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NASA NTRS1972

Possible production mechanisms of lunar magnetic fields.

Demonstration of the impossibility of the production of local surface magnetic fields on the moon by conduction currents in the lunar soil and in local lunar atmospheres by volcanic eruption. However, it is suggested that convection currents produced by the ionization (by radiation and/or by triboelectric effects) of volcanic-ash-particle flows may produce the local magnetic fields of about 1000 gamma that are believed to have existed on the moon about 3.5 x 10 to the 9th years ago. A simple electrogasdynamic model for such flows and experiments for further investigation of this hypothesis are discussed.

Cap, F. F.↗

DOE OSTI2014

Economic and Environmental Assessment of Switchgrass Production on High-Fertility Soil and an Assessment of Anaerobic Digests as an Intermediate Market for Switchgrass

This project had two parts. Part 1 was an economic and environmental assessment of switchgrass production on high-fertility soil, and included an assessment of the effects of field irrigation with treated municipal wastewater (Studies A,C, and E in Final Agreement). Part 2 was an assessment of methods to enhance anaerobic digestion of switchgrass, and included evaluation of several other potential biomass feedstocks (Studies B and D in Final Agreement). Results from Part 1 demonstrated that switchgrass does not compete economically against a corn and soybean rotation on highly productive soils. All four varieties of switchgrass lost money while corn and soybeans were profitable in all four years of this study. Breakeven prices for the four switchgrass varieties were calculated using production costs. The installation of a center pivot irrigation system had minimal impact on crop production and corn and soybean production remained profitable in the year the irrigator was installed. Because of drought and delays in installing the wastewater treatment plant, the irrigation system was not used until year 4 of this study. Therefore, longer term studies evaluating multiple year studies on the impact of irrigation on switchgrass are warranted. Results from irrigating with treated municipal wastewater showed no negative impact on soil quality. Results from Part 2 demonstrated that anaerobic digestion (AD) of switchgrass could be significantly enhanced using low heat (100oC) and mild caustic pretreatment without fine-grinding. Heat for pretreatment could be available from biogas-based combined heat and power (CHP) systems. In bench-top digesters simulating municipal wastewater treatment AD, methane production of coarse-ground switchgrass increased over 20-fold with pretreatment compared to untreated switchgrass. Bench-top studies simulating dairy-based AD also found high specific methane yield, but even untreated switchgrass digested reasonably well, indicating the value of AD micro-organisms acclimated to lignocellulosic feedstock. Similar results were found for corn stover. However, oak and maple leaves – representing common urban yard waste – were more resistant to digestion even with pretreatment. More pretreatment research is required before yard waste could become a significant feedstock for the low/medium-solids digesters common to municipal wastewater or livestock operations.

09 BIOMASS FUELS↗

NASA NTRSDate not supplied

Evaluating the Impact of Agricultural Soil NOx Emissions on Air Quality Using Advanced Satellite, Ground-based, and Model Data

Soil moisture can also influence the concentration of atmospheric trace gases by moderating the emission of nitrogen oxides (NOx = NO + NO2) from agricultural fields. Human activities can play an important role in controlling the available soil moisture depending on irrigation demand and agricultural management. To further complicate matters, nitrogen fertilizer use has also been found to be a significant source of NOx emissions in agricultural areas. In fact, some of the highest emissions have been reported from fertilized soils in high-temperature agricultural regions, such as the Imperial Valley of California. Since NO2 is an important precursor to ozone formation in the troposphere, which is a leading cause of premature death in humans, it is critical to understand how natural and anthropogenic factors contribute to NOx emissions in these areas. O3 pollution is also a growing threat to global food security due to its detrimental impacts on crop production. This work uses a suite of satellite, ground-based, and model data to investigate how agricultural soil NOx emissions from natural (rainfall) and anthropogenic factors (irrigation, nitrogen fertilizer) govern air quality over California. We evaluate the capabilities of using SMAP retrievals and SMAP Land Information System (LIS) output for monitoring irrigation activities over the major agricultural areas of California by conducting intensive analyses of soil moisture and precipitation data. High-resolution trace gas observations from the new generation TROPOspheric Monitoring Instrument (TROPOMI) sensor are used to characterize and monitor the variability of trace gases and air quality conditions associated with soil NOx emissions. We also synthesize satellite, ground-based, and agriculture data to estimate the separate contributions from rainfall, irrigation, and nitrogen fertilizer practices on soil NOx emissions and associated air quality conditions. Finally, unprecedented hourly trace gas retrievals from the NASA Tropospheric Emissions: Monitoring of Pollution (TEMPO) geostationary satellite sensor are used to monitor the diurnal evolution of NO2 and O3 concentrations from soil NOx emissions.

