More than half of the cultivation\uffe2\uff80\uff90induced carbon loss from agricultural soils could be restored through improved management. To incentivise carbon sequestration, the potential of improved practices needs to be verified. To date, there is sparse empirical evidence of carbon sequestration through improved practices in East\uffe2\uff80\uff90Africa. Here, we show that agroforestry and restrained grazing had a greater stock of soil carbon than their bordering pair\uffe2\uff80\uff90matched controls, but the difference was less obvious with terracing. The controls were treeless cultivated fields for agroforestry, on slopes not terraced for terracing, and permanent pasture for restrained grazing, representing traditionally managed agricultural practices dominant in the case regions. The gain by the improved management depended on the carbon stocks in the control plots. Agroforestry for 6\uffe2\uff80\uff9320\uffc2\uffa0years led to 11.4 Mg\uffc2\uffa0ha\uffe2\uff88\uff921 and restrained grazing for 6\uffe2\uff80\uff9317\uffc2\uffa0years to 9.6\uffc2\uffa0Mg\uffc2\uffa0ha\uffe2\uff88\uff921 greater median soil carbon stock compared with the traditional management. The empirical estimates are higher than previous process\uffe2\uff80\uff90model\uffe2\uff80\uff90based estimates and indicate that Ethiopian agriculture has greater potential to sequester carbon in soil than previously estimated.
", "keywords": ["AFRICA", "Carbon Sequestration", "ta1172", "agricultural practices", "GREENHOUSE-GAS MITIGATION", "East-Africa", "soil", "HIGHLANDS", "mitigation", "Soil", "NORTHERN ETHIOPIA", "SYSTEMS", "MANAGEMENT", "STOCKS", "2. Zero hunger", "SOIL ORGANIC-MATTER", "CLIMATE-CHANGE", "LAND-USE", "carbon stock", "Agriculture", "04 agricultural and veterinary sciences", "ta4111", "Models", " Theoretical", "15. Life on land", "Carbon", "Environmental sciences", "climate change", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "https://doi.org/10.1111/gcb.13288"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcb.13288", "name": "item", "description": "10.1111/gcb.13288", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcb.13288"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-06-01T00:00:00Z"}}, {"id": "28139267", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-25T16:22:51Z", "type": "Journal Article", "created": "2017-01-28", "title": "When is a terrace not a terrace? The importance of understanding landscape evolution in studies of terraced agriculture", "description": "Before the invention of modern, large-scale engineering projects, terrace systems were rarely built in single phases of construction, but instead developed gradually, and could even be said to have evolved. Understanding this process of landscape change is therefore important in order to fully appreciate how terrace systems were built and functioned, and is also pivotal to understanding how the communities that farmed these systems responded to changes; whether these are changes to the landscape brought about by the farming practices themselves, or changes to social, economic or climatic conditions. Combining archaeological stratigraphy, soil micromorphology and geochemistry, this paper presents a case-study from the historic and extensive terraced landscape at Konso, southwest Ethiopia, and demonstrates - in one important river valley at least - that the original topsoil and much of the subsoil was lost prior to the construction of hillside terraces. Moreover, the study shows that alluvial sediment traps that were built adjacent to rivers relied on widespread hillside soil erosion for their construction, and strongly suggests that these irrigated riverside fields were formerly a higher economic priority than the hillside terraces themselves; a possibility that was not recognised by numerous observational studies of farming in this landscape. Research that takes into account how terrace systems change through time can thus provide important details of whether the function of the system has changed, and can help assess how the legacies of former practices impact current or future cultivation.", "keywords": ["2. Zero hunger", "2311", "2305", "Agriculture", "06 humanities and the arts", "15. Life on land", "Landscape evolution", "01 natural sciences", "Terraces", "Soil", "Archaeology", "Rivers", "Land management", "0601 history and