@article{fdi:010092684,
  title = {{M}apping the extent and exploring the drivers of cocoa agroforestry in {N}igeria, insights into trends for climate change adaptation},
  author = {{K}oralewicz, {A}. and {V}lcek, {J}. and {O}liveras {M}enor, {I}mma and {H}irons, {M}. and {A}kinyugha, {A}. and {O}lowoyo, {O}. {S}. and {A}jayi-{E}benezer, {M}. and {O}wen, {O}.},
  editor = {},
  language = {{ENG}},
  abstract = {{C}limate change threatens {W}est {A}frica's cocoa sector due to rising temperatures and unpredictable rainfall, exacerbating concerns for environmental degradation and socio-economic challenges. {I}n {N}igeria, modernization efforts promoting full-sun cocoa have been linked to deforestation and biodiversity loss. {T}he promotion of traditional cocoa agroforestry methods are regaining interest as an approach to climate adaptation and forest restoration. {T}his case study on {E}kiti {S}tate, {N}igeria, aims to understand the physical extent to which full-sun and agroforestry cocoa practices have been employed, while exploring the complex and interlinked dynamics informing land use decision-making in the area. {R}emote sensing leveraging tasseled cap indices for {S}entinel 2 data were used to delineate cocoa agroforestry from full-sun systems. {I}nterviews with policymakers and local cocoa producers across 15 out of 16 local government areas were analyzed through thematic analysis and descriptive statistics. {A}groforestry constituted 18% of {E}kiti land while full-sun cocoa covered 13%. {T}hus, 57% of cocoa cover in {E}kiti {S}tate was agroforestry. {T}he classification had overall spatial differentiation accuracy of 73.1% with a kappa statistic of 68% indicating substantial agreement strength between the classification and the collected validation data. {I}nterviews were similarly aligned, with 74% of respondents using agroforestry or mixed methods. {T}he continued use, despite government promotion of full-sun methods, suggests limited policy uptake and the enduring value of agroforestry for farmers. {T}his research can contribute to improved monitoring of cocoa-driven tree loss and provide important context for policy and program design to enhance climate change adaptation in similar cocoa producing regions.},
  keywords = {{C}ocoa agroforestry ; {C}limate change ; {R}emote sensing ; {L}and classification ; {L}and management ; {P}olicy ; {NIGERIA}},
  booktitle = {},
  journal = {{A}groforestry {S}ystems},
  volume = {99},
  numero = {2},
  pages = {38 [20 p.]},
  ISSN = {0167-4366},
  year = {2025},
  DOI = {10.1007/s10457-024-01126-z},
  URL = {https://www.documentation.ird.fr/hor/fdi:010092684},
}