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  • The role of soil in regulation of climate

    The soil carbon (C) stock, comprising soil organic C (SOC) and soil inorganic C (SIC) and being the largest reservoir of the terrestrial biosphere, is a critical part of the global C cycle. Soil has been a source of greenhouse gases (GHGs) since the dawn of settled agriculture about 10 millenia ago. Soils of agricultural ecosystems are depleted of their SOC stocks and the magnitude of depletion is greater in those prone to accelerated erosion by water and wind and other degradation processes. Adoption of judicious land use and science-based management practices can lead to re-carbonization of depleted soils and make them a sink for atmospheric C. Soils in humid climates have potential to increase storage of SOC and those in arid and semiarid climates have potential to store both SOC and SIC. Payments to land managers for sequestration of C in soil, based on credible measurement of changes in soil C stocks at farm or landscape levels, are also important for promoting adoption of recommended land use and management practices. In conjunction with a rapid and aggressive reduction in GHG emissions across all sectors of the economy, sequestration of C in soil (and vegetation) can be an important negative emissions method for limiting global warming to 1.5 or 2°C This article is part of the theme issue ‘The role of soils in delivering Nature's Contributions to People’.
  • Countries’ commitments to soil organic carbon in Nationally Determined Contributions

    Soil carbon is the major active pool of terrestrial carbon, and as such, soil organic carbon (SOC) targets, policies and measures will be pivotal to achieving global climate targets. SOC sequestration may reduce the net annual greenhouse gas emissions from Agriculture, Forestry and Other Land Use by between 3% and 71%, while simultaneously supporting various ecosystem services. Accurate SOC accounting and monitoring, however, is constrained by various technical challenges related to indicators, rates of SOC change, measuring the impact of management practices on SOC, and the long-term persistence of sequestered SOC. We assessed countries’ pledges to the Paris Agreement for SOC in agriculture to better understand the level, transparency, and specificity of commitments. Reviewing 184 countries’ initial Nationally Determined Contributions (NDCs), we considered whether SOC was included, what was pledged, the level of ambition promised and the specificity of mitigation targets. Twenty-eight countries referred to SOC in their NDCs, citing quantified or unquantified mitigation targets, national policies or programs, and actions and measures to be implemented in agricultural lands (14), peatlands (6) or wetlands (14). Countries’ reasons for not including SOC in NDCs included the need to prioritize goals of sustainable development and food security above climate mitigation, a lack of incentives for farmers to improve management practices, and the difficulty of accurately monitoring changes in SOC. Including SOC targets in NDCs can improve NDCs’ comprehensiveness and transparency to track and compare policy progress across NDCs; it can also leverage SOC-related climate finance, technical support, and capacity building.Key policy insights Many NDCs specify practices known to have the potential to achieve SOC sequestration or protection without explicitly mentioning SOC. The SOC-related mitigation potential of these practices can be quantified in future NDCs.NDCs are not presently a good indicator of countries’ interest or commitment to SOC action at national level. To improve this, countries with existing SOC policies, programs, and actions can specify their SOC-related commitments in future NDCs.Increased collaboration between countries with experience managing SOC and countries needing support to develop SOC-related targets, policies, measures and incentives for land users and farmers would facilitate the provision of such needed support.To increase country commitments and attention to managing SOC, there is a need for improved SOC measurement and monitoring, for better evidence on the impacts of management practices on SOC, and for incentives for farmers to change practices and overcome barriers.
  • Mapping carbon accumulation potential from global natural forest regrowth

    To constrain global warming, we must strongly curtail greenhouse gas emissions and capture excess atmospheric carbon dioxide1,2. Regrowing natural forests is a prominent strategy for capturing additional carbon3, but accurate assessments of its potential are limited by uncertainty and variability in carbon accumulation rates2,3. To assess why and where rates differ, here we compile 13,112 georeferenced measurements of carbon accumulation. Climatic factors explain variation in rates better than land-use history, so we combine the field measurements with 66 environmental covariate layers to create a global, one-kilometre-resolution map of potential aboveground carbon accumulation rates for the first 30 years of natural forest regrowth. This map shows over 100-fold variation in rates across the globe, and indicates that default rates from the Intergovernmental Panel on Climate Change (IPCC)4,5 may underestimate aboveground carbon accumulation rates by 32 per cent on average and do not capture eight-fold variation within ecozones. Conversely, we conclude that maximum climate mitigation potential from natural forest regrowth is 11 per cent lower than previously reported3 owing to the use of overly high rates for the location of potential new forest. Although our data compilation includes more studies and sites than previous efforts, our results depend on data availability, which is concentrated in ten countries, and data quality, which varies across studies. However, the plots cover most of the environmental conditions across the areas for which we predicted carbon accumulation rates (except for northern Africa and northeast Asia). We therefore provide a robust and globally consistent tool for assessing natural forest regrowth as a climate mitigation strategy.
  • A global overview of studies about land management, land-use change, and climate change effects on soil organic carbon

