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Predicting the future climatic suitability for cocoa farming of the world's leading producer countries, Ghana and Côte d'Ivoire

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Abstract

Ghana and Côte d’Ivoire are the world’s leading cocoa (Thebroma cacao) producing countries; together they produce 53 % of the world’s cocoa. Cocoa contributes 7.5 % of the Gross Domestic Product (GDP) of Côte d’Ivoire and 3.4 % of that of Ghana and is an important cash crop for the rural population in the forest zones of these countries. If progressive climate change affected the climatic suitability for cocoa in West Africa, this would have implications for global cocoa output as well as the national economies and farmer livelihoods, with potential repercussions for forests and natural habitat as cocoa growing regions expand, shrink or shift. The objective of this paper is to present future climate scenarios for the main cocoa growing regions of Ghana and Côte d’Ivoire and to predict their impact on the relative suitability of these regions for growing cocoa. These analyses are intended to support the respective countries and supply chain actors in developing strategies for reducing the vulnerability of the cocoa sector to climate change. Based on the current distribution of cocoa growing areas and climate change predictions from 19 Global Circulation Models, we predict changes in relative climatic suitability for cocoa for 2050 using an adapted MAXENT model. According to the model, some current cocoa producing areas will become unsuitable (Lagunes and Sud-Comoe in Côte d’Ivoire) requiring crop change, while other areas will require adaptations in agronomic management, and in yet others the climatic suitability for growing cocoa will increase (Kwahu Plateu in Ghana and southwestern Côte d’Ivoire). We recommend the development of site-specific strategies to reduce the vulnerability of cocoa farmers and the sector to future climate change.

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... Fluctuations in climatic variables such as rainfall and temperature will affect coffee and cocoa plant production, biological diversity, and the geographic distribution of species-friendly habitats (de Sousa et al. 2019;Farrell et al. 2018;Läderach et al. 2013;Schroth et al. 2016;Wang et al. 2016). Changes in the average weather patterns may refer to climate change; the change might be quantitative or qualitative to the system. ...
... The remaining areas most likely to retain high suitability were found in the very high mountainous part in the proximity of forest reserves and riparian forests where precipitation is most likely to remain sufficiently high (Fig. 7). Similar results have been found by Baca et al. (2014) et Läderach et al. (2013. Climate change is thus likely to cause additional challenges that are already being faced the the coffee and cocoa sector in Togo. ...
... These results underline the urgency of planning the coffee and cocoa sector production and considering the potential impacts of climate variability in the adaptation strategies. Our result is in line with Läderach et al. (2013) classification, who classify globally the cocoa cultivation area in Togo under Zone 2 of cocoa suitability. According to him, this zone is characterized by medium suitability that can sustain over the coming decades despite increasing environmental pressures with adaptive strategies. ...
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Changes in climate patterns are the main challenges being faced by the coffee and cocoa production systems, one of the key sources of livelihood for farmers in Togo’s humid dense forests zone, also known as “Togo ecological zone IV”. The objective of this study was to analyze the climatic vulnerability of coffee-cocoa agroforestry systems (CCAFS) in Togo ecological zone IV both ongoing (last 40 years 1980–2019) and the incoming decades (by 2050) considering climate forecast under AR6 socioeconomic pathways. The Standardized Precipitation Index (SPI) approach with the Mann–Kendall & Sen’s tests and the MaxEnt tool were used to assess the drought condition and the potential impacts on CCAFS suitability in the study area. The results show instability in rainfall series with a non-significant progressive trend in the area during the past four decades, while a significant increase in temperature was observed. Beyond 2050, suitable areas for coffee and cocoa species will drift to the pic mountainous part. Thus, respectively 51.91 and 54.50% of currently suitable areas for the two species, will be lost under the future climate scenario SSP3-7.0 and SSP5-8.5. These losses are mainly due to the reduction of precipitation of the driest month (Bio14), precipitation of the driest quarter (Bio17), and precipitation of the coldest quarter (Bio19) of the year. Drought is therefore revealed as the main limiting climatic factor for coffee and cocoa in Togo. The increasing drought intensity in the future is a source of high vulnerability of CCAFS as well as the local farmers’ livelihoods.
... While these countries lead in total cocoa production, their yield per hectare in smallholder farmstypically 300-600 kg/hais amongst the lowest in the world Wessel and Quist-Wessel, 2015). In addition, climate suitability is expected to decrease in response to climate change with potential negative effects on yields (Anim- Kwapong and Frimpong, 2004;Gateau-Rey et al., 2018;Läderach et al., 2013;Schroth et al., 2016). Over the past three decades, increases in production have been driven by a sharp increase in plantation area with only marginal increases in yield (van Vliet and Giller, 2017;Wessel and Quist-Wessel, 2015). ...
... Another challenge is that cocoa is also replacing food croplands, threatening food security in the cocoa growing belt, as exemplified for Ghana (Ajagun et al., 2021). In the coming decades, increased demand for cocoa (growing at approximately 3% per year (Beg et al., 2017)), and the projected potential loss of about 50% of the current cocoa growing area due to decreasing climatic suitability (Läderach et al., 2013;Schroth et al., 2016) could drive producers to new areas, resulting in additional deforestation (Ruf et al., 2015) and food insecurity (Ajagun et al., 2021). To avoid further deforestation and expansion of cocoa fields into other sensitive areas, there is a need to evaluate opportunities to increase yields per unit area on existing lands to meet the growing demand for cocoa. ...
... Areas with large absolute yield gaps such as the wetter areas indicate potential for larger yield gains, whilst farmers in areas with low absolute yield gaps maybe more vulnerable due to climate change. Progressive climate change may alter simulated water-limited yields (upper limit of yields in rain-fed system) through direct changes in temperature and water availability (Bunn et al., 2019;Läderach et al., 2013;Schroth et al., 2016). Thus, it is important for climate change impact studies to carefully evaluate projected changes in climate and potential responses of cocoa growth and yield. ...
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CONTEXT Global cocoa production is largely concentrated in West Africa where over 70% of cocoa is produced. Here, cocoa farming is largely a rain-fed, low-input system with low average yields, which are expected to decline with climate change. With increasing demand, there is a need to evaluate opportunities to increase production whilst avoiding deforestation and expansion to croplands. Thus, it is important to know how much additional cocoa can be produced on existing farmland, and what factors determine this potential for increased yield. OBJECTIVE The objective was to quantify the cocoa yield gap in Ghana and identify the factors that can contribute to narrowing the gap. METHODS We calculated the cocoa yield gap as the difference between potential yield (i. water-limited potential(Yw) quantified using a crop model, ii. attainable yield in high-input systems(YE), iii. attainable yield in low-input systems(YF)) and actual farmer yield. Both absolute and relative yield gaps were calculated. We then related each yield gap (absolute & relative) as a function of environment and management variables using mixed-effects models. RESULTS AND CONCLUSIONS There were considerable yield gaps on all cocoa farms. Maximum water-limited yield gaps (YGW) were very large with a mean absolute gap of 4577 kg/ha representing 86% of Yw. Attainable yield gap in high-input (YGE) was lower with mean absolute gap of 1930 kg/ha representing 73% of YE. The yield gap in low-input (YGF) was even lower with mean absolute gap of 469 kg/ha representing 42% of YF. Mixed-effects models showed that, absolute YGW were larger at sites with higher precipitation in the minor wet and minimum temperature in the minor dry season explaining 22% of the variability in YGW. These same factors and cocoa planting density explained 28% of variability in absolute YGE. Regardless of climate, absolute YGF and relative YGW, YGE and YGF were reduced by increasing cocoa planting density and application of fungicide against black pod. The models explained 25% of the variability in absolute YGF, and 33%, 33% and 25% in relative YGW, YGE and YGF respectively. In conclusion, climate determined absolute YGW in Ghana whilst absolute YGE were determined by both climate and management. In contrast, absolute YGF and relative YGW, YGE and YGF can be reduced by agronomic management practices. SIGNIFICANCE Our study is one of the first to quantify cocoa yield gaps in West Africa and shows that these can be closed by improved agronomic practices.
... Global climate change will remain a major threat for agriculture for decades to come (Nelson et al. 2014). Spatial and temporal changes in temperature and precipitation regimes and the intensification of extreme events have increasingly impacted main global commodities, in many cases hampering production by loss of climatic suitability (Lobell et al. 2008;Läderach et al. 2013;Schroth et al. 2016;Caetano et al. 2018). To increase resilience to such a pressing issue, the agricultural sector should take action to mitigate and adapt to climate change. ...
... Ecological niche models (ENMs) have been commonly used to assess potential impacts of climate change on crops (Läderach et al. 2013;Caetano et al. 2018;Gomes et al. 2020). ENMs are statistical methods that associate the localities where an organism occurs to a set of environmental variables, allowing to identify where, in the environmental space (values of environmental variables), an organism has conditions that are suitable for its persistence (Elith et al. 2011;Peterson et al. 2011). ...
... Potential impacts of climate change on southern Bahia's cacao plantations have not been assessed yet. Similar to what is expected to happen in West Africa over the next decades (Läderach et al. 2013;Schroth et al. 2016), climate change could geographically shift or shrink suitable areas for cacao in southern Bahia. The risks of losing suitable areas due to increasing temperature and decreasing precipitation are high and could be exacerbated by inadequate management practices. ...
