Climate Change as a Threat to Growing Area Suitability for Cocoa

### **Chapter 1**

## Perspective Chapter: Microclimate, Plant Stress and Extension of Cacao Frontiers to Marginal Agroecologies of the Rainforest Tropics

*Samuel Ohikhena Agele, Olufemi Samuel Ibiremo and Oladitan Titilayo*

### **Abstract**

Cacao (*Theobroma cacao* L.) is an important cash crop of the rainforest tropics where it is a major foreign exchange earner, industrial raw material, livelihood, and offer ecosystem services. The rainforest of the tropics is noted for high productivity potential for cacao, however, and its development prospects is beset with numerous challenges among which is the threat of climate change which is setting new ecological boundaries. The new regimes of climate are expected to affect the area suitable for agriculture, thus, crop species are bound to grow in areas where they were not previously grown and areas that were hitherto not suitable for their production. Nevertheless, the shifting environment conditions and associated marginal growing environment conditions (weather: (increasing warming and drought) and soil) may offer opportunities for extending crop frontiers beyond its current ecological boundaries. It is therefore necessary to develop strategies for alleviating constraints imposed by changing environmental conditions thus setting the agenda for climate smart adaptable and sustainable production systems. In addition, efforts to unlock the potentials of the new environmental boundaries for crops will benefit from knowledge, technologies and innovations and climate mitigation.

**Keywords:** Theobroma, cultivation, marginal, agroecology, mitigation resilience, climate stress

### **1. Introduction**

The global environment change (GEC) including climate change has resulted in major shifts of crop growing environments (agroecologies, weather, soil) and thus changes in the suitability of agroecologies for crops especially fruit tree species (cocoa, citrus, oil palm). Climate change has been projected to cause shifts in the present day growing conditions and set new environment boundaries and habitat range for

crops and livestock, and such would crop yields and crop growing area suitability. In particular, increases in temperatures and declining rainfall had led to large parts of sub-Saharan The shifting climate in Sub-Saharan Africa has produced changes in rainfall pattern, temperature, season length and abiotic stress and shifts in suitability of crop growing areas especially for fruit tree species (cacao, oil palm, citrus, coffee etc.) along ecological transect of wet to dry forests. There is however, increasing need to extend production and thus, frontier of fruit tree cultivation to meet rising global demand along other benefits (food security, livelihood, ecosystem services). The new climatic regimes within agroecologies of Saharan Africa (SSA) will affect water resources, agriculture, food and nutrition security, livelihoods and economic growth.

Cacao (*Theobroma cacao*) is an important cash crop in Africa, Central and South America and Asia with an estimated annual production of 4.92 million tons [1]. In these regions, cacao is a major foreign exchange earner, and important as industrial raw material, livelihood, and ecosystem services provision. Based on its global importance, is the need for increased yields and expansion of cultivation to meet rising global demand for cacao beans.

In West Africa, the rainforest belt constitutes the cocoa growing regions where annual rainfall is high (ranging between 1500 and 2000 mm in a bi-modal distribution pattern, and wet-dry season transitions. The dry season is a terminal drought situation for crops especially for plantation (permanent) crops which undergo moderate to severe hydrothermal stresses [2–4].

Rainfall is most important determinant of the success of farming operation within the rainfed farming system where crops are seldom irrigated despite the climate stress of the seasonal wet and dry transitions.

In the West African cocoa producing regions, climate variability and extreme weather events constitute the greatest production constraint to crop productivity [5–7]. Climatic variability has produced significant reductions in cocoa yields and deterioration in bean quality [5, 6]. Agrometeorological studies would contribute to improved understanding of the effects of climate factors on plant environment. The understanding will help to improve farming practices, but also to assess certain risks to the cocoa tree due to irregular rainfall, extreme temperatures and humidity, and low insolation.

In the West Africa, farmers often grow crops in mixed stands (intercropping and agroforestry practices) which subject them to varying intensities of shading. Reports form cacao-based agroforestry system of tropical rainforest belt have shown that over 100 species covering 30 families of shade trees are found in cacao agroforests. Timber and fruit tree species are widely used by farmers to provide shade for transplanted cacao seedlings on the field [8, 9]. The heterogenous shading regime sin cacao agroforests are constituted by shade tree species; timber and fruit trees forming structurally complex closed canopy multi-strata system (under-growths, middle and upper storey species) which retain attributes of natural rainforest ecosystem. The agroforestry system retain the positive attributes of natural forest climax. The co-occurring species crops/trees therefore grow under variable shade intensities (20 to 70% reduction in incoming radiation) and some pockets of unshaded area (full sunlight). Thus, the variable shading scenarios in natural cacao based agroforestry systems of the humid tropics can be constituted by: A: 30:70 timber trees and fruit tree species in mixture - PAR interception ranging from 70 to 20%, B: 50:50 timber trees and fruit tree species in mixture - PAR interception ranging from 70 to 20%, and C: open field (full sun) cacao where light regimes is greater than 70% PAR interception [10].

Shade is known to buffer the effects of stress factors (high irradiance, temperatures and atmospheric deficits (low humidity) of the dry season on tropical perennial *Perspective Chapter: Microclimate, Plant Stress and Extension of Cacao Frontiers to Marginal… DOI: http://dx.doi.org/10.5772/intechopen.113388*

fruit tree species in plantations and lower incidence of shoot/branch die-back and tree mortality [11].

However, despite shade provision for transplanted cacao seedlings, high mortality percentages are recorded between first and second dry season. Such seedling death is attributable to high hydrothermal stresses of the terminal drought condition of the dry season [9].

The high seedling mortality constitutes constraints to establishment of seedlings in cocoa rehabilitation efforts following dry season drought. Other factors including low soil fertility, pests (termites and capsids) and poor access to improved planting materials [12].

The naturally occurring shading regimes and variable light intensities are known to expose cacao to modified microclimate, and altered availability and balance of resource use to crops (enhanced competition). Cacao-based agroforestry system ameliorated weather conditions, improved ecological benefits and ecosystem health, the resultant enhance carbon sequestration will reduce global warming.

Cacao-based agroforestry ecosystem contributes to terrestrial carbon budget via carbon storage in soil and crops, as well as microclimate amelioration, improved ecological benefits and ecosystem health. These services exert feedback on terrestrial climate. Reports indicate that the high potentials of net gains in C sequestration from cacao-based agroforestry system is a promising CO2 mitigation strategy [11].

### **2. The global economic and social impact of cocoa**

The cocoa industry has made enormous contribution to global socio-economies. Global cocoa production and expansion of the chocolate industry had retail value of USD 100 billion in 2021, this is expected to grow further until 2027 [13]. Other reports projected expansion growth of about USD 69.1 billion by 2030 [14, 15]. However, over 79% total annual cocoa bean production is processed into cocoa butter, chocolate, or other products outside the main producing centres especially in the Sub-Saharan Africa for example, Europe followed by Asia and Oceania [13]. Cocoa is vital for Nigeria's economy. More than 70% of cocoa farmers are smallholders with average farm size less than 1.5 ha, yield increases are mostly due to expansion of cocoa land area Cocoa yields are principally affected by soil and climatic variables [10, 16, 17]. There has been declining cocoa export from the mid-1980s to till date.

### **3. Agricultural ecology of the rainforest of Nigeria**

The rainforest zone of Nigeria is characterized by annual rainfall of over 1500 mm distributed in a bimodal pattern of seven to 8 months duration (the growing season), and 3 to 4 months of dry season (typically from late November to march) characterized by low humidity, temperatures over 32°C and clear skies. Rainfall is characterized by unpredictable onset and cessation dates, variable lengths of growing seasons, increasing intensities and duration of terminal drought situations and elevated soil and air temperatures.

Seasonality of sowing implies that crop production is rainfed and linked to seasonally available soil water (rainfed agriculture). The four to 6 months of dry weather results in soil water deficits and high soil and air temperatures [8, 10]. In fruit trees, unfavorable e soil and weather conditions of the short and long dry seasons are known to affect flowering and pod production with negative consequences on bean size. In fruiting trees, water deficits result in lower yields and an increase in the

level of mirid (capsid) damage and tree mortality. Since cacao is seldom irrigated, trees undergo severe water stress during the dry season, leading to branch die-back, and for pod-bearing trees, hydrothermal stresses affect pod filling and bean size. Additionally, the wet-dry seasonal transitions cause seasonal leaf shedding at the onset of dry season and leaflessness until beginning of rain. Under the episodes of drought of the dry season, tree crops including cacao, may be subjected to water stress-induced hydraulic failure and cavitation events in the soil-canopy continuum. Thus, fruit trees would have to adjust water relations and water use and other physiological functions for optimum productivity.

### **4. Climate change and extreme weather events and the changing cocoa production landscapes in West Africa**

The scenarios of climate change especially, temperature and rainfall patterns for West Africa including Nigeria have been variously modeled using process-based methods of the General Circulation Models (GCM) and Simple Climate Models (SCM) [18, 19]. The studies have indicated projected decline in mean annual rainfall by −3.1, −12.1 and −20.2% in year 2020, 2050, and 2080, respectively.

Cocoa is sensitive to changes in climate conditions for example, sunshine hour, temperature, rainfall, soil conditions and their effects on evapotranspiration. Drought affect growth and yield of cocoa, and the pattern of cropping of cocoa is related to rainfall distribution. Under the projected climate change from 2020 to 2080, cocoa yields may decrease significant below its current yield levels.

It is reported that climate change had produced shifts in the geographical distribution of host and pathogen/pests, altered crop yields and crop loses, stages and rates of development of cocoa pests and pathogens while modifications in host resistance and physiology of host-pathogen/pests interaction may change. Extreme climate induces drought and tree mortality events worldwide, and further increases in tree mortality events are predicted under future climate. Tree mortality enhanced by drought is also noticeable even in moist and wet tropical forests [20, 21]. Climate change is expected to exacerbate mortality events in tropical forest species especially the fruit tree species. Within ecosystems, plant species respond to drought and high temperature stresses of the wet-dry season transitions, environmental (climate) changes will affect ecosystem and plant distribution.

Climate projections using Global Climate Models and change scenarios (SSP-RCP2.5, 4.5 and 8.5), have identified important shifts and shrinkage of suitable areas for tropical crops [19, 22]. The change projections have indicated significant areas of West Africa are likely to experience unfavorable climatic conditions by 2050 [19]. Other reports have affirmed the shifting agroecological landscapes for cocoa in Ghana, Cote D'Ivoire [22]. These reports indicate the need for adaptation planning to ensure sustainability of crop production under current and future climate scenarios [23].

The projections of climate scenarios are relevant for assessing vulnerabilities and impacts of climate change on agriculture, also useful for identifying adaptation strategies capable of sustaining crop production under future climates. Such projections have been made using CORDEX RCP 4.5 and 8.5 in some cocoa producing regions of West Africa [24]. Results showed that critical temperatures thresholds (33°C) would be exceeded which will result in decline in cocoa performance.

There has been declines in quantity and quality of land and accelerated nutrient depletion within the cacao growing agroecology of West Africa particularly Nigeria. *Perspective Chapter: Microclimate, Plant Stress and Extension of Cacao Frontiers to Marginal… DOI: http://dx.doi.org/10.5772/intechopen.113388*

The ecological transect of wet/moist to dry forests of the humid tropics is characterized by increasing frequencies and intensities of droughts and dry spells, water resource scarcity, high temperatures, soil and atmospheric aridity, land degradation (soil erosion and fertility depletion), insect pests and disease pressures. The changing climate and agroecological conditions (vegetation and soil) constitute constraints to sustainable cocoa production in the West African rainforest belt.

### **5. Climate and soil requirements for cocoa**

Cocoa is essentially a plant of the tropical rainforest, it grows well within about 20° north and south of the equator. The equatorial environment with high temperatures and heavy rainfall (between 1500 and 3500 mm) and nitrogen-rich soil is best agroecology for cocoa.

Recommended weather conditions for cocoa especially temperatures: maximum temperatures of 30–32°C and 18–21°C and absolute minimum of 10°C. Light use efficiency relates to temperature because temperatures below 24°C is reported to decreasing radiation use efficiencies especially for photosynthesis rate at light saturation [25]. Cocoa plant has low light saturation point (LSP) of 400 μ E m−2 s−1 and low maximum photosynthetic rate (7 mg dm−1 h−1) at light saturation. It is reported that crop photosynthesis rate decreases if the photosynthetic apparatus is exposed to light intensities exceeding 60% of full sunlight (1800 μ mol m−2 s−1), and prolonged exposure to high light intensities damages the photosynthetic apparatus of leaves [25]. Low light intensities however suppress flower and pod production in cocoa. Opeke [8] and Wood and Lass [26] reported that cocoa optimum growth occur under rainfall of 1250–3000 mm per annum (preferably between 1500 and 2000 mm), dry season not longer than 3 months, maximum temperature between 30 and 32°C, minimum of 18–21°C, and no strong winds. Reports from studies under controlled-environment facility (growth chamber) have showed that cocoa performed well under high humidity (80–95% RH) and about 27°C [25].

Cocoa does well on deep soil of loamy sand texture, friable clays, red or reddishbrown in color and soil pH greater than 6.0 [26, 27]. Cocoa can be successfully grown on heavy clay soil, yellow to red overlying a deposit of hydrated iron oxides. Reports from other studies from analyses of soils from the different countries tended to fall into *Alfisols* and *Ultisols* classification [26, 27]. Commonly used terminologies such as "ideal cocoa soils," "ideal cocoa climate" and "marginal cocoa climate" to describe the suitability of agroecologies for its production.

In Nigeria, cocoa cultivation is restricted to south western and eastern parts of the country where the annual rainfall is above 1200 mm. Thus, cocoa production activities are concentrated along rainforest zone of southern Nigeria across in Ondo, Cross River, Ekiti, Osun, Oyo, and Ogun States where the environmental conditions are most suitable. The major cocoa producing areas lie between Latitude 5° 32′ to 7° 47′N and between Longitude 3° 55′ to 8o 42′E (**Figure 1**). The most important varieties of cocoa are *Theobroma cacao* (officially named in 1753 by the Swedish scientist Carl von Linné) and Criollo, Forastero and Trinitario (with numerous hybrids for each strain).

Soils of the south western Nigeria have developed form metamorphic rocks of the basement complex, majority of these soils are of Pre-Cambrian age [27]. The soils are mainly classified as Typic Kanhaplustalf and Typic Haplustalf. The soils of the south eastern Nigeria are derived from basalt under humid tropical forest vegetation and are predominantly classified as Typic Tropohumult (**Figure 2**) [28].

**Figure 1.** *Bimodal rainfall peaks of the rainforest zone of Nigeria: Rainfed and irrigation based cropping opportunities.*

**Figure 2.** *Cocoa producing states in Nigeria.*

### **6. Climate and agro-ecological conditions**

Climate factors play a primary role in determining the ecology of a region [29, 30]. Ecological conditions have profound impacts on the types and scales of agricultural activities [30, 31]. The vegetation zones of Nigeria, are determined by the prevailing climatic conditions, the zones differ in amount and distribution of rainfall, humidity, temperature, atmospheric pressure. The zones are different in annual rainfall and temperature, and predominant species composition (**Figure 3**). These zones have

*Perspective Chapter: Microclimate, Plant Stress and Extension of Cacao Frontiers to Marginal… DOI: http://dx.doi.org/10.5772/intechopen.113388*

**Figure 3.** *Vegetation zones of Nigeria.*

varying annual rainfall, temperature, atmospheric pressure, and predominant vegetation (dominant species).

Agro-Ecological Zonation (FAO-AEZ) identifies the land's suitability for crop farming and helps understanding of impacts of climate change on agriculture. Agroecological zonation has been used as a tool for identifying agricultural activities under current climate conditions and for predicting future area suitability for crops (FAO (1978, FAO/IIASA (2012) classified Africa into Agro-Ecological Zones (AEZs) based on temperature, precipitation, and soil moisture conditions. Agroceological zonation provides clear picture of land potentials of land resources for use through matching of production system requirements with the land characteristics within the agroecology. The most vulnerable crop producing zones to climate change can be delineated using the concept of AEZs [29, 32]. Modeling results have affirmed shifts in the AEZs under different climate change scenarios [33] and analysis of AEZ had established that climate change affects African landscapes and agroecologies. Results of such analyses for West Africa establish that that the moist (humid) and dry savanna are more vulnerable to climate change while the humid forest or sub-humid AEZs will become more productive in the future [33].

Image analysis using spot-vegetation sensors have showed changes in the composition and extent of different vegetation zones across Nigeria. Reports have confirmed the encroachment of the savanna into the forest belt of southern part of the country. The expansion of non-forest areas, fragmentation and shrinkage of forested ecosystems have ecological and socio-economic consequences [22]. Unsustainable anthropogenic

activities such as lumbering, open cast mining, and agriculture have accelerated the degradation of vegetation, soil quality, biodiversity loss, ecosystem services and climate change. The changes in the suitability of agroecologies and crop growing under the present and the future climate using model projections have affirmed differences in suitability ranges from moderate to marginal suitability and the very unsuitable.

### **7. Climate and agroecological suitability for cocoa**

Land suitability classification relates to comparison of requirements of land-use types with properties of land units. Land suitability assessment is a valuable tool for rational soil use planning and sustainable land management.

Agroecological suitability is a measure of the ability of an agroecology to support intended uses (agricultural activities involving production of arable (annual) and permanent (plantation) crops.

Suitability is indicated separately for each land-use type, showing whether the land is suitable or not suitable. Classification of current crop suitability refers to land suitability for a defined use in its present condition, without major improvements. Crop suitability describes appropriateness of an area of land based on the growing threshold of a crop in relation to climatic conditions (minimum and mean monthly temperature and total monthly rainfall) [19, 34]. Crop suitability is also relate to the spatial appropriateness and distribution of land area based on the growing climatic suitability threshold of a crop over time period [35].

Multiple global circulation models (IPSL-CM5A-LR, BCC-CSM 1.1 and MIROC-ESM-CHEM) have been used to simulate changes in crop growing area suitability across the agroecological zones of West Africa future climate change scenarios (RCP 2.6, 4.5, and 8.5) [19, 36]. Areas with increasing and decreasing land suitability were predicted to increase with time, the changes were greater for RCP 4.5 while RCP 8.5 gave the worst prediction indicating higher risk of crop cultivation in the future [36].

Climate departure defines a shift in the climate pattern of a region outside the range of historical variability and such description may be based on local temperature exceeding historical high. Mora et al. [37] described climate departure as the year in which the average temperature of the coldest year after 2005 was warmer than the historic hottest year at a given location. Climate departure manifests as deviation from the historical mean and/or variance of the local climate of an area or region induced by global warming. The authors suggested that West Africa will experience a climate departure based on temperature rise will occur about two decades (2029) earlier than the global mean temperature (2047). The study established the likelihood of changes in large-scale crop and growing area suitability across West African agroecologies.

