The Story From Across the Pond

There are so many stories that get played out on the legal stage and the stakes are highest when death is involved. I found two graphics each of which attempted to provided an overview of the death penalty in America. We start with the view from London (though the writer of the article was in New York while he was writing).

The Death Penalty in the US - An Overview with an emphasis on Texas
The Death Penalty in the US - An Overview with an emphasis on Texas

The graphic they’ve come up with over at The Independent does a great job of summarizing the story of the death penalty in the US. The best part of this graphic is the right-most graph showing that the states with the death penalty started with lower murder rates and *still* have lower murder rates than those states that have the death penalty. Murder rates in both types of states change over time, but those changes seem to be largely independent of the death penalty. Great way to show that the death penalty does not make a good deterrent.

One last notable point from this article is that the graphic seems to do a better job at representing “just the facts” than the text. From the other side of the pond, the continued use of the death penalty in the US looks, well, barbaric beyond anachronism.

From Usborne writing in The Independent: “China tops the world’s executions league table (officially it used the death penalty 470 times last year, though Amnesty International believes the true figure is far higher), followed by Iran and Saudi Arabia. Among developed industrialised nations, only the US, Japan and South Korea persist in retaining capital punishment. None of the United States’ European allies entertain it nor do its neighbours, Mexico and Canada.”

In case you aren’t accustomed to decoding dry British writing, it is most certainly not a good thing to fall into the same category as China or Iran when it comes to human rights.

The Story from the Backyard

Not to be outdone, the New York Times has also run a number of graphics about the death penalty which is a recurrent topic of popular and academic debate.

Death Penalty Overview - The New York Times
Death Penalty Overview - The New York Times

Here’s where the difference between the US depiction and the UK depiction starts to stand out. The UK added up all the executions since 1976 which tends to imply a great magnitude of death. There’s a big red 409 over Texas in their graphic and ‘just’ 20 in the NYTimes graphic, because the Times took a statistician’s more favored approach of looking at the number of death sentences per 1,000 murder convictions. This makes it easier to compare state by state data because it acts as a control for population size and murder rate. In this version, Oklahoma, Nevada, and Idaho appear to be more invested in the death penalty than Texas. Don’t mess with Texas becomes don’t mess with Nevada. (I guess what happens in Vegas really does stay in Vegas…but not in a good way).

The NYTimes graphic also looks at the sentencing rates when the race of the victims and perpetrators are the same and when they’re different. The way they’ve simply represented the facts speaks clearly to the continued machinations of racism in America. When whites are the victims, the perpetrators are more likely to be sentenced to death, especially if those perpetrators are black. Look at that part of the chart for a while then think about why the writer from The Independent has such strong negative feelings about America’s death penalty.

The Story from the US – 2003

Juries Reluctant to Give the Death Sentence
Juries Reluctant to Give the Death Sentence

This post is not about how the general population in America feels about the death penalty – check out some of the death penalty blogs listed below for more on public opinion. I was beguiled by this next graphic because it so simply illustrated ambivalence which is not all that easy. Each block is a case, every case has to have only one outcome with respect to death sentencing, and the designer manipulated this binary to produce a picture of declining conviction. Bravo.

The article’s text offered about five competing reasons for the decline in the rate of death sentences applied, including poor representation. They ended with this one:

Alan Vinegrad, a former United States attorney in Brooklyn, said the recent statistics represented something larger.

”It reflects that the tide is turning in this country with regard to attitudes about the death penalty,” Mr. Vinegrad said. ”There has been so much publicity about wrongfully convicted defendants on death row that people sitting on juries are reluctant to impose the ultimate sanction.”

Relevant Resources

About.com’s list of the Top Ten Death Penalty Blogs. Most are not big on graphics or visuals of any kind.

Amnesty International’s Human Rights Now blog which hosts their posts on the death penalty.

The Death Penalty Information Center

Liptak, Adam. (18 November 2007) Does the Death Penalty Deter Murders? in The New York Times. National Section.
–Including this, ““You have two parallel universes — economists and others,” said Franklin E. Zimring, a law professor at the University of California, Berkeley, and the author of “The Contradictions of American Capital Punishment.” Responding to the new studies, he said, “is like learning to waltz with a cloud.””

