47 research outputs found
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Quantifying Uncertainties in Sequential Chemical Extraction of Soil Phosphorus Using XANES Spectroscopy.
Sequential chemical extraction has been widely used to study soil phosphorus (P) dynamics and inform nutrient management, but its efficacy for assigning P into biologically meaningful pools remains unknown. Here, we evaluated the accuracy of the modified Hedley extraction scheme using P K-edge X-ray absorption near-edge structure (XANES) spectroscopy for nine carbonate-free soil samples with diverse chemical and mineralogical properties resulting from different degrees of soil development. For most samples, the extraction markedly overestimated the pool size of calcium-bound P (Ca-P, extracted by 1 M HCl) due to (1) P redistribution during the alkaline extractions (0.5 M NaHCO3 and then 0.1 M NaOH), creating new Ca-P via formation of Ca phosphates between NaOH-desorbed phosphate and exchangeable Ca2+ and/or (2) dissolution of poorly crystalline Fe and Al oxides by 1 M HCl, releasing P occluded by these oxides into solution. The first mechanism may occur in soils rich in well-crystallized minerals and exchangeable Ca2+ regardless of the presence or absence of CaCO3, whereas the second mechanism likely operates in soils rich in poorly crystalline Fe and Al minerals. The overestimation of Ca-P simultaneously caused underestimation of the pools extracted by the alkaline solutions. Our findings identify key edaphic parameters that remarkably influenced the extractions, which will strengthen our understanding of soil P dynamics using this widely accepted procedure
Vulnerability of Physically Protected Soil Organic Carbon to Loss Under Low Severity Fires
Soil aggregate degradation during medium and high severity fires is often identified as the main mechanism that leads to loss of soil organic matter (SOM) due to fire. Low severity fires, however, are considered not to cause aggregate degradation assuming that temperatures <250°C, as occurring during low-severity burns, have only limited effects on the stability of the soil organic binding agents. Recent studies suggest that low severity burns may cause soil aggregate degradation due to rapid vaporization of soil pore water that can induce pressure on the soil aggregates beyond their yield stress. Such pressure-driven degradation of soil aggregates may expose physically protected organic carbon to decomposition. Our study investigated the effect of a low-severity fire on soil organic matter (SOM), water extractable organic C, and N as well as respiration for two initial soil moisture conditions undergoing three âheating regimesâ using aggregates from a California forest and a Nevada shrubland soil. We found that initially moist soil aggregates that were rapidly heated up degraded the most, showing increased cumulative carbon mineralization when compared to aggregates that were not heated, aggregates that were dry before being heated, and initially moist soil aggregates that were slowly heated. Our results suggest that exposure of previously physically protected organic carbon within the soil aggregates to oxidative conditions was the most likely cause of increased rates of decomposition of organic matter after low-severity burns. Additionally, we show that for a shrubland soil, aggregates with relatively low organic carbon content, low severity burns increased cumulative carbon mineralization. We hypothesized that this was due to decomposition of cytoplasmic material from lysed microbes. Our results suggest that low severity burns can accelerate decomposition of soil organic carbon (SOC) protected in soil aggregates
Reflections on Earth surface research
To celebrate the first anniversary of Nature Reviews Earth & Environment, we asked six researchers investigating Earth surface processes to outline notable developments within their discipline and provide thoughts on important work yet to be done
Synergy between compost and cover crops in a Mediterranean row crop system leads to increased subsoil carbon storage
Subsoil carbon (C) stocks are a prime target for efforts to increase soil C storage for climate change mitigation. However, subsoil C dynamics are not well understood, especially in soils under long-term intensive agricultural management. We compared subsoil C storage and soil organic matter (SOM) composition in tomato-corn rotations after 25 years of differing C and nutrient management in the California Central Valley: CONV (mineral fertilizer), CONV+WCC (mineral fertilizer and cover crops), and ORG (composted poultry manure and cover crops). The cover crop mix used in these systems is a mix of oat (Avena sativa L.), faba bean (Vicia faba L.), and hairy vetch (Vicia villosa Roth). Our results showed a âŒ19Mgha-1 increase in soil organic C (SOC) stocks down to 1m under ORG systems, no significant SOC increases under CONV+WCC or CONV systems, and an increased abundance of carboxyl-rich C in the subsoil (60-100cm) horizons of ORG and CONV+WCC systems. Our results show the potential for increased subsoil C storage with compost and cover crop amendments in tilled agricultural systems and identify potential pathways for increasing C transport and storage in subsoil layers. Copyright
Divergent controls of soil organic carbon between observations and process-based models
