Items

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  Soil organic carbon is affected by organic amendments, conservation tillage, and cover cropping in organic farming systems: A meta-analysis

  Meta-analysis is often used to compare how soil health differs between organic and conventional farming systems. However, the burgeoning primary literature on organic farming now allows direct evaluation of the best management practices (BMPs) within organic farming systems on soil health improvements. Therefore, the main objective of this meta-analysis was to investigate the effect of BMPs, such as organic amendments, conservation tillage, and cover cropping, on soil health within organic farming systems. We focused on two principal soil health metrics: soil organic carbon (SOC) and microbial biomass carbon (MBC) concentrations. On average, adoption of BMPs increased depth-weighted SOC and MBC concentrations by 18 and 30 %, respectively, relative to organically-managed control groups. Among BMPs, organic amendments and conservation tillage practices showed net positive effect on soil health with 24 and 14 % increase in depth-weighted SOC concentrations, respectively. Although cover cropping did not have an overall influence on SOC concentrations, we found a temporal trend such that cover cropping significantly increased SOC concentrations after 5 years of its adoption. This indicates that the soil health benefits from BMPs accrue over time and highlights the need of long-term adoptability of BMPs to achieve agricultural sustainability. Future primary articles that focus on under-researched cropping practices in organic systems (e.g., crop rotation length and diversity, biochar addition) and the additive effects of multiple BMPs on soil health, will add to the synthesizable evidence base. Therefore, this meta-analysis confirms the soil health benefits of adopting BMPs within organic farming systems, identifies critical knowledge gaps, and provides directions for future organic farming research.
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  Soil organic carbon stocks maintained despite intensification of shifting cultivation

  Shifting cultivation systems of Southeast Asia are rapidly intensifying, especially through shortening of the fallow periods. It is typically assumed that intensification will result in a depletion of soil organic carbon (SOC) stocks, but existing estimates of carbon stocks in these systems are variable, and there is little certainty about the carbon outcomes of intensification. We investigated the effects of intensification on SOC stocks of a shifting cultivation system in northern Laos. Volume-specific soil samples were collected from 20 sites representing: i) various rotation intensities (fallow periods of 3–4 years and 7–10 years), ii) various stages of the rotation cycle (fallows and active fields) and iii) reference plots (old regrowth of 25–30 years). Samples were analyzed for SOC, soil texture, pH, Total Nitrogen and permanganate oxidizable carbon (POXC) – an active carbon fraction that has been suggested as an easily measured early indicator of land use induced changes in soil quality and SOC. There were no significant differences between SOC concentrations or stocks of any of the sites under shifting cultivation and the reference sites. However, the SOC stock under fallows in the intensive rotation category was significantly larger than the SOC stock under fallows in the extensive rotation category. This is likely because inputs of dead root biomass from the slashed vegetation provides an important input to the SOC pool. Fallow sites under intensive rotation had significantly higher contents of POXC in the topsoil than the active fields, which suggests that POXC captures the immediate effect of the decreased input of litter to the topsoil during the cultivation period. We conclude that in this study there is no evidence that intensification of shifting cultivation leads to a decline in total soil carbon stock, or to a decline in the more active carbon fraction measured by POXC. Therefore, narratives of shifting cultivation leading to a decline in soil carbon stocks need to be revisited, and land use policies related to the system should not uncritically be based on this incorrect assumption.
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  Grand challenges for the 21st century: what crop models can and can't (yet) do

  Crop production is at the core of a ‘perfect storm’ encompassing the grand challenges of achieving food and nutrition security for all, in the face of climate change, while avoiding further conversion of natural habitats for agriculture and loss of biodiversity. Here, we explore current trends in crop modelling related to these grand challenges by reflecting on research presented at the Second International Crop Modelling Symposium (iCropM2020). A keyword search in the book of abstracts of the symposium revealed a strong focus on ‘climate change’, ‘adaptation’ and ‘impact assessment’ and much less on ‘food security’ or ‘policy’. Most research focused on field-level investigations and far fewer on farm(ing) systems levels – the levels at which management decisions are made by farmers. Experimentation is key to development and testing of crop models, yet the term ‘simulation’ outweighed by far the terms ‘experiments’ and ‘trials’, and few contributions dealt with model improvement. Cereals are intensively researched, whereas roots, tubers and tropical perennials are under-researched. Little attention is paid to nutrient limitations apart from nitrogen or to pests and diseases. The aforementioned aspects represent opportunities for future research where crop models can help in devising hypotheses and driving new experimentation. We must also ensure that crop models are fit for their intended purposes, especially if they are to provide advice to policymakers. The latter, together with cross-scale and interdisciplinary efforts with direct engagement of stakeholders are needed to address the grand challenges faced by food and agricultural systems in the next century.
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  Soil and vegetation carbon stocks after land-use changes in a seasonally dry tropical forest

