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Sustainable soil carbon sequestration practices need to be rapidly scaled up and implemented to contribute to climate change mitigation. We highlight that the major potential for carbon sequestration is in cropland soils, especially those with large yield gaps and/or large historic soil organic carbon losses. The implementation of soil carbon sequestration measures requires a diverse set of options, each adapted to local soil conditions and management opportunities, and accounting for site-specific trade-offs. We propose the establishment of a soil information system containing localised information on soil group, degradation status, crop yield gap, and the associated carbon-sequestration potentials, as well as the provision of incentives and policies to translate management options into region- and soil-specific practices.

Perennial grass pastures are being increasingly adopted, but little is known about the flows of carbon (C) from photosynthesis into soil organic matter (SOM) that could be used for calculations in carbon accounting. Repeat-pulse labelling of perennial grass pastures (kikuyu and Rhodes grass) with [sup.14]C in the field in Western Australia was used to trace the allocation of C to SOM fractions and to determine the stability of each fraction over an extended period. For kikuyu, >40% of the [sup.14]C fed to the plants was allocated belowground within 10 days of labelling, and after 1 year half of this remained. Allocation of [sup.14]C belowground under Rhodes grass ranged between 20 and 24% of [sup.14]C applied and remained constant for up to 6 months. At least 90% of the [sup.14]C belowground was found in the surface 300 mm of soil. The allocation of [sup.14]C to the coarse (50 µm-2 mm) and fine ( Additional keywords: [sup.14]C pulse-labelling, C sequestration, kikuyu, Rhodes grass, coarse SOM fraction, fine SOM fraction, soil carbon., Introduction Replacement of annual grasses with perennial grasses has been promoted as an environment-friendly agricultural management practice for increasing rates of carbon (C) sequestration in soil. Perennial-based grass pastures have [...]

Quantifying the content and composition of soil carbon in the laboratory is time-consuming, requires specialised equipment and is therefore expensive. Rapid, simple and low-cost accurate methods of analysis are required to support current interests in carbon accounting. This study was completed to develop national and state- based models capable of predicting soil carbon content and composition by coupling diffuse reflectance mid-infrared (MIR) spectra with partial least-squares regression (PLSR) analyses. Total, organic and inorganic carbon contents were determined and MIR spectra acquired for 20 495 soil samples collected from 4526 locations from soil depths to 1 m within Australia's agricultural regions. However, all subsequent MIR/PLSR models were developed using soils only collected from the 0-10, 10-20 and 20-30 cm depth layers. The extent of grinding applied to air-dried soil samples was found to be an important determinant of the variability in acquired MIR spectra. After standardisation of the grinding time, national MIR/PLSR models were developed using an independent test-set validation approach to predict the square-root transformed contents of total, organic and inorganic carbon and total nitrogen. Laboratory fractionation of soil organic carbon into particulate, humus and resistant forms was completed on 312 soil samples. Reliable national MIR/PLSR models were developed using cross-validation to predict the contents of these soil organic carbon fractions; however, further work is required to enhance the representation of soils with significant contents of inorganic carbon. Regional MIR/PLSR models developed for total, organic and inorganic carbon and total nitrogen contents were found to produce more reliable and accurate predictions than the national models. The MIR/PLSR approach offers a more rapid and more cost effective method, relative to traditional laboratory methods, to derive estimates of the content and composition of soil carbon and total nitrogen content provided that the soils are well represented by the calibration samples used to build the predictive models. Additional keywords: humus organic carbon, mid-infrared spectroscopy, partial least squares regression, particulate organic carbon, resistant organic carbon, soil organic carbon, soil inorganic carbon., Received 8 March 2013, accepted 6 December 2013, published online 20 December 2013 Introduction The total carbon (TC) content of soil represents the sum of the contents of organic C [...]