Liptak, Adam. (15 June 2003) Juries Reject Death Penalty in Nearly All Federal Trials. National Section.

Usborne, David. (7 August 2008) Why is the United States still imposing the death penalty? in The Independent.

Spotting a Hidden Handgun - Graphic by Megan Jaegerman
Spotting a Hidden Handgun - Graphic by Megan Jaegerman

What Works

This is one of my favorite information graphics of all time. A somewhat smaller version of this appeared in the New York Times and was then amended as you see above to appear in Edward Tufte’s book “Beautiful Information”. Since Edward Tufte is seen by many as the king of presenting data visually, I’d say his endorsement is worth far more than mine. Click through the links under Relevant Resources to see what he has to say about this graphic on his blog (which is basically a scan of a page or two from his $52 book). You will also get to see more of Megan Jaegerman’s graphics including the lifecycle of women in the developed world, the price of mowing the lawn, the price of quitting smoking, a complete strength training workout, a guide to rest/ice/compression/elevation after a soft-tissue injury, and sports graphics covering hockey, figure skating, baseball, gymnastics, and diving.

I want you to have time to look at the stylistic conventions she has developed. So follow the first link below.

What Needs Work

Megan disappeared from the graphics scene. Megan, if you’re out there, know that you are missed.

Relevant Resources

Edward Tufte reviews Spotting a Hidden Handgun by Megan Jaegerman.

Tufte, Edward. (2006) Beautiful Evidence. The Graphics Press.

Jaegerman, Megan. (June 1997) Life: Start Here Women’s Health graphic adapted for the web. The New York Times.

Marijuana Arrests in New York City 1977 - 2006 (Harry G. Levine)
Marijuana Arrests in New York City 1977 - 2006 (Harry G. Levine)

What Works

Sometimes simple is powerful. Everything here is well-labeled, the time periods move in even intervals and the source is cited. The point that arrests for marijuana possession have skyrocketed comes across almost instantly.

The graphic is taken from testimony given by Harry G. Levine, Professor of Sociology at Queens College and the CUNY-Grad Center to the New York State Assembly on Codes and Corrections:

“New York City has arrested about 100 mostly young people a day, every day, for the last ten years. By the end of today another 90 to 100 will be arrested. About 85% of the people arrested are Black or Latino, most are working class or poor, from the outer boroughs and from less affluent and poorer neighborhoods.”

Marijuana Arrests in New York 1987-2006 | Whites, Blacks, Hispanics
Marijuana Arrests in New York 1987-2006 | Whites, Blacks, Hispanics

What Works

Levine includes this graphic in his testimony to demonstrate the uneven distribution of all these marijuana possession arrests across racial/ethnic boundaries. He is right to make sure to include a little decoder text about the distribution of whites, blacks, and hispanics as percentages of population of New York overall. Remember that in a world of equal arrest rates, whites would be arrested for possession roughly according to their percentage of the population, which is 36% in New York during the 1987-2006 period. But they were only accounted for 14% of the possession arrests. On the other hand, blacks should have been arrested 27% of the time but instead were arrested 54% of the time. Hispanics were the closest to even, representing 27% of the total population and 30% of the possession arrests.

What Needs Work

These stacked bar graphs always confuse people. So here we can use the y-axis to determine absolute number of arrests by racial/ethnic group but in other uses of this technique I’ve seen the bars all add to 100% and the viewer is supposed to suss out the relative proportion of the bar dedicated to the categorical break down. That clearly is not how this graph works, but still, where there is any chance of confusion, more work needs to be done to clear things up. I might have tried a hint of 3D, popping the white bar in front of the grey bar and the grey bar in front of the black bar just so that each bar reads as a distinct entity.

I would also have stuck the arrestee percentages directly next to the population percents. It would look more like:

Arrestees          Population
Blacks     54%     27%
Hispanics 30%     27%
Whites     14%     36%

Simple to do. Makes much more sense to read that data across rows. I would then have stuck the color shading key to the left of that little table and cut the “blacks arrested”, “whites arrested”, and “hispanics arrested” labels which would have cut down on the total amount of text the viewer would have to read through.