  The lack of robust scientific data still hinders estimates of soil and plant carbon (C) losses due to land-use changes in most dry tropical ecosystems. The present study investigated the effects of land-use and cover changes on total ecosystem C stocks in NE Brazil, aiming to quantify C losses after the removal of the native forest, known as Caatinga. The sampling design included the four main land-use/cover types (Dense Caatinga, Open Caatinga, Pastures and Crop fields) and the seven main soil classes (Arenosols, Acrisols, Regosols, Ferrasols, Luvisols, Planosols, and Leptosols), a combination that represents over 90% of the region. This design resulted in 192 sampling points (48 in each land-use), distributed proportionally to the area of occurrence of each soil class. In each sampling point, we determined C stocks in soil organic matter (SOM) and roots (to a depth of 1 m or rock layer), aboveground vegetation biomass (trees and herbs, separately), deadwood, and surface litter. Areas covered by Dense Caatinga store, on average, nearly 125 Mg ha−1 of C. Most of this C is stored in the soil organic matter (72.1%), followed by aboveground biomass (15.9%), belowground biomass (7.3%), deadwood (2.9%), litter (1.3%), and herbaceous biomass (0.5%). The substitution of Dense Caatinga to plant pastures and crop fields caused losses of >50% of ecosystem C stocks, reaching almost 65 Mg ha−1 of C, with nearly equal losses from the SOM and vegetation biomass compartments. Open Caatinga store nearly 30% less C than Dense Caatinga. Contrary to what was expected, the overall differences in C stocks between soil classes were not significant, with a few exceptions. We expect that the findings of this study will contribute to a more robust inventory of GHG emissions/removals due to land-use changes in NE Brazil and other dry tropical regions of the globe.
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  Stock and stability of organic carbon in soils under major agro-ecological zones and cropping systems of sub-tropical India

  We evaluated long-term impact of agro-ecological zones and cropping systems on stock and stability of organic C in soils along depth. Sixty geo-referenced soil samples were collected from Terai (TZ) and New Alluvial (NAZ) agro-ecological zones of Wet Bengal. In each zone, soil samples were drawn at 0−0.3, 0.3−0.6 and 0.6−0.9 m depth from rice-potato-jute (R-P-J), rice-vegetables-vegetables (R-V-V), vegetables-vegetables-vegetables (V-V-V) and rice-rice (R-R) cropping systems. Total organic C (TOC) in soils and its pools viz., easily oxidizable Walkley and Black C (CWB), very labile (CVL), labile (CL), less labile (CLL), non-labile (CNL), active (CAP), and passive (CPP) were measured separating on the basis of ease of oxidation with chromic acid for computing different indices of soil organic C (SOC). Among the cropping systems, on average, rice-based systems had higher TOC and CNL than non-rice (V-V-V) one, particularly in NAZ; while non-rice system had a higher per cent allocation of SOC in CVL. Again, a greater per cent of SOC occurred in CPP and CAP under rice-based and non-rice systems, respectively. Anaerobiosis thus facilitated formation of a higher proportion of SOC in recalcitrant pools. Stratification ratios of organic C were higher for soils under NAZ than those under TZ, and also for soils under rice-based systems than those under non-rice one indicating a better soil quality in the former than the latter zone and systems. This was again corroborated with higher values of carbon management index for NAZ than TZ and R-R than V-V-V systems. Further, the recalcitrant indices (RIs) of SOC were higher for soils of TZ than those of NAZ, contrary to the values of lability index (LI). Among the cropping systems, V-V-V had the highest LI values followed by R-V-V > R-P-J = R-R. Along depth, the values of RIs increased, but LI decreased. There was thus an overriding influence of rice and its ecology on the stock and stability of SOC masking the influence of its companion crops in rice-based systems. Therefore, rice-based systems, grown by default in many regions, had a better C economy in soils of this sub-tropical part of the world.
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  Barriers and strategies to boost soil carbon sequestration in agriculture

  The Paris Agreement calls for limiting global warming below 2°C. The “4 per 1,000 Initiative: Soils for food security and climate” was launched in 2015 to increase soil organic carbon sequestration with three objectives: mitigation of climate change, adaptation to climate change and improved food security. One of the challenges of the Initiative relates to its feasibility in contrasted biophysical, social and economic environments, questioning the adoption rate of required new practices. We conducted participatory multi-stakeholder workshops in France and Senegal to collect knowledge and perception of farmers, NGOs, agro-industries, administrations, donors and researchers on barriers and coping strategies for 4 per 1,000 innovations. Results in both countries reveal the predominance of social and economic barriers such as lack of knowledge or training, increased difficulties of fieldwork, workload, risk handling, funding and social pressure. Biophysical constraints such as limited potential of soil organic matter storage or rainfall scarcity and variability appear more important in Senegal. Identified actions to foster the sequestration of soil carbon call for an improved policy context leading to innovations in land planning, stakeholder communication, demonstration facilities, capacity building or financial support. Fewer constraints and coping strategies mention technical issues, showing that fostering agricultural soil carbon sequestration is more a question of enabling environment than technical innovations or farmers' willingness for change. We conclude that actions to support the 4 per 1,000 Initiative need to include a variety of stakeholders such as extension services, private sector, civil society, local institutions, policy makers, consumers, and not only farmers.
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  Soil carbon sequestration by agroforestry systems in China: A meta-analysis