Soil organic carbon (OC) exists as a diverse mixture of organic materials with different susceptibilities to biological decomposition. Computer simulation models constructed to predict the dynamics of soil OC have dealt with this diversity using a series of conceptual pools differentiated from one another by the magnitude of their respective decomposition rate constants. Research has now shown that the conceptual pools can be replaced by measureable fractions of soil OC separated on the basis of physical and chemical properties. In this study, an automated protocol for allocating soil OC to coarse (>50 µm) and fine ([less than or equal to] 50 µm) fractions was assessed. Automating the size fractionation process was shown to reduce operator dependence and variability between replicate analyses. Solid-state [sup.13]C nuclear magnetic resonance spectroscopy was used to quantify the content of biologically resistant poly-aryl carbon in the coarse and fine size fractions. Cross-polarisation analyses were completed for coarse and fine fractions of 312 soils, and direct polarisation analyses were completed for 38 representative fractions. Direct polarisation analyses indicated that the resistant poly-aryl carbon was under-represented in the cross-polarisation analyses, on average, by a factor of ~2. Combining this underrepresentation with a spectral analysis process allowed the proportion of coarse- and fine- fraction OC existing as resistant poly-aryl C to be defined. The content of resistant OC was calculated as the sum of that found in the coarse and fine fractions. Contents of particulate and humus OC were calculated after subtracting the resistant OC from the coarse and fine fractions, respectively. Across the 312 soils analysed, substantial variations in the contents of humus, particulate, and resistant carbon were noted, with respective average values of 9.4, 4.0, and 4.5 g fraction C/kg soil obtained. When expressed as a proportion of the OC present in each soil, the humus, particulate, and resistant OC accounted for 56, 19, and 26%, respectively. The nuclear magnetic resonance analyses also indicated that the use of a 50-µm sieve to differentiate particulate (>50µm) from humus (≤ 50 µm) forms of OC provided an effective separation based on extents of decomposition. The procedures developed in this study provided a means to differentiate three biologically significant forms of soil OC based on size, extent of decomposition, and chemical composition (poly-aryl content). Additional keywords: charcoal, humus, nuclear magnetic resonance spectroscopy, particulate, resistant, soil organic carbon, SOC., Received 21 December 2012, accepted 21 July 2013, published online 20 December 2013 Introduction Soil organic carbon (OC) is composed of a variety of materials that originate predominantly from carbon [...]

Competing Interests: Competing interests statement:The authors declare no competing interest.

Blue carbon habitats, including salt marshes, can sequester carbon at rates that are an order of magnitude greater than terrestrial forests. This ecosystem service may be under threat from nitrate (NO 3 - ) enrichment, which can shift the microbial community and stimulate decomposition of organic matter. Despite efforts to mitigate nitrogen loading, salt marshes continue to experience chronic NO 3 - enrichment, however, the long-term consequence of this enrichment on carbon storage remains unclear. To investigate the effect of chronic NO 3 - exposure on salt marsh organic matter decomposition, we collected sediments from three sites across a range of prior NO 3 - exposure: a relatively pristine marsh, a marsh enriched to ~70 μmol L -1 NO 3 - in the flooding seawater for 13 years, and a marsh enriched between 100 and 1000 μmol L -1 for 40 years from wastewater treatment effluent. We collected sediments from 20 to 25 cm depth and determined that sediments from the most chronically enriched site had less bioavailable organic matter and a distinct assemblage of active microbial taxa compared to the other two sites. We also performed a controlled anaerobic decomposition experiment to test whether the legacy of NO 3 - exposure influenced the functional response to additional NO 3 - . We found significant changes to microbial community composition resulting from experimental NO 3 - addition. Experimental NO 3 - addition also increased microbial respiration in sediments collected from all sites. However, sediments from the most chronically enriched site exhibited the smallest increase, the lowest rates of total NO 3 - reduction by dissimilatory nitrate reduction to ammonium (DNRA), and the highest DNF:DNRA ratios. Our results suggest that chronic exposure to elevated NO 3 - may lead to residual pools of organic matter that are less biologically available for decomposition. Thus, it is important to consider the legacy of nutrient exposure when examining the carbon cycle of salt marsh sediments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Natural climate solutions can mitigate climate change in the near-term, during a climate-critical window. Yet, persistent misunderstandings about what constitutes a natural climate solution generate unnecessary confusion and controversy, thereby delaying critical mitigation action. Based on a review of scientific literature and best practices, we distill five foundational principles of natural climate solutions (nature-based, sustainable, climate-additional, measurable, and equitable) and fifteen operational principles for practical implementation. By adhering to these principles, practitioners can activate effective and durable natural climate solutions, enabling the rapid and wide-scale adoption necessary to meaningfully contribute to climate change mitigation., (© 2024. The Author(s).)

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., (© 2023 Smithsonian Institution and The Authors. Global Change Biology published by John Wiley & Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Radiocarbon ( 14 C) is a critical tool for understanding the global carbon cycle. During the Anthropocene, two new processes influenced 14 C in atmospheric, land and ocean carbon reservoirs. First, 14 C-free carbon derived from fossil fuel burning has diluted 14 C, at rates that have accelerated with time. Second, 'bomb' 14 C 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 14 C/ 12 C ratio of atmospheric CO 2 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 14 C between the atmosphere, ocean and land. This milestone coincides with a rapid increase in 14 C measurement capacity worldwide. Leveraging future 14 C 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'.

