Browsing by Author "Vargas, Rodrigo"
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Item Building Trust in Earth Science Findings through Data Traceability and Results Explainability(IEEE Transactions on Parallel and Distributed Systems, 2022-11-08) Olaya, Paula; Kennedy, Dominic; Llamas, Ricardo; Valera, Leobardo; Vargas, Rodrigo; Lofstead, Jay; Taufer, MichelaTo trust findings in computational science, scientists need workflows that trace the data provenance and support results explainability. As workflows become more complex, tracing data provenance and explaining results become harder to achieve. In this paper, we propose a computational environment that automatically creates a workflow execution's record trail and invisibly attaches it to the workflow's output, enabling data traceability and results explainability. Our solution transforms existing container technology, includes tools for automatically annotating provenance metadata, and allows effective movement of data and metadata across the workflow execution. We demonstrate the capabilities of our environment with the study of SOMOSPIE, an earth science workflow. Through a suite of machine learning modeling techniques, this workflow predicts soil moisture values from the 27 km resolution satellite data down to higher resolutions necessary for policy making and precision agriculture. By running the workflow in our environment, we can identify the causes of different accuracy measurements for predicted soil moisture values in different resolutions of the input data and link different results to different machine learning methods used during the soil moisture downscaling, all without requiring scientists to know aspects of workflow design and implementation.Item Downscaling satellite soil moisture for landscape applications: A case study in Delaware, USA(Journal of Hydrology: Regional Studies, 2021-10-15) Warner, Daniel L.; Guevara, Mario; Callahan, John; Vargas, RodrigoStudy region: Delaware, USA and its surrounding watersheds. Study focus: An ensemble using multiple Kernel K-nearest neighbors (KKNN) models was trained to predict daily grids of SSM at 100-meter resolution based on SSM estimates from the European Space Agency’s Climate Change Initiative Soil Moisture Product, terrain data, soil maps, and local meteorological network data. Estimated SSM was evaluated against independent in situ SSM observations and were investigated for relationships with land cover class and vegetation phenology (i.e., NDVI). New hydrological insights for the region Downscaled daily mean SSM estimates had lower error in space (27%) and greater predictive performance over time compared to the raw, coarse resolution remotely sensed SSM dataset when calibrated to field observed values. Downscaled SSM identified stronger and more widespread temporal relationships with NDVI than other estimation methods. However, both coarse and fine resolution datasets greatly underestimated SSM in wetland areas. The findings highlight the need for enhanced in situ SSM monitoring across diverse settings to improve landscape-level downscaled SSM. The downscaling methodology developed in this study was able to produce daily SSM estimates, providing a framework that can support future SSM modeling efforts, hydroecological investigations, and agricultural studies in this and other regions around the world when used in conjunction with ground-based monitoring networks.Item Dynamics of short-term ecosystem carbon fluxes induced by precipitation events in a semiarid grassland(Biogeosciences, 2023-06-22) Delgado-Balbuena, Josué; Loescher, Henry W.; Aguirre-Gutiérrez, Carlos A.; Alfaro-Reyna, Teresa; Pineda-Martínez, Luis F.; Vargas, Rodrigo; Arredondo, TulioInfrequent and small precipitation (PPT) events characterize PPT patterns in semiarid grasslands; however, plants and soil microorganisms are adapted to use the unpredictable small pulses of water. Several studies have shown short-term responses of carbon and nitrogen mineralization rates (called the “priming effect” or the Birch effect) stimulated by wet–dry cycles; however, dynamics, drivers, and the contribution of the priming effect to the annual C balance are poorly understood. Thus, we analyzed 6 years of continuous net ecosystem exchange measurements to evaluate the effect of the PPT periodicity and magnitude of individual PPT events on the daily/annual net ecosystem C exchange (NEE) in a semiarid grassland. We included the period between PPT events, previous daytime NEE rate, and previous soil moisture content as the main drivers of the priming effect. Ecosystem respiration (ER) responded within a few hours following a PPT event, whereas it took 5–9 