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At least 847 records · Page 47

On the use of air temperature and precipitation as surrogate predictors in soil respiration modelling

Soil respiration (R S ), the soil-to-atmosphere CO 2 flux that is a major component of the global carbon cycle, is strongly influenced by local soil temperature (T soil ) and water content (SWC). Regional to global-scale R S modelling thus requires this information at local scales, but few high-quality, wall-to-wall (global) T soil and SWC data exist. As a result, such modelling efforts commonly use air temperature (T air ) and monthly precipitation (P m ) as surrogate predictors, but their site-scale accuracy and potential bias are unknown. In this report we used monthly data from 880 sites across a wide variety of different environmental conditions (i.e., climate, ecosystem type, elevation, vegetation leaf habit and drainage conditions) to determine the suitability of T air as a surrogate for T soil , and data from 507 sites to examine the suitability of P m as a surrogate for SWC. Site-specific linear and second-order exponential non-linear models were compared using model evaluation metrics (i.e., slope, p-value of slope, root mean square error [RMSE], index of agreement and model efficiency). We found that T soil and T air are highly correlated and explain similar R S variability. In contrast, P m is not a good surrogate for SWC, even though P m explains a similar amount of R S variability to SWC. The wide variability in the site-specific relationships between R S and SWC means that no single relationship can be used for large-scale modelling. The results from this study support the use of T air in continental-to-global scale R S models, and highlight the urgent need for continental-to-global scale SWC datasets for the modelling and evaluation of future soil carbon dynamics under global climate change.

54 ENVIRONMENTAL SCIENCES↗

Organic carbon enables the biotic engineering of beneficial soil structure in Profundihumic and Haplic Ferralsols

We investigated how organic matter may, directly and indirectly, modify the porosity of Ferralsols, that is, deeply weathered soils of the tropics and subtropics. Although empirical and anecdotal evidence suggests that organic matter accumulation may increase porosity, a mechanistic understanding of the processes underlying this beneficial effect is lacking, especially so for Ferralsols. To achieve our end, we leveraged the fact that the Profundihumic qualifier of Ferralsols (PF) is distinguished from Haplic Ferralsols (HF) by both a much larger average carbon content in the first 1 m of soil depth (19 kg C m -3 in PF vs. 10 kg C m -3 in HF) and a significantly lower bulk density (1.05 ± 0.08 kg L -1 in PF vs. 1.21 ± 0.05 kg L -1 in HF). Through exhaustive modelling of carbon – bulk density relationships, we demonstrate that the lower bulk density of PF cannot be satisfactorily explained by a simple dilution effect. Rather, we found that bulk density correlated with carbon content when combined with carbon: nitrogen ratio (r 2 = 0.51), black carbon content (r 2 = 0.75), and Δ 14 C (r 2 =0.81). Total pore space was greater in PF (61± 3%) than in HF (55 ± 2%), but x-ray computed tomography revealed that pore space inside soil aggregates of 4–5 mm diameter does not vary between the studied Ferralsols. We further observed nearly twice as many roots and burrows in PF compared with HF. We thus infer that the mechanism responsible for the increase in porosity is most likely an enhancement of resource availability (e.g., energy, carbon, and nutrients) for the organisms (earthworms, ants, termites, etc.) that physically displace soil particles and promote soil aggregation. As a result of increased resource availability, soil organisms can create especially the mesoscale structural soil features necessary for unrestricted water flow and rapid gas exchange. In conclusion, this insight paves the way for the development of land management technologies to optimize the physical shape and capacity of the soil bioreactor.