Ecological theory predicts a pulse disturbance results in loss of soil organic carbon and short-term respiration losses that exceed recovery of productivity in many ecosystems. However, fundamental uncertainties remain in our understanding of ecosystem recovery where spatiotemporal variation in structure and function are not adequately represented in conceptual models. Here we show that wildfire in sagebrush shrublands results in multiscale responses that vary with ecosystem properties, landscape position, and their interactions. Consistent with ecological theory, soil pH increased and soil organic carbon (SOC) decreased following fire. In contrast, SOC responses were slope aspect and shrub-microsite dependent, with a larger proportional decrease under previous shrubs on north-facing aspects compared to south-facing ones. In addition, respiratory losses from burned aspects were not significantly different than losses from unburned aspects. We also documented the novel formation of soil inorganic carbon (SIC) with wildfire that differed significantly with aspect and microsite scale. Whereas pH and SIC recovered within 37 months post-fire, SOC stocks remained reduced, especially on north-facing aspects. Spatially, SIC formation was paired with reduced respiration losses, presumably lower partial pressure of carbon dioxide (pCO 2 ), and increased calcium availability, consistent with geochemical models of carbonate formation. Our findings highlight the formation of SIC after fire as a novel short-term sink of carbon in non-forested shrubland ecosystems. Resiliency in sagebrush shrublands may be more complex and integrated across ecosystem to landscape scales than predicted based on current theory., (© 2022. The Author(s).)

Background: High-resolution soil moisture estimates are critical for planning water management and assessing environmental quality. In-situ measurements alone are too costly to support the spatial and temporal resolutions needed for water management. Recent efforts have combined calibration data with machine learning algorithms to fill the gap where high resolution moisture estimates are lacking at the field scale. This study aimed to provide calibrated soil moisture models and methodology for generating gridded estimates of soil moisture at multiple depths, according to user-defined temporal periods, spatial resolution and extent., Methods: We applied nearly one million national library soil moisture records from over 100 sites, spanning the U.S. Midwest and West, to build Quantile Random Forest (QRF) calibration models. The QRF models were built on covariates including soil moisture estimates from North American Land Data Assimilation System (NLDAS), soil properties, climate variables, digital elevation models, and remote sensing-derived indices. We also explored an alternative approach that adopted a regionalized calibration dataset for the Western U.S. The broad-scale QRF models were independently validated according to sampling depths, land cover type, and observation period. We then explored the model performance improved with local samples used for spiking. Finally, the QRF models were applied to estimate soil moisture at the field scale where evaluation was carried out to check estimated temporal and spatial patterns., Results: The broad-scale QRF model showed moderate performance (R 2 = 0.53, RMSE = 0.078 m 3 /m 3 ) when data points from all depth layers (up to 100 cm) were considered for an independent validation. Elevation, NLDAS-derived moisture, soil properties, and sampling depth were ranked as the most important covariates. The best model performance was observed for forest and pasture sites (R 2 > 0.5; RMSE < 0.09 m 3 /m 3 ), followed by grassland and cropland (R 2 > 0.4; RMSE < 0.11 m 3 /m 3 ). Model performance decreased with sampling depths and was slightly lower during the winter months. Spiking the national QRF model with local samples improved model performance by reducing the RMSE to less than 0.05 m 3 /m 3 for grassland sites. At the field scale, model estimates illustrated more accurate temporal trends for surface than subsurface soil layers. Model estimated spatial patterns need to be further improved and validated with management data., Conclusions: The model accuracy for top 0-20 cm soil depth (R 2 > 0.5, RMSE < 0.08 m 3 /m 3 ) showed promise for adopting the methodology for soil moisture monitoring. The success of spiking the national model with local samples showed the need to collect multi-year high frequency ( e.g. , hourly) sensor-based field measurements to improve estimates of soil moisture for a longer time period. Future work should improve model performance for deeper depths with additional hydraulic properties and use of locally-selected calibration datasets., Competing Interests: The authors declare that they have no competing interests., (© 2022 Xia et al.)

Constraining the climate crisis requires urgent action to reduce anthropogenic emissions while simultaneously removing carbon dioxide from the atmosphere. Improved information about the maximum magnitude and spatial distribution of opportunities for additional land-based removals of CO2 is needed to guide on-the-ground decision-making about where to implement climate change mitigation strategies. Here, we present a globally consistent spatial dataset (approximately 500-m resolution) of current, potential, and unrealized potential carbon storage in woody plant biomass and soil organic matter. We also provide a framework for prioritizing actions related to the restoration, management, and maintenance of woody carbon stocks and associated soils. By comparing current to potential carbon storage, while excluding areas critical to food production and human habitation, we find 287 petagrams (PgC) of unrealized potential storage opportunity, of which 78% (224 PgC) is in biomass and 22% (63 PgC) is in soil. Improved management of existing forests may offer nearly three-fourths (206 PgC) of the total unrealized potential, with the majority (71%) concentrated in tropical ecosystems. However, climate change is a source of considerable uncertainty. While additional research is needed to understand the impact of natural disturbances and biophysical feedbacks, we project that the potential for additional carbon storage in woody biomass will increase (+17%) by 2050 despite projected decreases (−12%) in the tropics. Our results establish an absolute reference point and conceptual framework for national and jurisdictional prioritization of locations and actions to increase land-based carbon storage.

