Publications

Works written by the AfSIS team and AfSIS affiliates.

• Mapping rootable depth and root zone plant-available water holding capacity of the soil of sub-Saharan AfricaLeenaars J.G.B., L. Claessens, G.B.M. Heuvelink, T. Hengl, M. Ruiperez González, L.G.J. van Bussel, N. Guilpart, H. Yang, K.G. Cassman, 2018
• Soil legacy data rescue via GlobalSoilMap and other international and national initiativesArrouays D., J.G.B. Leenaars, A.C. Richer-de-Forges, et al, 2017-12
• WoSIS: providing standardised soil profile data for the world 2017-09-01
• Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learningHengl T., J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, Helina Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, Nketia A. Kwabena, 2017-09
• Rooting for food security in Sub-Saharan AfricaGuilpart N., P. Grassini, J. van Wart, H. Yang, M.K. van Ittersum, L.G.J. van Bussel, J. Wolf, L. Claessens, J.G.B. Leenaars, K.G. Cassman, 2017
• Mapping root depth soil water in sub-Saharan Africa. Abstract book Pedometrics 2017. Wageningen: 130.Leenaars Johan G.B., Lieven Claessens, Gerard B.M. Heuvelink, TomHengl, Maria Ruipérez Gonzalez, Lenny G.J. van Bussel, Nicolas Guilpart, Haishun Yang, Kenneth G. Cassman, 2017
• Mapping of fertilizer recommendations for major crops in West AfricaLeenaars J.G.B., E.J. Dossa, M. Ruiperez Gonzalez, B. Kempen, 2017
• Ghana SoilGrids; Compilation of Legacy Soil Data and the Production of Gridded Functional Soil Class and Property MapsNketia K.A., J.G.B. Leenaars, T. Hengl, E. Asamoah, M. Ruiperez Gonzalez and A. Owusu Ansah, 2016-12
• A spatial data infrastructure for storing and exchanging global soil dataKempen B., J. Mendes de Jesus, N.H. Batjes, E. Ribeiro, J.G.B. Leenaars, T. Hengl, 2016-10
• The global yield gap atlas for targeting sustainable intensification options for smallholders in Sub-Saharan AfricaClaessens, L, Cassman KG, van Ittersum MK, Leenaars JGB, van Bussel L, Wolf J, van Wart JP, Grassini P, Yang H, Boogaard H, de Groot H, Guilpart N, Heuvelink GBM, Stoorvogel JJ, Hendriks C, Keestra S, Mol G, Zaal A, Wallinga J, and Jansen B, 2015
• Soil map providing basic information for crop and site specific water and fertility recommendations in EthiopiaWösten, H, Leenaars JGB, Eyasu E, Keestra S, Mol G, Zaal A, Wallinga J, and Jansen B, 2015
• Soil information to feed the african soil, crop and peopleLeenaars, JGB, Ruiperez Gonzalez M, Hengl T, Mendes de Jesus J, Kempen B, Claessens L, van Bussel LGJ, Wolf J, Yang H, Cassman KG, van Ittersum MK, Heuvelink GBM, Batjes NH, Keestra S, Mol G, Zaal A, Wallinga J, and Jansen B, 2015
• Soil data harmonisation and geostatistical modelling efforts in support of improved studies of global sustainabilityBatjes, NH, Kempen B, Leenaars JGB, and van den Bosch H, 2015
• Root zone plant-available water holding capacity of the Sub-Saharan Africa soil, version 1.0. Gridded functional soil informationLeenaars, JGB, Hengl T, Ruiperez Gonzalez M, Mendes de Jesus J, Heuvelink GBM, Wolf J, van Bussel L, Claessens L, Yang H, and Cassman, KG, 2015
• Mapping of soil properties and land degradation risk in Africa using MODIS reflectanceVågen,T-G, Winowiecki,LA, Tondoh,JE, Desta,LT, Gumbricht,T, 2015
• Mapping soil properties of Africa at 250 m resolution: Random forests significantly improve current predictionsHengl, T, Heuvelink GBM, Kempen B, Leenaars JGB, Walsh MG, Shepherd KD, Sila A, MacMillan RA, Mendes de Jesus J, Tamene L, and Tondoh JE, 2015
