UBC School of Journalism Data Visualization

The map “Horn of Africa Conflict Incidents and Location” shows an information about conflict – small and big – taking places in Somalia, Kenya, Djibouti, Eretria and Ethiopia   for the last 13 years (1997 – 2010)

http://www.google.com/fusiontables/DataSource?dsrcid=3470676

There are also 5 graphics that show how the aid flows during a conflict.

Jeffrey Gettleman wrote about the food crisis for The New York Times, noting that “this is what happens, economists say, when the global food crisis meets local chaos.” With rising commodity prices, rising food costs and civil war tied to an extremely dry climate, people living in the Horn of Africa were dying at a shocking rate. While there is food being produced in the area, it is almost all being exported – leaving the local population to starve. Ethiopia, for example, is Africa’s second biggest producer of maize. But where is it all going? If food is being produced in Africa, why are so many people starving?

According to data and reports, about 70 to 80 per cent of food produced in the Horn of Africa is exported out of Africa. The opposite is true in Canada, who only exports about 7 to 10 per cent of food produced. So while we reap the benefits of this exported food, here in North America, those who live in the countries from which we receive the food, suffer.

Between rising food costs, conflict, rising fuel costs and, of course, drought more and more people have been displaced.

With Somalia and the Horn of Africa on the brink of famine, a larger look at how drought and food scarcity—two of the factors defining famine—show that much of Africa faced the same perils in the year leading up to the current crisis.

The Horn of Africa is not the only region with limited quantities of freshwater available, but issues of access are compounded by the violence and conflict brewing in the region as well as and an underdeveloped infrastructure.

https://www.google.com/fusiontables/embedviz?viz=MAP&q=select+col2+from+3440080+&h=false&lat=0.8893160963233157&lng=24.685156249999984&z=3&t=3&l=col2

The crisis in the region is more clearly illustrated by access to food. In 2007,  the amount of calories available per capita per day in Ethiopia was 1979.68, one of the lowest rates in all of Africa. The year’s drought further reduced yields, livestock and crops died and dried up and the percentage of the country’s food exports remained high.

https://www.google.com/fusiontables/embedviz?viz=MAP&q=select+col0+from+3444381+&h=false&lat=5.7908968128719565&lng=19.338111249999997&z=3&t=3&l=col0&y=2&tmplt=2

When foreign development aid comes with strings attached—forcing recipients to spend it on goods and services from donor country—it can double the time it takes the help to arrive. Children have died awaiting such “tied” aid, which also can increase costs by more than 30 per cent.

Understandably, these policies have led to sharp criticism by activists. The decision by the U.S. Agency for International Development (USAID) to untie it’s donations was big news.

To place this decision in context, we plotted data from the OECD showing trends in tied-aid over the past two decades.

Trends in tied aid reported to OECD 1990-2010

You can see Canada’s steady efforts to untie aid since a 2001 meeting of donor countries resolved to end tied aid. Note the U.S.’s lag in following suit and its failure to report tied-aid data for a decade starting in 1995. The gap covers the period when global aid tying policies shifted, and when the US channeled huge sums to reconstruction efforts in Iraq and Afghanistan. Most of this aid was tied.

We collapsed across the EU countries because their policies were similar over the years. Our map allows exploration of some the policy variability that does exist.

Map of average tied aid reported to OECD 1990-2010

Each nation’s average amount of tied aid over 1990 to 2010 is plotted. When you click on a country, its data is shown on a line chart illustrating that nation’s history of tied aid.

Untying aid does not necessarily achieve the desired impact, as the article mentions. For instance, the U.K. had untied nearly 77 per cent of its aid by 2009, yet the vast majority of its procurement contracts are still signed with U.K. companies.

Data from an OECD report [link] allowed us to examine this continuing barrier to getting more development aid spent in recipient countries.

Untied aid reported to OECD vs. aid contracts executed in donor countries

Some of the nations with the highest amount of aid reported as “untied” still end up using companies within their borders to fulfill the majority of their aid contracts. Simply because less aid is coming with strings attached does not translate into investment in the poorest nations of the world.

Finally, food aid, pharmaceutical aid and automobiles were all excluded from the new agreement for USAID. Data at this level of detail is not readily available, but would make for a good target for a Freedom of Information Act request. It is interesting to note that these are all among the most powerful political lobbies in the U.S.

In the Guardian U.K.’s environmental blog, John Vidal, argues that Africa is the continent “must vulnerable to climate change.” November 21^st, 2011, Vidal posted about the relationship between civil war and climate change in Sudan, arguing that combination of issues may escalate issues the country is facing.

Below are data visualizations that we feel would contribute to reader engagement and understanding of Vidal’s article.

To provide the reader with the more context on conflict in Sudan we mapped all of the conflicts that have occurred there in the last ten years.

This map shows the concentration of conflicts allowing insights into which regions are potentially more susceptible to be affected by both conflict and climate change.  It is important to note that data used is from when Sudan and South Sudan were one country.

