Dataverse World Agroforestry (ICRAF)
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Growth of Dacryodes edulis F1 from breeding at Mbalmayo field site, Cameroon 2017
No full textGrowth evaluatio
Local agro-ecological knowledge of farmers in Bugesera District, Rwanda
No full textThis is a data set and a report on local agro-ecological knowledge of farmers in Bugesera District, Rwand
Soil Spectra and Wet Chemistry Measurements from ICRAF Soil-Plant Spectral Diagnostics Laboratory and Rothamsted Research: Africa Soil Information Service (AfSIS) Phase 2 Project Data 2014-2018 - TanSIS
No full textAfSIS Phase 2 was a collaborative project funded by the Bill and Melinda Gates Foundation (BMGF). Partners included, Columbia Global Center Africa (CGCA), Earth Institute (EI), International Soil Reference and Information Centre (ISRIC), Tanzania Agricultural Research Institute (TARI), Rothamsted Research (RRes) and World Agroforestry (ICRAF).
The project aimed to assist national programs in four African countries (Ethiopia, Ghana, Nigeria and Tanzania) to transition to modern agricultural research and data collection practices that were expected to result in faster agricultural development cycles.
In Tanzania, a country wide sampling targeting mainly the croplands was conducted. A total of 29,300 soil samples were collected at both 0-20cm, 20-50cm soil depths. All the samples collected were scanned using the four ZnSe Alpha I spectrometers at Selian Research Lab, Arusha, Tanzania. A subset of 461 soil samples was shipped to ICRAF and scanned on two spectrometers (HTS-xt and ZnSe Alpha I). The same 461 soil samples were also sent to RRes for wet chemistry analysis. The spectra data scanned at Selian (using ZnSe Alpha I) and that scanned at ICRAF Nairobi (using HTS-xt Tensor 27) and wetchem data (analyzed at RRes) are available on Dataverse here
Growth, flowering and fruiting of Allanblackia floribunda at Mbalmayo field site, Cameroon 2014-2016.
No full textGrowth, flowering and fruitin
Minimum Dietary Diversity for Women Survey
No full textTest-Retest of data collection mode on dietary diversity data (via the Minimum Dietary Diversity for Women indicator) and poverty data (via the Progress Out of Poverty Index) for women of reproductive age (15-49 years) in Kenya. Modes tested were face-to-face interviews and computer assisted telephone interviews (CATI). Data were collected in November and December 2016
Replication data for: Positioning fruit trees into climate change / variability scenarios: opportunities and constraints in the placement of fruit tree species in payment for environmental services.
No full textExtreme environmental conditions due to climate change or variability are a threat to crop production, productivity and livelihoods. Thus, providing alternative livelihoods to communities, especially the rural masses remain an important catalyst in reducing poverty, food insecurity and deforestation in the development of climate change/variability scenarios. This is critical in southern Africa where poverty, deforestation rate and food insecurity are high. These are challenges that rural development programs abating impacts of climate change/variability must address. Planting trees including those outside the forest has been a possible climate change mitigation or adaptation measure. Surprisingly, planting fruit trees have been given little attention and have always aligned to food security, but not their contribution to carbon sequestration and payment for environmental services (PES). There have been limited research studies quantifying carbon sequestration capacities in diverse fruit tree species. This contributes to low profile of fruit tree species in carbon trading. While the emphasis has been on forest trees, those trees outside the fore
st have also a role to play, especially with proper fruit orchard management systems and propagation protocols that maximize carbon reservoirs. This paper reviews the role of fruit trees in the context of carbon quantities sequestered and the reasons they should be considered in PES or better still carbon trading. It is envisaged that proper fruit tree orchard management practices and propagation protocols can be designed to increase carbon sequestration, while gaining some socio-economic benefits. We hypothesize that proper management of fruit trees offers an opportunity to extend and maximize fruit productivity and carbon storage over a long period. This provides a diverse development option within the framework of climate change/variability mitigation/adaptation. Planting fruit tree species presents many opportunities, but there are still limited documented research studies and piloted projects on any form of PES, especially carbon trading. It is clear that many research studies are warranted to quantify carbon storage within diverse fruit orchards and under different management systems
Replication data for: Mapping Leaf Area Index in subtropical upland ecosystems using RapidEye imagery and the randomForest algorithm.iForest - Biosciences and Forestry
