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Hydrological Drought in the Anthropocene: Impacts of Local Water Extraction and Reservoir Regulation in the U.S.

Hydrological drought is a substantial negative deviation from normal hydrologic conditions and is influenced by climate and human activities such as water management. By perturbing the streamflow regime, climate change and water management may significantly alter drought characteristics in the future. Here we utilize a high-resolution integrated modeling framework that represents water management in terms of both local surface water extraction and reservoir regulation, and use the Standardized Streamflow Index (SSI) to quantify hydrological drought. We explore the impacts of water management on hydrological drought over the contiguous US in a warming climate with and without emissions mitigation. Despite the uncertainty of climate change impacts, local surface water extraction consistently intensifies drought that dominates at the regional to national scale. However, reservoir regulation alleviates drought by enhancing summer flow downstream of reservoirs. The relative dominance of drought intensification or relief is largely determined by the water demand, with drought intensification dominating in regions with intense water demand such as the Great Plains and California, while drought relief dominates in regions with low water demand. Here, at the national level, water management increases the spatial extent of extreme drought despite some alleviations of moderate to severe drought. In an emissions mitigation scenario with increased irrigation demand for bioenergy production, water management intensifies drought more than the business-as-usual scenario at the national level, so the impacts of emissions mitigation must be evaluated by considering its benefit in reducing warming and evapotranspiration against its effects on increasing water demand and intensifying drought.

54 ENVIRONMENTAL SCIENCES↗

Impact of Vegetation Assimilation on Flash Drought Characteristics across the Continental United States

Predicting and managing the impacts of flash droughts is difficult owing to their rapid onset and intensification. Flash drought monitoring often relies on assessing changes in root-zone soil moisture. However, the lack of widespread soil moisture measurements means that flash drought assessments often use process-based model data like that from the North American Land Data Assimilation System (NLDAS). Such reliance opens flash drought assessment to model biases, particularly from vegetation processes. Here, we examine the influence of vegetation on NLDAS-simulated flash drought characteristics by comparing two experiments covering 1981–2017: open loop (OL), which uses NLDAS surface meteorological forcing to drive a land surface model using prognostic vegetation, and data assimilation (DA), which instead assimilates near-real-time satellite-derived leaf area index (LAI) into the land surface model. The OL simulation consistently underestimates LAI across the United States, causing relatively high soil moisture values. Both experiments produce similar geographic patterns of flash droughts, but OL produces shorter duration events and regional trends in flash drought occurrence that are sometimes opposite to those in DA. Across the Midwest and Southern United States, flash droughts are 4 weeks (about 70%) longer on average in DA than OL. Moreover, across much of the Great Plains, flash drought occurrence has trended upward according to the DA experiment, opposite to the trend in OL. This sensitivity of flash drought to the representation of vegetation suggests that representing plants with greater fidelity could aid in monitoring flash droughts and improve the prediction of flash drought transitions to more persistent and damaging long-term droughts.

Drought↗

A Holistic View of Water Management Impacts on Future Droughts: A Global Multimodel Analysis

Here, this study investigates the impacts of climate change and water management including agricultural irrigation, water withdrawal, and reservoir regulation on future meteorological, agricultural, and hydrological droughts and their connections. The analysis is based on the simulations from four global hydrological models forced with the projections from five global climate models for historical period 1971–2000 and future period 2070–2099 with and without water management. Three unified drought indices, the standardized precipitation index, standardized soil moisture index, and standardized streamflow index, are adopted to represent the meteorological, agricultural, and hydrological droughts, respectively. The analysis suggests that the climate-induced drought changes in all three types of droughts are enhanced but in different directions, while water-management-induced changes in agricultural and hydrological droughts are more consistent across space and simulations. Overall, water management activities reduce both the duration and intensity of agricultural droughts by roughly 1 order of magnitude, while increase those of hydrological droughts by up to 50%. Basin-scale analysis reveals that the higher is the intensity of irrigation, the larger will be the water-management-induced drought changes. Due to water management activities at some regions, the return periods of extreme agricultural droughts (in terms of severity) can change from 100 to 300 years or even longer, while typical 100-year hydrological droughts are likely to occur more often for the regions located in 25°N–40°N and 15°S–50°S. Lastly, this study provides a global view on drought modification in the Anthropocene, which will help improve adaptation strategies for future droughts.