The storage and cycling of soil organic carbon (SOC) are governed by multiple co-varying factors, including climate, plant productivity, edaphic properties, and disturbance history. Yet, it remains unclear which of these factors are the dominant predictors of observed SOC stocks, globally and within biomes, and how the role of these predictors varies between observations and process-based models. Here we use global observations and an ensemble of soil biogeochemical models to quantify the emergent importance of key state factors â namely, mean annual temperature, net primary productivity, and soil mineralogy â in explaining biome- to global-scale variation in SOC stocks. We use a machine-learning approach to disentangle the role of covariates and elucidate individual relationships with SOC, without imposing expected relationships a priori. While we observe qualitatively similar relationships between SOC and covariates in observations and models, the magnitude and degree of non-linearity vary substantially among the models and observations. Models appear to overemphasize the importance of temperature and primary productivity (especially in forests and herbaceous biomes, respectively), while observations suggest a greater relative importance of soil minerals. This mismatch is also evident globally. However, we observe agreement between observations and model outputs in select individual biomes â namely, temperate deciduous forests and grasslands, which both show stronger relationships of SOC stocks with temperature and productivity, respectively. This approach highlights biomes with the largest uncertainty and mismatch with observations for targeted model improvements. Understanding the role of dominant SOC controls, and the discrepancies between models and observations, globally and across biomes, is essential for improving and validating process representations in soil and ecosystem models for projections under novel future conditions
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Global ecological predictors of the soil priming effect.
Identifying the global drivers of soil priming is essential to understanding C cycling in terrestrial ecosystems. We conducted a survey of soils across 86 globally-distributed locations, spanning a wide range of climates, biotic communities, and soil conditions, and evaluated the apparent soil priming effect using 13C-glucose labeling. Here we show that the magnitude of the positive apparent priming effect (increase in CO2 release through accelerated microbial biomass turnover) was negatively associated with SOC content and microbial respiration rates. Our statistical modeling suggests that apparent priming effects tend to be negative in more mesic sites associated with higher SOC contents. In contrast, a single-input of labile C causes positive apparent priming effects in more arid locations with low SOC contents. Our results provide solid evidence that SOC content plays a critical role in regulating apparent priming effects, with important implications for the improvement of C cycling models under global change scenarios
Effect of cover crop on carbon distribution in size and density separated soil aggregates
Increasing soil organic carbon (SOC) stocks in agricultural soils can contribute to stabilizing or even lowering atmospheric greenhouse gas (GHG) concentrations. Cover crop rotation has been shown to increase SOC and provide productivity benefits for agriculture. Here we used a split field design to evaluate the short-term effect of cover crop on SOC distribution and chemistry using a combination of bulk, isotopic, and spectroscopic analyses of size-and density-separated soil aggregates. Macroaggregates (\u3e250 ”m) incorporated additional plant material with cover crop as evidenced by more negative ÎŽ13C values (â25.4%â with cover crop compared to â25.1%âwithout cover crop) and increased phenolic (plant-like) resonance in carbon NEXAFS spectra. Iron EXAFS data showed that the Fe pool was composed of 17â21% Fe oxide with the remainder a mix of primary and secondary minerals. Comparison of oxalate and dithionite extractions suggests that cover crop may also increase Fe oxide crystallinity, especially in the dense (\u3e2.4 g cmâ3) soil fraction. Cover crop ÎŽ13C values were more negative across density fractions of bulk soil, indicating the presence of less processed organic carbon. Although no significant difference was observed in bulk SOC on a mass per mass basis between cover and no cover crop fields after one season, isotopic and spectroscopic data reveal enhanced carbon movement between aggregates in cover crop soil
SoDaH: the SOils DAta Harmonization database, an open-source synthesis of soil data from research networks, version 1.0