54 ENVIRONMENTAL SCIENCES↗

Historical Land Management Alters New Soil Carbon Inputs by Annual and Perennial Bioenergy Crops

Bioenergy and bioproduct markets are expanding to meet demand for climate-friendly goods and services. Perennial biomass crops are particularly well suited for this goal because of their high yields, low input requirements, and potential to increase soil carbon (C). However, it is unclear how much C is allocated into belowground pools by perennial bioenergy crops and whether the belowground benefits vary with nitrogen (N) fertilizer inputs. Using in situ 13 C pulse-chase labeling, we tested whether the sterile perennial grass Miscanthus × giganteus (miscanthus) or annual maize transfers more photosynthetic C to belowground pools. The experiment took place at two sites in Central and Northwest (NW) Iowa with different management histories and two nitrogen (N) fertilizer rates (0 and 224 kg N ha −1 year −1 ) to determine if the fate of plant-derived soil C depends on soil fertility and crop type (perennial or annual). Maize allocated a greater percentage of total new 13 C to roots than miscanthus, but miscanthus had greater new 13 C in total and belowground plant biomass. We found strong interactions between site and most soil measurements—including new 13 C in mineral and particulate soil organic matter (SOM) pools—which appears to be driven by differences in historical fertilizer management. The NW Iowa site, with a history of manure inputs, had greater plant-available nutrients (phosphorus, potassium, and ammonium) in soils, and resulted in less 13 C from miscanthus in SOM pools compared to maize (approximately 64% less in POM and 70% less in MAOM). In more nutrient-limited soils (Central site), miscanthus transferred 4.5 times more 13 C than maize to the more stable mineral-associated SOM pool. Our results suggest that past management, including historical manure inputs that affect a site's soil fertility, can influence the net C benefits of bioenergy crops.

13C↗

A roadmap to understanding and anticipating microbial gene transfer in soil communities

Engineered microbes are being programmed using synthetic DNA for applications in soil to overcome global challenges related to climate change, energy, food security, and pollution. However, we cannot yet predict gene transfer processes in soil to assess the frequency of unintentional transfer of engineered DNA to environmental microbes when applying synthetic biology technologies at scale. This challenge exists because of the complex and heterogeneous characteristics of soils, which contribute to the fitness and transport of cells and the exchange of genetic material within communities. Here, we describe knowledge gaps about gene transfer across soil microbiomes. Here, we propose strategies to improve our understanding of gene transfer across soil communities, highlight the need to benchmark the performance of biocontainment measures in situ, and discuss responsibly engaging community stakeholders. We highlight opportunities to address knowledge gaps, such as creating a set of soil standards for studying gene transfer across diverse soil types and measuring gene transfer host range across microbiomes using emerging technologies. By comparing gene transfer rates, host range, and persistence of engineered microbes across different soils, we posit that community-scale, environment-specific models can be built that anticipate biotechnology risks. Such studies will enable the design of safer biotechnologies that allow us to realize the benefits of synthetic biology and mitigate risks associated with the release of such technologies.

bioccontainment↗

Ectomycorrhizal fungi alter soil food webs and the functional potential of bacterial communities

Most of Earth’s trees rely on critical soil nutrients that ectomycorrhizal fungi (EcMF) liberate and provide, and all of Earth’s land plants associate with bacteria that help them survive in nature. Yet, our understanding of how the presence of EcMF modifies soil bacterial communities, soil food webs, and root chemistry requires direct experimental evidence to comprehend the effects that EcMF may generate in the belowground plant microbiome. To this end, we grew Pinus muricata plants in soils that were either inoculated with EcMF and native forest bacterial communities or only native bacterial communities. We then profiled the soil bacterial communities, applied metabolomics and lipidomics, and linked omics data sets to understand how the presence of EcMF modifies belowground biogeochemistry, bacterial community structure, and their functional potential. We found that the presence of EcMF (i) enriches soil bacteria linked to enhanced plant growth in nature, (ii) alters the quantity and composition of lipid and non-lipid soil metabolites, and (iii) modifies plant root chemistry toward pathogen suppression, enzymatic conservation, and reactive oxygen species scavenging. Using this multi-omic approach, we therefore show that this widespread fungal symbiosis may be a common factor for structuring soil food webs.