Article
In southern Bahia, Brazil’s traditional cacao region, cacao is mostly grown under the shade of thinned Atlantic Forest (known as cabruca). These agroforestry systems are gradually being replaced by unshaded cacao monocultures that might be more vulnerable to changes in climate, however the impacts of climate change have not been evaluated yet. We assessed the impact of climate change on the climatic suitability of cacao plantations in southern Bahia and evaluated to what extent the cabrucas reduce the vulnerability of cacao as compared to unshaded plantations. We measured the maximum temperature in a gradient of canopy cover during the warmest month of the year and projected ecological niche models (MaxEnt) on climate projections for 2050 simulating the microclimate of three production systems: cabrucas, intermediate shading, and unshaded plantations. We found that canopy cover drastically reduces daily maximum temperature, so that understory temperature in cabrucas can be up to 6.0 ºC lower than in unshaded plantations. We show for the first time that all projected environmental changes negatively affect cacao in southern Bahia, diminishing its climatic suitability and reducing overall suitable areas across the region. More importantly, this study is the first one to show that cabrucas can reduce the negative impacts of climate change for cacao, especially where temperature extremes approach or exceed crop tolerance limits. We conclude that maximizing short-term profits by implementing unshaded monocultures will likely lead to production losses in the long term. Cabrucas have a central role in reducing the vulnerability of cacao to climate change and since these traditional agroforestry systems cannot be quickly restored, their conservation should be an important goal of agricultural policies in the region.
... In this context, we can include cocoa (Theobroma cacao L.), which is considered an essential crop in several tropical countries because of the supported income it provides many small farmers [6]; it is also involved in a global chain of chocolate production. South America represents 12.49% of global cocoa production and its countries receive US$2.4 billion/year [7] through its exportation. ...
... In general, its development occurs in hot and humid climates with a latitudinal range of 20˚N to 20˚S [12]. According to some studies, climate change can affect the cocoa growing zones [6]. In drier conditions, cocoa growth without intercropping may have a lower mortality rate than when planted in conjunction with another plant because it avoids competition for water with other crops [13]. ...
... The higher temperature depicted in the RCP scenarios hurts cocoa yields [50]. According to [6], high temperature can also cause stress indirectly due to the higher evapotranspirative demand of the air. Thus, some studies recommend the implementation of production technologies to stabilize the temperature of the microclimate and reduce the impacts of high rainfall, such as the use of shading plants and canopy manipulation [51]. ...
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Cocoa is a plant with origins in northwestern South America with high relevance in the global economy. Evidence indicates that cocoa is sensitive to a dry climate, under which crop production is reduced. Projections for future climate change scenarios suggest a warmer and drier climate in the Amazon basin. In this paper, we quantify the potential effects in cocoa production due to its edaphoclimatic suitability changes to the Brazilian Amazon biome and account for regional differences in planning occupation territories. We modeled the suitability of cocoa’s geographical distribution using an ensemble of 10 correlative models that were run in the “biomod2” library and projected to two future climate scenarios (RCPs 4.5 and 8.5) by 2050. Combining information on climate and soil suitability and installed infrastructure in the macro-regions of the Brazilian Amazon. We defined a zoning system to indicate how cocoa production may respond to climate change according to the current and future suitability model. Our results suggest that a reduction in precipitation and an increase in temperature may promote a reduction in the suitability of cocoa production in the Brazilian Amazon biome. In addition of the areas suitable for cocoa plantation, we found a 37.05% and 73.15% decrease in the areas suitable for intensification and expansion zones under RCP 4.5 and 8.5, respectively, compared with the current scenario. We conclude that there may be a need to expand land to cocoa production in the future, or else it will be necessary to plant a cocoa variety resistant to new climatic conditions. Besides, we recommend procedures to combat illegal deforestation to prevent the most critical climate change scenarios from occurring.
... An analysis of the impact of climate change on cocoa production suggests a relatively drastic decrease of climatic suitability (rainfall and temperatures) in current growing regions by 2050 (Asante and Amuakwa-Mensah, 2015;Läderach et al., 2013;USAID, 2011). The consequences are increase evapotranspiration, high seedling mortality and decline in cocoa yield (Kaba et al., 2021;USAID, 2011). ...
... Previous studies have focused more on clonal propagation, shading effect, the use of agroforestry systems and improving nutrients efficiency to enhance cocoa seedling survival (Famuwagun et al., 2018;Henao-Ramírez et al., 2021;Kaba et al., 2020;Lahive et al., 2019;Osorio et al., 2022). Unfortunately, cocoa seedling mortality on farmers field is still high and recent evidence (Baligar et al., 2017;Djan et al., 2018;Kaba et al., 2021;Läderach et al., 2013;USAID, 2011) show that higher atmospheric temperatures associated with climate change will lead to longer, more severe drought events and this will continue to have a negative impact on cocoa seedling establishment and survival. For instance, Padi et al. (2013) reported that the CRIG effort targeted at minimizing the effect of drought have mostly concentrated on choosing cocoa hybrids with high percentage survival under low shade conditions and on soil with low organic matter content. ...
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Cocoa (Theobroma cacao L) is an understorey plant that is highly sensitive to drought, especially at the seedling stage. In Ghana, only 20% cocoa seedlings survive the dry spells within 24 months after transplanting. Potassium (K) is known to enhance the growth of plants root to increase water uptake under drought conditions. This study assessed the effect of different levels of K fertilizer in enhancing the drought recovery and survival of four cocoa genotypes grown in Ghana. A 3 × 3 factorial experiment in Randomized Complete Block Design was carried out at the FRNR farm, Kwame Nkrumah University of Science and Technology, Ghana in 2019/2020 and 2020/2021 cropping seasons. The treatments consisted of 0 g, 4 g and 6 g plant −1 of muriate of potash (60% K 2 O) and three cocoa varieties: Amaz15-15XEqx78 (V1); CRG8914XPA150 (V2) and PA7/808XPound10 (V3). The result showed that cocoa varieties applied with 4 g or 6 gK plant −1 produced higher (p < .05) belowground and aboveground biomass than the control. The K treated seedlings had about 77% survival rate than the control (43%) seedlings. Among the varieties, V2 had better drought recovery and survival rate (81%), followed by V3 (78%) and V1 (71%). In addition to the morphological characteristics, K enhanced the nitrogen content in cocoa seedlings during drought recovery and this correlated positively (R = 0.863) with survival rate. In conclusion, when farmers grow V2 and apply 4 gK plant −1 during drought, over 80% of the seedling will recovery and survive. This has implications for K fertility management, yield and the livelihood of smallholder (70%) cocoa farmers.
... It is an important aid in understanding the influence of climate change on species distributions [30][31][32]. MaxEnt was used to predict the change in climate of some of the plantation growing areas like areas growing cocoa in African countries [33,34], coffee in Zimbabwe [35], and other agricultural crops [36][37][38]. Despite the important role of coconut in safeguarding the livelihood of millions of people in the south Indian region, the literature shows that there has been little research into the future climate suitability of the region for coconut cultivation. ...
... As coconut is grown across different agro-ecological zones of India, evaluating the impacts of climate change scenarios on the potential cultivable area will be helpful in understanding the relationships between coconut niches and the corresponding environment, identifying priority cultivation areas and planning adaptation strategies [55][56][57]. Species distribution models like MaxEnt are extensively used to predict the change in climate of some of the plantation growing areas like areas growing cocoa in African countries [33,34], coffee in Zimbabwe [35], and other agricultural crops [36][37][38]. In our study, for model calibration, we could generate 2480 candidate models involving environmental predictors and regularization multiplier and feature classes using the kuenm-R package and select the best candidate model (M_0.1_F_qp) ...
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Climate change and climate variability are projected to alter the geographic suitability of lands for crop cultivation. Early awareness of the future climate of the current cultivation areas for a perennial tree crop like coconut is needed for its adaptation and sustainable cultivation in vulnerable areas. We analyzed coconut’s vulnerability to climate change in India, based on climate projections for the 2050s and the 2070s under two Representative Concentration Pathways (RCPs): 4.5 and 8.5. Based on the current cultivation regions and climate change predictions from seven ensembles of Global Circulation Models, we predict changes in relative climatic suitability for coconut cultivation using the MaxEnt model. Bioclimatic variables Bio 4 (temperature seasonality, 34.4%) and Bio 7 (temperature annual range, 28.7%) together contribute 63.1%, which along with Bio 15 (precipitation seasonality, 8.6%) determined 71.7% of the climate suitability for coconuts in India. The model projected that some current coconut cultivation producing areas will become unsuitable (plains of South interior Karnataka and Tamil Nadu) requiring crop change, while other areas will require adaptations in genotypic or agronomic management (east coast and the south interior plains), and yet in others, the climatic suitability for growing coconut will increase (west coast). The findings suggest the need for adaptation strategies so as to ensure sustainable cultivation of coconut at least in presently cultivated areas.
... Thus, rainfall distribution throughout the year is also essential since the drought has a negative effect. Three consecutive months with less than 100 mm of total precipitation result in lower cocoa yields and lower long-term vitality of cocoa trees (Läderach et al., 2013). During the present investigation, a total of 611 mm was recorded between December 2013 and July 2015, quantity that is below the crop water requirements. ...
... According to García and Moreno (2016), cocoa is considered a hydroperiod crop, so precipitation plays an essential role in the grain yield potential due to water impacts growth, leaf emission, photosynthetic activity, and stomatal behavior. While cocoa has been described as particularly sensitive to water deficit, mature trees appear to be less sensitive than seedlings in the field, probably due to the greater availability of resources in the older trees (Läderach et al., 2013). A research carried out by Gateau et al. (2018) demonstrated that water stress in cocoa cultivation could generate up to 15 % mortality in trees and severely reduce crop yield by up to 89 %. ...
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The expansion and modernization of the cocoa area under new strategies, such as the use of adapted genetic material and the establishment of Agroforestry Systems with cocoa, under criteria of competitiveness and sustainability, require selecting sites with adequate biophysical conditions, which facilitate the optimization of resources for production. In this sense, we conducted a study in the Estación Agraria Cotové, of the Universidad Nacional de Colombia, located in a tropical dry forest life zone (TDF), at 540 meters of elevation, with an average temperature of 27 ºC, average annual precipitation annual of 1,031 mm and relative humidity less than 70 %. The yield components and productive potential of four cocoa clones, ICS 95, TSH565, CCN 51, and ICS 60, were evaluated. The cocoa clones were planted under two controlled sunlight habitats, generated by the timber species Gmelina arborea Roxb. (single-row and double-row arrangement), and two different canopy management of the cocoa plants (plagiotropic and orthotropic growth stimulus). The clones TSH 565 and CCN 51 showed the highest yields in the two harvest years. ICS 95 showed the lowest bean index. Regarding the pod index, no differences were observed between the cocoa clones. Clones TSH 565 and CCN 51 stood out as the earliest and most productive clones.