The concept of crop-climate departure (CCD) is useful for evaluating future changes in crop suitability over historical and future time periods. Crop-climate departure has been used to evaluate future changes in the crop suitability and planting month for crop species in some west African agroecologies [19]. The authors used using Global climate model simulations downscaled by the CORDEX regional climate model (RCA4) to drive the crop suitability model [36]. Results showed a reduction (negative linear correlation) and expansion (positive linear correlation) in area and crop suitability for the guinea and southern sahel zones of West Africa. The study recommended options for short and long-term adaptation and planning for future changes in the crop suitability and planting windows for improving food security and livelihood in West Africa savanna agroecologies.

### *Perspective Chapter: Microclimate, Plant Stress and Extension of Cacao Frontiers to Marginal… DOI: http://dx.doi.org/10.5772/intechopen.113388*

Crop distribution over agroecologies is predicted using species distribution models (SDMs). Species distribution models are built on genetic algorithm for setting rule for production (GARP) and CLIMEX, and maximum -entropy (MaxEnt) [38–40]. Among the species distribution models, MaxEnt is the most widely used model in recent years [41, 42]. Predictions of impacts of climate (current and future scenarios) on area (agroecology) suitability for crops using Global Circulation Models and adapted MAXENT model. MaxEnt has shown outstanding predictive performance compare with other modeling methods [43, 44]. The simulation of present and potential area suitability or crops in agroecologies and under future climate (2030s, 2050s and 2080s) using MaxEnt model has indicated variabilities in current regional and global agricultural crop area suitability from medium to high suitability in addition to potential undeveloped suitable areas [36]. The predictions also affirmed shifts in the current distribution of crop growing area especially under future climates (2050 and beyond). Especially for West Africa, the studies showed that some current agroecologies of West Africa will be suitable for crops while some others will become unsuitable.

In the rainforest of West Africa, (the cocoa growing belt of the region), predictions have affirmed that yearly and monthly rainfall will decrease slightly by 2050 (aside the coastal areas) and yearly in addition to increases in monthly minimum and maximum temperatures by 2030 with continue increases up till 2050 [19, 36]. In general, West African climate will become less seasonal due to within the year variations, increases in temperature in specific districts by about 1.2°C by 2030 and 2.1°C by 2050 and less seasonal precipitation with decreases in number of dry months (from 4 to 3 months). This trend may imply changes in the suitability and distribution of growing areas within the current cocoa-growing areas in some parts of West Africa (Ghana, Côte d'Ivoire and Nigeria) by 2050 due to temperature increases.

The changing landscapes (agroecologies) and may require changes in agricultural practices as adaptation to new environmental conditions that will prevail while the climatic suitability for growing crops in some parts of West Africa rainforest belt. The development of site-specific adaptation strategies will reduce the vulnerability of smallholder farmers to climate change challenges. The imports of progressive changes in climate and the suitability of crop growing area in particular, with the current areas becoming unsuitable for certain crops may require farmers to shift to alternative crops.

The suitability or otherwise of cocoa growing areas in the rainforest of Nigeria under present and the two future climate models (HadGEM2 and CNRM-CM5 under RCP 4.5 and 8.5) is presented in **Figure 4**. The results showed that compare with present day climate and growing area for cocoa, the unsuitable areas will increase under both scenario predictions and higher magnitude of change for CNRM-CM5 RCP 4.5 and 8.5. greater decline in area suitability is projected for RCP 4.5 for both HadGEM2 and CNRM-CM5.

### **8. Climate change and distribution range for species**

Climate change acts as a major cause of species extinction by impacting the distribution and abundance of species. Species may either keep their current range or respond to changing environmental conditions with range expansions, contractions or shifts [45, 46], which may ultimately contribute towards shrinkage in the forest cover and crucial biodiversity loss [47]. The non-significant changes in habitat suitability for species under climate change scenarios may indicate higher climate resilience. Climate warming can provoke species attrition (changes in species richness) in various ecologies, this may cause increases in colonization of new suitable

### *Shifting Frontiers of* Theobroma cacao *– Opportunities and Challenges for Production*

### **Figure 4.**

*Fruit tree species (including cacao) land areas of the rainforest zone of Nigeria under the present and future climate models.*

areas (expansion range for species) or retractions from unsuitable sites with harsher environmental conditions. Such phenomenon may lead to local and even global species extinction events [46, 48].

### **9. Environmental factors driving crop growing area suitability**

Environmental factors (weather and soil) drive changes in area suitability for crops in agroecologies (AZEs). Climate suitability relates to levels of climate variables which determine growing areas having the potential for successful cultivation and growth of certain crop (s) [45, 46]. Such bioclimatic variables include monthly temperature and rainfall, seasonality (annual range in temperature and precipitation) and extreme or limiting weather factors such as temperature of the warmest month, and rainfall of the wettest and driest months useful for generate biologically meaningful indicators for ecological niche modeling.

Temperature increases had been reported as a major driver of shifts in area suitability for crops under current and future climate. Reports identified temperature of the warmest month as the main driving factor. Temperature explains about 30% of the negative change in area suitability (under 2.4°C increases in temperature of the warmest month by 2050). Temperature seasonality has been identified as the main driving factor for negative change in suitability. The contribution of different bioclimatic variables to changes in crop growing area suitability between current and future climate scenarios, had shown decreasing and increasing trends for crop suitability in agroecologies.

### **10. Changes in global climate**

Global warming denotes the unusually rapid increase *in* Earth's average surface temperature over the *past* century primarily due to the greenhouse [49]. Over both the last 140 years and 100 years, estimates have shown that global average surface temperature has increased by 0.6 ± 0.2°C that is by approximately 0.5–1.0°F (0.3–0.6*°*C) over the last century [50]. Trends in global average surface temperature between 1993 and 2022 in degrees Fahrenheit per decade confirmed that most of the planet is warming (**Figure 4**). Only a few locations, mostly in

*Perspective Chapter: Microclimate, Plant Stress and Extension of Cacao Frontiers to Marginal… DOI: http://dx.doi.org/10.5772/intechopen.113388*

### **Figure 5.**

*Global average surface temperature: https://www.climate.gov/media/15022. The average yearly surface temperatures from 1880 to 2022. The cooler-than-average years are depicted in blue bars and warmer-thanaverage years are shown in red bars. (Source: NOAA Climate.gov graph, based on data from the National Centers for environmental information).*

Southern Hemisphere and oceans have cooled over this time period [51]. Trends of increased warming since 1981, has been twice as fast at 0.32°F (0.18°C) per decade [52]. The earth's temperature has risen by an average of 0.14° Fahrenheit (0.08°C) per decade since 1880, or about 2°F in total. The 10 warmest years in the historical record have all occurred since 2010. Over the twentieth-century average of 13.9 and 1.06°C warmer than the pre-industrial period (1880–1900), the year 2022 had warmer surface temperature (0.86°C/1.55°F) (**Figure 4**). Each month of 2022 ranked among the ten warmest for that month (Global Climate Report from NOAA National Centres for Environmental Information, [51]). The "coolest" month was November, which was 1.35°F (0.75°C) warmer than global average (**Figure 5**).

### **11. The changing climate: the case of Africa**

Based on the reports of [50] and Zougmoré et al. [53], over the coming decades, warming from climate change is expected across almost all the Earth's surface while global mean rainfall will increase. In particular, climate change constitutes increasingly serious threat for Africa, a region that has been described as among the most vulnerable continents to the challenges of climate change. Africa is warming faster than the rest of the world on average, records showed that surface temperatures have generally increased over Africa since the late nineteenth century to the early twenty first century by about 1°C, (**Figures 6** and **7**). Based on climate projections, many African countries and regions, this will severely compromise agricultural production and food security [50, 54]. Omotosho et al. [55] reported that in West Africa, seasonal cycle of rainfall is driven by the south-north movement of the Inter-Tropical Convergence Zone (ITCZ). The ITCZ is characterized by the confluence between moist south-westerly monsoon winds and the dry north-easterly.

### **Figure 6.**

*Variations of the Earth's surface temperature over the last 140 years and the last millennium. Based on records of changes in precipitations (A) and temperature (B) in Africa from 1920 to 2000. (The international research Institute for Climate and Society, Columbia University, Ne. (after [53]).*

### **12. Rainfall and temperature anomalies of the rainforest zone of Nigeria (1980–2020)**

The time series (year: 1980–2020) of a normalized annual departure of rainfall and temperatures standardized mean rainfall anomaly, δ) for the rainforest agroecological zone of Nigeria. moderate fluctuation in temperature and rainfall are represented by anomaly values of +5 while -5δ denote drought years, and above +0.5 as likelihood of flood events (**Figure 7a**). The normalized annual departure of

### **Figure 7.**

*Changes in global and sub-Saharan Africa (1900 to 2020). a. Rainfall anomaly trends (1980–2020) for rainforest zone of Nigeria. b. Maximum temperature anomaly trends (1980–2020). c. Minimum temperature anomaly trends (1980–2020).*

*Perspective Chapter: Microclimate, Plant Stress and Extension of Cacao Frontiers to Marginal… DOI: http://dx.doi.org/10.5772/intechopen.113388*

temperatures (maximum and minimum temperatures) is illustrated in **Figures 7** and **7b**. The results confirmed elevated temperatures characterized by high maxima and minima values which mean high probability of exceeding crop-specific high temperature thresholds. Temperature warming may elicit adjustment of plant physiological functions and water use. Such plasticity is important to acclimation to environmental stresses especially in plant species useful in the revegetation of degraded urban lands. The observed trends confirm changes in climate over Nigeria (for rainfall, maximum and minimum temperatures) for years 1980–2020).

### **13. Environmental factors driving growing area suitability**

Bioclimatic variables are derivable from WorldClim database, from monthly temperature and rainfall values. These Bioclimatic variables are biologically relevant and are often used in ecological niche modeling. Environmental factors (weather and soil) driving change in area suitability for cocoa in the West Africa rainforest belt are exemplified by changes in mean annual temperature and rainfall), seasonality (annual range in temperature and precipitation) and extreme or limiting weather such as temperature of the warmest month, and rainfall of the wettest and driest months. The contribution of bioclimatic variables to the predicted shift in growing area suitability for cocoa between current and 2050 climate scenarios had showed decreasing suitability of weather, soil and vegetation (agroecologies) for cocoa in the tropical rainforest belts of West Africa. Temperature increases had been reported as a major driver of shifts in area suitability for crops especially the changes in suitability between current and future climate especially, the temperature of the warmest month as the main driving factor (it explains about 30% for negative change in area suitability [24]. Climate change will also increase the pressure on forest areas and on other important habitats for fauna and flora [24].

Projections for future climate change suggest a warmer and drier climate in the West African rainforest belt. Information and knowledge improvements with respect to effects of these changes on cocoa production and area suitability in the West African rainforest biome. Simulations using models for the suitability of cocoa's geographical distribution using ensemble of correlative models and projections of two future climate scenarios (RCPs 4.5 and 8.5) by 2050 had been conducted. The models generated information on climate and soil suitability for cocoa. The current and future suitability model had indicated how cocoa production may respond to climate change, and had suggested that reduction in precipitation and increases in temperature may result in reduction in the suitability of the West African rainforest belt cocoa production. The areas suitable for cocoa plantation will decrease by about 37.05 and 73.15% (area suitability for intensification and expansion) under RCP 4.5 and 8.5, respectively, compared with the current climate. Model results also suggest that reduction in precipitation and increase in temperature which may produce a reduction in agroecological suitability for cocoa production in the West African rainforest*.*

### **14. Conclusions**

Global environment change including climate change has produced marginal environments (agroecologies, weather, soil) and thus major shifts in the suitability of agroecologies for crop production. Thus, climate change has created new environmental boundaries occasioned by changes in rainfall patterns and temperature

regimes, seasonal shifts and habitat range for crops. Such changes are expected to affect the area suitable for agriculture, crop species are bound to grow in areas where they were not previously grown and areas that were hitherto not suitable for their production. Climate change may bring about decreases in area suitability for agriculture, and decreases in length of growing seasons and crop yield potentials.

The changing environment conditions are projected to limit cocoa production while the expansion of its production has placed increasing pressure on forest resources in particular along the ecological transect of wet to dry forests. Increase in mean annual temperature up to 2°C will cause considerable decrease in suitability of the rainforest belt of West Africa for cocoa production.

Results of agroecological zoning quantification, show a promise for the extension of suitable areas for the intensification and expansion of cocoa cultivation under future climate. However there will remain, some tracts of land with high levels of soil and climate suitability in the rainforest for cocoa production. Although, tropical crop species are naturally adapted to warmer climates and are developing increasing resilience to climate-related stresses.

Increases in temperatures and declines in rainfall will lead to large parts of sub-Saharan Africa becoming unsuitable for crops. This situation may necessitate a transition to more heat and drought resistant crops to ensure food and nutrition security in the sub-region. The new climatic regimes set by global climate change will affect water resources, agriculture, food and nutrition security, livelihoods and economic growth. In future climates, 2050 and beyond, high percentage loss in the suitability of the West African rainforest for crop production is envisaged. There is however, increasing need to extend production and thus, frontier of fruit tree cultivation to meet rising global demand along other benefits (food security, livelihood, ecosystem services). Sustainable management practices would be required for enhanced productivity and climate mitigation in the era of shifting cacao agroecology and landscapes.

### **Author details**

Samuel Ohikhena Agele1 \*, Olufemi Samuel Ibiremo2 and Oladitan Titilayo3

1 Plant Physiology and Ecology Group, Department of Crop, Soil and Pest Management, Federal University of Technology, Akure, Nigeria

2 Cocoa Research Institute of Nigeria (CRIN), Ibadan, Nigeria

3 Department of Crop, Soil and Pest Management, Olusegun Agagu University of Science and Technology, Okiti Pupa, Nigeria

\*Address all correspondence to: ohiagele@yahoo.com

© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Perspective Chapter: Microclimate, Plant Stress and Extension of Cacao Frontiers to Marginal… DOI: http://dx.doi.org/10.5772/intechopen.113388*

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### **Chapter 2**

## Potential Impact of Stratospheric Aerosol Geoengineering on Cocoa Suitability in Nigeria

*Temitope S. Egbebiyi, Christopher Lennard, Pinto Izidine, Romaric C. Odoulami, Piotr Wiolski and Akintunde I. Makinde*

### **Abstract**

Cocoa is an important cash crop that contributes to the economy of Nigeria *via* job creation and foreign exchange earnings. However, escalating global warming trends threatens Cocoa cultivation and have resulted in a decline and heightened variability in Cocoa production in Nigeria, with potential for further exacerbation in the future. A potential way to reduce the warming is through climate intervention (CI) techniques, including Stratospheric Aerosol Injection (SAI), which involves the injection of sulphur into the stratosphere to reflect a small percentage of incoming solar radiation and lower earth's temperature. To gauge GHG and SAI impact on Cocoa suitability in Nigeria, we used Geoengineering Large Ensemble Simulations (GLENS) dataset as input into Ecocrop model for historical (2011–2030) and future periods (2070–2089). Our results show GHG impact will increase mean and minimum temperatures (up to 3°C) and total monthly rainfall (up to 15 mm) by the end of century in the southwest and north-east area of Nigeria while rainfall decrease of similar magnitude in the other parts of the country. With SAI intervention, rainfall may decrease by about 10–20 mm over the country and reduce mean and minimum temperature by 2°C. Suitable land for Cocoa cultivation in Nigeria may decrease by 24 and 18% under GHG and SAI, respectively, while unsuitable may increase by 14 and 24% by the end of century. Our study has implications for the economies based on Cocoa production in Nigeria.

**Keywords:** cacao, Nigeria, Ecocrop, crop suitability, stratospheric aerosol injection

### **1. Introduction**

Cocoa (*Theobroma cacao*) holds immense economic significance in Nigeria, contributing significantly to the social and economic well-being of the country. With a history spanning centuries, Cocoa has played a pivotal role in shaping Nigeria's economy and fostering rural livelihoods before the discovery of crude oil [1, 2]. Nigeria has achieved significant milestones in Cocoa production, ranked as one of the top four Cocoa-producing nations globally [2, 3], with Cocoa production largely concentrated in the southern regions of the country [1]. The crop has become a

cornerstone of Nigeria's agricultural sector, providing a livelihood for millions of smallholder farmers and supporting numerous downstream industries, such as Cocoa processing and chocolate production [4–6]. The foreign exchange earnings from Cocoa exports have also significantly contributed to Nigeria's overall revenue and balanced trade [1]. The Cocoa industry's growth and achievements have made it an essential component of Nigeria's socio-economic fabric. Moreover, its Pan-Africa significance as a tropical African plant cultivated for its oil and bold foliage places indispensable economic and livelihood significance on Cocoa amongst the people engaged in its cultivation [7–10]. However, climate change poses a severe threat to Cocoa cultivation, impacting its suitability and potentially hampering Cocoadependent economies.

The potential impact of climate change or global warming on Cocoa production and suitability in Nigeria is a pressing concern that has garnered extensive research attention. A number of studies (e.g., [11]) have underscored the alarming implications of rising temperatures and changing weather patterns on Cocoa yields. Global warming's adverse effects on Nigeria's Cocoa industry are evident, as projected decreases in Cocoa yield pose substantial economic risks for Cocoa farmers [12, 13]. Furthermore, Nwachukwu et al. [14] emphasise the vulnerability of Cocoa productivity to climate change-induced shifts in temperature and rainfall. These changes, combined with limited adaptation measures, could potentially exacerbate the negative effects on Cocoa suitability. Agbongiarhuoyi et al. [7] delve into the perceived effects of climate change, highlighting the concerns of Cocoa farmers about the impact on various aspects of Cocoa cultivation. In light of these findings, adaptation strategies become paramount. Jamal et al. [15] stress the importance of climate adaptation efforts, particularly for small-scale farmers who are disproportionately affected. These studies collectively underscore the significant potential impact of climate change on Cocoa production and suitability in Nigeria, urging the implementation of effective strategies to mitigate its adverse effects.