• Comparative analysis of options for the spatial framework of yield gap analyses: a focus on soil dataClaessens, L, Cassman KG, van Ittersum MK, Leenaars JGB, van Bussel L, Wolf J, van Wart JP, Grassini P, Yang H, Boogaard H, de Groot H, Guilpart N, Heuvelink GBM, Stoorvogel JJ, Hendriks C, Keestra S, Mol G, Zaal A, Wallinga J, and Jansen B, 2015
• SoilGrids1km — Global Soil Information Based on Automated MappingHengl, T, Mendes de Jesus J, MacMillan RA, Batjes NH, Heuvelink GBM, Ribeiro E, Samuel-Rosa A, Kempen B, Leenaars JGB, Walsh MG, and Ruiperez Gonzalez M, 2014
• Africa Soil Profiles Database, Version 1.2. A compilation of georeferenced and standardised legacy soil profile data for Sub-Saharan Africa (with datasetLeenaars, JGB, van Oostrum AJM, and Ruiperez Gonzalez M, 2014
• Africa Soil Profiles Database: a compilation of georeferenced and standardised legacy soil profile data for Sub-Saharan AfricaLeenaars, JGB, Kempen B, van Oostrum AJM, and Batjes NH, 2014
• Quantification of total element concentrations in soils using total X-ray fluorescence spectroscopy (TXRF)Towett, E.K., Shepherd, K.D, Cadisch, G. 2013. Quantification of total element concentrations in soils using total X-ray fluorescence spectroscopy (TXRF). Science of the Total Environment 463–464: 374–388 http://www.sciencedirect.com/science/article/pii/S, 2013-10-01 [+]
  Total X-ray fluorescence spectroscopy (TXRF) determines concentrations of major and trace elements in multiple media. We developed and tested a method for the use of TXRF for direct quantification of total element concentrations in soils using an S2 PICOFOX™ spectrometer (Bruker AXS Microanalysis GmbH, Germany). We selected 15 contrasting soil samples from across sub-Saharan Africa for element analysis to calibrate the instrument against concentrations determined using the inductively coupled plasma-mass spectroscopy (ICP-MS) standard method. A consistent underestimation of element concentrations using TXRF compared to ICP-MS reference analysis occurred, indicating that spectrometer recalibration was required. Single-element recalibration improved the TXRF spectrometer's sensitivity curve. Subsequent analysis revealed that TXRF determined total element concentrations of Al, K, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, and Ga accurately (model efficacy/slope close to 1:1 line, and R2 > 0.80) over a wide range of soil samples. Other elements that could be estimated with an acceptable precision (R2 > 0.60) compared with ICP-MS although generally somewhat under- or overestimated were P, Ca, As, Rb, Sr, Y, Pr, Ta and Pb. Even after recalibration, compared to ICP-MS the TXRF spectrometer produced underestimations for elements Na, Mg, Ba, Ce, Hf, La, Nd, W and Sm and overestimations for elements Bi, Tl and Zr. We validated the degree of accuracy of the TXRF analytical method after recalibration using an independent set of 20 soil samples. We also tested the accuracy of the analysis using 2 multi-element standards as well as the method repeatability on replicate samples. The resulting total element concentration repeatability for all elements analyzed were within 10% coefficient of variability after the instrument recalibration except for Cd and Tl. Our findings demonstrate that TXRF could be used as a rapid screening tool for total element concentrations in soils assuming that sufficient calibration measures are followed.