54 ENVIRONMENTAL SCIENCES↗

Season of drought affects growth, but not nonstructural carbohydrates dynamics, in Pinus taeda saplings

In temperate evergreen conifers, growth occurs mostly in summer but photosynthesis proceeds year-round; thus, nonstructural carbohydrates (NSCs) increase in winter but decrease in summer. Given that mild drought reduces growth but not photosynthesis, a drought in summer should increase NSCs more than one in winter. However, the active regulation hypothesis suggests that to increase future drought resilience, plants might downregulate growth to increase NSCs after a winter drought even if NSCs do not increase during the drought. To test whether this is so, potted Pinus taeda saplings (age year) were subjected to 6-month droughts in a greenhouse with one treatment receiving drought during winter (September–March), and another during summer (March–September). Here, both treatments were compared with a control. To measure dry biomass and NSCs, we harvested plants monthly following each drought, while to assess changes in growth rates, we measured height and diameter monthly. While we observed seasonal variation and an overall increase during the study, we found no drought-related changes in NSC dynamics; however, drought did reduce growth. Furthermore, drought in winter did reduce growth during the following summer, but the reduction was less than for a drought in summer. We conclude that the effect of drought on NSCs was too small to detect in our plants. While better control of soil water would have reduced a major source of uncertainty, plants with larger NSC reserves or more intense stress would also yield easier-to-detect effects. Although not definitive, our results suggest that water stress does not lead to dramatic changes in seasonal NSC dynamics in its aftermath, despite what one might expect under the active regulation hypothesis.

59 BASIC BIOLOGICAL SCIENCES↗

Multi‐season analysis reveals hundreds of drought‐responsive genes in sorghum

Persistent drought affects global crop production and is becoming more severe in many parts of the world in recent decades. Deciphering how plants respond to drought will facilitate the development of flexible mitigation strategies. Sorghum bicolor L. Moench (sorghum), a major cereal crop and an emerging bioenergy crop, exhibits remarkable resilience to drought. To better understand the molecular traits that underlie sorghum's remarkable drought tolerance, we undertook a large-scale sorghum gene expression profiling effort, totaling nearly 1500 transcriptome profiles, across a 3-year field study with replicated plots in California's Central Valley. This study included time-resolved gene expression data from roots and leaves of two sorghum genotypes, BTx642 and RTx430, with different pre-flowering and post-flowering drought-tolerance adaptations under control and drought conditions. Quantification of genotype-specific drought tolerance effects was enabled by de novo sequencing, assembly, and annotation of both BTx642 and RTx430 genomes. These reference-quality genomes were used to construct a pangene set for characterizing conserved and genotype-specific expression. By integrating time-resolved transcriptomic responses to drought in the field across three consecutive years, we identified a set of 726 drought-responsive genes that responded similarly in all 3 years of our field study. Functional enrichment analysis identified abiotic stress, secondary cell wall-related processes and metabolism as particularly affected under both types of drought stress. We also found that some glyoxylate cycle pathway genes, including malate synthase and isocitrate lyase, are differentially regulated particularly during post-flowering drought stress, implicating this pathway as potentially important for drought responsiveness. This expansive dataset represents a unique resource for sorghum and drought research communities and provides a methodological framework for the integration of multi-faceted time-resolved transcriptomic datasets.

Cole, Benjamin [USDOE Joint Genome Institute (JGI)↗

Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSM and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Furthermore, our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.

54 ENVIRONMENTAL SCIENCES↗

Future Opportunities and Challenges in Remote Sensing of Drought

The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.

