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At least 1,171 records · Page 65

SUMO Leaf Water Potential

The Los Alamos Survival–Mortality experiment (SUMO) is located on Frijoles Mesa near Los Alamos, New Mexico, USA, at an elevation of 2150 m. This was a tree manipulation study that investigated the relative impacts of drought and warming on plant function and reveals how trees adapt to drought and heat in semi-arid regions. The study factored the role of tree hydraulic acclimation to both precipitation and temperature and separated their effects.The experiment is located in a pinon-juniper woodland near the ponderosa pine (Pinus ponderosa) forest ecotone. Monthly pre-dawn and midday shoot water potentials for each target tree. See SUMO Target Tree Information data package (doi:10.15485/1440544) for additional information. Data released by Los Alamos National Lab for public use under LA-UR-18-23656.

54 ENVIRONMENTAL SCIENCES↗

SUMO Maximum Assimilation

The Los Alamos Survival–Mortality experiment (SUMO) is located on Frijoles Mesa near Los Alamos, New Mexico, USA, at an elevation of 2150 m. This was a tree manipulation study that investigated the relative impacts of drought and warming on plant function and reveals how trees adapt to drought and heat in semi-arid regions. The study factored the role of tree hydraulic acclimation to both precipitation and temperature and separated their effects.The experiment is located in a pinon-juniper woodland near the ponderosa pine (Pinus ponderosa) forest ecotone. Maximum assimilation rate measured monthly for each target tree. See SUMO Target Tree Information data package (doi:10.15485/1440544) for additional information. Data released by Los Alamos National Lab for public use under LA-UR-18-23656.

54 ENVIRONMENTAL SCIENCES↗

SUMO Chamber Conditions

The Los Alamos Survival–Mortality experiment (SUMO) is located on Frijoles Mesa near Los Alamos, New Mexico, USA, at an elevation of 2150 m. This was a tree manipulation study that investigated the relative impacts of drought and warming on plant function and reveals how trees adapt to drought and heat in semi-arid regions. The study factored the role of tree hydraulic acclimation to both precipitation and temperature and separated their effects.The experiment is located in a pinon-juniper woodland near the ponderosa pine (Pinus ponderosa) forest ecotone. Chamber conditions (temperature, relative humidity, vapor pressure deficit) for SUMO Open Top Chambers (OTCs) used to control air temperatures surrounding heated and control chamber trees. See SUMO Target Tree Information data package (doi:10.15485/1440544) for additional information. Data released by Los Alamos National Lab for public use under LA-UR-18-23656.

54 ENVIRONMENTAL SCIENCES↗

SUMO Micrometeorology

The Los Alamos Survival–Mortality experiment (SUMO) is located on Frijoles Mesa near Los Alamos, New Mexico, USA, at an elevation of 2150 m. This was a tree manipulation study that investigated the relative impacts of drought and warming on plant function and reveals how trees adapt to drought and heat in semi-arid regions. The study factored the role of tree hydraulic acclimation to both precipitation and temperature and separated their effects.The experiment is located in a pinon-juniper woodland near the ponderosa pine (Pinus ponderosa) forest ecotone. Daily average ambient micrometeorological conditions at the SUMO site. See SUMO Target Tree Information data package (doi:10.15485/1440544) for additional information. Data released by Los Alamos National Lab for public use under LA-UR-18-23656.

54 ENVIRONMENTAL SCIENCES↗

SUMO Nitrogen Labeling Experiment and Soil Biogeochemistry

The Los Alamos Survival–Mortality experiment (SUMO) is located on Frijoles Mesa near Los Alamos, New Mexico, USA, at an elevation of 2150 m. This was a tree manipulation study that investigated the relative impacts of drought and warming on plant function and reveals how trees adapt to drought and heat in semi-arid regions. The study factored the role of tree hydraulic acclimation to both precipitation and temperature and separated their effects.The experiment is located in a pinon-juniper woodland near the ponderosa pine (Pinus ponderosa) forest ecotone. In a semi-arid woodland, adult trees (piñon and juniper) were exposed to chronic warming (+4 °C) and precipitation reduction (-45 %). After five years of continuous treatment exposure, soil and plant nitrogen isotopic composition were measured to assess plant nitrogen allocation. See SUMO Target Tree Information data package (doi:10.15485/1440544) for additional information. Data released by Los Alamos National Lab for public use under LA-UR-18-23656.