archaeology", "Ethiopia", "2308", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://eprints.whiterose.ac.uk/112206/1/Ferro_Vazquez_et_al_JEMA_2017.pdf"}, {"href": "https://doi.org/28139267"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "28139267", "name": "item", "description": "28139267", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/28139267"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-11-01T00:00:00Z"}}, {"id": "10.5281/zenodo.17067648", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-25T16:20:54Z", "type": "Dataset", "title": "Potential annual soil loss by erosion (RUSLE), Ethiopia", "description": "unspecifiedAverage annual soil loss (t ha-1 yr-1) calculated using the Revised Universal Soil Loss Equation (RUSLE): A = R \u00d7 K \u00d7 LS \u00d7 C \u00d7 P. This model estimates sheet and rill erosion risk based on five factors: rainfall erosivity (R), soil erodibility (K), topography (LS), cover-management (C), and support practices (P). The resulting map supports erosion risk assessment and soil conservation planning in Ethiopia. Each input layer (R, K, LS, C, P) was derived as a separate spatial dataset as follows: R factor: Rainfall erosivity factor (MJ mm ha\u207b\u00b9 h\u207b\u00b9 yr\u207b\u00b9). Derived by clipping the global rainfall erosivity dataset of Panagos et al. (2017, https://doi.org/10.1038/s41598-017-04282-8), as published in Panagos et al. (2023, https://doi.org/10.1016/j.dib.2023.1094820), to the administrative country boundry of Ethiopia. K factor:\u00a0 Soil erodibility factor ((Mg/ha)[(MJ/ha)(mm/h)]\u207b\u00b9), calculated following the method of Torri et al. (1997, https://doi.org/10.1016/S0341-8162(97)00036-2).\u00a0 The input sand, silt, clay and soil organic carbon maps were obtained from SoilGrids (https://doi.org/10.5194/soil-7-217-2021) LS factor: Topographic factor computed using slope and flow accumulation following the method of Luvai et al. (2021, https://doi.org/10.7176/JEES/11-16-06), and applied to areas with slope <50% in accordance with Panagos, Borrelli, and Meusburger (2015, https://doi.org/10.1016/j.scitotenv.2015.01.008). The LS factor was derived from the MERIT Digital Elevation Model (https://doi.org/10.1002/2017GL072874). C factor: Cover-management factor, calculated following the method of Negese (2024: https://doi.org/10.1016/j.rsase.2023.101089), using NDVI data derived from Landsat 8 Surface Reflectance Tier 1 Collection 2 imagery (2018\u20132023) (https://www.usgs.gov/landsat-missions/landsat-8). P factor: Support practices factor. P = 1 due to data gaps. This research was carried out for the LSC-IS hubs project under the funding program Development Smart Innovation through Research in Agriculture (DeSIRA), European Union. EU Contribution Agreement to MinBUZA: FOOD/2020/419-433 ; MinBUZA to WUR\u00a0Grant number: 4000004100. \u00a0 Coordinate Reference System -\u00a0EPSG:20138", "keywords": ["Soil", "Land", "Mapping", "Soil erosion", "RUSLE", "Agriculture", "Ethiopia", "Crop production", "Modelling"], "contacts": [{"organization": "Colman, Betony", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17067648"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17067648", "name": "item", "description": "10.5281/zenodo.17067648", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17067648"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-09-06T00:00:00Z"}}, {"id": "10.5281/zenodo.6566752", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-08-25T16:21:08Z", "type": "Dataset", "title": "Soil carbon stock, litter decomposition, and weather data from Ethiopian forests", "description": "Open AccessIntroduction 100 sampling units (SU) were selected from the total of 631 SUs of the Forest Reference Level submission 2017 (FRL 2017). The sampling was designed unbiased for total growing stock per SU, altitude,and mean litter depth per SU. The actual field sampling succeeded on 98 of the pre-selected SUs due to accessibility restrictions. Soil profile sampling Soil sampling was performed from November 2017 till mid-January 2018. Samples were taken from undisturbed soil from depths of 0-10 cm, 10-20 cm, and 20-30 cm below the organic layer. Volumetric samples of 107.5 cm3 were taken vertically, using a 10 cm long conically shaped corer with a cutting lower edge diameter of 37 mm and upper diameter of 40 mm. Composite samples were formed by combining the volumetric samples taken from different depths of two parallel soil profiles. The samples were transported to EEFRI Soil Laboratory in Addis Ababa after 1-4 weeks of sampling at distant locations. Soil physical characteristics The soil samples were air-dried, homogenized, and subjected to oven-drying at 105\u00b0C until constant mass. Total bulk density was determined using