d for gross ecosystem exchange (GEE; where −NEE = GEE + ER) to respond. Precipitation events as low as 0.25 mm increased ER, but cumulative PPT > 40 mm infiltrating deep into the soil profile stimulated GEE. Overall, ER fluxes following PPT events were related to the change in soil water content at shallow depth and previous soil conditions (e.g., previous NEE rate, previous soil water content) and the size of the stimulus (e.g., PPT event size). Carbon effluxes from the priming effect accounted for less than 5 % of ecosystem respiration but were significantly high with respect to the carbon balance. In the long term, changes in PPT regimes to more intense and less frequent PPT events, as expected due to the effects of climate change, could convert the semiarid grassland from a small C sink to a C source.Item Estimating forest extent across Mexico(Environmental Research Letters, 2024-01-12) Braden, Dustin; Mondal, Pinki; Park, Taejin; Alanís de la Rosa, José Armando; Aldrete Leal, Metzli Ileana; Cuenca Lara, Rubi Angélica; Mayorga Saucedo, Rafael; Paz, Fernando; Salas-Aguilar, Victor Manuel; Soriano-Luna, María De Los Ángeles; Vargas, RodrigoInformation on forest extent and tree cover is required to evaluate the status of natural resources, conservation practices, and environmental policies. The challenge is that different forest definitions, remote sensing-based (RSB) products, and data availability can lead to discrepancies in reporting total forest area. Consequently, errors in forest extent can be propagated into forest biomass and carbon estimates. Here, we present a simple approach to compare forest extent estimates from seven regional and global land or tree cover RSB products at 30 m resolution across Mexico. We found substantial differences in forest extent estimates for Mexico, ranging from 387 607 km2 to 675 239 km2. These differences were dependent on the RSB product and forest definition used. Next, we compared these RSB products with two independent forest inventory datasets at national (n = 26 220 plots) and local scales (n = 754 plots). The greatest accuracy among RSB products and forest inventory data was within the tropical moist forest (range 82%–95%), and the smallest was within the subtropical desert (range <10%–80%) and subtropical steppe ecological zones (range <10%–60%). We developed a forest extent agreement map by combining seven RSB products and identifying a consensus in their estimates. We found a forest area of 288 749 km2 with high forest extent agreement, and 340 661 km2 with medium forest extent agreement. The high-to-medium forest extent agreement of 629 410 km2 is comparable to the official national estimate of 656 920 km2. We found a high forest extent agreement across the Yucatan Peninsula and mountain areas in the Sierra Madre Oriental and Sierra Madre Occidental. The tropical dry forest and subtropical mountain system represent the two ecological zones with the highest areas of disagreement among RSB products. These findings show discrepancies in forest extent estimates across ecological zones in Mexico, where additional ground data and research are needed. Dataset available at https://doi.org/10.3334/ORNLDAAC/2320.Item High methane concentrations in tidal salt marsh soils: Where does the methane go?(Global Change Biology, 2023-11-30) Capooci, Margaret; Seyfferth, Angelia L.; Tobias, Craig; Wozniak, Andrew S.; Hedgpeth, Alexandra; Bowen, Malique; Biddle, Jennifer F.; McFarlane, Karis J.; Vargas, RodrigoTidal salt marshes produce and emit CH4. Therefore, it is critical to understand the biogeochemical controls that regulate CH4 spatial and temporal dynamics in wetlands. The prevailing paradigm assumes that acetoclastic methanogenesis is the dominant pathway for CH4 production, and higher salinity concentrations inhibit CH4 production in salt marshes. Recent evidence shows that CH4 is produced within salt marshes via methylotrophic methanogenesis, a process not inhibited by sulfate reduction. To further explore this conundrum, we performed measurements of soil–atmosphere CH4 and CO2 fluxes coupled with depth profiles of soil CH4 and CO2 pore water gas concentrations, stable and radioisotopes, pore water chemistry, and microbial community composition to assess CH4 production and fate within a temperate tidal salt marsh. We found unexpectedly high CH4 concentrations up to 145,000 μmol mol−1 positively correlated with S2− (salinity range: 6.6–14.5 ppt). Despite large CH4 production within the soil, soil–atmosphere CH4 fluxes were low but with higher emissions and extreme variability during plant senescence (84.3 ± 684.4 nmol m−2 s−1). CH4 and CO2 within the soil pore water were produced from