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At least 163 records · Page 9

Impact of the numerical solution approach of a plant hydrodynamic model (v0.1) on vegetation dynamics

Abstract. Numerous plant hydrodynamic models have started to be implemented in vegetation dynamics models, reflecting the central role of plant hydraulic traits in driving water, energy, and carbon cycles, as well as plant adaptation to climate change. Different numerical approximations of the governing equations of the hydrodynamic models have been documented, but the numerical accuracy of these models and its subsequent effects on the simulated vegetation function and dynamics have rarely been evaluated. Using different numerical solution methods (including implicit and explicit approaches) and vertical discrete grid resolutions, we evaluated the numerical performance of a plant hydrodynamic module in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES-HYDRO version 0.1) based on single-point and global simulations. Our simulation results showed that when near-surface vertical grid spacing is coarsened (grid size >10 cm), the model significantly overestimates aboveground biomass (AGB) in most of the temperate forest locations and underestimates AGB in the boreal forest locations, as compared to a simulation with finer vertical grid spacing. Grid coarsening has a small effect on AGB in the tropical zones of Asia and South America. In particular, coarse surface grid resolution should not be used when there are large and prolonged water content differences among soil layers at depths due to long dry-season duration and/or well-drained soil or when soil evaporation is a dominant fraction of evapotranspiration. Similarly, coarse surface grid resolution should not be used when there is lithologic discontinuity along the soil depth. This information is useful for uncertainty quantification, sensitivity analysis, or the training of surrogate models to design the simulations when computational cost limits the use of ensemble simulations.

54 ENVIRONMENTAL SCIENCES↗

Composition and maturity of the 60013/14 core

The 60013/14 double drive tube (62 cm deep) is one of three regolith cores taken 35-40 m apart in a triangular array on the Cayley plains at station 10' (LM/ALSEP), Apollo 16. This trio, which includes double drive tube 60009/10 (59 cm deep) and deep drill core 60001-7 (220 cm), is the only such array of cores returned from the Moon. The top 45 cm of 60013/14 is mature, as is surface reference soil 60601 taken nearby. Maturity generally decreases with depth, with soil below 45 cm being submature. The zone of lowest maturity (34 is less than or equal to I(sub s)/FeO is less than 50) extends from 46 to 58 cm depth, and corresponds to the distinct region of light-colored soil observed during core processing. In the other two cores, most of the compositional variation results from mixing between fine-grained, mature soil with 10-11 micro-g/g Sc and coarse-grained ferroan anorthosite consisting of greater than 99% plagioclase with less than 0.5 micro-g/g Sc. This is most evident in 60009/10 which contains a high abundance of plagioclase at about 54 cm depth (minimum Sc: 3-4 micro-g/g); a similar zone occurs in 60001-7 at 17-22 cm (MPU-C), although it is not as rich in plagioclase (minimum Sc: 6-7 micro-g/g). Compositional variations are less in 60013/14 than in the other two cores (range: 7.9-10.0 micro-g/g Sc), but are generally consistent with the 'plagioclase dilution' effect seen in 60009/10, i.e., most 60013/14 samples plot along the mixing line of 60009/10. However, a plagioclase component is not the cause of the lower maturity and lighter color of the unit at 46-58 cm depth in 60013/14. Many of the samples in this zone have distinctly lower Sm/Sc ratios than typical LM-area soils and plot off the mixing trend defined by 60009/10. This requires a component with moderately high Sc, but low-Sm/Sc, such as feldspathic fragmental breccia (FFB) or granulitic breccia. A component of Descartes regolith, such as occurs at North Ray Crater (NRC) and which is rich in FFB, could account for the composition of these soils (i.e., a 3:1 mixture of 60601 and NRC soil). It seems unlikely that NRC ejecta would occur half a meter deep at the LM station, thus this low-Sm/Sc component may result from an older, local crater that penetrated the Cayley surface layer and excavated underlying Descartes material, as did North Ray Crater. There is no evidence for such a unit or component in the other two cores. Soil below the light-colored unit (58-62) cm has 'typical' Sm/Sc ratios, but the lowest absolute Sc concentrations, i.e., it is compositionally equivalent to a mixture of surface soil and plagioclase such as that in ferroan anorthosite. This is the only soil that might be related to the plagioclase-rich units in the other two cores. Except for the mature soil at the top of each core and, perhaps, the plagioclase-rich layers, there is little compositional evidence for any common unit among the three cores. Soil corresponding to the mare-glass-bearing unit (MPU-B) and regolith-breccia-bearing unit (MPU-A) of 60001-7 do not occur in 60013/14 or 60009/10.

