Pretentious, moi? Literary quotes in science

The most important thing to consider as a PhD student writing up is, of course – I’m sure we’d all agree – what quotes you plan to use in order to show of to your examiners just how cultured and well-read you are. A decade and more after submitting my thesis, I’m still proud of my selections, feeling they tick both boxes. (I will leave it to you to decide whether they also tick a third, ‘pretentious git’.) Having finally, reluctantly come around to the fact that the total number of people ever to have read my masterwork is unlikely to increase any time soon, I thought I’d share them with you here. First thing to note: I took this quote selection process very seriously (as is right and proper) and started noting down potential candidates fairly early in my PhD. I was determined to avoid anything commonplace, and in particular steered well clear of quotation dictionaries. Also – I only now realise – it never really occurred to me to quote a scientist, still less a scientific paper. I guess I thought that side of me would be well represented throughout the rest of my work, and I wanted these choice quotes to reflect instead my more arty, sophisticated, fancy-cocktail-and-complicated-music sensibilities.

I also need to give some context. I spent my PhD studying the phenomenon of rarity. Rarity is common: most species are extremely restricted both in terms of numbers of individuals and spatial distribution. What are the causes and consequences of this? In particular, I was interested in whether rare species are in any sense special – for instance, do their biological characteristics differ consistently from those of common species? So throughout my studies I was on red alert for any interesting use of the word ‘rare’, and especially anything that carried connotations of oddity arising as a function of being rare.

The perfect quote finally arrived in the cinema, as I was watching Terry Gilliam’s masterful interpretation of the great Hunter S. Thompson’s Fear and Loathing in Las Vegas. I had no notebook, no pen; however, I knew I had the novel at home so simply had to re-read it (always a pleasure) to find the quote, no? No. Turns out it’s not in the book; so I bought the VHS (OK, OK: I'm old) when it came out and watched it, finger poised over the pause button (and rewinding several times to make sure I’d interpreted Johnny Depp’s drawl perfectly) until I grabbed the quote:

There he goes, one of God’s own prototypes – a high-powered mutant of some kind never even considered for mass production. Too weird to live, too rare to die. Raoul Duke, Doctor of Journalism, of his Attorney

The rather odd attribution was because I was unsure if it was a Thompson original, or directly from Gilliam’s sceenplay, so I stuck with the character names. Only later did I find the original source, in The Great Shark Hunt, a collection of Thompson’s writing, where he uses it to describe his (HST, Doctor of Journalism, alter-ego: Raoul Duke) real-(if larger-than)-life attorney, Oscar Zeta Acosta.

So that was all nice and relevant to the topic of my thesis, but how should I demonstrate the true depth of my intellectual facilities? Being a bit of a francophile, I thought I should have something in French; and who better to quote than Enlightenment poster-boy Voltaire? But I didn’t want anything run-of-the-mill – nothing from Candide, say. Fortunately, I’d read a collection of Voltaire’s work, and came across this from Memnon to start my introduction:

Memnon conçut un jour le projet insensé d’être parfaitement sage. Il n’y a guère d’hommes à qui cette folie n’ait quelquefois passé par la tête. Voltaire, Memnon (ou la sagesse humaine), 1747

My French is far rustier these days, but a (very) loose translation is something like, “One day Memnon came up with the ludicrous plan of becoming perfectly wise. There are few men to whom this mad idea has not occurred, from time to time.” Seemed somehow apt.

Finally, I needed something to start the general discussion. My thesis was rather a rambling affair (the first comment of my external examiner was, “Tell me, why did you decide to write two theses…?”), and I found a gem in Francis Wheen’s terrific biography of Karl Marx. I was not trying to make a political point – although it’s hard to disagree with the sentiment of ‘from each according to his ability, to each according to his needs’ – but through Wheen’s book I had become quite fond of Marx the fallible man, especially the contradictions between his socialist ideas and his own rather upwardly-mobile social pretensions. He was quite the procrastinator too, and as a writer nearing the end of this major project, my PhD thesis – and freshly out of funding and relying on benefits and the generosity of friends – I certainly empathised with the sentiment expressed here:

The material I am working on is so damnably involved… but for all that, for all that, the thing is rapidly approaching completion. There comes a time when one has forcibly to break off. Marx, letter to Joseph Weydemeyer, 1851

I have never really stopped struggling with this. (Neither did Marx: it took a further 16 years after he wrote the above for the first volume of Das Kapital actually to appear…) Knowing when to finish something, to submit and move on, is not my greatest strength. Perhaps this is the place.

