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<p>Current policy guidelines recommend 16 to 18 trees/ha to achieve an optimal canopy cover in cocoa agroforestry systems, without considering species-specific differences in canopy architecture, thus limiting the ability to optimise shade management and undermining efforts to scale sustainable cocoa agroforestry. This study aims to develop an optimisation model that determines the number of emergent tree species needed to achieve optimum canopy cover. The study was conducted in the Juaboso District, Ghana. First, 30 × 30&#xa0;m plots were established across different cocoa shade systems. Shade trees in the plot were identified to the species level, and their projected crown diameters (CD) were measured. The mean crown area (MCA) was estimated for each species, along with their percentage contribution to canopy cover per hectare. Next, an integer linear programming model was developed to predict the number of shade trees based on farmer preferences and land size. Finally, a One-at-a-Time sensitivity analysis was used to assess the robustness of the model given a ± 10% bias in measured MCA. Results show that <i>P. angolensis</i> contributes 1.57% to canopy cover and requires 19–25 trees to achieve optimum cover. <i>Ceiba pentandra</i> contributes 1.35% and requires only 22–30 trees to achieve optimum canopy cover. <i>Terminalia superba,</i> the most dominant shade tree species, will need 51–68 trees per hectare to achieve optimum canopy cover. Simulations with seven cocoa farmers demonstrated the model’s ability to tailor shade tree recommendations, often deviating significantly from the generic guideline. The sensitivity analysis reveals that a 10% error in field estimates of MCA does not affect the practicality of the model’s recommendation, with a proportional difference of 11.1% over-recommendation and 9.1% under-recommendation across all species, regardless of their crown size. This study provides additional evidence for the need to revise blanket recommendations to a more nuanced approach that considers the species-specific contributions to shade and farmer preferences.</p>

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Modelling the number of shade tree species needed to reach the optimal canopy target in cocoa agroforestry systems

  • 期刊论文

  • 发表日期：

    2025年12月26日

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  • George Ashiagbor,
  • Isaac Stanisluv Essah,
  • Prince Paa Kwesi Baiden,
  • Abigail A. Adjetey Bisa,
  • Ophelia Ahorlu,
  • Gideon Enyinful-Andoh,
  • Winston Adams Asante,
  • Edward Yeboah,
  • James Mutegi,
  • Esther Mugi-Ngenga,
  • Kokou Adambounou Amouzou,
  • Thomas Oberthür

摘要

Current policy guidelines recommend 16 to 18 trees/ha to achieve an optimal canopy cover in cocoa agroforestry systems, without considering species-specific differences in canopy architecture, thus limiting the ability to optimise shade management and undermining efforts to scale sustainable cocoa agroforestry. This study aims to develop an optimisation model that determines the number of emergent tree species needed to achieve optimum canopy cover. The study was conducted in the Juaboso District, Ghana. First, 30 × 30 m plots were established across different cocoa shade systems. Shade trees in the plot were identified to the species level, and their projected crown diameters (CD) were measured. The mean crown area (MCA) was estimated for each species, along with their percentage contribution to canopy cover per hectare. Next, an integer linear programming model was developed to predict the number of shade trees based on farmer preferences and land size. Finally, a One-at-a-Time sensitivity analysis was used to assess the robustness of the model given a ± 10% bias in measured MCA. Results show that P. angolensis contributes 1.57% to canopy cover and requires 19–25 trees to achieve optimum cover. Ceiba pentandra contributes 1.35% and requires only 22–30 trees to achieve optimum canopy cover. Terminalia superba, the most dominant shade tree species, will need 51–68 trees per hectare to achieve optimum canopy cover. Simulations with seven cocoa farmers demonstrated the model’s ability to tailor shade tree recommendations, often deviating significantly from the generic guideline. The sensitivity analysis reveals that a 10% error in field estimates of MCA does not affect the practicality of the model’s recommendation, with a proportional difference of 11.1% over-recommendation and 9.1% under-recommendation across all species, regardless of their crown size. This study provides additional evidence for the need to revise blanket recommendations to a more nuanced approach that considers the species-specific contributions to shade and farmer preferences.