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    This global data set shows the spatial distribution of generalized soil classes as defined for IPCC Tier-I level national greenhouse gas inventory assessments. The database was derived from the Harmonized World Soil Data Base (HWSD ver. 1.1, at scale 1:1-1:5 M) and a series of taxotransfer procedures to convert FAO soil classifications (1974, 1985 and 1990 Legend) to the seven default IPCC soil classes: high activity clay (HAC), low activity clay (LAC), Sandy (SAN), Spodic (POD), Volcanic (VOL), wetlands (WET) and Organic (ORG). The resulting GIS database may be used for exploratory assessments at national and broader scale, for regions that lack more detailed soil information; inherent limitations of the data are discussed in the documentation. This dataset has been compiled in the framework of the GEF co-funded 'Carbon Benefits Project: Measuring, modelling and monitoring', Component A ( http://carbonbenefitsproject-compa.colostate.edu/index.htm).

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    Limited availability of P in soils to crops may be due to deficiency and/or severe P retention. Earlier studies that drew on large soil profile databases have indicated that it is not (yet) feasible to present meaningful values for “plant-available” soil P, obtained according to comparable analytical methods, that may be linked to soil geographical databases derived from 1:5 million scale FAO Digital Soil Map of the World, such as the 5 x 5 arc-minute version of the ISRIC-WISE database. Therefore, an alternative solution for studying possible crop responses to fertilizer-P applied to soils, at a broad scale, was sought. The approach described in this report considers the inherent capacity of soils to retain phosphorus (P retention), in various forms. Main controlling factors of P retention processes, at the broad scale under consideration, are considered to be pH, soil mineralogy, and clay content. First, derived values for these properties were used to rate the inferred capacity for P retention of the component soil units of each map unit (or grid cell) using four classes (i.e., Low, Moderate, High, and Very High). Subsequently, the overall soil phosphorus retention potential was assessed for each mapping unit, taking into account the P-ratings and relative proportion of each component soil unit. Each P retention class has been assigned to a likely fertilizer P recovery fraction, derived from the literature, thereby permitting spatially more detailed, integrated model-based studies of environmental sustainability and agricultural production at the global and continental level (< 1:5 million). Nonetheless, uncertainties remain high; the present analysis provides an approximation of world soil phosphorus retention potential.

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    The ICRAF-ISRIC Soil VNIR Spectral Library contains visible near infrared spectra of 4,438 soils selected from the Soil Information System (ISIS) of the International Soil Reference and Information Centre (ISRIC). The samples consist of all physically archived samples at ISRIC in 2004 for which soil attribute data was available. The spectra were measured at the World Agroforestry Center's (ICRAF) Soil and Plant Spectral Diagnostic Laboratory. The samples are from 58 countries spanning Africa, Asia, Europe, North America, and South America. Associated attribute data, such as geographical coordinates, horizon (depth), and physical and chemical properties, are provided in a single relational database. The purpose of the library is to provide a resource for research and applications for sensing soil quality both in the laboratory and from space.

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    Following publication of the World Map of the Satus of Human-induced Land Degradation (GLASOD), at scale 1:10M, the need for more detailed and more country-specific degradation assessment became apparent. In 1993, the members of the Asian Network on Problem Soils recommended the preparation of a qualitative assessment for South and Southeast Asian at a scale of 1:5 million. The assessment was carried out using a physiographic base map, compiled according to the SOTER methodology, and a slightly modified GLASOD methodology. The information was stored in a digital database and linked to a GIS enabling preparation of thematic outputs in the form of maps, graphs and tables.

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    Nutrient clusters based on fuzzy k-means of the soil fine earth fraction and spatially predicted at 250 m spatial resolution across sub-Saharan Africa using Machine Learning (ensemble between random forest and gradient boosting) using soil data from the Africa Soil Profiles database (AfSP) compiled by AfSIS and recent soil data newly collected by AfSIS in partnership with EthioSIS (Ethiopia), GhaSIS (Ghana) and NiSIS (Nigeria as made possible by OCP Africa and IITA), combined with soil data as made available by Wageningen University and Research, IFDC, VitalSigns, University of California and the OneAcreFund. [Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutriënt Cycling in Agroecosystems 109(1): 77-102). Maps produced for the Environmental Assessment Agency (PBL), funded by the Netherlands government, in collaboration with the AfSIS and the Vital Signs projects.