  China has a rich historical heritage of agroforestry, but a quantitative analysis of the potential of agroforestry systems (AFS) for soil organic carbon (SOC) sequestration is missing. A comprehensive meta-analysis of soil C sequestration rates derived from 43 studies was undertaken to determine its most influential parameters. Soil C sequestration rates were calculated for topsoils (0–20 cm, 97 sites) and at two subsoil layers (20–40 cm, 73 sites; 40–60 cm, 54 sites). The results showed highest C sequestration rates for the AFS-type shelterbelt in topsoils (0.92 Mg ha−1 yr−1), upper subsoils (0.72 Mg ha−1 yr−1) and lower subsoils (0.52 Mg ha−1 yr−1), followed by agrosilvicultural systems (0.70, 0.48 and 0.43 Mg ha−1 yr−1, respectively) and silvopastoral systems (0.23, 0.08 and 0.02 Mg ha−1 yr−1, respectively). We tested potential effects of different predictor variables (soil class, AFS-type, land use of the control site, system age, initial SOC stock, tree components, legumes and climatic properties) on soil C sequestration rates using a Random Forest regression model. We found changes in the conditional importance of the predictors for different soil layers. For both top- and subsoils, the AFS-type, initial SOC and soil class were most influential, followed by age. Other factors such as land use of the control, climate factors (climate zone, mean annual temperature, mean annual precipitation), leguminous species and tree components were of minor importance. We conclude that besides the AFS-type and the initial SOC, soil type plays a decisive role for the efficiency of soil C sequestration by agroforestry. Our meta-analysis provided evidence that existing AFS in China, particularly shelterbelts and agrosilvicultural systems, are effective practices to increase SOC stocks, both in top- and subsoils and especially in the subtropical climate zone.
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  Carbon sequestration potential through conservation agriculture in Africa has been largely overestimated: Comment on: “Meta-analysis on carbon sequestration through conservation agriculture in Africa”

  Soil organic carbon (SOC) sequestration depends on several factors,including land use, pedo-climatic conditions, topographic position andthe initial SOC stock (Post and Kwon, 2000; Minasny et al., 2017). Atthe plot scale, a positive SOC balance is created by increasing the inputof organic matter to the soil to exceed the carbon (C) losses by miner-alization, leaching and erosion or by decreasing the rate of SOC de-composition. In Africa, agricultural soils are generally known to havepotential as a C sink due to previous SOC depletion (Vågen et al., 2005;Swanepoel et al., 2016). Two widely promoted crop managementpractices to store C in agricultural soils are conservation agriculture(CA) and agroforestry. Both practices can increase SOC through in-creased C inputs from higher biomass productivity and reduced C losses(through soil cover and reduced soil tillage), leading to a net transfer ofC from the atmosphere to the soil, thus contributing to the mitigation ofclimate change (Smith et al., 2005;Powlson et al., 2011; Griscom et al.,2017).
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  Carbon and nitrogen transfer from litter to soil is higher in slow than rapid decomposing plant litter: A synthesis of stable isotope studies

  Litter decomposability determines litter mass loss rate, but how it affects soil carbon (C) and nitrogen (N) storage remains elusive. We compiled data from 25 litter decomposition studies tracing the fate of C and N during decomposition using stable C and N isotopes. An average of 24% of C lost from decomposing litter was recovered in the soil independent of the decomposition stage and the experimental conditions. In contrast, a higher amount of N lost from decomposing litter was recovered in the soil in laboratory (80%) than in field (58%) experiments. The proportion of the total C and N lost that was transferred to the soil was higher for slowly than for rapidly decomposing litter types. Our results demonstrate substantial soil C and especially N input from decomposing litters and suggest that slowly decomposing litters favor soil C and N storage compared to more rapidly decomposing litters.
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  Tropical agricultural land management influences on soil microbial communities through its effect on soil organic carbon

  We analyzed the microbial community that developed after 4 years of testing different soil-crop management systems in the savannah forest transition zone of Eastern Ghana where management systems can rapidly alter stored soil carbon as well as soil fertility. The agricultural managements were: (i) the local practice of fallow regrowth of native elephant grass (Pennisetum purpureum) followed by biomass burning before planting maize in the spring, (ii) the same practice but without burning and the maize receiving mineral nitrogen fertilizer, (iii) a winter crop of a legume, pigeon pea (Cajanus cajan), followed by maize, (iv) vegetation free winter period (bare fallow) followed by maize, and (v) unmanaged elephant grass-shrub vegetation. The mean soil organic carbon (SOC) contents of the soils after 4 years were: 1.29, 1.67, 1.54, 0.80 and 1.34%, respectively, differences that should affect resources for the microbial community. From about 290,000 sequences obtained by pyrosequencing the SSU rRNA gene, canonical correspondence analysis showed that SOC was the most important factor that explained differences in microbial community structure among treatments. This analysis as well as phylogenetic ecological network construction indicated that members of the Acidobacteria GP4 and GP6 were more abundant in soils with relatively high SOC whereas Acidobacteria GP1, GP7, and Actinobacteria were more prevalent in soil with lower SOC. Burning of winter fallow vegetation led to an increase in Bacillales, especially those belonging to spore-forming genera. Of the managements, pigeon-pea cultivation during the winter period promoted a higher microbial diversity and also sequestered more SOC, presumably improving soil structure, fertility, and resiliency. (C) 2013 Elsevier Ltd. All rights reserved.
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  A global, empirical, harmonised dataset of soil organic carbon changes under perennial crops

