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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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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Drought–induced increase in tree mortality and corresponding decrease in the carbon sink capacity of Canada's boreal forests from 1970 to 2020

Canada's boreal forests, which occupy approximately 30% of boreal forests world wide, play an important role in the global carbon budget. However, there is lit tle quantitative information available regarding the spatiotemporal changes in the drought-induced tree mortality of Canada's boreal forests overall and their associ ated impacts on biomass carbon dynamics. Here, we develop spatiotemporally ex plicit estimates of drought-induced tree mortality and corresponding biomass carbon sink capacity changes in Canada's boreal forests from 1970 to 2020. We show that the average annual tree mortality rate is approximately 2.7%. Approximately 43% of Canada's boreal forests have experienced significantly increasing tree mortality trends (71% of which are located in the western region of the country), and these trends have accelerated since 2002. This increase in tree mortality has resulted in sig nificant biomass carbon losses at an approximate rate of 1.51±0.29 MgC ha -1 year -1 (95% confidence interval) with an approximate total loss of 0.46±0.09 PgC year -1 (95% confidence interval). Under the drought condition increases predicted for this century, the capacity of Canada's boreal forests to act as a carbon sink will be further reduced, potentially leading to a significant positive climate feedback effect

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Poplar PtabZIP1-like enhances lateral root formation and biomass growth under drought stress

Developing drought-resistance varieties is a major goal for bioenergy crops, such as poplar (Populus), which will be grown on marginal lands with little or no water input. Root architecture can affect drought resistance, but few genes that affect root architecture in relation to water availability have been identified. Here in this study, using activation tagging in the prime bioenergy crop poplar, we have identified a mutant that overcomes the block of lateral root (LR) formation under osmotic stress. Positioning of the tag, validation of the activation and recapitulation showed that the phenotype is caused by the poplar PtabZIP1-like (PtabZIP1L) gene with highest homology to bZIP1 from Arabidopsis. PtabZIP1L is predominantly expressed in roots, particularly in zones where lateral root primordia (LRP) initiate and LR differentiate and emerge. Transgenics overexpressing PtabZIP1L showed precocious LRP and LR development, while PtabZIP1L suppression significantly delayed both LRP and LR formation. Transgenic overexpression and suppression of PtabZIP1L also resulted in modulation of key metabolites like proline, asparagine, valine and several flavonoids. Consistently, expression of both of the poplar Proline Dehydrogenase orthologs and two of the Flavonol Synthases genes was also increased and decreased in overexpressed and suppressed transgenics, respectively. These findings suggest that PtabZIP1L mediates LR development and drought resistance through modulation of multiple metabolic pathways.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Processed sap flow and fine-root trait data associated with summer drought responses in temperate trees in Lisle, Illinois, USA (2019–2021)

These data support the manuscript “Acquisitive root exploration strategies help maintain higher peak sap flux rates during summer drought, but more root biomass does not”. The dataset includes processed sap flow measurements and fine-root trait data collected between 2019 and 2021 from temperate monodominant tree plots established in the 1920s to 1930s ranging in size from 0.05 to 0.8 ha at The Morton Arboretum in Lisle, IL. Sap flow was measured with ICT sap flow sensors using the heat ratio method. Fine-root traits were measured from soil cores which includes specific root length (SRL), specific root area (SRA), diameter, biomass, and length for diameter classes ≤1 mm and ≤2 mm. The package contains comma separated value (CSV) data files and associated metadata that can be viewed and analyzed using common software such as spreadsheet programs, R, and Python. These data are used to investigate how variation in fine-root traits relate to tree water use and drought response during summer drought linking belowground root traits and aboveground physiological responses.

drought↗
DOE OSTI2025

Flash Drought indicators at catchment scale for CONUS

Flash droughts are defined by the rapid onset and intensification of drought conditions - a feature common across various proposed indicators. However, the absence of a standardized definition and detection method makes them particularly difficult to anticipate and manage. This dataset includes flash drought classifications based on six different methods across 222 catchments (4-digit Hydrologic Units, HUC4) in the Contiguous United States (CONUS) from 1983 to 2023. It also includes the pairwise agreement between indicators and the event-level multi-indicator agreement. For a detailed description of each file, refer to README_MSDlive.pdf