59 BASIC BIOLOGICAL SCIENCES↗

Data from Raczka et al., Interactions between microbial diversity and substrate chemistry determine the fate of carbon in soil, from Elizabeth Woods in Morgantown, West Virginia, USA

File types include: Soil respiration as 13C cumulative respiration from soil incubation experiment, qSIP (quantitative stable isotope probing) data that is "18S apes wide" which is the fungal atom percent excess or how much the fungi took up of the labeled litter and "16S apes wide" which is the bacterial atom percent excess or how much the bacteria took up of the labeled litter, metabolomic data from the incubated soil samples called "Metab Soil Unique Filtered", which is the metabolomic data that had an initial filter from the raw data, and lipidomic data from the incubated soil samples called "All lipids soil". These files were used according to methods in Raczka et al. 2021 Scientific Reports. Headers show soil type (Oak, Poplar) and litter type (also called substrate here, which is labeled as no litter (control), poplar, and oak). This research was done to understand interactions between ecosystem-level processes and microbial diversity that impacts the composition of decomposition products that can form stable soil organic matter.

54 ENVIRONMENTAL SCIENCES↗

Volumetric Soil Moisture Measurements at the Teller 27 Site, Seward Peninsula, Alaska, 2022-2023

The Teller 27 watershed on the Seward Peninsula, Alaska, has been well characterized by the NGEE Arctic project. The study site is underlain by discontinuous permafrost that is thawing as the climate warms. As a result, the site is experiencing a short-term wetting trend as a perched water table above the remaining permafrost provides plant available water during the growing season. Soil moisture patterns drive microbial activity and plant species compositions including plant density and height. This study aimed to understand how soil moisture patterns were influenced by tundra microtopography. To accomplish this, we placed a strategic network of soil moisture sensors in micro-highs, micro-lows, and control areas under different vegetation types within the Teller 27 watershed from summer of 2022 through fall of 2023. This data was used in conjunction with other soil data from the Teller 27 watershed to gain a more comprehensive understanding of soil moisture patterns in a rapidly thawing discontinuous permafrost region. This dataset includes six *.csv files: four of time series soil moisture data, one of field soil moisture data, and one of site conditions. The dataset also includes one *.kml file of the watershed and the soil moisture sensor sites as well as this user guide to provide details on data collection and processing methods. NGEE Arctic Project Summary The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

The impact of temperature, chlorides and sulfate-reducing bacteria on the corrosion of steel in soil

Here, this investigation aimed to study the corrosion performance of low-carbon steel in a soil environment at different temperatures. The steel specimens in the soil were treated at three temperatures: 5, 25 and 60°C. The specimens were embedded in chloride-free soil for 21 days, and then 3.5% (by weight) sodium chloride (NaCl) was added to the soil. The specimens were then kept in the chloride-contaminated soil for 54 days. The results of electrochemical experiments showed superior corrosion performance of the specimens at 60°C, which had the lowest corrosion activity, followed by the specimens at 5 and 25°C. The slow nature of the kinetics of the corrosion reactions at 5°C compared with that at ambient temperature was the reason for this improvement at 5°C. The lower number of microorganisms, including sulfate-reducing bacteria, in the soil at 60°C compared with that at the other temperatures was attributed to the lower corrosion activity of steel in the soil at 60°C compared with the corrosion activity of steel in the soil at other temperatures.

99 - GENERAL AND MISCELLANEOUS↗

Fundamental Studies of Soiling and Cementation of PV Cover Glass Materials: Addressing Reliability with Advanced X-ray Scattering/Spectroscopy and First Principles Modeling (Final Technical Report)

Accumulation of soils and other particulate matter on the front cover glass of solar photovoltaic (PV) modules results in transmission losses that detrimentally affect the power output of PV installations. The conventional solution to this problem is manual abrasive scrubbing of modules, which entails significant water usage and manpower. To further combat this issue, there is a concerted effort within the PV industry to develop anti-soiling (AS) coatings to mitigate power losses due to soiling of PV modules, which can exceed 35% in some cases. However, relatively little is known about the fundamental physical and chemical mechanisms that enable anti-soiling behavior. In this project, a combination of advanced X-ray analysis tools and first principles computational modeling has employed to understand the physical and chemical interactions between environmental soils and PV cover glass materials. The specific objectives were: 1) investigate soiling interactions and cementation behavior of relevant PV materials, including bare glass, conventional antireflective (AR) coatings, and a commercial AS coating, using a library of representative particulate soils, and 2) utilize first principles computational spectroscopy modeling to interpret the experimental X-ray spectroscopy measurements and determine the detailed surface chemistry changes that occur on these surfaces in the presence of soiling and cementation.

