Effects of land cover on ecosystem services in Tanzania: A spatial assessment of soil organic carbon

AbstractThe multiple ecosystem services provided by healthy soil are well known and include soil carbon sequestration to mitigate climate change, a medium for plant and agricultural production and regulating the hydrologic cycle. Despite the wide recognition of the importance of these services, drivers of soil organic carbon (SOC) dynamics across various land uses in East Africa are poorly understood. The objectives of this study were threefold: to quantify SOC stocks across Tanzania; assess the effect of land cover and erosion on SOC; and investigate the relationship between inherent and dynamic soil properties under diverse land uses. The Land Degradation Surveillance Framework (LDSF) was used to assess the variability of ecological metrics at different spatial scales. SOC was quantified within and between different land cover types (forest, woodland, shrubland, grassland and cropland) in Tanzania. A total of 2052 soil samples from 1082–1000m2 plots were collected from seven 100-km2 sentinel sites in 2010. Composite soil samples were collected at each plot from two depths (0–20 and 20–50cm) and cumulative soil mass samples were collected to 100cm. Soil samples were analyzed using a combination of traditional analytical laboratory methods and mid-infrared spectroscopy (MIR). Model performance of MIR spectral predictions for carbon was good, with an R2 of >0.95 and RMSEP of 4.3gkg−1, when using an independent validation datasets. Woodland and cropland were the most frequently occurring vegetation structure types in the sampled sites, with 388 and 246 plots, respectively. Average topsoil OC (and range) was 12.4 (1.5–81.4) gCkg−1 (n=1082) and average subsoil OC (and range) was 7.3 (0.64–53.8) gCkg−1 (n=970) for the seven sites. Forested plots had the highest mean topsoil organic carbon concentrations (17.3gCkg−1) followed by cropland (13.3gCkg−1), for all sites included in the study, but with high levels of variability between sites. Soil mass at 30cm was measured and these data were used to calculate carbon stocks for the different land cover types. An approach based on remote sensing was explored for the mapping of SOC stocks at 30cm for Tanzania using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery from 2012. Results indicate that the use of image reflectance for the mapping of SOC stocks has promising potential, with R2 values ranging from 0.77 to 0.81 and RMSEP values from 0.90 to 1.03kgm−2 for the three validation datasets. There is high utility of these maps for strategic land management interventions that prioritize ecosystem services

A practical guide for collecting farmers socio-economic and agronomic data: an AfSIS Project field protocol

One of the aims of the AfSIS (Africa Soil Information Service) project is to document farmers’ characteristics and practices to determine their ability to engage in effective soil and crop management. This document outlines how agronomic surveys are integrated with knowledge of farmers’ condition, wealth, status, access to knowledge, and access to markets, using pre-designed questionnaires and field surveys, and including the use of Global Positioning System-based field surveys and Geographic Information Systems

Maize response to macronutrients and potential for profitability in sub-Saharan Africa

The final publication is available at Springer via http://dx.doi.org/10.1007/s10705-015-9717-2Sub-Saharan Africa (SSA) is plagued by low productivity and little research is available on the attainable responses and profitability to applied nutrients under variable environments. The objective of this study was to determine the attainable maize grain response to and potential of profitability of N, P and K application in SSA using boundary line approaches. Data from experiments conducted in SSA under AfSIS project (2009–2012) and from FAO trials database (1969–1996) in 15 countries and constituting over 375 different experimental locations and 6600 data points are used. Both response to fertilizer and value cost ratio (VCR) are highly variable and no more than 61 % cases for N, 43 % for P and 25 % for K attain VCR of 2 or more. Also, based on the recent AfSIS data, VCR exceeds 1 in just 67 % (N), 57 % (P) and 40 % (K) of the cases, even when best management practices are applied on a research farm, and interest rates are zero. Chances for profitability are highest when soil organic carbon is 1–2 % and control maize grain yield is 1–3 t ha−1 but also depends on relatively static soil properties (primarily texture and mineralogy) that are not under farmer control. We conclude that return on investment of macronutrient fertilizer is highly variable and can be substantially increased by helping farmers decide where to apply the fertilizers. Consequently, farmers need access to information on factors influencing economic returns of fertilizer use in order to make the right decisions

Looking back and moving forward: 50 years of soil and soil fertility management research in sub-Saharan Africa

Article purchased; Published online: 02 Nov 2017Low and declining soil fertility has been recognized for a long time as a major impediment to intensifying agriculture in sub-Saharan Africa (SSA). Consequently, from the inception of international agricultural research, centres operating in SSA have had a research programme focusing on soil and soil fertility management, including the International Institute of Tropical Agriculture (IITA). The scope, content, and approaches of soil and soil fertility management research have changed over the past decades in response to lessons learnt and internal and external drivers and this paper uses IITA as a case study to document and analyse the consequences of strategic decisions taken on technology development, validation, and ultimately uptake by smallholder farmers in SSA. After an initial section describing the external environment within which soil and soil fertility management research is operating, various dimensions of this research area are covered: (i) ‘strategic research’, ‘Research for Development’, partnerships, and balancing acts, (ii) changing role of characterization due to the expansion in geographical scope and shift from soils to farms and livelihoods, (iii) technology development: changes in vision, content, and scale of intervention, (iv) technology validation and delivery to farming communities, and (v) impact and feedback to the technology development and validation process. Each of the above sections follows a chronological approach, covering the last five decades (from the late 1960s till today). The paper ends with a number of lessons learnt which could be considered for future initiatives aiming at developing and delivering improved soil and soil fertility management practices to smallholder farming communities in SSA