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    Depth to bedrock (R horizon) in cm, to maximum 175 cm, predicted using two sets of Africa soil profiles data. For details see published paper here below (Hengl T., G.B.M. Heuvelink, B. Kempen, J.G.B. Leenaars, M.G. Walsh, K.D. Shepherd, A. Sila, R.A. MacMillan, J. Mendes de Jesus, L.T. Desta, J.E. Tondoh, 2015. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions. PLoS ONE 10(6)

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    Sand content (50-2000 micro meter) in g/100g (w%) at 6 standard depths predicted using two sets of Africa soil profiles data. For details see published paper here below (Hengl T., G.B.M. Heuvelink, B. Kempen, J.G.B. Leenaars, M.G. Walsh, K.D. Shepherd, A. Sila, R.A. MacMillan, J. Mendes de Jesus, L.T. Desta, J.E. Tondoh, 2015. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions. PLoS ONE 10(6)

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    Exchangeable magnesium (Mg2+ measured in 1M NH4OAc buffered at pH 7 with part of the data converted from data measured according to Mehlich 3) in cmolc/kg (fine earth) at 2 depth intervals (0-20 cm and 20-50 cm) predicted using two Africa soil profiles datasets. For details see published paper here below (Hengl T., G.B.M. Heuvelink, B. Kempen, J.G.B. Leenaars, M.G. Walsh, K.D. Shepherd, A. Sila, R.A. MacMillan, J. Mendes de Jesus, L.T. Desta, J.E. Tondoh, 2015. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions. PLoS ONE 10(6)

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    Sum of exchangeable bases (Ca2+, Mg2+, K+, Na+ measured in 1M NH4OAc buffered at pH 7 with part of the data converted from data measured according to Mehlich 3) in cmolc/kg (fine earth) at 6 depth intervals predicted using two Africa soil profiles datasets. For details see published paper here below (Hengl T., G.B.M. Heuvelink, B. Kempen, J.G.B. Leenaars, M.G. Walsh, K.D. Shepherd, A. Sila, R.A. MacMillan, J. Mendes de Jesus, L.T. Desta, J.E. Tondoh, 2015. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions. PLoS ONE 10(6)

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    This harmonized set of soil parameter estimates for Latin America and the Caribbean was derived from a revised version of the 1:5M Soil and Terrain Database for the region (SOTERLAC, ver. 2.0) and the ISRIC-WISE soil profile database. The land surface of Latin America and the Caribbean has been characterized using 1585 unique SOTER units, corresponding with 5855 polygons. The major soils have been described using 1660 profiles, selected by national soil experts as being representative for these units. The associated soil analytical data have been derived from soil survey reports. These sources seldom hold all the physical and chemical attributes ideally required by SOTER. Gaps in the measured soil profile data have been filled using a step-wise procedure that uses taxotransfer rules, based on about 9600 soil profiles held in the WISE database, complemented with expert-rules. Parameter estimates are presented by soil unit for fixed depth intervals of 0.2 m to 1 m depth for: organic carbon, total nitrogen, pH(H2O), CECsoil, CECclay, base saturation, effective CEC, aluminium saturation, CaCO3 content, gypsum content, exchangeable sodium percentage (ESP), electrical conductivity of saturated paste (ECe), bulk density, content of sand, silt and clay, content of coarse fragments (less than 2 mm), and available water capacity (-33 to -1500 kPa). These attributes have been identified as being useful for agro-ecological zoning, land evaluation, crop growth simulation, modelling of soil carbon stocks and change, and analyses of global environmental change. The current parameter estimates should be seen as best estimates based on the current selection of soil profiles and data clustering procedure. Taxotransfer rules have been flagged to provide an indication of the possible confidence in the derived data. Results are presented as summary files and can be linked to the 1:5M scale SOTERLAC map in a GIS, through the unique SOTER-unit code. The secondary data set is considered appropriate for studies at the continental scale (greater than 1:5M). Correlation of soil analytical data should be done more rigorously when more detailed scientific work is considered.