Korotev, Randy L.↗

Bacterial Secondary Metabolite Biosynthetic Potential in Soil Varies with Phylum, Depth, and Vegetation Type

Microbes produce specialized compounds to compete or communicate with one another and their environment. Some of these compounds, such as antibiotics, are also useful in medicine and biotechnology. Historically, most antibiotics have come from soil bacteria which can be isolated and grown in the lab. Though the vast majority of soil bacteria cannot be isolated, we can extract their genetic information and search it for genes which produce these specialized compounds. These understudied soil bacteria offer a wealth of potential for the discovery of new and important microbial products. Here, we identified the ability to produce these specialized compounds in diverse and novel bacteria in a range of soil environments. This information will be useful to other researchers who wish to isolate certain products. Beyond their use to humans, understanding the distribution and function of microbial products is key to understanding microbial communities and their effects on biogeochemical cycles.

59 BASIC BIOLOGICAL SCIENCES↗

Enabling depth resolved temporal resolved soil microbial sampling with novel vadose zone diffusion sampler

To address the difficulty in Earth system science in making time-course measurements of molecular signatures in soil biochemistry, we developed a soil stake system to sample and replace a defined soil analog medium, connected through hydraulic connectivity via perforated casings and modular inserts. We deployed these stakes to a site in Prosser, WA and measured microbial colonization of sterile sand-clay inserts enriched with N-acetyl-glucosamine at different depths over spring and summer. DNA and RNA analyses revealed distinct microbial recruitment and activity patterns. Inserts showed lower microbial diversity but higher abundance of Proteobacteriota and Bacteriota compared to native soils, alongside seasonal shifts in taxonomic and functional profiles. The soil stake system offers a novel approach for studying microbial dynamics across temporal and spatial scales.

58 GEOSCIENCES↗

Remotely Sensed Soil Moisture Can Capture Dynamics Relevant to Plant Water Uptake

A frequently expressed viewpoint across the Earth science community is that global soil moisture estimates from satellite L-band (1.4 GHz) measurements represent moisture only in a shallow surface layer (0–5 cm) and consequently are of limited value for studying global terrestrial ecosystems because plants use water from deeper rootzones. Using this argumentation, many observation-based land surface studies avoid satellite-observed soil moisture. Here, based on peer-reviewed literature across several fields, we argue that such a viewpoint is overly limiting for two reasons. First, microwave soil emission depth considerations and statistical considerations of vertically correlated soil moisture information together indicate that L-band measurements carry information about soil moisture extending below the commonly referenced 5 cm in many conditions. However, spatial variations of effective depths of representation remain uncertain. Second, in reviewing isotopic tracer field studies of plant water uptake, we find a prevalence of vegetation that primarily draws moisture from these upper soil layers. This is especially true for grasslands and croplands covering more than a third of global vegetated surfaces. Even some deeper-rooted species (i.e., shrubs and trees) preferentially or seasonally draw water from the upper soil layers. Therefore, L-band satellite soil moisture estimates are more relevant to global vegetation water uptake than commonly appreciated (i.e., relevant beyond only shallow soil processes like soil evaporation). Our commentary encourages the application of satellite soil moisture across a broader range of terrestrial hydrosphere and biosphere studies while urging more rigorous estimates of its effective depth of representation.