Aaron R Naeger↗

DOE OSTI2017

Impact of Water Use by Utility-Scale Solar on Groundwater Resources of the Chuckwalla Basin, CA: Final Modeling Report

The DOE and BLM identified 285,000 acres of desert land in the Chuckwalla valley in the western U.S., for solar energy development. In addition to several approved solar projects, a pumped storage project was recently proposed to pump nearly 8000 acre-ft-yr of groundwater to store and stabilize solar energy output. This study aims at providing estimates of the amount of naturally-occurring recharge, and to estimate the impact of the pumping on the water table. To better provide the locations and intensity of natural recharge, this study employs an integrated, physically-based hydrologic model, PAWS+CLM, to calculate recharge. Then, the simulated recharge is used in a parameter estimation package to calibrate spatially-distributed K field. This design is to incorporate all available observational data, including soil moisture monitoring stations, groundwater head, and estimates of groundwater conductivity, to constrain the modeling. To address the uncertainty of the soil parameters, an ensemble of simulations are conducted, and the resulting recharges are either rejected or accepted based on calibrated groundwater head and local variation of the K field. The results indicate that the natural total inflow to the study domain is between 7107 and 12,772 afy. During the initial-fill phase of pumped storage project, the total outflow exceeds the upper bound estimate of the inflow. If the initial-fill is annualized to 20 years, the average pumping is more than the lower bound of inflows. The results indicate after adding the pumped storage project, the system will nearing, if not exceeding, its maximum renewable pumping capacity. The accepted recharges lead to a drawdown range of 24 to 45 ft for an assumed specific yield of 0.05. However, the drawdown is sensitive to this parameter, whereas there is insufficient data to adequately constrain this parameter.

14 SOLAR ENERGY↗

DOE OSTI2015

The hysteresis response of soil CO 2 concentration and soil respiration to soil temperature

Diurnal hysteresis between soil temperature (T s ) and both CO 2 concentration ([CO 2 ]) and soil respiration rate (R s ) were reported across different field experiments. However, the causes of these hysteresis patterns remain a subject of debate, with biotic and abiotic factors both invoked as explanations. Here, to address these issues, a CO 2 gas transport model is developed by combining a layer-wise mass conservation equation for subsurface gas phase CO 2 , Fickian diffusion for gas transfer, and a CO 2 source term that depends on soil temperature, moisture, and photosynthetic rate. Using this model, a hierarchy of numerical experiments were employed to disentangle the causes of the hysteretic [CO 2 ]-T s and CO 2 flux T s (i.e., F-T s ) relations. Model results show that gas transport alone can introduce both [CO 2 ]-T s and F-T s hystereses and also confirm prior findings that heat flow in soils lead to [CO 2 ] and F being out of phase with T s , thereby providing another reason for the occurrence of both hystereses. The area (A hys ) of the [CO 2 ]-T s hysteresis near the surface increases, while the A hys of the Rs-Ts hysteresis decreases as soils become wetter. Moreover, a time-lagged carbon input from photosynthesis deformed the [CO 2 ]-T s and R s -T s patterns, causing a change in the loop direction from counterclockwise to clockwise with decreasing time lag. An asymmetric 8-shaped pattern emerged as the transition state between the two loop directions. Lastly, tracing the pattern and direction of the hysteretic [CO 2 ]-T s and R s -T s relations can provide new ways to fingerprint the effects of photosynthesis stimulation on soil microbial activity and detect time lags between rhizospheric respiration and photosynthesis.