Catchment scale↗
DOE OSTI2026

Sensitivity Analysis of Drivers Water Shortage in the Los Angeles Region During Drought

The code and detailed step-by-step instructions for generating the model output data, processing results, and analysis and plotting are provided at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. The PyArtes model is a python adaptation of the Artes model. PyArtes uses many of the same input data and optimization model architecture as Artes. Documentation for the PyArtes model is provided in the Supplement to the paper. The primary data product are simulated monthly water shortages for indoor and outdoor demand under a large ensemble of drought scenarios (>13,000). The droughts are hypothetical and are not based on historical time series data of supply sources - though historical data did help inform ranges explored for supply parameters. Demands are informed by recent 2017-2021 water supply data. Demands used for the model can be accessed at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. Simulations resolve demand for over 90 water providers in the study region. The results report 36 months of water shortage data for each indoor and outdoor demand node. The study also developed a multilayer perceptron (MLP) neural network trained on a subset of the simulated shortage ensemble to emulate worst annual water shortage for a given set of parameter multipliers -- provided the parameter values fall within the ranges sampled in the ensemble. Emulated water shortages for synthetic ensembles are in the MLP-generated shortages folder. The MLP model was used to generate larger ensembles to support Sobol analysis that would have been extremely computationally expensive to simulate. Datasets provided in this repository*: Simulated shortages. These results are used for the analysis for Figures 5, 8, and 9 in the paper, and also to train the MLP emulator. .zip file containing outputs for the 13,312 scenario ensemble. Separate .csv files for indoor and outdoor shortage for each scenario. Rows = demand ids (~100), Columns = months (36) Units = acre-feet/month of shortage (shortage = monthly demand - supply). 1 acft = 1233.48 m^3 .csv files of aggregated shortages derived from the 13,312 ensemble Rows = scenarios (13,312), Columns = demand ids (~100) Units = acre-feet/year (either worst annual shortage or total shortage over the 3-year drought) .csv file of the parameter multipliers scenarios for the ensemble .csv file of the parameter ranges and baseline values the multipliers were applied to MLP-generated shortages. These results are used for Figures 4, 6, and 7 in the paper. mwd higher folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results Emulated shortages. Rows = scenarios, columns = demand ids, units acft Sobol results. Rows = demand ids, columns Sobol (S1, ST, or 95% confidence interval) value for each parameter mwd lower folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results same organization as mwd higher MLP performance: performance metrics (R^2, RMSE, BIAS, MAPE) for the testing subset (20% or 2,662 scenarios) and simulated vs emulated worst year shortage (acre-feet/year) for every demand node, MWD wholesale regions, and the entire study region (LAC). Supporting data for figures. Figure plotting scripts in the associated GitHub repo. These files support analysis and visualization. Geospatial Data used for plotting simulated water shortages and Sobol results. Dictionary of full names for demand nodes in the model and estimates of water supply by source type informed by Artes input files and California Urban Water Management Planning data: https://water.ca.gov/Programs/Water-Use-And-Efficiency/Urban-Water-Use-Efficiency/Urban-Water-Management-Plans *Readme files provided for each folder.

drought↗
NASA NTRS2015

The 2010 Russian Drought Impact on Satellite Measurements of Solar-Induced Chlorophyll Fluorescence: Insights from Modeling and Comparisons with the Normalized Differential Vegetation Index (NDVI)

