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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Using long‐term data from a whole ecosystem warming experiment to identify best spring and autumn phenology models

Abstract Predicting vegetation phenology in response to changing environmental factors is key in understanding feedbacks between the biosphere and the climate system. Experimental approaches extending the temperature range beyond historic climate variability provide a unique opportunity to identify model structures that are best suited to predicting phenological changes under future climate scenarios. Here, we model spring and autumn phenological transition dates obtained from digital repeat photography in a boreal Picea ‐ Sphagnum bog in response to a gradient of whole ecosystem warming manipulations of up to +9°C, using five years of observational data. In spring, seven equally best‐performing models for Larix utilized the accumulation of growing degree days as a common driver for temperature forcing. For Picea , the best two models were sequential models requiring winter chilling before spring forcing temperature is accumulated. In shrub, parallel models with chilling and forcing requirements occurring simultaneously were identified as the best models. Autumn models were substantially improved when a CO 2 parameter was included. Overall, the combination of experimental manipulations and multiple years of observations combined with variation in weather provided the framework to rule out a large number of candidate models and to identify best spring and autumn models for each plant functional type.

Schädel, Christina↗
DOE OSTI2022

Developing an ELM Ecosystem Dynamics Model on GPU with OpenACC

Porting a complex scientific code, such as the E3SM land model (ELM), onto a new computing architecture is challenging. The paper presents design strategies and technical approaches to develop an ELM ecosystem dynamics model with compiler directives (OpenACC) on NVIDIA GPUs. The code has been refactored with advanced OpenACC features (such as deepcopy and routine directives) to reduce memory consumption and to increase the levels of parallelism through parallel loop reconstruction and new data structures. As a result, the optimized parallel implementation achieved more than a 140-time speedup (50 ms vs 7600 ms), compared to a naive implementation that uses OpenACC routine directive and parallelizes the code across existing loops on a single NVIDIA V100. On a fully loaded computing node with 44 CPUs and 6 GPUs, the code achieved over a 3.0-times speedup, compared to the original code on the CPU. Furthermore, the memory footprint of the optimized parallel implementation is 300 MB, which is around 15% of the 2.15 GB of memory consumed by a naive implementation. This study is the first effort to develop the ELM component on GPUs efficiently to support ultra-high-resolution land simulations at continental scales.

Schwartz, Peter↗
DOE OSTI2022

Coral and Seawater Metagenomes Reveal Key Microbial Functions to Coral Health and Ecosystem Functioning Shaped at Reef Scale

The coral holobiont is comprised of a highly diverse microbial community that provides key services to corals such as protection against pathogens and nutrient cycling. The coral surface mucus layer (SML) microbiome is very sensitive to external changes, as it constitutes the direct interface between the coral host and the environment. Here, we investigate whether the bacterial taxonomic and functional profiles in the coral SML are shaped by the local reef zone and explore their role in coral health and ecosystem functioning. The analysis was conducted using metagenomes and metagenome-assembled genomes (MAGs) associated with the coral Pseudodiploria strigosa and the water column from two naturally distinct reef environments in Bermuda: inner patch reefs exposed to a fluctuating thermal regime and the more stable outer reefs. The microbial community structure in the coral SML varied according to the local environment, both at taxonomic and functional levels. The coral SML microbiome from inner reefs provides more gene functions that are involved in nutrient cycling (e.g., photosynthesis, phosphorus metabolism, sulfur assimilation) and those that are related to higher levels of microbial activity, competition, and stress response. In contrast, the coral SML microbiome from outer reefs contained genes indicative of a carbohydrate-rich mucus composition found in corals exposed to less stressful temperatures and showed high proportions of microbial gene functions that play a potential role in coral disease, such as degradation of lignin-derived compounds and sulfur oxidation. The fluctuating environment in the inner patch reefs of Bermuda could be driving a more beneficial coral SML microbiome, potentially increasing holobiont resilience to environmental changes and disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Whole-Ecosystem Warming Increases Plant-Available Nitrogen and Phosphorus in an Ombrotrophic Bog

