DOI: 10.5061/dryad.qfttdz0sm
title: Tree carbon fluxes and stocks in West African cocoa plantations

description: The study was conducted at 15 sites across Côte d’Ivoire, covering a
 South-North climate and vegetation gradient from evergreen to
 semi-deciduous forests. These sites were selected to represent varying
 cocoa field characteristics, including structural complexity (ranging from
 monocultures to agroforests), cocoa field age (young to mature), and cocoa
 tree productivity (low to high). Each site had 10 cocoa plots, ranging
 from 0.3 to 5 hectares. The carbon stocks of all trees, including remnant,
 spontaneous, and planted trees, have been estimated using the BIOMASS R
 package. This tool provides a robust and widely accepted methodology for
 calculating tree biomass and carbon stocks, ensuring accurate and reliable
 estimates for this dataset.
description: <strong>Study Sites</strong> Study
 plots have been selected from 15 locations throughout the cocoa production
 area (the forest zone) of Côte d’Ivoire (Fig. 1). These sites are situated
 along a South-North climate gradient, with mean annual temperatures
 ranging from 22.6°C to 26.2°C and annual rainfall varying between 1,900 mm
 and 1,100 mm. This climate gradient corresponds to a South-North
 vegetation gradient, transitioning from evergreen forests to
 semi-deciduous forests. To capture the diversity of cocoa fields, we
 identified 10 cocoa fields at each site, focusing on three key criteria:
 (i) structural complexity, ranging from nearly full-sun cocoa monocultures
 to complex cocoa agroforests; (ii) age of the cocoa fields, encompassing
 both young (&lt; 20 years) and mature (&gt; 20 years) plots; and
 (iii) cocoa tree yield, varying from low productivity (&lt; 300 kg) to
 high productivity (&gt; 300 kg). The study plots vary in size from 0.3
 to 5 hectares and serve as the sampling units, corresponding to the
 management units of the farmers. <strong>Data
 Collection</strong> All cocoa fields were mapped
 using GPS technology for precise delineation. Each companion tree with a
 minimum diameter at breast height (dbh) of 10 cm was identified to the
 species level. The dbh and the height of each tree was recorded. The
 origin of each tree—classified as planted, remnant, or spontaneous— and
 the age of each planted and spontaneous tree was recorded based on the
 farmer's declaration. Four socio-environmental factors of interest
 were identified for this study: Two social
 factors related to the cocoa farmer: botanical knowledge and land
 ownership status of the cocoa field, obtained through interviews with the
 farmers. Two field-related factors: cocoa tree
 density and previous land use. Cocoa tree density was estimated by
 counting the number of cocoa trees in a 1000 m² area within each cocoa
 field, and previous land use was obtained through interviews with the
 farmers. The aboveground biomass of each
 individual tree was estimated and then converted to Carbon, using the
 computeAGB() function from the BIOMASS package in the R software. Carbon
 Stocks per plot and per cohort was calculated by adding the stock of each
 tree.
description: # Tree carbon fluxes and stocks in West African cocoa plantations
 [https://doi.org/10.5061/dryad.qfttdz0sm](https://doi.org/10.5061/dryad.qfttdz0sm) ## Description of the data and file structure * Two Response Variables were calculated: Carbon Stocks per plot, Carbon Stocks per tree * Four Explanatory Variables were gathered through interviews and included characteristics related to the farmers (e.g., land ownership, botanical knowledge) and cocoa fields (previous land use, Cocoa plant density). ### Files and variables #### File: bd\_plot.csv **Description:** Geographical coordinates of the sampled plots ##### Variables * plot_ID: Unique identifier of the plot * lat: Latitude * lon: Longitude #### File: table\_stock.csv **Description:** Carbon stocks per cohort per plot ##### Variables * plot_ID: Unique identifier of the plot * origin: 1 planted, 2 spontaneous, 3 remnant * c_ha: Carbon stock per hectare (Mg.ha-1) * owner: ownership status of the cocoa farmer (1 owner, 2 not owner) * know_prod: Level of botanical knowledge of the cocoa farmer (no unit) * prev_landscap: Previous land-use (0 not forest, 1 forest) * dens_cocoa_ha: Cocoa plant density per hectare (stem.ha-1) #### File: bd\_taxon.csv **Description:** Botanical description of the sampled species ##### Variables * taxon_ID: Unique taxon identifier * genus: Botanical genus * species: Botanical species * family: Botanical family #### File: table\_flux.csv **Description:** Carbon stocks per individual tree ##### Variables * plot_ID: Unique identifier of the plot * origin: 1 planted, 2 spontaneous, 3 remnant * age: tree age (year) * taxon: Unique taxon identifier * c: Carbon stock per individual tree (Mg.ha-1) * owner: ownership status of the cocoa farmer (1 owner, 2 not owner) * know_prod: Level of botanical knowledge of the cocoa farmer (no unit) * prev_landscap: Previous land-use (0 not forest, 1 forest) * dens_cocoa_ha: Cocoa plant density per hectare (stem.ha-1) ## Code/software To view the data files, open it in R. Carbon stocks have been estimated using the R package BIOMASS version 2.1.11