mutants are PII/nitrogen dependent. Absolute quantification of htACCase subunits and PII in developing seeds suggests that Arabidopsis exerts tight regulation over individual protein stoichiometry to balance oil and protein accumulation. The effects on vegetative and seed development indicate that PII and BADC proteins have distinct yet overlapping roles in regulating plant metabolism.

Garneau, Matthew G. [Washington State Univ., Pullm↗
DOE OSTI2025

Bats flying through a Y-maze are visually attracted to wind turbine surfaces

Wind energy’s rapid expansion has led to unintended consequences for wildlife, with migratory bats among the species most at risk. The behavioural mechanisms underlying collisions remain poorly understood, but one hypothesis is that bats are attracted to wind turbine structures. Vision is important to bat orientation and obstacle avoidance, yet it has been relatively understudied in the context of bat–turbine interactions. We hypothesize that light reflected off turbine surfaces could attract bats, acting as a sensory pollutant that may increase collision risk. To test whether reflective turbine surfaces elicit attraction, we flew 242 Lasiurus cinereus and 154 Lasionycteris noctivagans through Y-maze assays. Bats were at least twice as likely to fly towards white turbine blade sections compared to less reflective black ones. This attraction intensified when the alternative exit was a dark, empty flyway, with 74% of L. cinereus and 97% of L. noctivagans flying towards the white turbine blade. These findings provide evidence that visual sensory pollutants could underlie bat–turbine interactions, and if so, wind turbines could be ecological traps.

17 WIND ENERGY↗
DOE OSTI2024

Forecast of Wildfire Potential Across California USA Using a Transformer

Wildfires are a major issue facing the United States, a matter further exacerbated by an ever-changing climate. In California alone, wildfires are responsible for billions of dollars in damages and take lives each year. Accurately predicting fire danger conditions allows preparation awareness before wildfires start. Transformers are a class of deep learning models designed to identify patterns in sequential datasets. In recent years, transformers have gained popularity through their impressive performance in natural language processing and other applications of signal recognition. This analysis demonstrates the ability of a transformer with a residual connection to forecast fire danger potential over the state of California. Wildland fire potential index (WFPI) maps collected from the US Geological Survey database from January 1st 2020 to December 31st 2023 were used to tune, train and evaluate the transformer. Meteorological inputs (provided by Daymet daily weather and climatological summaries), the normalized difference vegetation index (NDVI) (calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS)), and outputs from the Scott and Burgman fire behavior fuel models (to characterize maps of fuel types), were used as inputs. Our results show that a transformer can effectively emulate the US Forest Service modeled WFPI maps of California USA for four week long forecasts over the month of July, 2023, with correlations ranging from 0.85 – 0.98.

Limber, Russell [ORNL]↗
DOE OSTI2025

Ecological acclimation: A framework to integrate fast and slow responses to climate change

Ecological responses to climate change occur across vastly different time-scales, from minutes for physiological plasticity to decades or centuries for community turnover and evolutionary adaptation. Accurately predicting the range of ecosystem trajectories will require models that incorporate both fast processes that may keep pace with climate change and slower ones likely to lag behind and generate disequilibrium dynamics. However, the knowledge necessary for this integration is currently fragmented across disciplines. We develop ‘ecological acclimation’ as a unifying framework to emphasize the similarity of dynamics driven by processes operating on dramatically different time-scales and levels of biological organization. The framework focuses on ecoclimate sensitivities, measured as the change in an ecological response variable per unit of climate change. Acclimation processes acting at different time-scales cause these sensitivities to shift in magnitude and even direction over time. We highlight shifting ecoclimate sensitivities in case studies from diverse ecosystems, including terrestrial plant communities, coral reefs and soil microbiomes. Models predicting future ecosystem states inevitably make assumptions about acclimation processes; these assumptions must be explicit for users to evaluate whether a model is appropriate for a given forecast horizon. Similarly, decision frameworks that clearly account for multiple acclimation processes and their distinct time-scales will help natural resource managers plan for ecological impacts of climate change from years to many decades into the future. We outline a synthetic research programme focused on the time-scales of ecological acclimation to reduce uncertainty in ecological forecasts.

