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At least 793 records · Page 44

The Arctic-Boreal vulnerability experiment model benchmarking system

NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) integrates field and airborne data into modeling and synthesis activities for understanding Arctic and Boreal ecosystem dynamics. The ABoVE Benchmarking System (ABS) is an operational software package to evaluate terrestrial biosphere models against key indicators of Arctic and Boreal ecosystem dynamics, i.e.: carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance. The ABS utilizes satellite remote sensing data, airborne data, and field data from ABoVE as well as collaborating research networks in the region, e.g.: the Permafrost Carbon Network, the International Soil Carbon Network, the Northern Circumpolar Soil Carbon Database, AmeriFlux sites, the Moderate Resolution Imaging Spectroradiometer, the Orbiting Carbon Observatory 2, and the Soil Moisture Active Passive mission. The ABS is designed to be interactive for researchers interested in having their models accurately represent observations of key Arctic indicators: a user submits model results to the system, the system evaluates the model results against a set of Arctic-Boreal benchmarks outlined in the ABoVE Concise Experiment Plan, and the user then receives a quantitative scoring of model strengths and deficiencies through a web interface. This interactivity allows model developers to iteratively improve their model for the Arctic-Boreal Region by evaluating results from successive model versions. We show here, for illustration, the improvement of the Lund–Potsdam–Jena-Wald Schnee und Landschaft (LPJwsl) version model through the ABoVE ABS as a new permafrost module is coupled to the existing model framework. The ABS will continue to incorporate new benchmarks that address indicators of Arctic-Boreal ecosystem dynamics as they become available.

ABoVE↗

Field Micrometeorological Measurements, Process-Level Studies and Modeling of Methane and Carbon Dioxide Fluxes in a Boreal Wetland Ecosystem

The main instrumentation platform consisted of eddy correlation sensors mounted on a scaffold tower at a height of 4.2 m above the peat surface. The sensors were attached to a boom assembly which could be rotated into the prevailing winds. The boom assembly was mounted on a movable sled which, when extended, allowed sensors to be up to 2 m away from the scaffolding structure to minimize flow distortion. When retracted, the sensors could easily be installed, serviced or rotated. An electronic level with linear actuators allowed the sensors to be remotely levelled once the sled was extended. Two instrument arrays were installed. A primary (fast-response) array consisted of a three-dimensional sonic anemometer, a methane sensor (tunable diode laser spectrometer), a carbon dioxide/water vapor sensor, a fine wire thermocouple and a backup one-dimensional sonic anemometer. The secondary array consisted of a one-dimensional sonic anemometer, a fine wire thermocouple and a Krypton hygrometer. Descriptions of these sensors may be found in other reports (e.g., Verma; Suyker and Verma). Slow-response sensors provided supporting measurements including mean air temperature and humidity, mean horizontal windspeed and direction, incoming and reflected solar radiation, net radiation, incoming and reflected photosynthetically active radiation (PAR), soil heat flux, peat temperature, water-table elevation and precipitation. A data acquisition system (consisting of an IBM compatible microcomputer, amplifiers and a 16 bit analog-to-digital converter), housed in a small trailer, was used to record the fast response signals. These signals were low-pass filtered (using 8-pole Butterworth active filters with a 12.5 Hz cutoff frequency) and sampled at 25 Hz. Slow-response signals were sampled every 5 s using a network of CR21X (Campbell Scientific, Inc., Logan Utah) data loggers installed in the fen. All signals were averaged over 30-minute periods (runs).