Regional consistency is necessary for carbon credit integrity.

Land-based climate mitigation measures have gained significant attention and importance in public and private sector climate policies. Building on previous studies, we refine and update the mitigation potentials for 20 land-based measures in >200 countries and five regions, comparing "bottom-up" sectoral estimates with integrated assessment models (IAMs). We also assess implementation feasibility at the country level. Cost-effective (available up to $100/tCO 2 eq) land-based mitigation is 8-13.8 GtCO 2 eq yr -1 between 2020 and 2050, with the bottom end of this range representing the IAM median and the upper end representing the sectoral estimate. The cost-effective sectoral estimate is about 40% of available technical potential and is in line with achieving a 1.5°C pathway in 2050. Compared to technical potentials, cost-effective estimates represent a more realistic and actionable target for policy. The cost-effective potential is approximately 50% from forests and other ecosystems, 35% from agriculture, and 15% from demand-side measures. The potential varies sixfold across the five regions assessed (0.75-4.8 GtCO2eq yr -1 ) and the top 15 countries account for about 60% of the global potential. Protection of forests and other ecosystems and demand-side measures present particularly high mitigation efficiency, high provision of co-benefits, and relatively lower costs. The feasibility assessment suggests that governance, economic investment, and socio-cultural conditions influence the likelihood that land-based mitigation potentials are realized. A substantial portion of potential (80%) is in developing countries and LDCs, where feasibility barriers are of greatest concern. Assisting countries to overcome barriers may result in significant quantities of near-term, low-cost mitigation while locally achieving important climate adaptation and development benefits. Opportunities among countries vary widely depending on types of land-based measures available, their potential co-benefits and risks, and their feasibility. Enhanced investments and country-specific plans that accommodate this complexity are urgently needed to realize the large global potential from improved land stewardship., (© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Mangroves have among the highest carbon densities of any tropical forest. These 'blue carbon' ecosystems can store large amounts of carbon for long periods, and their protection reduces greenhouse gas emissions and supports climate change mitigation. Incorporating mangroves into Nationally Determined Contributions to the Paris Agreement and their valuation on carbon markets requires predicting how the management of different land-uses can prevent future greenhouse gas emissions and increase CO 2 sequestration. We integrated comprehensive global datasets for carbon stocks, mangrove distribution, deforestation rates, and land-use change drivers into a predictive model of mangrove carbon emissions. We project emissions and foregone soil carbon sequestration potential under 'business as usual' rates of mangrove loss. Emissions from mangrove loss could reach 2391 Tg CO 2 eq by the end of the century, or 3392 Tg CO 2 eq when considering foregone soil carbon sequestration. The highest emissions were predicted in southeast and south Asia (West Coral Triangle, Sunda Shelf, and the Bay of Bengal) due to conversion to aquaculture or agriculture, followed by the Caribbean (Tropical Northwest Atlantic) due to clearing and erosion, and the Andaman coast (West Myanmar) and north Brazil due to erosion. Together, these six regions accounted for 90% of the total potential CO 2 eq future emissions. Mangrove loss has been slowing, and global emissions could be more than halved if reduced loss rates remain in the future. Notably, the location of global emission hotspots was consistent with every dataset used to calculate deforestation rates or with alternative assumptions about carbon storage and emissions. Our results indicate the regions in need of policy actions to address emissions arising from mangrove loss and the drivers that could be managed to prevent them., (© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Recent developments in diffuse reflectance soil spectroscopy have increasingly focused on building and using large soil spectral libraries with the purpose of supporting many activities relevant to monitoring, mapping and managing soil resources. A potential limitation of using a mid-infrared (MIR) spectral library developed by another laboratory is the need to account for inherent differences in the signal strength at each wavelength associated with different instrumental and environmental conditions. Here we apply predictive models built using the USDA National Soil Survey Center-Kellogg Soil Survey Laboratory (NSSC-KSSL) MIR spectral library ( n = 56,155) to samples sets of European and US origin scanned on a secondary spectrometer to assess the need for calibration transfer using a piecewise direct standardization (PDS) approach in transforming spectra before predicting carbon cycle relevant soil properties (bulk density, CaCO 3 , organic carbon, clay and pH). The European soil samples were from the land use/cover area frame statistical survey (LUCAS) database available through the European Soil Data Center (ESDAC), while the US soil samples were from the National Ecological Observatory Network (NEON). Additionally, the performance of the predictive models on PDS transfer spectra was tested against the direct calibration models built using samples scanned on the secondary spectrometer. On independent test sets of European and US origin, PDS improved predictions for most but not all soil properties with memory based learning (MBL) models generally outperforming partial least squares regression and Cubist models. Our study suggests that while good-to-excellent results can be obtained without calibration transfer, for most of the cases presented in this study, PDS was necessary for unbiased predictions. The MBL models also outperformed the direct calibration models for most of the soil properties. For laboratories building new spectroscopy capacity utilizing existing spectral libraries, it appears necessary to develop calibration transfer using PDS or other calibration transfer techniques to obtain the least biased and most precise predictions of different soil properties.