We examine satellite-based measurements of chlorophyll solar-induced fluorescence (SIF) over the region impacted by the Russian drought and heat wave of 2010. Like the popular Normalized Difference Vegetation Index (NDVI) that has been used for decades to measure photosynthetic capacity, SIF measurements are sensitive to the fraction of absorbed photosynthetically-active radiation (fPAR). However, in addition, SIF is sensitive to the fluorescence yield that is related to the photosynthetic yield. Both SIF and NDVI from satellite data show drought-related declines early in the growing season in 2010 as compared to other years between 2007 and 2013 for areas dominated by crops and grasslands. This suggests an early manifestation of the dry conditions on fPAR. We also simulated SIF using a global land surface model driven by observation-based meteorological fields. The model provides a reasonable simulation of the drought and heat impacts on SIF in terms of the timing and spatial extents of anomalies, but there are some differences between modeled and observed SIF. The model may potentially be improved through data assimilation or parameter estimation using satellite observations of SIF (as well as NDVI). The model simulations also offer the opportunity to examine separately the different components of the SIF signal and relationships with Gross Primary Productivity (GPP).

vegetation↗
NASA NTRS2015

Variability and Predictability of West African Droughts. A Review in the Role of Sea Surface Temperature Anomalies

The Sahel experienced a severe drought during the 1970s and 1980s after wet periods in the 1950s and 1960s. Although rainfall partially recovered since the 1990s, the drought had devastating impacts on society. Most studies agree that this dry period resulted primarily from remote effects of sea surface temperature (SST) anomalies amplified by local land surface-atmosphere interactions. This paper reviews advances made during the last decade to better understand the impact of global SST variability on West African rainfall at interannual to decadal time scales. At interannual time scales, a warming of the equatorial Atlantic and Pacific/Indian Oceans results in rainfall reduction over the Sahel, and positive SST anomalies over the Mediterranean Sea tend to be associated with increased rainfall. At decadal time scales, warming over the tropics leads to drought over the Sahel, whereas warming over the North Atlantic promotes increased rainfall. Prediction systems have evolved from seasonal to decadal forecasting. The agreement among future projections has improved from CMIP3 to CMIP5, with a general tendency for slightly wetter conditions over the central part of the Sahel, drier conditions over the western part, and a delay in the monsoon onset. The role of the Indian Ocean, the stationarity of teleconnections, the determination of the leader ocean basin in driving decadal variability, the anthropogenic role, the reduction of the model rainfall spread, and the improvement of some model components are among the most important remaining questions that continue to be the focus of current international projects.

West Africa↗
NASA NTRSDate not supplied

Developing a Customized Composite Drought Index for Pakistan

This study aims to identify historical agricultural droughts between 2004-2019 using 10 geophysical variables (Table 1) and determine what variables have little importance in this identification. Satellite data products or model outputs are used for all input variables. Understanding the interactions between the data will provide information on temporal and spatial patterns of how drought is presented in irrigated and rainfed areas (Fig. 2). This knowledge will assist in creating a Customized Composite Drought Index in future work

Drought↗
NASA NTRS2020

Subseasonal-to-Seasonal Hindcast Skill Assessment of Ridging Events Related to Drought Over the Western United States

Persistent atmospheric ridging events centered near the western United States are associated with widespread precipitation deficits and meteorological drought. Due to the relatively low skill of- dynamical models in forecasting precipitation on subseasonal‐to‐seasonal (S2S) time scales across this region, forecasts of ridging are explored in this study as a potential bridge for early warning drought prediction. To assess skill, we evaluate deterministic and probabilistic S2S hindcasts (out to 6 week lead time) of ridging events and geopotential height anomalies over the western United States in five ensemble hindcast systems. Prediction skill for ridging events is shown to be highly variable across models. For some models, longer‐time‐averaged patterns of geopotential height anomalies across the first 6 weeks can be skillfully simulated, when evaluated probabilistically against climatology. The most skillful models show modest skill in forecasting above normal ridging occurrences at lead times of Weeks 3–4 and Weeks 5–6,with some sensitivity to the specific ridge location and method for determining skill. Using the European Centre for Medium‐Range Weather Forecasts (ECMWF) model as a case study, longer lead time forecast busts are shown to often occur under extended periods of highly active La Nina‐like tropical convection. Model errors at simulating these tropical convection features may have a disproportionately large impact and degrade downstream forecasts over the western United States. Despite the documented model shortcomings, our results highlight an opportunity to target skillful ridging forecasts from dynamical models for improving early warning drought forecasting at S2S lead times.