Solar Radiation Management (SRM) has been identified as a potential technique for climate mitigation efforts [16–18] aimed at reducing CO2 emissions to limit the increasing global temperature. One of the SRM prominent approaches is the Stratospheric Aerosol Injection (SAI) which involves the release of gaseous aerosol precursors such as sulphur dioxide (SO2) into the stratosphere to form aerosols that reflect into space a small amount of incoming solar radiation with the aim to reduce temperature at the earth's surface [18, 19]. Although this strategy may decrease global temperature, studies have revealed that it could have a negative impact on rainfall notably in most parts of Africa [20–24]. For example, findings have shown that the impact of SRM will help increase crop yield via the reduction in temperature and heat stress, whilst its resultant effects in rainfall deficit may lead to a reduction in suitable areas for crop cultivation and yield in other regions [16, 20]. Xia et al. [20] also revealed that SRM poses a threat to food security notably in areas like Nigeria, where agricultural productivity is dependent on monsoon rainfall [20, 25]. However, despite this research, there is still a dearth of information on how the SAG will affect Cocoa suitability and yield in Nigeria and the present study is in that direction.

This chapter explores the potential impact of SAI to counteract the adverse effects of climate change on Cocoa cultivation suitability in Nigeria. Section 2 describes the data and methodology on the paper, the results are presented and discussed in Sections 3 and 4, respectively, whilst the summary and conclusions are in Section 5.

*Potential Impact of Stratospheric Aerosol Geoengineering on Cocoa Suitability in Nigeria DOI: http://dx.doi.org/10.5772/intechopen.113773*

### **2. Data and methods**

### **2.1 Study domain**

Our study domain for this research is Nigeria, the most populous African nation and one of the four largest producers of Cocoa in the world (**Figure 1**). It has rainfed agriculture as its mainstay economy and means of livelihood. We define Nigeria domain from latitude 4–14o N and longitude 2.4–15°E with agroecological zones of Nigeria designated as Guinea, savanna and Sahel zones (**Figure 1**). The region is characterized by a strong north-to-south temperature and precipitation gradient [26] and the West African Monsoon Systems (WAMs) are the main rainfall-producing system in Nigeria [27]. The Nigeria climate is in the humid southern area, with rainfall amount up to 3000 mm/year and semi-arid in the north with rainfall amounting to about 450 mm/year [26]. The south experiences a bimodal rainfall regime between March–July and September–November whilst the Northern region experiences unimodal rainfall regime from May–October and agricultural production is highly dependent on rainfall [26]. Different crops are cultivated in different parts of Nigeria and contribute significantly to the economy of the country [26, 28]. Major crops grown in Nigeria include Maize, Yam, Cowpea, Cassava, Rice, Groundnut, Cocoa, Oil palm [29]. Cocoa is reported to be the most important cash crop in West Africa, particularly due to its substantial contribution to the country's GDP via export and foreign earnings [1, 30]. Hence, the need for this present study is to provide information on how climate geoengineering will affect Cocoa cultivation and suitability in Nigeria.

### **2.2 Data**

### *2.2.1 GLENS datasets*

For the study, we analysed the National Centre for Atmospheric Research Community Earth System Model (CESM1) simulation for the Stratospheric Aerosol Geoengineering Large Ensemble Project (GLENS) dataset [31]. The GLENS experiment uses the Whole Atmosphere Community Climate Model (WACCM) as its atmospheric component (WACCM; [32]) with a horizontal resolution of 0.9° latitude × 1.25° longitude and 70 vertical levels from the surface up to 140 km [31]. The experiment includes a multi-member ensemble simulation of future climate and we used two GLENS experiments, the control and the feedback, both experiments were forced with

### **Figure 1.**

*Map of Nigeria showing (a)agroecological zones designated as Guinea, savanna and Sahel zones and Cocoa producing states in Nigeria (source: [1]).*

high-end future greenhouse gas scenario (RCP8.5). However, for the feedback experiment, sulphur dioxide (SO2) was injected into the stratosphere simultaneously at four different locations, along longitude 180°E and latitudes 15°S, 15°N at 25 km and 30°S and 30°N at 22.8 km over a grid point and between 5 and 7 km above the tropopause to keep near-surface global temperature at the 2020 value under the RCP8.5 emissions scenario [19, 31]. The control experiment has two datasets: the baseline (2010–2030) and the RCP8.5 simulation dataset (2010–2097), whilst the feedback experiment period is from 2010 to 2097. The control experiment baseline datasets and feedback datasets have 20 ensemble members with simulation over the period 2010–2030 and three members extended to the end of century, 2010–2097. Hence, for consistency, we used simulations from the three ensemble members that extend to the end of century.

We analysed 20-year periods in each simulation dataset. Firstly, for the control baseline simulation dataset (hereafter Hist), we used 2011–2030 period to understand the spatial distribution and characteristics of Cocoa suitability distribution during the present-day climate. This period was chosen based on the previous findings by Tilmes et al. [31] and Simpson et al. [24] which defined this timeframe as a target for SAI to keep the surface temperature at 2020 levels under RCP8.5 scenario until the end of century. The control RCP8.5 simulation (hereafter, GHG) dataset was used to evaluate the spatial characteristics of Cocoa suitability under RCP8.5 scenario for the period 2070–2089, whilst the feedback simulation dataset (hereafter, SAI) was used to understand the spatial characteristics of Cocoa suitability over West Africa under RCP8.5 scenario with SAI interventions for the period 2070–2089. We also evaluate the global model capability to represent the current period by comparing the control baseline simulation to CRU-WFDEI suitability output. We quantify the impact of climate change on Cocoa suitability under RCP8.5 scenario by GHG minus HIST. Meanwhile the SAI minus HIST shows the impact of RCP8.5 and SAI on future crop suitability over West Africa and SAI minus GHG shows the SAI intervention of future suitability of Cocoa in the regions. As with previous studies e.g., [22, 23, 33], we used monthly datasets of mean and minimum monthly temperatures and total monthly rainfall.

### **2.3 Methods**

### *2.3.1 Bias correction*

All the GLENS datasets were bias corrected using the Climate Research Unit (CRU) observation-based reference dataset at a horizontal resolution of 0.5<sup>o</sup> for the period 1980–2009 [34]. A standard quantile-quantile bias-correction approach was employed to correct the two climate variables, temperature (minimum and mean) and rainfall required for our study period 2011–2030 for the historical/baseline period and 2070–2089 for RCP8.5 and SAI simulations [35]. The resultant bias corrected variables were used as input into Ecocrop model for our crop suitability experiments over Nigeria. This step is highly important because climate model simulation often deviates from the observed climatological data. Hence, the need for bias correction before the data is used for climate change impact assessments, such as hydrological modelling and agricultural impact studies [36].

### *2.3.2 Crop suitability modelling using Ecocrop*

The impact of SAI on Cocoa suitability in Nigeria was investigated using the Ecocrop suitability model. Crop suitability was calculated as described in

### *Potential Impact of Stratospheric Aerosol Geoengineering on Cocoa Suitability in Nigeria DOI: http://dx.doi.org/10.5772/intechopen.113773*

Ramirez-Villegas et al. [37] based on the crop growth suitability threshold from Food and Agriculture Organisation, FAO-Ecocrop database (**Table 1**) [37, 38]. The model evaluates the relative suitability of crops in response to a range of climates including rainfall, temperature, and the growing season for optimal crop growth and operates at a monthly scale with the capacity to analyse crop suitability across different geographical location [37, 39, 40]. Ecocrop works based on the environmental ranges of a crop coupled with numerical assessment of the environmental condition to determine the potential suitable climatic condition for a crop. The suitability rating can be linked to the agricultural yield which is partly dependent on the strength of the climate signal [37, 41]. We used Ecocrop to produce a monthly suitability index for Cocoa and demonstrate the impact of SAI on its suitability in Nigeria. Crop suitability thresholds are based on a FAO-hosted dataset which acts as a baseline from which to quantify departures in each scenario, under future climate simulation with natural forcing (GHG) and SAI at RCP8.5 using the GLENS ensemble simulation datasets.

### *2.3.3 Sensitivity to climatic variables, rainfall and temperature*

We also independently test the influence of fluctuations and trends in rainfall and temperature on Cocoa suitability. For example, to test the influence of rainfall, we use total monthly rainfall values over the study period for both the historical (2011–2030) and future periods (2070–2089) but keep temperature constant. The constant temperature is from the long-term mean monthly temperature so that the monthly temperature (both minimum and mean temperatures) for January to December each year over the study period with or without SAI is the same. This experiment is called "rain-vary". To test the influence of temperature, a similar approach was used, with the exception that total monthly precipitation values were held constant over the study period, whilst monthly temperatures, both minimum and average, varied from year to year. This experiment is called "temp-vary". When all the three variables (rainfall, mean and minimum temperature) vary simultaneously, the experiment is called "all-vary".

### *2.3.4 Statistical analysis*

The robustness of the projected impact of GHG and SAI on Cocoa suitability and planting season crops over Nigeria was assessed based on the condition that all three simulations agree on the sign of change. Previous studies [23, 39, 40, 42–45] have all used the methods to test and indicate the robustness of climate change signals. We also examined the fractional percentage of suitability for the three experiments over Nigeria by aggregating the different suitability index value at each grid point for the study period.


### **Table 1.**

*Cacao growth threshold as generated by the FAO-Ecocrop model.*

### **3. Results and discussion**

### **3.1 Impact of global warming and SAI on mean climate variables in Nigeria**

**Figure 2** shows the spatial distribution of the total monthly rainfall and temperature variables, minimum and mean temperatures over Nigeria. For example, CESM1 model shows rainfall gradient from south to north in rainfall distribution, as rainfall amount decreases as you move northward over Nigeria. Our simulation shows that the south coast in the Guinea zone of Nigeria receives the highest total monthly rainfall amount, 240 mm/year, whilst the lowest total monthly rainfall amount, 80 mm/year, is to the north. For temperature, our result shows the spatial distribution of both mean and minimum temperatures over Nigeria with about 20°C and 25°C, respectively. The impact of climate change, GHG (RCP8.5) relative to baseline period (2011–2030) varies for both rainfall and temperature in Nigeria (**Figure 2**, column 2). Whilst GHG shows a similar pattern of projected increase in mean and minimum temperature over Nigeria, there is a variation in the projected change in rainfall over the region. For example, an increase of 1°C minimum temperature is expected over the country except in Abuja, the north-central part, where a decrease of temperature of 1°C is projected. In contrast, a projected increase up to 2–3°C warming in mean temperature is expected over the country due to GHG. The projected increase in mean temperature is expected to be about 3°C around the south-east and northern Sahel, whilst a 2°C is expected in other parts of the country. For rainfall, with reference to the historical period, a projected increase in total monthly rainfall up to 25 mm (about 1.25 mm/month) by the end of century relative to the historical over the south-western part of Nigeria and up to 10 mm (0.5 mm/month) and 5 mm (0.25 mm/month) in the north-east and northwest Sahel zone of the country, were observed, respectively. On the other hand, GHG may lead to decrease in 10–15 mm in the south-east and central part of the country. These findings are in line with Pinto et al. [22] and Abiodun et al. [23].

The deployment of SAI shows a reverse pattern in total monthly rainfall and temperature variables in comparison to the baseline period and impact of RCP8.5 GHG over Nigeria (**Figure 2**, column 4). For example, the impact of SAI technique relative to historical period may lead to a decrease of about 1–2°C over Nigeria as it induces a cooling due to reduction in mean and minimum temperature. This implies that the deployment of SAI showed a reduction in climate warming over Nigeria and in total monthly rainfall up to about 5–25 mm relative to baseline period (2011–2030) across the country except the south-west zone of the country with higher magnitude up to 35 mm. Furthermore, we examined the impact of SAI deployment on rainfall and temperature relative to GHG. Our findings show that SAI deployment will lead to a decrease in mean and minimum temperature variables up to 3°C from the impact of GHG thus inducing further cooling over the country [46]. In addition, the projected impact of SAI deployment in comparison to GHG-induced impact shows a reduction in the magnitude of decrease in total monthly rainfall in the south-east zone of the country whilst it induces further drying in the south-west and north-east region of Nigeria.

### **3.2 Evaluation Cocoa suitability in the historical period**

Cocoa suitability varies over Nigeria for the historical period (**Figure 3**, column 1). In general, there is a decreasing suitability gradient from south to north of Cocoa over Nigeria. As a result, Cocoa suitability decreases northward and notably unsuitable in the northern part of Nigeria although with variation in spatial extent. *Potential Impact of Stratospheric Aerosol Geoengineering on Cocoa Suitability in Nigeria DOI: http://dx.doi.org/10.5772/intechopen.113773*

### **Figure 2.**

*The spatial distribution of climate variables (total monthly precipitation, mean and minimum monthly temperature) in the present-day climate over southern Africa (first column; 1980–2009) and their projected future changes in the period (2065–2090) under the RCP8.5 scenario without and with SAI (i.e., second and third columns, respectively). The extent to which the SAI influences the impacts of global warming on the variables is presented in the fourth column. The cross sign (+) indicates where at least 75% of the simulations agree on the sign of the changes.*

Ecocrop spatial suitability characteristics simulation depicts that a large area to the north of 10o N is unsuitable with Suitability Index Value (SIV) below 0.20 (0–0.20) for Cocoa in Nigeria, notably in Sahel zone in the northern part of Nigeria. However, our result shows that higher suitability (SIV ≥ 0.5) of Cocoa is observed to the south of 10 N, notably in the Guinea agroecological zone. In general, the observed data, CRU-WFDEI shows a good agreement with CESM1-WACCM dataset in the spatial suitability distribution of Cocoa over Nigeria (**Figure 3**). The model captures well main Cocoa producing areas in Nigeria, notably the south-west zone (with SIV above

### **Figure 3.**

*The spatial distribution of Cocoa suitability for the historical period over Nigeria (first column; 2011–2030) and their projected future changes in the period (2070–2089) under the RCP8.5 scenario without and with SAI (i.e., second and third columns, respectively). The impact of SAI-induced effect on global warming on Cocoa suitability is presented in the fourth column. The cross sign (+) indicates where all ensemble members agree on the sign of projected changes.*

0.6) which contributes about 80% of its production. The output shows that there is a strong spatial correlation (r = 1) between CRU-WFDEI and CESM1-WACCM data for Cocoa. Our findings are consistent with the results of Afolayan [1] on the spatial suitability distribution of Cocoa over Nigeria.

### **3.3 Projected changes in Cocoa suitability in Nigeria**

The impact of climate change (GHG) and SAI on Cocoa suitability shows a similar spatial pattern but with varied magnitude across the agroecological zones of Nigeria (**Figure 3**, column 2). GHG as projected may lead to an increase (up to 0.20) in suitability index of Cocoa along the south-west boundary of Oyo and Ogun state and about 0.1 along eastern savanna in Nigeria. On other hand, the projected impact of GHG over Nigeria may lead to a decrease (about 0.2) in Cocoa suitability in the Guinea-savanna zone (lat. 7–9o N). However, no change in Cocoa suitability is expected in the south coast of Nigeria in the Guinea zone, which means the area remains suitable for Cocoa as observed in the historical period. Similar characteristic is also observed in the northern Sahel zone north of 12o N, as the area remains unsuitable as observed in the historical period. These findings are consistent with previous studies e.g., [12, 14, 47] that reduction in rainfall and increases in temperature will affect the suitability and cultivation of Cocoa in Nigeria. Our result also agrees with Schroth et al. [30] that Guinea-savanna zone will be the most affected Cocoa cultivated area in Nigeria under GHG. Thus, reduction in suitable areas may lead to reduction in Cocoa yield and production over Nigeria [14, 48].

The impact of SAI on Cocoa suitability relative to the baseline period (2011–2030) shows a similar spatial suitability pattern as that of GHG but with a variation in the Guinea-savanna zone (**Figure 4**, column 4). With SAI, no change in Cocoa suitability is detected in the Guinea and Sahel zone of Nigeria, suggesting SAI preserves the spatial distribution of current Cocoa cultivation suitability in the future here. On the other hand, a decrease (up to 0.3) in Cocoa suitability is expected over Guineasavanna zone of Nigeria with SAI, and the magnitude of the projected decrease in Cocoa suitability is expected to be higher with SAI deployment in comparison to GHG-induced impact. In addition, SAI intervention is projected to result in decrease in suitability index value (about 0.35) of Cocoa in most parts of Nigeria. No projected change is expected in southern and north-eastern part of the country, this signifies that the southern zone remains a key region for the cultivation of Cocoa with SAI deployment over the country. However, the north-east in the Sahel zone remains unsuitable for growing Cocoa as observed in the historical period. The general projected decrease in the suitability under SAI may be linked to the projected reduction in rainfall over Nigeria.

### **3.4 Impact of global warming and SAI on planting season in Nigeria**

Our study also examines the best planting months (PM) within the Growing Season (GS) over Nigeria (**Figure 4**). The simulated planting month represents the best month of the planting window and varies across the three Agroecological zones of Nigeria. For the historical climate, Ecocrop simulation shows a variation in the planting windows for Cocoa over Nigeria (**Figure 4**, column 1). Ecocrop shows January as the best PM for Cocoa in Guinea zone south of 7o N and north of 12o N in the Sahel zone, both areas are notable for their suitability in the south and unsuitability in the north, respectively, for the cultivation of Cocoa in Nigeria. Also, March–May

*Potential Impact of Stratospheric Aerosol Geoengineering on Cocoa Suitability in Nigeria DOI: http://dx.doi.org/10.5772/intechopen.113773*

**Figure 4.**

*The spatial distribution of planting season of Cocoa for the historical period over Nigeria (first column; 2011–2030) and their projected future changes in the period (2070–2089) under the RCP8.5 scenario without and with SAI (i.e., second and third columns, respectively). The impact of SAI-induced effect on global warming on Cocoa's planting season is presented in the fourth column. The cross sign (+) indicates where all ensemble members agree on the sign of projected changes.*

is the best planting month over the south-west Guinea-savanna zones (lat. 7–10o N), notably in the major producing areas in the southern part of Nigeria. In addition, the months of October–November were observed as the most suitable period in the central extending to south-east savanna zones of the area. The simulated planting months are consistent with the past findings of Afolayan [1] that the months of March–May are the best planting months for Cocoa in Nigeria, notably in the southern part of Nigeria.

The impact of GHG and SAI on Cocoa planting season relative to the historical period shows similar spatial patterns across the different agroecological zones of Nigeria but with variation in magnitude (**Figure 5**, column 2). The impact of GHG may lead to a delayed planting season in the Guinea zone and an area in the Sahel zone of Nigeria although at different magnitude. For example, Cocoa planting season may be delayed by 2 months in south coast of Nigeria in the Guinea zone (south of 7o N) and south-east savanna around lat. 10o N whilst a month delay may be expected from the north-west Sahel zone extending to the central (about 11o N) savanna zone. Hence, GHG warming indicates a shift in Cocoa planting months to March over the Guinea zone and south-east savanna zone and February in the north-west Sahel zone and south-east savanna zone in comparison to the historical period. In contrast, a projected early planting may be expected over the Guinea-savanna zones (7–11o N) for Cocoa in Nigeria except along the south-west boundary between Ogun and Oyo state with one mouth delay. The projected early planting imply that June-July may be the best planting season in the Guinea-savanna zones and March along south-west boundary between Ogun and Oyo state of Nigeria. However, no change in planting season is expected in the north-east Sahel zone of Nigeria, hence, January remains the best planting month over the area. The impact of SAI on the plantings shows similar spatial pattern or characteristics as that of GHG effect relative to the historical period but at a higher magnitude. The projected delay and early planting in the Guinea-savanna and savanna-Sahel zones, respectively, may be up to 3 months under SAI relative to the historical period.

