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Replication Data for: Opportunities for sustainable intensification of coffee agro-ecosystems along an altitudinal gradient on Mt. Elgon, Uganda

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Replication Data for: Opportunities for sustainable intensification of coffee agro-ecosystems along an altitudinal gradient on Mt. Elgon, Uganda
 
Identifier https://doi.org/10.7910/DVN/VUAID3
 
Creator Rahn, Eric
Liebig, Theresa
Ghazoul, Jaboury
Van Asten, Piet
Läderach, Peter
Vaast, Philippe
Sarmiento, Alejandra
Garcia, Claude
Jassogne, Laurence
 
Publisher Harvard Dataverse
 
Description During the months of April and May 2014, vegetation structure was measured on the 150 selected plots. The altitude and plot boundary coordinates were recorded using Garmin eTrex GPS. Plot size was calculated based on plot boundary coordinates in R Statistics (R Core Team, 2014) using the sp package (Pebesma and Bivand 2005). The number of coffee trees, banana mats and stems, and shade trees were counted on the entire plot and densities (in number per ha) were calculated. Shade tree species were identified and the number of species per plot recorded. The canopy closure as an indicator for average plot- level shade was estimated using a Forestry Suppliers spherical crown densiometer (convex model A) according to Lemmon (1957) at four positions within the plot. Coffee yields were obtained through farmer recall per plot of the various harvests of the year and provided as coffee cherries or parchment, which was then converted into green been. The cumulative annual production was divided by the plot size and number of coffee trees to obtain green bean yield per hectare and green bean yield per coffee tree, respectively. The recall data was obtained using triangulation questions by an experienced local team, which proved to be successful in previous studies (Van Asten et al., 2011a; Wang et al., 2015). This allows a wide coverage of yield data. Data on age of the coffee trees, coffee management, and livelihood characteristics were obtained through structured farmer interviews during farm visits.
 
Subject Agricultural Sciences
Earth and Environmental Sciences
Coffee systems
Vegetation structure
Household characteristics
Smallholders
Households
Coffea
Africa
Decision and Policy Analysis - DAPA
 
Language English
 
Date 2018-05
 
Contributor Bejarano Lozano, Yesica
 
Type Survey Data
Experimental Data
Phenomic Data
Socio-economic Data
Coffee plot vegetation structure and soil measurements