No full textCanopy leaf area, frequently quantified by the Leaf Area Index (LAI), serves as the dominant control over primary production, energy exchange, transpiration, and other physiological attributes related to ecosystem processes. Maps depicting the spatial distribution of LAI across the landscape are of particularly high value for a better understanding of ecosystem dynamics and processes, especially over large and remote areas. Moreover, LAI maps have the potential to be used by process models describing energy and mass exchanges in the biosphere/ atmosphere system. In this article we assess the applicability of the RapidEye satellite system, whose sensor is optimized towards vegetation analyses, for mapping LAI along a disturbance gradient, ranging from heavily disturbed shrub land to mature mountain rainforest. By incorporating image texture features into the analysis, we aim at assessing the potential quality improvement of LAI maps and the reduction of uncertainties associated with LAI maps compared to maps based on Vegetation Indexes (VI) solely. We identified 22 out of the 59 image features as being relevant for predicting LAI. Among these, especially VIs were ran
ked high. In particular, the two VIs using RapidEyeÃÂâÃÂÃÂÃÂÃÂs RED-EDGE band stand out as the top two predictor variables. Nevertheless, map accuracy as quantified by the mean absolute error obtained from a 10-fold cross validation (MAE_CV) increased significantly if VIs and texture features are combined (MAE_CV = 0.56), compared to maps based on VIs only (MAE_CV = 0.62). We placed special emphasis on the uncertainties associated with the resulting map addressing that map users often treat uncertainty statements only in a pro-forma manner. Therefore, the LAI map was complemented with a map depicting the spatial distribution of the goodness-of-fit of the model, quantified by the mean absolute error (MAE), used for predictive mapping. From this an area weighted MAE (= 0.35) was calculated and compared to the unweighted MAE of 0.29. Mapping was done using randomForest, a widely used statistical modeling technique for predictive biological mapping
Replication data for: Can Integration of Legume Trees Increase Yield Stability in Rainfed Maize Cropping Systems in Southern Africa?
No full textGrowing maize (Zea mays) in association with legume tree in agroforestry arrangements has been shown to increase yields in many parts of sub-Saharan Africa (SSA). However, the stability of crop yields has not been critically analyzed in the various cropping systems that integrate leguminous trees. The objective of this analysis was to compare yield stability in improved cropping systems, namely maize-Gliricidia (Gliricidia sepium) intercropping and fertilized monoculture maize, with the de facto practice of resource-poor farmers who grow maize continuously without any external input. Yield stability was determined for three long-term field trials (12-13 consecutive years) conducted at Makoka Research Station in southern Malawi and Msekera Research Station in eastern Zambia. At Makoka, the most stable yield was recorded in maize-Gliricidia intercrops. Average yield was highest in maize-Gliricidia intercropping amended with 50% of the recommended N and P fertilizer, and this was comparable with yield recorded in monoculture maize that received inorganic fertilizer. On the two sites at Msekera, the highest yield was recorded in fertilized monoculture maize followed by maize-Gliricidia intercrops. However, yields were more stable in maize-Gliricidia intercropping compared to fertilized maize on both sites at Msekera. It is concluded that maize yields remain more stable in maize-Gliricidia intercropping than in fertilized maize monoculture in the longterm although average yields may be higher with full fertilization
Replication data for: Effect of organic fertilizer on the growth and fruit yield of six paprika (Capsicum annum L.) cultivars in Malawi
No full textThe production of paprika (Capsicum annum L.) under small-scale farm conditions in southern Africa is constrained by low soil fertility and lack of appropriate cultivars. The objective of this study was to determine the growth responses and fruit yields of six cultivars of paprika to organic and inorganic nutrient sources. The study was conducted in 2007 and 2008 at Chitedze Agricultural Research Station in Malawi. A combination of six paprika cultivars and four nutrient sources, namely (1) organic input from Gliricidia, (Gliricidia sepium) biomass, (2) inorganic fertilizer, (3) integrated nutrient input (Gliricidia biomass + inorganic fertilizer), and (4) control (no nutrient input) were compared. Each combination was replicated five times. A split-plot design was used where nutrient sources formed the main plot and cultivars the sub-plots. Plant height differed due to nutrient source in 2007 and 2008, while differences due to cultivar were minor
Africa RISING Project
No full textThe research was supported through the USAID funded project Africa RISING (Research in Sustainable Intensification for the Next Generation). The project was launched as part of the US government Feed the Future initiative to address global hunger and food security issues in key farming systems in sub-Saharan Africa. This study was focussed on identifying existing sustainable intensive agricultural methods in Sinana woreda, Oromo region. The study also collected local knowledge on agricultural methods so as to assist in the development and implementation of appropriately adapted technologies to intensify production of crops, livelihood and household production without extending the areas subject to cultivation. The research objectives of the study were: A. To characterize agro-ecological knowledge of farmers in the Africa RISING project sites A. To identify and map out community resources A. To assess land use and livelihood strategies at the household level A. To characterise existing tree cover and assess the drivers of tree cover change A. To determine temporal variation in availability of provisioning services (income, fuel, livestock feed, crops, labour.