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At least 505 records · Page 28

Promises and challenges of eco-physiological genomics in the field: tests of drought responses in switchgrass

Identifying the physiological and genetic basis of stress tolerance in plants has proven to be critical to understanding adaptation in both agricultural and natural systems. However, many discoveries were initially made in the controlled conditions of greenhouses or laboratories, not in the field. To test the comparability of drought responses across field and greenhouse environments, we undertook three independent experiments using the switchgrass reference genotype Alamo AP13. We analyzed physiological and gene expression variation across four locations, two sampling times, and three years. Relatively similar physiological responses and expression coefficients of variation across experiments masked highly dissimilar gene expression responses to drought. Critically, a drought experiment utilizing small pots in the greenhouse elicited nearly identical physiological changes as an experiment conducted in the field, but an order of magnitude more differentially expressed genes. However, we were able to define a suite of several hundred genes that were differentially expressed across all experiments. This list was strongly enriched in photosynthesis, water status, and reactive oxygen species responsive genes. The strong across-experiment correlations between physiological plasticity—but not differential gene expression—highlight the complex and diverse genetic mechanisms that can produce phenotypically similar responses to various soil water deficits.

54 ENVIRONMENTAL SCIENCES↗

Warming increased bark beetle-induced tree mortality by 30% during an extreme drought in California

Quantifying the responses of forest disturbances to climate warming is critical to our understanding of carbon cycles and energy balances of the Earth system. The impact of warming on bark beetle outbreaks is complex as multiple drivers of these events may respond differently to warming. Using a novel model of bark beetle biology and host tree interactions, we assessed how contemporary warming affected western pine beetle (Dendroctonus brevicomis) populations and mortality of its host, ponderosa pine (Pinus ponderosa), during an extreme drought in the Sierra Nevada, California, United States. When compared with the field data, our model captured the western pine beetle flight timing and rates of ponderosa pine mortality observed during the drought. In assessing the influence of temperature on western pine beetles, we found that contemporary warming increased the development rate of the western pine beetle and decreased the overwinter mortality rate of western pine beetle larvae leading to increased population growth during periods of lowered tree defense. We attribute a 29.9% (95% CI: 29.4%–30.2%) increase in ponderosa pine mortality during drought directly to increases in western pine beetle voltinism (i.e., associated with increased development rates of western pine beetle) and, to a much lesser extent, reductions in overwintering mortality. These findings, along with other studies, suggest each degree (°C) increase in temperature may have increased the number of ponderosa pine killed by upwards of 35%–40% °C-1 if the effects of compromised tree defenses (15%–20%) and increased western pine beetle populations (20%) are additive. Due to the warming ability to considerably increase mortality through the mechanism of bark beetle populations, models need to consider climate's influence on both host tree stress and the bark beetle population dynamics when determining future levels of tree mortality.

59 BASIC BIOLOGICAL SCIENCES↗

Research frontiers in drought-induced tree mortality: Crossing scales and disciplines

Sudden and widespread forest die-back and die-off (e.g., Huang & Anderegg, 2012) and increased mortality rates (e.g., Peng et al., 2011) in many forest ecosystems across the globe have been linked to drought and elevated temperatures (Allen et al., 2010, Fig. 1). Furthermore, these observations have caused a focus on the physiological mechanisms of drought-induced tree mortality (e.g. McDowell et al., 2008) and many studies, both observational and manipulative, have been carried out to explain tree death during drought from a physiological perspective.

54 ENVIRONMENTAL SCIENCES↗

Anisohydric behavior linked to persistent hydraulic damage and delayed drought recovery across seven North American tree species

Summary The isohydry‐anisohydry spectrum has become a popular way to characterize plant drought responses and recovery processes. Despite the proven utility of this framework for understanding the interconnected physiological changes plants undergo in response to water stress, new challenges have arisen pertaining to the traits and tradeoffs that underlie this concept. To test the utility of this framework for understanding hydraulic traits, drought physiology and recovery, we applied a 6 wk experimental soil moisture reduction to seven tree species followed by a 6 wk recovery period. Throughout, we measured hydraulic traits and monitored changes in gas exchange, leaf water potential, and hydraulic conductivity. Species’ hydraulic traits were not coordinated, as some anisohydric species had surprisingly low resistance to embolism (P 50 ) and negative safety margins. In addition to widespread hydraulic damage, these species also experienced reductions in photosynthesis and stem water potential during water stress, and delayed recovery time. Given that we observed no benefit of being anisohydric either during or after drought, our results indicate the need to reconsider the traits and tradeoffs that underlie anisohydric behavior, and to consider the environmental, biological and edaphic processes that could allow this strategy to flourish in forests.

