Search

Radiocarbon (14C) is a critical tool for understanding the global carbon cycle. During the Anthropocene, two new processes influenced 14C in atmospheric, land and ocean carbon reservoirs. First, 14C-free carbon derived from fossil fuel burning has diluted 14C, at rates that have accelerated with time. Second, bomb 14C produced by atmospheric nuclear weapon tests in the mid-twentieth century provided a global isotope tracer that is used to constrain rates of air-sea gas exchange, carbon turnover, large-scale atmospheric and ocean transport, and other key C cycle processes. As we write, the 14C/12C ratio of atmospheric CO2 is dropping below pre-industrial levels, and the rate of decline in the future will depend on global fossil fuel use and net exchange of bomb 14C between the atmosphere, ocean and land. This milestone coincides with a rapid increase in 14C measurement capacity worldwide. Leveraging future 14C measurements to understand processes and test models requires coordinated international effort-a decade of radiocarbon with multiple goals: (i) filling observational gaps using archives, (ii) building and sustaining observation networks to increase measurement density across carbon reservoirs, (iii) developing databases, synthesis and modelling tools and (iv) establishing metrics for identifying and verifying changes in carbon sources and sinks. This article is part of the Theo Murphy meeting issue Radiocarbon in the Anthropocene.

Background: Indigenous fire management in northern Australian savannas (beginning at least 11,000 years ago) involved frequent, small, cool, early dry season fires. This fire regime changed after European arrival in the late 1700s to unmanaged fires that burn larger areas, late in the dry season, detrimental to carbon stocks and biodiversity. Aims: Test the hypothesis that significant sequestration of pyrogenic carbon in soil accompanies the reimposition of an Indigenous fire regime. Methods: Savanna soils under the same vegetation, but with the number of fires varying from 0 to 13 (irrespective of the season) between 2000 and 2022 were sampled. Organic and pyrogenic carbon stocks as well as carbon isotope composition of the 0–5 cm soil layer were determined along sample transects with varying fire return intervals. Key results: An average increase of 0.25 MgC ha−1 was observed in soil pyrogenic carbon stocks in transects with ≥5 fires, compared to transects with 0–4 fires, with a small increase in soil organic carbon stocks that was not significant. Conclusions: A return to more frequent fires early in the dry season has the potential to sequester significant pyrogenic carbon in northern Australian savanna soils on decadal timescales. The reimposition of an Indigenous fire regime (frequent, small, cool, early dry season fires) has the potential to sequester significant pyrogenic carbon in northern Australian savanna soils on decadal timescales. We observed an increase of 0.25 MgC ha−1 in transects with ≥5 fires over a 22-year period. [ABSTRACT FROM AUTHOR]

Rapid and cost‐effective techniques for soil analysis are essential to guide sustainable land management and production agriculture. This study aimed at evaluating the performance and consistency of portable handheld Fourier‐transform near‐infrared spectrometers and the NeoSpectra scanners in estimating 12 common soil physical and chemical properties including pH; organic carbon (OC); inorganic carbon (IC); total nitrogen (TN); cation exchange capacity (CEC); clay, silt, and sand fractions; and exchangeable potassium (K), phosphorus (P), calcium (Ca), and magnesium (Mg). A diverse set of samples (n = 600) were retrieved from a national‐scale soil archive of the Kellogg Soil Survey Laboratory of USDA‐NRCS and scanned with five NeoSpectra scanners. Predictive models for the soil properties were developed using partial least squares regression (PLSR), Cubist, and memory‐based learning (MBL). Cubist outperformed PLSR and MBL, with the best prediction performance for clay, OC, and CEC (R2 > 0.7), followed by IC, sand, silt, and Mg (R2 > 0.6), and then pH, TN, and Ca (R2 > 0.5). K and P were predicted somewhat poorly with R2 of 0.48 and 0.22. All five NeoSpectra yielded comparable near‐infrared (NIR) spectral data and the PLSR models for the soil properties (in terms of model regression coefficients). However, the consistency assessment showed that the model performance was significantly decreased when the training and testing spectra were from different NeoSpectra scanners. It is concluded that NeoSpectra scanners could be rapid and cost effective for estimating certain soil properties, and calibration transfer should be considered for applications where multiple devices are involved and high estimation accuracy from NIR data is required. Core Ideas: Soil samples (n = 600) were retrieved from Kellogg Soil Survey Laboratory and analyzed with 5 NeoSpectra scanners.Partial least squares regression (PLSR), Cubist, and memory‐based learning (MBL) were employed to estimate 12 soil properties from NIR data.Cubist outperformed PLSR and MBL, with 10 of 12 properties having R2 > 0.5.The five NeoSpectra scanners yielded comparable NIR spectral data and PLSR models.Cross‐device assessment suggested that calibration transfer is needed to maintain higher accuracy of NIR models. [ABSTRACT FROM AUTHOR]