• Soil hydraulic information for river basin studies in semi-arid regionsWosten, JHM, Verzandvoort, SJE, Leenaars, JGB, Hoogland, T, Wesseling, JG, 2013-03 [+]
  Water retention and hydraulic conductivity characteristics of the soil are indispensable for hydrological catchment modelling and for quantifying water limited agricultural production. However, these characteristics are often not available for regions and data scarcity for tropical zones is even bigger than for temperate zones. Use of pedotransfer functions which translate soil survey data into soil hydraulic characteristics is an interesting alternative in such cases. In this study, existing pedotransfer functions are identified and their performance is tested for the Limpopo river basin in Africa where distribution of limited water resources is a major challenge. The well performing pedotransfer function developed by Hodnett and Tomasella (2002) was used to translate the map units of the soil and terrain (SOTER) database for southern Africa into hydrological response units. Ten functional soil characteristics were calculated and clustering resulted in a reduction of the 713 SOTER map units for the Limpopo river basin to 14 hydrological response units. The resulting hydrological response unit map provides the required spatial information on soil physical input data, both water retention and hydraulic conductivity, for hydrological modelling of the river basin as well as for assessment of agricultural production. The developed procedure is an attractive approach for other, similar data scarce environments.
• Africa Soil Profiles Database, Version 1.0. A compilation of geo-referenced and standardized legacy soil profile data for Sub Saharan Africa (with dataset)Leenaars, JGB, ISRIC - World Soil Information, Wageningen, TN, project, ASoil Infor, 2013
• Soil property maps of Africa at 1 kmISRIC – World Soil Information, 2013
• Africa Soil Profiles Database, Version 1.1. A compilation of geo-referenced and standardized legacy soil profile data for Sub Saharan AfricaLeenaars, JGB, 2013
• Soil hydraulic information for river basin studies in semi-arid regionsWösten, JHM, Verzandtvoort SJE, Leenaars JGB, Hoogland T, and Wesseling JG, 2013
• Soil Heterogeneity and Soil Fertility Gradients in Smallholder Agricultural Systems of the East African HighlandsTittonell, P., Muriuki, A., Klapwijk, C.J., Shepherd, K.D., Coe, R., Vanlauwe, B. 2013. Soil Heterogeneity and Soil Fertility Gradients in Smallholder Agricultural Systems of the East African Highlands. Soil Science Society of America Journal 2013 77: 5, 2012-08-09 [+]
  Heterogeneity in soil fertility in these smallholder systems is caused by both inherent soil-landscape and human-induced variability across farms differing in resources and practices. Interventions to address the problem of poor soil fertility in Africa must be designed to target such diversity and spatially heterogeneity. Data on soil management and soil fertility from six districts in Kenya and Uganda were gathered to understand the determinants of soil heterogeneity within farms. Analysis of the variance of soil fertility indicators across 250 randomly selected farms (i.e., 2607 fields), using a mixed model that considered site, sampling frame, farm type, and field as random terms, revealed that the variation in soil organic C (6.5–27.7 g kg−1), total N (0.6–3.0 g kg−1), and available P (0.9–27 mg kg−1) was mostly related to differences in the inherent properties of the soils across sites (50 to 60% of total variance). Exchangeable K+ (0.1–1.1 cmol(+) kg−1), Ca2+ (1.5–14.5 cmol(+) kg−1), Mg2+ (0.6–3.7 cmol(+) kg−1), and pH (5.1–6.9) exhibited larger residual variability associated with field-to-field differences within farms (30 to 50%). Soil fertility indicators decreased significantly with increasing distance from the homesteads. When this variable was included in the model, the unexplained residual variances—associated with soil heterogeneity within farms—were 38% for soil C; 32% for total N; 49% for available P; 56, 49, and 38% for exchangeable K+, Ca2+ and Mg2+, respectively; and 49% for the pH. In allocating nutrient resources, farmers prioritized fields they perceived as most fertile, reinforcing soil heterogeneity. Categorization of fields within a farm with respect to distance from the homestead, and soil fertility classes as perceived by farmers, were identified as entry points to target soil fertility recommendations to easily recognizable, distinct entities.