... The variables relate to the biological conditions of living organisms and are often used in ecological niche modeling around the globe (Hijmans et al., 2005). The dataset has been used in related studies (e.g., Läderach et al., 2013;, because of their high resolution and bias-corrected with the required accuracy for model prediction in agriculture. In a recent study over southern Kenya in EA by Wango et al. (2018), results revealed that all these 19 bioclimatic variables accurately depict the local variations in the climate of the study region. ...
... The approach is similar to the regression tree approach because it specializes in predictive accuracy at the cost of biological interpretation (Phillips et al., 2006). Since becoming available in 2004, it has been utilized for modeling species distributions in the EA region (Jassogne et al., 2013;Läderach et al., 2013) and around the globe (e.g., Scheldeman et al., 2007;He et al., 2019). ...
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Maize crop (Zea mays) is one of the staple foods in the East African (EA) region. However, the suitability of its production area is threatened by projected climate change. The Multimodel Ensemble (MME) from eight Coupled Model Intercomparison Project 5 (CMIP5) models was used in this paper to show climate change between the recent past (1970–2000) and the future (2041–2060), i.e., the mid-twenty-first century. The climatic suitability of maize crop production areas is evaluated based on these climate datasets and the current maize crop presence points using Maximum entropy models (MaxEnt). The MME projection showed a slight increase in precipitation under both RCP4.5 and RCP8.5 in certain places and a reduction in most of southern Tanzania. The temperature projection showed that the minimum temperature would increase by 0.3 to 2.95 °C and 0.3 to 3.2 °C under RCP4.5 and 8.5, respectively. Moreover, the maximum temperature would increase by 1.0 to 3.0 °C and 1.2 to 3.6 °C under RCP4.5 and 8.5 respectively. The impacts of these projected changes in climate on maize production areas are the reduction in the suitability of the crop, especially around central and western Tanzania, mid-northern and western Uganda, and parts of western Kenya by 20–40%, and patches of EA will experience a reduction of as high as 40–60%, especially in northern Uganda, and western Kenya. The projected changes in temperature and precipitation present a significant negative change in maize crop suitability. Thus, food security and the efforts towards the elimination of hunger in EA by the mid-twenty-first century will be hampered significantly. We recommend crop diversification to suit the new future environments, modernizing maize farming programs through the adoption of new technologies including irrigation, and climate-smart agricultural practices, etc.
... The optimum altitude for cocoa cultivation is currently 100 -250 meters above sea level. With climate warming, this will increase to 450 -500 meters by 2050 to compensate for the increase in temperature [26]. An increase in temperature should dry out the land more quickly and reduce its fertility. ...
... As opposed to Penman-Monteith, this method requires less data (Allen et al. 1998), and similar results are produced by both methods (Hargreaves & Allen 2003). A monthly difference was calculated between the mean maximum and minimum temperatures in the study area using WorldClim climatic variables to generate the ETP layer (Läderach et al. 2013). ...
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In recent years, palm oil production has grown rapidly as a result of rising demand. Oil palm plantations have been established on thousands of acres to meet this demand. The objective of this study is to assess the suitability of oil palm production as driven by soil, climate, and land use. The land suitability assessment (LSA) method was adopted in this study. We use geospatial techniques of overlay mapping as a suitable land suitability assessment method, in which the evaluation criteria are recorded as superimposed layers. A land suitability map is produced by integrating these layers into a single layer. The method is also applied to delineate available areas for growing oil palm in Peninsular Malaysia. The findings revealed that suitable soil areas for oil palm production are extensively found in the selected regions of Peninsular Malaysia, in states like Selangor and some parts of Kedah, Kelantan, and Terengganu with clay loam and sandy loam soil properties, while in the southern region like Melaka, moderate suitability for oil palm production was found due to the domination of clay soil in the area. Highly suitable areas were estimated (mean annual water deficit <150 mm) to be 3688254.00 ha (29.54%) of the total land area; suitable areas (mean annual water deficit <250 mm) were 6540669.00 ha (52.38%); moderately suitable areas were (mean annual water deficit <400 mm) 2227500.00 ha (17.84%), and unsuitable areas (mean annual water deficit >400mm) for oil palm production as a result of poor water availability was 31104.00ha (0.25%). The Land Use Land Cover Map of Peninsular Malaysia revealed the suitable areas to cover an average of 10885001.46 ha (82.45%), water bodies 1239505.58 ha (9.39%), built-up areas (unsuitable areas) 1051544.34 ha (7.96%), and bare surface areas are also not suitable areas for oil palm production at 26509.73 ha (0.20%). This study recommends that oil palm plantations be expanded into areas with highly suitable soils and climates.
... A favourable climatic and environmental setting maintains the farming and agricultural activities of the local population. This makes Côte d'Ivoire the largest cocoa producer in the world [94][95][96][97] and an active exporter of food-producing crops [98], such as coffee, bananas, pineapples and palm oil [99]. Aside from agriculture, the activities of population include exploration, mining [100][101][102] and limited fishing along the narrow continental shelf of the Atlantic Ocean [103]. ...
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In this paper, we propose an advanced scripting approach using Python and R for satellite image processing and modelling terrain in Côte d’Ivoire, West Africa. Data include Landsat 9 OLI/TIRS C2 L1 and the SRTM digital elevation model (DEM). The EarthPy library of Python and `raster’ and `terra’ packages of R are used as tools for data processing. The methodology includes computing vegetation indices to derive information on vegetation coverage and terrain modelling. Four vegetation indices were computed and visualised using R: the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index 2 (EVI2), Soil-Adjusted Vegetation Index (SAVI) and Atmospherically Resistant Vegetation Index 2 (ARVI2). The SAVI index is demonstrated to be more suitable and better adjusted to the vegetation analysis, which is beneficial for agricultural monitoring in Côte d’Ivoire. The terrain analysis is performed using Python and includes slope, aspect, hillshade and relief modelling with changed parameters for the sun azimuth and angle. The vegetation pattern in Côte d’Ivoire is heterogeneous, which reflects the complexity of the terrain structure. Therefore, the terrain and vegetation data modelling is aimed at the analysis of the relationship between the regional topography and environmental setting in the study area. The upscaled mapping is performed as regional environmental analysis of the Yamoussoukro surroundings and local topographic modelling of the Kossou Lake. The algorithms of the data processing include image resampling, band composition, statistical analysis and map algebra used for calculation of the vegetation indices in Côte d’Ivoire. This study demonstrates the effective application of the advanced programming algorithms in Python and R for satellite image processing.
... Over the past decades, the cocoa subsector of agriculture is observed to be vulnerable to the changing climate. Climate models have predicted spatially differentiated impacts for cocoa in Africa and other developing economies with losses of climatic suitability [2,3]. The models specifically predicted a decrease in climatic suitability for cocoa production in Ghana, Cote d'Ivoire and Liberia with an overall impact on future cocoa supplies [3]. ...
... Over the past decades, the cocoa subsector of agriculture is observed to be vulnerable to the changing climate. Climate models have predicted spatially differentiated impacts for cocoa in Africa and other developing economies with losses of climatic suitability [2,3]. The models specifically predicted a decrease in climatic suitability for cocoa production in Ghana, Cote d'Ivoire and Liberia with an overall impact on future cocoa supplies [3]. ...
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Over the years, cocoa has been the bedrock of the Ghanaian economy and a source of livelihood for most cocoa farming households. Empirical studies have established that cocoa farmers have begun to adopt various agronomic measures for climate change adaptation. However, factors that influence farmers’ decisions to adopt these agronomic practices to enable successful adaptation to climate change are least investigated. The study aims to investigate smallholder cocoa farmers’ decisions to adopt agronomic practices for climate change adaptation in Ghana. The study adopts a mixed method approach to research, and involved 259 cocoa farmers. Using the thematic and multivariate probit regression model to data analysis, the results revealed that farmers’ decisions to adopt soil conservation, pruning/shade management and planting of new crop varieties is determined by a number of mixed factors including; access to agricultural land, access to credit, farmer farm experience and access to extension services. The study recommends the need for the Ministry of Lands and Natural Resources together with the traditional authorities and other relevant land sector agencies to develop and implement context-specific and appropriate land-use policy strategies that support access to sustainable land for adoption of climate smart agricultural practices. Again, the study recommends the need for the Ministry of Food and Agriculture to deploy more extension agents into rural cocoa farming communities to take farmers through more pragmatic agronomic practices for climate change adaptation and improved returns in investment in cocoa farming.
... The global average surface temperature increased by +1.09°C over the last century, with the hottest temperatures ever recorded in the last three decades (IPCC, 2022). Besides, the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) indicated that under a business as usual scenario, West African countries will experience a 1.7°C increase in temperature by 2050 with no significant increase in rainfall and a marked reduction in suitable cultivation area (IPCC, 2022;LÄDERACH ET AL., 2013). ...
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Climate change is a serious threat to local communities in West Africa. This study evaluated climatic trends and the perceptions of farmers to climate change in central Côte d'Ivoire. We surveyed 259 households across three agro-ecological zones. The knowledge of farmers about climate change was compared to observed trends of various climatic parameters from meteorological records (1973-2016). Results from trend analysis and descriptive analysis showed that the minimum, maximum and mean temperatures and rainfall showed a significant upward trend in all ecoregions. The average temperature and amount of rainfall increased by 3.2% (0.89°C) and 166.58% (645.5 mm) respectively over the 44 years. Local farmers perceived an increasing trend in temperature (all respondents) and a decreasing trend in rainfall (91.51%). Most of the respondents identified deforestation (76.83%), natural climate variation (50.97%) and wildfires (31.27%) as the main causes of these climatic disturbances, which induced plant dieback (92.66%), poor crop growth (59.46%) and crop loss (20.46%). The impacts on people and their assets encompassed a decrease in household income (63.71%), demolition of roofs (44.4%) and walls (43.91%) of houses, the scarcity of water points (39.38%) and the emergence of new diseases (30.89%). These climatic disturbances resulted in specific endogenous on-farm and off-farm strategies to adapt to the impacts of observed changes on their livelihoods.