Andrew F. Feldman↗

How initial conditions-, structural-, and parameter-based model uncertainty interact and influence predictions in permafrost ecosystems: Modeling Archive

This dataset contains model output and input data, as well as source code examples for the Terrestrial Ecosystem Model with the Dynamic Vegetation Model and Dynamic Organic Soil (DVM-DOS-TEM) for the field sites Imnavait creek and the Bonanza creek Long Term Ecological Research Network (LTER). The data covers simulations from the last glacial maximum (LGM) until 2100 for a selection of paleo scenarios, setting the mean temperature of the LGM up to 10°C lower than pre-industrial conditions. The model structure was modulated to represent various model versions, and this dataset contains the relevant changes in the source code. The raw output data, the processed statistical data, the setup and processing scripts as well as parameter value distribution files from a parameter sensitivity analysis are included as well. Model outputs include active layer depth, organic soil carbon, soil layer depths, gross primary productivity (GPP) with and without nitrogen limitation, net primary productivity (NPP), soil liquid water content, heterotrophic, maintenance, and growth respiration, soil temperature, and vegetation carbon (*.nc files). The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research.Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

54 ENVIRONMENTAL SCIENCES↗

Implementation and Analysis of the Dual-channel Algorithm for the Retrieval of Soil Moisture and Vegetation Optical Depth for SMAP

In August 2020, SMAP released a new version of its soil moisture (SM) and vegetation optical depth (VOD) products. In this work, we review the methodology followed by the SMAP regularized dual-channel (DCA) retrieval algorithm. We show that the new implementation generated SM retrievals that not only satisfy the SMAP accuracy requirements but also show a performance comparable to the single-channel algorithm that uses the V polarized brightness temperature (SCA-V). Due to a lack of in situ measurements we cannot evaluate the accuracy of the VOD, but in this work, we will show analysis with the intention of providing an understanding of the VOD product.

O’Neill, P.↗

Evaluation of HCMM data for assessing soil moisture and water table depth

Data were analyzed for variations in eastern South Dakota. Soil moisture in the 0-4 cm layer could be estimated with 1-mm soil temperatures throughout the growing season of a rainfed barley crop (% cover ranging from 30% to 90%) with an r squared = 0.81. Empirical equations were developed to reduce the effect of canopy cover when radiometrically estimating the 1-mm soil temperature, r squared = 0.88. The corrective equations were applied to an aircraft simulation of HCMM data for a diversity of crop types and land cover conditions to estimate the 0-4 cm soil moisture. The average difference between observed and measured soil moisture was 1.6% of field capacity. HCMM data were used to estimate the soil moisture for four dates with an r squared = 0.55 after correction for crop conditions. Location of shallow alluvial aquifers could be accomplished with HCMM predawn data. After correction of HCMM day data for vegetation differences, equations were developed for predicting water table depths within the aquifer (r=0.8).

Moore, D. G.↗

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series

Abstract. Improving the quantification of soil thermal and physical properties is key to achieving a better understanding and prediction of soil hydro-biogeochemical processes and their responses to changes in atmospheric forcing. Obtaining such information at numerous locations and/or over time with conventional soil sampling is challenging. The increasing availability of low-cost, vertically resolved temperature sensor arrays offers promise for improving the estimation of soil thermal properties from temperature time series, and the possible indirect estimation of physical properties. Still, the reliability and limitations of such an approach need to be assessed. In the present study, we develop a parameter estimation approach based on a combination of thermal modeling, sliding time windows, Bayesian inference, and Markov chain Monte Carlo simulation to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution (i.e., down to 5 to 10 cm vertical resolution) from soil temperature time series. We provide the necessary framework to assess under which environmental conditions (soil temperature gradient, fluctuations, and trend), temperature sensor characteristics (bias and level of noise), and deployment geometries (sensor number and position) soil thermal diffusivity can be reliably inferred. We validate the method with synthetic experiments and field studies. The synthetic experiments show that in the presence of median diurnal fluctuations ≥ 1.5 ∘C at 5 cm below the ground surface, temperature gradients > 2 ∘C m−1, and a sliding time window of at least 4 d the proposed method provides reliable depth-resolved thermal diffusivity estimates with percentage errors ≤ 10 % and posterior relative standard deviations ≤ 5 % up to 1 m depth. Reliable thermal diffusivity under such environmental conditions also requires temperature sensors to be spaced precisely (with accuracy to a few millimeters), with a level of noise ≤ 0.02 ∘C, and with a bias defined by a standard deviation ≤ 0.01 ∘C. Finally, the application of the developed approach to field data indicates significant repeatability in results and similarity with independent measurements, as well as promise in using a sliding time window to estimate temporal changes in soil thermal diffusivity, as needed to potentially capture changes in bulk density or water content.