    Major drivers of gains or losses in soil organic carbon (SOC) include land management, land-use change, and climate change. Thousands of original studies have focused on these drivers of SOC change and are now compiled in a growing number of meta-analyses. To critically assess the research efforts in this domain, we retrieved and characterized 192 meta-analyses of SOC stocks or concentrations. These meta-analyses comprise more than 13,200 original studies conducted from 1910 to 2020 in 150 countries. First, we show that, despite a growing number of studies over time, the geographical coverage of studies is limited. For example, the effect of land management, land-use change, and climate change on SOC has been only occasionally studied in North and Central Africa, and in the Middle East and Central Asia. Second, the meta-analyses investigated a limited number of land management practices, mostly mineral fertilization, organic amendments, and tillage. Third, the meta-analyses demonstrated relatively low quality and transparency. Lastly, we discuss the mismatch between the increasing number of studies and the need for more local, reusable, and diversified knowledge on how to preserve high SOC stocks or restore depleted SOC stocks.
  • 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.
  • 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.
  • 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.
  • Healthy Soils Incentives Program

    he HSP Incentives Program provides financial incentives to California growers and ranchers to implement conservation management practices that sequester carbon, reduce atmospheric greenhouse gases (GHGs), and improve soil health. GHGs benefits are estimated using quantification methodology and tools developed by California Air Resources Board (CARB), USDA-NRCS and CDFA and soil health improvement will be assessed by measuring soil organic matter content.
  • Soil organic carbon storage as a key function of soils - A review of drivers and indicators at various scales

    The capacity of soils to store organic carbon represents a key function of soils that is not only decisive for climate regulation but also affects other soil functions. Recent efforts to assess the impact of land management on soil functionality proposed that an indicator- or proxy-based approach is a promising alternative to quantify soil functions compared to time- and cost-intensive measurements, particularly when larger regions are targeted. The objective of this review is to identify measurable biotic or abiotic properties that control soil organic carbon (SOC) storage at different spatial scales and could serve as indicators for an efficient quantification of SOC. These indicators should enable both an estimation of actual SOC storage as well as a prediction of the SOC storage potential, which is an important aspect in land use and management planning. There are many environmental conditions that affect SOC storage at different spatial scales. We provide a thorough overview of factors from micro-scales (particles to pedons) to the global scale and discuss their suitability as indicators for SOC storage: clay mineralogy, specific surface area, metal oxides, Ca and Mg cations, microorganisms, soil fauna, aggregation, texture, soil type, natural vegetation, land use and management, topography, parent material and climate. As a result, we propose a set of indicators that allow for time- and cost-efficient estimates of actual and potential SOC storage from the local to the regional and subcontinental scale. As a key element, the fine mineral fraction was identified to determine SOC stabilization in most soils. The quantification of SOC can be further refined by including climatic proxies, particularly elevation, as well as information on land use, soil management and vegetation characteristics. To enhance its indicative power towards land management effects, further “functional soil characteristics”, particularly soil structural properties and changes in the soil microbial biomass pool should be included in this indicator system. The proposed system offers the potential to efficiently estimate the SOC storage capacity by means of simplified measures, such as soil fractionation procedures or infrared spectroscopic approaches.
  • Regenerative Agriculture: An agronomic perspective

    Agriculture is in crisis. Soil health is collapsing. Biodiversity faces the sixth mass extinction. Crop yields are plateauing. Against this crisis narrative swells a clarion call for Regenerative Agriculture. But what is Regenerative Agriculture, and why is it gaining such prominence? Which problems does it solve, and how? Here we address these questions from an agronomic perspective. The term Regenerative Agriculture has actually been in use for some time, but there has been a resurgence of interest over the past 5 years. It is supported from what are often considered opposite poles of the debate on agriculture and food. Regenerative Agriculture has been promoted strongly by civil society and NGOs as well as by many of the major multi-national food companies. Many practices promoted as regenerative, including crop residue retention, cover cropping and reduced tillage are central to the canon of ‘good agricultural practices’, while others are contested and at best niche (e.g. permaculture, holistic grazing). Worryingly, these practices are generally promoted with little regard to context. Practices most often encouraged (such as no tillage, no pesticides or no external nutrient inputs) are unlikely to lead to the benefits claimed in all places. We argue that the resurgence of interest in Regenerative Agriculture represents a re-framing of what have been considered to be two contrasting approaches to agricultural futures, namely agroecology and sustainable intensification, under the same banner. This is more likely to confuse than to clarify the public debate. More importantly, it draws attention away from more fundamental challenges. We conclude by providing guidance for research agronomists who want to engage with Regenerative Agriculture.
  • WEBINAR: Regional Dialogue on Regenerative Agriculture, Agroecology & Climate Smart Agriculture

    Regenerative Agriculture vs. Agroecology: nomenclature hype or principle divergence? (a) A decade of CSA: what are the achievements, the challenges and the bottlenecks? (b) What practical implications for smallholder farmers, agriculture and the environment? Ismahane Elouafi Chief Scientist – Food and Agriculture Organization of the United Nations. Ken Giller Professor of Plant Production Systems – Wageningen University; Research. Professor Jacques Wery – Institute Agro France. Bruce Campbell - Director of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Jean-Marc Faurès - Regional Programme Leader - Food and Agriculture Organization of the United Nations Regional Offce for the Near East and North Africa. Theresa Wong - Natural Resources Offcer - Food and Agriculture Organization of the United Nations Regional Offce for the Near East and North Africa. Melle Leenstra - Agricultural Counsellor to Egypt & Jordan – Ministry of Agriculture, Nature and Food Quality. Reuben Sessa - Programme Officer (Climate Change) SP2 Management Team – Food and Agriculture Organization of the United Nations.
  • Center for Regenerative Agriculture and Resilient Systems

    Learn about all the resources available through the CSU, Chico Center for Regenerative Agriculture and Resilient Systems.