In the greater scheme of things, how you plot your data in a paper or in a PowerPoint presentation may not be the most important thing to worry about. But if you believe that small things matter, perhaps you should read on. The standard of presentation of data in graphs in ecological presentations is often less good than is desirable. Many authors have tried to help and for more instructions please read Cleveland (1993, 1994).

Begin with a few elementary rules that I should not have to state but are often ignored:

1. Label the axes and give the units of measure
2. Do not use a font size that requires a microscope to read.
3. Do not present point data without some measure of possible error.

Beyond these general rules there are many that become more specific. I want to call attention here to two rules that are often violated even in our best ecological journals. The first and simplest is never to plot in logs. It is bad enough to plot an axis in log-10 units (most people can work out that 2 in log-10 means 100 in real units), but I have never met anyone who can decipher log-e units (what does 4.38 in log-e units mean in real units?). The solution is simple. Label the scales in real units so that for example the scale may read 1-10-100-1000 with equal spacing so the axis is scaled in logs but the units are given in real measurements. In this way the reader has some idea of the scale of changes shown on the graph.

The second and perhaps more controversial problem I find with ecological graphics is the use of histograms for data that should be illustrated as point estimates (with confidence limits). If we take the advice of Cleveland (1993, page 8) histograms would be rare in scientific publications:

“The histogram is a widely used graphical method that is at least a century old. But maturity and ubiquity do not guarantee the efficacy of a tool……The venerable histogram, an old favourite, but a weak competitor, will not be encountered again [in this book].” (Cleveland 1993, p. 8)

He goes on to evaluate a whole array of graphical methods most of which are rarely seen in ecological papers. The box plot is perhaps the most common example he recommends and is available in many graphing packages. But note that EXCEL is not a very good standard for graphics, and while some if its graphics might be useful, caution is recommended. Many graphics options are available in R (http://www.r-project.org/ ) and some in SIGMAPLOT. Discussions about graphics packages on the web are extensive and everyone has their favourite package along with complaints about other packages. The general point is to think carefully about the graphics you use to convey your message to make it as clear as possible.

What exactly is wrong with histograms? They are misleading if the scale of the axis does not start at zero. The width of the bars is misleading if the scales are categories or precise values. The information in each histogram bar is entirely concentrated in the top of the bar and the included error bars. The amount of replication is difficult to evaluate, and distributions of data that are skewed are not presented. Finally, outliers are not identified. Perhaps the message is that if you have data that you think should be presented as a histogram, check Cleveland (1994) to see if there is not a better way to present it to your audience.

A final observation on graphics. I realize that at the present time in movies and games 3-D images and animations are quite incredible. But remember these are for entertainment not for communication. If you think your PowerPoint requires 3-D graphs with animations, be sure to check whether you are aiming more for entertainment than clear communication.

Cleveland, W.S. 1993. Visualizing Data. Hobart Press, Summit, New Jersey.

Cleveland, W.S. 1994. The Elements of Graphing Data. AT&T Bell Laboratories, Murray Hill, New Jersey.