Kannenberg, Steven A.↗

Seasonal and drought‐related changes in leaf area profiles depend on height and light environment in an Amazon forest

Summary Seasonal dynamics in the vertical distribution of leaf area index ( LAI ) may impact the seasonality of forest productivity in Amazonian forests. However, until recently, fine‐scale observations critical to revealing ecological mechanisms underlying these changes have been lacking. To investigate fine‐scale variation in leaf area with seasonality and drought we conducted monthly ground‐based LiDAR surveys over 4 yr at an Amazon forest site. We analysed temporal changes in vertically structured LAI along axes of both canopy height and light environments. Upper canopy LAI increased during the dry season, whereas lower canopy LAI decreased. The low canopy decrease was driven by highly illuminated leaves of smaller trees in gaps. By contrast, understory LAI increased concurrently with the upper canopy. Hence, tree phenological strategies were stratified by height and light environments. Trends were amplified during a 2015–2016 severe El Niño drought. Leaf area low in the canopy exhibited behaviour consistent with water limitation. Leaf loss from short trees in high light during drought may be associated with strategies to tolerate limited access to deep soil water and stressful leaf environments. Vertically and environmentally structured phenological processes suggest a critical role of canopy structural heterogeneity in seasonal changes in Amazon ecosystem function.

Smith, Marielle N.↗

PHOTO‐SENSITIVE LEAF ROLLING 1 encodes a polygalacturonase that modifies cell wall structure and drought tolerance in rice

Summary The biosynthesis and modification of cell wall composition and structure are controlled by hundreds of enzymes and have a direct consequence on plant growth and development. However, the majority of these enzymes has not been functionally characterised. Rice mutants with leaf‐rolling phenotypes were screened in a field. Phenotypic analysis under controlled conditions was performed for the selected mutant and the relevant gene was identified by map‐based cloning. Cell wall composition was analysed by glycome profiling assay. We identified a photo‐sensitive leaf rolling 1 ( psl1 ) mutant with ‘napping’ (midday depression of photosynthesis) phenotype and reduced growth. The PSL1 gene encodes a cell wall‐localised polygalacturonase (PG), a pectin‐degrading enzyme. psl1 with a 260‐bp deletion in its gene displayed leaf rolling in response to high light intensity and/or low humidity. Biochemical assays revealed PG activity of recombinant PSL1 protein. Significant modifications to cell wall composition in the psl1 mutant compared with the wild‐type plants were identified. Such modifications enhanced drought tolerance of the mutant plants by reducing water loss under osmotic stress and drought conditions. Taken together, PSL1 functions as a PG that modifies cell wall biosynthesis, plant development and drought tolerance in rice.

Zhang, Guangheng↗

Embolism spread in the primary xylem of Polystichum munitum : implications for water transport during seasonal drought

Abstract Xylem network structure and function have been characterized for many woody plants, but less is known about fern xylem, particularly in species endemic to climates where water is a limiting resource for months at a time. We characterized seasonal variability in soil moisture and frond water status in a common perennial fern in the redwood understory of a costal California, and then investigated the consequences of drought‐induced embolism on vascular function. Seasonal variability in air temperature and soil water content was minimal, and frond water potential declined slowly over the observational period. Our data show that Polystichum munitum was protected from significant drought‐induced hydraulic dysfunction during this growing season because of a combination of cavitation resistant conduits (Air‐seeding threshold (ASP) = −1.53 MPa; xylem pressure inducing 50% loss of hydraulic conductivity ( P 50 ) = −3.02 MPa) and a soil with low moisture variability. High resolution micro‐computed tomography (MicroCT) imaging revealed patterns of embolism formation in vivo for the first time in ferns providing insight into the functional status of the xylem network under drought conditions. Together with stomatal conductance measurements, these data suggest that P . munitum is adapted to tolerate drier conditions than what was observed during the growing season.