• The challenges of collating legacy data for digital mapping of Nigerian soilsOdeh, I.O.A.; Leenaars, J.G.B.; Hartemink, A.E.; Amapu, I., 2012
• Africa Soil Profiles Database, Version 1.0. A compilation of geo-referenced and standardized legacy soil profile data for Sub Saharan Africa (with dataset).Leenaars, JGB, 2012
• Organic matter stabilization in soil aggregates: Understanding the biogeochemical mechanisms that determine the fate of carbon inputs in soilsVerchot, LV, Dutaur, L, Shepherd, KD, Albrecht, A, 2011-03-15 [+]
  We studied the biochemical and biophysical processes of carbon sequestration in an intensive agroforestry system on two soils (Feralsol – Luero; Arenosol – Teso) in W. Kenya to elucidate the mechanisms associated with long-term carbon storage. Specifically, we looked at a top-down model (macro-aggregates form around organic matter particles and micro-aggregates form within the macro-aggregates) and a bottom-up model (micro-aggregates form independently and are incorporated into macro-aggregates) of soil aggregate formation. Soil samples were collected from experiments on improved tree fallows using different species and two tillage treatments; water-stable aggregates were extracted and sorted into three size classes: macro-aggregates (> 212 μm), meso-aggregates (53–212 μm) and micro-aggregates (20–53 μm). Organic matter characterization of each fraction was based on 13C isotope abundance, Fourier transform infrared (FTIR) spectroscopy and the abundance of polysaccharides. Improved fallows increased soil C by 0.28 and 0.26 kg m­2 in the top 20 cm of the soil profile in Luero and Teso, respectively. Tillage altered the distribution of aggregates among size classes. Changes in the δ13C signature in each fraction indicated that more of the new carbon was found in the macro-aggregates (35–70%) and meso-aggregates (18–49%) in Luero and less (9–17%) was found in the micro-aggregates. In Teso, about 40–80% of the new aggregate C was found in the meso-aggregates, 14–45% was found in the micro-aggregates and only 4–26% was found in the macro-aggregates. The meso-aggregates and macro-aggregates to a lesser extent, in both sites, were enriched in carboxylic-C and aromatic-C, indicating the importance of OM decomposition and plant-derived C in the stabilization of larger aggregates, supporting the top-down model of aggregate formation. Microbially derived polysaccharides play a leading role in the formation of stable micro-aggregates and carboxylic-C promotes stabilization through surface occlusion. This bottom-up process is essential to promote long-term carbon sequestration in soils. Additionally, the micro-aggregates at both sites were enriched in polysaccharides and had elevated ratios of galactose + mannose:arabinose + xylose than the other aggregate fractions, indicating the importance of microbial processes in the formation of stable micro-aggregates and supporting the bottom-up model.
• Generic prediction of soil organic carbon in {Alfisols} using diffuse reflectance Fourier transformed mid-infrared spectroscopyKamau-Rewe, M, Rasche, F, Cobo, JG, Dercon, G, Shepherd, KD, Cadisch, G, 2011
• Factors influencing uptake of integrated soil fertility management knowledge among smallholder farmers in western KenyaAdolwa, IS, Esilaba, AO, Okoth, P, Mulwa, MR, 2010-11 [+]
  12th KARI Biennial Scientific Conference: Transforming agriculture for improved livelihoods through agricultural product
• Financial Value of Nitrogen Fixation in Soybean in Africa: Increasing Benefits for Smallholder FarmersChianu, JN, Huising, J, Danso, S, Okoth, P, Chianu, JN, Sanginga, N, 2010-10-30 [+]
  The knowledge that soil microorganisms form an important component of below ground biodiversity, providing ecosystem services, is often not incorporated in formulation of policies to conserve and manage these microorganisms. Using the method of cost replacement or cost savings in terms of mineral nitrogen fertilizer that would have been required to attain the same level of nitrogen-fixed biologically, this study contributes to awareness on the importance of these microorganisms. Applying the knowledge gained from several on-station and on-farm trials in Africa, complemented with assumptions on FAO-sourced data from 19 African countries, this study estimated the financial value of nitrogen fixation of legume nodulating bacteria (LNB) associated with promiscuous soybean varieties. Results show that the financial value of the nitrogen-fixing attribute of soybean in Africa, especially the promiscuous varieties, annually amounts to about $ 200 million US dollars across the 19 countries. With the fertilizer price of ~$ 795 t-1 (June 2008), this would amount to $ 375 million. The study recommends various ways of increasing the chances of smallholder farmers benefiting from the nitrogen-fixing attribute of LNB, especially since many cannot afford adequate quantities of inorganic fertilizers for increased crop productivity.