climate adaptation↗
DOE OSTI2025

Seeing the forest for all the trees: Mycorrhizal‐associated nutrient economies are modulated by stem density and the synchrony between overstorey and understorey communities

1. Identifying relationships between plant communities and soil characteristics is a critical step in understanding the consequences of species gains and losses in ecosystems. The mycorrhizal associated nutrient economy (MANE) hypothesis predicts that the degree to which tree species and their mycorrhizal associates affect soil properties is driven by the relative dominance of different mycorrhizal types (often measured by relative basal area). While this approach emphasizes the importance of canopy trees, it does not account for how other factors (e.g. the density and composition of understorey trees) may alter tree–soil relationships. 2. We analysed tree–soil data from an eastern deciduous forest in southern Indiana, USA that contains >29,000 georeferenced stems, including 21 species that associate with arbuscular mycorrhizal (AM) fungi and 14 that associate with ectomycorrhizal (ECM) fungi. We sampled soils (upper 5 cm) from across the plot and modelled soil characteristics to tree communities. Given differences in soil characteristics among AM-dominated and ECM-dominated neighbourhoods, we hypothesized that relationships between tree-mycorrhizal dominance and soils would be affected by both the density of stems in the plot (owing to ‘Zinke’ individual plant effects) and composition of the understorey trees (owing to ‘trait divergence effects’) 3. In support of our Zinke hypothesis, we found that the relationships between tree-mycorrhizal dominance and soil variables (soil pH, nitrification rates and carbon to nitrogen ratio) were strengthened as stand density increased. In support of the trait divergence hypothesis, we found that as the mismatch between overstorey and understorey composition increased (e.g. AM-dominated understories beneath ECM-dominated overstories and vice versa), the relationship between tree dominance and soil variables weakened. We were able to use these insights to create mycorrhizal metrics to predict soil variables that were sensitive to the structural composition of neighbourhoods. 4. Synthesis. Our results indicate that relationships between plants and soils in forests are not only shaped by dominant overstorey trees but also the density and composition of understorey trees. Thus, efforts to predict the ecosystem consequences of species gains and losses may benefit from considering these elements of forest structure and not only the basal area of the dominant trees.

MANE framework↗
DOE OSTI2026

Linking Community‐Climate Disequilibrium to Ecosystem Function

Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community‐climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, in this work, we develop a simple theoretical model to address both of these problems by linking community‐climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near‐term even when climate change is expected to enhance functioning in the long‐term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre‐existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community‐climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community‐climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.

climate change↗
DOE OSTI2026

Eddy Covariance Theory: A Review

Eddy covariance (EC), the gold standard for measuring ecosystem scale gas and heat exchanges, has transformed our understanding of the breathing of the biosphere, and thus global change biology. Despite numerous methodological improvements and insights gained from the technique, the community faces persistent challenges that have been present since the first EC measurements. Here, we review the theoretical developments underpinning EC. We present theoretical developments in four important areas that have relevance to EC measurements of the net ecosystem exchanges (NEE) of gases and heat from a single tower: (i) measuring the total vertical flux density, (ii) flux attenuation, (iii) coordinate rotations, and (iv) energy balance closure. Persistent problems with EC measurements, such as the inability to close the energy budget, led us to identify two priorities for revisiting the theory underlying: (i) sensible heat flux calculations, and (ii) constraining the mean vertical wind velocity. We present a framework for improved calculation of sensible heat flux derived from first principles of fluid mechanics and thermodynamics that considers coupled heat and mass transfer so that conservation of both is obeyed. These refinements are motivated by the need for unbiased measurements of energy and mass transfer between the land surface and atmosphere for ecosystem research and to validate satellite observations and land surface models.

ecosystem fluxes↗
DOE OSTI2025

A 13‐Year Record Indicates Differences in the Duration and Depth of Soil Carbon Accrual Among Potential Bioenergy Crops