The impacts of SAI intervention (i.e., SAI-GHG) on planting season show a similar spatial characteristic as its impact relative to the historical period but with variation in magnitude (**Figure 5**, column 4). An early planting up to 3 months may be expected in the north savanna zone extending into the Sahel zone except in the north-east of Nigeria whilst a month early planting is expected in the south-coast of the country. On the other hand, the intervention may lead to a one-month delay in the planting of Cocoa and up to 3 months in the Guinea zone.

### **Figure 5.**

*The spatial distribution of Cocoas maize sensitivity to rainfall and temperature for the historical period over southern Africa (first panel, first row; 2011–2030) and relative changes over the historical period (first row, panel 2 & 3) and their projected future changes in the period (2070–2089) under the RCP8.5 scenario without (GHG) and with SAI (i.e., second and third rows, respectively). All-vary means both total monthly rainfall and monthly minimum and mean temperature varies, RAIN, monthly variation of minimum and mean temperature with annual mean total monthly rainfall (i.e., the same 12 monthly rainfall values are constant for the 30-year period) and TEMP; varying total monthly rainfall with constant annual minimum and mean temperature (i.e., the same 12 monthly minimum and mean temperature values are used for the 30-year period).*

### **3.5 Sensitivity of Cocoa suitability to climate variables (rainfall and temperature)**

We also examine the sensitivity of Cocoa suitability to temperature and rainfall to test independently the influence of their variation and trend for the three time periods, historical, GHG and SAI. In general, Cocoa suitability shows a decreasing suitability gradient from south to north over reference period for the all-vary experiment (see further description in Section 3.1) (**Figure 5**). The effect of rainfall variability at constant mean and minimum temperature (rain-vary) relative to the reference period (5a) shows no change in Cocoa suitability along the south coast, whilst southern savanna extending into the Sahel zone (5b-5i) will remain unsuitable. Similar suitability characteristics are also expected with variability in minimum and mean temperature at constant rainfall (temp-vary) over these zones. However, over the Guinea-savanna zones (7–10o N), about 0.15 suitability increase is expected and up to 0.25 along south-west boundary of Oyo and Ogun state.

The sensitivity of Cocoa suitability to rainfall and temperature variability shows a similar response under the GHG and SAI across the three experiments (all-vary,

### *Potential Impact of Stratospheric Aerosol Geoengineering on Cocoa Suitability in Nigeria DOI: http://dx.doi.org/10.5772/intechopen.113773*

rain-vary and temp-vary) but with varied impact in the Guinea-savanna zones. Our results show the impact of GHG and deployment of SAI on all three experiments will lead to no change Cocoa suitability over south coast and northern Sahel zone of Nigeria. However, in the Guinea-savanna zone, the impact of the scenario across the three experiments varies for both GHG and SAI. The impact of GHG on all-vary and rain-vary experiments may lead to a SIV increase (0.15) in south-west boundary from Oyo to Ogun state and central savanna zone relative to the historical period. However, projected SIV decrease (up to 0.35) may be expected over the country except along south-west boundary from Oyo to Ogun state and central savanna zones. Also, SIV decrease (up to 0.35) is expected in the Guinea-savanna zones under temp-vary experiments. In contrast, the impact of SAI deployment on all three climate sensitivity over Nigeria is expected to lead to a decrease up to 0.35 in Cocoa suitability in the Guinea-savanna zones (6–10o N), whilst no change in suitability is expected in south coast (4–6<sup>o</sup> N) and northern Sahel zones (10–12o N) over Nigeria. This means that the deployment of SAI may lead to reduced area in the cultivation of Cocoa in Nigeria, as the south coast may be the only suitable for growing the crop.

In summary, we find that Cocoa suitability is sensitive to variability in both temperature and rainfall under SAI but more sensitive to rainfall variability with constant temperature under GHG. This agrees with past findings, by Challinor et al. [49] and Ramirez-Villegas et al. [37], that variability in rainfall affects the suitability of crops in Sub-Saharan Africa.

### **3.6 Percentage distribution of Cocoa suitability**

We further examine the percentage distribution of different suitability condition to evaluate the impact of GHG and SAI on Cocoa at each grid point over Nigeria (**Figure 6**). The bar plot shows the percentage distribution of Cocoa suitability at each grid point over Nigeria for the historical period and the resultant impacts of GHG and SAI. Our result showed that about 42% of the land area in Nigeria is unsuitable for Cocoa cultivation and about 50% area is suitable (both suitable and highly suitable) over the historical period, whilst about 8% of the area is marginally suitable.

The impact of GHG and SAI on the percentage suitability distribution of Cocoa in Nigeria shows a similar pattern as the historical period albeit with varied magnitude. For example, global warming is projected to result in a decrease in suitable area for Cocoa cultivation in Nigeria relative to the historical period of about 18% and an increase (about 13%) in unsuitable area. This suggests that more areas will become unsuitable for growing Cocoa in Nigeria, as marginally suitable areas for Cocoa cultivation are projected to increase by about 2% across the country.

In addition, the impact of SAI shows a similar pattern in the percentage distribution of Cocoa suitability across grid points relative to the historical and GHG over Nigeria. SAI intervention may lead to a projected decrease of about 24% in suitable areas for Cocoa cultivation relative to the historical period and 18% decrease in comparison to the impact of GHG. In addition, the intervention may also lead to a further increase of about 14% and 24% in unsuitable areas for Cocoa relative to GHG and historical period, respectively, whilst no significant change was observed in areas with very marginal and marginal suitability for Cocoa in Nigeria.

The above result shows that GHG warming is projected to reduce the percentage of land suitable for Cocoa cultivation across Nigeria and SAI intervention would worsen this. Under both GHG and SAI scenarios, within in the GLENS modelling framework, there would be a resultant decrease in Cocoa production and yield in Nigeria [20].

**Figure 6.**

*A bar chart of percentage grid point distribution of Cocoa suitability over Nigeria for the historical period (2011–2030) and under the impact of GHG and SAI for the period (2070–2089)***.**

### **3.7 Implication of SAI on Cocoa production and Nigerian economy**

The availability of suitable land for cultivation is vital for crop growth and yield. The impact of SAI on Cocoa suitability and planting season is expected to have significant implication on socio-economy and GDP in Nigeria. The projected increase in unsuitable area in cultivating Cocoa and the corresponding decrease in suitable areas despite SAI intervention relative to the GHG impact over the country raises a concern considering the importance for Cocoa production to the economy of Nigeria. Cocoa is the major cash crops in Nigeria and most important agricultural export which can be processed into various products (e.g., Cocoa powder, Chocolates) for human consumption with a significant contribution to the socio-economy and GDP of the country via foreign exchange earnings [30]. SAI intervention on Cocoa suitability compared to the impact of climate change may further worsen the challenge of food and agricultural production in the region. This is because although SAI intervention reduces warming over Nigeria, its impact on Cocoa suitability relative to GHG will lead to a decrease in suitable areas for the Cocoa cultivation and may further lead to an increase in unsuitable areas relative to GHG as seen from our findings (**Figure 5**). The reduction of suitable land for Cocoa production and resultant decrease in production would lead to a decrease in Cocoa exports and its contribution to the GDP of the country [20, 30].

### **4. Conclusions**

The present study examined the impact of SAI on Coca suitability and planting season over in Nigeria using the GLENS CESM1(WACCM) experiment. We used GLENS experiment, which is aimed at reducing the mean global surface temperature by injecting sulphur at four latitudes as a climate intervention measure to reduce the impact of greenhouse gases on Cocoa production in Nigeria. To examine the impact of SAI intervention, we compared the GLENS output to historical and high-end emission scenario, RCP8.5 (GHG). We also examined the sensitivity of the crops to rainfall and temperature under GHG and SAI. The summary of our findings is listed below:


To our knowledge, this is the first study that examines the effect of SAI on Cocoa suitability in Sub-Saharan Africa. Hence, there are caveats to the interpretation of the result presented in this study. First, Ecocrop is a simple statistical model that evaluates crop suitability using total monthly rainfall and minimum and mean temperature climate variables. The model does not consider the effect of other factors, such as evapotranspiration and soil moisture, or non-climatic factors like pest and diseases and soil type which may further affect crop suitability. Also, the result is particular to solar geoengineering dataset, the GLENS experiment which used high-end representative scenario (RCP8.5) of climate geoengineering.

Nevertheless, the result from the study has helped improve our understanding of the potential impact of GHG and SAI on Cocoa suitability in Nigeria, the fourth largest producer of Cocoa in the world. Despite the caveats, one of advantage of using Ecocrop is that it is a simple and straight forward crop model to use with limited data requirement. Moreover, the observation and model representation of climate variables such as rainfall and temperature provide a basis for confidence in their outputs and the results are consistent with previous study on climate change and

geoengineering impacts with complex models [20, 37]. Further studies on the impact of SAI on other crop types, such as legumes, root and tuber, other horticultural crops including vegetables are recommended in the quest to understand food security risk under both GHG emissions and SAI. These studies should use more than just the GLENS datasets and models should be used to provide robust information on the impact of SAI on Cocoa.

### **Acknowledgements**

We acknowledge the financial support of the DEGREES Modelling Fund (DMF) of the DEGREES Initiative. Further supports were received from the National Research Fund (NRF) Scarce Skills Postdoctoral Fellowship, *ACCESS Annual Cycle* and *Seasonality Project* (ACyS); the DAAD within the framework of the ClimapAfrica programme with funds from the German Federal Ministry of Education and Research. We also appreciate the Centre for High Performance Computing (CHPC), South Africa for the computational resources. The data used in this study are freely available to the community via the Earth System Grid (https://www.cesm.ucar.edu/ projects/community-projects/GLENS/). The CESM project is supported primarily by the National Science Foundation.

### **Author details**

Temitope S. Egbebiyi1,2\*, Christopher Lennard1 , Pinto Izidine3 , Romaric C. Odoulami<sup>2</sup> , Piotr Wiolski1 and Akintunde I. Makinde1

1 Department of Environmental and Geographical Science, Climate Systems Analysis Group, University of Cape Town, Cape Town, South Africa

2 African Climate and Development Initiative, University of Cape Town, Cape Town, South Africa

3 KNMI - Royal Netherlands Meteorological Institute, Netherlands

\*Address all correspondence to: temitope.egbebiyi@uct.ac.za

© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Potential Impact of Stratospheric Aerosol Geoengineering on Cocoa Suitability in Nigeria DOI: http://dx.doi.org/10.5772/intechopen.113773*

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### **Chapter 3**

## Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate

*Antoine Alban Kacou M'bo, Mamadou Cherif, Kouakou Kouadio, Mahyao Germain Adolphe, Adama Bamba, Evelyne N'Datchoh Toure, Alla Kouadio Okou, Renée Brunelle, Yanick Rouseau and Daouda Koné*

### **Abstract**

Cocoa supports about 3.5 million people. Farmers produce each year 1.5 million ton. This performance hides production constraints, the most is climate variability. The climatic variables, temperature, precipitation, and 16 climatic indices were identified to assess the potential impacts on cacao in the past year, currently and under future climate. The climate data in the southern and central cocoa production zone were analysed for periods of 2021–2050 and 2041–2070. The climate reference period is 1981–2010. The climate projections are from the CORDEX RCP 4.5 and 8.5. The results suggest an increase in daily temperature of 1.0–2.1°C in the central region and 0.9–2.0°C in the southern region by 2041–2070. Cocoa could be affected by the projected changes, especially in the central region where the maximum daily temperature at which production is reduced (33°C) would be exceeded between 92 and 142 days per year by this time horizon. The direction of changes in precipitation cannot be established due to a lack of consensus between the climate models analysed. However, the little rainy season would start slightly earlier, potentially reducing the duration of the little dry season between the rainy seasons. The climate scenarios enhanced deterioration of growing environment conditions. It is necessary to take adaptation measures to mitigate climate impacts.

**Keywords:** climate, cacao, production, sustainability, Côte d'Ivoire

### **1. Introduction**

Cocoa is one of Côte d'Ivoire's main sources of foreign currency and the driving force behind its economic growth. It alone accounts for 15% of GDP. With an annual production of more than one million five hundred thousand tons since 2015 [1], this performance is due not only to the valuable results of agronomic research but also to the favourable ecological conditions in the southern half of the country. However, this spectacular overall result, which has made Côte d'Ivoire the world's leading producer, is based on a rapid and poorly controlled increase in the area under cultivation, leading to extensive deforestation. Furthermore, the ageing of cocoa trees and the lack of appropriate maintenance have led to a drop in the productivity of orchards, resulting in the impoverishment of communities [2].

Cocoa production is subject to significant inter-annual variability, accentuated by the action of soil and climate hazards, strong parasitic pressure from insects, and diseases such as *Swollen shoot* [3, 4] and the brown rot disease caused by *Phytophtora sp*., [5]. The greatest production constraint since 2010 has been climatic variability [6–8]. This can be seen in the significant reduction in the total leaf area of cocoa trees, and in the fall of flowers and young fruit [9–11], leading to a drastic drop in yield and the failure to rehabilitate and replant cocoa orchards. The effects of climate variability can also be seen in the interruption of young fruit growth, the reduction in bean and pod size, and the deterioration in bean quality [12–14].

Cocoa production areas experience significant inter-annual variability [15]. Climate is one of the main factors explaining this variability. It is important to note that rainfall is the most significant factor in cocoa growing, as a prolonged lack of water during the flowering phase can lead to a drop in production. Other climatic (temperature, humidity, solar radiation), ecological, biological, and physical factors can also have a significant influence on the phenology of the cocoa tree and its yields. The cocoa tree, an ombrophilous plant, requires specific climatic conditions for its development [16], annual rainfall of between 1300 and 2000 mm with a limited number of dry days (less than 3 months), an average daily temperature of between 24°C and 28°C, relative humidity of between 80% and 90%, daily sunshine of more than four hours, and deep, well-aerated soil rich in clay and humus. To develop and improve cocoa-growing conditions in Côte d'Ivoire, agrometeorological studies would contribute to a better understanding of the climatic factors likely to influence the plant's environment. This could not only help to improve farming practices, but also assess certain risks to the cocoa tree due to irregular rainfall, extreme temperatures and humidity, and low insolation. The effects of climate shock are expected to vary from one region to another, implying a need for adaptation or mitigation by context [8, 17]. Communities dependent on cocoa production are increasingly vulnerable to the impacts of climate change. These impacts stem from an increase in temperature and a change in rainfall patterns.

To better assess the impact of the climate, climate scenarios are an important step in assessing the vulnerabilities and impacts of climate change, and in identifying adaptation strategies capable of sustaining cocoa production over the coming decades. A climate scenario is a plausible description of the future state of the climate [18]. According to the Ouranos report [19], climate scenarios are produced by combining in-situ observations used as a reference dataset and climate projections for a given climate variable. This combination results in a climate scenario or a sequence of values associated with this variable for a period extending over several decades and for a given frequency. Climate models refer to greenhouse gas (GHG) emission scenarios as Representative Concentration Pathways (RCPs) to represent future radiative forcing. There are several groups of RCP models, but the most widely used are RCP 4.5 and RCP 8.5, which correspond respectively to a decrease in GHG emissions (optimistic scenario) and a constant increase in emissions throughout the century (pessimistic scenario). These models are part of the CORDEX (COordinated Regional Climate Downscaling EXperiment) – Africa domain [20–22]. In the present analysis, the RCP 4.5 and RCP 8.5 models were used to develop climate scenarios for the cocoa-growing *Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*

area in Côte d'Ivoire. The projections are likely values that lie within a confidence interval. 16 climatic indices were defined according to the requirements of the cocoa tree, and calculations were then made taking into account the uncertainty associated with the inter-model differences between the RCP 4.5 and RCP 8.5 greenhouse gas (GHG) emission scenarios. These calculations were used to develop climate scenarios for the cocoa-growing zone in Côte d'Ivoire, to interpret the impact of fluctuations in climatic variables on the cocoa tree in future decades, and to identify endogenous adaptation practices to cope with the future climate.

### **2. Zones and time horizons**

The cocoa production zone in Côte d'Ivoire is divided into two climatic regions. The central region (between 5.5° and 8° north latitude) and the southern region (below 5.5° north latitude) (**Figure 1**). In each of the two climate regions, the projected climate parameters are temperature and rainfall over two (2) time horizons (2021 to 2050 and 2041 to 2070) compared with the reference period 1981–2010. The study began in 2019, and as the data for the 2011–2020 decade is not complete, the 1991–2020 normal has not been used as a reference. The length of the time horizons of thirty (30) years follows the normal standard in climatology [23, 24]. This duration is generally long enough to obtain representative climate statistics, except for extreme and scarcer events [19]. A total of 16 climate indices were identified and calculated to assess the impact of climate change on cocoa production. The parameters and thresholds associated with these indices are based on information presented in scientific articles and on WASCAL-CEA-CCBAD experts' knowledge of cocoa physiology and climate. These indices depend on two climatic variables, either temperature, rainfall, or both. The interpretation of the results is grouped by climatic variable.

**Figure 1.** *Ivorian cocoa production area is divided into climatic regions.*

### **2.1 Temperature**

The ideal conditions to grow cocoa are when the annual average daily maximum temperature is between 30°C and 32°C and the annual average daily minimum temperature is between 18°C and 21°C [12]. These conditions are associated with maximum photosynthesis. A monthly average daily minimum of at least 15°C is necessary for plant health. A reduction in the growth and development of cocoa trees can occur if the number of days with a maximum temperature of over 33°C is too great [25, 26]. Taking into account this information on temperature-related aspects from the literature review, the following climatic variables were selected: average daily temperature (tas, °C), minimum daily temperature (tasmin, °C), and maximum daily temperature (tasmax, °C). These were used to calculate the following climatic indices:


### **2.2 Rainfall**

Rainfall between 1500 and 2000 mm per year is generally considered to be the most favourable for cocoa farming. Too much rain can increase the occurrence of diseases and attract pests, thus increasing the mortality rate of cocoa trees. Less than 1200 mm/year can lead to reduced root growth, leaf drop, and reduced plant growth. Cocoa trees must receive at least 700 mm of rain during the rainy season. What's more, for cocoa to ripen properly, the rainy season must last 4 consecutive months, from the flowering phase to the end of the main harvesting season (March to November). In addition, dry periods of more than 14 days can lead to a drop in production, and a dry season of more than 3 months is not tolerated by cocoa trees**.** Taking into account the information on rainfall from the literature review, the Daily rainfall (pr, mm) climate variable was adopted. This variable was used to calculate the following climate indices:


*Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*


### **3. Climate variability in the cocoa-growing zone**

### **3.1 Current climate in the centre region**

### *3.1.1 Temperature*

Temperatures are high in February to March (**Figure 2**). During these months, the average temperature is 27.1°C, while the average maximum daily temperature is 32.6° C. The greatest inter-annual variation occurs between December and March. Temperatures are lowest in July and August. During these months, the average temperature is 24.1°C, while the average maximum daily temperature is 27.8°C. Temperatures rise slightly in October-November. The lowest temperatures are recorded in February–March (23.3°C) and October-November (22.1°C). In January, July, August, and December, the average daily minimum temperature is 21.7°C.