... A set of 19 bioclimatic variables downloaded from WorldClim [3] provide average climate conditions for 1970-2000 at 30 arc-s resolution (Table 1). WorldClim data is routinely used for cropland suitability studies because they provide a comprehensive picture of monthly, quarterly, and annual bioclimatic conditions [35,44,45]. The 1-km rasters were resampled to a 180-m resolution. ...
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Given the impact that climate change is projected to have on agriculture, it is essential to understand the mechanisms and conditions that drive agricultural land suitability. However, existing literature does not provide sufficient guidance on the best modeling methodology to study crop suitability, and there is even less research on how to evaluate the accuracy of such models. Further, studies have yet to demonstrate the use of the Maximum Entropy (Maxent) model in predicting presence and yield of large-scale field crops in the United States. In this study, we investigate the application of the Maxent model to predict crop suitability and present novel methods of evaluating its predictive ability. Maxent is a correlative machine learning model often used to predict cropland suitability. In this study, we used Maxent to model land suitability for corn production in the contiguous United States under current bioclimatic conditions. We developed methods for evaluating Maxent’s predictive ability through three comparisons: (i) classification of suitable land units and comparison of results with another similar species distribution model (Random Forest Classification), (ii) comparison of output response curves with existing literature on corn suitability thresholds, and (iii) with correlation of predicted suitability with observed extent and yield. We determined that Maxent was superior to Random Forest, especially in its modeling of areas in which land was likely suitable for corn but was not currently associated with observed corn presence. We also determined that Maxent’s predictions correlated strongly with observed yield statistics and were consistent with existing literature regarding the range of bioclimatic variable values associated with suitable production conditions for corn. We concluded that Maxent was an effective method for modeling current cropland suitability and could be applied to broader issues of agriculture–climate relationships.
... In West Africa, where more than two-thirds of the world's cocoa is produced (Abdulai et al., 2020), current cocoa yields are 80-95% below potential production levels (Asante et al., 2021) estimated at 1000 kg ha − 1 and 1900 kg ha − 1 for on-farm and production on experimental fields, respectively (Bymolt et al., 2018). Major causes for the shortfall include increased temperature and erratic rainfall (Läderach et al., 2013), poor agronomic practices (Asante et al., 2021), pests and diseases, ageing cocoa farms, poor soil conditions, high cost of inputs, and low quality genetic materials (Anim- Kwapong and Frimpong, 2004;Vaast and Somarriba, 2014;Wessel and Quist-Wessel, 2015). ...
Article
CONTEXT Cocoa agroforestry systems differ in the diversity of shade tree species composition. Though cocoa benefits from shade, there is a lack of species-specific information on shade trees that enhance soil fertility and yield. OBJECTIVE We examined how soil characteristics and cocoa yield were affected by eight commonly retained forest tree species, compared with unshaded control plots over a 3-year period. METHODS Using 74 circular plots from 10 cocoa farms in the Western region of Ghana, we sampled soils from two random points within each plot. Soil nutrients at the beginning and end of the study were analyzed, and yield was expressed as number of harvested pods and dry weight of beans per hectare. RESULTS AND CONCLUSIONS Levels of soil K and Ca were below recommended values. Although soil available phosphorus (P) was higher in control plots than under shade trees, yield around shade trees were higher than on unshaded plots. Cocoa yield differences between shade tree species and control plots were significant only in the major crop season, but not in the minor crop season. Cocoa yields under Cedrela odorata, Khaya ivorensis, Terminalia superba and Milicia excelsa were significantly higher than on control plots. Hence, the inclusion of specific shade tree species in cocoa agroforestry systems is important to maintain high yields in cocoa systems with low inputs. SIGNIFICANCE To our knowledge, this study presents one of the first attempt to assess the impacts of specific shade tree species on soil characteristics and cocoa yield.
... Cocoa requires equitable climate with well-distributed annual rainfall of 1500 to 2000 mm under rainfed environment [4]. It requires fairly well defined dry and wet seasons for proper growth, flushing, flowering, fruiting and productivity [5,6,7] [11,12]. There is concern that anticipated rise in global temperature may also rise the potential evapotranspiration that consequently perturb the suitability of climatic condition for cocoa [13]. ...
Article
Climate influences the spread of the any crop by imposing environmental restrictions. The present investigation was carried to understand the effect of climate on cocoa in various cocoa growing regions. In order to establish the relationship between weather parameters and cocoa productivity, Coimbatore, Theni, and Tenkasi were chosen as the study regions. Historical climate data was acquired from India Meteorological Department (IMD) for the past 30 years (1991-2020). Cocoa yield was simulated by using the Agricultural Policy/Environmental eXtender (APEX) and it was correlated with the weather variables such as rainfall, maximum temperature, minimum temperature, atmospheric water demand (PET), and crop water requirement (ET). Cocoa crop had positive correlation with rainfall and Actual Evapotranspiration. Whereas, both maximum and minimum temperature had significantly negative effect. Climatic conditions, such as decrease in rainfall, increase in temperature and increase in PET, would significantly reduce the cocoa bean yield. The anticipated increase in temperature and erratic rainfall distribution requires suitable management measures for sustainable cocoa productivity.
... The disturbance of the cacao-forest balance is the cause of the deterioration of the cacao landscape leading to a modification of the climatic factors (Brou, 2010;Läderach et al., 2013). This change is reflected, among other things, in a decrease in annual rainfall since 1970 in the south forest region (Tanina et al., 2011), which is considered favorable for cacao production. ...
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The strong climatic fluctuation observed during the major cocoa production period with reductions in rainfall and rising temperatures lead to a low graining index. This climatic situation makes cocoa marketing difficult for producers. The stability of quantitative productivity parameters in six cacao clones on farm was analyzed during the main production season. Flowering, average pod weight, number of beans per pod, average bean weight, bean size, and pod index were analyzed. The results obtained showed that the flowering intensity of the clones was high in September (49.07). The average weight of pods decreased from 511.38 g in September to 433.53 g in January. The average weight of a bean and the weight of 100 beans, respectively of 1.3 g and 125.62 g at the beginning of the season dropped in January to 1.13 g and 94.03 g. Clones C8 and C15 showed more stable agronomic characteristics, notably average pod weight, average bean weight, bean size, and pod index during the major production phase. These two promising clones could be used in the rehabilitation phase of degraded cacao plantation, given the stability of their agronomic characteristics.
... As coconut and arecanut are grown across different agro-ecological zones of India, evaluating the impacts of climate change scenarios on the potential cultivable area will be helpful in understanding the relationships between crops niches and the corresponding environment, identifying priority cultivation areas, planning adaptation strategies (Davies et al., 2009;Xu et al., 2018). Species distribution models like Maxent are extensively used to predict the change in climate of some of the plantation growing areas like cocoa in African countries (Läderach et al., 2013;Schroth et al., 2016), coffee at Zimbabwe (Pham et al., 2019) coconut in India and other agricultural crops (Kogo et al., 2019, He andZhou, 2016;Jayasinghe and Kumar, 2019). In this study the MaxEnt model prediction for coconut having the mean AUC values of coconut 0.899+0.002 ...
... The total area under cocoa cultivation in 2021 amounts to 4.3 Mha in Côte d'Ivoire and 2.7 Mha in Ghana, corresponding to 13.5 % and 11.3 % of Côte d'Ivoire's and Ghana's land area respectively. The detected cocoa plantings align well with climatically suitable growing regions in both countries 25 , although we have not restricted the detection to those areas a priori, as in previous mapping projects 13 . Compared to the official FAOSTAT figures 26 , our result deviates only marginally from the harvested area (average 2017-2020) in Côte d'Ivoire, but drastically differs for Ghana's total harvested area. ...
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C\^ote d'Ivoire and Ghana, the world's largest producers of cocoa, account for two thirds of the global cocoa production. In both countries, cocoa is the primary perennial crop, providing income to almost two million farmers. Yet precise maps of cocoa planted area are missing, hindering accurate quantification of expansion in protected areas, production and yields, and limiting information available for improved sustainability governance. Here, we combine cocoa plantation data with publicly available satellite imagery in a deep learning framework and create high-resolution maps of cocoa plantations for both countries, validated in situ. Our results suggest that cocoa cultivation is an underlying driver of over 37% and 13% of forest loss in protected areas in C\^ote d'Ivoire and Ghana, respectively, and that official reports substantially underestimate the planted area, up to 40% in Ghana. These maps serve as a crucial building block to advance understanding of conservation and economic development in cocoa producing regions.
... For instance, cacao farms in the Brazilian amazon (Igawa et al., 2022) where reduction in precipitation and an increase in temperature may affect cacao production. Läderach et al. (2013) demonstrated that future climate change will affect cacao farming in Africa's largest cocoa producer countries. Santosa et al. (2018) showed that productions of cacao in Java-Indonesia fluctuates under climate variability. ...
Article
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A detailed description and up to date biogeographic regionalization of cultivated cacao (Theobroma cacao L.) are lacking in Colombia. Here we propose a new biogeographical regionalization of cultivated cacao for Colombia. We used spatial partitioning, geospatial mapping of macro/microclimate variables and a hierarchical area taxonomy classification to describe, define and propose the biogeographical regions of cultivated cacao. The cacao regions were identified from distributions of 4,974 cocoa producing farms across Colombia. Our proposed regionalization comprises four regions (north-eastern, north-western, south-western, east), 31 sub-regions and 54 provinces. Solar radiation, precipitation, and soil temperature seasonality best explained the biogeographical regions. Rivers networks helped explain the differences at the sub-regional and provinces level. Our results indicate that biogeography is a strong indicator of cacao's agricultural expansion across the different growing regions in Colombia. This up-to-date biogeographical classification could be a useful tool for agricultural planning of cacao in Colombia. Particularly, the baseline information provided might be of use on the development of denominations of origin for cacao.