Policies aiming to preserve vegetated coastal ecosystems (VCE; tidal marshes, mangroves and seagrasses) to mitigate greenhouse gas emissions require national assessments of blue carbon resources. Here, we present organic carbon (C) storage in VCE across Australian climate regions and estimate potential annual CO 2 emission benefits of VCE conservation and restoration. Australia contributes 5-11% of the C stored in VCE globally (70-185 Tg C in aboveground biomass, and 1,055-1,540 Tg C in the upper 1 m of soils). Potential CO 2 emissions from current VCE losses are estimated at 2.1-3.1 Tg CO 2 -e yr -1 , increasing annual CO 2 emissions from land use change in Australia by 12-21%. This assessment, the most comprehensive for any nation to-date, demonstrates the potential of conservation and restoration of VCE to underpin national policy development for reducing greenhouse gas emissions.

Salt marshes sequester carbon at rates more than an order of magnitude greater than their terrestrial counterparts, helping to mitigate climate change. As nitrogen loading to coastal waters continues, primarily in the form of nitrate, it is unclear what effect it will have on carbon storage capacity of these highly productive systems. This uncertainty is largely driven by the dual role nitrate can play in biological processes, where it can serve as a nutrient-stimulating primary production or a thermodynamically favorable electron acceptor fueling heterotrophic metabolism. Here, we used a controlled flow-through reactor experiment to test the role of nitrate as an electron acceptor, and its effect on organic matter decomposition and the associated microbial community in salt marsh sediments. Organic matter decomposition significantly increased in response to nitrate, even at sediment depths typically considered resistant to decomposition. The use of isotope tracers suggests that this pattern was largely driven by stimulated denitrification. Nitrate addition also significantly altered the microbial community and decreased alpha diversity, selecting for taxa belonging to groups known to reduce nitrate and oxidize more complex forms of organic matter. Fourier Transform-Infrared Spectroscopy further supported these results, suggesting that nitrate facilitated decomposition of complex organic matter compounds into more bioavailable forms. Taken together, these results suggest the existence of organic matter pools that only become accessible with nitrate and would otherwise remain stabilized in the sediment. The existence of such pools could have important implications for carbon storage, since greater decomposition rates as N loading increases may result in less overall burial of organic-rich sediment. Given the extent of nitrogen loading along our coastlines, it is imperative that we better understand the resilience of salt marsh systems to nutrient enrichment, especially if we hope to rely on salt marshes, and other blue carbon systems, for long-term carbon storage., (© 2019 John Wiley & Sons Ltd.)

To predict the behavior of the terrestrial carbon cycle, it is critical to understand the source, formation pathway, and chemical composition of soil organic matter (SOM). There is emerging consensus that slow-cycling SOM generally consists of relatively low molecular weight organic carbon substrates that enter the mineral soil as dissolved organic matter and associate with mineral surfaces (referred to as "mineral-associated OM," or MAOM). However, much debate and contradictory evidence persist around: (a) whether the organic C substrates within the MAOM pool primarily originate from aboveground vs. belowground plant sources and (b) whether C substrates directly sorb to mineral surfaces or undergo microbial transformation prior to their incorporation into MAOM. Here, we attempt to reconcile disparate views on the formation of MAOM by proposing a spatially explicit set of processes that link plant C source with MAOM formation pathway. Specifically, because belowground vs. aboveground sources of plant C enter spatially distinct regions of the mineral soil, we propose that fine-scale differences in microbial abundance should determine the probability of substrate-microbe vs. substrate-mineral interaction. Thus, formation of MAOM in areas of high microbial density (e.g., the rhizosphere and other microbial hotspots) should primarily occur through an in vivo microbial turnover pathway and favor C substrates that are first biosynthesized with high microbial carbon-use efficiency prior to incorporation in the MAOM pool. In contrast, in areas of low microbial density (e.g., certain regions of the bulk soil), MAOM formation should primarily occur through the direct sorption of intact or partially oxidized plant compounds to uncolonized mineral surfaces, minimizing the importance of carbon-use efficiency, and favoring C substrates with strong "sorptive affinity." Through this framework, we thus describe how the primacy of biotic vs. abiotic controls on MAOM dynamics is not mutually exclusive, but rather spatially dictated. Such an understanding may be integral to more accurately modeling soil organic matter dynamics across different spatial scales., (© 2018 John Wiley & Sons Ltd.)