young carbon, with most Δ14C-CH4 and Δ14C-CO2 values at or above modern. We found evidence that CH4 within soils was produced by methylotrophic and hydrogenotrophic methanogenesis. Several pathways exist after CH4 is produced, including diffusion into the atmosphere, CH4 oxidation, and lateral export to adjacent tidal creeks; the latter being the most likely dominant flux. Our findings demonstrate that CH4 production and fluxes are biogeochemically heterogeneous, with multiple processes and pathways that can co-occur and vary in importance over the year. This study highlights the potential for high CH4 production, the need to understand the underlying biogeochemical controls, and the challenges of evaluating CH4 budgets and blue carbon in salt marshes.Item Hyperspectral Reflectance for Measuring Canopy-Level Nutrients and Photosynthesis in a Salt Marsh(Journal of Geophysical Research: Biogeosciences, 2022-11-04) Vázquez-Lule, Alma; Seyfferth, Angelia L.; Limmer, Matt A.; Mey, Paul; Guevara, Mario; Vargas, RodrigoSalt marsh ecosystems are underrepresented in process-based models due to their unique location across the terrestrial–aquatic interface. Particularly, the role of leaf nutrients on canopy photosynthesis (FA) remains unclear, despite their relevance for regulating vegetation growth. We combined multiyear information of canopy-level nutrients and eddy covariance measurements with canopy surface hyperspectral remote sensing (CSHRS) to quantify the spatial and temporal variability of FA in a temperate salt marsh. We found that FA showed a positive relationship with canopy-level N at the ecosystem scale and for areas dominated by Spartina cynosuroides, but not for areas dominated by short S. alterniflora. FA showed a positive relationship with canopy-level P, K, and Na, but a negative relationship with Fe, for areas associated with S. cynosuroides, S. alterniflora, and at the ecosystem scale. We used partial least squares regression (PLSR) with CSHRS and found statistically significant data–model agreements to predict canopy-level nutrients and FA. The red-edge electromagnetic region and ∼770 nm showed the highest contribution of variance in PLSR models for canopy-level nutrients and FA, but we propose that underlying sediment biogeochemistry can complicate interpretation of reflectance measurements. Our findings highlight the relevance of spatial variability in salt marshes vegetation and the promising application of CSHRS for linking information of canopy-level nutrients with FA. We call for further development of canopy surface hyperspectral methods and analyses across salt marshes to improve our understanding of how these ecosystems will respond to global environmental change. Plain Language Summary Canopy photosynthesis in salt marshes contributes to the carbon stored in these ecosystems; however, its relationship with canopy-level nutrients has been underrepresented in models. Reflectance from near surface remote sensing could be a cost-effective nondestructive tool to monitor canopy photosynthesis and associated nutrients in salt marshes. We combined canopy-level nutrient information with hyperspectral canopy reflectance to represent the spatial and temporal variability of canopy photosynthesis in a salt marsh in the Mid-Atlantic cost of the U.S. We found that local variability such as different salt marsh species have an influence on the relationship between canopy photosynthesis and associated nutrients, in consequence the most limiting nutrients for photosynthesis were phosphorus, potassium, and sodium. We propose that underlying sediment biogeochemistry can potentially obscure the expected relationships between plant nutrients and photosynthesis in remote sensing of coastal wetlands. These results open the possibility to use similar reflectance information from airborne or spaceborne platforms to explore these relationships at broader scales. Key Points - Local environmental variability influences the relationship of canopy nutrients with canopy photosynthesis in a salt marsh ecosystem - Sediment biogeochemistry can obscure expected relationships between plant nutrients and photosynthesis in remote sensing of coastal wetlands - Canopy surface hyperspectral remote sensing is a promising technique for studying vegetation dynamics of salt marshesItem Management Impacts on Carbon Dynamics in a Sierra Nevada Mixed Conifer Forest(Public Library Science, 2/26/16) Dore,Sabina; Fry,Danny L.; Collins,Brandon M.; Vargas,Rodrigo; York,Robert A.; Stephens,Scott L.; Sabina Dore, Danny L. Fry, Brandon M. Collins, Rodrigo Vargas, Robert A. York, Scott L. Stephens; Vargas, RodrigoForest ecosystems can act as sinks of carbon and