### *3.1.2 Precipitation*

The sources of information available to assess the projected changes in these indices were: (1) rainfall climate scenarios, which were produced from reanalyses (the ERA5-Land ensemble) and climate projections (the CORDEX ensemble) using the

### **Figure 2.**

*Monthly climate normals for temperature, Central region. ERA5-Land reanalysis data for the period 1981–2010 were used. The diagrams are shown for: (A) mean temperature, (B) mean daily minimum temperature The vertical limits of the boxes correspond to the 10th, 50th, and 90th percentiles, while the ends of the error bars indicate the monthly minimum and maximum values.*

*Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*

### **Figure 3.**

*Monthly climate normals for precipitation, Central region. ERA5-Land reanalysis data for the period 1981–2010 were used. The vertical limits of the boxes correspond to the 10th, 50th, and 90th percentiles, while the ends of the error bars indicate the minimum and maximum monthly values.*

bias adjustment method, (2) rainy season detection parameters, and (3) the usual length of the break between rainy seasons in Côte d'Ivoire. An analysis of rainfall climate scenarios was completed to estimate monthly accumulations for the reference period and to visualize the characteristics of the two seasons, in terms of start, end, duration, and accumulation.

The data indicate more abundant rainfall between March and October inclusive, as well as the presence of two rainy seasons in the central region. Monthly rainfall is highest in September, followed by June, according to the median values (**Figure 3**). Interannual variability is greatest between June and September. The parameters initially chosen to detect the end of the rainy seasons during the reference period result in a long rainy season that ends 8 days before the start of the short season, on average (**Table 1**); this implies a quasi-unimodal distribution of rainfall. The period during which there is a decrease in rainfall between seasons seems too short considering the usual length of this period in Côte d'Ivoire (4–6 weeks) (**Figure 4**). Also, the timing of the break does not correspond to the decrease in rainfall between days 200 and 230 for the reference period.


### **Table 1.**

*Characteristics of rainy seasons detected in the central region.*

### **Figure 4.**

*Rainy seasons, based on initial definition of ONSET and cessation of rainy season for the central region.*

### **Figure 5.**

*Rainy seasons, based on revised definition of ONSET and cessation of rainy season for the central region.*

These preoccupations prompted a sensitivity analysis of the parameters of the endof-rainy-season indices. The formulation of these indices is that the season ends after the cumulative daily rainfall has been below a threshold P (mm/day) for a number of consecutive days t. A total of 25 combinations of thresholds P and t were tested with the reanalysis data for the reference period. For each of the combinations of these thresholds, the end dates of the rainy seasons were noted (averaged over the region). One of the combinations tested resulted in a dry period lasting 24 days (**Table 1**), which seems more compatible with reality (**Figure 5**). Using these rainy season detection parameters, the main rainy season extends from 7 April to 31 July, on average (**Table 1**). This corresponds to duration of 116 days. The short rainy season extends from 27 August to 17 November, lasting 83 days. Note that we now detect a dry season between the two rainy seasons with the revised parameters.

### **3.2 Current climate in the southern region**

### *3.2.1 Temperature*

The 30-year (1981–2010) monthly averages of mean, minimum, and maximum daily temperatures show important intra-annual variability. The high values of temperatures are recorded between February and April with average values about 23.6°C, 26.1°C and 30.2°C. The lower temperatures are observed in July and August during the little dry season. During these months, the average values are around 22.1°C for the minimum temperature, 23.9°C for the mean temperature and 26.7°C for the maximum temperature (**Figure 6**).

### *3.2.2 Precipitation*

The projected changes in precipitation were assessed using (i) rainfall climate scenarios, which were produced from reanalyses (the ERA5-Land ensemble) and bias corrected climate projections (the CORDEX ensemble), (ii) existing definition of

*Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*

### **Figure 6.**

*Monthly climate normals for temperature, southern region ERA5-Land reanalysis data for the period 1981–2010 were used. The diagrams are shown for: (A) mean temperature, (B) minimum temperature, (C) and daily maximum temperature. The vertical limits of the boxes correspond to the 10th, 50th, and 90th percentiles, while the ends of the error bars indicate the minimum and maximum monthly values.*

ONSET and cessation of rainy seasons, and (iii) usual duration of the little dry rainy season in the considered areas of Côte d'Ivoire. The seasonal analysis of the rainfall shows two rainy seasons in the southern region as well. Monthly rainfall is highest in May to June, followed by September-October, according to the median values (**Figure 7**). Interannual variability is greatest between June and August. The parameters initially chosen to detect the end of the rainy seasons result in a long

### **Figure 7.**

*Monthly climate normals for precipitation, southern region. ERA5-Land reanalysis data for the period 1981–2010 were used. The vertical limits of the boxes correspond to the 10th, 50th, and 90th percentiles, while the ends of the error bars indicate the minimum and maximum monthly values.*

rainy season that ends 16 days before the start of the short season, on average (**Table 2**); as was the case in the central region, this implies a quasi-unimodal distribution of rainfall. The period during which there is a decrease in rainfall between seasons seems short, considering the usual length of this period in Côte d'Ivoire (4–6 weeks) (**Figure 8**). Also, the timing of the break does not correspond to the decrease in rainfall between days 195 and 235 for the reference period (**Figure 9**).

A sensitivity analysis was also carried out for the southern region. One of the combinations tested (10 mm/day for 10 days) resulted in a dry period lasting 31 days (**Table 2**) between the two rainy seasons, which seems more compatible with the reality in Côte d'Ivoire (**Figure 10**).


### **Table 2.**

*Characteristics of rainy seasons of the southern region.*

### **Figure 8.**

*Rainy season, based on initial definition of ONSET and cessation of rainy season for the southern region.*

**Figure 9.**

*Rainy seasons, based on revised definition of ONSET and cessation of rainy season for the southern region.*

*Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*

### **Figure 10.**

*Rainy seasons, based on revised parameters for the central region The vertical limits of the boxes correspond to the 10th, 50th, and 90th percentiles, while the ends of the horizontal bars indicate the minimum and maximum values for each of the climate indices associated with the rainy seasons. The vertical red lines correspond to the days of the year for the reference period, i.e. 97 (7 April), 212 (31 July), 239 (27 August), and 321 (17 November).*

Using these rainy season detection parameters, the main rainy season extends from 28 March to 31 July, on average (**Table 2**). This corresponds to duration of 126 days. The short season runs from 31 August to 19 November, lasting 81 days. Note that there is a dry season between the two rainy seasons with the revised parameters.

### **3.3 Future climate in the centre regions**

### *3.3.1 Temperature*

The following trends can be observed:


All the scenarios and climate indices suggest warming over the next few decades. This warming would be greater for the RCP 8.5 scenario group than for the RCP 4.5 group. Also, the difference between the RCP groups would be greater for the most distant period. The most favourable temperature for growing cocoa is between 18 and 32°C. The analyses show that the number of months with an average minimum daily temperature below 15°C is zero. It is more the average maximum daily temperature that is likely to be problematic for cocoa growing. It could reach this threshold by 2021–2050 and even exceed it by 2041–2070. In addition, the number of days with an average daily maximum temperature of over 33°C could double or even triple by 2041–2070. The spatial distribution of temperatures and indices is similar.

### *3.3.2 Precipitation*

The following trends can be observed:


### *3.3.3 Major rainy season*

The following trends can be observed:


*Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*


### *3.3.4 Short rainy season*

The following trends were observed:


### *3.3.5 Little dry season*

The rainy seasons are shown in **Figure 10**. The average duration of the break between rainy seasons or little dry season is around 8 days over the 1981–2010 period, based on thresholds of 5 mm/day for 20 days. The break would last between [3; 10] days for the 2021–2050 and 2041–2070 horizons, representing potential changes between [5; +2] days. The length of the break between rainy seasons averaged 27 days over the 1981–2010 period, based on thresholds of 10 mm/day for 10 days. The break would last between [20; 27] days by 2021–2050 and between [21; 27] days by 2041–2070, representing potential changes between [7; 0] and between [6; 0] days, respectively. The pause would therefore be shorter than in the present climate.

### **3.4 Future climate in the south region of Côte d'Ivoire**

### *3.4.1 Temperature*

The following trends were observed:


All the scenarios and climate indices suggest warming over the next few decades. This warming would be greater for the RCP 8.5 scenario group than for the RCP 4.5 group. Also, the difference between the RCP groups would be greater for the most distant period. As previously mentioned, the most favourable temperature for cocoa cultivation is between 18 and 32°C. The results indicate that the number of months with an average daily minimum temperature below 15°C is zero. Concerning the upper limit of 32°C associated with cocoa cultivation, the results indicate that the average maximum daily temperature (between [29.4; 30.8]°C) would not exceed this threshold in the climatic horizons considered in this study. However, this does not mean that, in some years, the annual average would not exceed this threshold. In addition, the number of days with an average daily maximum temperature of over 33° C, which was only 2 days for the 1981–2010 period, could increase significantly. The cocoa tree's comfort limit would be exceeded more often by 2041–2070.

### *3.4.2 Precipitation*

The following trends were observed:

• Cumulative annual precipitation: The average value for the period 1981–2010 is 1888 mm. This would rise to between [1800; 2115] mm by 2021–2050 and

*Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*

between [1812; 2164] mm by 2041–2070, representing potential changes of between [88; +227] mm and between [76; +276] mm, respectively.


### *3.4.3 Major rainy season*

The following trends were observed:


### *3.4.4 Little rainy season*

The following trends are observed:

• Start of season: The season begins on day 243 of the year during the 1981–2010 period. It would begin between days [237; 245] of the year by 2021–2050 and between days [235; 244] of the year by 2041–2070, representing potential changes between [6; +2] days and between [8; +1] days, respectively.


### *3.4.5 Little dry season*

The rainy seasons are shown in **Figure 10**. The average duration of the little dry season the break between rainy seasons is around 16 days over the period 1981–2010, based on thresholds of 5 mm/day for 20 days. The break would last between [6; 21] days by 2021–2050 and between [6; 20] days by 2041–2070, representing potential changes between [10.0; +5.0] and between [10.0; +4.0] days, respectively. The length of the break between rainy seasons averages 31 days over the 1981–2010 period, based on thresholds of 10 mm/day for 10 days. The break would last between [19; 35] days by 2021–2050 and between [21; 35] days by 2041–2070, representing potential changes between [12; +4] and between [10; +4] days, respectively (**Figure 11**).

### **4. Influence of climatic variables on cocoa tree physiology and post-harvest aspects**

The aim was to establish the link between the fluctuation of climatic variables during the periods 2021 to 2050 and 2041 to 2070, on the establishment of orchards, the survival of cocoa trees after planting, the growth and development of cocoa trees, flowering, fruiting, drying and the technological quality of merchantable beans and cocoa pests and diseases. About cocoa diseases, the influence of climatic variables was

### **Figure 11.**

*Rainy seasons, based on revised parameters for the southern region. The vertical limits of the boxes correspond to the 10th, 50th and 90th percentiles, while the ends of the error bars indicate the minimum and maximum values for each of the climate indices associated with the rainy seasons. The vertical red lines correspond to the days of the year for the reference period, i.e., 87 (28 March), 212 (31 July), 243 (31 August) and 323 (19 November).*

*Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*

analysed on the development of brown rot and swollen shoot. Concerning pests, the analysis focused on mirids, stem borers, mealybugs, psyllids, and defoliating caterpillars. The immediate and lasting repercussions of climate change on diseases and pests are among the major concerns of scientists and policy-makers around the world. Rainfall and temperature are the most important factors in the development of diseases and pests.

**Tables 3**–**10** summarise the results of the climate scenarios and their influence on cocoa production in the Central and Southern zones of Côte d'Ivoire.

### **5. Identification of climate smart practices for adaptation to climate variability in cocoa production**

Generally, the adoption of climate-smart practices by cocoa farmers remains limited for a variety of reasons. Surveys carried out in Abengourou, Gagnoa, Vavoua, and Soubré to collect and analyse adaptation practices in cocoa farming enabled a range of agroecological practices covering all stages of cultivation to be inventoried (**Table 11**). The most promising practices for coping with the effects of climate change in cocoa farming were identified using multiple criteria (economic, social, and gender equality, environmental, and efficiency). This multi-criteria analysis shows that the most promising practices relate to tree planting, for shade purposes and other benefits provided by trees and agroforestry [27, 28]. These practices deserve to be included in the training curricula of professionals who work with cocoa farmers, just as these practices deserve to be widely disseminated and promoted among cocoa farmers. Cocoa cooperatives also play a role in disseminating these messages and in meeting the needs of their members, both men and women. These organizations benefit from taking climate change into account in the products and services they offer so that they can make informed and strategic decisions.

### **6. Conclusions**

The analysis of the climate scenarios for the next 50 years for the central and southern zones of Côte d'Ivoire concerning cocoa farming provides an understanding of the projected impact of future climate on cocoa trees and the surrounding environment. In general, the various climate scenarios showed that there would be an increase in the average maximum temperature (up to 1.3°C higher by 2021–2050 and 2.2°C higher by 2041–2070) and an increase in the number of hot days (≥33°C) in both zones (Centre and South), although these changes would be more marked in the Centre zone. No consensus has been reached between the climate model projections for rainfall, except that the short rainy season could start earlier than in the present climate. These predictions could have impacts on cocoa cultivation. With respect to physiology, rainfall forecasts are favourable to the establishment, growth, flowering, and fruiting of cocoa trees. On the other hand, an increase in the number of hot days would be harmful to the cocoa tree. Concerning cocoa diseases (CSSVD and brown rot), increases in temperature and the number of hot days would help slow their progress in the orchards. About the main pests, increases in temperature and rainfall would not alter their dynamics, but only the delay in the start of the main rainy season could reduce the outbreak of defoliating caterpillars. For soil on


### *Shifting Frontiers of* Theobroma cacao *– Opportunities and Challenges for Production*


 **3.** *Interpretation of the influence of climatic variables for the period 2021–2050 on cocoa physiology and post-harvest aspects in the central zone.*

### *Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*


### *Shifting Frontiers of* Theobroma cacao *– Opportunities and Challenges for Production*

**Table 4.** *Interpretation of the influence of climatic variables for the period 2041–2070 on cocoa physiology and post-harvest aspects in the central zone.*

### *Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*


### *Shifting Frontiers of* Theobroma cacao *– Opportunities and Challenges for Production*


 **5.** *Interpretation of the influence of climatic variables for the period 2021–2050 on cacao diseases*

 *and pests in the central zone.*

### *Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*


### *Shifting Frontiers of* Theobroma cacao *– Opportunities and Challenges for Production*


*Interpretation of the influence of climatic variables for the period 2041–2070 on cocoa diseases and pests in the central zone.*

### *Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*


### *Shifting Frontiers of* Theobroma cacao *– Opportunities and Challenges for Production*


**Table 7.** *Interpretation of the influence of climatic variables for the period 2021–2050 on cocoa physiology and post-harvest aspects in the southern zone.*

### *Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*


### *Shifting Frontiers of* Theobroma cacao *– Opportunities and Challenges for Production*


 *Interpretation of the influence of climatic variables for the period 2041–2070 on cacao physiology and post-harvest aspects in the southern zone.*

### *Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*


### *Shifting Frontiers of* Theobroma cacao *– Opportunities and Challenges for Production*


 **9.** *Interpretation of the influence of climatic variables for the period 2021–2050 on cocoa diseases and pests in the southern zone.*

**Table**

### *Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*




 *zone.*

### *Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*

## **Illustrations Agroecological practices identified** Temporary shade plants • Plantation of banana trees for temporary shade • Planting tree legumes (*Cajanus cajan*) for temporary shade and human consumption Permanent shade trees • Plantation of compatible fruit and forest species for shade purposes • Plantation of perennial legumes (e.g. *Acacia mangium* and Albizia)

Crop system management





**Table 11.** *Identification of agroecological practices to adapt to climate change effect in cocoa farming.*

which crop is grown, (cocoa trees, and associated crops) would also be affected by climate change, with an increase in the number of hot days (≥33°C). This would result in high evapotranspiration, low soil water retention, and rapid degradation of organic matter, leading to a decline in soil fertility. In addition, climate change could lead to lower yields and higher levels of poverty in rural areas. Given the impact that climate change would have on cocoa farming over the periods 2021–2050 and 2041–2070, strategies are proposed to improve the resilience of producers within cocoa cooperatives in Côte d'Ivoire. A set of agro-ecological practices have been identified that could counteract the adverse effects of climate change.

### **Acknowledgements**

This work was done in the framework of the Adaptcoop project in Côte d'Ivoire. The authors would like to thank the IDRC (International Development Research Centre of Canada) for funding the project. We also thank SOCODEVI, and OURANOS from Canada, and WASCAL/CEA-CCBAD (African Centre of Excellence on Climate Change, Biodiversity and Sustainable Agriculture) and CNRA (Centre National of Research on Agriculture), from Côte d'Ivoire.

### **Conflict of interest**

The authors declare no conflict of interest.