14 SOLAR ENERGY↗

Effects of Revegetation on Soil Physical and Chemical Properties in Solar Photovoltaic Infrastructure

Solar photovoltaic (PV) technology is being deployed at an unprecedented rate. However, utility-scale solar energy development is land intensive and its large-scale installation can have negative impacts on the environment. In particular, solar energy infrastructure can require extensive landscape modification that transforms soil ecological functions, thereby impacting hydrologic, vegetative, and carbon dynamics. However, reintroducing native vegetation to solar PV sites may be a means of restoring their soils. To this end, we investigated critical soil physical and chemical parameters at a revegetated photovoltaic array and an adjacent reference grassland in Colorado, United States. Seven years after revegetation, we found that carbon and nitrogen remained lower in the PV soil than in the reference soil and contained a greater fraction of coarse particles. We also found that the PV modules introduced heterogeneity in the soil moisture distribution, with precipitation accumulating along the lower edges of panels. The redistribution of soil moisture by panel arrays could potentially be used in concert with planting strategies to maximize plant growth or minimize soil erosion, and should be considered when evaluating the potential to co-locate vegetation with solar infrastructure.

14 SOLAR ENERGY↗

Fungal Community, Not Substrate Quality, Drives Soil Microbial Function in Northeastern U.S. Temperate Forests

Mycorrhizal fungi can affect soil organic matter cycling through several mechanisms including priming, nutrient competition, and direct enzyme production. Differences in nutrient foraging strategies between ectomycorrhizal (EcM) and arbuscular mycorrhizal (AM) fungi produce divergent belowground dynamics: where EcM can take up organic nitrogen and directly break down soil organic matter (SOM) by producing enzymes, AM fungi are limited to scavenging mineral N. EcM-associated tree species also have leaf litter with relatively higher ratios of carbon to nitrogen (C:N), and belowground saprotrophic communities more dominated by fungi. Consequently, free-living microbes in EcM-dominated soils should experience nitrogen limitation, with subsequent increases in enzyme production and decreased carbon use efficiency (CUE). However, the relative importance of the effects of substrate quality and fungal community composition on enzyme production and CUE are unclear. To assess this distinction, we sampled the organic horizon and 10 cm of the mineral horizon in northern temperate forest soils along a gradient of EcM dominance. We characterized fungal community composition by measuring EcM relative abundances from extracted fungal DNA and the fungal to bacterial (F:B) ratios from phospholipid fatty acid (PLFA) analysis. We assessed soil substrate quality as the soil C:N ratio. Soil microbial functions were measured as potential activities of five hydrolytic and two oxidative enzymes, and microbial CUE. We found that the fungal community, represented by either the F:B ratio, EcM relative abundance, or both, affected CUE and six measured enzyme activities, while the C:N ratio affected only oxidative and chitin-targeting extracellular enzyme activities. Our results highlight the use of EcM relative dominance as a predictor of soil microbial community composition and function independent of substrate quality.