thus mitigate anthropogenic carbon emissions. When forests are actively managed, treatments can alter forests carbon dynamics, reducing their sink strength and switching them from sinks to sources of carbon. These effects are generally characterized by fast temporal dynamics. Hence this study monitored for over a decade the impacts of management practices commonly used to reduce fire hazards on the carbon dynamics of mixed-conifer forests in the Sierra Nevada, California, USA. Soil CO2 efflux, carbon pools (i.e. soil carbon, litter, fine roots, tree biomass), and radial tree growth were compared among un-manipulated controls, prescribed fire, thinning, thinning followed by fire, and two clear-cut harvested sites. Soil CO2 efflux was reduced by both fire and harvesting (ca. 15%). Soil carbon content (upper 15 cm) was not significantly changed by harvest or fire treatments. Fine root biomass was reduced by clear-cut harvest (60-70%) but not by fire, and the litter layer was reduced 80% by clear-cut harvest and 40% by fire. Thinning effects on tree growth and biomass were concentrated in the first year after treatments, whereas fire effects persisted over the seven-year post-treatment period. Over this period, tree radial growth was increased (25%) by thinning and reduced (12%) by fire. After seven years, tree biomass returned to pre-treatment levels in both fire and thinning treatments; however, biomass and productivity decreased 30%-40% compared to controls when thinning was combined with fire. The clear-cut treatment had the strongest impact, reducing ecosystem carbon stocks and delaying the capacity for carbon uptake. We conclude that post-treatment carbon dynamics and ecosystem recovery time varied with intensity and type of treatments. Consequently, management practices can be selected to minimize ecosystem carbon losses while increasing future carbon uptake, resilience to high severity fire, and climate related stresses.Item Methane fluxes in tidal marshes of the conterminous United States(Global Change Biology, 2024-09-05) Arias‐Ortiz, Ariane; Wolfe, Jaxine; Bridgham, Scott D.; Knox, Sara; McNicol, Gavin; Needelman, Brian A.; Shahan, Julie; Stuart‐Haëntjens, Ellen J.; Windham‐Myers, Lisamarie; Oikawa, Patty Y.; Baldocchi, Dennis D.; Caplan, Joshua S.; Capooci, Margaret; Czapla, Kenneth M.; Derby, R. Kyle; Diefenderfer, Heida L.; Forbrich, Inke; Groseclose, Gina; Keller, Jason K.; Kelley, Cheryl; Keshta, Amr E.; Kleiner, Helena S.; Krauss, Ken W.; Lane, Robert R.; Mack, Sarah; Moseman‐Valtierra, Serena; Mozdzer, Thomas J.; Mueller, Peter; Neubauer, Scott C.; Noyce, Genevieve; Schäfer, Karina V. R.; Sanders‐DeMott, Rebecca; Schutte, Charles A.; Vargas, Rodrigo; Weston, Nathaniel B.; Wilson, Benjamin; Megonigal, J. Patrick; Holmquist, James R.Methane (CH4) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre-industrial times. Wetlands account for a large share of global CH4 emissions, yet the magnitude and factors controlling CH4 fluxes in tidal wetlands remain uncertain. We synthesized CH4 flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH4 emissions. This effort included creating an open-source database of chamber-based GHG fluxes (https://doi.org/10.25573/serc.14227085). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH4 m−2 year−1, with a median of 3.9 g CH4 m−2 year−1, and only 25% of sites exceeding 18 g CH4 m−2 year−1. The highest fluxes were observed at fresh-oligohaline sites with daily maximum temperature normals (MATmax) above 25.6°C. These were followed by frequently inundated low and mid-fresh-oligohaline marshes with MATmax ≤25.6°C, and mesohaline sites with MATmax >19°C. Quantile regressions of paired chamber CH4 flux and porewater biogeochemistry revealed that the 90th percentile of fluxes fell below 5 ± 3 nmol m−2 s−1 at sulfate concentrations >4.7 ± 0.6 mM, porewater salinity >21 ± 2 psu, or surface water salinity >15 ± 3 psu. Across sites, salinity was the dominant predictor of annual CH4 fluxes, while within sites, temperature, gross primary productivity (GPP), and tidal height controlled variability at diel and seasonal scales. At the diel scale, GPP preceded temperature in importance for predicting CH4 flux changes, while the opposite was observed at the seasonal scale. Water levels influenced the timing and pathway of diel CH4 fluxes, with pulsed releases of stored CH4 at low to rising tide. This study provides data and methods to improve tidal marsh CH4 emission estimates, support blue carbon assessments, and refine national and global GHG inventories.Item Physiochemical Controls on the Horizontal Exchange of Blue Carbon Across the Salt Marsh-Tidal Channel Interface(Journal of Geophysical