  A global, unified dataset on Soil Organic Carbon (SOC) changes under perennial crops has not existed till now. We present a global, harmonised database on SOC change resulting from perennial crop cultivation. It contains information about 1605 paired-comparison empirical values (some of which are aggregated data) from 180 different peer-reviewed studies, 709 sites, on 58 different perennial crop types, from 32 countries in temperate, tropical and boreal areas; including species used for food, bioenergy and bio-products. The database also contains information on climate, soil characteristics, management and topography. This is the first such global compilation and will act as a baseline for SOC changes in perennial crops. It will be key to supporting global modelling of land use and carbon cycle feedbacks, and supporting agricultural policy development.
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  A meta-analysis of global cropland soil carbon changes due to cover cropping

  Including cover crops within agricultural rotations may increase soil organic carbon (SOC). However, contradictory findings generated by on-site experiments make it necessary to perform a comprehensive assessment of interactions between cover crops, environmental and management factors, and changes in SOC. In this study, we collected data from studies that compared agricultural production with and without cover crops, and then analyzed those data using meta-analysis and regression. Our results showed that including cover crops into rotations significantly increased SOC, with an overall mean change of 15.5% (95% confidence interval of 13.8%–17.3%). Whereas medium-textured soils had highest SOC stocks (overall means of 39 Mg ha−1 with and 37 Mg ha−1 without cover crops), fine-textured soils showed the greatest increase in SOC after the inclusion of cover crops (mean change of 39.5%). Coarse-textured (11.4%) and medium-textured soils (10.3%) had comparatively smaller changes in SOC, while soils in temperate climates had greater changes (18.7%) than those in tropical climates (7.2%). Cover crop mixtures resulted in greater increases in SOC compared to mono-species cover crops, and using legumes caused greater SOC increases than grass species. Cover crop biomass positively affected SOC changes while carbon:nitrogen ratio of cover crop biomass was negatively correlated with SOC changes. Cover cropping was associated with significant SOC increases in shallow soils (≤30 cm), but not in subsurface soils (>30 cm). The regression analysis revealed that SOC changes from cover cropping correlated with improvements in soil quality, specifically decreased runoff and erosion and increased mineralizable carbon, mineralizable nitrogen, and soil nitrogen. Soil carbon change was also affected by annual temperature, number of years after start of cover crop usage, latitude, and initial SOC concentrations. Finally, the mean rate of carbon sequestration from cover cropping across all studies was 0.56 Mg ha−1 yr−1. If 15% of current global cropland were to adopt cover crops, this value would translate to 0.16 ± 0.06 Pg of carbon sequestered per year, which is ~1–2% of current fossil fuels emissions. Altogether, these results indicated that the inclusion of cover crops into agricultural rotations can enhance soil carbon concentrations, improve many soil quality parameters, and serve as a potential sink for atmosphere CO2.
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  A trade-off between plant and soil carbon storage under elevated CO 2

  Terrestrial ecosystems remove about 30 per cent of the carbon dioxide (CO2) emitted by human activities each year1, yet the persistence of this carbon sink depends partly on how plant biomass and soil organic carbon (SOC) stocks respond to future increases in atmospheric CO2 (refs. 2,3). Although plant biomass often increases in elevated CO2 (eCO2) experiments4–6, SOC has been observed to increase, remain unchanged or even decline7. The mechanisms that drive this variation across experiments remain poorly understood, creating uncertainty in climate projections8,9. Here we synthesized data from 108 eCO2 experiments and found that the effect of eCO2 on SOC stocks is best explained by a negative relationship with plant biomass: when plant biomass is strongly stimulated by eCO2, SOC storage declines; conversely, when biomass is weakly stimulated, SOC storage increases. This trade-off appears to be related to plant nutrient acquisition, in which plants increase their biomass by mining the soil for nutrients, which decreases SOC storage. We found that, overall, SOC stocks increase with eCO2 in grasslands (8 ± 2 per cent) but not in forests (0 ± 2 per cent), even though plant biomass in grasslands increase less (9 ± 3 per cent) than in forests (23 ± 2 per cent). Ecosystem models do not reproduce this trade-off, which implies that projections of SOC may need to be revised.
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  How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal

  There is growing international interest in better managing soils to increase soil organic carbon (SOC) content to contribute to climate change mitigation, to enhance resilience to climate change and to underpin food security, through initiatives such as international ‘4p1000’ initiative and the FAO's Global assessment of SOC sequestration potential (GSOCseq) programme. Since SOC content of soils cannot be easily measured, a key barrier to implementing programmes to increase SOC at large scale, is the need for credible and reliable measurement/monitoring, reporting and verification (MRV) platforms, both for national reporting and for emissions trading. Without such platforms, investments could be considered risky. In this paper, we review methods and challenges of measuring SOC change directly in soils, before examining some recent novel developments that show promise for quantifying SOC. We describe how repeat soil surveys are used to estimate changes in SOC over time, and how long-term experiments and space-for-time substitution sites can serve as sources of knowledge and can be used to test models, and as potential benchmark sites in global frameworks to estimate SOC change. We briefly consider models that can be used to simulate and project change in SOC and examine the MRV platforms for SOC change already in use in various countries/regions. In the final section, we bring together the various components described in this review, to describe a new vision for a global framework for MRV of SOC change, to support national and international initiatives seeking to effect change in the way we manage our soils.
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  Lower microbial carbon use efficiency reduces cellulose-derived carbon retention in soils amended with compost versus mineral fertilizers