Go ahead and click through to the full report to see the other graphics and read the whole story about the astronomical increase in marijuana possession arrests in NYC with the disappointing follow-on that the arrests are being doled out in minority communities disproportionately more often than elsewhere in the city.

One parting quote to provoke you to jump across and read it all, in response to why there are so many arrests so unevenly distributed across the city’s population, “it is not because of any dramatic increase in marijuana use – which has not changed significantly since the early 1980s. Nor is the dramatic racial imbalance in the arrests the result of marijuana use patterns. In fact, marijuana use among Blacks and Hispanics is lower than for Whites, and has been for decades, as U.S. government statistics show. “

One More Thing

If you’re wondering where all the weed comes from, as I was, you might want to link through to the 2007 article “Home Grown” in The Economist via Proquest (subscription required) which notes in classically dry Economist fashion, “Marijuana is now by far California’s most valuable agricultural crop. Assuming, very optimistically, that the cops are finding every other plant, it is worth even more than the state’s famous wine industry.”

Relevant Resources

Becker, Howard. (1953) On Becoming a Marihuana User originally in American Journal of Sociology Vol. 59 November 1953 (235-242).

Dwyer, Jim. (30 April 2008) On Arrests, Demographics, and Marijuana The New York Times, NY/Region Section.

Levine, Harry G. (May 2007) Testimony before the New York State Assembly Committees on Codes and Assemblies.

Schlosser, Eric. (2003) Reefer Madness: Sex, Drugs and Cheap Labor in the American Black Market. First Mariner Books.

Home Grown: Cannabis in California (20 October 2007) in The Economist Vol. 385, Issue 8551 (60).

Violent Crimes in the USA | Change from 1978-1998
Violent Crimes in the USA | Change from 1978-1998

What Works

This map uses a two color pie chart scheme to represent increases and decreases in violent crime respectively. It also breaks the pie into pieces for added granularity of detail – one for murder, one for forcible rape, one for armed robbery, one for aggravated assault. (also known as mincemeat pie, right?)

What Needs Work

I still think there’s got to be a better way to represent gains and losses on a spectrum. Changing from one color pie to another at zero is a little arbitrary. Three dimensions might help – states with increases in crime could bulge while states with decreases could sink.

I included this graph not so much as a particularly good or bad example of building an info graphic but as a contrast to the previous post. This is a typical depiction of crime mapping. It depicts violent crime by victimization. Most crime coverage focuses on this salacious category – rapes and murders and beatings.

Relevant Resources

Ford, Steve. (2006) Map of Violent Crime in the USA 1978-1998

Mapping the location of crimes committed in Brooklyn, 1998
Mapping the location of crimes committed in Brooklyn, 1998
Mapping the home addresses of the imprisoned population in Brooklyn, 2003
Mapping the home addresses of the imprisoned population in Brooklyn, 2003

What Works

The beauty of these graphics is that, given their captions, they are instantly legible. On the left, the map shows where crimes are committed in 1998. It’s a diffuse pattern with a few warm spots. On the right, the map shows where the imprisoned population calls home (2003 data). It’s an image with vivid hot spots amidst a sea that’s mostly dark. In thirty seconds or less, viewers can see that while crimes are committed all over Brooklyn, the population in prison tends to come from a handful of very localized neighborhoods. It would have been easy, and easy on the eyes, to use two different colors for the different maps, but because this idea works as a comparison, it’s important to keep the color scale the same across both images.

These maps are used as tools of analysis and pattern recognition, helping to make data legible both for the public and for the researchers who use these tools not only as tools for publication but also as tools of analysis. They go further, augmenting these maps with finer grained maps as you’ll see if you keep reading.

What Needs Work

A stronger outline of Manhattan would help non-New Yorkers recognize the location immediately.