15N isotopic composition↗

Pinus ponderosa physiology data from the 2023 girdling manipulation field experiment at Game Ridge, Missoula County, Montana, USA

This dataset contains physiology data on Pinus ponderosa saplings, including: leaf water potential (MPa, megapascals), leaf osmotic potential (MPa, megapascals), leaf pressure potential (MPa, megapascals), leaf relative water content (% saturated mass), as well as soluble sugars (% dry mass),starch (% dry mass), and total nonstructural carbohydrates (% dry mass) found in branch phloem and xylem. Data files and data dictionary(ies) are uploaded as .csv files and .xlsx files. The Users Guide is a .pdf file. Location data can be found in the Google Earth file GameRidge_SitePlotCoordinates.kmz.kml included here. These datasets were collected for Plant Carbohydrate Depletion, Mycorrhizal Networks, and Vulnerability to Drought: An Experimental Test in the Field. This experiment examined the interdependency between plant hydraulics and carbohydrate availability and sought to develop ways to incorporate interactions with below ground symbiotic organisms to better model and quantify forest response to drought.

54 ENVIRONMENTAL SCIENCES↗

Microbial community data from throughfall exclusion experiment: Metadata, SI, community composition, LefSe, and FunGuilR data tables from PARCHED Panama tropical forest soils, 2024-2025

Soil contains more carbon (C) than terrestrial vegetation and the atmosphere combined, with some of the largest terrestrial C stocks in tropical rainforests. Soil microbes decompose organic matter, playing a vital role in the storage or loss of soil C. With climate change, drought conditions are predicted to increase in many tropical regions, including both chronic drying and extended drought, potentially influencing these processes. This project explored the effects of chronic and seasonal drying on soil microbial communities across four distinct tropical forests in a long-term drying experiment. We investigated the effects of a chronic drying manipulation on soil microbial community abundance and variation across different forests and seasons. We also compared findings with previously published data from these forests after short-term drying. This project used soils from a long-term drying experiment established in 2018 across four seasonal lowland forests in Panama. Soils were collected from 0 – 10 cm depths during three seasonal periods in control and drying plots in 2024 and 2025 from a total of 32 plots (n = 4 per forest per treatment). The forests varied in baseline rainfall and soil fertility. We calculated alpha and beta diversity indices and compared taxonomic community composition. We found significant biogeographic variation in microbial diversity and taxonomy, with significant differences across the forests and significant effects of the drying treatment. Metadata and sample IDs are within Metadata_16S.csv and Metadata_ITS.csv. Relative abundance tables of every sample at every season are shown in the Excel workbooks 16S Relative Abundance.xlsx and ITS Relative Abundance.xlsx. They are then also shown in CSV files by each taxonomic level. Linear discriminant analysis effect size (LefSe) tables are shown for the full 16S and ITS datasets (n = 96), subsets for every site at every season (n = 8), and then for the forests with each plot merged by season (n = 8). FunGuildR data table of ITS data is uploaded.

Bacteria↗

Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoonal Asia

We developed further our advanced methods of time series analysis and empirical model reduction (EMR) and applied them to climatic time series relevant to hydroclimate over Monsoonal Asia. The EMR methodology was both generalized further and laid on a rigorous mathematical basis via multilayered stochastic models (MSMs). We identified easily testable conditions that imply the existence of a global random attractor for MSMs and allow for non-polynomial predictors. This existence, in turn, guarantees the numerical stability of the MSMs so obtained. We showed that, in the presence of low-frequency variability (LFV), EMR prediction can be improved further by including information from selected times in the system’s past. This prediction method, dubbed Past-Noise Forecasting (PNF), was successfully applied to the Madden-Julian Oscillation (MJO). Our time series analysis and forecasting methods, based on singular-spectrum analysis (SSA) and its enhancements, were applied to several multi-centennial proxy records provided by the Lamont team. These included the Palmer Drought Severity Index (PDSI) for 1300–2005 from the Monsoonal Asia Drought Atlas (MADA), and a 300-member ensemble of pseudo-reconstructions of Indus River discharge for 1702–2005. The latter was shown to exhibit a robust 27-yr low-frequency mode, which helped multi-decadal retroactive forecasts with no look-ahead over this 300-year interval.