... The low productivity phenomenon is aggravated by the climate change impacts. Läderach et al. (2013) predicted low productivity in spatially differentiated cocoa growing areas of Ghana and Ivory Coast. These predicted potential effects are already observed in Ghana, where higher productive region for cocoa shifted from Ashanti Region to Western Region (Ghana COCOBOD 2019). ...
Article
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A survey was conducted to investigate farmers’ knowledge, attitudes towards pesticide use, storage/disposal, exposure risks and health symptoms in one of the eight cocoa growing regions in Ghana. A considerable proportion of the farmers (32%) used the bush as a storage facility for pesticides, 17% of the farmers stored chemicals in their living rooms, 3% of the farmers stored chemicals in their kitchen, 15% in their food storeroom, and 4% in the animal house. Personal protective equipment (PPE) use was positively associated with advice obtained from agrochemical shops (OR = 1.735, p < 0.01) and extension services (OR = 1.643, p < 0.01) as sources of information for PPE use. Female farmers (OR = 0.481, p < 0.01) were less likely to use PPE. With respect to location, farmers in Suaman district were less likely to use PPE (OR = 0.56, p < 0.010) compared with farmers in Wassa Amenfi. It is recommended that these factors should be considered for policy intervention. Reinforcement of appropriate pesticide storage and PPE education are necessary for securing safety in pesticide use.
... The bioclimatic predictors represent an annual average, seasonal, and intra-seasonal as well as limiting environmental factors (O'Donnell and Ignizio, 2012). These predictors are related to plant physiological processes and have been widely used in species distribution modeling (Remya et al., 2015;Hijmans and Graham, 2006) and in cropland suitability mapping including rice (Läderach et al., 2013;Beck, 2013;Liu et al., 2015). Most of the 19 bioclimatic predictors are highly correlated, which may represent a major source of error in the correlative models (Braunisch et al., 2013). ...
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CONTEXT: Although rice production has increased significantly in the last decade in West Africa, the region is far from being rice self-sufficient. Inland valleys (IVs) with their relatively higher water content and soil fertility compared to the surrounding uplands are the main rice-growing agroecosystem. They are being promoted by governments and development agencies as future food baskets of the region. However, West Africa’s crop production is estimated to be negatively affected by climate change due to the strong dependence of its agriculture on rainfall. OBJECTIVE: The main objective of the study is to apply a set of machine learning models to quantify the extent of climate change impact on land suitability for rice using the presence of rice-only data in IVs along with bioclimatic indicators. METHODS: We used a spatially explicit modeling approach based on correlative Ecological Niche Modeling. We deployed 4 algorithms (Boosted Regression Trees, Generalized Linear Model, Maximum Entropy, and Random Forest) for 4-time periods (the 2030s, 2050s, 2070s, and 2080s) of the 4 Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8) from an ensemble set of 32 spatially downscaled and bias-corrected Global Circulation Models climate data. RESULTS AND CONCLUSIONS: The overall trend showed a decrease in suitable areas compared to the baseline as a function of changes in temperature and precipitation by the order of 22–33% area loss under the lowest reduction scenarios and more than 50% in extreme cases. Isothermality or how large the day to night temperatures oscillate relative to the annual oscillations has a large impact on area losses while precipitation increase accounts for most of the areas with no change in suitability. Strong adaptation measures along with technological advancement and adoption will be needed to cope with the adverse effects of climate change on inland valley rice areas in the sub-region. SIGNIFICANCE: The demand for rice in West Africa is huge. For the rice self-sufficiency agenda of the region, “where” and “how much” land resources are available is key and requires long-term, informed planning. Farmers can only adapt when they switch to improved breeds, providing that they are suited for the new conditions. Our results stress the need for land use planning that considers potential climate change impacts to define the best areas and growing systems to produce rice under multiple future climate change uncertainties.
... The bioclimatic predictors represent an annual average, seasonal, and intra-seasonal as well as limiting environmental factors (O'Donnell & Ignizio, 2012). These predictors are related to plant physiological processes and have been widely used in species distribution modeling (Remya et al., 2015;Hijmans & Graham, 2006) and in cropland suitability mapping including rice (Läderach et al., 2013;Beck, 2013;Liu et al., 2015). Most of the 19 bioclimatic predictors are highly correlated, which may represent a major source of error in the correlative models (Braunisch et al., 2013). ...
Article
Full-text available
CONTEXT Although rice production has increased significantly in the last decade in West Africa, the region is far from being rice self-sufficient. Inland valleys (IVs) with their relatively higher water content and soil fertility compared to the surrounding uplands are the main rice-growing agroecosystem. They are being promoted by governments and development agencies as future food baskets of the region. However, West Africa's crop production is estimated to be negatively affected by climate change due to the strong dependence of its agriculture on rainfall. OBJECTIVE The main objective of the study is to apply a set of machine learning models to quantify the extent of climate change impact on land suitability for rice using the presence of rice-only data in IVs along with bioclimatic indicators. METHODS We used a spatially explicit modeling approach based on correlative Ecological Niche Modeling. We deployed 4 algorithms (Boosted Regression Trees, Generalized Linear Model, Maximum Entropy, and Random Forest) for 4-time periods (the 2030s, 2050s, 2070s, and 2080s) of the 4 Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8) from an ensemble set of 32 spatially downscaled and bias-corrected Global Circulation Models climate data. RESULTS AND CONCLUSIONS The overall trend showed a decrease in suitable areas compared to the baseline as a function of changes in temperature and precipitation by the order of 22–33% area loss under the lowest reduction scenarios and more than 50% in extreme cases. Isothermality or how large the day to night temperatures oscillate relative to the annual oscillations has a large impact on area losses while precipitation increase accounts for most of the areas with no change in suitability. Strong adaptation measures along with technological advancement and adoption will be needed to cope with the adverse effects of climate change on inland valley rice areas in the sub-region. SIGNIFICANCE The demand for rice in West Africa is huge. For the rice self-sufficiency agenda of the region, “where” and “how much” land resources are available is key and requires long-term, informed planning. Farmers can only adapt when they switch to improved breeds, providing that they are suited for the new conditions. Our results stress the need for land use planning that considers potential climate change impacts to define the best areas and growing systems to produce rice under multiple future climate change uncertainties.
... Favourable climatic conditions are necessary at every stage of cocoa production. As a result, differences in cocoa yields are affected more by rainfall than by any other climatic factor, making the crop sensitive to a soil water deficiency (Agbongiarhuoyi et al., 2013;Läderach et al., 2013;Ehiakpor et al., 2016a, Ehiakpor et al., 2016bSchroth et al., 2016;Osei, 2017). In Ghana, climate change is expected to adversely affect cocoa productivity and reduce the area suitable for cocoa cultivation (Denkyirah et al., 2017;Okoffo et al., 2016). ...
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Studies have generally shown that climate change has tremendous impacts on cocoa productivity. Although there is an increasing proliferation of studies on adaptation strategies of cocoa farmers, many of the studies are not linked to climate services that provide information to help ensure climate smart decision-making among cocoa farmers. This study investigates the perception and adaptation strategies of cocoa farmers to draw insights into climate services necessary for adaptation. Through a semi-structured questionnaire survey of 150 cocoa farming households and Focus Group Discussions, the study found that key adaptation strategies include changing planting dates, diversification to non-farm activities, planting improved cocoa varieties, crop diversification, and tree planting. Age and information seeking behaviour of farmers have positive influence on access to climate services which serves as a basis for these adaptation strategies. The existing climate services are not comprehensive enough to cover the wide array of adaptation needs of farmers. Current services focus on only dissemination of rainfall and temperature information through radio and television without providing information on other adaptation needs such as planning and harvesting dates. The findings suggest that there is a need for scaling up access to climate services in areas of planting services and crop improvement through zero literacy devices if cocoa farmers’ adaptation to climate impacts are to be addressed.
... It is projected that forest clearance boosted cocoa-growing areas from 250.000 ha in 1961 to 4.000.000 ha in 2004 (Franzen and Mulder, 2007;Läderach et al., 2013;Konate et al., 2017). It is estimated that income produced by cocoa plantations following deforestation accounts for 10% of national GDP (Brou et al., 2004;Sonwa et al., 2007;Morris, 2010;Beucher and Bazin, 2012). ...
Article
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African forests, especially in Côte d'Ivoire, have been lost during the past three decades. Worldwide, forests are being destroyed to make room for farmland. Deforestation depletes floral resources and fragments habitat. Cocoa growth threatens critical ecological zones, particularly in Côte d'Ivoire. The 2002-2007 conflict impacted Mount Peko National Park (PNMP). This issue has hastened the decline of endangered animal habitats (Colobus and Elephants). The classification approach based on Random Forest (RF) algorithm using the Mean Accuracy Decrease (MDA) has been applied for choosing a variable to select the best predictor variables in the model. A Spectral Index map and time series satellite images of the PNMP from 1985 to 2020 were used to identify land cover changes. RStudio and QGIS 3.4 software have been used to create training data. Among thirteen (13) variables studied, NIR (Near Infrared), ShortWave Infrared 1 (SWIR 1) and SWIR bands had the increased importance of the variable for the performance of the classification prediction model. The NIR band was the greatest predictor. MDA predicted 75%. User accuracy (UA), Producer accuracy (PA), and Overall accuracy (OA) classifications were 98.75% ± 1.94, 99% ± 1.95, 97% ± 1.93. The park's dense forest remained unchanged, but nonforest was reforested and 12.22% was turned to forest. During the study period, extensive cocoa plantations were established in formerly forested regions.