Brodersen, Craig R.↗

Gene network analysis of poplar root transcriptome in response to drought stress identifies a PtaJAZ3PtaRAP2.6-centered hierarchical network

Using time-series transcriptomic data from poplar roots undergoing polyethylene glycol (PEG)-induced drought stress, we built a genetic network model of the involved putative molecular responses. We found that the network resembled a hierarchical structure. The highest hierarchical level in this structure is occupied by 9 genes, which we called superhubs because they were primarily connected to 18 hub genes, which are then connected to 2,934 terminal genes. We were only able to regenerate transgenic plants overexpressing two of the superhubs, suggesting that the majority of the superhubs might interfere with the regeneration process and did not allow recovery of transgenic plants. The two superhubs encode proteins with closest homology to JAZ3 and RAP2.6 genes of Arabidopsis and were consequently named PtaJAZ3 and PtaRAP2.6. PtaJAZ3 and PtaRAP2.6 overexpressing transgenic lines showed a significant increase in both root elongation and lateral root proliferation and these responses were specific for the drought stress conditions and were highly correlated with the levels of overexpression of the transgenes. Several lines of evidence suggest of regulatory interactions between the two superhubs. Both superhubs were significantly induced by methyl jasmonate (MeJA). Because jasmonate signaling involves ubiquitin-mediated proteasome degradation, treatment with proteasome inhibitor abolished the MeJA induction for both genes. PtaRAP2.6 was upregulated in PtaJAZ3 transgenics but PtaJAZ3 expression was not affected in the PtaRAP2.6 overexpressors. The discovery of the two genes and further future insights into the associated mechanisms can lead to improved understanding and novel approaches to regulate root architecture in relation to drought stress.

59 BASIC BIOLOGICAL SCIENCES↗

Global analysis of epigenetic regulation of gene expression in response to drought stress in Sorghum.

Abiotic stresses including drought are major limiting factors of crop yields and cause significant crop losses. Acquisition of stress tolerance to abiotic stresses requires coordinated regulation of a multitude of biochemical and physiological changes, and most of these changes depend on alterations in gene expression. The goal of this work is to perform global analysis of differential regulation of gene expression and alternative splicing, and their relationship with chromatin landscape in drought sensitive and tolerant cultivars. our Iso-Seq study revealed transcriptome-wide full-length isoforms at an unprecedented scale with over 11000 novel splice isoforms. Additionally, we uncovered alternative polyadenylation sites of ~11000 expressed genes and many novel genes. Overall, Iso-Seq results greatly enhanced sorghum gene annotations that are not only useful in analyzing all our RNA-seq, ChIP-seq and ATAC-seq data but also serve as a great resource to the plant biology community. Our studies identified differentially expressed genes and splicing events that are correlated with the drought-resistant phenotype. An association between alternative splicing and chromatin accessibility was also revealed. Several computational tools developed here (TAPIS and iDiffIR) have been made freely available to the research community in analyzing alternative splicing and differential alternative splicing.

09 BIOMASS FUELS↗

Characterizing proteases in sorghum drought response using activity-based protein profiling (ABPP)

Sorghum (Sorghum bicolor) is a C4 grass species that is a major food and bioenergy crop grown worldwide. Understanding the response of sorghum to climate change is therefore critical to future sustainable food and bioenergy production. Major advancements in genome sequencing have provided a wealth of genomic data for DOE-relevant plant species, but the functions of many of these genes remain unknown. Genotype to phenotype characterization of sorghum and other bioenergy crops is needed to identify key genes responsible for plant resilience to drought and other environmental stressors. Proteases, which modulate protein degradation and cellular signaling processes by catalyzing the hydrolysis of proteins into smaller proteins, peptides, or amino acids, are highly implicated in plant drought stress responses. We developed a method for using activity-based protein profiling (ABPP) of selected protease activities (serine and cysteine proteases) to characterize drought stress responses in sorghum roots and leaves. Analysis of these ABPP data identified several known serine and cysteine proteases as well as uncharacterized sorghum proteins which may have protease activities that can be explored in future validation studies.