Research: Biogeosciences, 2023-06-06) Fettrow, Sean; Jeppi, Virginia; Wozniak, Andrew; Vargas, Rodrigo; Michael, Holly; Seyfferth, Angelia L.Tidal channels are biogeochemical hotspots that horizontally exchange carbon (C) with marsh platforms, but the physiochemical drivers controlling these dynamics are poorly understood. We hypothesized that C-bearing iron (Fe) oxides precipitate and immobilize dissolved organic carbon (DOC) during ebb tide as the soils oxygenate, and dissolve into the porewater during flood tide, promoting transport to the channel. The hydraulic gradient physically controls how these solutes are horizontally exchanged across the marsh platform-tidal channel interface; we hypothesized that this gradient alters the concentration and source of C being exchanged. We further hypothesized that trace soil gases (i.e., CO2, CH4, dimethyl sulfide) are pushed out of the channel bank as the groundwater rises. To test these hypotheses, we measured porewater, surface water, and soil trace gases over two 24-hr monitoring campaigns (i.e., summer and spring) in a mesohaline tidal marsh. We found that Fe2+ and DOC were positively related during flood tide but not during ebb tide in spring when soils were more oxidized. This finding shows evidence for the formation and dissolution of C-bearing Fe oxides across a tidal cycle. In addition, the tidal channel contained significantly (p < 0.05) more terrestrial-like DOC when the hydraulic gradient was driving flow toward the channel. In comparison, the channel water was saltier and contained significantly (p < 0.05) more marine-like DOC when the hydraulic gradient reversed direction. Trace gas fluxes increased with rising groundwater levels, particularly dimethyl sulfide. These findings suggest multiple physiochemical mechanisms controlling the horizontal exchange of C at the marsh platform-tidal channel interface. Plain Language Summary Tidal salt marshes store large amounts of carbon belowground in soils, but there is also a significant amount of carbon flowing into and out of these ecosystems via tidal channels. We investigated the carbon flowing between the channel bank and surface water in a salt marsh in Delaware. We found that soil minerals (i.e., iron oxides) control the mobility of carbon as iron oxides retain carbon during ebb tides and release carbon during flood tides as the minerals dissolve. The gradient between the groundwater and surface water elevation (i.e., hydraulic gradient) controls the flow direction for dissolved carbon, altering the concentration and source of carbon found in the tidal channel across tidal cycles. In addition, gases trapped in channel banks are pushed out of the soils as the tide rises. These findings will improve our understanding of carbon cycles in these critical carbon sinks. Key Points - Physiochemical mechanisms control horizontal exchange of carbon across marsh-tidal channel interfaces, affecting lateral carbon flux - Dissolution and reprecipitation of carbon-bearing Fe oxides during flood and ebb tides control the horizontal mobility of carbon - Hydraulic gradients control the carbon character in the tidal channel, and rising tides push greenhouse gases out of the channel bankItem Sea Surface Temperature Influence on Terrestrial Gross Primary Production along the Southern California Current(Public Library of Science (PLOS), 2015-04-29) Reimer, Janet J.; Vargas, Rodrigo; Rivas, David; Gaxiola-Castro, Gilberto; Hernandez-Ayon, J. Martin; Lara-Lara, Ruben; Janet J. Reimer, Rodrigo Vargas, David Rivas, Gilberto Gaxiola-Castro, J. Martin Hernandez-Ayon, Ruben Lara-Lara; Reimer, Janet J.; Vargas, RodrigoSome land and ocean processes are related through connections (and synoptic-scale teleconnections) to the atmosphere. Synoptic-scale atmospheric (El Niño/Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO], and North Atlantic Oscillation [NAO]) decadal cycles are known to influence the global terrestrial carbon cycle. Potentially, smaller scale land-ocean connections influenced by coastal upwelling (changes in sea surface temperature) may be important for local-to-regional water-limited ecosystems where plants may benefit from air moisture transported from the ocean to terrestrial ecosystems. Here we use satellite-derived observations to test potential connections between changes in sea surface temperature (SST) in regions with strong coastal upwelling and terrestrial gross primary production (GPP) across the Baja California Peninsula. This region is characterized by an arid/ semiarid climate along the southern California Current. We found that SST was correlated with the fraction of photosynthetic active radiation (fPAR; as a proxy for