the total dry mass and volume of the composite samples. Organic carbon content (C % by wet oxidation method), and soil physical characteristics: moisture content, bulk density of the total sample, and bulk density of fine fraction (particles passing the 2 mm sieve). The mass of the coarse fraction was weighed. The soil fine fraction was also subjected to laser diffraction for more accurate particle size analysis for proportions of clay, silt, and sand. In addition to this 28 samples were also analyzed for C content in the laboratory of Natural Resources Institute Finland to determine C content by LECO CHN analyzer. This was done to calibrate the bulk of wet digestion-based estimates (Fig. 1). Before analysis, the soils were tested for the presence of inorganic C. For Figure 1. See Soil_C_Ethiopia.pdf Figure 1. Comparison of results from wet oxidation (Walkley-Black) and dry oxidation (CHN analyzer). The dotted line shows the theoretical 1:1 match between the axis, the solid line shows linear regression (intercept = 0) between the methods. The estimated slope value of 1.165 was used in adjusting the wet digestion results to match those obtained by dry oxidation: OCadj = 1.165 * OCwet. Based on a linear regression between the wet and dry oxidation analysis results, a correction factor of 1.165 was applied to adjust the organic C% obtained by wet digestion. The adjusted data are shown in the file \u201cSOC_Ethiopia_2017-2018.csv\u201d. SOC stocks were calculated by multiplying the proportion of organic C with BD of fine earth, after which the result was corrected for stoniness, a visually estimated proportion of large stones (S, value from 0 to 1) in the soil profile that could not be included in the volumetric soil samples (FAO VS-FAST). (SOCstock = C_{org} * BD_{fe} * (1-S) ) Soil organic carbon stock data Files: \u201cSOC_Ethiopia_2017-2018.csv\u201d and \u201cSOC_Ethiopia_2017-2018.xlsx\u201d The file includes soil characteristics from layers of 0-10 cm, 10-20 cm, and 20-30 cm below the loose organic layer on top of the soil. The data are used for SOC stock estimation in the respective layers as described above. In the .csv file individual columns are for LAT is the latitude of the sampling site corresponding to FieldCode and SU_nr LON is the longitude of the sampling site corresponding to FieldCode and SU_nr The coordinates are expressed as decimal degrees of the WGS84 system FieldCode refers to the Region and Sampling Unit number of the Ethiopian NFI (see below) SU_nr is the Sampling Unit number of the Ethiopian NFI Region is the name of the administrative region where the sample was taken Biome is the name of the forest biome type where the sample was collected BiomeSimplified is the name of a biome with some close types combined DepthRange is the upper and lower limit of the soil sample in the field, cm StoninessVFAST is a percentage of stones (VS-FAST by FAO) in the ca. 40 cm deep soil profile exposed during the sampling FreshMassInField is the mass of the total composite soil sample of the given layer, g, primarily indicative of checking the correct number of subsamples in composite NrComposites is the number of subsamples included in the composite for each soil layer CorerVolume is a constant of 107.5 cm3 because only one type of corer was used for undisturbed, volumetric sampling CompositeVolume is the volume of the composite sample for each soil depth layer CoarseFractionMass is the dry mass, g of soil particles > 2mm that did not pass the sieve, but were included in the sample volume FE_DryMass is oven-dry mass, g of the fine fraction that passed the 2 mm sieve. BDtot is total bulk density, g m-3, calculated for the composite sample BDfe is the bulk density of the fine earth fraction, g m-3 OC_adj is organic carbon (OC) content (%) in the composite sample, adjusted according to the comparison between dry and wet oxidation methods (Fig. 1) SOCfe is SOC stock calculated for soil fine earth fraction, t ha-1 in the 10 cm deep soil layer SOCfe_stoniness is SOC stock of the fine earth fraction, t ha-1 in the 10 cm deep soil layer, adjusted for stoniness. The correction assumes that the volume occupied by larger stones would be void of OC. Litter stock data File: \u201cLitter_Ethiopia_2017-2018.csv\u201d The file includes measurements of litter layer on Ethiopian NFI Sampling Unit (SU) sites where sampling for SOC stock determination was done. The depth of the litter layer was measured in the SU\u2019s of the NFI, and this data contains in addition to depth also a volumetric sample of the litter