Limiting climate warming to <2°C requires increased mitigation efforts, including land stewardship, whose potential in the United States is poorly understood. We quantified the potential of natural climate solutions (NCS)-21 conservation, restoration, and improved land management interventions on natural and agricultural lands-to increase carbon storage and avoid greenhouse gas emissions in the United States. We found a maximum potential of 1.2 (0.9 to 1.6) Pg CO 2 e year -1 , the equivalent of 21% of current net annual emissions of the United States. At current carbon market prices (USD 10 per Mg CO 2 e), 299 Tg CO 2 e year -1 could be achieved. NCS would also provide air and water filtration, flood control, soil health, wildlife habitat, and climate resilience benefits.

Decomposition of plant litter is a key control over carbon (C) storage in the soil. The biochemistry of the litter being produced, the environment in which the decomposition is taking place, and the community composition and metabolism of the decomposer organisms exert a combined influence over decomposition rates. As deciduous shrubs and trees are expanding into tundra ecosystems as a result of regional climate warming, this change in vegetation represents a change in litter input to tundra soils and a change in the environment in which litter decomposes. To test the importance of litter biochemistry and environment in determining litter mass loss, we reciprocally transplanted litter between heath (Empetrum nigrum), shrub (Betula nana), and forest (Betula pubescens) at a sub-Arctic treeline in Sweden. As expansion of shrubs and trees promotes deeper snow, we also used a snow fence experiment in a tundra heath environment to understand the importance of snow depth, relative to other factors, in the decomposition of litter. Our results show that B. pubescens and B. nana leaf litter decomposed at faster rates than E. nigrum litter across all environments, while all litter species decomposed at faster rates in the forest and shrub environments than in the tundra heath. The effect of increased snow on decomposition was minimal, leading us to conclude that microbial activity over summer in the productive forest and shrub vegetation is driving increased mass loss compared to the heath. Using B. pubescens and E. nigrum litter, we demonstrate that degradation of carbohydrate-C is a significant driver of mass loss in the forest. This pathway was less prominent in the heath, which is consistent with observations that tundra soils typically have high concentrations of "labile" C. This experiment suggests that further expansion of shrubs and trees may stimulate the loss of undecomposed carbohydrate C in the tundra., (© 2018 The Authors. Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.)

Potential natural vegetation (PNV) is the vegetation cover in equilibrium with climate, that would exist at a given location if not impacted by human activities. PNV is useful for raising public awareness about land degradation and for estimating land potential. This paper presents results of assessing machine learning algorithms-neural networks (nnet package), random forest (ranger), gradient boosting (gbm), K-nearest neighborhood (class) and Cubist-for operational mapping of PNV. Three case studies were considered: (1) global distribution of biomes based on the BIOME 6000 data set (8,057 modern pollen-based site reconstructions), (2) distribution of forest tree taxa in Europe based on detailed occurrence records (1,546,435 ground observations), and (3) global monthly fraction of absorbed photosynthetically active radiation (FAPAR) values (30,301 randomly-sampled points). A stack of 160 global maps representing biophysical conditions over land, including atmospheric, climatic, relief, and lithologic variables, were used as explanatory variables. The overall results indicate that random forest gives the overall best performance. The highest accuracy for predicting BIOME 6000 classes (20) was estimated to be between 33% (with spatial cross-validation) and 68% (simple random sub-setting), with the most important predictors being total annual precipitation, monthly temperatures, and bioclimatic layers. Predicting forest tree species (73) resulted in mapping accuracy of 25%, with the most important predictors being monthly cloud fraction, mean annual and monthly temperatures, and elevation. Regression models for FAPAR (monthly images) gave an R-square of 90% with the most important predictors being total annual precipitation, monthly cloud fraction, CHELSA bioclimatic layers, and month of the year, respectively. Further developments of PNV mapping could include using all GBIF records to map the global distribution of plant species at different taxonomic levels. This methodology could also be extended to dynamic modeling of PNV, so that future climate scenarios can be incorporated. Global maps of biomes, FAPAR and tree species at one km spatial resolution are available for download via http://dx.doi.org/10.7910/DVN/QQHCIK., Competing Interests: Tomislav Hengl and Ichsani Wheeler are employed by Envirometrix Ltd.