58 GEOSCIENCES↗

NASA NTRS2017

The Sensitivity of Ground-Reflected GNSS Signals to Near-Surface Soil Moisture, as Recorded by Spaceborne Receivers

Spatial and temporal variations in near-surface soil moisture are important to measure for climate studies, numerical weather forecasts, and drought monitoring. Several previous studies have shown success in using ground-reflected Global Navigation Satellite System (GNSS) signals as a form of bistatic radar to sense soil moisture. However, the ability of this type of data to sense soil moisture variations from space is still a nascent field of study. In the past two years, three satellites have been launched that were either designed to capture ground-reflected GNSS signals or have been modified to record these signals. The data provided by these satellites are giving scientists an unprecedented opportunity to investigate their ability to detect changes in Earth’s land surface, including but certainly not limited to near-surface soil moisture. This paper will present spaceborne observations of ground-reflected GNSS signals and evaluate their sensitivity to near-surface soil moisture. This sensitivity will be compared to empirical and theoretical sensitivities of monostatic L-band radar measurements to soil moisture. We will also comment on possibilities for retrieval algorithm development, using techniques employed for monostatic radar as a guide.

Chew, C.↗

DOE OSTI2020

High Throughput Argon-37 Field System

We report Pacific Northwest National Laboratory (PNNL) has developed a unique fieldable 37 Ar measurement system designed to measure 37 Ar activity concentrations from soil gas samples to detect above ground and underground nuclear explosions. The Argon-37 Field System is modular in design to accommodate both chemical processing and nuclear detection. The system can be packed into shipping crates and shipped to a location near where the sampling is taking place. The system can process six 2-m 3 whole-air samples in 24 hours and can measure the 37 Ar activity in each of the samples using six proportional counters. The proportional counters, designed and built at PNNL, are surrounded with both active and passive shielding to reduce background and can achieve a minimum detection concentration of 10 mBq/m 3 of 37 Ar in whole-air equivalent. The Argon-37 Field System has undergone extensive testing against rigorous requirements to assure the system meets the needs of the noble gas nuclear explosion monitoring community.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2024

Data for Microbial-Explicit Processes and Refined Perennial Plant Traits Improve Modeled Ecosystem Carbon Dynamics

Globally, soils hold approximately half of ecosystem carbon and can serve as a source or sink depending on climate, vegetation, management, and disturbance regimes. Understanding how soil carbon dynamics are influenced by these factors is essential to evaluate proposed natural climate solutions and policy regarding net ecosystem carbon balance. Soil microbes play a key role in both carbon fluxes and stabilization. However, biogeochemical models often do not specifically address microbial-explicit processes. Here, we incorporated microbial-explicit processes into the DayCent biogeochemical model to better represent large perennial grasses and mechanisms of soil carbon formation and stabilization. We also take advantage of recent model improvements to better represent perennial grass structural complexity and life-history traits. Specifically, this study focuses on: 1) a plant sub-model that represents perennial phenology and more refined plant chemistry with downstream implications for soil organic matter (SOM) cycling though litter inputs, 2) live and dead soil microbe pools that influence routing of carbon to physically protected and unprotected pools, 3) Michaelis-Menten kinetics rather than first-order kinetics in the soil decomposition calculations, and 4) feedbacks between decomposition and live microbial pools. We evaluated the performance of the plant sub-model and two SOM cycling sub-models, Michaelis-Menten (MM) and first-order (FO), using observations of net ecosystem production, ecosystem respiration, soil respiration, microbial biomass, and soil carbon from long-term bioenergy research plots in the mid-western United States. The MM sub-model represented seasonal dynamics of soil carbon fluxes better than the FO sub-model which consistently overestimated winter soil respiration. While both SOM sub-models were similarly calibrated to total, physically protected, and physically unprotected soil carbon measurements, the models differed in future soil carbon response to disturbance and climate, most notably in the protected pools. Adding microbial-explicit mechanisms of soil processes to ecosystem models will improve model predictions of ecosystem carbon balances but more data and research are necessary to validate disturbance and climate change responses and soil pool allocation.

Field Data↗

NASA NTRS1981

The DMSP imager (SSMI): Unfinished plans

The basic theory relating microwave emissivity to soil and snow moisture is presented along with data from field and aircraft measurements to support the theory. Data from the ESMR on Nimbus-5 and the S-194 L Band radiometer on Skylab were compared with Antecedent Precipitation indices (APT) to show the sensitivity of spaceborne observations to soil moisture. Similarly, data from the ESMR and SMMR on the Nimbus spacecraft were compared with surface measurements of snow depth with good results.