54 ENVIRONMENTAL SCIENCES↗

RhizoGrid Indexed Sorghum Rhizosphere Multi-Omics

PerCon SFA project data dentification of spatially resolved biomarkers of drought in Sorghum bicolor rhizosphere molecular-microbe interactions using a novel root cartography "RhizoGrid" system for sampling plants under drought and control conditions across 10 equally sized root zone environments (4 quadrants each). Each quadrant was sampled and processed for 16S amplicon, metabolomics, and X-ray computed tomography (XCT). Data download includes experimental metadata and results files for 16S rRNA sequence analysis of microbial community assembly (processed data files), liquid chromatography mass spectrometry (LC-MS) metabolomics analysis of microbial community root exudates (processed data files), X-ray computed tomography (XCT) spatial gradient analysis (raw and processed data files) of microbial community composition, and related computational modeling outputs.

59 BASIC BIOLOGICAL SCIENCES↗

Overexpression of an Agave Phosphoenolpyruvate Carboxylase Improves Plant Growth and Stress Tolerance

It has been challenging to simultaneously improve photosynthesis and stress tolerance in plants. Crassulacean acid metabolism (CAM) is a CO2-concentrating mechanism that facilitates plant adaptation to water-limited environments. We hypothesized that the ectopic expression of a CAM-specific phosphoenolpyruvate carboxylase (PEPC), an enzyme that catalyzes primary CO2 fixation in CAM plants, would enhance both photosynthesis and abiotic stress tolerance. To test this hypothesis, we engineered a CAM-specific PEPC gene (named AaPEPC1) from Agave americana into tobacco. In comparison with wild-type and empty vector controls, transgenic tobacco plants constitutively expressing AaPEPC1 showed a higher photosynthetic rate and biomass production under normal conditions, along with significant carbon metabolism changes in malate accumulation, the carbon isotope ratio δ13C, and the expression of multiple orthologs of CAM-related genes. Furthermore, AaPEPC1 overexpression enhanced proline biosynthesis, and improved salt and drought tolerance in the transgenic plants. Under salt and drought stress conditions, the dry weight of transgenic tobacco plants overexpressing AaPEPC1 was increased by up to 81.8% and 37.2%, respectively, in comparison with wild-type plants. Our findings open a new door to the simultaneous improvement of photosynthesis and stress tolerance in plants.

59 BASIC BIOLOGICAL SCIENCES↗

Transcriptome and Degradome Profiling Reveals a Role of miR530 in the Circadian Regulation of Gene Expression in Kalanchoë marnieriana

Crassulacean acid metabolism (CAM) is an important photosynthetic pathway for plant adaptation to dry environments. CAM plants feature a coordinated interaction between mesophyll and epidermis functions that involves refined regulations of gene expression. Plant microRNAs (miRNAs) are crucial post-transcription regulators of gene expression, however, their roles underlying the CAM pathway remain poorly investigated. Here, we present a study characterizing the expression of miRNAs in an obligate CAM species Kalanchoë marnieriana. Through sequencing of transcriptome and degradome in mesophyll and epidermal tissues under the drought treatments, we identified differentially expressed miRNAs that were potentially involved in the regulation of CAM. In total, we obtained 84 miRNA genes, and eight of them were determined to be Kalanchoë-specific miRNAs. It is widely accepted that CAM pathway is regulated by circadian clock. We showed that miR530 was substantially downregulated in epidermal peels under drought conditions; miR530 targeted two tandem zinc knuckle/PLU3 domain encoding genes (TZPs) that were potentially involved in light signaling and circadian clock pathways. Our work suggests that the miR530-TZPs module might play a role of regulating CAM-related gene expression in Kalanchoë.