S2S↗
NASA NTRS2022

Desert Locust Cropland Damage Differentiated from Drought, with Multi-Source Remote Sensing in Ethiopia

In 2020, Ethiopia had the worst desert locust outbreak in 25 years, leading to food insecurity. Locust research has typically focused on predicting the paths and breeding grounds based on ground surveys and remote sensing of outbreak factors. In this study, we hypothesized that it is possible to detect desert locust cropland damage through the analysis of fine-scale (5–10 m) resolution satellite remote sensing datasets. We performed our analysis on 121 swarm point locations on croplands derived from the Food and Agriculture Organization (FAO) of the United Nations, and 94 ‘non-affected’ random cropland sample points generated for this study that are distributed within 20–25 km from the ‘center’ of swarm affected sample locations. Integrated Drought Condition Indices (IDCIs) and Vegetation Health Indices (VHIs) calculated for the affected sample locations for 2000–2020 were strongly correlated (R(exp 2) > 0.90) with that of the corresponding non-affected group of sample sites. Drought indices were strongly correlated with the evaluation Standardized Precipitation Evapotranspiration Indices (SPEIs) and showed that 2020 was the wettest year since 2000. In 2020, the NDVI and backscatter coefficient of cropland phenologies from the affected versus non-affected cropland sample sites showed a slightly wider, but significant gap in March (short growing season) and August-October (long growing season). Thus, slightly wider gaps in cropland phenologies between the affected and non-affected sites were likely induced from the locust damage, not drought, with fine scale data representing a larger gap.

Desert locust↗
NASA NTRS2024

Increasing Prevalence of Hot Drought Across Western North America Since the 16th Century

Across western North America (WNA), 20th-21st century anthropogenic warming has increased the prevalence and severity of concurrent drought and heat events, also termed hot droughts. However, the lack of independent spatial reconstructions of both soil moisture and temperature limits the potential to identify these events in the past and to place them in a long-term context. We develop the Western North American Temperature Atlas (WNATA), a data-independent 0.5° gridded reconstruction of summer maximum temperatures back to the 16th century. Our evaluation of the WNATA with existing hydroclimate reconstructions reveals an increasing association between maximum temperature and drought severity in recent decades, relative to the past five centuries. The synthesis of these paleo-reconstructions indicates that the amplification of the modern WNA megadrought by increased temperatures and the frequency and spatial extent of compound hot and dry conditions in the 21st century are likely unprecedented since at least the 16th century.

Drought↗
DOE OSTI2021

Hydraulically‐vulnerable trees survive on deep‐water access during droughts in a tropical forest

Summary Deep‐water access is arguably the most effective, but under‐studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep‐water access may delay plant dehydration. Here, we tested the role of deep‐water access in enabling survival within a diverse tropical forest community in Panama using a novel data‐model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990–2015) to vapor pressure deficit, water potentials in the whole‐soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water‐access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35 years (1981–2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress‐related mortality risk through deep‐water access. The role of deep‐water access in mitigating mortality of hydraulically‐vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A high-resolution record of Late Holocene drought in the eastern Sierra Nevada (California, USA) from June Lake carbonate geochemistry

As historic drought conditions become more common in western North America, Late Quaternary hydroclimate records become vital for putting present anthropogenic conditions into a longer-term context. Here, we establish a high-resolution record of drought for the eastern Sierra Nevada (California) using lacustrine carbonates from well-dated sediment cores. We used oxygen and carbon stable-isotope ratios, combined with high-resolution scanning X-ray fluorescence counts of calcium (Ca) and titanium (Ti), to reconstruct the drought record over the last 4600 years in June Lake. We found elevated δ 18 O and δ 13 C carbonate isotope values coinciding with peaks in both total inorganic carbon and Ca/Ti, suggesting enhanced carbonate precipitation in response to evaporative concentration of lake water. At least six intervals of prolonged (centennial-scale) carbonate deposition were identified, including three pulses during the Late Holocene Dry Period (LHDP; ~3500–2000 cal yr BP), the Medieval Climate Anomaly (~1200–800 cal yr BP), and the Current Warm Period, which began around 100 cal yr BP. This record highlights the complexities of the LHDP, an interval that was more variable at June Lake than has been previously described in regional records.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Prolonged Drought in a Northern California Coastal Region Suppresses Wildfire Impacts on Hydrology