Verma, S. B.↗

Models for Facilitating Government-Funded Activities in the Post-ISS LEO Ecosystem

This study helps elucidate NASA’s future options for facilitating government-funded activities in the post-International Space Station (ISS) low-Earth orbit (LEO) ecosystem. NASA is preparing for the retirement of the ISS and transition of LEO activities to one or more Commercial LEO Destinations (CLDs) by 2030. This transition necessitates new models for connecting NASA and other users of the LEO environment to platforms and opportunities. In light of this transition, NASA senior leadership tasked the Office of Technology, Policy, and Strategy (OTPS) with answering two questions: 1) what are potential models for an ISS National Lab facilitating government-funded or subsidized activities on a commercial LEO platform after the transition of the ISS to one or more private platforms, and 2) in light of these options, what modifications would be helpful to make in the current ISSNL-CASIS partnership and the NASA management processes as NASA plans for the transition of the ISS by 2030? To answer the first question, we conducted a stakeholder-driven analysis to identify a trade space of six differentiated model options. We then evaluated their performance in three potential future scenarios, according to evaluation criteria deemed important to stakeholders. The six models are illustrative and representational of a potential trade space. Additionally, each model requires change to current legislation. To further aid in leadership decision-making, we provided considerations for how to strengthen each model by mixing and matching different model aspects. To answer the second question, we looked to strengths of the top-performing models to evolve the current ISSNL-CASIS relationship and improve NASA’s posture for success post-ISS. We identified four possible modifications to the ISSNL-CASIS partnership and NASA’s management of these activities. By implementing these modifications early, NASA can increase the return from ISSNL-CASIS and help prepare for future models as one or more CLD replaces the ISS by 2030.

ISS↗

Higher climatological temperature sensitivity of soil carbon in cold than warm climates

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs). In this study, to assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times that reflect long-term and broad-scale rates of decomposition. We show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Current ESMs fail to capture this pattern, except in an ESM that explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. Lastly, these results support projections of strong carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behaviour.

54 ENVIRONMENTAL SCIENCES↗

Asymmetric winter warming advanced plant phenology to a greater extent than symmetric warming in an alpine meadow

1. The warming of terrestrial high-latitude ecosystems, while increasing, will likely be asymmetric across seasons—where winter non-growing seasons will warm more than summer-growing seasons. Asymmetric winter warming in temperature-sensitive ecosystems may delay spring phenological events by reducing the opportunity that a plants’ chilling requirement is met. Similarly, symmetric warming can advance spring phenology. 2. To explore the impact of asymmetric warming on plant phenology, we applied a year-round warming and a winter warming treatment to our experimental plots. Over a 2-year period, we monitored leaf-out and flowering phenology for 11 plant species. 3. There was variation among species, however, both winter and year-round warming, advanced the leaf-out day and the first flowering day relative to the control treatment. So, winter warming advanced leaf-out and flowering phenology by 11.1 (±2.4) and 12.6 (±2.9) days respectively. However, year-round warming had less of an impact advancing leaf-out and flowering phenology by 5.1 (±2.1) and 10.0 (±3.0) days respectively. 4. Our study provides direct evidence that asymmetric winter warming has a larger impact on plant phenology than symmetric year-round warming. Increasing soil temperature in the winter from below to above freezing temperatures advanced the spring phenology of alpine plants. Winter warming increased soil temperature more than year-round warming, which explains why phenology advanced under winter warming more than under year-round warming. In addition, early or mid-season flowering plant species displayed different phenology strategies in warmer winters. 5. Relative to other ecosystems, alpine ecosystems such as the Tibetan Plateau will likely respond to asymmetric warming given the higher amplitude of winter temperature increases due to climatic warming. Conclusively, our data indicate that seasonal variation in warming should be considered when predicting and modelling the response of alpine ecosystems to climatic change.

54 ENVIRONMENTAL SCIENCES↗

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions

Abstract Wetland methane (CH 4 ) emissions ( $${F}_{{{CH}}_{4}}$$ F C H 4 ) are important in global carbon budgets and climate change assessments. Currently, $${F}_{{{CH}}_{4}}$$ F C H 4 projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent $${F}_{{{CH}}_{4}}$$ F C H 4 temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that $${F}_{{{CH}}_{4}}$$ F C H 4 are often controlled by factors beyond temperature. Here, we evaluate the relationship between $${F}_{{{CH}}_{4}}$$ F C H 4 and temperature using observations from the FLUXNET-CH 4 database. Measurements collected across the globe show substantial seasonal hysteresis between $${F}_{{{CH}}_{4}}$$ F C H 4 and temperature, suggesting larger $${F}_{{{CH}}_{4}}$$ F C H 4 sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH 4 production are thus needed to improve global CH 4 budget assessments.