Wardlow, Brian D.↗

Drought Prediction for Socio-Cultural Stability Project

The primary objective of this project is to answer the question: "Can existing, linked infrastructures be used to predict the onset of drought months in advance?" Based on our work, the answer to this question is "yes" with the qualifiers that skill depends on both lead-time and location, and especially with the associated teleconnections (e.g., ENSO, Indian Ocean Dipole) active in a given region season. As part of this work, we successfully developed a prototype drought early warning system based on existing/mature NASA Earth science components including the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5) forecasting model, the Land Information System (LIS) land data assimilation software framework, the Catchment Land Surface Model (CLSM), remotely sensed terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE) and remotely sensed soil moisture products from the Aqua/Advanced Microwave Scanning Radiometer - EOS (AMSR-E). We focused on a single drought year - 2011 - during which major agricultural droughts occurred with devastating impacts in the Texas-Mexico region of North America (TEXMEX) and the Horn of Africa (HOA). Our results demonstrate that GEOS-5 precipitation forecasts show skill globally at 1-month lead, and can show up to 3 months skill regionally in the TEXMEX and HOA areas. Our results also demonstrate that the CLSM soil moisture percentiles are a goof indicator of drought, as compared to the North American Drought Monitor of TEXMEX and a combination of Famine Early Warning Systems Network (FEWS NET) data and Moderate Resolution Imaging Spectrometer (MODIS)'s Normalizing Difference Vegetation Index (NDVI) anomalies over HOA. The data assimilation experiments produced mixed results. GRACE terrestrial water storage (TWS) assimilation was found to significantly improve soil moisture and evapotransportation, as well as drought monitoring via soil moisture percentiles, while AMSR-E soil moisture assimilation produced marginal benefits. We carried out 1-3 month lead-time forecast experiments using GEOS-5 forecasts as input to LIS/CLSM. Based on these forecast experiments, we find that the expected skill in GEOS-5 forecasts from 1-3 months is present in the soil moisture percentiles used to indicate drought. In the case of the HOA drought, the failure of the long rains in April appears in the February 1, March 1 and April 1 initialized forecasts, suggesting that for this case, drought forecasting would have provided some advance warning about the drought conditions observed in 2011. Three key recommendations for follow-up work include: (1) carry out a comprehensive analysis of droughts observed over the entire period of record for GEOS-5 forecasts; (2) continue to analyze the GEOS-5 forecasts in HOA stratifying by anomalies in long and short rains; and (3) continue to include GRACE TWS, Soil Moisture/Ocean Salinity (SMOS) and the upcoming NASA Soil Moisture Active/Passive (SMAP) soil moisture products in a routine activity building on this prototype to further quantify the benefits for drought assessment and prediction.

Peters-Lidard, Christa↗

Kenya Food Security & Agriculture II: Utilizing NASA Earth Observations to Enhance Drought Warning Systems and Develop Capacity to Use the RHEAS Model in Kenya

Twenty-three counties in Kenya experience frequent drought, which damages agricultural productivity and threatens the health and well being of millions. NASA DEVELOP partnered with NASA SERVIR, the Regional Centre for Mapping of Resources for Development (RCMRD) and Kenya’s National Drought Management Authority (NDMA) to enhance drought-detection capacity using NASA Earth observations. Currently, the NDMA publishes monthly Early Warning Bulletins with drought conditions for each arid or semi-arid county in Kenya. These bulletins utilize the Vegetation Condition Index (VCI) from the Moderate Resolution ImagingSpectroradiometer (MODIS) as well as a variety of biophysical, social and economic drought indicators, but do not allow for advanced forecasting. To improve drought-monitoring capabilities, the team created a Combined Drought Indicator (CDI) using the Regional Hydrologic Extremes Assessment System (RHEAS) model and data from Aqua and Terra MODIS and the National Centers for Environmental Prediction. The CDI combined precipitation anomalies, soil moisture anomalies, evaporative stress, and VCI according to weights determined by principal component analysis. To evaluate the performance of the CDI across Kenya, the team compiled a dataset of drought events from historical reports and the NDMA’s records. Results suggested that the CDI detected drought earlier thanVCI alone. However, more validation is needed to ensure that the CDI accurately and consistently detects drought earlier than current warning systems. In order to better understand the behavior of individual indices and the potential for earlier drought detection, the team also conducted a time-lag analysis. The team found that VCI responds to drought, on average, one month later than most other indices included in the CDI, suggesting that incorporating additional indices could improve early drought warning systems in Kenya.

Food Security & Agriculture↗

Kenya Food Security & Agriculture II: Utilizing NASA Earth Observations to Enhance Drought Warning Systems and Develop Capacity to Use the RHEAS Model in Kenya