Data collected from research networks present opportunities to test theories and develop models about factors responsible for the long-term persistence and vulnerability of soil organic matter (SOM). Synthesizing datasets collected by different research networks presents opportunities to expand the ecological gradients and scientific breadth of information available for inquiry. Synthesizing these data is challenging, especially considering the legacy of soil data that have already been collected and an expansion of new network science initiatives. To facilitate this effort, here we present the SOils DAta Harmonization database (SoDaH; https://lter.github.io/som-website, last access: 22 December 2020), a flexible database designed to harmonize diverse SOM datasets from multiple research networks. SoDaH is built on several network science efforts in the United States, but the tools built for SoDaH aim to provide an open-access resource to facilitate synthesis of soil carbon data. Moreover, SoDaH allows for individual locations to contribute results from experimental manipulations, repeated measurements from long-term studies, and local- to regional-scale gradients across ecosystems or landscapes. Finally, we also provide data visualization and analysis tools that can be used to query and analyze the aggregated database. The SoDaH v1.0 dataset is archived and available at https://doi.org/10.6073/pasta/9733f6b6d2ffd12bf126dc36a763e0b4 (Wieder et al., 2020)
An open-source database for the synthesis of soil radiocarbon data: International Soil Radiocarbon Database (ISRaD) version 1.0
Radiocarbon is a critical constraint on our estimates of the timescales of soil carbon cycling that can aid in identifying mechanisms of carbon stabilization and destabilization and improve the forecast of soil carbon response to management or environmental change. Despite the wealth of soil radiocarbon data that have been reported over the past 75 years, the ability to apply these data to global-scale questions is limited by our capacity to synthesize and compare measurements generated using a variety of methods. Here, we present the International Soil Radiocarbon Database (ISRaD; http://soilradiocarbon.org, last access: 16 December 2019), an open-source archive of soil data that include reported measurements from bulk soils, distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods, samples of soil gas or water collected interstitially from within an intact soil profile, CO2 gas isolated from laboratory soil incubations, and fluxes collected in situ from a soil profile. The core of ISRaD is a relational database structured around individual datasets (entries) and organized hierarchically to report soil radiocarbon data, measured at different physical and temporal scales as well as other soil or environmental properties that may also be measured and may assist with interpretation and context. Anyone may contribute their own data to the database by entering it into the ISRaD template and subjecting it to quality assurance protocols. ISRaD can be accessed through (1) a web-based interface, (2) an R package (ISRaD), or (3) direct access to code and data through the GitHub repository, which hosts both code and data. The design of ISRaD allows for participants to become directly involved in the management, design, and application of ISRaD data. The synthesized dataset is available in two forms: the original data as reported by the authors of the datasets and an enhanced dataset that includes ancillary geospatial data calculated within the ISRaD framework. ISRaD also provides data management tools in the ISRaD-R package that provide a starting point for data analysis; as an open-source project, the broader soil community is invited and encouraged to add data, tools, and ideas for improvement. As a whole, ISRaD provides resources to aid our evaluation of soil dynamics across a range of spatial and temporal scales. The ISRaD v1.0 dataset is archived and freely available at https://doi.org/10.5281/zenodo.2613911 (Lawrence et al., 2019).Max Planck Institute for Biogeochemistry; European Research CouncilEuropean Research Council (ERC) [695101]; USGS Land Change Science mission area; US Department of AgricultureUnited States Department of Agriculture (USDA) [2018-67003-27935]; US Geological Survey Powell Center for the working group on Soil Carbon Storage and FeedbacksOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
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Early spring, severe frost events, and drought induce rapid carbon loss in high elevation meadows.
By the end of the 20th century, the onset of spring in the Sierra Nevada mountain range of California has been occurring on average three weeks earlier than historic records. Superimposed on this trend is an increase in the presence of highly anomalous "extreme" years, where spring arrives either significantly late or early. The timing of the onset of continuous snowpack coupled to the date at which the snowmelt season is initiated play an important role in the development and sustainability of mountain ecosystems. In this study, we assess the impact of extreme winter precipitation variation on aboveground net primary productivity and soil respiration over three years (2011 to 2013). We found that the duration of snow cover, particularly the timing of the onset of a continuous snowpack and presence of early spring frost events contributed to a dramatic change in ecosystem processes. We found an average 100% increase in soil respiration in 2012 and 2103, compared to 2011, and an average 39% decline in aboveground net primary productivity observed over the same time period. The overall growing season length increased by 57 days in 2012 and 61 days in 2013. These results demonstrate the dependency of these keystone ecosystems on a stable climate and indicate that even small changes in climate can potentially alter their resiliency