54 ENVIRONMENTAL SCIENCES↗

The confluences of ideas leading to, and the flow of ideas emerging from, individual-based modeling of riverine fishes

In this review article, we trace the history of events leading to the development of individual-based models (IBMs) to represent aquatic organisms in rivers and streams. As a metaphor, we present this history as a series of confluences between individual scientists (tributaries) sharing ideas. We describe contributions of these models to science and management. One iconic feature of river IBMs is the linkage between flow and the physical habitat experienced by individual animals, and the first model that focused on this linkage is briefly described. We continue by reviewing the contributions of riverine IBMs to eight broad areas of scientific inquiry. The first four areas include research to understand the effects of flow regimes on fish populations, species interactions (e.g., size-mediated competition and predation), fish movement and habitat selection, and contaminant and water quality impacts on populations. Next, we review research using IBMs to guide conservation biology of imperiled taxa through population viability analysis, including research to understand river fragmentation by dams and reconnection, to understand genetic outcomes for riverine metapopulations, and to anticipate the future effects of temperature and climate change. This rich body of literature has contributed to both theoretical insights (e.g., about animal behavior and life history) and applied insights (e.g., population-level effects of flow regimes, temperature, and the effects of hydropower and other industries that share rivers with aquatic biota). Lastly, we finish by exploring promising branches that lie ahead in the braided, downstream channel that represents future river modeling research.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify these services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index (SPI), standardized soil water content index (SSWI), and standardized streamflow index (SSI). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI12 than SPI12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to extreme climate conditions in order to protect and restore freshwater provisioning and food provisioning services in the UMRB.

54 ENVIRONMENTAL SCIENCES↗

Assessment of Aerosol Distributions from GEOS-5 Using the CALIPSO Feature Mask

A-train sensors such as MODIS, MISR, and CALIPSO are used to determine aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important for climate assessment, air quality applications, and for comparisons and analysis with aerosol transport models. The Aerosols-Clouds-Ecosystems (ACE) satellite mission proposed in the NRC Decadal Survey describes a next generation aerosol and cloud suite similar to the current A-train, including a lidar. The future ACE lidar must be able to determine aerosol type effectively in conjunction with modeling activities to achieve ACE objectives. Here we examine the current capabilities of CALIPSO and the NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-5), to place future ACE needs in context. The CALIPSO level 2 feature mask includes vertical profiles of aerosol layers classified by type. GEOS-5 provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures and extinction profiles along the CALIPSO orbit track. In previous work, initial comparisons between GEOS-5 derived aerosol mixtures and CALIPSO derived aerosol types were presented for July 2007. In general, the results showed that model and lidar derived aerosol types did not agree well in the boundary layer. Agreement was poor over Europe, where CALIPSO indicated the presence of dust and pollution mixtures yet GEOS-5 was dominated by pollution with little dust. Over the ocean in the tropics, the model appeared to contain less sea salt than detected by CALIPSO, yet at high latitudes the situation was reserved. Agreement between CALIPSO and GEOS-5, aerosol types improved above the boundary layer, primarily in dust and smoke dominated regions. At higher altitudes (> 5 km), the model contained aerosol layers not detected by CALIPSO. Here we present new results for a full year study using the new Version 3 CALIPSO data and most recent GEOS-5 model results.