Warming is expected to increase the net release of carbon from peatland soils, contributing to future warming. This positive feedback may be moderated by the response of peatland vegetation to rising atmospheric [CO 2 ] or to increased soil nutrient availability. We asked whether a gradient of whole-ecosystem warming (from + 0 °C to + 9 °C) would increase plant-available nitrogen and phosphorus in an ombrotrophic bog in northern Minnesota, USA, and whether elevated [CO 2 ] would modify the nutrient response. We tracked changes in plant-available nutrients across space and through time and in comparison with other nutrient pools, and assessed whether nutrient warming responses were captured by a point version of the land-surface model, ELM-SPRUCE. We found that warming exponentially increased plant-available ammonium and phosphate, but that nutrient dynamics were unaffected by elevated [CO 2 ]. The warming response increased by an order of magnitude between the first and fourth year of the experimental manipulation, perhaps because of dramatic mortality of Sphagnum mosses in the surface peat of the warmest treatments. However, neither the magnitude nor the temporal dynamics of the responses were captured by ELM-SPRUCE. Here, relative increases in plant-available ammonium and phosphate with warming were similar, but the response varied across raised hummocks and depressed hollows and with peat depth. Plant-available nutrient dynamics were only loosely correlated with inorganic and organic porewater nutrients, likely representing different processes. Future predictions of peatland nutrient availability under climate change scenarios must account for dynamic changes in nutrient acquisition by plants and microbes, as well as microtopography and peat depth.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Characterizing the movements and habitat use of two fish species of concern in a regulated ecosystem

In freshwater ecosystems in the northwest United States, the distribution and movements of fish between their essential habitats are particularly impacted by the presence of hydroelectric dams. Bull Trout Salvelinus confluentus and Westslope Cutthroat Trout Oncorhynchus clarkii var. lewisi are two fish species of concern inhabiting the Pend Oreille River between Idaho and Washington states. The purpose of this study was to identify the behavior and habitat use of Bull Trout and Westslope Cutthroat Trout in the restricted area of the Pend Oreille River, downstream of Albeni Falls Dam (AFD), using a long-term radiotelemetry dataset. Between 2015 and 2018, 24 Bull Trout and 24 Westslope Cutthroat Trout were captured, tagged, and released downstream AFD. Among the fish tagged, 79% (n = 19 of 24) of Bull Trout and 67% (n = 16 of 24) of Westslope Cutthroat Trout were detected during the study period. Our results revealed movements of fish towards tributary confluences mostly in May, June, and July for both species with Bull Trout traveling longer distances than Westslope Cutthroat Trout. Although the sample size was limited, Bull Trout individual movements towards the dam suggested attempts to re-ascend the river, indicating the importance of restoring upstream connectivity.

Garavelli, Lysel↗
DOE OSTI2023

Landscape-scale management for biodiversity and ecosystem services

Compelling evidence has accumulated that biodiversity in agricultural landscapes is declining. Reversing this trend requires us to transform how we envision and manage agricultural systems. Here, while most current efforts focus on modifying practices at the field scale, organisms are also affected by ecological patterns and processes that transcend individual fields and farms. Consequently, effective conservation of biodiversity and related ecosystem services will require addressing practices at the landscape scale as well.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Assessing the ability of $\mathrm{MODIS}$ $\mathrm{EVI}$ to estimate terrestrial ecosystem gross primary production of multiple land cover types

Terrestrial ecosystem gross primary production (GPP) is the largest component in the global carbon cycle. The enhanced vegetation index (EVI) has been proven to be strongly correlated with annual GPP within several biomes. However, the annual GPP-EVI relationship and associated environmental regulations have not yet been comprehensively investigated across biomes at the global scale. In this report we explored relationships between annual integrated EVI (iEVI) and annual GPP observed at 155 flux sites, where GPP was predicted with a log-log model: 1n(GPP) = a x 1n(iEVI) + b. iEVI was computed from MODIS monthly EVI products following removal of values affected by snow or cold temperature and without calculating growing season duration. Through categorisation of flux sites into 12 land cover types, the ability of iEVI to estimate GPP was considerably improved (R 2 from 0.62 to 0.74, RMSE from 454.7 to 368.2 g C m -2 yr -1 ). The biome-specific GPP-iEVI formulae generally showed a consistent performance in comparison to a global benchmarking dataset (R 2 = 0.79, RMSE = 387.8 g C m -2 yr -1 ). Specifically, iEVI performed better in cropland regions with high productivity but poorer in forests. The ability of iEVI in estimating GPP was better in deciduous biomes (except deciduous broadleaf forest) than in evergreen due to the large seasonal signal in iEVI in deciduous biomes. Likewise, GPP estimated from iEVI was in a closer agreement to global benchmarks at mid and high-latitudes, where deciduous biomes are more common and cloud cover has a smaller effect on remote sensing retrievals. Across biomes, a significant and negative correlation (R 2 = 0.37, p < 0.05) was observed between the strength (R 2 ) of GPP-iEVI relationships and mean annual maximum leaf area index (LAI max ), and the relationship between the strength and mean annual precipitation followed a similar trend. LAI max also revealed a scaling effect on GPP-iEVI relationships. Our results suggest that iEVI provides a very simple but robust approach to estimate spatial patterns of global annual GPP whereas its effect is comparable to various light-use-efficiency and data-driven models. The impact of vegetation structure on accuracy and sensitivity of EVI in estimating spatial GPP provides valuable clues to improve EVI-based models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Interactive effects of precipitation, temperature, and grazing pressure on the net ecosystem carbon balance of grazing lands across the continental United States

