Near-infrared spectra for the AfSIS Sentinel Sites in Tanzania

The Africa Soil Information Service (AfSIS), was a project led by the Tropical Soil Biology and Fertility Institute (TSBF) of the International Center for Tropical Agriculture (CIAT), based in Nairobi, in collaboration with several partners including the World Agroforestry Centre (ICRAF). The AfSIS projectf aimed to narrow sub-Saharan Africa’s (SSA) soil information gap and provide a consistent baseline for monitoring soil ecosystem services. Sentinel sites were established and top- and subsoil samples were collected from each subplot at 0-20 cm and 20-50 cm depth increments, respectively, and pooled (composited) into one sample for each plot and depth, resulting in a total of 320 standard soil samples per sentinel site (Vågen et al., 2010). These samples were analyzed using near-infrared (NIR) spectroscopy. NIR spectral measurements were conducted through regional laboratories in eastern, southern and West Africa (Vågen et al., 2010). The NIR spectral laboratory network used standard instrumentation and standard operating procedures to ensure reproducibility of results among laboratories and over time (Vågen et al., 2010). The ICRAF laboratory provided technical backstopping and quality control for the network of NIR spectral laboratories. This is the complete dataset of the NIR spectra matched with the Sentinel Site sample details for all seven AfSIS sentinel sites sampled and analyzed in Tanzania in 2010. Reference: Vågen, T-G., Shepherd, K., Walsh, M., Winowiecki, L., Desta, L. and Tondoh, J. 2010. Soil health surveillance: Technical specifications. World Agroforestry Centre (ICRAF). Nairobi, Kenya

Near-infrared spectra for the AfSIS Sentinel Sites in Tanzania

The Africa Soil Information Service (AfSIS), was a project led by the Tropical Soil Biology and Fertility Institute (TSBF) of the International Center for Tropical Agriculture (CIAT), based in Nairobi, in collaboration with several partners including the World Agroforestry Centre (ICRAF). The AfSIS projectf aimed to narrow sub-Saharan Africa s (SSA) soil information gap and provide a consistent baseline for monitoring soil ecosystem services. Sentinel sites were established and top- and subsoil samples were collected from each subplot at 0-20 cm and 20-50 cm depth increments, respectively, and pooled (composited) into one sample for each plot and depth, resulting in a total of 320 standard soil samples per sentinel site (Vågen et al., 2010). These samples were analyzed using near-infrared (NIR) spectroscopy. NIR spectral measurements were conducted through regional laboratories in eastern, southern and West Africa (Vågen et al., 2010). The NIR spectral laboratory network used standard instrumentation and standard operating procedures to ensure reproducibility of results among laboratories and over time (Vågen et al., 2010). The ICRAF laboratory provided technical backstopping and quality control for the network of NIR spectral laboratories. This is the complete dataset of the NIR spectra matched with the Sentinel Site sample details for all seven AfSIS sentinel sites sampled and analyzed in Tanzania in 2010.Reference:Vågen, T-G., Shepherd, K., Walsh, M., Winowiecki, L., Desta, L. and Tondoh, J. 2010. Soil health surveillance: Technical specifications. World Agroforestry Centre (ICRAF). Nairobi, Kenya

Wet chemistry data for a subset of AfSIS: Phase I archived soil samples

This dataset contains a subset of the samples collected during the AfSIS Phase I project and was a collaborative effort between World Agroforestry (ICRAF) and Rothamsted Research. The soil samples were retrieved from ICRAF Soil Archive: https://worldagroforestry.org/output/icraf-soil-archive-physical-archive-systematically-collected-soil-samples and subject to wet chemical analysis at Rothamsted Research in the UK under a Global Challenges Research Fund project, "BBS/OS/GC/000014B: Chemical and Biological Assessment of AfSIS soils" funded through the UK Biotechnology and Biological Sciences Research Council. This dataset includes the Site, Cluster, Plot as well as the GPS coordinates and wet chemistry data from 2002 samples collected from 18 countries and 51 LDSF sites. The original data collection was part of the AfSIS Phase I project, funded by the Bill and Melinda Gates Foundation (BMGF) and took place between 2009-2013. ICRAF and CIAT contributed the Site, Cluster, Plot and GPS coordinates for the soil samples, ICRAF organized the sub-sampling of the soil samples from the ICRAF physical archive in Nairobi and Rothamsted analysed the soil samples in the UK in 2017 and 2018. Visit our websites here: https://worldagroforestry.org/landhealth and https://www.rothamsted.ac.uk/. The AfSIS Phase I project funded by the Bill and Melinda Gates Foundation (BMGF) from 2009-2013, aimed to provide a consistent baseline of soil information across sub-Saharan Africa (SSA). Led by CIAT-TSBF, partners included: ISRIC, CIESIN, The Earth Institute at Columbia University and World Agroforestry (ICRAF). ICRAF led the systematic assessments of soil health using the Land Degradation Surveillance Framework (LDSF), which was developed at ICRAF, http://landscapeportal.org/blog/2015/03/25/the-land-degradation-surveillance-framework-ldsf/. LDSF sites were randomized using spatial stratification based on Koeppen-Geiger Climate zones across 19 countries in SSA. In total 60 LDSF sites were sampled. Soil samples were collected using the LDSF at two depths, 0-20 cm (labelled Topsoil) and 20-50 cm (labelled Subsoil). In each LDSF site, approximately 320 standard soil samples were collected. All of these were also scanned using MIR Spectroscopy and are available on Dataverse here: Vågen, Tor-Gunnar;Winowiecki, Leigh Ann;Desta, Luseged;Tondoh, Ebagnerin Jérôme;Weullow, Elvis;Shepherd, Keith;Sila, Andrew, 2020, "Mid-Infrared Spectra (MIRS) from ICRAF Soil and Plant Spectroscopy Laboratory: Africa Soil Information Service (AfSIS) Phase I 2009-2013", https://doi.org/10.34725/DVN/QXCWP1, World Agroforestry - Research Data Repository, V1