The map adds context to the story by pinpointing the incidents of conflict by region and specific location (longitude and latitude). Additional context about the nature of the conflict, injuries and battle deaths (part of the Armed Conflict and Location Event Data  set) is available by clicking on the pin point. This information adds to Vidal’s story by adding data to dispute the UN’s assertion that it was primarily climate change and environmental degradation that led to the more than 200,000 Sudanese deaths

To show the relationship between conflict and the environment we wanted to investigate the correlation between  internally displaced people and cereal yield.

Generally,this graph comparison shows that as internal displacement increases cereal yield decrease. We would have preferred to see the relationship between internal displacement and decertification, however, within our research we were unable to find any specific data on decertification in Sudan. The cereal yield was chosen as a substitute because yields are  impacted by issues surrounding climate change such as changing rainfall patters.

Lastly, we have graphed the urban and rural access to improved water sources.

The rate of access to improved water sources is has decreased by 21 per cent over an 18 year period. Though more drastic in the urban environment, this visualization shows that the water access is decreasing in both rural and urban settings. Water access could be impacted by both climate change and conflict. Though it is hard to conclude how either one, or both, are impacting this data, it clear that Sudan’s population – especially in urban centres – is facing the consequences of a water crisis.

By Alberto Mendoza Galina and Meg Mittelstedt

In the article “Sudan – battling between forces of civil war and climate change” John Vidal shows two main approaches to explaining civil conflict in Sudan: one focused on climate change and food security and the other one founded on governance issues triggered by historical tensions, proliferation of arms and lack of democracy.

While Vidal indicates that conflict in Sudan is a complex issue, his main assertion is that climate change is exacerbating the conflict.

We found data to evaluate his assertions, which we have presented below in several visualizations.

We examined three different variables related to food security: agricultural food production per capita, food consumption per capita expressed in kilocalories consumed per day and an indirect measure of food availability, also known as food security, which is the prevalence of undernourishment shown as percentage of the population.

Graph 1. Sudan Indicators on Food Security

Graph 1. Sudan Indicators on Food Security

Graph 1, Sudan Indicators on Food Security, shows a comparison of different indicators of food production, per capita food production and prevalence of undernourishment in percentage of population between 1992-2010.

Despite the article’s assumptions that civil war is caused in part by climate change and food security issues, the trend in food production per capita and food consumption per capita is on the rise in Sudan. Furthermore, data indicates a steady decrease in undernourishment prevalence in Sudan, from almost 40 per cent of the population being undernourished to 22 per cent by 2007. All these indicators point to food being more available. This data does not support food security as one of the determining factors of Sudan’s civil war.

However, on the other hand, the Sudan Battle Deaths by Arable Land table may tell a different story. According to this data, the number of deaths in civil war increases in years where there is less available arable land. In general, from 2002 onwards, arable tends to increase in Sudan, and battle deaths decrease.

Graph 2.- Sudan Battle Deaths by Arable Land.

Graph 2- Sudan Battle Deaths by Arable Land.

The increase in arable land may explain the increased trend in food production and food supply demonstrated in Graph 1, as well as the decrease in undernourishment. However, it also demonstrates that climate change (which should reduce available arable land) and food security do not explain the full story of conflict in Sudan. There must be other variables involved.

Map 1. Sudan Conflicts 1989 – 2007

Map 1. Sudan Conflicts 1989 - 2007

This Google map shows the locations where conflicts occurred in Sudan indicating the groups involved: whether militia, rebel groups or civilians between 1989 and 2007.

The map shows that the highest concentration of battle deaths and actual clashes occurred in southern Sudan, including the border regions with Chad, Central Africa Republic, Uganda, Ethiopia and Eritrea.

In his article “Food speculation: ‘People die from hunger while banks make a killing on food,’” John Vidal argues that deregulated speculation in commodities — which began in 1991 when the Commodities Futures Trading Commission (CFTC) secretly granted 19 banks exemptions from hedging regulations — is increasing global food prices and contributing to hunger. According to the article, the most tangible effects of this were first felt in 2008 when, during the global financial crisis, unprecedented food speculation activity caused excessive fluctuations in commodity prices.

We have created a number of visualizations to illustrate the discussion about deregulation in commodities speculation and its effect on food prices and hunger.

MAP

In Vidal’s article, he suggests that western Malawi “went hungry” in 2008 even though “there had been no drought…there was plenty of food in the markets…and there was no evidence that the local merchants were hoarding food.” Even so, Vidal writes, “there were food riots in more than 20 countries.”

Our map visualizes where food riots occurred in Africa — the country most affected by the 2007-2008 “world food price crisis.” Users can click on each affected country and learn what happened during each riot and what the principle causes were. In many cases rising food prices caused the riots. The map does not, however, show what caused the spike in food prices.

GRAPHS

In order to show the relationship between commodities speculation and rising food prices, we gathered investment data from the U.S. Commodity Futures Trading Commission (CFTC) and commodities price data from IndexMundi.com.