More Than Critique

This post reminds us that there are many victims of crime. The authors’/graphic designers write, “If crime maps succeeded dramatically in mobilizing public opinion, redefining the city as a mosaic of safe and unsafe spaces, and forcing the reallocation and targeting of police resources on specific neighborhoods, the gains were short-lived. The resulting crime prevention techniques, and the community-policing movement in general, soon reached the inevitable limits of any purely tactical approach. The city spaces that were targeted came safer, but too often crime incidents were simply displaced to other locations.”

Nobody is denying that being mugged or raped or murdered is fun for the person who was mugged or raped or robbed or murdered. But the report by the Spatial Design Lab at Columbia University sponsored by The Architectural League that uses maps as a tool of analysis and discovery to suggest that because perpetrators live in areas with lots of other perpetrators, those entire communities are also the victims, not of the crimes per se, but of the impact of high concentrations of recurrent incarceration. Convicted people go away to prison leaving these neighborhoods with a gender imbalance (only 12% of the prison population is female). The money spent to imprison this largely male population is not being invested in developing these communities. This study finds a block where $4.4m has been spent to imprison its one-time residents. One block, $4.4m.

Million Dollar Block, Brownsville neighborhood in Brooklyn 2003
Million Dollar Block, Brownsville neighborhood in Brooklyn 2003

The authors pose the question their maps have helped make obvious: “What if we sought to undo this shift, to refocus public spending on community infrastructures that are the real foundation of everyday safety, rather than criminal justice institutes of prison migration?”

Relevant Resources

Spatial Information Design Lab at Columbia University (2006) Architecture and Justice sponsored by The Architectural League.

Spatial Information Design Lab Main Page

The Architectural League

Prisoners of the Census - Prisoners per 100,000 (1925-2001)
Prisoners of the Census - Prisoners per 100,000 (1925-2001)

Crime and Criminal Justice

The theme for this week, in case you haven’t figured it out by glancing at the graphics, is crime, deviance and justice in these here United States. I thought it would be a nice exercise to see what is available from official sources (ie government agencies). In the US, we’ve got the CIA, the FBI, the Bureau of Justice Statistics, and then lots of state and local agencies. I stuck with the feds here but the rest of the week will look at cities and states as the level of analysis. So far, none of the federal agencies has produced a graphic that tells a comprehensive story about incarceration, crime, and/or justice in the US. I couldn’t even find much about the immense expenditures dedicated to incarceration (in a handful of states, more is spent on criminal justice, including incarceration, than on education). There also were very few graphics dedicated to the differential impact of incarceration practices on poor and minority communities.

CIA

The CIA doesn’t do much with graphics, but this is what they had to say about the US and drugs: “world’s largest consumer of cocaine (shipped from Colombia through Mexico and the Caribbean), Colombian heroin, and Mexican heroin and marijuana; major consumer of ecstasy and Mexican methamphetamine; minor consumer of high-quality Southeast Asian heroin; illicit producer of cannabis, marijuana, depressants, stimulants, hallucinogens, and methamphetamine; money-laundering center”

I would love to see this on a map, especially if the map were able to show how much of our illicit habit, by weight, is made in America and how many people and plants in other countries are dying to stock our habits.

FBI

The FBI doesn’t do much with graphics either, but they had this factoid box:

FBI Crime Clock - 2007
FBI Crime Clock - 2007

This is an easy but illogical way to summarize data points. This style of arbitrary ratio style summary misses opportunities to provide context and compelling visuals. X crimes per unit of time seems a strange way to measure; going by victims or convicted criminals by 100,000 people or by percentage of the total population might make more sense. Furthermore, a good information graphic should begin to tell the story at first glance, before you have to read anything. One quick test: if someone who doesn’t speak the language can’t make heads or tails of the graphic, it just isn’t that good. Granted, language is often necessary to pin down the details, but the overall theme should be clear without resorting to text. There’s no way to tell this is about crime in America. Again, I’m always skeptical of these ratio summaries. It’s really hard to understand much about crime by recounting how often it happens. Then smaller populations are going to look safer because crime happens less often even though it might be just as common in terms of the percent of the population who ends up becoming a victim or a perpetrator.