Savage, R. C.↗

NASA NTRS1974

The effects of the physical and chemical properties of soils on the spectral reflectance of soils

The effects of organic matter, free iron oxides, texture, moisture content, and cation exchange capacity on the spectral reflectance of soils were investigated along with techniques for differentiating soil orders by computer analysis of multispectral data. By collecting soil samples of benchmark soils from the different climatic regions within the United States and using the extended wavelength field spectroradiometer to obtain reflectance values and curves for each sample, average curves were constructed for each soil order. Results indicate that multispectral analysis may be a valuable tool for delineating and quantifying differences between soils.

Montgomery, O. L.↗

DOE OSTI2018

Phosphorus transformation response to soil properties changes induced by manure application in a calcareous soil

Management of phosphorus (P) loss in soils with heavy manure application requires improved understanding of the transformation characteristics of soil P. Influences of manure application on the forms and sorption-desorption characteristics of P in surface (0–30 cm) and subsurface (30–60 cm) layer of a calcareous soil were investigated in this paper in a six-year field trial in comparison to chemical fertilizer application. Hedley fractionation and P K-edge X-ray absorption near-edge structure spectroscopy were used to determine the soil P forms. Manure (M) and chemical fertilizer (F) treatments resulted in P accumulation in two soil depths, but the total P accumulation in surface soil with M treatment was significantly lower than F treatment with similar P surplus. Compared to control, M and F treatments were significantly increased the proportion of labile P at both depths. In surface soil, M treatment significantly decreased stable Ca-associated P proportion and increased Fe-associated P and inositol hexakisphosphate proportions. The accumulation and transformation of P in M treatment distinctly decreased P sorption maximun, sorption coefficient and buffer capacity, and increased the degree of P saturation and P desorption relative to F treatment. The soil properties of pH, organic carbon (OC), total nitrogen (TN), Mehlich-3 extractable Ca and Fe, and phytase in surface soil and pH, OC, TN, Mehlich-3 extractable Ca and dehydrogenase in subsurface soil had significant effects on the compositions of soil P (P < 0.05), respectively. Finally, lowered pH due to manure application mainly contributed to P transformation and release in the calcareous soil.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1997

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quasi-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well-managed watershed in southwest Oklahoma. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗

NASA NTRS1997

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well- managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗

DOE OSTI2021

A modular methodology for time-domain stochastic seismic wave propagation

Presented here is a modular methodology for time-domain stochastic seismic wave propagation analysis. Presented methodology is designed to analyse uncertain seismic motions as an input, propagating through uncertain material. Traditional approach for uncertain wave propagation relies on models that include deep bedrock, local soil site, and their random process and random field information. Such models can become quite large and computationally intractable. The modular approach proposed herein features two step approach that allows separate consideration of the deep bedrock and local site along with corresponding random field information. In this work, the first step considers an auxiliary stochastic motions problem in the bedrock. Stochastic local site response can then be simulated in a reduced domain within certain depth from the surface. Application of uncertain seismic motions at depth, for local uncertain site response is done using stochastic effective forces developed through the Domain Reduction Method. By using Hermite polynomial chaos expansion to represent the non-Gaussian random field of material parameters and non-stationary random process of seismic motion, the proposed modular methodology is formulated using intrusive stochastic Galerkin approach, as seen in the Stochastic Elastic–Plastic Finite Element Method (SEPFEM). Developed modular methodology is illustrated using a 1-D stochastic seismic wave propagation analysis with three cases, and simulation results are also verified with results from conventional approach.

58 GEOSCIENCES↗

DOE OSTI2020

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term experiments

Climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (<10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Crop diversification improves water-use efficiency and regional water sustainability

As global water scarcity intensifies, identifying agricultural practices that enhance sustainable water management is critical. Temporal crop diversification-rotating multiple species over time-has been proposed to improve soil health and water retention based on field-scale experiments. However, widespread adoption remains limited on farms, in part due to unverified benefits at larger scales. Here, we assess the influence of crop diversification on agricultural water-use efficiency (WUE, ratio of gross primary productivity to evapotranspiration) along a spectrum of monoculture to complex species rotations in California. Leveraging new high-resolution remote sensing datasets, we show that crop diversification is a key driver of agricultural WUE, and increasing the number of species planted in the previous 6 years from two to four increases WUE by ∼20% after accounting for differences between crops. Our results provide spatially explicit, large-scale quantification of crop diversification’s improvements to WUE, with direct implications for climate adaptation. More broadly, our framework offers a tool to evaluate other sustainable practices and guide policy and farm-scale decision-making.