Grazing lands cover approximately one-third of the contiguous United States, support much of the nation's beef production, and are an important component of the U.S. terrestrial carbon budget. In this study, we quantified net ecosystem carbon balance (NECB), the net status of grazing lands as a carbon sink (C-sink) or source (C-source) and a key determinant of soil health and productivity. Our primary objective was to synthesize multiple years of annual NECB across heterogeneous grazing lands across the continental U.S and evaluate annual NECB against physical drivers (mean annual precipitation (MAP), mean annual temperature (MAT), vegetation, and moisture condition) and management practices (grazing pressure index (GPI) and fertilization history). We hypothesized that (1) NECB is higher in mesic and fertilized grasslands; (2) NECB increases with MAP and MAT but decreases with GPI; and (3) interactive effects exist among MAP, MAT, and GPI. Using carbon fluxes measured by eddy covariance towers and methane emissions including both enteric methane and manure derived from stocking rates across seven USDA Long-term Agroecosystem Research Network sites, we found: (1) grazing lands were a C-sink or carbon neutral at most sites; (2) vegetation type, moisture conditions, or fertilization had no significant effect on NECB; (3) NECB increased with MAP and MAT, but decreased with a higher GPI; and (4) MAT had a significant positive effect on NECB when MAP exceeded 750 mm (greater water availability). The effect of GPI on NECB was significantly negative when MAP was below 1000 mm, significantly negative when MAT < 12 °C and significantly positive when MAT > 16 °C. Thus, most grazing lands in our study acted as C-sinks unless water deficit, low temperature, or heavy grazing were interactively present. Understanding how climate and management influence NECB of grazing lands is key to maintaining resilient agroecosystems that secure beef production and sustain rural prosperity.

LTAR↗
DOE OSTI2018

Leaf area density from airborne LiDAR: Comparing sensors and resolutions in a temperate broadleaf forest ecosystem

Forest processes that play an essential role in carbon sequestration, such as light use efficiency, photosynthetic capacity, and trace gas exchange, are closely tied to the three-dimensional structure of forest canopies. However, the vertical distribution of leaf traits is not uniform; leaves at varying vertical positions within the canopy are physiologically unique due to differing light and environmental conditions, which leads to higher carbon storage than if light conditions were constant throughout the canopy. Due to this within-canopy variation, three-dimensional structural traits are critical to improving our estimates of global carbon cycling and storage by Earth system models and to better understanding the effects of disturbances on carbon sequestration in forested ecosystems. In this study, we describe a reproducible and open-source methodology using the R programming language for estimating leaf area density (LAD; the total leaf area per unit of volume) from airborne LiDAR. Using this approach, we compare LAD estimates at the Smithsonian Environmental Research Center in Maryland, USA, from two airborne LiDAR systems, NEON AOP and NASA G-LiHT, which differ in survey and instrument specifications, collections goals, and laser pulse densities. Furthermore, we address the impacts of the spatial scale of analysis as well as differences in canopy penetration and pulse density on LAD and leaf area index (LAI) estimates, while offering potential solutions to enhance the accuracy of these estimates. LAD estimates from airborne LiDAR can be used to describe the three-dimensional structure of forests across entire landscapes. Furthermore, this information can help inform forest management and conservation decisions related to the estimation of aboveground biomass and productivity, the response of forests to large-scale disturbances, the impacts of drought on forest health, the conservation of bird habitat, as well as a host of other important forest processes and responses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using stable isotopes to inform water resource management in forested and agricultural ecosystems