Delgado-Baquerizo et al . ( Science Advances , 12 April 2017, e1602008) use statistical correlations to infer that paleoclimate (6000 to 22,000 years ago) is a more important driver of current soil organic carbon stocks than the current-day climate. On the other hand, a wealth of radiocarbon measurements indicates that the organic carbon in most topsoils is only a few decades to perhaps a few centuries old. These seemingly incongruous results can perhaps be reconciled by considering that the long-term pedogenic development of a soil strongly influences the physiochemical properties, which lead to stabilization of new carbon entering that soil regardless of current climate.

Better stewardship of land is needed to achieve the Paris Climate Agreement goal of holding warming to below 2 °C; however, confusion persists about the specific set of land stewardship options available and their mitigation potential. To address this, we identify and quantify "natural climate solutions" (NCS): 20 conservation, restoration, and improved land management actions that increase carbon storage and/or avoid greenhouse gas emissions across global forests, wetlands, grasslands, and agricultural lands. We find that the maximum potential of NCS-when constrained by food security, fiber security, and biodiversity conservation-is 23.8 petagrams of CO 2 equivalent (PgCO 2 e) y -1 (95% CI 20.3-37.4). This is ≥30% higher than prior estimates, which did not include the full range of options and safeguards considered here. About half of this maximum (11.3 PgCO 2 e y -1 ) represents cost-effective climate mitigation, assuming the social cost of CO 2 pollution is ≥100 USD MgCO 2 e -1 by 2030. Natural climate solutions can provide 37% of cost-effective CO 2 mitigation needed through 2030 for a >66% chance of holding warming to below 2 °C. One-third of this cost-effective NCS mitigation can be delivered at or below 10 USD MgCO 2 -1 Most NCS actions-if effectively implemented-also offer water filtration, flood buffering, soil health, biodiversity habitat, and enhanced climate resilience. Work remains to better constrain uncertainty of NCS mitigation estimates. Nevertheless, existing knowledge reported here provides a robust basis for immediate global action to improve ecosystem stewardship as a major solution to climate change., Competing Interests: The authors declare no conflict of interest.

Human appropriation of land for agriculture has greatly altered the terrestrial carbon balance, creating a large but uncertain carbon debt in soils. Estimating the size and spatial distribution of soil organic carbon (SOC) loss due to land use and land cover change has been difficult but is a critical step in understanding whether SOC sequestration can be an effective climate mitigation strategy. In this study, a machine learning-based model was fitted using a global compilation of SOC data and the History Database of the Global Environment (HYDE) land use data in combination with climatic, landform and lithology covariates. Model results compared favorably with a global compilation of paired plot studies. Projection of this model onto a world without agriculture indicated a global carbon debt due to agriculture of 133 Pg C for the top 2 m of soil, with the rate of loss increasing dramatically in the past 200 years. The HYDE classes "grazing" and "cropland" contributed nearly equally to the loss of SOC. There were higher percent SOC losses on cropland but since more than twice as much land is grazed, slightly higher total losses were found from grazing land. Important spatial patterns of SOC loss were found: Hotspots of SOC loss coincided with some major cropping regions as well as semiarid grazing regions, while other major agricultural zones showed small losses and even net gains in SOC. This analysis has demonstrated that there are identifiable regions which can be targeted for SOC restoration efforts., Competing Interests: The authors declare no conflict of interest.

Seagrass ecosystems have recently been identified for their role in climate change mitigation due to their globally-significant carbon sinks; yet, the capacity of seagrasses to sequester carbon has been shown to vary greatly among seagrass ecosystems. The recalcitrant nature of seagrass tissues, or the resistance to degradation back into carbon dioxide, is one aspect thought to influence sediment carbon stocks. In this study, a global survey investigated how the macromolecular chemistry of seagrass leaves, sheaths/stems, rhizomes and roots varied across 23 species from 16 countries. The goal was to understand how this seagrass chemistry might influence the capacity of seagrasses to contribute to sediment carbon stocks. Three non-destructive analytical chemical analyses were used to investigate seagrass chemistry: thermogravimetric analysis (TGA) and solid state 13 C-NMR and infrared spectroscopy. A strong latitudinal influence on carbon quality was found, whereby temperate seagrasses contained 5% relatively more labile carbon, and tropical seagrasses contained 3% relatively more refractory carbon. Sheath/stem tissues significantly varied across taxa, with larger morphologies typically containing more refractory carbon than smaller morphologies. Rhizomes were characterized by a higher proportion of labile carbon (16% of total organic matter compared to 8-10% in other tissues); however, high rhizome biomass production and slower remineralization in anoxic sediments will likely enhance these below-ground tissues' contributions to long-term carbon stocks. Our study provides a standardized and global dataset on seagrass carbon quality across tissue types, taxa and geography that can be incorporated in carbon sequestration and storage models as well as ecosystem valuation and management strategies.

