Keith D. Shepherd

Digital Soil Map of the World

Increased demand and advanced techniques could lead to more refined mapping and management of soils. 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such information among diverse audiences remains challenging because of inconsistent use of technical jargon, and outdated, imprecise methods.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.

Integrated Soil Fertility Management: Operational Definition and Consequences for Implementation and Dissemination

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.

Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions

80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. Over the period 2008–2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management—organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na). We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15–75% in Root Mean Squared Error (RMSE) across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols) help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring pedological knowledge from data rich countries to countries with limited soil data.

Infrared spectroscopy—enabling an evidence-based diagnostic surveillance approach to agricultural and environmental management in developing countries

Science-based approaches to agricultural and environmental management are needed to accelerate development progress in the worlds poorest countries. We present a diagnostic surveillance framework modelled on medical diagnostic approaches for evidence-based management of agriculture and environment in developing countries. Infrared (IR) spectroscopy can play a pivotal role in making the surveillance framework operational, by providing a rapid, low cost and highly reproducible diagnostic screening tool. We review the wide applicability of IR spectroscopy for setting up measurement systems for the management of soils, crops, agricultural inputs, livestock health, agricultural products and water quality. IR spectroscopy is already being used in the design of soil surveillance systems, but the principles are generally applicable. A new evidence-based interpretation approach to plant analysis, combining plant and soil IR spectroscopy measurements, is proposed. Finally, an idealised design is proposed for making IR spectroscopy-based diagnostic surveillance operational in developing countries over the next ten years. Large area surveillance frameworks for agricultural and environmental problems will deploy integrated spectral indicators of soil, crop and livestock health and water quality. Spectral indicators will help to quantify risk factors associated with problems and assess intervention impacts. Smallholder farmers will have access to IR spectroscopy-based analysis of soils, crops and inputs through a network of hand-held or mobile IR spectroscopy units. Agricultural processing industries will make extensive use of IR spectroscopy on the factory floor to add value to agricultural produce and improve food safety. Regional centres of scientific and technological excellence will be required to support (i) high quality laboratory reference analyses, (ii) development of IR spectroscopy calibration databases and interpretation systems and (iii) up-grading of scientific and technical skills through training and education. Key challenges for adoption of this design include (i) building human capacity in science- and technology-based approaches, (ii) development of rugged low cost IR spectroscopy instrumentation and (iii) development of decision support systems to interpret IR spectroscopy data into management recommendations.

Factors affecting the use of fertilizers and manure by smallholders: the case of Vihiga, western Kenya

Sub-Saharan Africa faces huge food supply challenges due to increasing human population, limited opportunities to increase arable land, and declining yields associated with continuously declining soil fertility. To cater for their food requirements, smallholders use only modest levels of inorganic fertilizers and rely to a large extent on manure, which is generally of low quality. To explore factors influencing fertilizer and manure use at the farm level, 253 farm households in Vihiga district of western Kenya were sampled. A pair of Tobit models was used to relate amounts of manure and fertilizer used to household variables. The results indicate that the use of both manure and fertilizer reciprocally influence each other and are strongly influenced by household factors, and also imply that manure and fertilizer uses are endogenous. Policy changes are required to (1) reduce the burden on farming alone in rural areas; (2) promote the use of higher-cost, higher-value inputs such as fertilizers; (3) improve access to input and output markets; and (4) encourage farmer education so as to promote sustainable soil fertility management. Improved understanding of the biophysical and socioeconomic environment of smallholder systems can help target sustainable soil fertility interventions more appropriately.

Quantification of total element concentrations in soils using total X-ray fluorescence spectroscopy (TXRF)☆

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 spectrometers 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 R(2)>0.80) over a wide range of soil samples. Other elements that could be estimated with an acceptable precision (R(2)>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.

The global Land-Potential Knowledge System (LandPKS): Supporting evidence-based, site-specific land use and management through cloud computing, mobile applications, and crowdsourcing

Agricultural production must increase significantly to meet the needs of a growing global population with increasing per capita consumption of food, fiber, building materials, and fuel. Consumption already exceeds net primary production in many parts of the world (Imhoff et al. 2004). In addition to reducing consumption, there are two options to meet these needs: production intensification and land conversion. Both strategies present unique opportunities, challenges, and risks. The largest gains achievable through agricultural intensification will likely occur on lands with the largest unrealized production potential, or yield gap. These lands have high potential production and low current production. Similarly, the highest returns on investments to be gained by land conversion should occur on lands with the highest potential production, assuming similar infrastructure, per acre conversion costs, and other market conditions. The biggest long-term risk for both strategies is that application of nonsustainable land management practices will result in soil degradation that is often costly, if not impossible, to reverse. Exploiting these opportunities and minimizing risks depend on careful matching of production systems with the sustainable production potential of each type of land. Similar analyses can be applied to biodiversity conservation to prioritize land conservation and restoration efforts. The ability…