### **Author details**

Antoine Alban Kacou M'bo1 \*, Mamadou Cherif<sup>1</sup> , Kouakou Kouadio1,2, Mahyao Germain Adolphe<sup>3</sup> , Adama Bamba1,4, Evelyne N'Datchoh Toure1,4, Alla Kouadio Okou5 , Renée Brunelle<sup>6</sup> , Yanick Rouseau<sup>7</sup> and Daouda Koné<sup>1</sup>

1 African Center of Excellence on Climate Change, Biodiversity and Sustainable Agriculture (CEA-CCBAD/WASCAL), Université Félix Houphouet-Boigny (UFHB), Côte d'Ivoire

2 Geophysical Station of Lamto (GSL), N'Douci, Côte d'Ivoire

3 Centre National de Recherche Agronomique, Gagnoa Research Station, Côte d'Ivoire

4 Laboratoire des Sciences de la Matière, de l'environnement et de l'Energie Solaire (LASMES), UFR-SSMT of Felix Houphouët Boigny University, Côte d'Ivoire

5 Agence National d'Appui au Developpement Rurale (ANADER), Côte d'Ivoire

6 SOCODEVI, International Cooperation Organization, Canada

7 OURANOS, Consortium on Regional Climatology and Adaptation to Climate Change Montréal, Québec, Canada

\*Address all correspondence to: mbo.antoine@ufhb.edu.ci

© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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[5] Kébé BI, Koffie K, N'guessan KF. Le swollen shoot en Côte d'Ivoire: Situation et perspectives. In: Résumés des Actes de la 15ème conférence internationale sur la recherche cacaoyère. (San José, Costa Rica, 9–14 octobre 2006). 2006. p. 66

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[8] Schroth G, Läderach P, Matinez-Valle AI, Bunn C, Jassogne L. Vulnerability to climate change of cocoa in West Africa: patterns, opportunities and limitations to adaptation. Science of the Total Environment. 2016;**556**:231-241. DOI: 10.1016/j.scitotenv.2016.03.024

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[10] Dje KB. Impacts des phénomènes ENSO sur la pluviométrie et leurs incidences sur la production cacaoyère en Côte d'Ivoire. In: Communication présentée à la Conférence internationale pour la réduction de la vulnérabilité des systèmes naturels économiques et sociaux en Afrique de l'Ouest face aux changements climatiques, Ouagadougou, du 24 au 27 janvier 2007. 2007

[11] Santos E Ad, Almeida AAF d, Branco MCDS, Santos ICD, Ahnert D, Baligar VC. Path analysis of phenotypic traits in young cacao plants under drought conditions. PLoS One. 2018; **13**(2):e0191847. DOI: 10.1371/journal. pone.0191847

[12] Daymond AJ, Hadley P. Differential effects of temperature on fruit development and bean quality of contrasting genotypes of cacao (Theobroma cacao). Annals of Applied Biology. 2008;**153**(2):175-185

*Climate Variability and Outlook of Cocoa Production in Côte D'ivoire under Future Climate DOI: http://dx.doi.org/10.5772/intechopen.112643*

[13] Läderach P, Martínez A, Schroth G, Castro N. Predicting the future climatic suitability for cocoa farming of the world's leading producer countries, Ghana and Côte d'Ivoire. Climatic Change. 2013;**2013**(119):841-854. DOI: 10.1007/s10584-013-0774-8

[14] Moser G, Leuschner C, Hertel D, Hölscher D, Köhler M, Leitner D, et al. Response of cocoa trees (*Theobroma cacao*) to a 13-month desiccation period in Sulawesi, Indonesia. Agroforestry Systems. 2010;**79**(2):171-187

[15] CIAT (International Center for Tropical Agriculture). Predicting the Impact of Climate Change on the Cocoa-Growing Regions in Ghana and Cote d'Ivoire. Managua, Nicaragua: CIAT; 2011. Available from: https://www.eene ws.net/assets/2011/10/03/document\_ cw\_01.pdf

[16] Braudeau J. In: Larose GPM, editor. Le cacaoyer. Paris; 1969. p. 304

[17] Wessel M, Quist-Wessel PMF. Cocoa production in West Africa, A review and analysis of recent developments. NJAS Wageningen Journal of Life Sciences. 2015;**74–75**:1-7

[18] Parry M, Carter T. Climate Impact and Adaptation Assessment: A Guide to the IPCC Approach. London: Earthscan Publications; 1998. DOI: 10.1002/(SICI) 1097-0088(19990330)19:4<459::AID-JOC398>3.0.CO;2-0

[19] Ouranos. Renforcement de la résilience des coopératives des coopératives cacaoyères aux changements climatiques en Côte d'Ivoire – Scénarios et indices climatiques. Rapport présenté par Ouranos et WASCAL-CEA-CCBAD. 2021:53+12

[20] Kalognomou EA, Lennard C, Shongwe ME, Pinto I, Favre A, Kent M, et al. Diagnostic evaluation of precipitation in CORDEX models over Southern Africa. Journal of Climate. 2013;**23**:9477-9506. DOI: 10.1175/JCLI-D-12-00703.1

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[23] Kisembe J, Favre A, Dosio A, Lennard C, Sabiiti G, Nimusiima A. Evaluation of rainfall simulations over Uganda in CORDEX regional climate models. 2018. DOI: 10.1007/ s00704-018-2643-x

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### **Chapter 4**

## Cocoa Production and Distribution in Bahia (Brazil) after the Witch's Broom

*Hélio Rocha Sousa Filho, Marcos de Almeida Bezerra, Raildo Mota de Jesus and Jorge Chiapetti*

### **Abstract**

*Theobroma cacao* production in the state of Bahia (Brazil) suffered crises due to a combination of falling prices, the end of subsidized credit, droughts, international supply and witches' broom disease. The objective was to verify the distribution of the cocoa crop in the state of Bahia and to analyze the indicators of harvested area, production and productivity, starting from the crop crisis that started in the late 1980s. Data were collected from the Brazilian Institute of Geography database. and Statistics, period from 1988 to 2019. Cocoa production is present in 26% of the municipalities, distributed in nine economic regions, especially in the east of the state. Harvested area decreased by 30.7%, production by 65.4% and productivity by 50.1%; numbers that demonstrate the dimension of the problem. In the economic regions, there was a separation of two periods: 1988–1999 and 2000–2019. In the first, the indicators show higher numbers that decrease with the deepening of the crisis. In the second, cultivars resistant to witches' broom and new management and production techniques were implanted, measures related to the behavior of the indicators. Thus, decades after the cocoa farming crisis, increasing production and productivity levels remains a challenge.

**Keywords:** cocoa cultivation, agricultural production, harvested area, productivity, crisis cocoa

### **1. Introduction**

The cocoa tree (*Theobroma cacao*) is cultivated in tropical areas. Its importance is connected to its seed, the cocoa bean, a commodity traded on international stock exchanges. Driven by the consumption of chocolate-based products, world demand for cocoa beans has been increasing in recent years [1]. In the nineteenth century, most of the cocoa produced in the world came from Latin America, from the tropical zone [2]. In recent years, statistics indicate that Africa has the highest levels of cocoa bean production in the world, followed by Central and South America, Australia, and Asia [3].

In Brazil, cocoa production cannot cover the industry's shortfall in supply, making the country's installed capacity dependent on the importation of cocoa beans [4]. The Brazilian context of insufficient production arose from a combination of factors that contributed to the cocoa production crisis [5]. Witches' broom was one such factor, being a disease of the cocoa tree caused by the *Moniliophthora perniciosa* fungus, one of the most devastating parasites for cocoa production [6]. The fungus infects the plant and leaches nutrients for its growth, in addition to affecting the fruits and causing the loss of beans [7].

After the outbreak of witches' broom on cocoa plantations in South America and the Caribbean, cocoa bean production recorded a fall of 50–90% [8]. In Brazil, witches' broom had previously been recorded in the eighteenth century in the Amazon region, although it was first recorded on cocoa plantations in Northeast Brazil, in the state of Bahia, in 1989 [9].

A crisis began in cocoa production in Bahia at the end of the 1980s, caused by a combination of events such as a drop in prices, the end of subsidized credit, droughts, increased supply from other countries, and fungal diseases. In this scenario, the spread of witches' broom throughout Bahia's cocoa crop aggravated problems in production and productivity, causing unemployment and rural exodus [10]. The fall in production also affected the cities that depended on cocoa cultivation in some way, causing a drop in the circulation of merchandise, decreased municipal tax revenue, and an increase in social problems [5]. One analysis indicated an interdependence between Brazil's cocoa production and that of Bahia, as there was a successive decline in production in Bahia between 1990 and 2004, which impacted national production [11].

Considering the cocoa crisis that began in Bahia in 1989, this study used the harvested area, production, and productivity indicators to investigate the impacts the crisis caused on the cocoa crop. According to the literature, indicators are tools of investigation, measurement, and information on the state of a system, and may be applied to understanding phenomena or processes, managing complex issues, and in decision making [12, 13].

In the context presented above, it is relevant to understand the panorama of cocoa culture in Bahia in the last three decades, after the outbreak of witches' broom, which is one of the factors that most contributed to the decrease in Brazilian cocoa production [10, 11]. On a global level, it is important to gather information on the evolution of cocoa cultivation after an agricultural crisis, especially in Bahia, Brazil, one of the most traditional and most important cocoa-producing regions in the world [14]. The behavior of the indicators may indicate appropriate strategies for crop recovery and the construction of policies that enhance the development of cocoa culture, since positive results in agriculture are drivers of improved quality of rural life [13]. Thus, this study aimed to verify the distribution of cocoa culture in the state of Bahia and analyze the harvested area, production, and productivity indicators, from the crop crisis that began at the end of the 1980s.

### **2. Material and methods**

The cocoa-producing municipalities in the state of Bahia in Northeast Brazil made up the study area. The cultivation of cocoa is of great economic and social importance for Bahia, which is one of the main cocoa producers in Brazil. Economic division of the regions was adopted for the analysis, according to Law no. 6.349 of

### *Cocoa Production and Distribution in Bahia (Brazil) after the Witch's Broom DOI: http://dx.doi.org/10.5772/intechopen.112199*

17th December 1991, which divided the state into fifteen regions and was adopted by the Superintendência de Estudos Econômicos e Sociais da Bahia (Superintendence of Economic and Social Studies of Bahia) [15]. This division was chosen because it groups the municipalities by economic and commercial characteristics, whereby one or various productive activities identify and determine regional potential [16, 17]. Thus, it may be possible to establish in which regions cocoa culture has the greatest representation.

Information was collected from a database, based on publications by the Instituto Brasileiro de Geografia e Estatística (Brazilian Institute of Geography and Statistics) (IBGE). Information from the Produção Agrícola Municipal (Municipal Agricultural Production) (PAM) survey, which provides data on a municipal, state, and national scale, was also used. The PAM survey is carried out on all production units wholly or partially dedicated to agriculture or livestock. This research is the result of a monthly systematic agricultural survey of annual consolidation [18]. Harvested area, quantity produced (production), and mean yield (productivity) of the permanent cocoa crop in beans, in the municipal and state territories, were selected as indicators. These three indicators were chosen for their availability of access to a chronological series of data. The time frame analyzed was between 1988 and 2019, totaling 32 years. This time frame is from the year before witches' broom was recorded in Bahia up to the last year in which consolidated data are available.

To carry out the analyses, data on harvested area (hectare), production (tons), and productivity (kilogram per hectare) were initially accessed through Table number 1613 of the PAM survey, via the IBGE system of Automatic Recovery. The consolidated values of the variables on state level basis from the database were used in the analysis. Subsequently, the cocoa-producing municipalities in Bahia were selected and classified according to economic region. After this stage, annual values of each of the harvested area, production and productivity indicators of each economic region were calculated, resulting in matrices of 32 × 3, displaying the 32 years observed as rows and the three indicators as columns. The data were auto-scaled and subjected to principal components analysis (PCA). This exploratory method was applied for its capacity to reduce the dimensions of the data and identify inter-relationships between the observations and variables [19]. Execution of the principal components analysis (PCA) will establish patterns of behavior for the indicators, highlighting similarities and/or differences in the evolution of agricultural activity in the regions. Analysis calculations were executed using Past software (Hammer Copyright. 2018, version 3.2, NOR).

### **3. Results and discussion**

The state of Bahia has 417 municipalities, with cocoa production being distributed in 26% of these municipalities (**Table 1**). The data also show growth of around 17% in the quantity of cocoa-producing municipalities when comparing 1988 and 2019. This demonstrates resilience in cocoa cultivation in this period, even with the drop in bean prices, the end of subsidized agricultural credit, and the emergence and spread of witches' broom, which contributed to the third major crisis of the sector [11].

In 1979, the Comissão Executiva do Plano da Lavoura Cacaueira (Executive Commission of the Cocoa Tree Crop Plan) (CEPLAC) carried out a survey on the distribution of the cocoa area in Bahia and its production. In this study, it was found that the cocoa cultivation was present in 83 municipalities, in seven sub-regions, and that some municipalities had the potential to expand their cultivated areas [20].


### **Table 1.**

*Distribution of the number of cocoa-producing municipalities in the economic regions of Bahia (1988–2019).*

According to the most current data from 2019, cocoa production was recorded in nine economic regions in Bahia.

The Litoral Sul and Extremo Sul regions have the highest percentages of cocoaproducing municipalities, with 98% and 85%, respectively. This demonstrates the representativity and importance of cocoa in this part of the state. When examining the history of cocoa in Bahia, it can be noted that a high number of cocoa-producing municipalities are concentrated in these regions. This is not by chance, as cocoa culture began in the south of the state [11]. Another stand-out region is Recôncavo Sul, with cocoa production in more than half of its municipalities, demonstrating that cocoa is also a representative crop of the economy of this region.

The cocoa production record in the municipalities of the Chapada Diamantina, Médio São Francisco, and Oeste regions is relevant data, as they are regions without a tradition of cocoa culture. Trying to make cocoa production viable in these regions may constitute escape zones for cocoa tree diseases, expansion to new production centers, and an opportunity to increase production and generate jobs and income [21]. In addition, it enables crop diversification with the perspective of becoming a new vector of local development.

Analysis of the spatial distribution of the cocoa-producing municipalities in the regions of Bahia, demonstrates that cocoa cultivation is predominant in the east of

*Cocoa Production and Distribution in Bahia (Brazil) after the Witch's Broom DOI: http://dx.doi.org/10.5772/intechopen.112199*

### **Figure 1.**

*Location of the 15 economic regions of the state of Bahia and distribution of the cocoa-producing municipalities in 2019.*

the state, in the humid zone, in a strip close to the coast (**Figure 1**). This is due to the existence of edaphoclimatic conditions, and processing and exportation infrastructure that favor cocoa production activity [10, 22].

The edaphic and climatic conditions in the south of Bahia are beneficial for cocoa cultivation, as the plant grows in fragments of native forest, in the shade of big trees, with adequate rainfall and deep soils [4, 23]. These conditions contributed to the dissemination of the cocoa tree in the Extremo Sul region, as well as expansion to the municipalities of the humid zone of the Recôncavo Sul and Sudoeste regions.

Starting in 2010, with research and increased technology, experimental areas and cocoa production were created in municipalities in the Chapada Diamantina, Médio São Francisco, and Oeste regions, which do not have naturally favorable edaphoclimatic conditions [24]. Cocoa cultivation was implanted in the humid and sub-humid transition zone and in semi-arid locations. This new expansion is due to irrigated cocoa tree cultivation with sun exposure, the adoption of agronomic management of high technification, and highly productive cloned cultivars resistant to fungal diseases [24].

In recent years, CEPLAC has recommended integrated management in the control of fungal diseases of cocoa trees such as witches' broom, the main pest affecting cocoa plantations in Bahia. The strategies that make up integrated management of witches' broom are culture control, chemical control, biological control, and the insertion of genetically enhanced cultivars [25]. The integrated approach has assisted in production continuity [14]. The large-scale adoption of these strategies may positively interfere in cocoa culture indicators in the producing regions.

Until the mid-1980s, the state of Bahia produced 400 thousand tons of cocoa [14, 26]. Between 1988 and 2019, graphic analysis of the data on the harvested area,

**Figure 2.**

*Evolution of the harvested area, production, and productivity indicators of the cocoa crop in the state of Bahia, between 1988 and 2019. Harvested area (scale of 0–700,000 hectares); production (scale of 0–400,000 tons) and productivity (scale of 0–650 kilograms per hectare).*

production, and productivity indicators demonstrates the occurrence of variations and lower final numbers (**Figure 2**). Although witches' broom is indicated as the main cause of these alterations in the 1990s, other factors contributed significantly, such as the fall in the supply of subsidized agricultural credit and the decrease in the price per ton of cocoa beans in the 1980s and 1990s [27].

The harvested area indicator shows a reduction of around 8% in the first four years. From 1992 onwards, there are positive and negative fluctuations, with a general decrease until 2002, when a value of 487 thousand hectares was recorded. From then on, there was an increasing trend until recording 553 thousand hectares in 2016, although this fell value to 413 thousand hectares in 2019. In addition to the fluctuations in harvested area, it decreased by 30.7% between 1988 and 2019.

The production indicator showed a reduction of 66%, between 1988 and 2002. From 2003 onwards, there is a trend of growth until 2015. However, in 2019 production decreased again, recording around 113 thousand tons, which is a fall of 65.4% in relation to 1988. It should be highlighted that despite the reduced production in periods of crisis, cocoa continues to be one of the main agricultural products in the south of Bahia [28].

In the mid-1990s, the decline in cocoa production in Bahia and the need to renew cocoa plantations led the federal government to launch the Cocoa Crop Recovery Program. This program offered credit for producers to invest in recovering plantations and controlling witches' broom. Government technical bodies recommended measures to combat witches' broom disease: phytosanitary pruning, fungicide application, biological control and replanting of cocoa plantations, using clones of resistant cultivars [23].

The productivity indicator showed an increase between 1988 and 1989, from 549 kg/ha to 600 kg/ha. Productivity then decreased to a certain level between 2000 and 2003, recording around 226 kg/ha. Despite oscillations, from 2003 onwards,

### *Cocoa Production and Distribution in Bahia (Brazil) after the Witch's Broom DOI: http://dx.doi.org/10.5772/intechopen.112199*

there was a general trend of increase until 2015. In 2016 production decreased to 209 kg/ha, the lowest recorded yield, this year falling within the period of one of the most severe droughts in Bahia's history, whereby rainfall levels fell below the average, resulting in negative consequences for agriculture and livestock in general [29]. In 2019, productivity reached 274 kg/ha; however, compared with 1988, this is a decrease to the order of 50.1%.

Analysis of the production and productivity indicators shows a positive trend from the beginning of the 2000s, which coincides with the start of the movement substituting traditional cultivars for clones resistant to witches' broom [30]. In the 2000s, CEPLAC started a program of cocoa tree improvement in Bahia that resulted in highly productive cultivars that were resistant to the disease [31].

The cocoa culture problems in Bahia are dealt with on various fronts, with the aim of recovering the losses caused by the crisis. One of the initiatives observed is production for the fine aroma cocoa market, which already has 50 local brands of chocolate in the south of Bahia [10]. This market pays a higher value for cocoa beans in relation to traditional production; however, the production of fine aroma cocoa requires the selection of plant varieties and special care in the ripening, harvest, and post-harvest of the cocoa. This is all done with the aim of achieving distinctive sensory characteristics of aroma and outstanding flavor [32].