layer. The dry bulk density was used to calculate the carbon stocks in the litter pool. The depth of the litter layer was measured in the field. Litter from the respective spot was sampled quantitatively from a frame of 0.01m2 of area for litter dry mass estimate. The organic C stock in a litter (L) was calculated as, (L = {M over z} * {C_{om} over A}, ) where M = Dry mass of the litter sample, g z = Depth of the litter layer in the field, m Com = Conversion factor from dry organic matter to carbon (C), 0.5 A = area of quantitative collection of litter (0.01 m2) In the .csv file individual columns are for LAT, LON is the GPS coordinates (decimal degrees of WGS84) for the Sampling Units (SU_ID) SU_ID is the Sampling Unit identification number of the Ethiopian NFI FieldCode refers to the Region and Sampling Unit number of the Ethiopian NFI (see below) Region is the name of the administrative region where the sample was taken Litter_dry is the dry mass, g of the litter sample Area_m2 is the area, m2 of litter sampling MeanLitterDepth is the mean depth of the litter layer at the sampling area CDensityLitter is the dry bulk density of the litter, g m-2 multiplied by the assumed organic C proportion of the oven-dry litter materials (0.50) LitterCStock_tha is the litter stock, t ha-1 calculated from the C density of the litter layer Litter bag data (decomposition and quality) The leaves and twigs were sampled from 2 species (Juniperus and Podocarpus) and 3 locations of the elevation gradient in the Chilimo forest (Table 1). The forest was considered an old-growth with Juniperus procera and Podocarpus falcatusbeing the main species forming the tree canopy. The sites form an elevation gradient (Table 1). Table 1. Geographical locations of the study sites in the Chilimo forest. id Latitude (deg.) Longitude (deg.) Elevation (m a.s.l) 1 9.0672 38.1443 2500 2 9.0712 38.1556 2670 3 9.0869 38.1684 2800 The dying and dead leaves were sampled directly from the trees later referred to as \u201cfresh\u201d and from the branches found on the ground, referred to as \u201cold\u201d. The old leaves were assumed to be dead for around 3 months. The diameter of the branches/twigs was less than 1 cm in diameter. The samples were first sorted and air-dried in an elevated temperature of the greenhouse and thereafter oven-dried in the oven overnight at 45 \u00b0C. The samples were analyzed for acid, water, ethanol dissolved,and undissolved fractions (AWEN) (Table 2) and for the decomposition rates of the litter installed into the litter bags corresponding to each of the Chilimo sites. Table 2. Acid, water, ethanol (A, W, E, respectively) dissolved and undissolved fractions (N) from the litter components of the dominant tree species in the Chilimo forest. Litter type Species A W E N leaves fresh Juniperus 0.45 0.13 0.1 0.33 leaves fresh Podocarpus 0.42 0.28 0.05 0.25 leaves old Juniperus 0.44 0.07 0.08 0.41 leaves old Podocarpus 0.44 0.09 0.05 0.42 twigs Juniperus 0.61 0.04 0.02 0.32 twigs Podocarpus 0.56 0.15 0.02 0.27 A sufficient amount of litter was placed into the litter bags (polyurethane mesh 1 mm) and the mesh bags were installed on top of the soil surface under the forest canopy (later referred to as \u201ccanopy\u201d) and in the forest gap caused by harvesting (later referred as \u201copen\u201d). The installation of the litter bags (for each species 3 replicates of each litter type for each site and canopy type for the 3 periods, in total 12 litter bags for leaves and 6 bags for twigs) was done on 22.9.2017. The mesh bags were left on the ground, protected from grazing by the fence, and retrieved subsequently on 12.10.2017, 31.10.2017, and 12.12.2017. Despite the efforts took few samples were lost. The retrieved samples were oven-dried and initial mass and mass loss data for each period and litter type with a detailed description of the variables can be found in the file \u201clitter.chilimo_07.02.22.xlsx\u201d. Soil temperature data During the period from 22.9.2017 to 12.12.2017, we monitored the soil temperature at 5 cm depth under the canopy and in the open canopy on all Chilimo sites continuously every 4 hours intervals with the Maxim iButton temperature loggers. However, some sensors were lost. Daily means and their standard deviation of the continuous temperatures can be found in the file \u201csoil.temp.chilimo_07.02.22.xlsx\u201d. Processed weather data The air temperature and precipitation data for 98 sampling units corresponding to soil carbon data originated from 73 weather stations located across Ethiopia and were