Twenty-three counties in Kenya experience frequent drought, which damages agricultural productivity and threatens the health and well being of millions. NASA DEVELOP partnered with NASA SERVIR, the Regional Centre for Mapping of Resources for Development (RCMRD) and Kenya’s National Drought Management Authority (NDMA) to enhance drought-detection capacity using NASA Earth observations. Currently, the NDMA publishes monthly Early Warning Bulletins with drought conditions for each arid or semi-arid county in Kenya. These bulletins utilize the Vegetation Condition Index (VCI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as a variety of biophysical, social and economic drought indicators, but do not allow for advanced forecasting. To improve drought-monitoring capabilities, the team created a Combined Drought Indicator (CDI) using the Regional Hydrologic Extremes Assessment System (RHEAS) model and data from Aqua and Terra MODIS and the National Centers for Environmental Prediction.The CDI combined precipitation anomalies, soil moisture anomalies, evaporative stress, and VCI according to weights determined by principal component analysis. To evaluate the performance of the CDI across Kenya, the team compiled a dataset of drought events from historical reports and the NDMA’s records. Results suggested that the CDI detected drought earlier than VCI alone. However, more validation is needed to ensure that the CDI accurately and consistently detects drought earlier than current warning systems. In order to better understand the behavior of individual indices and the potential for earlier drought detection, the team also conducted a time-lag analysis. The team found that VCI responds to drought, on average, one month later than most other indices included in the CDI, suggesting that incorporating additional indices could improve early drought warning systems in Kenya.

Food Security & Agriculture↗

A Greening Future Elevates Flash Drought Risk in Northern Mid‐to‐High Latitudes

Flash droughts have become a growing concern, as they can emerge rapidly and increase the risk of crop failure. Although past studies have investigated the meteorological drivers and future changes of flash drought, why flash drought is more frequent over humid and vegetated regions remains underexplored. This study delves further into the mechanism by which vegetation regulates flash drought and its future change using observations from multiple data sets and large ensemble simulations from three Earth system models. On an interannual timescale, both observations and simulations show robust increases in flash drought frequency and a higher flash-to-sub-seasonal drought ratio during spring or antecedent conditions with dense vegetation, supporting the important role of vegetation in flash drought occurrence, especially in the northern mid-to-high latitudes. In the latter regions, the large ensemble simulations show robust increases in flash drought (e.g., 67% and 46% increases in Eastern U.S. and North Asia in 2050–2100 relative to 1950–2000 under the high emission scenario), where the growing season is lengthening. Although greening might suggest reduced drought stress, it drives precipitation-soil moisture-evapotranspiration decoupling by increasing evapotranspiration partitioning to transpiration. As transpiration can access deep soil water through the plant root system, its increased portion can weaken the constraints of concurrent precipitation on evapotranspiration, thus accelerating soil moisture depletion under high evaporative demand, driving a slow-to-rapid drought transition. How vegetation regulates flash drought by regulating surface moisture budget is supported by observations and simulations. Although warming supports early planting, agriculture may increasingly be threatened by surging flash drought risk.

Drought↗

FIND: A Synthetic weather generator to control drought Frequency, Intensity, and Duration

Water systems worldwide are experiencing climate change-induced shifts in drought properties like frequency, intensity, and duration, affecting water security and reliability. To develop and test effective drought preparedness plans, researchers often use synthetic weather generators to create hydrological scenarios that explore drought variability beyond historical records. Existing weather generators typically allow users to adjust streamflow statistics like percentiles or temporal correlation but do not directly control drought properties of frequency, intensity, and duration. To fill this gap, we propose FIND (Frequency, INtensity, and Duration) synthetic weather generator. FIND incorporates a standardized drought index to directly and in dependently control drought frequency, intensity, and duration in generated streamflow time series while preserving observed hydrological variability. Use cases for FIND include i) water systems analysis applications that seek to train and test drought strategies under historical and plausible future drought conditions, and ii) bottom-up vulnerability studies relating system vulnerability outcomes to specific changes in drought properties of frequency, intensity, and duration. Here, we demonstrate FIND’s versatility through three experiments: replicating historically observed drought properties, generating streamflow scenarios for multiple sites preserving correlation between their drought conditions, and generating a set of scenarios with direct and independent changes in drought properties. FIND source code is openly available for applications beyond the scope of this paper.

42 ENGINEERING↗

Uncertainty Analysis of Simulations of the Turn-of-the-Century Drought in the Western United States

Here, we perform the first uncertainty quantification analysis of the turn-of-the-century drought in the western United States using a large perturbed-parameter ensemble of the Community Atmosphere Model version 4.0 (CAM4). We develop several metrics to characterize the aridity bias, spatial extent, and tropical forcing of the drought and use statistical models to ascertain that the modeled drought was mainly sensitive to CAM4 parameters related to deep convection and clouds. Deep convection parameters account for over half the variance across the drought metrics. We employ observed estimates of these drought metrics to infer probability distributions of the model parameters that lead to a better agreement with observations, thereby providing guidance on how to improve the simulation of drought in CAM4. We find that in some cases, the suggested parameter values that improve the simulation of one drought characteristic would degrade the simulation of another, suggesting that there is a complex relationship between the model parameters and drought in the western United States. We also demonstrate reductions in the uncertainty of the drought metrics of up to 30% by constraining with observations of all metrics. Additionally, we demonstrate for the first time that improvements to the simulation of the spatial extent of the turn-of-the-century drought also lead to improvements in the spatial extent of the Australian Millennium drought, suggesting that physics of drought as encoded by the model parameters may be generalizable.