Six years after replacing a maize/soybean cropping system, perennial grasses miscanthus (Miscanthus × giganteus) and switchgrass (Panicum virgatum), and a 28-species restored prairie increased particulate organic carbon in surface soils without increasing soil organic carbon (SOC). To resolve potential changes in the quantity and distribution of SOC, soils were resampled after seven to thirteen years to measure bulk density, carbon (C) content, and stable C isotopes to a depth of 1 m. SOC stocks increased between 1.75 and 2.5 Mg ha −1 year −1 in all perennial crops between 2008 and 2016 (nine growing seasons). Despite relatively low litter inputs and belowground biomass, the highest rate of SOC accrual was in restored prairie (2.5 Mg ha −1 year −1 ), followed by miscanthus (2.0 Mg ha −1 year −1 ) and switchgrass (1.75 Mg ha −1 year −1 ). The change in SOC in maize/soybean was not significant. After 2016, total SOC decreased in maize/soybean and miscanthus, resulting in slower overall rates of SOC accumulation over the full sampling period for miscanthus (0.8 Mg ha −1 year −1 ). The rate of SOC accumulation was greatest below 50 cm depth for restored prairie and switchgrass but in the top 10 cm for miscanthus. Stable isotope analysis showed 13 C enrichment in all depths of switchgrass soils, an indication of new organic C accumulation, but mixed results in all other crops. Planting perennial crops on land formerly in an annual maize/soybean cropping system can slow or reverse soil carbon losses, with the greatest increases in SOC from species-rich prairie.

agriculture↗
DOE OSTI2025

Integrated Modeling Driven Evaluation of Opportunities for Climate‐Resilient Perennial Biomass Crop Plantings in Flood‐Prone Agricultural Landscapes

Adapting to future climate change in flood-prone landscapes will require climate-resilient agricultural systems. Planting perennial crops, like switchgrass and willow, along river corridors can mitigate future flooding while supporting bioenergy markets. We developed an integrated assessment linking climate, hydrologic, and inundation model results to assess future flood risk to river-adjacent agricultural lands in the Mid-Atlantic Region (MAR) and explore this opportunity. We produced ensemble streamflow projections for every MAR stream using a hydrologic model driven by a suite of downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 climate projections. We then conducted high-resolution inundation mapping based on projected flood frequencies for baseline and future periods. Results show that in the near-term future, at least two-thirds of the streams will experience 100-year floods more severe than the baseline 200-year floods. Riparian zones are projected to face a median rise of inundation by 9.5%–24.1%. Results show that there is an opportunity to mitigate flooding in over half of MAR's counties with the quantities of switchgrass and willow plantings anticipated for mature bioenergy markets, even under the most extreme (200-year) flood events. Our integrated modeling framework can guide similar regions to evaluate opportunities for flood-resilient agricultural systems under climate change.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Regulation of Transpiration and Whole‐Tree Crown Conductance in Tropical Forests

We found a consistent, emergent relationship between tropical tree crown conductance and its sensitivity to vapour pressure deficit across diverse species and sites. This reveals convergent stomatal–hydraulic regulation alongside distinct drought sensitivities among plant functional types.

Rahman, Mizanur [Pacific Northwest National Labora↗
DOE OSTI2025

Land change, fire, and climate weaken carbon sink in the conterminous United States

The land carbon sink of the conterminous United States was evaluated using a bottom-up modeling framework and 30-meter land change data from 1985 to 2020. This cross-scale, cross-landscape, and cross-system approach tracked fractional land cover changes and applied regional model calibration. Results show average terrestrial and aquatic carbon sinks of +110 ± 37 and +19 ± 0.5 teragrams of carbon per year, respectively. The terrestrial carbon sink, showing no clear trend, peaked in the 1990s, with more years as a carbon source since 2000, contradicting recent national and global studies. Land change had the largest impact (−70 ± 5.5 teragrams of carbon per year), exceeding impacts of climate (−33 ± 48 teragrams of carbon per year), wildfire (−7.7 ± 2.4 teragrams of carbon per year), and erosion transport (−1.9 ± 0.13 teragrams of carbon per year). The positive CO 2 fertilization effect (+69 ± 12 teragrams of carbon per year) was insufficient to maintain the carbon sink strength. Our framework reveals key paths of carbon loss, with implications for carbon budget and energy policies in the United States and beyond.

Liu, Jinxun [US Geological Survey, Reston, VA (Uni↗