obtained from Ethiopian Meteorological Agency (http://www.ethiomet.gov.et/). Sampling units were joined with weather data by the closest proximity to their corresponding weather stations. Precipitation was unaltered. The air temperature required correction by elevation is described in more detail in Lehtonen et al. (2020). The monthly values of air temperature and precipitation with an accompanied readme description of the variables can be found for 98 sampling units in the file \u201csampling.units98_meteo_07.02.22.xlsx\u201d and the Chilimo study sites in the file \u201cmonthly.weather.chilimo_07.02.22.xlsx\u201d. The monthly values in the file 'sampling.units98_meteo_07.02.22.xlsx' correspond to long-term average over the period from 1986 to 2017. References: Lehtonen, A., \u0164upek, B., Nieminen, T.M., Bal\u00e1zs, A., Anjulo, A., Teshome, M., Tiruneh, Y. and Alm, J., 2020. Soil carbon stocks in Ethiopian forests and estimations of their future development under different forest use scenarios. Land Degradation & Development, 31(18), pp.2763-2774. FRL 2017. https://redd.unfccc.int/files/ethiopia_frel_3.2_final_modified_submission.pdf", "keywords": ["2. Zero hunger", "REDD", " soil carbon stock", " litter bag studies", " Ethiopia", "15. Life on land", "6. Clean water"], "contacts": [{"organization": "Alm, Jukka, \u0164upek, Boris, Anjulo, Agena, Teshome, Mindaye, Tiruneh, Yibeltal, Abay, Abebe, Alebachew, Mehari, Tervahauta, Arja, Lehtonen, Aleksi,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.6566752"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.6566752", "name": "item", "description": "10.5281/zenodo.6566752", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.6566752"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-20T00:00:00Z"}}, {"id": "10.7910/DVN/QTACSN", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-25T16:21:53Z", "type": "Dataset", "title": "An integrated approach for understanding the factors that facilitate or constrain the adoption of soil carbon enhancing practices in East Africa, Kenya and Ethiopia.", "description": "The survey data on soil carbon enhancing practices in Ethiopia is systematically organized in Microsoft Excel tables. The data entails general household characteristics, plot characteristics, crops grown, yield, practices implemented, inputs, livestock ownership, social capital, access to credit, access to extension services.", "keywords": ["Agricultural economics", "Agricultural Sciences", "Soil carbon enhancing practices", "Land management", "Earth and Environmental Sciences", "Africa", "land management", "agricultural economics", "Decision and Policy Analysis - DAPA", "Ethiopia", "Natural resources", "natural resources", "Low soil fertility"], "contacts": [{"organization": "Ng\u2019ang\u2019a, Stanley Karanja, Gelaw, Fekadu, Nguru, Wilson Maina, Magambo Kanyenji, George, Girvetz, Evan,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/QTACSN"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/QTACSN", "name": "item", "description": "10.7910/DVN/QTACSN", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/QTACSN"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/FNEGDP", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-25T16:21:52Z", "type": "Dataset", "title": "Current and future forage suitability maps for Ethiopia and Kenya", "description": "This data was produced using Targeting Tools \u2013 a web-based GIS tool, which matches a suitability criteria that include climate and environmental requirements for each of the forage varieties with a spatial database that\u2019s comprises organic carbon, soil PH, annual precipitation, mean temperature, growing days and elevation data to characterize the suitability.", "keywords": ["Forage", "Agricultural Sciences", "Forage suitability", "Agrobiodiversity - AGBIO", "Earth and Environmental Sciences", "Maps", "Africa", "forage", "Ethiopia", "Agroecosystems and Sustainable Landscapes - ASL", "Kenya"], "contacts": [{"organization": "Mutua, John, Notenbaert, An,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/FNEGDP"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/FNEGDP", "name": "item", "description": "10.7910/DVN/FNEGDP", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/FNEGDP"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "2580184031", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-25T16:22:47Z", "type": "Journal Article", "created": "2017-01-28", "title": "When is a terrace not a terrace? The importance of understanding landscape evolution in studies of terraced