• The diversity of rural livelihoods and their influence on soil fertility in agricultural systems of East AfricaTittonell, P, Muriuki, A, Shepherd, KD, Mugendi, D, Kaizzi, KC, Okeyo, J, Verchot, LV, Coe, R, Vanlauwe, B, 2010-02 [+]
  Technological interventions to address the problem of poor productivity of smallholder agricultural systems must be designed to target socially diverse and spatially heterogeneous farms and farming systems. This paper proposes a categorisation of household diversity based on a functional typology of livelihood strategies, and analyses the influence of such diversity on current soil fertility status and spatial variability on a sample of 250 randomly selected farms from six districts of Kenya and Uganda. In spite of the agro-ecological and socio-economic diversity observed across the region (e.g. 4 months year−1 of food self-sufficiency in Vihiga, Kenya vs. 10 in Tororo, Uganda) consistent patterns of variability were also observed. For example, all the households with less than 3 months year−1 of food self-sufficiency had a land:labour ratio (LLR) 1 produced enough food to cover their diet for at least 5 months. Households with LLR < 1 were also those who generated more than 50% of their total income outside the farm. Dependence on off/non-farm income was one of the main factors associated with household diversity. Based on indicators of resource endowment and income strategies and using principal component analysis, farmers’ rankings and cluster analysis the 250 households surveyed were grouped into five farm types: (1) Farms that rely mainly on permanent off-farm employment (from 10 to 28% of the farmers interviewed, according to site); (2) larger, wealthier farms growing cash crops (8–20%); (3) medium resource endowment, food self-sufficient farms (20–38%); (4) medium to low resource endowment relying partly on non-farm activities (18–30%); and (5) poor households with family members employed locally as agricultural labourers by wealthier farmers (13–25%). Due to differential soil management over long periods of time, and to ample diversity in resource endowments (land, livestock, labour) and access to cash, the five farm types exhibited different soil carbon and nutrient stocks (e.g. Type 2 farms had average C, N, P and K stocks that were 2–3 times larger than for Types 4 or 5). In general, soil spatial variability was larger in farms (and sites) with poorer soils and smaller in farms owning livestock. The five farm types identified may be seen as domains to target technological innovations and/or development efforts.
• Application of a global soil spectral library as tool for soil quality assessment in Sub-Saharan AfricaTerhoeven-Urselmans, T, Shepherd, KD, Chabrillat, S, Ben-Dor, E, 2010 [+]
  A EUFAR Workshop on Quantitative Applications of Soil Spectroscopy
• Tripling crop yields in tropical AfricaSanchez, PA, 2010 [+]
  Between 1960 and 2000, Asian and Latin American food production tripled, thanks to the use of high-yielding varieties of crops. Africa can follow suit, but only if depletion of soil nutrients is addressed.