54 ENVIRONMENTAL SCIENCES↗

Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

Soil Moisture↗

A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth's surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1-2 GHz). Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm) observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am) equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM), and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm) and descending (01:30 am) paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for the radiative transfer was varied by imposing a bias on an existing regression. These scenarios were evaluated through the Rvalue technique, resulting in optimal bias values on top of this regression. In a next step, these optimal bias values were incorporated in order to re-calibrate the existing linear regression, resulting in a quasi-global uniform LST relation for day-time observations. In a final step, day-time soil moisture retrievals using the re-calibrated land surface temperature relation were again validated through the Rvalue technique. Results indicate an average increasing Rvalue of 16.5%, which indicates a better performance obtained through the re-calibration. This number was confirmed through an independent Triple Collocation verification over the same domain, demonstrating an average root mean square error reduction of 15.3%. Furthermore, a comparison against an extensive in situ database (679 stations) also indicates a generally higher quality for the re-calibrated dataset. Besides the improved day-time dataset, this study furthermore provides insights on the relative quality of soil moisture retrieved from AMSR-E's day- and night-time observations.

soil moisture↗

Development and Validation of The SMAP Enhanced Passive Soil Moisture Product

Since the beginning of its routine science operation in March 2015, the NASA SMAP observatory has been returning interference-mitigated brightness temperature observations at L-band (1.41 GHz) frequency from space. The resulting data enable frequent global mapping of soil moisture with a retrieval uncertainty below 0.040 cu m/cu m at a 36 km spatial scale. This paper describes the development and validation of an enhanced version of the current standard soil moisture product. Compared with the standard product that is posted on a 36 km grid, the new enhanced product is posted on a 9 km grid. Derived from the same time-ordered brightness temperature observations that feed the current standard passive soil moisture product, the enhanced passive soil moisture product leverages on the Backus-Gilbert optimal interpolation technique that more fully utilizes the additional information from the original radiometer observations to achieve global mapping of soil moisture with enhanced clarity. The resulting enhanced soil moisture product was assessed using long-term in situ soil moisture observations from core validation sites located in diverse biomes and was found to exhibit an average retrieval uncertainty below 0.040 cu m/cu m. As of December 2016, the enhanced soil moisture product has been made available to the public from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center.

SMAP Enhanced↗

Assessment of Version 4 of the SMAP Passive Soil Moisture Standard Product

NASAs Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2-3 days. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAPs radiometer-derived standard soil moisture product (L2SMP) provides soil moisture estimates posted on a 36-km fixed Earth grid using brightness temperature observations and ancillary data. A beta quality version of L2SMP was released to the public in October, 2015, Version 3 validated L2SMP soil moisture data were released in May, 2016, and Version 4 L2SMP data were released in December, 2016. Version 4 data are processed using the same soil moisture retrieval algorithms as previous versions, but now include retrieved soil moisture from both the 6 am descending orbits and the 6 pm ascending orbits. Validation of 19 months of the standard L2SMP product was done for both AM and PM retrievals using in situ measurements from global core calval sites. Accuracy of the soil moisture retrievals averaged over the core sites showed that SMAP accuracy requirements are being met.

SMAP↗

The Contributions of Gauge-Based Precipitation and SMAP Brightness Temperature Observations to the Skill of the SMAP Level-4 Soil Moisture Product

Soil Moisture Active Passive (SMAP) mission L-band brightness temperature (Tb) observations are routinely assimilated into the Catchment land surface model to generate Level-4 Soil Moisture (L4_SM) estimates of global surface and root-zone soil moisture at 9-km, 3-hourly resolution with ~2.5-day latency. The Catchment model in the L4_SM algorithm is driven with ¼-degree, hourly surface meteorological forcing data from the Goddard Earth Observing System (GEOS). Outside of Africa and the high latitudes, GEOS precipitation is corrected using Climate Prediction Center Unified (CPCU) gauge-based, ½-degree, daily precipitation. L4_SM soil moisture was previously shown to improve over land model-only estimates that use CPCU precipitation but no Tb assimilation (CPCU_SIM). Here, we additionally examine the skill of model-only (CTRL) and Tb assimilation-only (SMAP_DA) estimates derived without CPCU precipitation. Soil moisture is assessed versus in situ measurements in well-instrumented regions and globally through the Instrumental Variable (IV) method using independent soil moisture retrievals from the Advanced Scatterometer. At the in situ locations, SMAP_DA and CPCU_SIM have comparable soil moisture skill improvements relative to CTRL for the unbiased root-mean-square error (surface and root-zone) and correlation metrics (root-zone only). In the global average, SMAP Tb assimilation increases the surface soil moisture anomaly correlation by 0.10-0.11 compared to an increase of 0.02-0.03 from the CPCU-based precipitation corrections. The contrast is particularly strong in central Australia, where CPCU is known to have errors and observation-minus-forecast Tb residuals are larger when CPCU precipitation is used. Validation versus streamflow measurements in the contiguous U.S. reveals that CPCU precipitation provides most of the skill gained in L4_SM runoff estimates over CTRL.