The evolution of the cocoa crisis certainly did not affect the harvested area, production, and productivity indicators in the same way or at the same time in all the cocoa-producing regions of Bahia. Thus, through the principal components analysis (PCA), it was possible to observe the interactions between the three indicators as well as the relationships between the observations from 1988 to 2019 (**Figure 3**). Among the ten cocoa-producing regions of Bahia, Chapada Diamantina, Médio São Francisco, and Oeste did not have enough data to be included in the analysis, as production in these regions only began in 2010.

In the Metropolitana de Salvador region, the two PCs (first two components) explain 99.64% of the total variation. PR (production) and PD (productivity) contribute the most to PC1 (first component); HA (harvested area) has the largest contribution to PC2 (second component). The biplot graph for PC1 versus PC2 demonstrates a trend towards separation of 1988 to 1999 from 2000 to 2019. In PC1, the positive vectors of HA, PR, and PD are more related to the period of 1988 to 1999. The results indicate that in most of the period between 1988 and 1999 the indicators were higher (**Figure 3a**).

In the Litoral Norte region, the two PCs explain 99.76% of the total variation (**Figure 3b**). HA and PR contribute the most to PC1; PD has the largest contribution to PC2. The biplot graph for PC1 versus PC2 demonstrates a separation of 1988 to 1999 from 2000 to 2019. In PC1, the positive vectors of the three variables are related to the period of 1988 to 1999, in addition, the lower distance between the HA vector and PR indicates a greater correlation between the two indicators. The data demonstrate that the indicators were higher between 1988 and 1999.

In the Recôncavo Sul region, the two PCs explain 99.67% of the total variation (**Figure 3c**). HA and PR contribute the most to PC1; PD has the largest contribution to PC2. The biplot graph for PC1 versus PC2 demonstrates a separation of 1988 to 1989 from 1990 to 2019. In PC1, the positive vectors PR and PD are more related to 1988 and 1989. The data indicate less variation of the indicators between 1990 and 2019 and higher values.

In the Litoral Sul region, the two PCs explain 99.92% of the total variation (**Figure 3d**). PR and PD contribute the most to PC1; HA has the largest contribution

### **Figure 3.**

*Principal components analysis carried out on cocoa crop indicators in seven economic regions in the state of Bahia, from 1988 to 2019 (*▲*1988–1989;* ▲*1990–1999; and* ▲*2000–2019). Data from the Produção Agrícola Municipal (Municipal Agricultural Production) survey of the IBGE, using three indicators, HA: harvested area; PR: production; PD: productivity. On the graphs for (a) região Metropolitana de Salvador, (b) Litoral Norte, (c) Recôncavo Sul, (d) Litoral Sul, (e) Extremo Sul, (f) Sudoeste, and (g) Paraguaçu the first two principal components (PC) are demonstrated and explain approximately 95% of the data variability in all the analyses.*

### *Cocoa Production and Distribution in Bahia (Brazil) after the Witch's Broom DOI: http://dx.doi.org/10.5772/intechopen.112199*

to PC2. The biplot graph for PC1 versus PC2 demonstrates a separation of 1988–1999 from 2000 to 2019. In PC1, the positive vectors HA, PR, and PD are related to the period of 1988–1999, in addition, the lower distance between the PR vector and PD indicates a greater correlation between the two indicators. The data demonstrate that the indicators were higher between 1988 and 1999.

In the Extremo Sul region, the two PCs explain 99.71% of the total variation (**Figure 3e**). HA and PR contribute the most to PC1; PD has the largest contribution to PC2. The biplot graph for PC1 versus PC2 demonstrates a separation of 1988–1999 from 2000 to 2019. In PC1, the positive vectors HA, PR, and PD are related to the period of 1988–1999. It can also be seen that from 1990 to 1999 the points are much more clustered, indicating proximity of the values. The data demonstrate that the indicators were higher between 1988 and 1999.

In the Sudoeste region, the two PCs explain 99.64% of the total variation (**Figure 3f**). PR and PD contribute the most to PC1; HA has the largest contribution to PC2. The biplot graph for PC1 versus PC2 demonstrates a trend towards separation of 1988–1999 from 2000 to 2019. In PC1, the positive vectors of PR and PD are more related to the period of 1988–1999, while the HA vector is close to some points from the 2000s. The data demonstrate that in 1988, 1989, and some years from the 1990s, the indicators were higher than the period to 2000–2019.

In the Paraguaçu region the two PCs explain 99.61% of the total variation (**Figure 3g**). HA and PR contribute the most to PC1; PD has the largest contribution to PC2. The biplot graph for PC1 versus PC2 demonstrates a separation of 1988–1999 from 2000 to 2019. In PC1, the positive vectors HA, PR, and PD are more related to the period of 1988–1999, in addition, the lower distance between the HA vector and PR demonstrates a greater correlation between the two indicators. The data demonstrate that the indicators were higher between 1988 and 1999.

In summary, the PCAs carried out on the data on the harvested area, production, and productivity indicators of the cocoa crop, separated or tended to separate the Metropolitana de Salvador, Litoral Norte, Litoral Sul, Extremo Sul, Sudoeste, and Paraguaçu regions into two periods. The first period between 1988 and 1999 is made up of the years following the beginning of the crop crisis, where the values of the indicators are higher and suffer a decrease over the years. In the second period, between 2000 and 2019, the numbers remain lower than in the first period, demonstrating that the productive activity of cocoa did not manage to recover.

In the Recôncavo Sul region, the PCA demonstrates that the data from the 1990s and the 2000s are close (**Figure 3c**), without apparent visual separation. This indicates that in this region, the variation in the harvested area, production, and productivity indicators occurred differently to the other regions, which leads to the inference that the crisis affected the three indicators in the Recôncavo Sul region differently in comparison to the other regions.

Growth rates for the harvested area, production, and productivity indicators were estimated based on the separation of the data into two periods indicated by the principal components analysis. For the harvested area, the growth rate demonstrated that there was a decrease in almost all the regions (**Table 2**). The reduction in the areas with cocoa may be explained by abandonment and substitution of the crop, as with the incidence of witches' broom and all the other previously cited events, maintaining the crop area became a challenge for producers.

The Metropolitana de Salvador, Litoral Sul, and Recôncavo Sul regions were those that had a positive growth rate for the harvested area indicator in at least one period


### **Table 2.**

*Growth rate of the harvested area of the cocoa crop in regions of Bahia (1988–2019).*

(**Table 2**). The literature reports that between 1990 and 2004 the advance of witches' broom in 41 municipalities of the Litoral Sul region was not reflected in widespread abandonment or substitution of cocoa for other crops [11]. Regarding the Recôncavo Sul region, it should be pointed out that it is located between humid, sub-humid, and dry climate zones, which may have inhibited the incidence and distribution of witches' broom [23].

The production indicator also had a negative growth rate in most regions. Between 1988 and 1999, the Metropolitana de Salvador region was the only region that presented growth (**Table 3**). In absolute terms, this region has one of the lowest expressions in cocoa production, which may be why this growth has not been considered of great relevance to the general panorama.


### **Table 3.**

*Growth rate in cocoa tree production in regions of Bahia (1988–2019).*

### *Cocoa Production and Distribution in Bahia (Brazil) after the Witch's Broom DOI: http://dx.doi.org/10.5772/intechopen.112199*

In the Recôncavo Sul region, a positive growth rate is observed between 2000 and 2019 (**Table 3**). A study on cocoa culture in municipalities in this region indicated that the cocoa crisis at the end of the 1980s was not as intense as in the South of Bahia, as, among other reasons, cocoa culture in Recôncavo Sul was intercropped with food crops, differently to the cocoa monoculture in other regions [33]. On this point, it has been suggested that there is a relationship between agricultural crop diversity in a determined region and cushioning of the cocoa crisis.

The Litoral Sul region, the largest cocoa-producing region of Bahia and the most traditional cocoa culture, had a negative growth rate in both periods (**Table 3**). In this region, one of the factors that affected the decrease in production was alteration of the agrarian structure between 1988 and 2017. The cocoa crisis intensified agrarian processes with occupations of farms, the creation of settlements, and some of the old cocoa farms being taken over by squatters [11]. In this context, these small producers were unable, for various reasons, to achieve the level of production of the old farms and maintain the necessary farming practices.

In general, in the 1988/1999 period, all the regions had a negative growth rate for the productivity indicator (**Table 4**). The literature indicates that from the 1990s there was a decrease in productivity of the cocoa crop in Bahia associated with the reduction in agricultural credit, which hampered the use of inputs and farming practices by the farmers [27]. In addition, the witches' broom outbreak at the end of the 1980s also contributed, as it negatively impacts cocoa productivity [23, 34].

In the 2000/2019 period, it was found that only the Litoral Norte and Litoral Sul regions had a positive growth rate for productivity (**Table 4**). Regarding the Litoral Sul region, it should be highlighted that the action of research centers installed in the region may be related to this growth in productivity. CEPLAC, for example, invested in genetic improvement of the cocoa tree in seeking to overcome witches' broom and improve productivity. The renovation of crops with resistant cultivars was implemented and spread among farmers, being indicated as the measure that most created the real possibility of crop recovery [30]. In recent years, superior varieties resistant to witches' broom, if well managed, can reach over 1000 kg/ha/year [35].


### **Table 4.**

*Productivity growth rate of the cocoa tree crop in regions of Bahia (1988–2019).*

### **4. Conclusions**

Up to 2019, cocoa production was present in 26% of the municipalities in the state of Bahia, distributed across 60% of the economic regions. The analysis also demonstrated that between 1988 and 2019, the number of cocoa-producing municipalities increased from 95 to 112, growth of around 17%. These data express the resilience of cocoa culture in Bahia, given the crisis caused by a combination of events at the end of the 1980s.

Examination of the harvested area, production, and productivity indicators indicates that the cocoa culture crisis considerably affected cocoa activity in the state. Comparing 1988–2019, the harvested area decreased 30.7%, production fell 65.4%, and productivity was reduced by 50.1%. These numbers demonstrate the extensive scale of the problem and indicate the need to confront the cocoa crisis on various fronts.

Among the cocoa-producing regions of Bahia, the highest percentages of cocoaproducing municipalities are in Litoral Sul, Extremo Sul, and Recôncavo Sul, with 98%, 85%, and 60%, respectively. This demonstrates the importance of cocoa culture as an agricultural activity that identifies these regions and generates revenue. This merits attention from government bodies connected to agriculture, through decentralized regional development policies and actions. The Chapada Diamantina, Médio São Francisco, and Oeste regions should also be highlighted for beginning cocoa production in areas outside the humid climate zone, which may constitute a promising expansion of cocoa culture with the potential to generate jobs and revenue.

Data analysis on a regional scope also demonstrates that in six economic regions the data separate, or tend to separate, two periods, from 1988 to 1999 and from 2000 to 2019. In the first period, the harvested area, production, and productivity indicators have higher numbers, although they decrease with the deepening of the events that caused the crisis. In the second period, there is the implementation of cultivars resistant to witches' broom and the adoption of new management and production techniques, combat measures that are related to the behavior of the indicators. In the Recôncavo Sul region, the data do not present an apparent separation between the two periods, which indicates that in this region the harvested area, production, and productivity indicators were affected differently by the crisis in comparison to the other regions.

It is concluded that decades after the cocoa crop crisis in Bahia, there remains the challenge of increasing levels of production and productivity, expanding the crop to new regions, and recovering traditional producers.

### **Acknowledgements**

The authors would like to thank the State University of Santa, through the Graduate Program in Development and the Environment, and the State University of Southwest Bahia.

### **Conflict of interest**

The authors declare no conflict of interest.

*Cocoa Production and Distribution in Bahia (Brazil) after the Witch's Broom DOI: http://dx.doi.org/10.5772/intechopen.112199*

### **Author details**

Hélio Rocha Sousa Filho1 \*, Marcos de Almeida Bezerra2 , Raildo Mota de Jesus1 and Jorge Chiapetti1

1 State University of Santa Cruz, Ilhéus, Brazil

2 State University of Southwest Bahia, Jequié, Brazil

\*Address all correspondence to: hrochasousa@gmail.com

© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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### **Chapter 5**

## Challenges and Opportunities for Indonesian Cocoa Development in the Era of Climate Change

*Kurnia Dewi Sasmita, Edi Wardiana, Saefudin, Dibyo Pranowo, Asif Aunillah, Nur Kholilatul Izzah, Maman Herman, Nur Kholis Firdaus, Iing Sobari, Sakiroh and Dewi Listyati*

### **Abstract**

In recent years, the area of cocoa plantations in Indonesia has tended to decline, one of which is attributed to climate change that threatens the sustainability of production; even though cocoa production and consumption have become popular globally, the consumer demand for cocoa products has also increased. Climate change causes increased air temperature, erratic rainfall patterns, increased sea level and surface temperature, and extreme weather. Cocoa requires an ideal rainfall of 1500–2500 mm/year and dry months (rainfall <60 mm) for about 1–3 month a year. Climate change can be a challenge for Indonesian cocoa development. Several efforts should be made to turn existing challenges into opportunities through appropriate technological inputs, such as the use of improved cocoa genetic resources (recommended clones) as well as improving nursery and field management practices, including shading and watering the seedlings, modification of growing media, mycorrhizal application, rainwater harvesting, and managing shade plants and intercropping.

**Keywords:** cacao clone, growing media, harvesting rainwater, intercropping, mycorrhiza, shading, watering

### **1. Introduction**

Indonesia is one of the world's largest cocoa producers. Most of Indonesia's cocoa (about 80%) is cultivated on smallholder plantations (SP), while a small portion is owned by the state (government plantations (GP)) and private plantations (PP). Over the past 5 years, Indonesia's cocoa bean production has decreased from 270,000 tons in 2017 to 170,000 tons in 2021. This has resulted in Indonesia's ranking as the world's fourth largest cocoa producer dropping to seventh after Côte d'Ivoire, Ghana, Ecuador, Cameroon, Nigeria, and Brazil. One of the main causes is the global climate change [1].

Based on data [2], in the last 10 years (2013–2022), Indonesian cocoa has faced the problem of decreasing planting area. The average rate of decline in the area of Indonesian cocoa plantations has reached 1.80%, and based on the plantation conditions, immature young plants have decreased drastically, around 6.62% per year. Even though the reduction in the area does not have much impact on national cocoa production, this trend will pose a significant threat to the development of Indonesian cocoa in the future. However, during 2013–2022 there was a slight increase in production (0.96% per year) due to an increase in harvested area, although the productivity remained below 1 ton/hectare/year (**Figure 1**).

Many factors affect the decline in the area and productivity of Indonesian cocoa, one of which is due to the impact of climate change. The effect of climate change on cocoa growth and production is very significant because cocoa cultivation is highly dependent on climatic conditions. This impact affects not only Indonesian cocoa but almost all cocoa plantations in the world. Previous studies in Ghana and Côte d'Ivoire showed that due to the impact of climate change, there would be a significant reduction in the extent or size of suitable lands for cocoa for estimates until 2050 [4]. The impact of the 2015–2016 El Niño on cocoa in Brazil caused high plant mortality and a severe decline in production [5]. Therefore, the impact of climate change on cocoa has become a global concern; on the one hand, world cocoa production tends to decrease, while on the other hand, consumer demand continues to increase.

Climate change causes an increase in air temperature, erratic rainfall patterns, an increase in sea surface temperature and sea levels, and extreme weather. These changes affect not only environmental factors related to plant physiological aspects [6] but also the aspects of the diversity and spread of pests and diseases. Climate change is an important factor affecting the quality of cocoa beans. A long dry season leads to a smaller size of cocoa beans, and the flowers easily wilt or fall off [7], and an increase in temperature in the cocoa planting area accelerates the fruit ripening process, resulting in imperfect flavors [8]. In addition, climate change affects pests' life

**Figure 1.** *Productivity of Indonesian cocoa, 2003–2023. Source: [3].*

*Challenges and Opportunities for Indonesian Cocoa Development in the Era of Climate Change DOI: http://dx.doi.org/10.5772/intechopen.112238*

cycles, which indirectly affect the growth and production of cocoa. The intensity of cocoa pod disease attacks increases due to climate change [9]. In Brazil, the spread of the fungus *Phytophthora palmivora*, which causes black pod disease in cocoa, increases during the more intense rainy season and higher temperatures [10]. Moreover, the biological agents controlling cocoa pests are also affected, so the pests become resistant and attack cocoa plants easily [11]. High rainfall will also influence production due to low solar radiation, thereby reducing the number of flowers and delaying fruit ripening [12]. Therefore, in addition to the need for adaptation through good plant management practices, breeding programs for resistance to biotic and abiotic factors also play an important role [6, 11].

In Indonesian cocoa plantations, the adaptation process to climate changes can be carried out in various ways, including the extensification and intensification programs. However, the options for area extensification programs are rather limited, considering the increasing competition for land use with other sectors. The experience in Ghana and Côte d'Ivoire showed that the optimal altitude for cocoa cultivation is estimated to increase toward the hilly areas. However, this area is included in the protected forest zone. Thus, it will be an obstacle if used for cocoa expansion [13].

This chapter identified the strategy for adaptation of cocoa plantations to climate change and emphasized intensification by improving plant genetic resources and managing plants from the nursery to the field level. In addition, fixing the limitations and deficiencies of land suitability needs to be carried out through appropriate technological inputs.

### **2. Challenges facing Indonesian cocoa in the era of climate change**

### **2.1 Impact of climate change on the ecosystems of cocoa plantation**

Climate change has brought about changes in several climatic elements, including increasing air temperature, changing rainfall patterns, increasing sea surface temperature and sea levels, and extreme weather. Climate changes affect the agricultural ecosystem, including the cocoa ecosystem. Climate changes also impact the degradation of soil quality (physical, chemical, and biological), so it could disturb plant growth, and even many cocoa plants have died. Such conditions contribute to a decline in the number (population) of cocoa plants in Indonesia. Hence, efforts are needed to reduce the negative impacts of climate change through appropriate technological innovations.

### *2.1.1 Increasing air temperature*

Based on the studies, the temperature of the earth's surface was predicted to increase by 2.1–3.9°C due to global climate change [14]. The measurements over 95 years (1901–1995), in the low latitudes of Asia, Africa, and Central America, air temperature increased with variations of less than 1.5°C, while at the higher latitude, their increase was relatively greater [15]. In various regions of Indonesia, there is also an increase in air temperature, which varies from one region to another. Over the past 30 years (1991–2020), temperatures in the Indonesian regions have increased by an average of around 0.9°C [16].

