General vulnerability of Africa

In 2010 Niger experienced a coup where they displaced the government, largely in the support of its people (Guardian 2010, Aljazeera 2010). At the same time, this military government had to tackle problems extending from floods and terrorist activities in their uranium mining region (BBC 2010, Guardian 2010). Additionally, South Sudan is currently in dangers of civil war breakout. According to AFP news (Youtube link 1) and CNN news (Youtube link 2) it has been linked to poor governance. I will use Busby et al (2013) research to extend my discussion on food security and go more in-depth into the general vulnerability of African nations to climate change.  

Component of their model

Source Busby et al (2013)

Busby et al (2013) research looks exactly at this interaction between governance, household resilience, climatic vulnerability, population density and their interaction with vulnerability (fig 1). It is measured in terms of relativity to other African nations. That means nations that are shown as not vulnerable in fig 2, could still be vulnerable compared to other nations outside of the continent   

Last entry, I emphasised one of the ‘threat multiplier’ that is food insecurity. Busby et al (2013)research looks into a range of these threat multiplier caused by climate change-drought, floods, storms-such as dislocation, migration, and competition over scarce resources. In turn these act as threat multiplier that could lead to interstate or/and civil war (CAN 2007). However, their method only uses historic data for all the factors seen in fig 1 and doesn’t take into account future projections.  

source Busby et al (2013)

Results

A number of interesting patterns were from fig 2. Areas that have the highest composite vulnerability appears in DRC, Guinea, Sierra Leone, Somalia and South Sudan. More interestingly, Busby et al (2013) used their method to find the causes of vulnerability for the above countries.

·        Common to DRC and Somalia is the fact that vulnerability largely driven by low household resilience and poor governance. Additionally, DRC is also exposed to droughts in the north and wide fire in the South. 

·        In West African countries, Guinea and Sierra Leone, their vulnerability is large driven by climatic security concerns. More than 6% of Guinea’s area is located in the most vulnerable score, while more than 10% of Sierra Leone’s population live in extreme vulnerability. The cause of vulnerability was found to be high population density and low household resilience.

·        In Somalia, although climatic vulnerability is moderate, vulnerability is found to be exasperated by low household resilience and “terrible governance”, which represented 30% of the overall vulnerability score.

·        For South Sudan, their result showed that governance and physical exposure is the main driver of Sudan’s vulnerability. 

Figure 3 is a composite of 4 different maps that has the weighting of the 4 variable discussed changed (from equal weighting to 40% and 20% for the other three variables).  It shows although the weighting was changed, the above listed countries are still deemed the most vulnerable in Africa and with a few others like Ethiopia and Niger etc.

source Busby et al (2013)

More importantly, this piece of research gives a lot of insight into how policy maker could target specific areas of needs so that it could be targeted to reduce vulnerability in the future. This research represents a worrying future. Those who are exposed most to the climate changes in North Africa are less vulnerable when governance and resilience is taken into account. On the other hand, the above four countries although have less physical exposure have higher vulnerabilities when governance and resilience is taken into account.

 

Source Transparency international 

Since future projections isn’t taken into account we should also ask ourselves what kind of other factors could lead to the worsening of governance and household resilience in the future. In turn, how it would lead to greater/lesser vulnerability in the future. As mention in the last entry, food insecurity (induced by climate change) is likely to increase in certain countries and would act as a threat multiplier. The outlook for improve governance and household resilience is low. Most of the countries in Africa are not likely to meet their MDG goals which strongly effects household resilience (MDG 2013). The CPI 2013 as shown in fig 4 also gives a bleak image of good governance; many of the countries are perceived to be highly corrupted in 2013. When government budget goes disappears public investments are likely to suffer. That could contribute to reduction in resilience since early warning system for wild fires or plans to improve water supply cannot be implemented. This could suggest if future projections are taken into account by Busby et al, the levels of vulnerability could be even higher.  Although it might not be true, I think here is a strong case that current countries with poor governance will likely to experience societal disorder. Cooch (2013; Ted video below) also make an interest case study which highlights the problem of corruption about Equatorial Guinea and how its vast oil wealth have not led to elevation of poverty despite (the ted video would give more insight into corruption).   

The above have showed countries that have low levels of resilience, induced by a whole range of factors which was captured within the modelling. In turn, the maps can be indicators of where future societal disorder would rise because these countries lacks economic, social and governmental ability to compact the direct and indirect effect of climate change.