Complicated analyses for trivial problems?

By Joern Fischer

Journals  are “still packed with papers describing more and more sophisticated analyses applied to more and more trivial problems.”

Ehrlich, P. R. 1997. A world of wounds: ecologists and the human dilemma. Ecology Institute, Oldendorf/Luhe, German

Oh isn’t Paul Ehrlich a cynical bastard, one might say. (No offense, bastard is used as an affectionate term in Australian, which is after all, where I have lived for most of my adult life…) What’s to his claim?

I fear that unfortunately, Paul may well be right. Take a comparison between the 1960s and now. In the 1960s, we saw some great ecology (MacArthur’s work above all), but because there were virtually no computers, analyses were simple. It was vital that ecologists had a strong ecological intuition and good ideas. Take an average issue of a leading journal today, and you find that complicated methods account for much of what was done. Be it null model analysis, generalised linear mixed modelling, maximum entropy models or spatial optimisation: these are now part of the standard toolkit of … hang on … yes: of ecologists. But shouldn’t the word at that point have been something else? Like applied statisticians, or perhaps applied mathematicians?

I find the trend towards more and more complicated methods concerning for two reasons. One, we end up using a lot of analyses that we don’t fully understand. A good ecologist these days is one who can write a lot of code in R. But writing code isn’t the same as having been trained in statistics per se. I have worked with several trained statisticians, and they regularly express dismay of what ecologists come up with — especially when they ‘develop’ new methods. You just have to watch the experience of a modern PhD student in ecology — you’ll find that a lot of her or his time is spent on learning methods, but mostly this means on learning how to implement a certain model. It is not realistically feasible for most ecologists to fully understand any of the four methods I listed above, for example. A deep understanding requires time (and skill), and typically falls in the domain of statisticians or applied mathematicians…

The second problem follows from the first one. If we need to learn complicated methods, this necessarily skews our activities away from actual ecology, towards trying our best to be what most of us will never be: namely statisticians or mathematicians. Reed Noss lamented the dying out of naturalists as early as 1996, and his fears are becoming more and more true. Reed called the alternative armchair ecology, or keyboard ecology…. what’s the proportion of armchair or keyboard ecology in a current issue of leading journals, such as Ecology Letters or Conservation Biology?

Personally, I don’t quite know how to deal with this problem, but I’ll try to offer some suggestions. In Australia, I knew my way about nature reasonably well — there were lots of species I could identify, and walking around I could tell you a bit about what’s going on in the ecosystem, from a landscape ecological perspective. Now in Europe, often, I feel completely lost. There’s a frog, and I have no idea what it might be. Here’s a bird call I don’t know, but the stupid little bird is hiding in the top of the canopy, so I can’t see it …. it’s like starting all over again!

While I don’t quite know how to solve the problem of increasingly complex methods being applied to increasingly trivial problems — and us losing our field intuition at the same time — I’m convinced that we need to be aware of this problem and face it. Three possible solutions come to mind. First, the best solution might lie in collaborations with people who actually specialise in quantitative skills: much better the real experts are in charge and thereby control the quality, than we all try to be good at everything. And solution number two: I’d encourage everyone to use the simplest methods possible for a given question. And number three: keep pushing the envelopes of ideas and theory in ecology and conservation, rather than get lost in applying the same old theories in ever more sophisticated ways. And finally, make sure you get out in the field to sharpen your ecological intuition.

What do you think? Is this trend of more complicated analyses real (and concerning), or am I just getting too old to keep up with it? Comments welcome…

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2 thoughts on “Complicated analyses for trivial problems?

  1. I will try a comparison and parallell. The phenomenon you describes seem to be general: one can find it in literature, music and arts.

    Just to give an example: read a paper from ‘Ecology’ published in the seventies. How honest, symple and informative they are. Listen a music from the 70`s-80`s. Very clever, symple and full with informations.

    Now read a paper today, which is certainly more technical but often (not always) the message is very the same as it would be if the methods of the 70`s would be used.

    And listen a music composed today – where one can rarely find a sentence, but lots of noize and technology…

    Sorry I may look a bit simple, the reality is more complex, clearly, but still…
    T

  2. Pingback: Why we do need more complex analyses in ecological research – a response to “Complicated analyses for trivial problems?” | Ideas for Sustainability

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