Seagrass ecosystems are significant carbon sinks, and their resident microbial communities ultimately determine the quantity and quality of carbon sequestered. However, environmental perturbations have been predicted to affect microbial-driven seagrass decomposition and subsequent carbon sequestration. Utilizing techniques including 16S-rDNA sequencing, solid-state NMR and microsensor profiling, we tested the hypothesis that elevated seawater temperatures and eutrophication enhance the microbial decomposition of seagrass leaf detritus and rhizome/root tissues. Nutrient additions had a negligible effect on seagrass decomposition, indicating an absence of nutrient limitation. Elevated temperatures caused a 19% higher biomass loss for aerobically decaying leaf detritus, coinciding with changes in bacterial community structure and enhanced lignocellulose degradation. Although, community shifts and lignocellulose degradation were also observed for rhizome/root decomposition, anaerobic decay was unaffected by temperature. These observations suggest that oxygen availability constrains the stimulatory effects of temperature increases on bacterial carbon remineralization, possibly through differential temperature effects on bacterial functional groups, including putative aerobic heterotrophs (e.g. Erythrobacteraceae, Hyphomicrobiaceae) and sulfate reducers (e.g. Desulfobacteraceae). Consequently, under elevated seawater temperatures, carbon accumulation rates may diminish due to higher remineralization rates at the sediment surface. Nonetheless, the anoxic conditions ubiquitous to seagrass sediments can provide a degree of carbon protection under warming seawater temperatures., (© FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Seagrasses are among the Earth's most efficient and long-term carbon sinks, but coastal development threatens this capacity. We report new evidence that disturbance to seagrass ecosystems causes release of ancient carbon. In a seagrass ecosystem that had been disturbed 50 years ago, we found that soil carbon stocks declined by 72%, which, according to radiocarbon dating, had taken hundreds to thousands of years to accumulate. Disturbed soils harboured different benthic bacterial communities (according to 16S rRNA sequence analysis), with higher proportions of aerobic heterotrophs compared with undisturbed. Fingerprinting of the carbon (via stable isotopes) suggested that the contribution of autochthonous carbon (carbon produced through plant primary production) to the soil carbon pool was less in disturbed areas compared with seagrass and recovered areas. Seagrass areas that had recovered from disturbance had slightly lower (35%) carbon levels than undisturbed, but more than twice as much as the disturbed areas, which is encouraging for restoration efforts. Slow rates of seagrass recovery imply the need to transplant seagrass, rather than waiting for recovery via natural processes. This study empirically demonstrates that disturbance to seagrass ecosystems can cause release of ancient carbon, with potentially major global warming consequences., (© 2015 The Author(s).)

Rotational grazing management strategies have been promoted as a way to improve the sustainability of native grass-based pasture systems. From disturbance ecology theory, rotational grazing relative to continuous grazing can increase pasture productivity by allowing vegetation to recover after short intense grazing periods. This project sought to assess whether soil organic carbon (SOC) stocks would also increase with adoption of rotational grazing management. Twelve pairs of rotationally and continuously grazed paddocks were sampled across a rainfall gradient in South Australia. Pasture productivity approximated as the normalized difference vegetation index (NDVI) was on average no different between management categories, but when the data from all sites were aggregated as log response ratios (rotational/continuous) a significant positive trend of increasing NDVI under rotational grazing relative to continuous grazing was found (R2 = 0.52). Mean SOC stocks (0-30 cm) were 48.3 Mg C ha-1 with a range of 20-80 Mg C ha-1 across the study area with no differences between grazing management categories. SOC stocks were well correlated with rainfall and temperature (multiple linear regression R2 = 0.61). After removing the influence of climate on SOC stocks, the management variables, rest periods, stocking rate and grazing days, were found to be significantly correlated with SOC, explaining 22% of the variance in SOC, but there were still no clear differences in SOC stocks at paired sites. We suggest three reasons for the lack of SOC response. First, changes in plant productivity and turnover in low-medium rainfall regions due to changes in grazing management are small and slow, so we would only expect at best small incremental changes in SOC stocks. This is compounded by the inherent variability within and between paddocks making detection of a small real change difficult on short timescales. Lastly, the management data suggests that there is a gradation in implementation of rotational grazing and the use of two fixed categories (i.e. rotational v. continuous) may not be the most appropriate method of comparing diverse management styles.