Information on the geographic variation in soil has traditionally been presented in polygon (choropleth) maps at coarse scales. Now scientists, planners, managers and politicians want quantitative information on the variation and functioning of soil at finer resolutions; they want it to plan better land use for agriculture, water supply and the mitigation of climate change land degradation and desertification. The GlobalSoilMap project aims to produce a grid of soil attributes at a fine spatial resolution (approximately 100 m), and at six depths, for the purpose. This paper describes the three-dimensional spatial modelling used to produce the Australian soil grid, which consists of Australia-wide soil attribute maps. The modelling combines historical soil data plus estimates derived from visible and infrared soil spectra. Together they provide a good coverage of data across Australia. The soil attributes so far include sand, silt and clay contents, bulk density, available water capacity, organic carbon, pH, effective cation exchange capacity, total phosphorus and total nitrogen. The data on these attributes were harmonised to six depth layers, namely 0–0.05 m, 0.05–0.15 m, 0.15–0.30 m, 0.30–0.60 m, 0.60–1.00 m and 1.00–2.00 m, and the resulting values were incorporated simultaneously in the models. The modelling itself combined the bootstrap, a decision tree with piecewise regression on environmental variables and geostatistical modelling of residuals. At each layer, values of the soil attributes were predicted at the nodes of a 3 arcsecond (approximately 90 m) grid and mapped together with their uncertainties. The assessment statistics for each attribute mapped show that the models explained between 30% and 70% of their total variation. The outcomes are illustrated with maps of sand, silt and clay contents and their uncertainties. The Australian three-dimensional soil maps fill a significant gap in the availability of quantitative soil information in Australia.

The Soil and Landscape Grid of Australia (SLGA) is the first continental version of the GlobalSoilMap concept and the first nationally consistent, fine spatial resolution set of continuous soil attributes with Australia-wide coverage. The SLGA relies on digital soil mapping methods and integrates historical soil data, new measurement with spectroscopic sensors, novel spatial modelling and a web-service delivery architecture. The SLGA provides soil, regolith and landscape estimates at the centre point of 3 arcsecond grid cells (~90 × 90 m) across Australia. At each point, there are estimates of 11 soil attributes and confidence intervals for each estimate to a depth of 2 m or less, depth of regolith and a set of terrain descriptors. The information system also includes a library of mid-infrared spectra, an inference engine that allows estimation of additional soil parameters and an information model that enables users to access the system via web services. The explicit mapping of depth, bulk density and coarse fragments allows estimation of material stores and fluxes on a volumetric basis. The SLGA therefore has immediate applications in carbon, nitrogen and water process modelling. The map of regolith depth will find immediate application to studies of vadose zone processes, including solute transport, groundwater and nutrient fluxes beyond the root zone. Landscape attributes at 1 and 3 arcseconds are useful for a wide spectrum of ecological, hydrological and broader environmental applications. The SLGA can be accessed at no cost from www.csiro.au/soil-and-landscape-grid. It is managed and delivered as part of the Australian Soil Resource Information System (ASRIS).

The importance of building/maintaining soil carbon, for soil health and CO 2 mitigation, is of increasing interest to a wide audience, including policymakers, NGOs and land managers. Integral to any approaches to promote carbon sequestering practices in managed soils are reliable, accurate and cost-effective means to quantify soil C stock changes and forecast soil C responses to different management, climate and edaphic conditions. While technology to accurately measure soil C concentrations and stocks has been in use for decades, many challenges to routine, cost-effective soil C quantification remain, including large spatial variability, low signal-to-noise and often high cost and standardization issues for direct measurement with destructive sampling. Models, empirical and process-based, may provide a cost-effective and practical means for soil C quantification to support C sequestration policies. Examples are described of how soil science and soil C quantification methods are being used to support domestic climate change policies to promote soil C sequestration on agricultural lands (cropland and grazing land) at national and provincial levels in Australia and Canada. Finally, a quantification system is outlinedconsisting of well-integrated datamodel frameworks, supported by expanded measurement and monitoring networks, remote sensing and crowd-sourcing of management activity datathat could comprise the core of a new global soil information system. Take Home messages:Increasing soil organic carbon (SOC) stocks would improve the performance of working (managed) soils especially under drought or other stressors, increase agricultural resilience and fertility, and reduce net GHG emissions from soils.There are many improved management practices that can be and are currently being applied to cropland and grazing lands to increase SOC.Land managers are decision makers who operate in larger contexts that bound their agricultural and financial decisions (e.g. market forces, crop insurance, input subsidies, conservation mandates, etc.).Any effort to value improvements in the performance of agricultural soils through enhanced levels of SOC will require feasible, credible and creditable assessment of SOC stocks, which are governed by dynamic and complex soil processes and properties. This paper evaluates currently accepted methods of quantifying and forecasting SOC that, when augmented and pulled together, could provide the basis for a new global soil information system.

Soil legacy data rescue via GlobalSoilMap and other international and national initiatives The International Center for Tropical Agriculture (CIAT) believes that open access contributes to its mission of reducing hunger and poverty, and improving human nutrition in the tropics through research aimed at increasing the eco-efficiency of agriculture. CIAT is committed to creating and sharing knowledge and information openly and globally. We do this through collaborative research as well as through the open sharing of our data, tools, and publications.

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