Never underestimate the importance of a good figure

27 07 2022

I seem to end up frequently explaining to students and colleagues that it’s a good idea to spend a good deal of time to make your scientific figures the most informative and attractive possible.

But it’s a fine balance between overly flashy and downright boring. Needless to say, empirical accuracy is paramount.

But why should you care, as long as the necessary information is transferred to the reader? The most important answer to that question is that you are trying to catch the attention of editors, reviewers, and readers alike in a highly competitive sea of information. Sure, if the work is good and the paper well-written, you’ll still garner a readership; however, if you give your readers a bit of visual pleasure in the process, they’re much more likely to (a) remember and (b) cite your paper.

I try to ask myself the following when creating a figure — without unnecessary bells and whistles, would I present this figure in a presentation to a group of colleagues? Would I present it to an audience of non-experts? Would I want this figure to appear in a news article about my work? Of course, all of these venues require differing degrees of accuracy, complexity, and aesthetics, but a good figure should ideally serve to educate across very different audiences simultaneously.

A sub-question worth asking here is whether you think a colleague would use your figure in one of their presentations. Think of the last time you made a presentation and found that perfect figure that brilliantly portrays the point you are trying to get across. That’s the kind of figure you should strive to make in your own research papers.

I therefore tend to spend quite a bit of time crafting my figures, and after years of making mistakes and getting a few things right, and retrospectively discovering which figures appear to garner more attention than others, I can offer some basic advice about the DOs and DON’Ts of figure making. Throughout the following section I provide some examples from my own papers that I think demonstrate some of the concepts.

tables vs. graphs — The very first question you should ask yourself is whether you can turn that boring and ugly table into a graph of some sort. Do you really need that table? Can you not just translate the cell entries into a bar/column/xy plot? If you can, you should. When a table cannot easily be translated into a figure, most of the time it probably belongs in the Supplementary Information anyway.

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Cartoon guide to biodiversity loss LXXIII

15 07 2022

Welcome to the fourth set of 6 cartoons for 2022. See full stock of previous ‘Cartoon guide to biodiversity loss’ compendia here.


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Journal ranks 2021

4 07 2022

Now that Clarivate, Google, and Scopus have recently published their respective journal citation scores for 2021, I can now present — for the 14th year running on ConvervationBytes.com — the 2021 conservation/ecology/sustainability journal ranks based on my journal-ranking method.

Like last year, I’ve added a few journals. I’ve also included in the ranking the Journal Citation Indicator (JCI) in addition to the Journal Impact Factor and Immediacy Index from Clarivate ISI, and the CiteScore (CS) in addition to the Source-Normalised Impact Per Paper (SNIP) and SCImago Journal Rank (SJR) from Scopus. 

You can access the raw data for 2021 and use my RShiny app to derive your own samples of journal ranks.

I therefore present the new 2021 ranks for: (i) 106 ecology, conservation and multidisciplinary journals, (ii) 27 open-access (i.e., you have to pay) journals from the previous category, (iii) 64 ‘ecology’ journals, (iv) 32 ‘conservation’ journals, (v) 43 ‘sustainability’ journals (with general and energy-focussed journals included), and (vi) 21 ‘marine & freshwater’ journals.

Remember not to take much notice if a journal boasts about how its Impact Factor has increased this year, because these tend to increase over time anyway What’s important is a journal’s relative (to other journals) rank.

Here are the results:

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