Welton, Ellsworth↗

Microbial carbon limitation: The need for integrating microorganisms into our understanding of ecosystem carbon cycling

Abstract Numerous studies have demonstrated that fertilization with nutrients such as nitrogen, phosphorus, and potassium increases plant productivity in both natural and managed ecosystems, demonstrating that primary productivity is nutrient limited in most terrestrial ecosystems. In contrast, it has been demonstrated that heterotrophic microbial communities in soil are primarily limited by organic carbon or energy. While this concept of contrasting limitations, that is, microbial carbon and plant nutrient limitation, is based on strong evidence that we review in this paper, it is often ignored in discussions of ecosystem response to global environment changes. The plant‐centric perspective has equated plant nutrient limitations with those of whole ecosystems, thereby ignoring the important role of the heterotrophs responsible for soil decomposition in driving ecosystem carbon storage. To truly integrate carbon and nutrient cycles in ecosystem science, we must account for the fact that while plant productivity may be nutrient limited, the secondary productivity by heterotrophic communities is inherently carbon limited. Ecosystem carbon cycling integrates the independent physiological responses of its individual components, as well as tightly coupled exchanges between autotrophs and heterotrophs. To the extent that the interacting autotrophic and heterotrophic processes are controlled by organisms that are limited by nutrient versus carbon accessibility, respectively, we propose that ecosystems by definition cannot be ‘limited’ by nutrients or carbon alone. Here, we outline how models aimed at predicting non‐steady state ecosystem responses over time can benefit from dissecting ecosystems into the organismal components and their inherent limitations to better represent plant–microbe interactions in coupled carbon and nutrient models.

Soong, Jennifer L.↗

Critical Load Exceedances for North America and Europe using an Ensemble of Models and an Investigation of Causes for Environmental Impact Estimate Variability: An AQMEII4 Study

Exceedances of critical loads for deposition of sulphur (S) and nitrogen (N) to different ecosystems were estimated using European and North American ensembles of air quality models, under Phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4), to identify where risk of ecosystem harm is expected to occur based on model deposition estimates. The ensembles were driven by common emissions and lateral boundary condition inputs. Model output was regridded to common North American and Europe 0.125° resolution domains, which were then used to calculate critical load exceedances. New, targeted deposition diagnostics implemented in AQMEII4 allowed an unprecedented level of post-simulation analysis to be carried out and facilitated the identification of specific causes of model-to-model variability in critical load exceedance estimates. New datasets for North American critical loads for acidity for forest soil water and aquatic ecosystems were combined with the ensemble deposition predictions to show a substantial decrease in the area and number of locations in exceedance between 2010 and 2016 (forest soils: 13.2 % to 6.1 %; aquatic ecosystems: 21.2 % to 11.4 %). All models agreed in the direction of the ensemble exceedance change between 2010 and 2016. The North American ensemble also predicted a decrease in both severity and total area in exceedance between the years 2010 and 2016 for eutrophication-impacted ecosystems in the USA (sensitive epiphytic lichen: 81.5 % to 75.8 %). The exceedances for herbaceous community richness also decreased between 2010 and 2016, from 13.9 % to 3.9 %. The uncertainty associated with the North American eutrophication results is high; there were sharp differences between the models in both predictions of total N deposition and the change in N deposition, and hence in the predicted eutrophication exceedances between the two years. The European ensemble was used to predict relatively static exceedances of critical loads with respect to acidification (4.48 % to 4.32 % from 2009 to 2010) while eutrophication exceedance increased slightly (60.2 % to 62.2 %). While most models showed the same changes in critical load exceedances as the ensemble between the two years, the spatial extent and magnitude of exceedances varied significantly between the models. The reasons for this variation were examined in detail by first ranking the relative contribution of different sources of sulphur and nitrogen deposition in terms of deposited mass and model-to-model variability in that deposited mass, followed by their analysis using AQMEII4 diagnostics, along with evaluation of the most recent literature. All models in both the North American and European ensembles had net annual negative biases with respect to observed wet deposition of sulphate, nitrate and ammonium. Diagnostics and recent literature suggest that this bias may stem from insufficient cloud scavenging of aerosols and gases, and may be improved through the incorporation of multiphase hydrometeor scavenging within the modelling frameworks. The inability of North American models to predict the timing of the seasonal peak in wet ammonium ion deposition (observed maximum was in April, while all models predicted a June maximum) may also relate to the need for multiphase hydrometeor scavenging (absence of snow scavenging in all models employed here). High variability in the relative importance of particulate sulphate, nitrate and ammonium deposition fluxes between models was linked to the use of updated particle dry deposition parameterizations in some models. However, recent literature and further development of some of the models within the ensemble suggests these particulate biases may also be ameliorated via the incorporation of multiphase hydrometeor scavenging. Annual sulphur and nitrogen deposition prediction variability was linked to SO 2 and HNO 3 dry deposition parameterizations, and diagnostic analysis showed that the cuticle and soil deposition pathways dominate the deposition mass flux of these species. Further work improving parameterizations for these deposition pathways should reduce variability in model acidifying gas deposition estimates. The absence of base cation chemistry in some models was shown to be a major factor in positive biases in fine mode particulate ammonium and particle nitrate concentrations. Models employing ammonia bidirectional fluxes had both the largest and the smallest magnitude biases, depending on the model and bidirectional flux algorithm employed. A careful analysis of bidirectional flux models suggests that those with poor NH 3 performance may underestimate the extent of NH 3 emissions fluxes from forested areas. Based on these results, an increased process-research focus is therefore recommended for the following model processes and on observations which may assist in model evaluation and improvement: multiphase hydrometeor scavenging combined with updated particle dry deposition, cuticle and soil deposition pathway algorithms for acidifying gases, base cation chemistry and emissions, and NH 3 bidirectional fluxes. Comparisons with satellite observations suggest that oceanic NH 3 emissions sources should be included in regional chemical transport models. The choice of land use database employed within any given model was shown to significantly influence deposition totals in several instances, and employing a common land use database across chemical transport models and critical load calculations is recommended for future work.