Bureau of Justice Statistics

The Bureau of Justice Statistics had by far the most info graphics though, as you can see, they are all the same style. As for “What Works”, well, it works that they tried to map trends in crime over time graphically. What needs work? Besides the rather uninventive presentation – I think these line graphs are easily understood but so standard in appearance that they risk putting people to sleep – my biggest concern is that there is no overview graphic that tells the whole story. All of these graphs tell one tiny little part of the story and are designed to be read in isolation from all the other graphics. In that sense, they help viewers understand crime and punishment in America about as much as that FBI Crime Clock factoid box does. Information graphics are at their most deceiving when they appear to be depicting simple, straightforward relationships in absence of all the messy real life context that frames just about any problem on the ground.

Bureau of Justice Statistics - Four Measures of Serious Violent Crime (to 2006)
Bureau of Justice Statistics - Four Measures of Serious Violent Crime (to 2005)

Bureau of Justice Statistics - Violent Crime by Gender of Victim (to 2005)
Bureau of Justice Statistics - Violent Crime by Gender of Victim (to 2006)
Bureau of Justice Statistics - Arrests by Type of Drug Law Violated (to 2006)
Bureau of Justice Statistics - Arrests by Type of Drug Law Violated (to 2006)

Bureau of Justice Statistics - Arrests by Type of Drug  (to 2006)
Bureau of Justice Statistics - Arrests by Type of Drug (to 2006)

Just to take one example, the graph showing victims by gender is on the brink of revealing one of the most interesting elements of the bursting incarceration system. Violent crimes are way down but the prisons are bursting indicating that more and more of the people in prison are serving time for property crimes. That’s why I included the arrest rates for drug crimes – the huge majority are for possession, most likely possession of marijuana. It bothers me that I have to throw in little graph after little graph to tell a partial story. I couldn’t even find a little graphic that shows that black folks are far more likely to be arrested for possession than white folks even though white folks are slightly more likely to use (marijuana) than black folks. Community policing gone wrong? Perhaps.

If you know of a graphic that attempts to tell the story of the three-strikes/broken windows policy impacts on incarceration practices all in one image, please send it in and I’ll amend this post and thank you profusely.

Relevant Resources

FBI Crime Clock

CIA World Fact Book – United States

Bureau of Justice Statistics – Key Facts at a Glance

State of the World's Fisheries and Aquaculture - UNEP GRID-Arendal
State of the World's Fisheries and Aquaculture - UNEP GRID-Arendal

What Works

I couldn’t end the agriculture week without including a bit about the state of the oceans as a source of food. To be clear, agriculture is often related to farming the land and raising land-based livestock. Aquaculture is the term used to talk about fish farming. Catching fish out of the open water is not considered agriculture. I ought to have used the broader theme of food production.

I like this graphic because it’s got multiple levels of information – aquaculture vs. open water catches by volume, fish catch by country, and the status of the stocks by oceanic region. It can be difficult to figure out how to represent global level data when it isn’t possible to fall back on national boundaries. It’s a little odd to see the oceans chunked into squares, though.

What Needs Work

This graphic has a sort of not-quite-done look to it overall. The treatment of the aquaculture vs. open water catch could have been more elegantly integrated – superimposing the red and blue blocks on one another makes it look a little bit like the kids left their wooden blocks laying around on top of a map. I might have preferred pie charts with two pie pieces – one for the aquaculture bit and one for the open catch bit to communicate relative share. The size of the pies would be determined by absolute value of the total catch + aquaculture.

What I really would have liked to see would have been a more logical representation of the catch volume by oceanic region. The colors chosen don’t indicate much of anything, except perhaps the static areas which are just blue, standard ocean color. What would have been great would have been to indicate the relationship between areas that have decreased yields because they have been overfished and areas that are currently being overfished which will soon have decreased yields even though their current yields are high. This is complicated because the largest increase and the largest decrease are far more closely related to one another than they are to steady areas or areas with only a slight increase. It would be great if the ocean regions could be depicted by the replacement rate with an extra classification for areas that have been severely over-farmed to the point that the concept of replacement rate no longer has the same meaning.