Kalanchoë↗

Assessment of Climate Change Impacts on Renewable Energy Resources in Western North America

We examine a 25 km resolution climate model dataset to evaluate how regional climate change impacts solar and wind energy under a high-emission scenario. Our study considers the Western Electricity Coordinating Council (WECC) region, which covers the western United States and southwestern Canada, focusing specifically on locations with existing solar and wind infrastructure. First, we conduct a historical model comparison of solar and wind energy capacity factors to highlight model uncertainties across the study area. Using future climate projections, we then assess the seasonal patterns of solar and wind capacity factors for three timeframes: historical, mid-century, and end of century. Additionally, we estimate the frequency of solar and wind resource droughts during these periods for the entire WECC and its five operational subregions, finding that certain subregions are more susceptible to energy droughts due to limited renewable resources. Finally, we present day-ahead capacity factor forecasts to support energy storage planning and provide estimates of offshore wind energy capacity within the WECC. Our results indicate that offshore wind capacity factors are nearly twice as high as onshore values, with less seasonal variation, which suggests that offshore wind could offer a more consistent renewable energy supply in the future.

climate change↗

Accessing Fungal Contributions to the Birch Effect: Real-Time Respiration from Pore-Scale Microfluidics

Drying and rewetting of soil stimulates soil carbon emission. The Birch effect, driven by these cycles, leads to CO2 efflux, which can be monitored using real-time mass spectrometry (RTMS). Although soil fungi retain water during droughts, their contribution to CO2 release during drying–rewetting cycles remains unclear. In this study, we present the first demonstration of integrating micromodels with RTMS to monitor the Birch effect by simulating drought and rewetting. Micromodels were inoculated with axenic fungal culture and dried to assess moisture retention. After drying, RTMS quantified CO2 release upon rewetting with H218O mixtures. Our results showed that soil fungi released CO2 upon rehydration and immediately utilized the external water source at the pore scale by generating subsequent 46CO2. This work is the first to integrate RTMS with microsystems to investigate pore-scale biogeochemistry and the involvement of fungi in the Birch effect.

54 ENVIRONMENTAL SCIENCES↗

Climate Induced Birch Mortality in Trans-Baikal Lake Region, Siberia

The Trans-Baikal (or Zabailkal'e) region includes the forest-steppe ecotones south and east of Lake Baikal in Russia and has experienced drought for several years. The decline and mortality of birch (Betula pendula) stands within the forest-steppe ecotone Trans-Baikal region was studied based on a temporal series of satellite data, ground measurements, and tree ring analysis. During the first decade of the 21st century birch stands decline and mortality were observed on )about 5% of the total area of stands within our 1250 km(exp 2 study area. Birch forest decline and mortality occurs mainly at the margins of stands, within the forest-steppe ecotone on slopes with direct insolation. During the first decade of the 21st century summer (June-August) precipitation was about 25% below normal. Soil water content measurements were lowest within dead stands and highest within healthy stands and intermediate within damaged stands. Drought impact on stands was amplified by an increase in summer air temperatures (+0.9 C) in comparison with the previous decade. Tree ring data of ''surviving'' and ''dead'' tree groups showed a positive correlation with summer/annual precipitation and negative correlation with summer air temperatures. Temperature and precipitation extreme anomalies tend to occur in the region with a period of about 27 years. The observed anomaly was the most severe since the beginning of meteorological observations in the year 1900. Data for the other sites showed a positive climate impact on the growth and expansion of Siberian forests. That is, the same species (B. pendula) showed considerable increase (1.4 times both in height and stem volume) during 20th-21st centuries as temperature increased but precipitation remained at adequate levels.