... Aboveground interactions include the exposure of the different species in the various strata of the AFS to climate and weather (Niether et al., 2018). While some shade in AFS can even support the physiological functioning of the cacao trees (Baligar et al., 2008) and their longevity by reducing stressful environmental conditions (Läderach et al., 2013), heavy shade reduces light for photosynthesis and can lead to delayed growth and reduced cocoa yield . Belowground interactions in AFS are less obvious than those aboveground, and remain largely unclear and unexplored. ...
Thesis
There is hardly any place left on earth that can be considered untouched nature. Humans penetrate into all areas of this earth, and may it be through greenhouse gas emissions or other types of air and environmental pollution. Deforestation and the conversion of land to agriculture are processes that accompany the spread of humans on this earth, and which shape the landscapes. In this context, tropical forests are nowadays in the focus of forest clearing and land use change. To maintain or restore the ecosystem functions and biodiversity of tropical forests, alternative agricultural land uses are needed. In order to test alternative production systems, the Research Institute of Organic Agriculture (FiBL) launched the research project "Comparison of cropping systems in the tropics" (https://systems-comparison.fibl.org/). In Alto Beni (Bolivia), five different cacao production systems are being tested in a long-term trial with regard to their economic, ecological and social impacts. The farming systems range from monocultures to simple agroforestry systems, each under conventional and organic management, to highly complex successional, multistrata agroforestry systems. The plots were established in 2008, in a completely randomized block design, with four replications. The general objective of this dissertation is to compare, within the long-term experiment in Bolivia, the different cacao cropping systems in terms of their capacity to store and convert carbon, and to draw conclusions on the availability of nutrients through microbial activity. It was hypothesized that (1) AFS store more above and below ground biomass, in the form of carbon, over time, and that (2) both biological management and AFS result in higher biological activity. To verify this, (1) the different aboveground biomass pools were studied, (2) the biomass obtained from pruning was measured, (3) the annual leaf fall was recorded, (4) the decomposition of leaf litter within one year was analyzed, and (5) the root growth was estimated. The work performed showed that total aboveground biomass is greater in AFS than in monocultures. However, in the monocultures, the biomass of cacao trees is larger than in the other cropping systems. The total aboveground biomass in AFS is only about one-third of the biomass stored in trees in the surrounding forests. In managed AFS, the biomass produced by pruning can be twice that of natural leaf fall, and is thus an important source of carbon and nitrogen. The half-life of litter decomposition in the different systems did not differ, despite different microclimates and higher microbial activity in the organically managed plots. Nitrogen-rich leaves of legumes were decomposed faster than lignin-rich cacao leaves. Soil quality is improved 6 years after installation, in the organically managed plots compared to the conventional plots, as evidenced by higher carbon and nitrogen levels, as well as higher microbial activity. Fine root growth is also greater in AFS and biologically managed plots than in the monocultures. The different studies show that AFS have a pronounced advantage over monocultures in terms of biomass accumulation, even if they do not reach the level of primary or secondary forests. The work shows that there is a strong linkage of the different carbon pools in AFS. More aboveground biomass and fast-growing legumes allow regular pruning, which stimulates carbon and nitrogen cycling. Accumulated litter is decomposed by microorganisms, leading to better soil conditions and nutrient availability. Therefore, it can be concluded from the present work that AFS cannot per se prevent the clearing of rainforests for agricultural land. However, AFS, unlike monocultures, have a better ecological balance, with more biomass and better soils. The more stable and sustainable AFS are therefore preferable from an ecological perspective to monocultures which are designed for short-term profit.
... The bioclimatic predictors represent an annual average, seasonal, and intra-seasonal as well as limiting environmental factors (O'Donnell and Ignizio, 2012). These predictors are related to plant physiological processes and have been widely used in species distribution modeling (Remya et al., 2015;Hijmans and Graham, 2006) and in cropland suitability mapping including rice (Läderach et al., 2013;Beck, 2013;Liu et al., 2015). Most of the 19 bioclimatic predictors are highly correlated, which may represent a major source of error in the correlative models (Braunisch et al., 2013). ...
Article
CONTEXT Although rice production has increased significantly in the last decade in West Africa, the region is far from being rice self-sufficient. Inland valleys (IVs) with their relatively higher water content and soil fertility compared to the surrounding uplands are the main rice-growing agroecosystem. They are being promoted by governments and development agencies as future food baskets of the region. However, West Africa's crop production is estimated to be negatively affected by climate change due to the strong dependence of its agriculture on rainfall. OBJECTIVE The main objective of the study is to apply a set of machine learning models to quantify the extent of climate change impact on land suitability for rice using the presence of rice-only data in IVs along with bioclimatic indicators. METHODS We used a spatially explicit modeling approach based on correlative Ecological Niche Modeling. We deployed 4 algorithms (Boosted Regression Trees, Generalized Linear Model, Maximum Entropy, and Random Forest) for 4-time periods (the 2030s, 2050s, 2070s, and 2080s) of the 4 Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8) from an ensemble set of 32 spatially downscaled and bias-corrected Global Circulation Models climate data. RESULTS AND CONCLUSIONS The overall trend showed a decrease in suitable areas compared to the baseline as a function of changes in temperature and precipitation by the order of 22–33% area loss under the lowest reduction scenarios and more than 50% in extreme cases. Isothermality or how large the day to night temperatures oscillate relative to the annual oscillations has a large impact on area losses while precipitation increase accounts for most of the areas with no change in suitability. Strong adaptation measures along with technological advancement and adoption will be needed to cope with the adverse effects of climate change on inland valley rice areas in the sub-region. SIGNIFICANCE The demand for rice in West Africa is huge. For the rice self-sufficiency agenda of the region, “where” and “how much” land resources are available is key and requires long-term, informed planning. Farmers can only adapt when they switch to improved breeds, providing that they are suited for the new conditions. Our results stress the need for land use planning that considers potential climate change impacts to define the best areas and growing systems to produce rice under multiple future climate change uncertainties.
... This has had negative implications for livelihoods since the cocoa sector is highly sensitive to climate variability (Peprah, 2015). For instance, historical data shows a progressive rise in temperature and decrease in mean annual rainfall in all six agro-ecological zones of Ghana, with the projection of a drastic decrease in climatic suitability for cocoa in the current growing regions by 2050 (Eastin, 2018;Läderach et al., 2013). Current projections are that higher temperatures and lower rainfall in parts of Africa combined with a doubling of the population will lead to a 43% increase in food insecurity (Funk & Brown, 2009). ...
Article
Environmental and climate change issues have exacerbated the existing gender inequalities in Ghana's cocoa sector. The current underrepresentation and unequal access to opportunities for women in climate action initiatives has negative implications for their livelihoods. This research focuses on how harvesting cocoa waste enabled the creation of a sustainable micro enterprise to encourage adoption of shaded cocoa production to generate biomass (waste) for organic compost production. The study followed a prescribed training programme for organic compost production and agribusiness management skills. The study employed the analysis of project notes and post-training community-visit observation records and interviews to assess the success of the training workshops and the overall project progress. Results from the analyses indicate that the knowledge and skills provided engendered motivation for a continuous and expanded adoption of climate-smart agri-innovation of shaded cocoa production. Further, the results show evidence of positive social, environmental, cultural, and economic impacts and favourable prospects of improved livelihoods for female cocoa farmers. These insights imply that SDG13, which calls for urgent climate action, can be integrated with SDG5, which places emphasis on gender equity, to improve the adoption of cocoa agroforestry and the livelihood of women in the cocoa sector of Ghana.
... Drought stress is the most common environmental stress causing threat to successful production of crop plants. There is a growing concern about the global increase Open Access *Correspondence: ccrp@kau.in 2 Cocoa Research Centre, Kerala Agricultural University, Thrissur, India Full list of author information is available at the end of the article in temperature and simultaneous increase in potential evapo-transpiration [5]. Plant water demand may result in increased drought stress during the day and a further deterioration of climatic condition for cocoa. ...
Article
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Background: Cocoa, being a shade loving crop cannot withstand long periods of water stress. Breeding for drought tolerance is the need of the hour due to change in climatic condition and extension of crop to non-traditional areas. Hybrids were produced by crossing four tolerant genotypes in all possible combination. The cross GV1 55 x M 13.12 didn't yield any fruit due to cross incompatibility between these genotypes. Various biochemical parameters act as the true indicators to select tolerant and susceptible types. The major biochemical parameters considered after imposing stress included proline, nitrate reductase activity, superoxide dismutase content and glycine betaine. Results: The drought tolerant hybrids were having high amount of proline, superoxide dismutase enzyme and gly-cine betaine content. Normally, plants having drought stress show low amount of nitrate reductase activity. However, in case of hybrids, the drought tolerant hybrids were having higher NR activity than the susceptible hybrids. The highest amount of NR was found in the control plants kept at fully irrigated conditions. Conclusions: This experiment showed the role of different biochemical enzymes and osmolytes in giving tolerance to plants during drought stress. Logistic regression analysis selected proline and nitrate reductase as the two biochemical markers for identifying efficient drought tolerant genotypes in the future breeding programmes.
... Drought stress is the most common environmental stress causing threat to successful production of crop plants. There is a growing concern about the global increase in temperature and simultaneous increase in potential evapo-transpiration [5]. Plant water demand may result in increased drought stress during the day and a further deterioration of climatic condition for cocoa. ...
Article
Full-text available
Background Cocoa, being a shade loving crop cannot withstand long periods of water stress. Breeding for drought tolerance is the need of the hour due to change in climatic condition and extension of crop to non-traditional areas. Hybrids were produced by crossing four tolerant genotypes in all possible combination. The cross GV1 55 x M 13.12 didn’t yield any fruit due to cross incompatibility between these genotypes. Various biochemical parameters act as the true indicators to select tolerant and susceptible types. The major biochemical parameters considered after imposing stress included proline, nitrate reductase activity, superoxide dismutase content and glycine betaine. Results The drought tolerant hybrids were having high amount of proline, superoxide dismutase enzyme and glycine betaine content. Normally, plants having drought stress show low amount of nitrate reductase activity. However, in case of hybrids, the drought tolerant hybrids were having higher NR activity than the susceptible hybrids. The highest amount of NR was found in the control plants kept at fully irrigated conditions. Conclusions This experiment showed the role of different biochemical enzymes and osmolytes in giving tolerance to plants during drought stress. Logistic regression analysis selected proline and nitrate reductase as the two biochemical markers for identifying efficient drought tolerant genotypes in the future breeding programmes.