• Integrated soil fertility management: Operational definition and consequences for implementation and disseminationVanlauwe, B, Bationo, A, Chianu, JN, Giller, KE, Merckx, R, Mokwunye, U, Ohiokpehai, O, Pypers, P, Tabo, R, Shepherd, KD, Smaling, EMA, Woomer, PL, Sanginga, N, 2010 [+]
  Traditional farming systems in Sub-Saharan Africa depend primarily on mining soil nutrients. The African green revolution aims to intensify agriculture through the dissemination of integrated soil fertility management (ISFM). This paper develops a robust and operational definition of ISFM based on detailed knowledge of African farming systems and their inherent variability and of the optimal use of nutrients. The authors define ISFM as a set of soil fertility management practices that necessarily include the use of fertilizer, organic inputs and improved germplasm, combined with the knowledge on how to adapt these practices to local conditions, aimed at maximizing agronomic use efficiency of the applied nutrients and improving crop productivity. All inputs need to be managed in accordance with sound agronomic principles. The integration of ISFM practices into farming systems is illustrated with the dual-purpose grain legume–maize rotations in the savannas and fertilizer micro-dosing in the Sahel. Finally, the dissemination of ISFM practices is discussed.
• Ecology and Management of Soil Biodiversity in Mabira forest, Uganda: Towards Conservation and Sustainable ManagementRwakaikara-Silver, BE, Isabirye, A, Akol, C, Nkwiine, M, Okwakol, JN, Huising, J, Okoth, P, Brooijmans, W, Etyang, TB, 2010
• Effects of improved fallow with Sesbania sesban on maize productivity and Striga hermonthica infestation in Western KenyaSjögren H,, Shepherd, KD, Karlsson, A, 2010 [+]
  Striga hermonthica is a major constraint to smallholder subsistence agriculture production in the sub-Saharan African region. Low soil fertility and overall environmental degradation has contributed to the build-up of the parasitic weed infestation. Improved cropping systems have to be introduced to address the interrelated problems of S. hermonthica and soil fertility decline. Thus, the effects of improved fallow with leguminous shrub Sesbania sesban on maize yields and levels of S. hermonthica infestation on farm land in the bimodal highlands of western Kenya were investigated. The experimental treatments were arranged in a phased entry, and randomized complete block scheme were six months Sesbania fallow, 18 months Sesbania fallow, six months natural fallow consisting of regrowth of natural vegetation without cultivation, 18 months natural fallow, continuous maize cropping without fertilizer application, and continuous maize cropping with P and N fertilization. Results show that Sesbania fallows significantly (p<0.05) increase maize yield relative to continuous unfertilized maize. S. hermonthica plant populations decrease in continuous maize between the first season (mean = 428 000 ± 63 000 ha−1) and second season (mean=51 000 ± 15 000 ha−1), presumably in response to good weed management. S. hermonthica seed populations in the soil decrease throughout the duration of the experiment in the continuous maize treatments. Short-duration Sesbania fallows can provide modest yield improvements relative to continuous unfertilized maize, but short-duration weedy fallows are ineffective. Continuous maize cultivation with good weed control may provide more effective S. hermonthica control than fallowing.
• Mapping continuous depth functions of soil carbon storage and available water capacityMalone, BP, McBratney, AB, Minasny, B, Laslett, GM, 2009-12-15 [+]
  There is a need for accurate, quantitative soil information for natural resource planning and management. This information shapes the way decisions are made as to how soil resources are assessed and managed. This paper proposes a novel method for whole-soil profile predictions (to 1 m) across user-defined study areas where limited soil information exists. Using the Edgeroi district in north-western NSW as the test site, we combined equal-area spline depth functions with digital soil mapping techniques to predict the vertical and lateral variations of carbon storage and available water capacity (AWC) across the 1500 km2 area. Neural network models were constructed for both soil attributes to model their relationship with a suite of environmental factors derived from a digital elevation model, radiometric data and Landsat imagery. Subsequent fits of the models resulted in an R2 of 44% for both carbon and AWC. For validation at selected model depths, R2 values ranged between 20 and 27% for carbon prediction (RMSE: 0.30–0.52 log (kg/m3)) and between 8 and 29% for AWC prediction (RMSE: 0.01 m/m). Visually, reconstruction of splines at selected validation data points indicated an average fit with raw data values. In order to improve upon our model and validation results there is a need to address some of the structural and metrical uncertainties identified in this study. Nevertheless, the resulting geo-database of quantitative soil information describing its spatial and vertical variations is an example of what can be generated with this proposed methodology. We also demonstrate the functionality of this geo-database in terms of data enquiry for user-defined queries.