Forest die-off↗

Transitioning Enhanced Land Surface Initialization and Model Verification Capabilities to the Kenya Meteorological Department (KMD)

Flooding, severe weather, and drought are key forecasting challenges for the Kenya Meteorological Department (KMD), based in Nairobi, Kenya. Atmospheric processes leading to convection, excessive precipitation and/or prolonged drought can be strongly influenced by land cover, vegetation, and soil moisture content, especially during anomalous conditions and dry/wet seasonal transitions. It is thus important to represent accurately land surface state variables (green vegetation fraction, soil moisture, and soil temperature) in Numerical Weather Prediction (NWP) models. The NASA SERVIR and the Short-term Prediction Research and Transition (SPoRT) programs in Huntsville, AL have established a working partnership with KMD to enhance its regional modeling capabilities. SPoRT and SERVIR are providing experimental land surface initialization datasets and model verification capabilities for capacity building at KMD. To support its forecasting operations, KMD is running experimental configurations of the Weather Research and Forecasting (WRF; Skamarock et al. 2008) model on a 12-km/4-km nested regional domain over eastern Africa, incorporating the land surface datasets provided by NASA SPoRT and SERVIR. SPoRT, SERVIR, and KMD participated in two training sessions in March 2014 and June 2015 to foster the collaboration and use of unique land surface datasets and model verification capabilities. Enhanced regional modeling capabilities have the potential to improve guidance in support of daily operations and high-impact weather and climate outlooks over Eastern Africa. For enhanced land-surface initialization, the NASA Land Information System (LIS) is run over Eastern Africa at ~3-km resolution, providing real-time land surface initialization data in place of interpolated global model soil moisture and temperature data available at coarser resolutions. Additionally, real-time green vegetation fraction (GVF) composites from the Suomi-NPP VIIRS instrument is being incorporated into the KMD-WRF runs, using the product generated by NOAA/NESDIS. Model verification capabilities are also being transitioned to KMD using NCAR's Model *Corresponding author address: Jonathan Case, ENSCO, Inc., 320 Sparkman Dr., Room 3008, Huntsville, AL, 35805. Email: Jonathan.Case-1@nasa.gov Evaluation Tools (MET; Brown et al. 2009) software in conjunction with a SPoRT-developed scripting package, in order to quantify and compare errors in simulated temperature, moisture and precipitation in the experimental WRF model simulations. This extended abstract and accompanying presentation summarizes the efforts and training done to date to support this unique regional modeling initiative at KMD. To honor the memory of Dr. Peter J. Lamb and his extensive efforts in bolstering weather and climate science and capacity-building in Africa, we offer this contribution to the special Peter J. Lamb symposium. The remainder of this extended abstract is organized as follows. The collaborating international organizations involved in the project are presented in Section 2. Background information on the unique land surface input datasets is presented in Section 3. The hands-on training sessions from March 2014 and June 2015 are described in Section 4. Sample experimental WRF output and verification from the June 2015 training are given in Section 5. A summary is given in Section 6, followed by Acknowledgements and References.

land surface modeling↗

North American Megadroughts in the Common Era: Reconstructions and Simulations

During the Medieval Climate Anomaly (MCA), Western North America experienced episodes of intense aridity that persisted for multiple decades or longer. These megadroughts are well documented in many proxy records, but the causal mechanisms are poorly understood. General circulation models (GCMs) simulate megadroughts, but do not reproduce the temporal clustering of events during the MCA, suggesting they are not caused by the time history of volcanic or solar forcing. Instead, GCMs generate megadroughts through (1) internal atmospheric variability, (2) sea-surface temperatures, and (3) land surface and dust aerosol feedbacks. While no hypothesis has been definitively rejected, and no GCM has accurately reproduced all features (e.g., timing, duration, and extent) of any specific megadrought, their persistence suggests a role for processes that impart memory to the climate system (land surface and ocean dynamics). Over the 21st century, GCMs project an increase in the risk of megadrought occurrence through greenhouse gas forced reductions in precipitation and increases in evaporative demand. This drying is robust across models and multiple drought indicators, but major uncertainties still need to be resolved. These include the potential moderation of vegetation evaporative losses at higher atmospheric [CO2], variations in land surface model complexity, and decadal to multidecadal modes of natural climate variability that could delay or advance onset of aridification over the the next several decades. Because future droughts will arise from both natural variability and greenhouse gas forced trends in hydroclimate, improving our understanding of the natural drivers of persistent multidecadal megadroughts should be a major research priority.