  Cellulose decomposition is a key process in soil carbon (C) cycling due to the high abundance of cellulose in plant biomass. Microbial functional groups that sequester C from cellulose, and the accumulation of cellulose C in soil aggregates, remains debated. We hypothesized that cellulose derived 13C would be more efficiently converted into soil organic C by microorganisms, and retained in soil subjected to long-term application of compost. In this study, soil sampled from a long-term (27 years) field experiment with application of compost (Compost), NPK fertilizers (NPK) and without fertilizers (control), was incubated with 13C-cellulose for 120 days. The cellulose 13C content, microbial community structure (lipid biomarkers) and microbial 13C use efficiency (CUE) were measured. The incorporation of 13C into large macroaggregates (>2000 μm), small macroaggregates (250–2000 μm), microaggregates (53–250 μm), and silt + clay fraction (<53 μm) was analyzed to elucidate cellulose 13C sequestration process in aggregates. In contrast to our initial hypothesis, 13C remaining in soil after 120 days of incubation was maximal in unfertilized soil (25%) and minimal in Compost soil (17%). Compost soil had higher abundance of fungi and especially fast-growing bacteria (Gram-negative (G–) bacteria) than NPK and control soils. This accelerated decomposition and lowered CUE of 13C, therefore reducing the amount of 13C remaining in the Compost soil. In contrast, in the other soils, the lower fungal abundance reduced cellulose decomposition, which in turn contributed to growth of Gram-positive (G+) bacteria characterized by larger CUE than G– bacteria. This increased the ratio of G+/G– bacteria, resulting in larger CUE and more 13C remaining in NPK and control soils. Cellulose-derived 13C content decreased in small macroaggregates and microaggregates for all three soils, and in silt + clay fraction for the Compost soil; meanwhile, cellulose-derived 13C content increased in the silt + clay fraction for NPK and control soils from day 14 onwards. The ratios of 13C content in small macroaggregates and microaggregates to that in silt + clay fraction were higher in NPK and unfertilized soils than in Compost soil during the incubation. This indicated that less 13C was redistributed from large aggregates to silt + clay fraction in Compost soil. Overall, cellulose was more rapidly decomposed and incorporated into aggregates in organic C-rich soil, but their transformation efficiency into soil organic C was lower than in organic C-poor soil.
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  Microbial diversity drives carbon use efficiency in a model soil

  Empirical evidence for the response of soil carbon cycling to the combined effects of warming, drought and diversity loss is scarce. Microbial carbon use efficiency (CUE) plays a central role in regulating the flow of carbon through soil, yet how biotic and abiotic factors interact to drive it remains unclear. Here, we combine distinct community inocula (a biotic factor) with different temperature and moisture conditions (abiotic factors) to manipulate microbial diversity and community structure within a model soil. While community composition and diversity are the strongest predictors of CUE, abiotic factors modulated the relationship between diversity and CUE, with CUE being positively correlated with bacterial diversity only under high moisture. Altogether these results indicate that the diversity × ecosystem-function relationship can be impaired under non-favorable conditions in soils, and that to understand changes in soil C cycling we need to account for the multiple facets of global changes.
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  Post-agricultural restoration of soil organic carbon pools across a climate gradient

  Post-agricultural natural restoration is a worldwide strategy for eco-environmental sustainability. However, it is unclear how it affects soil organic carbon (SOC) pools and composition among soil types across climate gradient. Here, we investigated 23-year post-agricultural restorations of SOC in three soils: Luvic Phaeozem, Calcaric Cambisol and Ferralic Cambisol typical for mid-temperate, warm-temperate and subtropical zones, respectively. Six SOC fractions with different protection mechanisms (non-protected, physically, chemically, biochemically, physico-chemically and physico-biochemically) were separated. Compared with pre-restoration in 1990, post-agricultural restoration rebuilt SOC similarly (+68–+91%) among the three soils despite of different SOC background. Compared with continuous cultivation, post-agricultural restoration increased total SOC pools in all the three soils (+33–+60%) mainly because of the increments of non-protected pool (coarse particulate organic C, cPOC). However, the pure physically, chemically, and biochemically protected SOC fractions were less sensitive to post-agricultural restoration. The physico-biochemically protected SOC was hampered by restoration in the two temperate soils but remained stable in the subtropical soil, suggesting a divergent self-restoring trend. Positive correlations of the total SOC and most fractions with wetness (precipitation/temperature ratio) demonstrated the climate dependency of SOC. In conclusion, post-agricultural natural restoration builds up SOC pool mainly due to the cPOC increment and shifts SOC composition towards more easily available C in three soils across the climatic gradient.
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  Prediction of soil organic carbon stock by laboratory spectral data and airborne hyperspectral images