58 GEOSCIENCES↗

Evolution of global snow drought characteristics from 1850 to 2100

Abstract Seasonal snow is an integral part of the global water supply and storage system. Snow droughts impact ecological, agricultural, and urban systems by altering the amount and timing of meltwater delivery. These droughts are characterized by a lack of on-the-ground snow (snow water equivalent, SWE) that can be caused by low total precipitation (dry drought) or low proportion of precipitation falling as snowfall (warm drought), often combined with an early melt. The standardized SWE index (SWEI) ranks the current status of SWE for a given location compared to a baseline condition and identifies the existence, but not the cause, of snow drought. In this work, we use estimates of SWE, temperature, and precipitation from nine coupled model intercomparison project phase 6 (CMIP6) models to quantify the frequency, severity, and type of snow droughts globally for historical and future scenarios. Compared to a historical baseline (1850–1900) total snow drought frequency more than doubles under socio-economic pathway (SSP)2-4.5 and SSP5-8.5; all of the increase in snow drought frequency comes from an increase in warm droughts. The probability distribution of future SWEI in major snowy basins around the world are likely to be centered on more negative values, which corresponds to more severe drought and, with only moderate changes in distribution spread, more frequent drought. CMIP6 simulations pinpoint snow drought as an emerging global threat to water resources and highlight the need to explore higher resolution future models that better capture complex mountain topography, wildland fires, and snow-forest interactions.

CMIP6↗

Projected evolution of droughts and human exposure in the contiguous United States under SSP5-8.5: a regional downscaling perspective

The increasingly unpredictable and extreme weather patterns under a warming climate underscore the urgency of accurate regional assessments of future drought risk. This study evaluates the projected drought evolution in the contiguous United States under the high-emission shared socioeconomic pathway 5–8.5 climate scenario for the coming decades. Using a multi-model ensemble of six Coupled Model Intercomparison Project Phase 6 global climate models combined with dynamical downscaling techniques, we analyzed near-term (2020–2039) and mid-term (2040–2059) drought patterns using the self-calibrating palmer drought severity index (ScPDSI), the standardized precipitation index (SPI-12), and the Standardized Precipitation-Evapotranspiration Index (SPEI-12). Results reveal a widespread increase in abnormally dry (D0) and moderate drought (D1) conditions, particularly in urban areas, while severe (D2), extreme (D3), and exceptional (D4) droughts are expected to become less common in many regions. Meanwhile, persistent and intensifying droughts are projected in the western and southwestern U.S., driven by long-term soil moisture deficits. The ScPDSI projects that 1.1 million urban residents will be affected by D0 conditions in 2050, while SPI-12 suggests a decrease in the total affected populations after 2040. ScPDSI indicates prolonged droughts in the West, and SPI-12 captures transient variability. Although the total drought-exposed population is expected to decrease, urban areas will continue to bear a greater burden, particularly for mild droughts (D0, D1). These findings highlight a shift toward more frequent mild droughts, fewer severe droughts, and persistent drying in the Southwest, emphasizing the need for region-specific adaptation strategies.

CMIP6↗

Experimental drought and heat can delay phenological development and reduce foliar and shoot growth in semiarid trees