09 BIOMASS FUELS↗

Biogeochemical consequences of microbial evolution under drought (Final technical report)

As the climate changes, droughts may become more severe. Scientists are uncertain about how drought will affect the natural world, particularly the bacteria, fungi, and other microbes that live in soils and control the Earth’s flows of carbon and nutrients. Researchers at the University of California, Irvine, and Lawrence Berkeley National Laboratory teamed up to study how microbes at the soil surface change with drought and what that means for the carbon cycle. Since 2007, the researchers have used shelters with retractable roofs to prevent nearly half of normal rainfall from reaching grass and shrub landscapes, and their soil microbiomes, in Southern California.

54 ENVIRONMENTAL SCIENCES↗

An Inventory of AI-ready Benchmark Data for US Fires, Heatwaves, and Droughts

Extreme weather events, including fires, heatwaves, and droughts, have significant impacts on earth, environmental, and energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning for, and responding to these extremes. Records of extreme weather events provide an important data source for understanding present and future extremes, but the existing data needs preprocessing before it can be used for analysis. Moreover, there are many nonstandard metrics defining the levels of severity or impacts of extremes. In this study, we compile a comprehensive benchmark data inventory of extreme weather events, including fires, heatwaves, and droughts. The dataset covers the period from 2001 to 2020 with a daily temporal resolution and a spatial resolution of 0.5°×0.5° (~55km×55km) over the continental United States (CONUS), and a spatial resolution of 1km × 1km over the Pacific Northwest (PNW) region, together with the co-located and relevant meteorological variables. By exploring and summarizing the spatial and temporal patterns of these extremes in various forms of marginal, conditional, and joint probability distributions, we gain a better understanding of the characteristics of climate extremes. The resulting AI/ML-ready data products can be readily applied to ML-based research, fostering and encouraging AI/ML research in the field of extreme weather. This study can contribute significantly to the advancement of extreme weather research, aiding researchers, policymakers, and practitioners in developing improved preparedness and response strategies to protect communities and ecosystems from the adverse impacts of extreme weather events. Usage Notes We presented a long term (2001-2020) and comprehensive data inventory of historical extreme events with daily temporal resolution covering the separate spatial extents of CONUS (0.5°×0.5°) and PNW(1km×1km) for various applications and studies. The dataset with 0.5°×0.5° resolution for CONUS can be used to help build more accurate climate models for the entire CONUS, which can help in understanding long-term climate trends, including changes in the frequency and intensity of extreme events, predicting future extreme events as well as understanding the implications of extreme events on society and the environment. The data can also be applied for risk accessment of the extremes. For example, ML/AI models can be developed to predict wildfire risk or forecast HWs by analyzing historical weather data, and past fires or heateave , allowing for early warnings and risk mitigation strategies. Using this dataset, AI-driven risk assessment models can also be built to identify vulnerable energy and utilities infrastructure, imrpove grid resilience and suggest adaptations to withstand extreme weather events. The high-resolution 1km×1km dataset ove PNW are advantageous for real-time, localized and detailed applications. It can enhance the accuracy of early warning systems for extreme weather events, helping authorities and communities prepare for and respond to disasters more effectively. For example, ML models can be developed to provide localized HW predictions for specific neighborhoods or cities, enabling residents and local emergency services to take targeted actions; the assessment of drought severity in specific communities or watersheds within the PNW can help local authorities manage water resources more effectively.

Lin, Xinming↗

Meteorological and Hydrological Drought Analysis Datasets for Livneh, ClimRR, and TGW

The current dataset contains data upload links to the following SPI & SRI drought analysis data over CONUS: Climate Forcing and Simulation Scenario: Livneh (https://www.nature.com/articles/sdata201542): Historical ClimRR (https://climrr.anl.gov/climrrdata): Historical, Mid-Century, End-Century TGW (https://tgw-data.msdlive.org/): Historical, Mid-Century, End-Century Analysis Period: Vary by Climate Forcing Drought Type: Meteorological (Precipitation) and Hydrological (Runoff) Drought (3-Month SRI) Output Format: NetCDF and CSV Spatial Resolution: 1/16th Degree for NetCDF and HUC4 for CSV Temporal Resolution: Monthly