• A new information system for managing sub-Saharan Africa’s soil: Why and how?Walsh, MG, Ahamed, S, Hartemink, AE, Huising, J, Okoth, P, Palm, CA, Sanchez, PA, Sanginga, N, Shepherd, KD, Vågen, T-G, Winowiecki, LA, 2009
• Soil spectral diagnosticsShepherd, KD
• Below-ground Biodiversity in Sierra de Santa Marta, Los Tuxtlas, Veracruz, MexicoBarois, I, Huising, J, Okoth, P, Trejo, D, de Santos, LM
• Empirical estimates of uncertainty for mapping continuous depth functions of soil attributesMalone, BP, McBratney, AB, Minasny, B [+]
  We use an empirical method where model output uncertainties are expressed as a prediction interval (PI) of the underlying distribution of prediction errors. This method obviates the need to identify and determine the contribution of each source of uncertainty to the overall prediction uncertainty. Conceptually, in the context of digital soil mapping, rather than a single point estimate at every prediction location, a PI, characterised by upper and lower prediction limits, encloses the prediction (which lies somewhere on the interval) and ideally the true but unknown value 100(1 − α)% of times on average the target variable (typically 95%). The idea is to partition the environmental covariate feature space into clusters which share similar attributes using fuzzy k-means with extragrades. Model error for predicting a target variable is then estimated from which cluster PIs are constructed on the basis of the empirical distribution of errors associated with the observations belonging to each cluster. PIs for each non-calibration observation are then formulated on the basis of the grade of membership each has to each cluster. We demonstrate how we can apply this method for mapping continuous soil depth functions. First, using soil depth functions and digital soil mapping (DSM) methods, we map the continuous vertical and lateral distribution of organic carbon (OC) and available water capacity (AWC) across the Edgeroi district in north-western NSW, Australia. From those predictions we define a continuous PI for each prediction node, generating upper and lower prediction limits of both attributes. From an external validation dataset, preliminary results are encouraging where 91% and 93% of the OC and AWC observations respectively fall within the bounds of their 95% PIs. Ideally, 95% of instances should fall within these bounds.
• Spearheading collation, access and exchange of soil information in Africavan den Bosch H., S. Mantel, B.H. Batjes and J.G.B. Leenaar
• Digital Soil Map of the WorldSanchez, PA, Ahamed, S, Carr, F, Hartemink, AE, Hempel, J, Huising, J, Lagacherie, P, McBratney, AB, McKenzie, NJ, Mendon, MDL, Minasny, B, Montanarella, L, Okoth, P, Palm, CA, Sachs, JD, Shepherd, KD, Vågen, T-G, Vanlauwe, B, Walsh, MG, Winowiecki, LA, Z [+]
  Soils are increasingly recognized as major contributors to ecosystem services such as food production and climate regulation (1, 2), and demand for up-to-date and relevant soil information is soaring. But communicating such information among diverse audiences remains challenging because of inconsistent use of technical jargon, and outdated, imprecise methods. Also, spatial resolutions of soil maps for most parts of the world are too low to help with practical land management. While other earth sciences (e.g., climatology, geology) have become more quantitative and have taken advantage of the digital revolution, conventional soil mapping delineates space mostly according to qualitative criteria and renders maps using a series of polygons, which limits resolution. These maps do not adequately express the complexity of soils across a landscape in an easily understandable way.