  Soil organic carbon (SOC) plays an important role in controlling the function and quality of soil and offsetting the emissions of greenhouse gases. However, the dynamic monitoring and estimation of SOC are very difficult due to the complex traditional methods and the changing environmental variables. For instance, the calculation of SOC stock requires measurement of a few relevant soil attributes, such as soil organic matter (SOM), soil bulk density (SBD), soil moisture, and soil weight, in the laboratory. Many studies have suggested that visible and near-infrared (vis–NIR) spectra are a practical and affordable alternative to accurately and rapidly estimate the soil attributes relevant to SOC stock, and airborne hyperspectral images can be used as a valuable data source to perform digital soil mapping with high spatial resolution. The objective of this research was to check the predicted capability of SOC stock through laboratory and airborne vis–NIR spectral data. A total of 50 topsoil samples (0–15 cm) from the farmland of Iowa City were used as the study object. The partial least squares regression model was used to predict SOC stock through the direct and indirect methods. In the direct method, the SOC stock was predicted using the spectral data. In the indirect method, the relevant soil properties (SOM and SBD) of the SOC stock were predicted using the spectral data, and then the SOC stock was calculated. The mechanism of the prediction methods and the potential influencing factors of the model performance were discussed from the aspect of electromagnetic theory and empirical statistics. Results showed the following: (i) SOC stock can be successfully predicted using the laboratory spectra and the airborne hyperspectral image through the direct and indirect methods; (ii) the SOC stock and its relevant soil properties (SOM and SBD) showed evident spectral absorption characteristics in the vis–NIR spectral band; (iii) the atmospheric environment and soil surface conditions were the main influencing factors of the prediction accuracy between the airborne and laboratory spectra. This research might be useful for the dynamic monitoring and modeling of SOC in agricultural and environmental fields.
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  Soil organic and inorganic carbon sequestration by consecutive biochar application: Results from a decade field experiment

  Biochar addition can expand soil organic carbon (SOC) stock and has potential ability in mitigating climate change. Also, some incubation experiments have shown that biochar can increase soil inorganic carbon (SIC) contents. However, there is no direct evidence for this from the field experiment. In order to make up the sparseness of available data resulting from the long-term effect of biochar amendment on soil carbon fractions, here we detected the contents and stocks of the bulk SIC and SOC fractions based on a 10-year field experiment of consecutive biochar application in Shandong Province, China. There are three biochar treatments as no-biochar (control), and biochar application at 4.5 Mg ha−1 year−1 (B4.5) and 9.0 Mg ha−1 year−1 (B9.0), respectively. The results showed that biochar application significantly enhanced SIC content (3.2%–24.3%), >53 μm particulate organic carbon content (POC, 38.2%–166.2%) and total soil organic carbon content (15.8%–82.2%), compared with the no-biochar control. However, <53 μm silt–clay-associated organic carbon (SCOC) content was significantly decreased (14%–27%) under the B9.0 treatment. Our study provides the direct field evidence that SIC contributed to carbon sequestration after the biochar application, and indicates that the applied biochar was allocated mainly in POC fraction. Further, the decreased SCOC and increased microbial biomass carbon contents observed in field suggest that the biochar application might exert a positive priming effect on native soil organic carbon.
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  Stability of soil organic carbon during forest conversion is more sensitive in deep soil than in topsoil in subtropical forests

  Despite much research, a lot of uncertainty remains regarding the effects of forest conversion to plantation on soil organic carbon (SOC) stabilization, particularly in deep soils. After comparing the SOC content and its distribution in over 200 years old natural broadleaved of forest of Castanopsis carlesii to that in an adjacent 38 years old C. carlesii plantation, we evaluated the effect of land use intensification on soil carbon (C) storage indicators - soil aggregates, density fractions and SOC mineralization rate. The conversion of natural forest to plantation caused divergent, but seemingly progressive responses in the topsoil and deep soil. In the topsoil, SOC stocks were up to 32 % lower following the forest conversion, with a lower labile C pool, whereas the recalcitrance indices in the topsoil of the plantation forest was similar to that in the topsoil of the natural forest. In contrast, in the deep soil, SOC stocks were unaltered, but the recalcitrance indices of SOC decreased by 64 % after forest conversion. The decreased stability of deep SOC was confirmed by the observed decrease in biochemically protected C and increase in specific C mineralization (normalized for soil C content). The decline in biochemically protected C may attribute to greater physical accessibility of organic C to microbes due to soil disturbance induced by forests conversion practices. Consequently, our results supported the view that despite the variable processing rates of C in differently protected pools, all SOC pools are potentially decomposable and dynamic. Physical disturbance appears to be the key factor modifying SOC protection status and long-term stabilization.
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  The Rock-Eval® signature of soil organic carbon in arenosols of the Senegalese groundnut basin. How do agricultural practices matter?