GPP) with lags ranging from 0 to 5 months. In contrast ENSO was not as strongly related with fPAR as SST in these coastal ecosystems. Our results show the importance of local-scale changes in SST during upwelling events, to explain the variability in GPP in coastal, water-limited ecosystems. The response of GPP to SST was spatially-dependent: colder SST in the northern areas increased GPP (likely by influencing fog formation), while warmer SST at the southern areas was associated to higher GPP (as SST is in phase with precipitation patterns). Interannual trends in fPAR are also spatially variable along the Baja California Peninsula with increasing secular trends in subtropical regions, decreasing trends in the most arid region, and no trend in the semi-arid regions. These findings suggest that studies and ecosystem process based models should consider the lateral influence of local-scale ocean processes that could influence coastal ecosystem productivity.Item SoilGrids250m: Global gridded soil information based on machine learning(PLOS (Public Library of Science), 2017-02-16) Heng, Tomislav; Mendes de Jesus, Jorge; Heuvelink, Gerard B. M.; Ruiperez Gonzalez, Maria; Kilibarda, Milan; Blagotić, Aleksandar; Shangguan, Wei; Wright, Marvin N.; Geng, Xiaoyuan; Bauer-Marschallinger, Bernhard; Guevara, Mario Antonio; Vargas, Rodrigo; MacMillan, Robert A.; Batjes, Niels H.; Leenaars, Johan G. B.; Ribeiro, Eloi; Wheeler, Ichsani; Mantel, Stephan; Kempen, Bas; Tomislav Hengl, Jorge Mendes de Jesus, Gerard B. M. Heuvelink, Maria Ruiperez Gonzalez, Milan Kilibarda, Aleksandar Blagotić, Wei Shangguan, Marvin N. Wright, Xiaoyuan Geng, Bernhard Bauer-Marschallinger, Mario Antonio Guevara, Rodrigo Vargas, Robert A. MacMillan, Niels H. Batjes, Johan G. B. Leenaars, Eloi Ribeiro, Ichsani Wheeler, Stephan Mantel, Bas Kempen; Guevara, Mario Antonio; Vargas, RodrigoThis paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methodsÐrandom forest and gradient boosting and/or multinomial logistic regressionÐas implemented in the R packages ranger, xgboost, nnet and caret. The results of 10±fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.Item Spatial biases of information influence global estimates of soil respiration: How can we improve global predictions?(Global Change Biology, 2021-05-01) Stell, Emma; Warner, Daniel; Jian, Jinshi; Bond-Lamberty, Ben; Vargas, RodrigoSoil respiration (Rs), the efflux of CO2 from soils to the atmosphere, is a major component of the terrestrial carbon cycle, but is poorly constrained from regional to global scales. The global soil respiration database (SRDB) is a compilation of in situ Rs observations from around the globe that has been consistently updated with new measurements over the past decade. It is unclear whether the addition of data to new versions has produced better-constrained global Rs estimates. We compared two versions of the SRDB (v3.0 n = 5173 and v5.0 n = 10,366) to determine how additional data influenced global Rs annual sum, spatial patterns and associated uncertainty (1 km spatial resolution) using a machine learning approach. A quantile regression forest model parameterized using SRDBv3 yielded a global Rs sum of 88.6 Pg C year−1, and associated uncertainty of 29.9 (mean absolute error) and 57.9 (standard deviation) Pg C year−1, whereas parameterization using SRDBv5 yielded 96.5 Pg C year−1 and associated uncertainty of 30.2 (mean average error) and 73.4 (standard deviation) Pg C year−1. Empirically estimated global heterotrophic respiration (Rh) from v3 and v5 were 49.9–50.2 (mean 50.1) and 53.3–53.5 (mean 53.4) Pg C year−1, respectively. SRDBv5’s inclusion of new data from underrepresented regions (e.g., Asia, Africa, South America) resulted in overall higher model uncertainty. The largest differences between models parameterized with different SRDVB versions were in arid/semi-arid regions. The SRDBv5 is still biased toward northern latitudes and temperate zones, so we tested an optimized global distribution of Rs measurements, which resulted in a global sum of 96.4 ± 21.4 Pg C year−1 with an overall lower model uncertainty. These results support current global estimates of Rs but highlight spatial biases that influence model parameterization and interpretation and provide insights for design of environmental networks to improve global-scale Rs estimates.Item Spatial variability and uncertainty of soil nitrogen across the conterminous United States at different depths(Ecosphere, 2022-07-27) Smith, Elizabeth M.; Vargas, Rodrigo; Guevara, Mario; Tarin, Tonantzin; Pouyat, Richard V.Soil nitrogen (N) is an important driver of plant productivity and ecosystem functioning; consequently, it is