• Developing SoilML as a global standard for the collation and transfer of soil data and informationMontanarella, L, Wilson, P, Cox, S, McBratney, AB, Ahamed, S, McMillan, B, Jacquier, D, Fortner, J
• Homosoil, a methodology for quantitative extrapolation of soil information across the globeMallavan, BP, Minasny, B, McBratney, AB [+]
  In many places in the world, soil information is difficult to obtain and can be non-existent. When no detailed map or soil observation is available in a region of interest, we have to extrapolate from other parts of the world. This chapter will discuss the Homosoil method, which assumes homology of soil-forming factors between a reference area and the region of interest. This includes: climate, physiography, and parent materials. The approach will involve seeking the smallest taxonomic distance of the scorpan factors between the region of interest and other reference areas (with soil data) in the world. Using the digital information of soil climate from the Climate Research Unit (CRU) (solar radiation, rainfall, temperature, and evapo-transpiration), topography from the HYDRO1k (elevation, slope, and compound topographic index), and lithology of the world on a 0.5°× 0.5° grid, we calculated Gower’s similarity index between an area of interest and the rest of the world. The rules calibrated in the reference area can be applied in the region of interest realising its limitations and extrapolation consequences.
• The Solution to Global Warming Could Be in the SoilOkoth, P, Huising, J, Jefwa, J, Okoth, S, Ayuke, F, Mung, J [+]
  14th meeting of the Subsidiary Body on Scientific, Technical and Technological Advice of the Convention on Biological Diversity
• The upsurge of soil science and the new global soil map.Hartemink, AE [+]
  Proceedings 9th International Conference of the East and Southeast Asia Federation of Soil Science Societies, Seoul, South Korea
• Rapid estimation of soil engineering properties using diffuse reflectance near infrared spectroscopyWaruru BK, Shepherd KD, Ndegwa GM, Kamoni PT, Sila AM. 2014. Rapid estimation of soil engineering properties using diffuse reflectance near infrared spectroscopy. Biosystems Engineering 121:177-185. [+]
  Materials testing involve complex reference methods and several soil tests have been used for indexing material functional attributes for civil engineering applications. However, conventional laboratory methods are expensive, slow and often imprecise. The potential of soil diffuse reflectance near infrared (NIR) spectroscopy for the rapid estimation of selected key engineering soil properties was investigated. Two samples sets representing different soils from across the Lake Victoria basin of Kenya were used for the study: A model calibration set (n = 136) was obtained using a conditioned Latin hypercube sampling, and a validation set (n = 120) using a spatially stratified random sampling strategy. Spectral measurements were obtained for air-dried (<2 mm) soil sub-samples using a Fourier-transform diffuse reflectance near infrared (NIR) spectrometer. Soil laboratory reference data were also obtained for liquid limit (LL), plastic limit (PL), plasticity index (PI), linear shrinkage (LS), coefficient of linear extensibility (COLE), volumetric shrinkage (VS), clay activity number (Ac), total clay content, air-dried moisture content, and cation exchange capacity (CEC). Soil reference data were calibrated to smoothed first derivative NIR spectra using partial least squares (PLS) regression. At the calibration stage, coefficient of determination for full cross-validation (R2) of ≥0.70 was obtained for CEC, mc, LL, PI, LS, COLE and VS. Further independent validation gave R2 ≥ 0.70 and RPD (ratio of reference data SD and root mean square error of prediction) 1.7–2.2 for LL, PI, mc and CEC. The results suggested that NIR–PLS has potential for the rapid estimation of several key soil engineering properties. Further work should focus on extending calibration libraries using more diverse soil types and testing alternative infrared diffuse reflectance based methods.
• Soil spectroscopy: an opportunity to be seizedNocita M, Stevens A, van Wesemael B, Brown DJ, Shepherd KD, Towett, E, Vargase R, Montanarella L. 2014. Soil spectroscopy: an opportunity to be seized. Global Change Biology. Article first published online. 21 Jun 2014, DOI: 10.1111/gcb.12632