agriculture", "description": "Before the invention of modern, large-scale engineering projects, terrace systems were rarely built in single phases of construction, but instead developed gradually, and could even be said to have evolved. Understanding this process of landscape change is therefore important in order to fully appreciate how terrace systems were built and functioned, and is also pivotal to understanding how the communities that farmed these systems responded to changes; whether these are changes to the landscape brought about by the farming practices themselves, or changes to social, economic or climatic conditions. Combining archaeological stratigraphy, soil micromorphology and geochemistry, this paper presents a case-study from the historic and extensive terraced landscape at Konso, southwest Ethiopia, and demonstrates - in one important river valley at least - that the original topsoil and much of the subsoil was lost prior to the construction of hillside terraces. Moreover, the study shows that alluvial sediment traps that were built adjacent to rivers relied on widespread hillside soil erosion for their construction, and strongly suggests that these irrigated riverside fields were formerly a higher economic priority than the hillside terraces themselves; a possibility that was not recognised by numerous observational studies of farming in this landscape. Research that takes into account how terrace systems change through time can thus provide important details of whether the function of the system has changed, and can help assess how the legacies of former practices impact current or future cultivation.", "keywords": ["2. Zero hunger", "Soil", "2311", "Rivers", "2305", "Agriculture", "0601 history and archaeology", "Ethiopia", "06 humanities and the arts", "2308", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://eprints.whiterose.ac.uk/112206/1/Ferro_Vazquez_et_al_JEMA_2017.pdf"}, {"href": "https://doi.org/2580184031"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2580184031", "name": "item", "description": "2580184031", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2580184031"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-11-01T00:00:00Z"}}, {"id": "6fd2f113-9c67-49a4-99e1-8c6c7d4d5e72", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-17.0, -34.0], [-17.0, 17.5], [49.0, 17.5], [49.0, -34.0], [-17.0, -34.0]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Angola"}, {"id": "Benin"}, {"id": "Botswana"}, {"id": "Burkina Faso"}, {"id": "Burundi"}, {"id": "Cameroon"}, {"id": "Central African Republic"}, {"id": "Chad"}, {"id": "Demcratic Republic of the Congo"}, {"id": "Eswatini"}, {"id": "Ethiopia"}, {"id": "Gabon"}, {"id": "Ghana"}, {"id": "Guinea"}, {"id": "Guinea-Bissau"}, {"id": "Kenya"}, {"id": "Lesotho"}, {"id": "Madagascar"}, {"id": "Malawi"}, {"id": "Mali"}, {"id": "Mauritania"}, {"id": "Mozambique"}, {"id": "Namibia"}, {"id": "Niger"}, {"id": "Nigeria"}, {"id": "Republic of the Congo"}, {"id": "Rwanda"}, {"id": "Senegal"}, {"id": "Sierra Leone"}, {"id": "Somalia"}, {"id": "South Africa"}, {"id": "South Sudan"}, {"id": "Sudan"}, {"id": "Tanzania"}, {"id": "Togo"}, {"id": "Uganda"}, {"id": "Zambia"}, {"id": "Zimbabwe"}], "scheme": "Region"}], "updated": "2021-07-14T11:51:39", "type": "Dataset", "language": "eng", "title": "Africa Soil Profiles Database, version 1.0", "description": "ISRIC World Soil Information is compiling legacy soil profile data of Sub Saharan Africa, as a project activity of the AfSIS project (Globally integrated Africa Soil Information Service). http://africasoils.net/services/data/soil-databases/\n\nAfrica Soil Profiles database, version. 1.0 (April 2012) identifies less than 15700 unique soil profiles inventoried from a wide variety of data sources. From the less than 14600 profiles that are geo-referenced, soil layer attribute data are available for less than 12500 and soil analytical data for less than 10000 profiles. The database includes, but is not limited, to the soil attributes specified by GlobalSoilMap.net. Soil attribute values are standardized according to e-SOTER conventions and validated according to routine rules. Odd values are flagged. The degree of validation, and associated reliability of the data, varies because reference soil profile data, that are previously and thoroughly validated, are compiled together with non-reference soil profile data of lesser inherent representativeness.