Soil spectroscopy: an opportunity to be seized

c Whashington State University, 405 Johnson Hall, PO Box 646420, Pullman, WA 99164-6420 USA d World Agroforestry Centre (ICRAF), United Nations Avenue, PO Box 30677, 00100 Nairobi Kenya e Food and Agriculture Organization (FAO), Viale delle Terme di Caracalla 00153 Rome, Italy * Corresponding author. Via Enrico Fermi 2749 e TP 280, I-21027 Ispra, VA, Italy. Tel.: +39 0332 78 3682; fax: +39 0332 78 6394. E-mail addresses: marco.nocita@jrc.ec.europa.eu; marco.nocita@gmail.com

A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study

We focus on project cost, benefit and risk analysis.We propose a modelling framework that uses a hybrid and dynamic Bayesian network(BN).BN offers unique features of analysing risk scenarios and budget policies.It uses uncertainty and variability of risk and economic factors in its predictions.The framework is illustrated by a case study of agricultural development projects. Successful implementation of major projects requires careful management of uncertainty and risk. Yet such uncertainty is rarely effectively calculated when analysing project costs and benefits. This paper presents a Bayesian Network (BN) modelling framework to calculate the costs, benefits, and return on investment of a project over a specified time period, allowing for changing circumstances and trade-offs. The framework uses hybrid and dynamic BNs containing both discrete and continuous variables over multiple time stages. The BN framework calculates costs and benefits based on multiple causal factors including the effects of individual risk factors, budget deficits, and time value discounting, taking account of the parameter uncertainty of all continuous variables. The framework can serve as the basis for various project management assessments and is illustrated using a case study of an agricultural development project.

Terrestrial pyrogenic carbon export to fluvial ecosystems: lessons learned from the White Nile watershed of East Africa

Pyrogenic carbon (PyC) is important because of its role in the global organic C (OC) cycle and in modifying soil properties. However, our understanding of PyC movement from terrestrial to fluvial ecosystems is not robust. This study examined (i) whether erosion or subsurface transport was more important for PyC export from headwaters, (ii) whether PyC was exported preferentially to total OC (TOC), and (iii) whether the movement of PyC from terrestrial to aquatic ecosystems provides an explanation for the coupling of PyC and non-PyC observed in rivers at a global scale. In the Guineo-Congolian highland forest region of western Kenya, duplicate catchments with sizes of 1–12 ha were equipped with stream gauges in primary forest and adjacent mixed agricultural landscapes that were cleared by fire 10, 16, or 62 years before. Stream water samples were taken weekly throughout 1 year and compared with runoff to assess PyC movement. Additional stream samples were taken from all major tributaries of the White Nile watershed of Lake Victoria. PyC was not found to be preferentially eroded relative to TOC or non-PyC, as topsoil (0–0.15 m) PyC concentrations (6.3 ± 0.3% of TOC; means and standard errors) were greater than runoff sediment (1.9 ± 0.4%) and dissolved PyC concentrations (2.0 ± 0.4%, n = 252). In addition, PyC proportions in eroded sediment were lower than and uncorrelated (r2 = 0.04; P = 0.14) with topsoil PyC. An enrichment of PyC was found with depth in the soil, from 6.3 ± 0.3% of TOC in the topsoil (0–0.15 m) to 12.3 ± 0.3% of TOC at 1–2 m. Base flow PyC proportions of TOC correlated well with subsoil PyC (r2 = 0.57; P   0.05). Similar PyC proportions were found in the studied headwater streams (2.7 ± 0.2%), their downstream inflow into Lake Victoria (3.7%), the other nine major rivers into Lake Victoria (4.9 ± 0.8%), and its outflow into the White Nile (1.1%). A strong positive correlation between dissolved PyC and non-PyC (r2 = 0.91; P < 0.0001) in the headwater streams reflect relationships previously seen for a range of globally important rivers, and contrasts with a negative relationship for suspended sediments (r2 = −0.5; P < 0.0001). The estimated PyC export from the Lake Victoria watershed of 11 Gg yr−1 may therefore originate to a large extent from subsoil pathways in dissolved form that appeared to be an important source of PyC in aquatic environments and may explain the coupling of PyC and non-PyC at a global scale.