  Soil organic carbon (SOC) ensures soil quality and productivity of cultivated systems in the Sahelian region. This study uses Rock-Eval® pyrolysis to examine how cultural practices impact the quantity of SOC and quality of SOM in cultivated sandy soils in the Senegal groundnut basin. This cost-effective method provides information on SOC thermal stability, which has been shown to be related qualitatively to biogeochemical stability of SOC. We sampled soils within two villages in agricultural plots representative of local agricultural systems, and in two local preserved areas (tree plantation and shrubby savanna). SOC concentrations ranged from 1.8–18.5 g.kg−1 soil in the surface layer (0−10 cm) and from 1.5–11.3 g.kg−1 soil in the 10−30 cm layer. SOC contents of cultivated soils decreased significantly (p-value < 0.0001) according to field amendment, in the following order: addition of organic wastes> addition of manure > millet residues left after harvest > no organic input. We found that the quantity and the quality of SOC are linked, and that both depend on land-use and agricultural practices, especially upon the type of organic inputs. Quantity of SOC and quality of SOM are correlated strongly in the tree plantation (R² = 0.98) and in the protected shrubby savanna (R² = 0.97). They are also correlated significantly in cultivated soils receiving organic wastes (R² = 0.82), manure (R² from 0.74 and 0.91), or millet residues (R2 = 0.91) but not in soils that receive no organic inputs. Indexes based upon Rock-Eval® pyrolysis were represented in an I/R diagram that illustrates the level of SOC stabilization. The indexes of the studied soils were plotted against comparable results from literature. Thermal signatures of the Senegalese Arenosols show an inversion of I and the R indexes compared to data from the literature. This result highlights SOC stabilization as a function of soil depth. Indeed, the refractory pool in the studied soils (where refractory pool ranged from 7.7–21.3 % in the 0−10 cm layer, and from 12.5–24.3 % in the 10−30 cm) was more abundant than in Ferralsols in natural conditions, where refractory pool ranged from 2 to 9%. The soil organic matter in these Arenosols while positively affected by organic inputs, is dominated by more or less labile forms that mineralize quickly: a quality that is excellent for productivity of these agrosystems, but not for mitigation of climate change in the long term.
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  Priming mechanisms providing plants and microbes access to mineral-associated organic matter

  Mineral-associated organic matter (MAOM) is considered a stable reservoir for soil nutrients that influences long-term soil carbon (C) and nitrogen (N) dynamics. However, recent experimental and theoretical evidence shows that root exudates may mobilize MAOM, thereby providing plants and microbes access to a large and N-rich pool. Given the mechanisms underlying MAOM C and N mobilization remain largely untested, we examined direct and indirect pathways by which root exudates destabilize this nutrient pool in laboratory mesocosms. We simulated root exudation with 13C-labeled oxalic acid to test whether root exudates are directly capable of mobilizing MAOM from mineral surfaces; and with 13C-labeled glucose to test whether indirect stimulation of microbial and extracellular enzyme activity leads to MAOM decomposition. We also tested the potential for oxalic acid and glucose to mobilize MAOM in an additional subset of sterilized soils to clarify the potential for non-microbial pathways of MAOM destabilization. Over the course of the 12-day MAOM incubation with and without simulated exudates, we measured C cycling (CO2 respiration rates, 13C–CO2 efflux), N cycling (inorganic N pools, gross N mineralization) and related microbial processes (enzyme activities and microbial community composition via phospholipid fatty acid analysis). Both of the simulated root exudates enhanced MAOM-C mineralization, with cumulative respiration increasing 35–89% relative to the water-only control. Likewise, glucose additions enhanced the production of an exo-cellulase and a chitinase by up to 130% and 39%, respectively, while oxalic acid enhanced oxidative enzyme activities up to 91% greater than control rates. We observed a positive association between glucose-induced shifts in enzyme activities, MAOM-C mineralization, and gross ammonification. Oxalic acid additions were associated with initial increases in fungal relative abundance and in sterile soils appeared to stimulate the release of metals and dissolved organic nitrogen into exchangeable pools. Our results indicate that common root exudates, like glucose and oxalic acid, can significantly increase the turnover and potential release of C and N from MAOM through indirect (e.g., enzyme induction) and direct (e.g., mobilization of metal oxides) mechanisms.
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  Mapping topsoil organic carbon concentrations and stocks for Tanzania