Machismo and excellence in cooking and statistics

The inevitable return to TV this week of Masterchef, after a close season shorter even than the English Premier League, has (for strange reasons that I hope nonetheless will become clear) triggered this response of sorts to Brian McGill’s post on Statistical machismo over at Dynamic Ecology last year. Brian lamented the use by ecologists of the latest ‘must use’ statistical method, which is typically complicated both to perform and (perhaps especially) to interpret, without necessarily having much of an effect on the conclusions drawn. He felt this macho posturing – as he puts it, “my paper is better because I used tougher statistics”; in Masterchef terms, “analysis doesn’t get any tougher than this” – ends up overcomplicating papers and wasting everyone’s time. I enjoyed the post at the time, and felt it raised some interesting points; and though I disagreed with the thrust of it, this was not to the extent that I felt compelled to comment, still less to respond. Now that I’ve come up with a convoluted, almost certainly over-played culinary analogy, though, I’m going to have a bash at expressing my thoughts on the matter properly.

If you watch Masterchef (especially the early rounds) you’ll probably see a great deal of culinary machismo. Even if you don’t, you probably know what I mean: food prepared by someone who is a decent chef, but a pretty awful cook. Smears of jus and droplets of fluid gel on big white plates, but the chicken’s raw; burnt chips in a flowerpot; spun sugar on a duff dessert. Contrast this with what a good non-cheffy cook might produce: a really excellent, well seasoned, ugly stew; a pudding that tastes sublime but looks like a car crash. When I lived in Thornton le Clay near York, our pub specialised in the latter: fantastic, simple, pub food, cooked to perfection with no pretension (it's unfair on them to suggest it was ugly, but the emphasis was on flavour not prettiness). Next village we lived, the pub was very gastro, and the food – though twice the price, and served on wooden boards as likely as not – was nowhere near as good.

This, I think (bear with me!), is similar to the issue that Brian raises. In particular, the use of advanced techniques – statistical or culinary – without having mastered the basics, indeed without even considering the basics, reeks of posturing. In these cases, I agree, we should beware.

Consider for example something like Generalised Linear Mixed Effects Models (GLMMs) as a statistical equivalent of nitro-poached aperitifs or popping candy cheesecake. I am very wary of GLMMs. Ben Boelker’s TREE paper on them basically says as much: do not go here unless you really know what you’re doing. As a minimum, you ought to have mastered the basic component techniques of GLMs and LMMs (and naturally, you need to know your LMs for either of them). Yet I see students who describe themselves as ‘not very confident’ at statistics merrily fitting GLMMs with no clear idea of what model they’ve fitted, or why. Not machismo in this case, but rather blindly following a statistical recipe which demands a great deal more skill than their current aptitude allows.

So yes, in these kinds of cases – and similarly in some of the others Brian mentions – doing a simple analysis well is probably preferable to making a dogs dinner out of a complicated one.

And yet…

Let’s stretch this analogy further. If you really want perfect chips, you’ll triple cook them. Liquid nitrogen really does make excellent ice cream. The way to ensure your meat is exactly à point every time is to cook it sous vide in a water bath. Simply put: some methods of cooking are better than others, and if you can master a Blumenthal-esque skillset, the resulting food will be objectively, qualitatively superior to the lovely, hearty stuff I used to eat in my local, or that I aim to cook at home.

In the same way, some methods of statistical analysis are simply better than others. Brian’s post mentions phylogenetic correction, for example, complaining that it hardly ever affects the result of an analysis, yet entails a great deal of work and additional assumptions. Well perhaps (and his point about errors in phylogenies is a good one), and of course you can fluke the ‘correct’ result with simple statistics, just as you can fluke excellent food with a less scientific approach than that employed by the molecular gastronomists. But if you want consistent excellence – if you want to do something right – you use the best available methods.

Specifically regarding the inclusion of phylogenies in comparative analyses, it’s largely immaterial in my view whether or not this has a large effect on your results; rather it’s simply sensible to consider evolutionary processes when you're modelling a pattern which is the result of evolution. This point is nicely made in a new paper in Methods in Ecology and Evolution by Hernández et al., in which they make a plea for moving beyond phylogenies as ‘statistical fix’ (i.e., ‘phylogenetic correction’) and embracing instead a fully evolutionary view of macroecology in which we test mechanistic hypotheses rather than just describing patterns. (One could of course make a similar case for including spatial processes.)

The cooking/statistics analogy breaks down in one important aspect, however: there are very good reasons why you might not even attempt to master those fancy cooking skills. I read the Fat Duck cookbook much as I might read an account of the building of a great cathedral: full of admiration for the skill, craftmanship and effort involved, but with no intention of even attempting to replicate the endeavour. Blumethal’s Pot roast loin of pork, braised belly, gratin of truffled macaroni, for instance, includes 74 incredients, including two separate stocks (a further 24 ingredients and several hours of prep time), and requires nine separate procedures to produce a single course. You (or at least, I) would never do that to feed two at home; it is only feasible at a restaurant scale. Even those recipes that look technically manageable need expensive equipment, putting them well out the reach of the home cook, who might be better advised to concentrate on mastering more simple skills.

Developing beyond being a good ‘home statistician’ – mastering the essentials of analysis – on the other hand, requires none of this expense. Unlike haute cuisine, mastering statistics – especially in the age of R – is free. We have no excuse not to master the best available methods. So you maybe should roll up your sleeves and chase that Michelin (Fisher? Pearson? Gaussian?) Star after all. Not because you feel you have to in order to show off – I’m with Brian there – but because doing things right is important.