climate-resilient agriculture↗

DOE OSTI2011

EDITORIAL HPJ SPECIAL ISSUE INTRODUCTION

Radioecology is the study of the fate and transport and potential effects of radionuclides and associated contaminants in the environment. In short, it is the science that describes the fundamental connection between environmental health and human health risks. As such, radioecology can and has provided the credible, consistent and defensible basis for the successful and cost-effective environmental cleanup and closure of nuclear production and waste sites. In addition, radioecology also provides the technical basis for making timely and reliable decisions on cleanup in the aftermath of nuclear incidents such as Chernobyl and Fukushima. The 1986 Chernobyl Nuclear Power Plant (ChNPP) accident resulted in catastrophic health, social, and economic consequences in many countries, predominantly, Ukraine, Belarus, and Russia. The extent of radioactive contamination, levels and forms of contamination, and diversity of the ecosystems affected by the accident did not have any precedent and provided unique opportunities for environmental scientists around the world. Following the natural course of their development, populations of species and their communities found themselves in conditions of chronic radiation exposure that exceeded the natural background by factors of hundreds and thousands. Anything similar would have been extremely difficult if not impossible to recreate in a scientific laboratory. Consequently, since the first few years after the accident, many teams of scientists have visited the Chernobyl Exclusion Zone (ChEZ). The knowledge gained by studying the consequences of this accident has tremendous importance. The concept of an international research and technical center to address the problems involving nuclear and radiological accidents became a reality with the establishment of the International Chernobyl Center (ICC). In May 1995, the US and Ukraine signed a Protocol of Intent on establishment of the ICC, and the government of Ukraine appealed to the international scientific community to support ICC and join its activities (Chernobyl Center 2006). In December 1995, a memorandum of understanding (MOU) on the ChNPP closure was signed by the government of Ukraine, all of the G7 governments, and the European Commission. The ICC foundation was considered critical to ensure the safe decommissioning of the ChNPP reactor units and improvement of the safety of the Chernobyl Containment Shelter. On the 10th anniversary of the Chernobyl accident (26 April 1996), Mr. Viktor Yushchenko, the President of Ukraine, issued a decree to establish the Chernobyl Center for Nuclear Safety, Radioactive Waste and Radioecology (Chernobyl Center). On the same day, a MOU involving the US participation in Chernobyl Center activities was signed by the US and Ukraine (Chernobyl Center 2006). In July 1998, the US and Ukraine signed an agreement to establish the International Radioecology Laboratory (IRL) as part of the Chernobyl Center. The creation of IRL was a logical continuation of previous programs to conduct scientific research in radioecology and provide Ukraine and the rest of the world with the necessary infrastructure and scientific basis to conduct research in radioecology, radiobiology, dosimetry, and environmental protection in the ChEZ (Chernobyl Center 2006). A recent collaborative effort with IRL has been implemented through a project titled 'Long-term impacts from radiation/contamination within the Chernobyl Exclusion Zone' (Farfan et al. 2008; Gerdes et al. 2009; Marra et al. 2010). This collaboration had the following objectives: (1) Assess the long-term impacts to the environment from radiation exposure within the ChEZ; (2) Provide information on remediation guidelines and ecological risk assessment within radioactively contaminated territories based on the results of long-term field monitoring, analytical measurements, and numerical modeling of soils and groundwater radioactive contamination; and (3) Recommend the development and testing of effective cleanup technologies to reduce environmental and health risks. Based on this work, a large amount of data are now available for publication, some of which are presented in this Special Issue of the Health Physics Journal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs

This submission aimed to assess differences in short-term step warming manipulations and long-term chronic response to climate change in Alaskan ecosystems. Briefly, climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (< 10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.The model used in the current study is available publicly (https://github.com/jinyun1tang/ECOSYS), and the current submission contains the python/ matlab codes for analyzing output from the model (includng a readme file to explain the codes). The benchmark data, also enclosed, was collected from a range of published and publicly available sources (extracted using GRABIT: https://www.mathworks.com/matlabcentral/fileexchange/7173-grabit). These sources describe warming induced changes in tundra/ boreal ecosystems.

54 ENVIRONMENTAL SCIENCES↗