  Tanzania is one of the countries that has embarked on a national programme under the United Nations collaborative initiative on Reducing Emissions from Deforestation and forest Degradation (REDD). Tanzania is currently developing the capacity to enter into a carbon monitoring REDD+ regime. In this context spatially representative soil carbon datasets and accurate predictive maps are important for determining the soil organic carbon pool. The main objective of this study was to model and map the SOC stock for the 0–30-cm soil layer to provide baseline information for REDD+ purposes. Topsoil data of over 1400 locations spread throughout Tanzania from the National Forest Monitoring and Assessment (NAFORMA), were used, supplemented by two legacy datasets, to calibrate simple kriging with varying local means models. Maps of SOC concentrations (g kg−1) were generated for the 0–10-cm, 10–20-cm, 20–30-cm, 0–30-cm layers, and maps of bulk density and SOC stock (kg m−2) for the 0–30-cm layer. Two approaches for modelling SOC stocks were considered here: the calculate-then-model (CTM) approach and the model-then-calculate approach (MTC). The spatial predictions were validated by means of 10-fold cross-validation. Uncertainty associated to the estimated SOC stocks was quantified through conditional Gaussian simulation. Estimates of SOC stocks for the main land cover classes are provided. Environmental covariates related to soil and terrain proved to be the strongest predictors for all properties modelled. The mean predicted SOC stock for the 0–30-cm layer was 4.1 kg m−2 (CTM approach) translating to a total national stock of 3.6 Pg. The MTC approach gave similar results. The largest stocks are found in forest and grassland ecosystems, while woodlands and bushlands contain two thirds of the total SOC stock. The root mean squared error for the 0–30-cm layer was 1.8 kg m−2, and the R2-value was 0.51. The R2-value of SOC concentration for the 0–30-cm layer was 0.60 and that of bulk density 0.56. The R2-values of the predicted SOC concentrations for the 10-cm layers vary between 0.46 and 0.54. The 95% confidence interval of the predicted average SOC stock is 4.01–4.15 kg m−2, and that of the national total SOC stock 3.54–3.65 Pg. Uncertainty associated with SOC concentration had the largest contribution to SOC stock uncertainty. These findings have relevance for the ongoing REDD+ readiness process in Tanzania by supplementing the previous knowledge of significant carbon pools. The soil organic carbon pool makes up a relatively large proportion of carbon in Tanzania and is therefore an important carbon pool to consider alongside the ones related to the woody biomass. Going forward, the soil organic carbon data can potentially be used in the determination of reference emission levels and the future monitoring, reporting and verification of organic carbon pools.
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  Realising the Carbon Benefits of Sustainable Land Management Practices: Guidelines for Estimation of Soil Organic Carbon in the Context of Land Degradation Neutrality Planning and Monitoring. A report of the Science-Policy Interface.

  Land degradation is one of the threats to human and natural systems. Fortunately, over the past few decades awareness of this challenge has grown, and 122 countries have committed to setting land degradation neutrality (LDN) targets, of which 84 have officially validated their targets, and 51 have put their targets into legislation. In this concept, LDN is achieved if new degradation is balanced by reversal of degradation elsewhere in the same land type by restoration or rehabilitation. The primary instrument for achieving LDN is through the implementation of sustainable land management (SLM) practices. Because of its multifunctional roles and its sensitivity to land management soil organic carbon (SOC) was selected as one of three indicators for LDN. Compared with the other global LDN indicators, that is, land cover change and land productivity dynamics (LPD) (measured as net primary productivity), SOC is challenging to manage and monitor at large scales. Moreover, SOC density in soils can vary greatly, even on the scale of meters, and fluctuates over time, for example between seasons. Comparative evaluation of SOC change between different SLM options (e.g. for land planning), tracking SOC dynamics through time (i.e. SOC monitoring) and effectively mapping SOC changes at large scales (e.g. for verifying LDN achievement) requires the combination of rigorous soil sampling schemes and the use of software tools/biophysical models for SOC assessment. To provide practical guidance to support the deployment of SLM interventions to maintain or enhance SOC stocks, for LDN and for other objectives such as landbased climate change adaption and/or mitigation a series of decision trees was developed, based on the latest available knowledge. This report reviews and compares available tools and models for SOC estimation. It presents practical guidance for land managers and puts forward policy-oriented proposals. Guidance for land managers emphasizes the selection of SLM practices to maintain or enhance soil organic carbon and achieve LDN. It addresses the choice of SLM practices suited to the local socio-economic and biophysical context; methods for measurement and monitoring of SOC; and the use of tools/models for SOC assessment to estimate SOC and map SOC, and how to choose an appropriate tool/model according to the purpose. Policy-oriented options include to (i) share the guidance for land managers at the appropriate level; (ii) monitor SOC change as an indicator of SLM intervention to support assessment of LDN achievement in 2030; (iii) apply gender-responsive actions addressing gender-based differences and promote gender equality and women’s empowerment; (iv) design a framework for LDN Planning and means to support it.
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  Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning

  Spatial predictions of soil macro and micro-nutrient content across Sub-Saharan Africa at 250 m spatial resolution and for 0–30 cm depth interval are presented. Predictions were produced for 15 target nutrients: organic carbon (C) and total (organic) nitrogen (N), total phosphorus (P), and extractable—phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), sodium (Na), iron (Fe), manganese (Mn), zinc (Zn), copper (Cu), aluminum (Al) and boron (B). Model training was performed using soil samples from ca. 59,000 locations (a compilation of soil samples from the AfSIS, EthioSIS, One Acre Fund, VitalSigns and legacy soil data) and an extensive stack of remote sensing covariates in addition to landform, lithologic and land cover maps. An ensemble model was then created for each nutrient from two machine learning algorithms—random forest and gradient boosting, as implemented in R packages ranger and xgboost—and then used to generate predictions in a fully-optimized computing system. Cross-validation revealed that apart from S, P and B, significant models can be produced for most targeted nutrients (R-square between 40–85%). Further comparison with OFRA field trial database shows that soil nutrients are indeed critical for agricultural development, with Mn, Zn, Al, B and Na, appearing as the most important nutrients for predicting crop yield. A limiting factor for mapping nutrients using the existing point data in Africa appears to be (1) the high spatial clustering of sampling locations, and (2) missing more detailed parent material/geological maps. Logical steps towards improving prediction accuracies include: further collection of input (training) point samples, further harmonization of measurement methods, addition of more detailed covariates specific to Africa, and implementation of a full spatio-temporal statistical modeling framework.