54 ENVIRONMENTAL SCIENCES↗

Regularized Dual-Channel Algorithm for the Retrieval of Soil Moisture and Vegetation Optical Depth from SMAP Measurements

In August 2020, SMAP released a new version of its soil moisture (SM) and vegetation optical depth (VOD) retrieval products. In this work, we review the methodology followed by the SMAP regularized dual-channel (DCA) retrieval algorithm. We show that the new implementation generates SM retrievals that not only satisfy the SMAP accuracy requirements but also show a performance comparable to the single-channel algorithm that uses the V polarized brightness temperature (SCA-V). Due to a lack of in situ measurements we cannot evaluate the accuracy of the VOD. In this work, we show analyses with the intention of providing an understanding of the VOD product. We compare the VOD results with those from SMOS. We also study the relation of the SMAP VOD with two vegetation parameters: tree height and biomass.

Julian Chaubell↗

Regolith history from cosmic-ray-produced nuclides

A model is given for regolith development by which the meteoroid impact parameters (time of last major impact, soil escape rate, and soil turnover depths) are determined from the Gd isotope data for the Apollo 15 and 16 drill stems. The time of the last major impact, cosmic-ray-produced-nuclide-clock reset time, at the Apollo 15 site is 0.6-1.3 aeon. The reset time at the Apollo 16 site is between 1.54 plus or minus 0.14 and 3.3-4.0 aeon. The average soil escape rate from the moon corresponding to the 1.54 plus or minus 0.14 aeon reset time is between 70 and 110 cm/aeon and corresponding to the 3.3 and 4.0 aeon reset time is between 36 and 56 cm/aeon. The soil turnover depth for the 1.54 plus or minus 0.14 aeon reset time is 250 cm and for the 3.3-4.0 aeon reset time is 750 cm. The Gd data restrict the change with time of the meteoroid flux during the past 1.4 aeon.

Fireman, E. L.↗

The effect of repeated hurricanes on the age of organic carbon in humid tropical forest soil

Abstract Increasing hurricane frequency and intensity with climate change is likely to affect soil organic carbon (C) stocks in tropical forests. We examined the cycling of C between soil pools and with depth at the Luquillo Experimental Forest in Puerto Rico in soils over a 30‐year period that spanned repeated hurricanes. We used a nonlinear matrix model of soil C pools and fluxes (“soilR”) and constrained the parameters with soil and litter survey data. Soil chemistry and stable and radiocarbon isotopes were measured from three soil depths across a topographic gradient in 1988 and 2018. Our results suggest that pulses and subsequent reduction of inputs caused by severe hurricanes in 1989, 1998, and two in 2017 led to faster mean transit times of soil C in 0–10 cm and 35–60 cm depths relative to a modeled control soil with constant inputs over the 30‐year period. Between 1988 and 2018, the occluded C stock increased and δ 13 C in all pools decreased, while changes in particulate and mineral‐associated C were undetectable. The differences between 1988 and 2018 suggest that hurricane disturbance results in a dilution of the occluded light C pool with an influx of young, debris‐deposited C, and possible microbial scavenging of old and young C in the particulate and mineral‐associated pools. These effects led to a younger total soil C pool with faster mean transit times. Our results suggest that the increasing frequency of intense hurricanes will speed up rates of C cycling in tropical forests, making soil C more sensitive to future tropical forest stressors.