Wildfires naturally occur in many landscapes, however they are undergoing rapid regime shifts. Despite the emphasis in the literature on the most severe hydrological responses to wildfire, there remains a knowledge gap on the thresholds of wildfire (i.e., burned area/drainage area ratio, BAR) required to initiate hydrological responses. We investigated hydrological changes in the Russian River Watershed (RRW) in California, a coastal, Mediterranean, drought-prone, wildfire-adapted ecosystem, following ten wildfires that burned 30% of the watershed. Our findings suggest that sub-watersheds of the RRW have not burned beyond an intrinsic, unknown, threshold required to initiate change. Using paired watersheds, we examined spatiotemporal patterns of pre-and-post wildfire hydrology with a rainfall-runoff hydrological model. Even though these successive wildfires burned 1%–50% of each sub-watershed (1%–30% at moderate/high severity), we found little evidence of wildfire-related shifts in hydrology. As a function of BAR, wildfire imposed limited effects on runoff ratios (runoff/precipitation) and runoff residuals (observations—model simulations). Our findings that post-wildfire runoff enhancements asymptote beyond 30% burn indicate that when a watershed is burned beyond a certain threshold, the magnitude of the hydrologic response no longer increases. Drought and storm conditions explained much of the variability observed in streamflow, whereas wildfire explained only moderate variability in streamflow even when wildfire accounted for >45% BAR. While the BAR in the RRW was sufficiently beyond previously reported minimum disturbance thresholds (>20% burned forest), the lack of hydrological response is attributed to buffering effects of wildfire adaptation and drought factors that are unique to Mediterranean ecoregions.

Newcomer, Michelle E.↗
DOE OSTI2024

Systematic Underestimation of Canopy Conductance Sensitivity to Drought by Earth System Models

The response of vegetation canopy conductance (g c ) to changes in moisture availability ($γ^{m}_{gc}$) is a major source of uncertainty in climate projections. While vegetation typically reduces stomatal conductance during drought, accurately modeling how and to what degree stomata respond to changes in moisture availability at global scales is particularly challenging, because no global scale g c observations exist. Here, we leverage a collection of satellite, reanalysis and station-based near-surface air and surface temperature estimates, which are physically and statistically linked to $γ^{m}_{gc}$ due to the local cooling effect of g c through transpiration, to develop a novel emergent constraint of $γ^{m}_{gc}$ in an ensemble of Earth System Models (ESMs). We find that ESMs systematically underestimate $γ^{m}_{gc}$ by ~33%, particularly in grasslands, croplands, and savannas in semi-arid and bordering regions of the Central United States, Central Europe, Southeastern South America, Southern Africa, Eastern Australia, and parts of East Asia. We show that this underestimation occurs because ESMs inadequately reduce g c when soil moisture decreases. As g c controls carbon, water and energy fluxes, the misrepresentation of modeled $γ^{m}_{gc}$ contributes to biases in ESM projections of gross primary production, transpiration, and temperature during droughts. Our results suggest that the severity and duration of droughts may be misrepresented in ESMs due to the impact of sustained g c on both soil moisture dynamics and the biosphere-atmosphere feedbacks that affect local temperatures and regional weather patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Can Large‐Scale Satellite Products Track the Effects of Atmospheric Dryness and Soil Water Deficit on Ecosystem Productivity Under Droughts?