... The three major cocoa producing countries are Ivory Coast, Ghana, and Indonesia. In West Africa, 89.5% of the current cocoa production areas are predicted to experience a decline in cocoa suitability until 2050 (5,6). The biggest cocoa producing island Sulawesi in Indonesia will need strong climate adaptation strategies by 2050 (7). ...
Preprint
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Production of cocoa, the third largest trade commodity globally has experienced climate related yield stagnation since 2016, forcing farmers to expand production in forested habitats and to shift from nature friendly agroforestry systems to intensive monocultures. The goal for future large-scale cocoa production combines high yields with biodiversity friendly management into a climate adapted smart agroforestry system (SAS). As pollination limitation is a key driver of global production, we use data of more than 150,000 cocoa farms and results of hand pollination experiments to show that manually enhancing cocoa pollination (hereafter manual pollination) can produce SAS. Manual pollination can triple farm yields and double farmers annual profit in the major producer countries Ivory Coast, Ghana, and Indonesia, and can increase global cocoa supplies by up to 13%. We propose a win win scenario to mitigate negative long term price and socioeconomic effects, whereby manual pollination compensates only for yield losses resulting from climate and disease related decreases in production area and conversion of monocultures into agroforestry systems. Our results highlight that yields in biodiversity friendly and climate adapted SAS can be similar to yields currently only achieved in monocultures. Adoption of manual pollination could be achieved through wider implementation of ecocertification standards, carbon markets, and zero deforestation pledges.
... In the context of cacao agriculture, most studies have focused on the consequences of projected climate change (Mora et al. 2013;Trisos et al. 2020). In the African country of Ivory Coast, it has been shown that the relative climate suitability of cocoa production areas will suffer a reduction by 2050 due to a decrease in rainfall and temperature conditions (Läderach et al. 2013). Because most climate change studies worldwide are based on predictive modelling, they mainly rely on projected mean values, increasing the level of uncertainty (Ruf et al. 2015;Bunn 2019;Brown et al. 2020). ...
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Previous research indicates that some important cocoa cultivated areas in West Africa will become unsuitable for growing cocoa in the next decades. However, it is not clear if this change will be mirrored by the shade tree species that could be used in cocoa-based agroforestry systems (C-AFS). We characterized current and future patterns of habitat suitability for 38 tree species (including cocoa), using a consensus method for species distribution modelling (SDM) considering for the first time climatic and soil variables. The models projected an increase of up to 6% of the potential suitable area for cocoa by 2060 compared to its current suitable area in West Africa. Furthermore, the suitable area was highly reduced (14.5%) once considering only available land-use not contributing to deforestation. Regarding shade trees, 50% of the 37 shade tree species modelled will experience a decrease in geographic rate extent by 2040 in West Africa, and 60% by 2060. Hotspots of shade tree species richness overlap the current core cocoa production areas in Ghana and Côte d’Ivoire, suggesting a potential mismatch for the outer areas in West Africa. Our results highlight the importance of transforming cocoa-based agroforestry systems by changing shade tree species composition to adapt this production systems for future climate conditions.
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The growing need for information on the dynamics of land use and agricultural activity in the Amazon requires additional studies. This research work aimed to propose a methodology for mapping small-scale cocoa fields, as well as discussing the spatial dynamics of these fields in the municipality of Tomé-Açu, state of Pará. A database was built on the QGIS platform, intended for manipulation and analysis of georeferenced data. The mapping of cocoa fields comprised a 2017, 3 m spatial resolution PlanetScope image mosaic, bands 1, 2 and 3. Images were classified by preliminary visual analysis of spatial and spectral patterns. The product was further refined through participatory mapping with local stakeholders. Cocoa fields predominated in landholdings smaller than 50 ha, which is the size of the fiscal module defined for the study area. Nearly 4,000 hectares of cocoa fields were registered in 2017. These fields are clustered near the road network, in consolidated agricultural areas, far from the agricultural expansion frontier. RESUMO: A crescente demanda por informações sobre a dinâmica de uso das terras e da atividade agrícola na Amazônia, exige um esforço para que novos estudos sejam realizados. Este trabalho teve por objetivo propor uma metodologia para o mapeamento de pequenos cultivos de cacau, bem como discutir as relações espaciais dos mesmos no contexto do município de Tomé-Açu, Estado do Pará. Para isso, foi construída uma, v. 13, n. 2, p. 155-170, 2021, ISSN online 2318-0188 base de dados na plataforma QGIS, destinada à manipulação e à análise de dados georreferenciados. O mapeamento dos cultivos de cacau considerou mosaico de imagens PlanetScope, bandas 1, 2 e 3, ano de 2017, com resolução espacial de 3 m. As imagens foram classificadas por análise visual preliminar, considerando padrões espaciais e espectrais. O produto obtido foi refinado posteriormente a partir de mapeamentos participativos com atores locais. Verificou-se que as áreas com cacau se concentram em propriedades de até 50 ha, valor este relativo ao módulo fiscal definido para a área de estudo. Foram registrados quase 4 mil hectares de cultivos de cacau no ano de 2017. Os plantios de cacau estão concentrados próximos à malha viária, em áreas agrícolas consolidadas, distantes das frentes pioneiras de expansão agrícola. PALAVRAS-CHAVE: Geotecnologias, Análise espacial, Cultura perene. PATRONES ESPACIALES DE SISTEMAS AGROFORESTALES CON CULTIVO DE CACAO EN TOMÉ-AÇU, NORDESTE DE LA AMAZONÍA BRASILEÑA RESUMEN: La creciente demanda de información sobre la dinámica del uso del suelo y la actividad agrícola en la Amazonía requiere un esfuerzo para la realización de nuevos estudios. Este trabajo tuvo como objetivo proponer una metodología para el mapeo de pequeños cultivos de cacao, así como discutir sus relaciones espaciales en el contexto del municipio de Tomé-Açu, Estado de Pará, Brasil. Para ello, se construyó una base de datos en la plataforma QGIS, destinada a la manipulación y análisis de datos georreferenciados. El mapeo de cultivos de cacao consideró mosaico de imágenes PlanetScope, bandas 1, 2 y 3, año 2017, con una resolución espacial de 3 m. Las imágenes se clasificaron mediante un análisis visual preliminar, considerando patrones espaciales y espectrales. El producto obtenido se refinó aún más a partir del mapeo participativo con actores locales. Se encontró que las áreas con cacao se concentran en propiedades de hasta 50 ha, lo cual está relacionado con el módulo fiscal definido para el área de estudio. En 2017 se registraron casi 4.000 hectáreas de cultivos de cacao. Las plantaciones de cacao se concentran cerca de la red vial, en áreas agrícolas consolidadas, lejos de los frentes pioneros de expansión agrícola.
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The revival of cocoa farming in the Forest-Savannah Transition Zone (FSTZ) of Ghana despite high production risk raises questions on the factors underlying it, and whether the renewed interest in cocoa can be sustained. This paper examines the reasons that underlie households’ decision to farm cocoa or otherwise in the FSTZ, and how risk perceptions, demographic factors and livelihood assets predict such crop choice decisions. Methods of data collection include household surveys and key informant interviews. Four hundred and eight household heads and 32 key informants were interviewed in 12 farming communities. Findings indicate divergent crop choice decisions on cocoa among farming households. While market security generally created a strong incentive for cocoa farming, some households exhibited risk aversion by avoiding or abandoning cocoa farming. The decision to farm cocoa was negatively predicted by perceptions of drought and lack of money as the most severe risk factors of cocoa farming, the sex of the household head (being a female) and lack of land ownership and social network with cocoa farmers. Currently, it appears the renewed interest in cocoa farming can be sustained, especially considering market uncertainties for alternative crops (cashew and food crops). This may, however, not be the case in the long term. More households are likely to avoid or abandon cocoa farming if climate and food security risks should worsen as projected, and more so if the cashew market is stabilised by government. Cocoa investment programmes in the FSTZ aiming at long-term sustainability ought to target households that are more likely to farm cocoa under high production risk. Such programmes may also attract new farmers and sustain their interest in cocoa farming by enhancing their access to land, capital, and irrigation facilities (for managing drought). At the moment, crop diversification (towards cashew and food crops) rather than crop switching is needed to manage the climate, market and food security risks confronting farmers. Overall, the paper contributes to a better understanding of the determinants of farmers’ crop choice decisions on cocoa in the context of multiple risks.
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Se presenta la distribución potencial de cultivos en el estado de Mérida, utilizando modelos de distribución basados en datos recopilados en el campo y variables ambientales, y su distribución potencial en escenarios de cambio climático (CC). Se registró la presencia y ausencia de los cultivos: papa, zanahoria, café, cacao y plátano, y se estimó estadísticamente la distribución de cada uno. Con base en las trayectorias de concentración representativas (RCP), se desarrollaron modelos espaciales en escenarios CC. El cultivo de cacao muestra un área potencial de 3,62%, mientras que el cultivo de café de sombra presenta un área posible de 20,33%. Los modelos espaciales actuales tienen un alto potencial climático para la distribución de cultivos de papa y café de sombra. En los escenarios CC, el café disminuyó el área ideal, mientras que los cultivos de papa en 2100 pierden el 69% del área potencial.