The increase in air temperature is related to the changes in relative humidity and the evapotranspiration rate in agricultural areas, including cocoa plantations. If the

air temperature increases, evapotranspiration increases while the relative humidity decreases. In the dry season, the changes are more significant because an increase in solar radiation triggers them. On the other hand, there is a substantial difference between the temperature of the day and the night. Previous research on cocoa plantations in East Java showed that the increase in temperature within 2–4 months before harvest time had a negative impact on production [17]. Similarly, in Gunungkidul, Yogyakarta, the changes in air temperature are one of the factors affecting fluctuations in cocoa yields [18].

### *2.1.2 Extreme weather events: Changes in rainfall, increasing temperatures, and rise in sea levels*

One of the effects of climate change is that rainfall patterns become irregular, making the wet and dry seasons more erratic. At the same time, one area may experience drought, while another area will experience flooding and landslides. Prolonged drought will cause forest fires and trigger soil degradation, reducing soil fertility and killing various soil microorganisms. The final impact of these problems will result in reduced agricultural land that is considered suitable for certain commodities, including areas for cocoa cultivation.

Cocoa plants only require dry months (rainfall <600 mm/month) for 1–3 months. Therefore, the occurrence of prolonged dry months due to the impact of climate change will reduce cocoa production and quality. Dry months for 1–6 months before harvest reduce the cocoa pod quality in Sukabumi, West Java [19]. Meanwhile, decreased rainfall 2–4 months before harvest has negatively impacted cocoa production in East Java [17]. In 2019, a prolonged drought in Lampung reduced the number of cocoa pods, even causing crop failure [20]. Drought stress reduces vegetative growth, plant biomass, relative water content, leaf chlorophyll content, and nitrate reductase activity, while leaf phenol and proline content increased [21]. Drought stress also reduces mesophyll thickness, leaves, and abaxial epidermis, affecting the stomata's density and closure [22]. Other studies have shown that the number of dry months was correlated positively with the severity of vascular streak dieback (VSD) disease [23].

On the other hand, excessive rainfall causes soil erosion, flooding, and landslides. Soil erosion causes a decrease in soil fertility, which reduces the productivity of cocoa plants. Floods will damage cocoa plantations at low and medium altitudes. In addition, the landslide risk can occur because cocoa is generally intensively cultivated in low to medium altitudes (0–700 m above sea level (asl)). In addition to heavy rainfall, flooding will damage cocoa plantations in the coastal areas due to rising sea levels caused by climate change. During excessive rainfall, the spread of cocoa disease caused by *Phytophthora palmivora* and *Ceratobasidium theobromae* is relatively faster. The rainfall factor causes fluctuations in cocoa yields in Gunungkidul, Yogyakarta [18].

Another impact of climate change is extreme weather, which causes heavy rains, strong winds, and high waves in water areas. The indirect effect of extreme weather is reduced biodiversity, such as pollinators, birds as seed dispersers, and populations of natural enemies for pests and diseases [23]. The effect of La Niña in 2016 reduced the number of cocoa pods in Bali, and the vegetative growth of plants appears to be more dominant than the generative growth [24].

### **2.2 Development of Indonesia's cocoa area and production, 2013-2022**

The total area of Indonesian cocoa during the last 10 years (2013–2022) has decreased by 1.80% per year. The sharp decline occurred in government plantations *Challenges and Opportunities for Indonesian Cocoa Development in the Era of Climate Change DOI: http://dx.doi.org/10.5772/intechopen.112238*

### **Figure 2.**

*Development of Indonesia's cocoa area (ha) during 2013–2022 based on ownership status. Source: [2].*

(GP) and private plantation (PP) by 28.33 and 11.33% per year, respectively. Smallholder plantation (SP), which dominates Indonesia's cocoa population, has experienced a decrease in land area but is relatively smaller than those of GP and PP, which is around 1.37% per year (**Figure 2**).

**Figure 3** shows that the area of mature plants (MP) increased by 1.99% per year. In line with the increasing plant age, many plants changed their status. Initially they

**Figure 3.**

*Development of Indonesia's cocoa area (ha) during 2013–2022 based on planting status. Source: [2].*

**Figure 4.**

*Development of Indonesia's cocoa production (tons of dry beans)) during 2013–2022 based on ownership status. Source: [2].*

were categorized as immature plantations (IMP), then changed to MP. However, the increase in MP number was not proportional to the decrease in IMP (about 6.62% per year), even though the damaged plant (DP) decreased by 2.71% per year. It indicates that during the last 10 years (2013–2022), many young cocoa plants have died before entering their production period. The declined area of DP is caused by the death of many plants, causing a decrease in the total area. This phenomenon will threaten national cocoa production in the next few years.

Many factors contribute to the high rate of decline in IMP, such as stress on the biophysical environment due to changes in climatic conditions. Cocoa plants that are stressed by the biophysical environment will be very vulnerable to pests and disease attacks, even though control has been carried out. Therefore, it is necessary to take action to suppress and reduce the impact of climate change by manipulating growing environmental conditions and implementing good agricultural practices.

Indonesia's total cocoa production during 2013–2022 increased, although relatively small, by about 0.96% per year (**Figure 4**). The main driver of this increase in production was the increase of MP area, as shown in Table 2. Over the past 10 years, the cocoa production of SP has increased by 1.98% per year. Meanwhile, GP and PP cocoa production experienced a sharp decline of 30.49 and 17.6% per year, respectively. The extent of the SP planting area has contributed significantly to the increase in national cocoa production.

### **3. The technological innovation of adaptation to climate change through good agricultural practices**

Cocoa crop management in the era of climate change requires several adaptation strategies, including the use of drought-tolerant clones, followed by improvements in cultivation management from the nursery to the field level.

*Challenges and Opportunities for Indonesian Cocoa Development in the Era of Climate Change DOI: http://dx.doi.org/10.5772/intechopen.112238*

### **3.1 Drought-tolerant clones**

The use of drought-tolerant clones is the leading strategy in dealing with the phenomenon of climate change. Cocoa clones known to be drought-resistant are Sca 6, Amelonado, TSH 919 [25], KW 163, KW 165, KW 215 [19], KW 641 [23, 26], KW 514, KW 535, KW 619, KW 516 [26], and KW 562 [27].

### **3.2 Management at nursery level**

### *3.2.1 Shading and watering of cocoa seedlings*

Several methods can be used in water-saving irrigation systems in nurseries, such as sprinkler irrigation, drip irrigation, and capillary wick system. Shading of cocoa seedlings using "paranet" made from nylon materials and watering using sprinkler irrigation method at the Pakuwon Agroscience Park, Indonesian Agricultural Research and Development Agency, has been proven to improve seedling growth and save water use (**Figure 5**). Dealing with water shortages for nurseries, especially during the dry season, can be assisted by micro and semipermanent rainwater harvesting ponds (**Figure 6**).

### *3.2.2 Modification of growing media*

Modifying the growing media has been shown to increase the resistance of cocoa seedlings under water-stress conditions. Several ameliorants can be used as growing media for cocoa seedlings, including manure, compost, biochar, sawdust, and hydrogel [28–30]. Using up to 9 g of cocoa pod husk (CPH) biochar per kg of soil and 12 g

### **Figure 5.**

*Shading and sprinkler irrigation for cocoa and coffee seedling at Pakuwon Agroscience Park, in Sukabumi, West Java.*

**Figure 6.** *Micro and semipermanent rainwater harvesting ponds at Pakuwon Agroscience Park, in Sukabumi, West Java.*

of CPH biochar per kg of soil with every 6 days of water frequency increases water use efficiency by 208.8 and 262.22%, respectively, compared to control (without biochar) [28]. In addition, adding compost to growing media increases the height, stem diameter, number of leaves, and root weight of cocoa seedlings [31]. Growing media mixed with sawdust, rice husk biochar, and compost in ratios of 60:20:20 and 60:10:30 recovered cocoa seedlings after water stress [30].

### *3.2.3 Mycorrhizal applications*

Mycorrhizal inoculation in nurseries is crucial because it overcomes the problems of limited nutrition, various abiotic stresses (salinity, drought, extreme temperatures, and acidity), and biotic stresses. Therefore, it is necessary for seedlings to be resistant to environmental stress and soil-borne pathogens [32]. Application of mycorrhiza increases water use efficiency [33, 34], nutrient uptakes [34], and seedling growth of cocoa [34–39]. Mycorrhizal inoculation at the nursery stage is expected to have a positive impact on the growth of cocoa plants in the field.

Research progress (1):

An experiment entitled "The Application of Mycorrhiza and Ameliorants to Improve the Growth of Cocoa Plants in Acid Soil" was conducted in a greenhouse at the Pakuwon Agroscience Park, Sukabumi, West Java, starting in 2022/2023. Cocoa seedlings were planted in the polybags on acidic soil media. A completely randomized factorial design consisting of two factors with three replications was used in this study. The first factor consisted of mycorrhizal and without mycorrhizal applications, while the second factor was the application of ameliorant (dolomite and cow manure) and control. Preliminary results showed that mycorrhizal application in acid soil increases cocoa seedlings' root volume and fresh weight. In addition, cow manure had a better effect than dolomite and control (with or without mycorrhizal application) (**Figures 7** and **8**).

*Challenges and Opportunities for Indonesian Cocoa Development in the Era of Climate Change DOI: http://dx.doi.org/10.5772/intechopen.112238*

### **Figure 7.**

*The effect of mycorrhizal, dolomite, and cow manure on the root volume of cocoa seedlings at 3 months after application in acid soil.*

### **Figure 8.**

*The effect of mycorrhizal, dolomite, and cow manure on the fresh weight of cocoa seedlings at 3 months after application in acid soil.*

Research progress (2):

The experiment entitled "The Application of Mycorrhiza and Ameliorants to Improve the Growth of Cocoa Plants in Drought Conditions" was conducted in a greenhouse at the Pakuwon Agroscience Park, Sukabumi, West Java, starting in 2022/2023. Cocoa seedlings were planted in the polybags. A split plot design with four replications was used in this study. The main plot consisted of two watering treatments, 123 and

61 ml/polybag every 3 days (applied 2.5 months after planting), while the split plot was subjected to the application of mycorrhizal, hydrogel, biochar, cow manure, and control mycorrhizal applied 1,5 months after planting. Preliminary results showed that the watering of cocoa seedlings significantly affects the root volume and fresh weight of cocoa seedlings. In conditions of limited water (watering of 61 ml/polybag), using mycorrhiza added with hydrogel, biochar, or cow manure increased root volume and fresh weight of seedlings compared to the control (**Figures 9** and **10**).

### **Figure 9.**

*The effect of mycorrhizal, biochar, cow manure, and two watering treatments on the root volume of cocoa seedlings at 5 months after planting.*

### **Figure 10.**

*The effect of mycorrhizal, biochar, cow manure, and two watering treatments on the fresh weight of cocoa seedlings at 5 months after planting.*

*Challenges and Opportunities for Indonesian Cocoa Development in the Era of Climate Change DOI: http://dx.doi.org/10.5772/intechopen.112238*

### **3.3 Crop management at the field level**

Crop management at the field level is focused on three main activities, such as: (i) harvesting rainwater by constructing water storage ponds, (ii) shading cocoa to reduce the effect of solar radiation and high temperatures, and (iii) reducing the evapotranspiration rates by planting intercrops or cover crops.

### *3.3.1 Harvesting rainwater*

The technology for rainwater harvesting is through making ponds, channel reservoirs, and "rorak" systems (sediment pits). Making ponds for cocoa planting is more directed to meet water needs at the start of planting when cocoa's sensitivity to water is limited. The ponds are simple in their construction and size, so it applies to the farmer's level (**Figure 11**). In large cocoa planting areas, permanent ponds of a larger size are needed so that they can serve the existing cocoa population. In this case, the role of the government is very much needed considering the cost of building such a reservoir is very high. Meanwhile, during the dry season when the water starts to decrease, the rorak can function to accommodate organic matter sourced from the pruning of cocoa plants, shading plants, or cover crops. Mowidu and Endang Sri Dewi [40] stated that using rorak in cocoa cultivation increases the total nitrogen (N) and phosphorus (P) available in the soil.

### *3.3.2 Shading cocoa*

Cocoa is a shade-demanding crop that requires shade crops, with only about 60–80% of the solar radiation necessary for growth. Without shade crops, cocoa yields can be increased in the short term, but in the long term, the sustainability of

### **Figure 11.**

*The simple ponds for harvesting rainwater at smallholder cocoa plantation, Soppeng, South Sulawesi.*

production is threatened. Physiologically, the function of shade on cocoa plants is related to the improvement of microclimate and site conditions (reduction of air and soil temperature extremes, reduction of wind speed, maintenance of soil moisture and water availability, improvement and maintenance of soil fertility including reduction of erosion) and the reduction of solar radiation penetration in both quantity and quality to avoid flushing in cocoa [41]. Therefore, in the current era of climate change, the discussion on the function and role of shade trees for cocoa crops has become a matter of great urgency. Improper management of shade trees will not provide optimal benefits. In fact, it will have a negative impact on cocoa plants. Proper management of shade trees can support growth and increase yields. However, too much shade creates a microclimate that favors the incidence of diseases. Therefore, the selected shade trees should have an architecture capable of transmitting optimal solar radiation for cocoa, their roots should not compete with cocoa for water and nutrients, they should not become host for cocoa pests and diseases, they should be relatively easy to plant and maintain, and they should have a high economic value.

The critical period for cocoa is the young plant stage or initial planting period. Therefore, shade plants should be planted before cocoa, so they can provide shade when cocoa begins to enter production period. In the early stages of cocoa growth, temporary shade plants can use annual or biennial crops such as bananas (**Figure 12**). Bananas have wide canopies that could shade young cocoa plants and maintain adequate soil moisture levels. And for permanent shade perennial crops, such as coconut, areca nut, rubber, *Gliricidia, Albizia*, *Leucaena, Cassia,* or *Erythrina*, can be used. The

*Challenges and Opportunities for Indonesian Cocoa Development in the Era of Climate Change DOI: http://dx.doi.org/10.5772/intechopen.112238*

**Figure 13.** *Mulch from cocoa pruning at cocoa plantations of Pakuwon Agroscience Park, in Sukabumi, West Java.*

research results at cocoa plantations in Sulawesi with *Gliricidia* shade plants showed their tolerance to drought [42, 43].

The increase in air temperature due to climate change requires shade trees to be planted at closer distance. Pruning of shade trees is carried out according to seasonal conditions, where pruning should not be carried out in the dry season to allow the tree to withstand too much sunlight. Pruning of shade trees should be done before the rainy season. The leaves from cocoa pruning can be utilized as mulch to minimize evapotranspiration and as a source of organic matter (**Figure 13**).

### *3.3.3 Intercropping*

Cocoa planted under shade plants is an intercropping pattern. Cocoa is planted between two rows of shade crops, and the distance between the cocoa and shade crops is quite large. This cropping pattern still leaves space between the two crops, so there is still an opportunity to plant other crops as intercrops. Intercropping between cocoa and shade trees suppresses weed growth, reduces evapotranspiration, and can withstand runoff, erosion, and landslides on sloping topography. In addition, planting intercrops will produce various agricultural products, so if properly and correctly managed, it will sustainably increase farmers' income. By planting intercrops on an annual or a biennial basis, results will be obtained quickly, the frequency of tillage will be more intensive, so that the soil's physical, chemical, and biological conditions will always be maintained, and as a source of easy and cheap organic material.

The integration of cacao, shade plants, and intercrops is similar to the cacao agroforestry model that has been widely discussed in the era of climate change. A dynamic cocoa agroforestry system can develop various crops with different life cycles. It resembles multistoreyed cropping systems [44] and high-density cropping systems in coconut [45].

The selection of intercrops to be planted between cacao is based on the microclimatic conditions between the canopies and market opportunities. Some intercrops identified as tolerant and able to adapt well to highly shaded conditions are colocasia, amorphophallus, banana, ginger, turmeric, arrowroot, and kacholam [46]. In addition, the selection of intercrops should also consider the habitus of the trees lower than cacao, the rooting structure of the intercrops should be different from that of cacao, and intercrops should not be hosts to cacao pests and diseases. On the other hand, legume cover crops as intercrops may not provide direct economic returns, but these crops can help fertilize the soil, suppress weed growth, and retain runoff to prevent sloping topography from erosion and landslides. In livestock areas, planting fodder crops as intercrops can easily and sustainably provide fodder, allowing for mixed farming. Research shows that sequential planting of rice and soybean as intercrops under cocoa could improve productivity in the long term [47], as can intercropping with patchouli; even the nutrients given to patchouli plants can be absorbed by cocoa plants, allowing them to grow better than cocoa monoculture [48]. In addition to choosing the right type of intercrops and spacing them appropriately, providing adequate intakes for each combined crop (cocoa, shade plants, and intercrops) will avoid the effects of water and nutrient competition that may occur.

### **4. Conclusion**

The impact of climate change on cocoa production in Indonesia has been highlighted. The rate of decline in Indonesia's cocoa area during 2003–2022 is 1.80% per year, with young cocoa plants declining the most at 6.62% per year. During the same period, the slight increase in production (0.96% per year) is not due to increased productivity but rather to an increase in harvested area. As a result, Indonesia has fallen from fourth to seventh place as the world's largest cocoa producer. To minimize further impacts of climate change on Indonesian cocoa, adaptation strategies through improved crop management are needed. Strategies through extensification programs are still open to opportunities, but these strategies face obstacles because they will compete with other sector development. The intensification strategy that needs to be implemented starts from selecting cocoa clones that are considered drought tolerant, followed by good nursery management through watering and shading, modification of growth media, and application of mycorrhiza to produce planting material with good vigor. Furthermore, at the field level, practices, such as rainwater harvesting technology, optimal management of shade crops, and planting appropriate intercrops, should be promoted for adoption by farmers for sustainable cocoa production. The advantage of yields of intercrops can meet farmers' short-term food and income needs.

*Challenges and Opportunities for Indonesian Cocoa Development in the Era of Climate Change DOI: http://dx.doi.org/10.5772/intechopen.112238*

### **Author details**

Kurnia Dewi Sasmita1 \*, Edi Wardiana1 , Saefudin1 , Dibyo Pranowo1 , Asif Aunillah<sup>2</sup> , Nur Kholilatul Izzah1 , Maman Herman1 , Nur Kholis Firdaus1 , Iing Sobari1 , Sakiroh1 and Dewi Listyati3

1 Research Center for Horticultural and Estate Crops, National Research and Innovation Agency, Cibinong, Bogor, Indonesia

2 Research Center for Agroindustry, National Research and Innovation Agency, Bogor, Indonesia

3 Research Center for Behavioral and Circular Economics, National Research and Innovation Agency, South Jakarta, Indonesia

\*Address all correspondence to: kdsasmita79@yahoo.com

© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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### Section 2