critical to understand its spatial variability from local-to-global scales. Here, we provide a quantitative assessment of the three-dimensional spatial distribution of soil N across the United States (CONUS) using a digital soil mapping approach. We used a random forest-regression kriging algorithm to predict soil N concentrations and associated uncertainty across six soil depths (0–5, 5–15, 15–30, 30–60, 60–100, and 100–200 cm) at 5-km spatial grids. Across CONUS, there is a strong spatial dependence of soil N, where soil N concentrations decrease but uncertainty increases with soil depth. Soil N was higher in Pacific Northwest, Northeast, and Great Lakes National Ecological Observatory Network (NEON) ecoclimatic domains. Model uncertainty was higher in Atlantic Neotropical, Southern Rockies/Colorado Plateau, and Southeast NEON domains. We also compared our soil N predictions with satellite-derived gross primary production and forest biomass from the National Biomass and Carbon Dataset. Finally, we used uncertainty information to propose optimized locations for designing future soil surveys and found that the Atlantic Neotropical, Pacific Northwest, Pacific Southwest, and Appalachian/Cumberland Plateau NEON domains may require larger survey efforts. We highlight the need to increase knowledge of biophysical factors regulating soil processes at deeper depths to better characterize the three-dimensional space of soils. Our results provide a national benchmark regarding the spatial variability and uncertainty of soil N and reveal areas in need of a better representation.Item Spatiotemporal variability and origin of CO2 and CH4 tree stem fluxes in an upland forest(Global Change Biology, 2021-07-02) Barba, Josep; Poyatos, Rafael; Capooci, Margaret; Vargas, RodrigoThe exchange of multiple greenhouse gases (i.e., CO2 and CH4) between tree stems and the atmosphere represents a knowledge gap in the global carbon cycle. Stem CO2 and CH4 fluxes vary across time and space and are unclear, which are their individual or shared drivers. Here we measured CO2 and CH4 fluxes at different stem heights combining manual (biweekly; n = 678) and automated (hourly; n > 38,000) measurements in a temperate upland forest. All trees showed CO2 and CH4 emissions despite 20% of measurements showing net CH4 uptake. Stem CO2 fluxes presented clear seasonal trends from manual and automated measurements. Only automated measurements captured the high temporal variability of stem CH4 fluxes revealing clear seasonal trends. Despite that temporal integration, the limited number of automated chambers made stand-level mean CH4 fluxes sensitive to “hot spots,” resulting in mean fluxes with high uncertainty. Manual measurements provided better integration of spatial variability, but their lack of temporal variability integration hindered the detection of temporal trends and stand-level mean fluxes. These results highlight the potential bias of previous studies of stem CH4 fluxes solely based on manual or automated measurements. Stem height, temperature, and soil moisture only explained 7% and 11% of the stem CH4 flux variability compared to 42% and 81% for CO2 (manual and automated measurements, respectively). This large unexplained variability, in combination with high CH4 concentrations in the trees' heartwood, suggests that stem CH4 fluxes might be more influenced by gas transport and diffusivity through the wood than by drivers of respiratory CO2 flux, which has crucial implications for developing process-based ecosystem models. We postulate that CH4 is likely originated within tree stems because of lack of a consistent vertical pattern in CH4 fluxes, evidence of CH4 production in wood incubations, and low CH4 concentration in the soil profile but high concentrations within the trees' heartwood.Item Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions(Nature Communications, 2021-04-15) Chang, Kuang-Yu; Riley, William J.; Knox, Sara H.; Jackson, Robert B.; McNicol, Gavin; Poulter, Benjamin; Aurela, Mika; Baldocchi, Dennis; Bansal, Sheel; Bohrer, Gil; Campbell, David I.; Cescatti, Alessandro; Chu, Housen; Delwiche, Kyle B.; Desai, Ankur R.; Euskirchen, Eugenie; Friborg, Thomas; Goeckede, Mathias; Helbig, Manuel; Hemes, Kyle S.; Hirano, Takashi; Iwata, Hiroki; Kang, Minseok; Keenan, Trevor; Krauss, Ken W.; Lohila, Annalea; Mammarella, Ivan; Mitra, Bhaskar; Miyata, Akira; Nilsson, Mats B.; Noormets, Asko; Oechel, Walter C.; Papale, Dario; Peichl, Matthias; Reba, Michele L.; Rinne, Janne; Runkle, Benjamin R. K.; Ryu, Youngryel; Sachs, Torsten; Schäfer, Karina V. R.; Schmid, Hans Peter; Shurpali, Narasinha; Sonnentag, Oliver; Tang, Angela C. I.; Torn, Margaret