critical loads↗

Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)

Explicit consideration of microbial physiology in soil biogeochemical models that represent coupled carbon–nitrogen dynamics presents opportunities to deepen understanding of ecosystem responses to environmental change. The MIcrobial-MIneral Carbon Stabilization (MIMICS) model explicitly represents microbial physiology and physicochemical stabilization of soil carbon (C) on regional and global scales. Here we present a new version of MIMICS with coupled C and nitrogen (N) cycling through litter, microbial, and soil organic matter (SOM) pools. The model was parameterized and validated against C and N data from the Long-Term Inter-site Decomposition Experiment Team (LIDET; six litter types, 10 years of observations, and 13 sites across North America). The model simulates C and N losses from litterbags in the LIDET study with reasonable accuracy (C: R 2 =0.63; N: R 2 =0.29), which is comparable with simulations from the DAYCENT model that implicitly represents microbial activity (C: R 2 =0.67; N: R 2 =0.30). Subsequently, we evaluated equilibrium values of stocks (total soil C and N, microbial biomass C and N, inorganic N) and microbial process rates (soil heterotrophic respiration, N mineralization) simulated by MIMICS-CN across the 13 simulated LIDET sites against published observations from other continent-wide datasets. We found that MIMICS-CN produces equilibrium values in line with measured values, showing that the model generates plausible estimates of ecosystem soil biogeochemical dynamics across continental-scale gradients. MIMICS-CN provides a platform for coupling C and N projections in a microbially explicit model, but experiments still need to identify the physiological and stoichiometric characteristics of soil microbes, especially under environmental change scenarios.

