The potential impact of climate change upon our cocoa supply chain


Article written by Ryo Kurashina, Data Scientist, ECOM Research 



Growing ‘suitability’ of existing cocoa acreage is projected to decrease under climate change


The ECOM Research department conducted a study into the potential impact of climate change upon our cocoa supply chain.  Modelling across 12 cocoa origins has shown the growing suitability of existing cocoa acreage is projected to decrease under  realistic IPCC climate change scenarios.


Why is this important?

A cocoa farm's suitability provides insight into the available land area for cultivation. Anticipated changes in a farm’s suitability underscores the need to measure and assess it, facilitating the development of effective intervention strategies. This approach enables us to proactively help to mitigate potential adverse effects on our supply chain.


What’s driving the decrease in cocoa suitability?

The release of CO2 into the atmosphere through the burning of fossil fuels is set to bring a marked shift to our planet’s environment in the coming decades. Under a realistic ‘medium’ emissions scenario, average surface temperatures at origin are set to rise at a rate of 1°C every 30 years. Rainfall on average is also set to decrease but these values were found to vary more widely. 


Fig. 1: Projected mid-century change in cocoa suitability for West Africa.


We found that this combination of increasing temperatures, particularly in the warmest quarter of the year, and decreasing annual rainfall creates an environment under which cocoa is not expected to grow as productively as it does under current climatic conditions. This signal is much clearer in West Africa than it is in South America, which likely explains the larger projected decrease in cocoa suitability. 


How did we come to this conclusion? 

Harnessing high-resolution climate data, the known locations of cocoa farms and machine learning techniques, we were able to build a picture of the cocoa  growing ecologies in West Africa and South America. This was done by training a machine learning model  to ‘learn’ the favourable climatic conditions in which cocoa grows. For example, how much annual rainfall does cocoa need? What temperatures does it prefer to grow in? This is all information that may be  extracted by the model during the training process.


Fig. 2: Projected mid-century change in cocoa suitability for South America. Note most of the areas of increased suitability lie away from the known cocoa farms locations.


Currently, 85-90% (1) of farms are classified by the model as ‘suitable’ to grow cocoa in West Africa and South America. We found that the suitability of most of these farms is projected to decrease under climate change (see Figs. 1 and 2). In both Côte D’Ivoire and Ghana, a consistent reduction in suitability is observed owing to the uniformity of climate within the cocoa-growing regions (Fig. 1).


In Peru and Ecuador, the picture is a little different due to the variations in climate attributed to the presence of the Andes. Despite large areas of suitability increase projected, most of the farms in our supply chain are still expected to decrease in suitability (see Fig. 2). 


Is it all bad news?

Not necessarily. Our analysis assumes a zero intervention strategy. Hence, under the correct actions, such as increased canopy shade and irrigation, many of the negative consequences that are currently projected may be mitigated. In addition, there is ongoing research that suggests that some of the projected suitability decrease may be offset by the increase in CO2 concentrations in the atmosphere (2). However, it is important to note that research into this hypothesis is still in its early stages and more work is required to verify these ideas.


This article is a summary of the full report that ECOM Research produced with respect to cocoa suitability.  Further detail is available upon request.


ECOM RESEARCH: Richard Puddifoot (Head of Research); Laurent Souron (Cocoa); Digby Beatson-Hird (Coffee); Roberto Ruiz (Cotton); Juan Beltran, Ryo Kurashina, Darrell Hoffman (Data Scientists)


(1) Given perfect knowledge of all cocoa farms, this value would be equal to, or very close to, 100%. However in practice this is never the case due to incomplete data. Hence, a model such as this will always misclassify some farms as unsuitable.

(2) Black, Emily, et al. "Cocoa plant productivity in West Africa under climate change: a modelling and experimental study." Environmental Research Letters 16.1 (2020): 014009.



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