Large-scale controls of soil organic carbon in (sub)tropical soils

Soil organic carbon (SOC) is a key component of terrestrial ecosystems. Experimental studies have shown that soil texture and geochemistry have a strong effect on carbon stocks. However, those findings primarily rely on data from temperate regions or use model approaches that are often based on limited data from tropical and sub-tropical regions. Here, we evaluate the controls on soil carbon stocks in Africa, using a dataset of 1,580 samples. These were collected across Sub-Saharan Africa (SSA) within the framework of the Africa Soil Information Service (AfSIS) project, which was built on the well-established Land Degradation Surveillance Framework (LDSF). Samples were taken from two depths (0–20 cm and 20–50 cm) at 46 LDSF sites that were stratified according to Koeppen-Geiger climate zones. The different pH-values, clay content, exchangeable cations and extractable elements across various soils of the different climatic zones (i.e. from arid to humid (sub)tropical) allow us to identify different soil and climate parameters that best explain SOC variance across SSA. We tested if these SOC predictors differed across climatological conditions, using the ratio of potential evapotranspiration (PET) to mean annual precipitation (MAP) as indicator. For water-limited regions (PET/MAP > 1), the best predictors were climatic variables, likely because of their effect on the quantity of carbon inputs. Geochemistry dominated SOC storage in energy-limited systems (PET/MAP < 1), reflecting its effect on carbon protection. On a continental scale, climate (e.g. PET) is key to predicting SOC content in topsoil, whereas geochemistry, particularly iron-oxyhydroxides and aluminum-oxides, is more important in subsoil. Clay content had little influence on SOC at both depths. These findings contribute to an improved understanding of the controls on SOC stocks in tropical and sub-tropical regions

Continental-scale controls on soil organic carbon across sub-Saharan Africa

Earlier studies have demonstrated that soil texture and geochemistry strongly affect soil organic carbon (SOC) content. However, those findings primarily rely on data from temperate regions with soil mineralogy, weathering status and climatic conditions that generally differ from tropical and sub-tropical regions. We investigated soil properties and climate variables influencing SOC concentrations across sub-Saharan Africa. A total of 1,601 samples were analyzed, collected from two depths (0–20 cm and 20–50 cm) at 45 sentinel sites from 17 countries as part of the Africa Soil Information Service (AfSIS) project. The dataset spans climatic conditions from arid to humid and includes soils with a wide range of pHH20 values, weathering status, soil texture, exchangeable cations, extractable metals and a variety of important land cover types. The most important SOC predictors were identified by linear mixed effects models, regression trees and random forest models. Our results indicate that SOC is primarily controlled by aridity index (PET/MAP), exchangeable calcium (Caex) and oxalate-extractable aluminum (Alox); this was found across both depth intervals. Oxalate-extractable iron (Feox) emerged as the most important predictor for both depth intervals in the regression tree and random forest analyses. However, its influence on SOC concentrations was strong only below Feox concentrations of 0.25 wt %. This suggests that Feox can act as a pedogenic threshold – even on a continental scale. Across model-ling approaches, clay and fine silt content (< 8 µm) and land cover were not significant SOC pre-dictors, in contrast to common assumptions. Our findings indicate that the key controlling factors of SOC across sub-Saharan Africa are similar to what has been reported for temperate regions – except for soil texture and vegetation cover. However, the strength and importance of the controlling factors vary across the environmental gradient we studied

Mid-Infrared Reflectance Spectroscopy for Estimation of Soil Properties of Alfisols from Eastern India

Mid-infrared (MIR) spectroscopy is emerging as one of the most promising technologies, as it is a rapid and cost-effective alternative to routine laboratory analysis for many soil properties. This study was conducted to evaluate the potential of mid-infrared spectroscopy for the rapid and nondestructive measurement of some important soil properties of Alfisols. A total of 336 georeferenced soil samples fromthe 0&ndash;15 cm soil layer of Alfisols that were collected from the eastern Indian states of Odisha and Jharkhand were used. The partial least-squares regression (PLSR), random forest, and support vector machine regression techniques were compared for the calibration of the spectral data with the wet chemistry soil data. The PLSR-based predictive models performed better than the other two regression techniques for all the soil properties, except for the electrical conductivity (EC). Good predictions with independent validation datasets were obtained for the clay and sand percentages and for the soil organic carbon (SOC) content, while satisfactory predictions were achieved for the silt percentage and the pH value. However, the performance of the predictive models was poor in the case of the EC and the extractable nutrients, such as the available phosphorus and potassium contents of the soil. Specific regions of the MIR spectra that contributed to the prediction of the soil SOC, the pH, and the clay and sand percentages were identified. The study demonstrates the potential of the MIR spectroscopic technique in the simultaneous estimation of the SOC content, the sand, clay, and silt percentages, and the pH of Alfisols from eastern India