Relevant Resources

United Nations Environment Programme – GRIDA (2009) State of the World’s Fisheries and Aquaculture

Public Service Announcement: The amount of mercury and arsenic found in predator fish is high enough that people who eat these fish recently can suffer the effects of heavy metal poisoning. To figure out what is safe to eat and what should be avoided, check out the Monterrey Aquarium, one of the best, if not *the* best source for guidelines about what to eat when what you’re eating lived in the water. They even have an iPhone app for easy reference at the grocery store and your favorite restaurants.

Monterrey Aquarium Seafood Watch

US Milk Production 1980 and 2003 by Region
US Milk Production 1980 and 2003 by Region

What Works

The first map was produced by the USDAs Economic Research Service in 2004 to show the change in milk production by US region from 1980 – 2003. The accompanying text is surprisingly brief, “Since 1980, milk production in the U.S. has increased almost 33 percent. Regional production growth has been most pronounced in the Pacific and Mountain regions, the result of development of low-cost systems of milk production in the Pacific region and some Mountain States. Growth has been much slower in the Northeast and Southern Plains, and the other six regions have seen essentially flat or declining production.”

The graphic is a fairly straightforward way to combine a map with a bar graph. I like it better than if it were just a bar graph with regional labels, but I would like it even more if it were better integrated so that the data from the graphs were embedded in the map, maybe by showing the change in production by color or by applying concavity/convexity to the map.

What Needs Work

There is a serious drawback to the map + graph combination. One of the problem with images is that they tend to appear as sealed, complete narratives that are telling the whole story. It’s hard to interrogate an image, harder than interrogating a text. We’re taught not to believe everything we read, but those strategies don’t translate directly into the world of images. The important missing information here is that the population in the US is shifting to the south and west out of the north east. The image doesn’t suggest causal links; but the text does. However, it leaves out the no-brainer that since milk is a localized commodity, population growth is generally going to result in increased milk production in that area.

US Population Change, 1970-2030
US Population Change, 1970-2030

Bonus Image

I found this image depicting population density and population change in the US. Cool colors indicate a loss of population; warm ones suggest growth. The z-axis represents human volume. A solid graphic. I have looked and looked and been unable to find the original source which just goes to show that once information hits the digital domain it really does have a life of its own. Hackers were right about that, information wants to be free.

Relevant Resources

Blayney, Donald. (2004) Milk production shifts West USDA Economic Research Center.

Dupuis, E. Melanie. (2002) Nature’s Perfect Food: How Milk Became America’s Drink. New York: NYU Press.

Mendelson, Anne. (2008) Milk: The Surprising Story of Milk Through the Ages. Knopf.

Wired magazine info porn - World Food Supply and Demand Diverge
Wired magazine info porn - World Food Supply and Demand Diverge

What Works

This is a simple concept, displayed beautifully. The demand for food will outstrip our current ability to produce it.

What Needs Work

Since the timeline is already marching along the x-axis I want to see some context. Tell me when Nobel Peace Prize winner Norman Borlaug revolutionized agriculture and increased yields by orders of magnitude. Show me how global population maps onto the demand for food. Tell me if I should be concerned about the growing Chinese and Indian middle classes who will probably demand more meat (and hence more land per kcalorie). This data is out there and adding it to this graphic would have elevated it from simply beautiful, to being both beautiful and smart.

Relevant Resources

Doyle, Stephen and Zavislak, Zack. (November 2008) “The Future of Food.” in Wired Magazine. 188-205 [So sorry, but I cannot find this article online. If you want to see more, let me know, because the food info porn went on for pages and I scanned them all. There was a centerfold on cows.]

Nobelprize.org Norman Borlaug Biography

Naim, Moises. (March/April 2008) Can the World Afford a Middle Class? in Foreign Policy.

Watts, Jonathan. (20 May 2008) More wealth, more meat. How China’s rise spells trouble in The Guardian.

Figure 1 from "Diet, Energy, and Global Warming" by Eshel and Martin
US Greenhouse Gas Inventory Report - Executive Summary, Figure ES-11
US Greenhouse Gas Inventory Report - Executive Summary, Figure ES-11

Why This?