atmospheric temperature↗

Wildfires Dynamics in Siberian Larch Forests

Wildfire number and burned area temporal dynamics within all of Siberia and along a south-north transect in central Siberia (45deg-73degN) were studied based on NOAA/AVHRR (National Oceanic and Atmospheric Administration/ Advanced Very High Resolution Radiometer) and Terra/MODIS (Moderate Resolution Imaging Spectroradiometer) data and field measurements for the period 1996-2015. In addition, fire return interval (FRI) along the south-north transect was analyzed. Both the number of forest fires and the size of the burned area increased during recent decades (p < 0.05). Significant correlations were found between forest fires, burned areas and air temperature (r = 0.5) and drought index (The Standardized Precipitation Evapotranspiration Index, SPEI) (r = 0.43). Within larch stands along the transect, wildfire frequency was strongly correlated with incoming solar radiation (r = 0.91). Fire danger period length decreased linearly from south to north along the transect. Fire return interval increased from 80 years at 62 N to 200 years at the Arctic Circle (6633' N), and to about 300 years near the northern limit of closed forest stands (about 71+ N). That increase was negatively correlated with incoming solar radiation (r = 0.95). Keywords: wildfires; drought index; larch stands; fire return interval; fire frequency; burned area; climate-induced trends in Siberian wildfires

wildfires↗

New Methods for Retrieval of Chlorophyll Red Fluorescence from Hyperspectral Satellite Instruments: Simulations and Application to GOME-2 and SCIAMACHY

Global satellite measurements of solar-induced fluorescence (SIF) from chlorophyll over land and ocean have proven useful for a number of different applications related to physiology, phenology, and productivity of plants and phytoplankton. Terrestrial chlorophyll fluorescence is emitted throughout the red and far-red spectrum, producing two broad peaks near 683 and 736nm. From ocean surfaces, phytoplankton fluorescence emissions are entirely from the red region (683nm peak). Studies using satellite-derived SIF over land have focused almost exclusively on measurements in the far red (wavelengths greater than 712nm), since those are the most easily obtained with existing instrumentation. Here, we examine new ways to use existing hyperspectral satellite data sets to retrieve red SIF (wavelengths less than 712nm) over both land and ocean. Red SIF is thought to provide complementary information to that from the far red for terrestrial vegetation. The satellite instruments that we use were designed to make atmospheric trace-gas measurements and are therefore not optimal for observing SIF; they have coarse spatial resolution and only moderate spectral resolution (0.5nm). Nevertheless, these instruments, the Global Ozone Monitoring Instrument 2 (GOME-2) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), offer a unique opportunity to compare red and far-red terrestrial SIF at regional spatial scales. Terrestrial SIF has been estimated with ground-, aircraft-, or satellite-based instruments by measuring the filling-in of atmospheric andor solar absorption spectral features by SIF. Our approach makes use of the oxygen (O2) gamma band that is not affected by SIF. The SIF-free O2 gamma band helps to estimate absorption within the spectrally variable O2 B band, which is filled in by red SIF. SIF also fills in the spectrally stable solar Fraunhofer lines (SFLs) at wavelengths both inside and just outside the O2 B band, which further helps to estimate red SIF emission. Our approach is then an extension of previous approaches applied to satellite data that utilized only the filling-in of SFLs by red SIF. We conducted retrievals of red SIF using an extensive database of simulated radiances covering a wide range of conditions. Our new algorithm produces good agreement between the simulated truth and retrievals and shows the potential of the O2 bands for noise reduction in red SIF retrievals as compared with approaches that rely solely on SFL filling. Biases seen with existing satellite data, most likely due to instrumental artifacts that vary in time, space, and with instrument, must be addressed in order to obtain reasonable results. Our 8-year record of red SIF observations over land with the GOME-2 allows for the first time reliable global mapping of monthly anomalies. These anomalies are shown to have similar spatiotemporal structure as those in the far red, particularly for drought-prone regions. There is a somewhat larger percentage response in the red as compared with the far red for these areas that are drought sensitive. We also demonstrate that good-quality ocean fluorescence line height retrievals can be achieved with GOME-2, SCIAMACHY, and similar instruments by utilizing the full complement of radiance measurements that span the red SIF emission feature.

spatiotemporal structure↗