Present and future climatic trends are expected to markedly alter water fluxes and stores in the hydrologic cycle. In addition, water demand continues to grow due to increased human use and a growing population. Sustainably managing water resources requires a thorough understanding of water storage and flow in natural, agricultural, and urban ecosystems. Measurements of stable isotopes of water (hydrogen and oxygen) in the water cycle (atmosphere, soils, plants, surface water, and groundwater) can provide information on the transport pathways, sourcing, dynamics, ages, and storage pools of water that is difficult to obtain with other techniques. However, the potential of these techniques for practical questions has not been fully exploited yet. Here, we outline the benefits and limitations of potential applications of stable isotope methods useful to water managers, farmers, and other stakeholders. We also describe several case studies demonstrating how stable isotopes of water can support water management decision-making. Finally, we propose a workflow that guides users through a sequence of decisions required to apply stable isotope methods to examples of water management issues. We call for ongoing dialogue and a stronger connection between water management stakeholders and water stable isotope practitioners to identify the most pressing issues and develop best-practice guidelines to apply these techniques.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Environmental fate of radiocesium in biota inhabiting a contaminated ecosystem on the U.S. Department of Energy's Savannah River Site

Although biomagnification of radiocesium ( 137 Cs) has been reported in food webs, most previous research has been limited to select trophic linkages. Few studies have included a comprehensive survey of fauna associated with aquatic, semi-aquatic, and terrestrial habitats within a single study framework. The objectives of this study were to advance our understanding of the dynamics of 137 Cs accumulation within food webs by quantifying 137 Cs activity across a wide range of biota found within a contaminated canal, as well as test the hypothesis that life-stage and body size influence 137 Cs bioaccumulation in select herpetofauna. With extensive sampling across multiple taxa collected from a contaminated canal system and associated floodplain on the Savannah River Site, we assessed 137 Cs activity and stable nitrogen isotopes for both aquatic organisms that were restricted to the contaminated effluent canal, and semi-aquatic organisms able to move freely between the contaminated canal and the adjacent uncontaminated terrestrial habitat. We found 137 Cs activity to be highly variable among species, with evidence for and against biomagnification in semi-aquatic and aquatic organisms, respectively. Furthermore, 137 Cs activity decreased with life stage and body size in bullfrogs (Lithobates catesbeianus), despite post-metamorphic bullfrogs having a more carnivorous diet compared to tadpoles, while cottonmouths (Agkistrodon piscivorus) retained similar 137 Cs activity regardless of their age and size. While evidence of biomagnification has been observed in some contaminated systems, results of our study suggest the extent to which 137 Cs biomagnifies within food webs is context-dependent and likely influenced by a suite of biotic and abiotic factors. Further, our data indicate sampling of a broad suite of species and environmental attributes are needed to elucidate the fate and dynamics of anthropogenic pollutants within contaminated ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Keratinophilic fungi: Specialized fungal communities in a desert ecosystem identified using cultured-based and Illumina sequencing approaches

Soil fungi in desert ecosystems are adapted to harsh environmental conditions such as high soil surface temperatures and limited organic matter and water. Given limited carbon inputs from plant material, heterotrophic fungi likely use unconventional sources of carbon in these systems. A baiting method was used to culture keratinophilic fungi from biocrust and rhizosphere soils in an arid grassland in Utah, USA. Fungi were baited using llama and sheep wool, horsehair, and snakeskin on two media, and pure cultures were identified using ITS and LSU rRNA sequences. One hundred-eighteen fungal colonies were grown, representing a total of 32 Operational Taxonomic Units (OTUs) at 97 % similarity. Cultures were dominated by the phylum Ascomycota (88 %) followed by Mucoromycota (8.6 %) and Basidiomycota (3.4 %). The orders Pleosporales, Eurotiales, Hypocreales, and Sordariales were commonly isolated, with the dominant taxa Alternaria (27 %), Aspergillus (22 %), Fusarium (11 %), and Chaetomium (8%). Thirty percent of the fungi isolated have the capacity to degrade keratin in vitro using a keratin azure assay, with Penicillium showing the highest degradation followed by Geomyces, Alternaria, and Fusarium. Although keratin degraders can be infectious, dermatophytes associated with skin infections were not isolated in culture or detected in Illumina sequencing. Illumina sequencing was used to determine general patterns in seasonal variation and habitat preference of keratinophiles. Alternaria was the most abundant genus with >70 % of the sequences. The combination of Illumina data with culture-dependent approaches facilitated the characterization of a specialized community and confirmed the low abundance of dermatophytes in this arid site.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Satellite detection of soil moisture related water stress impacts on ecosystem productivity using the MODIS-based photochemical reflectance index