14C↗

Representation of Stormflow and a More Responsive Water Table in a TOPMODEL-Based Hydrology Model

This study presents two new modeling strategies. First, a methodology for representing the physical process of stormflow within a TOPMODEL framework is developed. In using this approach, discharge at quickflow time scales is simulated and a fuller depiction of hydrologic activity is brought about. Discharge of water from the vadose zone is permitted in a physically realistic manner without a priori assumption of the level within the soil column at which stormflow saturation can take place. Determination of the stormflow contribution to discharge is made using the equation for groundwater flow. No new parameters are needed. Instead, regions of near saturation that develop during storm events, producing vertical recharge, are allowed to contribute to soil column discharge. These stormflow contributions to river runoff, as for groundwater flow contributions, are a function of catchment topography and local hydraulic conductivity at the depth of these regions of near saturation. The second approach improves groundwater flow response through a reduction of porosity and field capacity with depth in the soil column. Large storm events are better captured and a more dynamic water table develops with application of this modified soil column profile (MSCP). The MSCP predominantly reflects soil depth differences in upland and lowland regions of a watershed. Combined, these two approaches - stormflow and the MSCP - provide a more accurate representation of the time scales at which soil column discharge responds and a more complete depiction of hydrologic activity. Storm events large and small are better simulated, and some of the biases previously evident in TOPMODEL simulations are reduced.

Shaman, Jeffrey↗

Remote sensing of soil moisture by Skylab radiometer and scatterometer sensors

A Skylab experiment was designed to evaluate the feasibility of monitoring the moisture content of the soil from space. Data from various Skylab sensors were collected across two test sites while direct measurements of soil moisture were being made at the surface depths of soil. Correlations were obtained between the moisture content of the soil and radiometer sensors (S193 and S194) and the scatterometer instrument (S193). The high correlations obtained indicate that microwave sensors may be quite useful for such measurements in the future.-

Eagleman, J. R.↗

Remote sensing of soil moisture by Skylab radiometer and scatterometer sensors

A Skylab experiment was designed to evaluate the feasibility of monitoring the moisture content of the soil from space. Data from various Skylab sensors were collected across two test sites while direct measurements of soil moisture were being made at the surface depths of soil. Correlations were obtained between the moisture content of the soil and radiometer sensors (S193 and S194) and the scatterometer instrument (S193). The high correlations obtained indicate that microwave sensors may be quite useful for such measurements in the future.-

Eagleman, J. R.↗

Linking Manganese Fractions and Organic Carbon in Soils of Contrasting Land Use Systems

Manganese (Mn) is an essential micronutrient that influences carbon (C) cycling by binding or oxidizing soil organic matter. Mn fractions in soil and their plant availability depend largely on soil pH, which is commonly altered by agricultural practices. Fractions of Mn in soils range from readily available (e.g., bioavailable Mn, exchangeable Mn) to stabilized (e.g., Mn-oxide minerals, Mn contained in silicates). Furthermore, the distribution of soil Mn with depth was assessed in contrasting land use systems (organic agriculture, conventional agriculture, and unmanaged forest) using a sequential extraction method that targets Mn fractions ranging in bioavailability. Both agricultural sites had similar amounts of total Mn but had available Mn (1–7% of total Mn) lower than that of the unmanaged forested site (15% of total Mn). Manganese and organic C were generally positively correlated, but this relationship depended on soil depth, Mn fractions, and concentrations, while land management change had little influence.

Crops↗

Soil pH Buffering Capacity, Geochemical Characterization, and Soil Water Retention for Arctic Soils of Seward Peninsula and Utqiagvik, Alaska, 2013-2019

This dataset provides pH titration data and soil pH buffering capacities of 21 Arctic soils that were collected between 2013-2019. Geochemical data including soil organic carbon, carbon:nitrogen ratio, initial pH, and gravimetric water content are also reported. Additional measurements of cation exchange capacity and soil water retention (dry range) are presented for selected soils. A script, developed in R, is also included for a simple biogeochemical simulation that incorporates soil pH buffering capacity. This dataset contains 7 csv files and one R script.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↗