S.; Trotta, Carlo; Tuittila, Eeva-Stiina; Ueyama, Masahito; Vargas, Rodrigo; Vesala, Timo; Windham-Myers, Lisamarie; Zhang, Zhen; Zona, DonatellaWetland methane (CH4) emissions (FCH4) are important in global carbon budgets and climate change assessments. Currently, FCH4 projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent FCH4 temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that FCH4 are often controlled by factors beyond temperature. Here, we evaluate the relationship between FCH4 and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between FCH4 and temperature, suggesting larger FCH4 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 CH4 production are thus needed to improve global CH4 budget assessments.Item The paradox of assessing greenhouse gases from soils for nature-based solutions(Biogeosciences, 2023-01-03) Vargas, Rodrigo; Le, Van HuongQuantifying the role of soils in nature-based solutions requires accurate estimates of soil greenhouse gas (GHG) fluxes. Technological advances allow us to measure multiple GHGs simultaneously, and now it is possible to provide complete GHG budgets from soils (i.e., CO2, CH4, and N2O fluxes). We propose that there is a conflict between the convenience of simultaneously measuring multiple soil GHG fluxes at fixed time intervals (e.g., once or twice per month) and the intrinsic temporal variability in and patterns of different GHG fluxes. Information derived from fixed time intervals – commonly done during manual field campaigns – had limitations to reproducing statistical properties, temporal dependence, annual budgets, and associated uncertainty when compared with information derived from continuous measurements (i.e., automated hourly measurements) for all soil GHG fluxes. We present a novel approach (i.e., temporal univariate Latin hypercube sampling) that can be applied to provide insights and optimize monitoring efforts of GHG fluxes across time. We suggest that multiple GHG fluxes should not be simultaneously measured at a few fixed time intervals (mainly when measurements are limited to once per month), but an optimized sampling approach can be used to reduce bias and uncertainty. These results have implications for assessing GHG fluxes from soils and consequently reduce uncertainty in the role of soils in nature-based solutions.Item The unexplored role of preferential flow in soil carbon dynamics(Soil Biology and Biochemistry, 2021-08-28) Franklin, Shane M.; Kravchenko, Alexandra N.; Vargas, Rodrigo; Vasilas, Bruce; Fuhrmann, Jeffry J.; Jin, YanWater is a crucial factor controlling the fate and processing of soil organics. Water commonly flows through the vadose zone via preferential flow pathways, resulting in nonuniform and rapid infiltration. Hence, a large portion of the soil matrix is bypassed. Preferential flow paths, often associated with well-connected macropore networks (>300 μm Ø), offer a unique balance between water availability, nutrient delivery, and re-oxygenation upon drainage. The heightened concentrations of moisture, nutrients, and oxygen make these locations optimal for high rates of microbial activity. Flow paths often display temporal stability. This stability results in repeated wetting and biogeochemical reactivation through time creating a lasting impact on micro-environmental conditions relevant to microbial functioning and carbon cycling in soil. Despite decades of research on preferential flow, there is still a need to link flow paths and the resultant heterogeneous moisture distributions to soil function. In this review, we discuss how preferential flow can serve as a framework of reference for the spatially and temporally heterogeneous biogeochemical cycling of soil carbon. We highlight the importance of combining current knowledge of pore-scale carbon dynamics with an appreciation of connected networks of hydraulically active pores/paths within the soil profile. Such combination opens new possibilities for upscaling pore-scale processes with the inclusion of resource heterogeneity at the macroscale. Working within this hydraulically connected framework can provide insight for the mechanistic representation of hot moments, which are temporally isolated large pulses of CO2 after rewetting or thawing events. We conclude with suggestions on knowledge gaps and stress the critical need of linking soil physics with biology to mechanistically understand soil functions. Highlights • Preferential flow paths play a key role in soil carbon dynamics. • Pore-scale carbon dynamics could be upscaled using hydraulic connectivity. • A conceptual model is presented that considers how soil pores function from hydrological and microbial perspectives.