SMAP↗

X-ray Amorphous Materials in Soils from the Antarctica Dry Valleys: Insights into Aqueous Alteration Processes on Mars

The CheMin XRD instrument onboard the Curiosity rover has discovered abundant quantities of X-ray amorphous materials (25-40 wt. %) in windblown deposits and sedimentary rocks on Mars. The large amounts of X-ray amorphous materials on Mars is surprising because these materials are usually not found in large abundances in terrestrial soils. We have previously identified short-range ordered or X-ray amorphous materials in Antarctica Dry Valleys (ADV) soils. The ADV are one of the driest and coldest environments on Earth and provide an ideal process analog environment for Mars. The objective of this study was to further characterize the chemistry and mineralogy of ADV soils, specifically to quantify and characterize the X-ray amorphous materials. Two soils were characterized from different elevations in the ADV - a low elevation, coastal, subxerous soil in Taylor Valley and a high elevation, ultraxerous soil in University Valley. Rietveld analysis of XRD patterns generated with a CheMin-like analog instrument indicated up to 40 and 15 wt. % X-ray amorphous materials in the Taylor and University Valley soils, respectively. The high abundance of X-ray amorphous materials in Taylor Valley is surprising for one of the driest places on Earth. These materials may have been physically and chemical altered during soil formation, however, the limited interaction with water and low temperatures may have resulted in the formation of “immature” X-ray amorphous or SRO materials. Perhaps, a similar process contributes to the formation of the high content of X-ray amorphous materials detected on Mars.

Antarctica↗

Gatlinburg & Beatty Wildfires: Evaluating the Role of Soil Moisture in Determining Vegetation Health, Fuel Loads, and Wildfires in the Gatlinburg and Beatty Wildfires

Wildfire potential monitoring, which is increasingly vital under climate change-induced droughts, could be improved by incorporating remotely-sensed soil moisture data. To better understand the connections between soil moisture and vegetation health, stakeholders are interested in using soil moisture data in the development of fire-related indices. NASA DEVELOP partnered with the Desert Research Institute’s Western Regional Climate Center (WRCC), NOAA’s National Integrated Drought Information System (NIDIS), the North Carolina State Climate Office, and Oklahoma State University to evaluate how measures of remotely-sensed standardized soil moisture compare to vegetation health and fire fuel indices in a case study of two fire events: the 2016 Chimney Tops 2 Fire near Gatlinburg, Tennessee and the 2021 Bootleg Fire near Beatty, Oregon. The team visualized vegetation change six months prior to each event using spectral vegetation indices observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Terra satellite and the Keetch-Byram Drought Index (KBDI). These visualizations were compared to soil moisture data from European Space Agency's (ESA) Climate Change Initiative Soil Moisture (CCI SM) project, collected in part by the Soil Moisture Active Passive (SMAP) satellite. Overall, period of record percentiles and fraction of available water standardizations correlated more strongly with fuel load and vegetation indices, indicating their utility for fire potential monitoring. Soil moisture conditions remained exceptionally dry for several months before the Chimney Tops 2 Fire whereas drought conditions only intensified immediately prior to the Bootleg Fire. This indicates greater sensitivity to drought conditions under Western fire regimes. These findings will inform partners’ monitoring of wildfire potential in both regions and development of early warning systems.

soil moisture↗