Drivers of tree presence and densities: the case of cocoa agroforestry systems in the Soubre region of Republic of Côte d’Ivoire

Gyau, Amos; Smoot, Kaitlyn; Diby, Lucien; Kouamé, Christophe

doi:10.1007/s10457-014-9750-1

Cited by 22 publications

(11 citation statements)

References 19 publications

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“…In the Soubre region, located in the Republic of Côte d'Ivore, it was verified the preference of small farmers less financially benefited and those isolated from the larger centers for the introduction of tree species whose products had high demand in the local community (Gyau et al, 2015). The possibility of producing crops with high value in large markets was not an important factor in the choice of species composition of AFSs by these farmers.…”

Section: Resultsmentioning

confidence: 99%

Carbon stock in the development of different designs of biodiverse agroforestry systems

Fernandes

Matsumoto

Fernandes³

2018

Rev. bras. eng. agríc. ambient.

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The objective of this study was to estimate the carbon stock in the different designs of biodiverse agroforestry systems (AFSs) in the region of the Environmental Protection Area (EPA) of Pratigi, Bahia, Brazil. Phytosociology aspects related to the potentiality of carbon stock of 10 farms were evaluated using plots of 10 x 50 m allocated in each AFS, inventorying 928 individuals of 17 families and 37 species, established in 2013. The biomass above and below the soil of the arboreal individuals were estimated by indirect method, using specific allometric equations for each species or group of species, with diameter above 1 cm. Carbon stock (CS) was estimated from the biomass. Cacao (Theobroma cacao) and rubber tree (Hevea brasiliensis) were the dominant species in all of the designs, which also contained fruit trees, and native and exotic shade trees. There was variation of the estimate of carbon stock (8.01-1.42 Mg ha-1) between the types of AFSs. The designs with a larger relative density of fruit and shade trees led to larger carbon storage, influenced by the wealth and diversity of species in the initial phase of establishment of biodiverse AFSs.

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Section: Resultsmentioning

confidence: 99%

Carbon stock in the development of different designs of biodiverse agroforestry systems

Fernandes

Matsumoto

Fernandes³

2018

Rev. bras. eng. agríc. ambient.

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“…Lam) in Cameroon [19]. In contrast, trees are seldom found on cocoa farms in Côte d'Ivoire and Ghana [20,21], where less is known about the farmers' interest in trees on cocoa farms. Thus, it is encouraging that in Côte d'Ivoire, the Coffee-Cocoa Board has recently indicated that, using a participatory approach [22], farmers' opinions and objectives should now be taken into account when selecting trees for planting on cocoa farms [23].…”

Section: Introductionmentioning

confidence: 99%

“…However, the relative contribution of these factors to the decision to adopt may vary with practice and context [25,[27][28][29][30][31][32]. For example, social network effects, ethnic group, and geographic zone were found to determine the presence of trees and their density on cocoa farms in the Soubré region in Côte d'Ivoire [20], as did the severity of cocoa diseases and the existence of programs for extension and certification of cocoa, However, in the humid forest zones of Cameroon and Nigeria, strategies for growing fruit trees were identified as suitable for market access, land-use, and access to forest resources [33]. In the Eastern region of Ghana, farmer interviews found that Spathodea campanulate P. Beauv.…”

Section: Introductionmentioning

confidence: 99%

Rebuilding Tree Cover in Deforested Cocoa Landscapes in Côte d’Ivoire: Factors Affecting the Choice of Species Planted

Atangana¹,

Gnangoh²,

Yao³

et al. 2021

Forests

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Intensive cocoa production in Côte d’Ivoire, the world’s leading cocoa producer, has grown at the expense of forest cover. To reverse this trend, the country has adopted a “zero deforestation” agricultural policy and committed to rehabilitating its forest cover through the planting of high-value tree species in cocoa landscapes using a participatory approach. However, little is known regarding the factors influencing farmers’ introduction of high-value tree species to cocoa landscapes. We tested the hypothesis that ten previously reported factors to influence agroforestry system adoption to predict the number and choice of tree species that farmers introduce to cocoa farms. We interviewed 683 households in the cocoa-producing zone of Côte d’Ivoire and counted tree species on their cocoa farms. On average, two tree species were recorded per surveyed farm. Generalized Poisson regression models revealed that, in the cocoa production area, experience in tree planting and expected benefits, including income and food, influence tree species introduction through planting or “retention” when clearing land for cocoa establishment. The age of the farmer also influenced (p = 0.017) farmers’ tree species planting on cocoa farms. Fewer tree species were introduced into current intensive cocoa-production areas than in “old cocoa-loops” and forested areas. The number of tree species introduced to cocoa farms increased with expected benefits and experience in tree planting. The number of planted tree species also increased with farmers’ age. Tree species were mostly selected for the provision of shade to cocoa, production of useful tree products (38%), and income from the sale of these products (7%). Fruit tree species were the most planted, while timber tree species were mostly spared when clearing land for cocoa production.

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“…Regrettably, the expansion of cocoa production lands significantly contributes to the loss of forest cover [11,12]. Such expansions are somewhat specific to countries and production landscapes [13][14][15][16]; therefore, some are more destructive to forests than others. On a global scale, cocoa production was responsible for 57% of the global agricultural land expansion rate (132,000 ha year −1 ) in the period 2000-2013 [2].…”

Section: Introductionmentioning

confidence: 99%

Delineation of Cocoa Agroforests Using Multiseason Sentinel-1 SAR Images: A Low Grey Level Range Reduces Uncertainties in GLCM Texture-Based Mapping.

Numbisi

Coillie

Wulf

2019

IJGI

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Delineating the cropping area of cocoa agroforests is a major challenge in quantifying the contribution of land use expansion to tropical deforestation. Discriminating cocoa agroforests from tropical transition forests using multispectral optical images is difficult due to the similarity of the spectral characteristics of their canopies. Moreover, the frequent cloud cover in the tropics greatly impedes optical sensors. This study evaluated the potential of multiseason Sentinel-1 C-band synthetic aperture radar (SAR) imagery to discriminate cocoa agroforests from transition forests in a heterogeneous landscape in central Cameroon. We used an ensemble classifier, Random Forest (RF), to average the SAR image texture features of a grey level co-occurrence matrix (GLCM) across seasons. We then compared the classification performance with results from RapidEye optical data. Moreover, we assessed the performance of GLCM texture feature extraction at four different grey levels of quantization: 32 bits, 8 bits, 6 bits, and 4 bits. The classification’s overall accuracy (OA) from texture-based maps outperformed that from an optical image. The highest OA (88.8%) was recorded at the 6 bits grey level. This quantization level, in comparison to the initial 32 bits in the SAR images, reduced the class prediction error by 2.9%. The texture-based classification achieved an acceptable accuracy and revealed that cocoa agroforests have considerably fragmented the remnant transition forest patches. The Shannon entropy (H) or uncertainty provided a reliable validation of the class predictions and enabled inferences about discriminating inherently heterogeneous vegetation categories.

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Drivers of tree presence and densities: the case of cocoa agroforestry systems in the Soubre region of Republic of Côte d’Ivoire

Cited by 22 publications

References 19 publications

Carbon stock in the development of different designs of biodiverse agroforestry systems

Carbon stock in the development of different designs of biodiverse agroforestry systems

Rebuilding Tree Cover in Deforested Cocoa Landscapes in Côte d’Ivoire: Factors Affecting the Choice of Species Planted

Delineation of Cocoa Agroforests Using Multiseason Sentinel-1 SAR Images: A Low Grey Level Range Reduces Uncertainties in GLCM Texture-Based Mapping.

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