We report satellite remote sensing provides continuous observations of vegetation properties that can be used to estimate global terrestrial ecosystem gross primary production (GPP). The Photochemical Reflectance Index (PRI) has been shown to be sensitive to vegetation photosynthetic light use efficiency (LUE), GPP and canopy water-stress. Here in this paper, we use the NASA EOS MODIS (Moderate Resolution Imaging Spectroradiometer) based PRI with eddy covariance CO2 flux measurements and meteorological observations from 20 tower sites representing major plant functional type (PFT) classes within the continental USA (CONUS) to assess GPP sensitivity to soil moisture related water stress. The sPRI (scaled PRI) metric derived using MODIS band 13 as a reference channel (sPRI13) shows generally higher correspondence with tower GPP estimates than other potential MODIS reference bands. The sPRI13 observations were used as a proxy for soil moisture related water supply constraints to LUE within a satellite data driven terrestrial carbon flux model to estimate GPP (GPPPRI). The GPPPRI calculations show generally favorable correspondence with tower GPP estimates (0.457 ≤ R2 ≤ 0.818), except for lower GPPPRI performance over evergreen needleleaf forest (ENF) sites. A regional model sensitivity analysis using the sPRI13 as a water supply proxy indicated that water restrictions limit GPP over more than 21% of the CONUS domain, particularly in drier climate areas where atmospheric moisture deficits (VPD) alone are insufficient to represent both atmosphere demand and water supply controls affecting productivity. Our results indicate strong potential of the MODIS sPRI13 to represent soil moisture related water supply controls influencing photosynthesis, with enhanced (1-km resolution) delineation of these processes closer to the scale of in situ tower observations. Lastly, these observations may provide an effective tool for characterizing sub-grid spatial heterogeneity in soil moisture related controls that inform coarser scale observations and estimates determined from other satellite observations and earth system models.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Characterizing spatiotemporal dynamics in phenology of urban ecosystems based on Landsat data

Seasonal phenology of vegetation plays an important role in global carbon cycle and ecosystem productivity. In urban environments, vegetation phenology is also important because of its influence on public health (e.g., allergies), and energy demand (e.g. cooling effects). In this study, we studied the potential use of remotely sensed observations (i.e. Landsat data) to derive some phenology indicators for vegetation embedded within the urban core domains in four distinctly different U.S. regions (Washington, D.C., King County in Washington, Polk County in Iowa, and Baltimore City and County in Maryland) during the past three decades. We used all available Landsat observations (circa 3000 scenes) from 1982 to 2015 and a self-adjusting double logistic model to detect and quantify the annual change of vegetation phenophases, i.e. indicators of seasonal changes in vegetation. The proposed model can capture and quantify not only phenophases of dense vegetation in rural areas, but also those of mixed vegetation in urban core domains. The derived phenology indicators show a good agreement with similar indicators derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and in situ observations, suggesting that the phenology dynamic depicted by the proposed model is reliable. The vegetation phenology and its seasonal and interannual dynamics demonstrate a distinct spatial pattern in urban domains with an earlier (9–14 days) start-of season (SOS) and a later (13–20 days) end-of season (EOS), resulting in an extended (5–30 days) growing season length (GSL) when compared to the surrounding suburban and rural areas in the four study regions. There is a general long-term trend of decreasing SOS (-0.30 day per year), and increasing EOS and GSL (0.50 and 0.90 day per year, respectively) over past three decades for these study regions. The magnitude of these trends varies among the four urban systems due to their diverse local climate conditions, vegetation types, and different urban-rural settings. The Landsat derived phenology information for urban domains provides more details when compared to the coarse-resolution datasets such as MODIS, thus improves our understanding of human-natural systems interactions (or feedbacks) in urban domains. Such information is very valuable for urban planning in light of rapid urbanization and expansion of major metropolitans at the national and global levels.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A decreasing carbon allocation to belowground autotrophic respiration in global forest ecosystems