Higher temperatures associated with climate change are anticipated to trigger an earlier start to the growing season, which could increase the terrestrial C sink strength. Greater variability in the amount and timing of precipitation is also expected with higher temperatures, bringing increased drought stress to many ecosystems. We experimentally assessed the effects of higher temperature and drought on the foliar phenology and shoot growth of mature trees of two semiarid conifer species. We exposed field-grown trees to a ~45% reduction in precipitation with a rain-out structure (‘drought’), a ~4.8 °C temperature increase with open-top chambers (‘heat’), and a combination of both simultaneously (‘drought + heat’). Over the 2013 growing season, drought, heat, and drought + heat treatments reduced shoot and needle growth in piñon pine ( Pinus edulis ) by ≥39%, while juniper ( Juniperus monosperma ) had low growth and little response to these treatments. Needle emergence on primary axis branches of piñon pine was delayed in heat, drought, and drought + heat treatments by 19–57 days, while secondary axis branches were less likely to produce needles in the heat treatment, and produced no needles at all in the drought + heat treatment. Growth of shoots and needles, and the timing of needle emergence correlated inversely with xylem water tension and positively with nonstructural carbohydrate concentrations. Our findings demonstrate the potential for delayed phenological development and reduced growth with higher temperatures and drought in tree species that are vulnerable to drought and reveal potential mechanistic links to physiological stress responses. Furthermore, climate change projections of an earlier and longer growing season with higher temperatures, and consequent increases in terrestrial C sink strength, may be incorrect for regions where plants will face increased drought stress with climate change.

54 ENVIRONMENTAL SCIENCES↗

Amazon drought resilience – emerging results point to new empirical needs

Will climate change turn tropical forests from a carbon sink to a source (Pan et al., 2011)? Tropical forests cycle more carbon, water, and energy than any other biome (Bonan, 2008). The Amazon is the largest tropical forest, spanning one-third of South America, and any perturbation in its function has repercussions on the global climate. Mild and severe droughts in the Amazon are predicted to double and triple in area, respectively, by 2100, while the area under wet extremes will increase (Duffy et al., 2015). Our understanding of the role of plants' hydrological environments in determining their drought response, however, is limited (Chitra-Tarak et al., 2018, 2021). An important review by Costa et al. (2023; pp. 714–733) published in this issue of New Phytologist highlights that shallow-water table (WT) forests constitute c. 50% of the Amazon and may act as hydrological refugia during droughts, yet they have been neglected in Amazon forest research to date. Emerging results suggest that the shallow-WT forests that dominate the Amazon basin may increase in productivity under moderate droughts due to relief from hypoxia, suggesting a potential buffer from drought relative to deeper WT forests (Fig. 1). During severe droughts, however, shallow-WT forests may be vulnerable to collapse due to drought-intolerant traits. Addressing the underrepresentation of relatively drought-resilient shallow-WT forests in the Amazon's forest inventories may help resolve the much-debated incongruence in recent studies of the Amazon's drought resilience. Data from forest inventories (biased toward deep-WT forests) indicate that the Amazon's carbon sink is declining, partially because of drought impacts (Phillips et al., 2009; Brienen et al., 2015), whereas basin-wide satellite-based measures of gross primary productivity, which include shallow-WT forests, indicate varied regional responses to droughts (Saleska et al., 2007; Brando et al., 2010). Costa et al.'s (2023) descriptive insights of the intricate balance of geology, topography, hydrology, vegetation, and drought on ecosystem function, as well as their conceptual predictive framework, are useful for developing new empirical research in these understudied ecosystems and improving Earth system models.

54 ENVIRONMENTAL SCIENCES↗

Drought Drives Spatial Variation in the Millet Root Microbiome

Efforts to boost crop yield and meet global food demands while striving to reach sustainability goals are hindered by the increasingly severe impacts of abiotic stress, such as drought. One strategy for alleviating drought stress in crops is to utilize rootassociated bacteria, yet knowledge concerning the relationship between plant hosts and their microbiomes during drought remain under-studied. One broad pattern that has recently been reported in a variety of monocot and dicot species from both native and agricultural environments, is the enrichment of Actinobacteria within the drought-stressed root microbiome. In order to better understand the causes of this phenomenon, we performed a series of experiments in millet plants to explore the roles of drought severity, drought localization, and root development in provoking Actinobacteria enrichment within the root endosphere. Through 16S rRNA ampliconbased sequencing, we demonstrate that the degree of drought is correlated with levels of Actinobacterial enrichment in four species of millet. Additionally, we demonstrate that the observed drought-induced enrichment of Actinobacteria occurs along the length of the root, but the response is localized to portions of the root experiencing drought. Finally, we demonstrate that Actinobacteria are depleted in the dead root tissue of Japanese millet, suggesting saprophytic activity is not the main cause of observed shifts in drought-treated root microbiome structure. Collectively, these results help narrow the list of potential causes of drought-induced Actinobacterial enrichment in plant roots by showing that enrichment is dependent upon localized drought responses but not root developmental stage or root death.

59 BASIC BIOLOGICAL SCIENCES↗