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Cacao (Theobroma cacao L.) is among the most important cash crops in tropical countries. The existing cacao genetic diversity represents a key resource to ensure the long-term sustainability of cacao cultivation but it remains vastly underused. The objective of this paper is to describe the current state of conservation and use of cacao genetic materials in six countries in South (Peru and Ecuador) and Central America (Nicaragua, Honduras, El Salvador, Guatemala). For each country, we reviewed the regulations for cacao genetic resources, we carried out a survey of 176 gene banks and nurseries, and we performed a review of breeding and selection programs. We found that all countries had poor systems of certification, verification and traceability. Gene banks conserved many local materials in Peru and Ecuador while they mainly conserved international clones in Central American countries. In all countries except Honduras, more than half of the gene banks did not have any characterization or evaluation data of the conserved materials. Although nurseries in all countries had fair productive capacities, varieties sold were unevenly characterized in Peru, Ecuador and Guatemala, and less than half of the nurseries provided technical assistance to farmers in Ecuador and El Salvador. Breeding and selection programs had not fully used the cacao diversity in these countries. Based on the results, we identified the strengths and weakness, as well as the most appropriate investment areas for each country. A better conservation and use of cacao genetic resources in Latin America would benefit not only these countries but also the whole cacao sector
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Potential distribution of crops in the state of Mérida is proposed using a models based on field data collection and environmental variables and its potential distribution in climate change scenarios (CC). The presence and absence of crops: potato, carrot, coffee, cocoa, and banana were registered, and the distribution for each was statistically estimated. Based on the representative concentration trajectories (RCP), spatial models were developed in CC scenarios. The cocoa crop shows a potential area of 3,62%, while the shade coffee crop presents a possible area of 20,33%. Current spatial models have a high climatic potential for the distribution of potato and shade coffee crops. In CC scenarios, coffee decreased the ideal area, while potato crops by 2100 lose 69% of the potential area.
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Agroforestry is part of the package of good agricultural practices (GAPs) referred to as a reference to basic environmental and operational conditions necessary for the safe, healthy, and sustainable production of cocoa. Furthermore, cocoa agroforestry is one of the most effective nature-based solutions to address global change including land degradation, nutrient depletion, climate change, biodiversity loss, food and nutrition insecurity, and rural poverty and current cocoa supply chain issues. This study was carried out in SouthWestern Côte d'Ivoire through a household survey to assess the willingness of cocoa farmers to adopt cocoa agroforestry, a key step towards achieving sustainability in the cocoa supply chain markedly threatened by all types of biophysical and socioeconomic challenges. In total, 910 cocoa households were randomly selected and individually interviewed using a structured questionnaire. Findings revealed that from the overwhelming proportion of farmers practicing full-sun cocoa farming with little or no companion trees associated, 50.2 to 82.1% were willing to plant and to keep fewer than 20 trees per ha in their farms for more than 20 years after planting. The most preferred trees provide a range of ecosystem services, including timber and food production, as well as shade regulation. More than half of the interviewed households considered keeping in their plantations for more than 20 years subject to the existence of a formal contract to protect their rights and tree ownership. This opinion is significantly affected by age, gender, access to seedlings of companion trees and financial resources. A bold step forward towards transitioning to cocoa agroforestry and thereby agroecological intensification lies in (i) solving the issue of land tenure and tree ownership by raising awareness about the new forest code and, particularly, the understanding of cocoa agroforestry, (ii) highlighting the added value of trees in cocoa lands, and (iii) facilitating access to improved cocoa companion tree materials and incentives. Trends emerged from this six-year-old study about potential obstacles likely to impede the adoption of agroforestry by cocoa farmers meet the conclusions of several studies recently rolled out in the same region for a sustainable cocoa sector, thereby confirming that not only the relevance of this work but also its contribution to paving the way for the promotion of agroecological transition in cocoa farming.
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A brief history of development of the 1985 Hargreaves equation and its comparison to evapotranspiration (ET) predicted by the Food and Agricultural Organization of the United Nations (FAO) Penman-Monteith method are described to provide background and information helpful in selecting an appropriate reference ET equation under various data situations. Early efforts in irrigation water requirement computations in California and other and and semiarid regions required the development of simplified ET equations for use with limited weather data. Several initial efforts were directed towards improving the usefulness of pan evaporation for estimating irrigation water requirements. Similarity with climates of other countries allowed developments in California to be extended overseas. Criticism of empirical methods by H. L. Penman and others encouraged the search for a robust and practical method that was based on readily available climatic data for computing potential evapotranspiration or reference crop evapotranspiration (ETo). One of these efforts ultimately culminated in the 1985 Hargreaves ET, method. The 1985 Hargreaves ETo method requires only measured temperature data, is simple, and appears to be less impacted than Penman-type methods when data are collected from and or semiarid, nonirrigated sites. For irrigated sites, the Hargreaves 1985 ETo method produces values for periods of five or more days that compare favorably with those of the FAO Penman-Monteith and California Irrigation Management Information Services (CIMIS) Penman methods. The Hargreaves ETo predicted 0.97 of lysimeter measured ETo at Kimberly, Idaho after adjustment of lysimeter data for differences in surface conductance from the FAO Penman-Monteith definition. Monthly ETo by the 1985 Hargreaves equation compares closely with ETo calculated using a simplified, "reduced-set" Penman-Monteith that requires air temperature data only.
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c1 Address for correspondence: Pear Tree Cottage, Frog Lane, Ilmington, Shipston on Stour, Warwickshire, CV36 4LQ, UK. Email: mikecarr@cwms.org.uk
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Global circulation models all forecast that climate change will increase mean temperatures and change precipitation regimes. As a result, traditional coffee growing regions may disappear and new regions may appear. At the same time, demand for high quality, responsibly sourced coffee continues to grow globally. For sustainable sources of coffee, participants in the global coffee supply chain need to know where coffee will grow in the future and how the suitability of these areas will change over time. With this information, the supply chain then needs to develop appropriate site-specific mitigation and adaptation strategies for both the short and the long term, to guarantee coffee supply as well as to support improved livelihoods for rural communities. In this paper, we firstly quantify the impact of climate change on the suitability of land to grow coffee in a case study in Nicaragua and on acidity content of beverage coffee in a case study in the Veracruz Department of Mexico. Secondly, we propose site-specific adaptation strategies and finally identify critical potential impacts of climate change on the overall supply chain and the implications for all actors in the system. We conclude the paper by identifying key directions for future research to seek mitigation and adaptation strategies at both the community and the supply-chain level. KeywordsAdaptation-Climate change-Coffee-Spatial modelling-Supply chains
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The mountain chain of the Sierra Madre de Chiapas in southern Mexico is globally significant for its biodiversity and is one of the most important coffee production areas of Mexico. It provides water for several municipalities and its biosphere reserves are important tourist attractions. Much of the forest cover outside the core protected areas is in fact coffee grown under traditional forest shade. Unless this (agro)forest cover can be sustained, the biodiversity of the Sierra Madre and the environmental services it provides are at risk. We analyzed the threats to livelihoods and environment from climate change through crop suitability modeling based on downscaled climate scenarios for the period 2040 to 2069 (referred to as 2050s) and developed adaptation options through an expert workshop. Significant areas of forest and occasionally coffee are destroyed every year by wildfires, and this problem is bound to increase in a hotter and drier future climate. Widespread landslides and inundations, including on coffee farms, have recently been caused by hurricanes whose intensity is predicted to increase. A hotter climate with more irregular rainfall will be less favorable to the production of quality coffee and lower profitability may compel farmers to abandon shade coffee and expand other land uses of less biodiversity value, probably at the expense of forest. A comprehensive strategy to sustain the biodiversity, ecosystem services and livelihoods of the Sierra Madre in the face of climate change should include the promotion of biodiversity friendly coffee growing and processing practices including complex shade which can offer some hurricane protection and product diversification; payments for forest conservation and restoration from existing government programs complemented by private initiatives; diversification of income sources to mitigate risks associated with unstable environmental conditions and coffee markets; integrated fire management; development of markets that reward sustainable land use practices and forest conservation; crop insurance programs that are accessible to smallholders; and the strengthening of local capacity for adaptive resource management.
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A recent debate has contrasted two conservation strategies in agricultural landscapes; either “land sparing” farm development combining intensive production practices with forest set-asides, or “wildlife-friendly” farming with greater on-farm habitat value but lower yields. We argue that in established mosaic landscapes including old cacao production regions where natural forest has already been reduced to relatively small fragments, a combination of both strategies is needed to conserve biodiversity. After reviewing the evidence for the insufficiency of either strategy alone if applied to such landscapes, the paper focuses on the cacao production landscape of southern Bahia, Brazil, once the world’s second largest cacao producer. Here, small remaining areas of Atlantic Forest are embedded in a matrix dominated by traditional cacao agroforests, resulting in a landscape mosaic that has proven favorable to the conservation of the region’s high biodiversity. We show that current land use dynamics and public policies pose threats but also offer opportunities to conservation and describe a three-pronged landscape conservation strategy, consisting of (i) expansion of the protected areas system, (ii) promotion of productive yet biodiversity-friendly cacao farming practices, and (iii) assistance to land users to implement legally mandated on-farm reserves and voluntary private reserves. We discuss recent experiences concerning the implementation of this strategy, discuss likely future scenarios, and reflect on the applicability of the Bahian experience to biodiversity rich cacao production regions elsewhere in the tropics. KeywordsAgroforest–Atlantic Forest– Cabruca –Landscape scale conservation–On-farm reserves– Theobroma cacao
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Research on coffee agroforestry systems in Central America has identified various environmental factors, management strategies and plant characteristics that affect growth, yield and the impact of the systems on the environment. Much of this literature is not quantitative, and it remains difficult to optimise growing area selection, shade tree use and management. To assist in this optimisation we developed a simple dynamic model of coffee agroforestry systems. The model includes the physiology of vegetative and reproductive growth of coffee plants, and its response to different growing conditions. This is integrated into a plot-scale model of coffee and shade tree growth which includes competition for light, water and nutrients and allows for management treatments such as spacing, thinning, pruning and fertilising. Because of the limited availability of quantitative information, model parameterisation remains fraught with uncertainty, but model behaviour seems consistent with observations. We show examples of how the model can be used to examine trade-offs between increasing coffee and tree productivity, and between maximising productivity and limiting the impact of the system on the environment. KeywordsYield-Environmental impact-Climate-Soil-Management-Sensitivity analysis
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