Tidwell, Vincent C [Pacific Northwest National Lab↗

Leveraging hyperspectral imaging to identify drought tolerant Populus species and genotypes within species

The aim of this study was to identity variation in drought tolerance across genotypes of Populus deltoides, Populus trichocarpa, and hybrids of the two species. A panel of 102 Populus genotypes, comprising 37 genotypes of P. trichocarpa, 37 of P. deltoides and 28 unique hybrid genotypes (P. trichocarpa x P. deltoides and P. deltoides x P. trichocarpa) were evaluated in the greenhouse under two treatments, well-watered (WW) and drought (DS). Plant physiological data were collected throughout the experiment once the drought treatment began. Throughout the experiment, we tracked soil volumetric water content, pot weight, stomatal conductance, quantum yield of photosystem II, and electron transport rate. In addition to those measurements, upon completion of the experiment, we assessed above and belowground plant biomass, plant height and stem diameter, leaf number, specific leaf area, relative water content, total protein, and total chlorophyll. We obtained hyperspectral signatures of one leaf from each plant at the end of the experiment. Columns BC – LL are hyperspectral averages for one leaf from each plant at each wavelength as described in the column header.

Hyper-spectral imaging, Populus, plant stress tole↗

A bi-level spatiotemporal clustering approach and its application to drought extraction

We present a novel flexible bi-level spatiotemporal clustering algorithm to extract events based on their intensity and spatiotemporal structures. Our algorithm consists of using (i) a novel space-time k-means clustering to obtain spatiotemporally coherent intensity clusters, and (ii) a density-based spatial clustering of applications with noise (DBSCAN) to spatiotemporally section the intensity clusters into individual events. We discuss the development of the algorithm, the selection, tuning and meaning of the parameters within each step, as well as its validation. Finally, we apply the algorithm to a spatiotemporal drought index, standardized vapor pressure deficit drought index (SVDI), over the continental United States (US) from 1980–2021 and show that it captures historical drought events over the continental United States and their spatiotemporal extents.

17 WIND ENERGY↗

Drought adaptation in Arabidopsis thaliana by extensive genetic loss-of-function

Interdisciplinary syntheses are needed to scale up discovery of the environmental drivers and molecular basis of adaptation in nature. Here we integrated novel approaches using whole genome sequences, satellite remote sensing, and transgenic experiments to study natural loss-of-function alleles associated with drought histories in wild Arabidopsis thaliana. The genes we identified exhibit population genetic signatures of parallel molecular evolution, selection for loss-of-function, and shared associations with flowering time phenotypes in directions consistent with longstanding adaptive hypotheses seven times more often than expected by chance. We then confirmed predicted phenotypes experimentally in transgenic knockout lines. These findings reveal the importance of drought timing to explain the evolution of alternative drought tolerance strategies and further challenge popular assumptions about the adaptive value of genetic loss-of-function in nature. These results also motivate improved species-wide sequencing efforts to better identify loss-of-function variants and inspire new opportunities for engineering climate resilience in crops.

Life Sciences & Biomedicine - Other Topics↗

An investigation of surface albedo variations during the recent sahel drought

Applications Technology Satellite 3 green sensor data were used to measure surface reflectance variations in the Sahara/Sahel during the recent drought period; 1967 to 1974. The magnitude of the seasonal reflectance change is shown to be as much as 80% for years of normal precipitation and less than 50% for drought years. Year to year comparisons during both wet and dry seasons reveal the existence of a surface reflectance cycle coincident with the drought intensity. The relationship between the green reflectance and solar albedo is examined and estimated to be about 0.6 times the reflectance change observed by the green channel.

Norton, C. C.↗

An investigation of surface albedo variations during the recent Sahel drought

Applications Technology Satellite (ATS) 3 green sensor data are used to measure surface reflectance variations in the Sahara/Sahel during the recent drought period 1967-74. The magnitude of the seasonal reflectance change is shown to be as much as 80% for years of normal precipitation and less than 50% for drought years. Year-to-year comparisons during both wet and dry seasons reveal the existence of a surface reflectance cycle coincident with the drought intensity. The relationship between the green reflectance and solar albedo is examined and estimated to be about 0.6 times the reflectance change observed by the green channel.

Norton, C. C.↗