The first graph displays the commodity prices of cereals between 1997 and 2012, and clearly shows massive price increases in 2008 and continued fluctuations since then.

The second graph displays that heightened activity in commodity futures investing since 2008 corresponds quite closely with the fluctuations in commodity prices.

In Sudan – battling the twin forces of civil war and climate change, Guardian blogger John Vidal argues that deep-set tensions between hostile groups have flared into full conflicts in the country as a result of food shortages caused by climate change.

To investigate the effects of rainfall changes on food supply, we visualized changes in main crop yields over the past 20 years as the climate has become more unpredictable (click the image for the interactive version):

Food supply, while showing peaks and troughs, actually seems to show a trend towards increase in the past 20 years.

So, has conflict actually increased over these past 20 years? We compared arms imports to GDP to see if Sudan was spending any extra income on conflict:

(Although it’s difficult to tell in this screenshot, the interactive version shows sporadic spending, with a peak in arms imports in 2004)

To summarize the connection between climate change and conflict, we produced a map of precipitation change (1990s average compared to average from 1911-1951) and major conflict zones in Sudan:

Marker colour code: Red: -30 to -21% rainfall change; Yellow: -20 to -11; Blue: -10 to 0; Green: positive rainfall change.

It’s hard to draw solid conclusions from this. What we had originally envisioned was comparing desertification with conflict zones, but data on the encroaching desert was impossible to come by. While precipitation change seems like a worthy proxy for desertification, the climatic factors that contribute to a drying land are many and varied. The timing of precipitation, the severity and the associated temperature are all contributing factors.

by Kyle Farquharson and Golnaz Fakhari

To complement the article entitled “India’s Malnutrition Dilemma”, by David Rieff, which appears in the online edition of The New York Times Magazine on Oct. 8, 2009, we have included a map and three data sets that illustrate the scale of the hunger crisis in India, and compare the issue of malnutrition in that country to a similar problem in China. Rieff draws the same comparison in his article.

India State Hunger Index

Data from India’s State Hunger Index, plotted as a bar graph on Many Eyes, underscore the severity of the predicament at the state level.

The Index examines three factors among children surveyed: 1) the prevalence of calorie undernourishment; 2) the proportion of underweight among children under age five; and 3) the mortality rate (deaths per 100) of children below five. These data sets combine to generate an Index Rank. As you will notice, of the 17 states surveyed in compiling information for the Index, Madhya Pradesh, near the geographic centre of the subcontinent, appears to be most severely afflicted by hunger.

We have also presented the ISHI figures in map form, below.

China’s Per-Capita GDP and Food Production

Like its comparably populous neighbour to the southwest, China has experienced rapid economic growth over the last two decades. However, the Chinese have largely managed to overcome the significant challenge of malnourishment, while India continues to struggle in that regard.

As you will note, while per-capita GDP in China has increased at a bullish pace, a rise in food production has been almost commensurate with the country’s economic growth, as the slope of both bar graphs is relentless.

India’s Per-Capita GDP and Food Production

This graph, whose focus is India, tells a different story. While food production and per-capita GDP have grown commensurately and consistently in China since 1990, India has experienced several instances of regression in its food supply over the same period. In the decade prior to the 21st century, the ability of the South Asian nation to nourish itself grew quite robustly, like its economy. However, from 1999 to 2000, food production decreased. And despite substantial gains on the nutrition front the following year, 2002 saw another substantial decline. Since the turn of the 21st century, nutrition in India has undergone a bumpy and inconstant climb, in keeping with the situation Rieff describes in his feature story. As Rieff contends, India has managed to virtually eradicate famine, but struggles to deal with endemic malnutrition, possibly because the former represents a more urgent conundrum than the latter.

Prevalence of Undernourishment in Subsaharan Africa

 

In 2008 the price of food on the world market escalated to previously unheard of highs. This caused a food crisis in many of the world’s poorest countries.

John Vidal reports that the food price spike was not attributable to any reductions in the food supply. In fact, there was plenty of food to go around – prices were just too high. Vidal argues that the cause of this price inflation was rampant speculation in the commodity markets.

For some reason, the markets were spooked in 2008. This scare led traders to speculate that food would be in tight supply.  The more the traders speculated, the higher the prices spiked causing a feedback loop that led to a price bubble. A bubble that was not based on any actual food shortages.

The conditions that led to the price hike in 2008 are again present in the commodity markets.

World Commodity Food Prices

With no discernible food shortages in 2008, a look at the historical trading data can show the correlation between trading volume and prices.

Since the U.S. corn market is the world’s largest, it is a good model to show the 2008 speculation at work.

The U.S. corn supply data shows a steady increase in corn supply for the last decade. Historically, an increase in supply would correlate to a decrease in price. However, the corn data shows the 2008 price spike occurred while there was substantial supply in the market.

The volatility data gives some insight into the reason for the price spike. High volatility in the market shows a high trading volume.  The spike in volatility for 2008 reveals the market conditions that were at play with the record volumes of corn traded.