Belowground autotrophic respiration (RAsoil) depends on carbohydrates from photosynthesis flowing to roots and rhizospheres, and is one of the most important but least understood components in forest carbon cycling. Carbon allocation plays an important role in forest carbon cycling and reflects forest adaptation to changing environmental conditions. However, carbon allocation to RAsoil has not been fully examined at the global scale. To fill this knowledge gap, first, the spatio-temporal patterns of RAsoil from 1981 to 2017 were predicted by a Random Forest (RF) algorithm using the most updated Global Soil Respiration Database (v5) with global environmental variables; second, carbon allocation from photosynthesis to RAsoil (CAB), was calculated as the ratio of RAsoil to gross primary production; and its temporal and spatial patterns were assessed in global forest ecosystems. . Globally, mean RAsoil from forests was 8.9 ± 0.08 Pg C yr-1 (mean ± standard deviation) from 1981 to 2017 with strong spatial variabilities. Temporally, RAsoil increased at a rate of 0.0059 Pg C yr-2, paralleling broader soil respiration changes and indicating increasing carbon respired by roots. Mean CAB was 0.243 ± 0.016 and decreased over time. The temporal trend of CAB varied greatly in space, reflecting uneven responses of CAB to environmental changes. This study is the first attempt to predict global CAB and analyze its temporal and spatial patterns. With the linkage of carbon use efficiency, the developed CAB offers an completely independent approach to quantify global aboveground autotropic respiration spatially and temporally, which could provide crucial insights into carbon flux partition and global carbon cycling under climate change.

Tang, Xiaolu↗
DOE OSTI2017

Cross-biome assessment of gross soil nitrogen cycling in California ecosystems

Microbial transformations of nitrogen (N) largely determine whether N is retained in ecosystems via net primary productivity or lost via gaseous emissions and leaching. The controls on soil N cycling are often studied at single locales, making it difficult to predict N cycling at regional to global scales. We hypothesized that contemporary soil properties exhibit consistent relationships with instantaneous gross N cycling rates across diverse biomes that create a continuum in these properties. We measured ex situ gross N cycling rates and soil properties at 33 study sites representing five biome classifications in California including deserts, grasslands, shrublands, forest, and wetlands. Desert soils had significantly lower total N, organic carbon (C), microbial biomass N, and soil moisture as well as higher pH than all other biomes, whereas forests and wetlands had significantly lower soil nitrate ($NO_3^-$) concentrations (P < 0.001 for all). Gross mineralization rates were best predicted by the combination of soil moisture and soil C:N ratios (R 2 = 0.46), which exerted positive and negative controls, respectively. Grasslands exhibited marginally higher gross mineralization than all other biomes, whereas deserts had the lowest rates due to low soil moisture (P = 0.09). Gross nitrification rates were positively correlated to soil $NO_3^-$ concentrations (R 2 = 0.34) and negatively correlated to soil C:N ratios (R 2 = 0.31). The negative relationship between gross nitrification and soil C:N ratios was driven by forest soils, which had significantly higher C:N ratios and lower gross nitrification than all other biomes (P < 0.05). Dissimilatory $NO_3^-$- reduction to $NH_4^+$ (DNRA) occurred in soils from all biomes. The strong positive correlation between DNRA rates and soil $NO_3^-$ (R 2 = 0.41) suggests $NO_3^-$ limitation of DNRA. Predictable patterns in gross N cycling across biomes in California suggest that contemporary soil properties are important drivers of instantaneous soil N cycling rates that integrate over differences in vegetation type, atmospheric N deposition rates, and local climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

N-induced soil acidification triggers metal stimulation of soil methane oxidation in a temperate steppe ecosystem

Methane (CH 4 ) is a potent greenhouse gas, and it is well established that low nitrogen (N) stimulates- and high N suppresses CH 4 oxidation in grassland ecosystems. Here, in this study, we examined the response of CH 4 uptake to long-term (>10 years) multi-level N additions in a temperate steppe of northern China. The N impacts on CH 4 uptake transitioned from positive to negative at the N addition rate of 4 g N m -2 y -1 . However, the high-N suppression on CH 4 uptake was partially relieved when the continuous (>10 years) high N inputs (16 g N m -2 y -1 to 64 g N m -2 y -1 ) caused soil pH drop to < 5.7. Further experiments revealed that continuous high-N inputs acidified soil to pH < 5.7 that released metal ions to stimulate monooxygenase enzyme activity; therefore, the CH 4 oxidation suppression was partially relieved under continuous N loading. Structural equation model results confirmed that metal ions, such as Iron (Fe 3+ ), Manganese (Mn 4+ ), and Copper (Cu) desorbed by soil particles, were negatively correlated with soil pH while positively correlated with CH 4 oxidation under high N inputs. These analyses suggested that continuous high N inputs-induced soil acidification can release previously bounded metal elements that partially alleviated the N suppression on CH 4 uptake. The N-induced soil acidification impacts on CH 4 uptake might play a critical role in global CH 4 cycling and deserve further investigation as external N inputs continue climbing.

59 BASIC BIOLOGICAL SCIENCES↗