Sea sharing or sea sparing: How should we manage our oceans?

What with Brian Cox spending an hour explaining the importance of body size in ecological systems, and then prime time marine conservation courtesy of Hugh Fearnley-Whittingstall’s ongoing Fishfight, I feel that my research interests have been rather well covered by TV of late. But whereas I have nothing but praise so far for Cox’s Wonders of Life, I find myself somewhat more ambivalent in my views of Fishfight. On the one hand, it is fantastic to see the issue of marine conservation gain such prominence. Hugh F-W is an excellent and extremely savvy campaigner, and his energy and drive to reduce the wasteful practice of discards (subject of the first Fishfight series) has had a real, positive impact at the EU level. Of course, we need to make sure that the fish now landed instead of discarded at sea actually make it to market, rather than landfill – but that’s not to take away from what Fishfight achieved. And the focus of this second series, on marine protected areas, is also a really important issue – few would argue with the central tenet that we should take better care of the marine environment, and that protecting certain areas should be a part of this. Neither am I entirely averse to using shock tactics to elicit an emotional response in the audience – indeed, I attempt just this in my marine conservation lectures here in Sheffield, where I channel Jeremy Jackson in documenting the often calamitous history of human impacts on the ocean.

On the other hand, however – and notwithstanding the considered input of scientists whom I know, like and respect such as Alex Rodgers and Callum Roberts – we need to recognise that Fishfight is a campaign, and campaigning TV by its very nature is not especially fussed about issues of balance. This is the point made by SeaFish in their response to the series. SeaFish were derided on Twitter last night by George Monbiot as an industry quango whose interest is "minimum of conservation and maximum of exploitation", but actually they are a respected body who take science pretty seriously - although as an industry body of course they consider the social and economic as well as the ecological consequences of marine environmental policy. They have been making the point that MPAs in the UK ought to be established based only on sound scientific criteria – the reason rather few have so far been agreed is that often we lack these data.

Now, I used to be of a similar view to the Fishfight gang – that the priority ought to be just establishing  MPAs, on the assumption that even if they were suboptimally positioned, any protection of any area would be better than none. Then I started talking to people who study these things and was politely told that, actually, a poorly designed MPA can actually do more harm than good. So, my view now is that MPAs need to be carefully designed, set up with specific and explicit goals, and not simply placed willy-nilly.

More generally, and as always, the truth will usually lie somewhere between environmental campaigners and industry groups. Some scientists have been quite vocal regarding the oversimplification of complex issues that is inevitable in campaigning TV. Marine conservation biologist Mike Kaiser, for example, has been quite active on Twitter putting across a fisheries science view, and I agree with this blog post by Jess Woo, that framing this campaign in terms of a ‘fight’ is unfortunate – “the last thing marine conservation (and particularly fisheries management) needs is a ruckus”.

All of which has got me thinking: what does marine conservation need? Well, some kind of clear vision would be useful, regarding how we balance the needs of conservation with feeding 9 billion people. There have been studies looking at this from a fisheries perspective, but it struck me that there are real parallels here with the land sharing vs. land sparing debate in terrestrial conservation. Should we concentrate conservation effort into the preservation of wild areas, and exploit other areas for food production as intensively as we can? Or should we aim for a more balanced approach, seeking a way to allow human activities and nature to coexist? In farming terms, this is the difference between a mosaic of industrial farms interspersed with nature reserves, and a more extensive system of wildlife-friendly farms.

The obvious upshot of this terrestrial debate is that if you want a large network of fully protected nature reserves, you have to balance that with farming the fuck out of what’s left. Translating this to a marine context, a network of no-take MPAs requires fishing the fuck out of unprotected areas. There is no real incentive for more responsible fishing outside the MPAs: the focus should just be on productivity. So the depressing images of dredged and trawled habitats that Fishfight uses to tug the heartstrings would not disappear if MPAs were widely established. In this case, you’re pinning an awful lot on not only the (widely supported) in situ success of MPAs, but also in their (often positive, but more variable) spillover effects. Responsible fishing, by contrast, requires more extensive areas to be exploited, which may limit the extent of fully protected MPAs.

More generally, whilst we should be cautious extending the fisheries—agriculture analogy too far (fishing, remember, still largely targets wild, and often highly mobile organisms), I think it does provide some useful context. Ray Hilborn, a fisheries ecologist who also happens to be a farmer, has commented on this before: how farmers are praised for bringing the landscape under the plough in order to produce food, whereas fishermen are castigated for doing similar (often in far more hazardous circumstances). Let’s just remember that (to use Oxfam’s terminology) the social foundation of access to an adequate, healthy food supply is of equal importance to the environmental ceiling of preserving biodiversity. If we get marine management right, we should be able to do both. I’m not convinced that starting a fight with some of the most important and knowledgeable marine stakeholders is the best way to achieve this.