\n \nUpdated milestone versions of the dataset have been posted online and made available to the project serving as input to the soil property maps generated by AfSIS. The continuously growing dataset will also be made available through the World Soil Information Service upon continuation of the project activity. The version is released here is version 1.0., the latest version is 1.1.", "formats": [{"name": "zip"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["soil profiles", "Soil science", "Angola", "Benin", "Botswana", "Burkina Faso", "Burundi", "Cameroon", "Central African Republic", "Chad", "Demcratic Republic of the Congo", "Eswatini", "Ethiopia", "Gabon", "Ghana", "Guinea", "Guinea-Bissau", "Kenya", "Lesotho", "Madagascar", "Malawi", "Mali", "Mauritania", "Mozambique", "Namibia", "Niger", "Nigeria", "Republic of the Congo", "Rwanda", "Senegal", "Sierra Leone", "Somalia", "South Africa", "South Sudan", "Sudan", "Tanzania", "Togo", "Uganda", "Zambia", "Zimbabwe"], "contacts": [{"name": "Ad van Oostrum", "organization": "ISRIC - World Soil Information", "position": "Guest researcher", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "ad.vanoostrum@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}, {"name": "Johan Leenaars", "organization": "ISRIC - World Soil Information", "position": "Senior soil scientist", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "johan.leenaars@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}], "denominator": "2500000"}, "links": [{"href": "https://files.isric.org/public/afsp/AF-AfSP1.0.zip", "name": "Download", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://isric.org/projects/africa-soil-profiles-database-afsp", "name": "Project webpage", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://isric.org/sites/default/files/isric_report_2012_03.pdf", "name": "Report", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://files.isric.org/public/thumbnails/afsp/AfSP010Qry_ISRIC.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "6fd2f113-9c67-49a4-99e1-8c6c7d4d5e72", "name": "item", "description": "6fd2f113-9c67-49a4-99e1-8c6c7d4d5e72", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/6fd2f113-9c67-49a4-99e1-8c6c7d4d5e72"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1925-01-01T00:00:00Z", "2011-01-01T00:00:00Z"]}}, {"id": "b3df7f8d-aa90-4206-a11c-5d95b4dd2327", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-17.0, -34.0], [-17.0, 17.5], [49.0, 17.5], [49.0, -34.0], [-17.0, -34.0]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Angola"}, {"id": "Benin"}, {"id": "Botswana"}, {"id": "Burkina Faso"}, {"id": "Burundi"}, {"id": "Cameroon"}, {"id": "Central African Republic"}, {"id": "Chad"}, {"id": "Demcratic Republic of the Congo"}, {"id": "Eswatini"}, {"id": "Ethiopia"}, {"id": "Gabon"}, {"id": "Ghana"}, {"id": "Guinea"}, {"id": "Guinea-Bissau"}, {"id": "Kenya"}, {"id": "Lesotho"}, {"id": "Madagascar"}, {"id": "Malawi"}, {"id": "Mali"}, {"id": "Mauritania"}, {"id": "Mozambique"}, {"id": "Namibia"}, {"id": "Niger"}, {"id": "Nigeria"}, {"id": "Republic of the Congo"}, {"id": "Rwanda"}, {"id": "Senegal"}, {"id": "Sierra Leone"}, {"id": "Somalia"}, {"id": "South Africa"}, {"id": "South Sudan"}, {"id": "Sudan"}, {"id": "Tanzania"}, {"id": "Togo"}, {"id": "Uganda"}, {"id": "Zambia"}, {"id": "Zimbabwe"}], "scheme": "Region"}], "updated": "2021-07-14T11:52:31", "type": "Dataset", "language": "eng", "title": "Africa Soil Profiles Database, version 1.1", "description": "The Africa Soil Profiles Database, Version 1.1, is compiled by ISRIC - World Soil Information (World Data Center for Soils) as a project activity for the Globally integrated- Africa Soil Information Service (AfSIS) project (www.africasoils.net/data/legacyprofile). 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The value of each pixel represents the total annual evaporation for that specific year. 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By relating biomass production to total Evapotranspiration (sum of soil evaporation, canopy transpiration and interception), this indicator provides insights on the impact of vegetation development on consumptive water use and thus on water balance in a given domain. When the focus is on monitoring performance of irrigated agriculture in relation to water consumption, it is more appropriate to use transpiration alone as a denominator, as a measure of water beneficially consumed by the plant. This latter indicator, for which we use the term \\\"net water productivity\\\", provides useful information on how effectively vegetation (and particularly crops) uses water to develop its biomass (and thus yield). 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