Quantifying carbon fluxes into and out of coastal soils is critical to meeting greenhouse gas reduction and coastal resiliency goals. Numerous 'blue carbon' studies have generated, or benefitted from, synthetic datasets. However, the community those efforts inspired does not have a centralized, standardized database of disaggregated data used to estimate carbon stocks and fluxes. In this paper, we describe a data structure designed to standardize data reporting, maximize reuse, and maintain a chain of credit from synthesis to original source. We introduce version 1.0.0. of the Coastal Carbon Library, a global database of 6723 soil profiles representing blue carbon‐storing systems including marshes, mangroves, tidal freshwater forests, and seagrasses. We also present the Coastal Carbon Atlas, an R‐shiny application that can be used to visualize, query, and download portions of the Coastal Carbon Library. The majority (4815) of entries in the database can be used for carbon stock assessments without the need for interpolating missing soil variables, 533 are available for estimating carbon burial rate, and 326 are useful for fitting dynamic soil formation models. Organic matter density significantly varied by habitat with tidal freshwater forests having the highest density, and seagrasses having the lowest. Future work could involve expansion of the synthesis to include more deep stock assessments, increasing the representation of data outside of the U.S., and increasing the amount of data available for mangroves and seagrasses, especially carbon burial rate data. We present proposed best practices for blue carbon data including an emphasis on disaggregation, data publication, dataset documentation, and use of standardized vocabulary and templates whenever appropriate. To conclude, the Coastal Carbon Library and Atlas serve as a general example of a grassroots F.A.I.R. (Findable, Accessible, Interoperable, and Reusable) data effort demonstrating how data producers can coordinate to develop tools relevant to policy and decision‐making. [ABSTRACT FROM AUTHOR]

The ability to accurately measure organic carbon (OC) in marine sediments or soils is overall taken for granted in scientific communities, yet this seemingly mundane task remains a methodological challenge when the soil matrix contains calcium carbonate (CaCO3), creating inaccuracies in Blue Carbon estimates. Here, we compared five common methods combining acidification, combustion, and wet oxidation pre‐treatments for determination of OC in sediments and soils containing CaCO3 based on the analyses of artificial soil mixtures made of different OC and CaCO3 contents, and multiple soils from Australian seagrass cores. The results obtained showed that methods involving acidification pre‐treatment entailed −17 ± 0.2% (mean ± SE) underestimation of OC content (ranging from −8% to −26%), whereas the combustion‐based method was accurate for samples with high CaCO3 content but entailed 32–47% overestimation in samples with low CaCO3 content. The Heanes method (wet oxidation method) showed <5% deviation from the known OC content, but this method is not suitable for soil samples containing reduced iron, sulfur and potentially manganese compounds. The differences observed among methods have significant impacts on local, regional, and global Blue Carbon storage calculations. We provide key methodological guidelines for the analysis of OC in soils with high and low CaCO3 contents, aiming at improving accuracy in current Blue Carbon science. [ABSTRACT FROM AUTHOR]

Soil amendments are a broad class of materials that enhance physical, chemical or biological characteristics in croplands, pastures, or rangelands. While organic soil amendments such as manure, mulch and seaweed have well established agronomic benefits, there has been renewed private and governmental interest in quantifying and incentivizing their role in mitigating climate change. Likewise, biostimulants and biopesticides, which are intended to target specific plant or microbial processes, are emerging with claims of improved soil health, crop yields, soil organic carbon sequestration, and greenhouse gas emission reductions. We conducted a literature review to address the climate mitigation potential of organic soil amendments, including biostimulants and biopesticides. In doing so, we identify three elements of climate mitigation through the use of soil amendments: soil organic carbon sequestration, soil greenhouse gas emission reductions, and life cycle emission reductions. We review common soil amendment classes in detail, addressing the empirical evidence (or lack thereof) in which they meet these three elements of climate mitigation. We conclude by suggesting priorities for government and private investment. [ABSTRACT FROM AUTHOR]