58 GEOSCIENCES↗

Respiration regimes in rivers: Partitioning source–specific respiration from metabolism time series

Respiration in streams is controlled by the timing, magnitude, and quality of organic matter (OM) inputs from internal primary production and external fluxes. Here, we estimated the contribution of different OM sources to seasonal, annual, and event-driven characteristics of whole-stream ecosystem respiration (ER) using an inverse modeling framework that accounts for possible time-lags between OM inputs and respiration. We modeled site-specific, dynamic OM stocks contributing to ER: autochthonous OM from gross primary production (GPP); allochthonous OM delivered during flow events; and seasonal pulses of leaf litter. OM stored in the sediment and dissolved organic matter (DOM) transported during baseflow were modeled as a stable stock contributing to baseline respiration. We applied this modeling framework to five streams with different catchment size, climate, and canopy cover, where multi-year time series of ER and environmental variables were available. Overall, the model explained between 53% and 74% of observed ER dynamics. Respiration of autochthonous OM tracked seasonal peaks in GPP in spring or summer. Increases in ER were often associated with high-flow events. Respiration associated with litter inputs was larger in smaller streams. Time lags between leaf inputs and respiration were longer than for other OM sources, likely due to lower biological reactivity. Model estimates of source-specific ER and OM stocks compared well with existing measures of OM stocks, inputs, and respiration or decomposition. Our modeling approach has the potential to expand the scale of comparative analyses of OM dynamics within and among freshwater ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

The Functionally-Assembled Terrestrial Ecosystem Simulator Version 1

The Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) is a vegetation model for use in Earth system models (ESMs). The model includes a size- and age-structured representation of tree dynamics, competition between functionally diverse plant functional types, and the biophysics underpinning plant growth, competition, mortality, as well as the carbon, water, and energy exchange with the atmosphere. The FATES model is designed as a modular vegetation model that can be integrated within a host land model for inclusion in ESMs. The model is designed for use in global change studies to understand and project the responses and feedbacks between terrestrial ecosystems and the Earth system under changing climate and other forcings.

Xu, Chonggang↗

The Functionally-Assembled Terrestrial Ecosystem Simulator Version 1

The Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) is a vegetation model for use in Earth system models (ESMs). The model includes a size- and age-structured representation of tree dynamics, competition between functionally diverse plant functional types, and the biophysics underpinning plant growth, competition, mortality, as well as the carbon, water, and energy exchange with the atmosphere. The FATES model is designed as a modular vegetation model that can be integrated within a host land model for inclusion in ESMs. The model is designed for use in global change studies to understand and project the responses and feedbacks between terrestrial ecosystems and the Earth system under changing climate and other forcings.

Xu, Chonggang↗

Observed and Imputed Volumetric Soil Water Content Timeseries for the New Mexico Elevation Gradient

Reliable soil water content (SWC) data are essential for understanding dryland ecosystem dynamics, but high-frequency SWC sensors often fail, creating gaps in critical datasets. To address this, we developed a Bayesian mixture model that imputes missing SWC using both linear interpolation and an ecosystem water balance model (SOILWAT2), tested across six AmeriFlux eddy covariance tower sites in the New Mexico Elevation Gradient, demonstrating its effectiveness in reconstructing SWC patterns while providing insights into the factors driving SWC variability. Daily volumetric soil water content (SWC) data are provided as csv-formatted spreadsheets for the six AmeriFlux sites (US-Seg, US-Ses, US-Wjs, US-Mpi, US-Vcp, and US-Vcs). For each site there is an observed SWC file (site_SWC_gapfill.csv) and a file that contains imputed SWC (imputed_SWC_site.csv). The observed SWC files contain temperature corrected sensor values, tower precipitation data, as well as outputs from SOILWAT2 simulations that were used to impute SWC. The imputed files contain the original observed SWC values and the imputed missing SWC values. When SWC was missing from the original data, the missing value was imputed based on the Bayesian imputation mixture model. The posterior mean of all imputed values is reported as "mean_X". When the observed SWC was NOT missing, mean_X = observed SWC value (original data). The standard deviation, 2.5th percentile and the 97.5th percentile for the imputed values are also reported in the imputed files. There are readme text files for each file type explaining the contents of each column.

54 ENVIRONMENTAL SCIENCES↗