Drought stress, characterized by increased vapor pressure deficit (VPD) and soil water content (SWC) deficit, significantly impacts ecosystem productivity (GPP). Accurately assessing these factors in satellite remote sensing (RS) GPP products is crucial for understanding the large-scale ecological consequences of drought. However, the accuracy of RS GPP in capturing the effects of VPD and SWC deficit, compared to EC flux data, remains under-investigated. Here we evaluated 10 RS GPP products and their mean (RSmean) concerning VPD and SWC deficit across diverse ecosystems along a dryness gradient. Our results revealed that RSmean and individual products generally capture the GPP response direction (VPD: mainly negative, SWC deficit: mixed positive/negative) but consistently misestimate the absolute GPP changes. This discrepancy is ecosystem-specific and consistent across all RS products, underscoring the need to enhance RS products to better account for ecosystem-specific VPD effects and non-linear SWC deficit responses, thereby improving RS GPP accuracy under drought.

Wang, Xiaorong [Univ. of Hong Kong, Pokfulam (Hong↗
DOE OSTI2025

Photosynthetic responses to light levels in drought-tolerant novel peanut (Arachis hypogaea L) genotypes

Abstract Drought is a significant abiotic stressor that reduces peanut production because it alters photosynthetic activity and impacts crop growth. Therefore, developing drought-tolerant peanut genotypes capable of maintaining higher photosynthetic rates (A) under stress is crucial. This study assessed changes in photosynthetic and chlorophyll fluorescence responses to light (photosynthetic photon flux density, PPFD) in newly bred drought-tolerant peanut genotypes. Ten genotypes [NM-3, NM-5, NM-6, NM-23, NM-69, NM-70, NM-74, NM-77, V-C, and C-76–16] were evaluated under full irrigation (FC 100 ) and deficit irrigation (FC 50 ) in a split-plot design with four replications in a greenhouse. Under high PPFD levels, genotype NM-5 with deficit irrigation exhibited significantly higherA, stomatal conductance (gs), quantum efficiency of photosystem II (ΦPSII), and electron transport rate (ETR) by 40–59%, 135–525%, 31–212%, and 31–102%, respectively, than check varieties (V-C and C-76–16) and other genotypes. The NM-74 and NM-77 genotypes also performed well under deficit irrigations but with slightly lowerA,gs, ΦPSII, and ETR. Genotypes NM-5, NM-23, NM-74, and NM-77 exhibited significantly higher quantum efficiency of photosystem II (Fv’/Fm’) and photochemical quenching (qP) with higher light intensities in the daily cycle under deficit irrigation. The decline in ETR at the same PPFD levels in NM-3, NM 69, NM-70, and C-76–16 indicated photoinhibition or saturation of the photosynthetic apparatus compared to other genotypes. Concurrently, FC 100 irrigation level minimizes photoinhibition, enhancingA,gs, ΦPSII, and ETR in the genotypes than FC 50 . Therefore, we conclude that NM-5, NM-74, and NM-77 genotypes can perform better under water deficit environments. As such, chlorophyll fluorescence parameters Fv’/Fm’ and qP can be considered for selective breeding to enhance photosynthetic efficiencies.

Science & Technology - Other Topics↗
DOE OSTI2022

Mechanisms of woody-plant mortality under rising drought, CO 2 and vapour pressure deficit

Drought-associated woody plant mortality may have increased over the past several decades, and is projected to increase in the future, impacting terrestrial climate forcing, biodiversity, and resource availability. The mechanisms underlying such mortality, however, are debated owing to interactions between multiple drivers and mechanisms. In this work, we synthesize knowledge of drought-related tree mortality under a warming and drying atmosphere with rising atmospheric CO 2 . Drought-associated mortality results from the depletion of pools of water and carbon within a plant and declines in their fluxes relative to demand by living tissues. These pools and fluxes are interdependent and underlay plant defenses against biotic agents. Death via failure to maintain a positive water balance is particularly dependent on soil-to-root conductance, capacitance, vulnerability to hydraulic failure, cuticular water losses, and dehydration tolerance, all of which could be exacerbated by reduced carbon supply rates to support cellular survival e.g. the carbon starvation process. The depletion of plant water and carbon pools accelerates under rising vapor pressure deficit; however, increasing CO 2 can mitigate these impacts. Advancing knowledge and reducing predictive uncertainties requires studies that integrate carbon, water, and defensive processes, and utilize a range of experimental and modeling approaches.

54 ENVIRONMENTAL SCIENCES↗