Continuing what I have decided will be an agriculture theme for the week, I went looking for data related to energy efficiency of diets. This concept first became news in the 1970’s during the energy crisis, championed in the book “Diet for a Small Planet” by Frances Moore Lappé which has recently been released as a 20th anniversary edition. I was interested in getting to the bottom of the planetary (rather than the personal) part of her argument which is that to produce unit weight of protein in the form of beef/veal, the animal is going to need an input equivalent to 21 units of protein and we’d be globally better off if we just ate the plant sources ourselves in terms of energy consumption and intelligent stewardship of the planet. I didn’t quite find what I was looking for to back up that data (yet) but I did find the contemporary twist on that argument which relates dietary choice to greenhouse gas emissions.

What Works

The first graphic doesn’t work all that well and probably makes no sense to you so we’ll come back to that. The second graphic, from the EPA, is not particularly pretty, but it has strength in simplicity and it makes intelligent use of the x-axis to represent greenhouse gas sinks. (Note: The visual representation does a great job of communicating that are emissions dwarf our sinks better than reading a number on a page would do.) Whereas the first graphic fails miserably to represent the difference in the energy efficiency of diets, the second graphic at least conveys the conclusion of the report that went along with the first graphic which is that the difference between eating the standard American diet and a vegan diet is, “far from trivial, …[it] amounts to over 6% of the total U.S. greenhouse gas emissions.”

The details of the report accompanying the first graphic are worth perusing and I only wish they would have spent more time trying to represent them graphically. The authors, Eshel and Martin, compute the comparative impacts of transit choice vs. dietary choice and find that, “while for personal transportation the average American uses 1.7 × 107–6.8 × 107 BTU yr−1, for food the average American uses roughly 4 × 107 BTU yr−1.” That would make an excellent graphic in about ten different ways and catapult them past the problem that many readers are going to get tripped up looking at the orders of magnitude and units and miss the point.

What Needs Work

The first graphic is supposed to show the composition of the hypothetical diets considered. The mean American diet as reported by FAOSTAT has a little break-out component that provides more detail about the constituents of the animal products category but it took me a long hard look to figure that out. The break out part should have been constructed so it wasn’t exactly the same scale as the rest of the graphic (which it isn’t, by the way) otherwise it just reads like another column with viewers liable to assume that they can follow the scale on the y-axis. But the y-axis doesn’t relate to the break-out part at all – only the percentages listed alongside it are salient.

My bigger problem with the first graphic are the next five bars. Just to help you navigate α represents the proportion of the standard 3744 kcal diet that comes from animal sources. See α, think animal. A key would have been nice. Now that you know that, looking at the graph, it appears that each of the diets gets the same amount of kcals from plant sources because the green segments are all the same size. However, this is not actually what the authors are trying to convey. You have to read through the text quite carefully to pick out what proportion of each diet comes from animal sources overall. Once having done that, this graphic can help you further breakdown how those animal sources are apportioned. For example, the ovo-lacto group gets none of their animal protein from animal flesh – only from dairy (.85 of animal protein total) and eggs (.15 of animal protein total). But it took a good ten minutes of going between text and graphic to figure out what they have charted here. In all honesty, I’m still a little confused about whether the last three diets just switch out fish for meat for poultry and keep the same total number of kcalories in the animal flesh category relative to dairy+eggs. And I certainly can’t tell if any of those hypothetical diets have a greater or lesser proportion of kcals coming from plants by looking at this graphic.

In summary, the two graphics here were not trying to make the same point. The first one was trying to explain how the authors modeled their hypothetical diets in order to convince you that, in the end, and in conjunction with some other writing and graphic representation, if Americans moved to vegan diets the national greenhouse gas emission rate would drop by 6%, on par with what would happen if everyone started driving a Prius. The second graphic does this much better using aggregate data (and thus a totally different approach than Eshel and Martin).

Relevant Resources

Eshel, Gidon and Martin, Pamela. (May 2005) Diet, Energy and Global Warming. Submitted to Earth Interactions.

United States Environmental Protection Agency. (April 2008) Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006

Moore Lappé, Frances. (1971, 1991) Diet for a Small Planet Ballantine Books.