How to review a scientific paper

30 09 2014

F6a00d834521baf69e200e55471d80f8833-800wiollowing one of the most popular posts on ConservationBytes.com, as well as in response to several requests, I’ve decided to provide a few pointers for early-career scientists for reviewing manuscripts submitted to peer-reviewed journals.

Apart from publishing your first peer-reviewed paper – whether it’s in Nature or Corey’s Journal of Bullshit – receiving that first request to review a manuscript is one of the best indications that you’ve finally ‘made it’ as a recognised scientist. Finally, someone is acknowledging that you are an expert and that your opinions and critiques are important. You deserve to feel proud when this happens.

Of course, reviewing is the backbone of the scientific process, because it is the main component of science’s pursuit of objectivity (i.e., subjectivity reduction). No other human endeavour can claim likewise.

It is therefore essential to take the reviewing process seriously, even if you do so only from the entirely selfish perspective that if you do not, no one will seriously review your own work. It is therefore much more than an altruistic effort to advance human knowledge – it is at the very least a survival mechanism. Sooner or later if you get a reputation for providing bad reviews, or refuse to do them, your own publication track record will suffer as a result.

Just like there are probably as many different (successful) ways to write a scientific paper as there are journals, most people develop their own approaches for reviewing their colleagues’ work. But just as it’s my opinion that many journal editors do an awful job of editing, I know that many reviewers do rather a shit job at their assigned tasks. This perspective comes from many years as an author, a reviewer, an editor and a mentor.

So take my advice as you will – hopefully some of it will prove useful when you review manuscripts. Read the rest of this entry »





Time to put significance out of its misery

28 07 2014

If you’ve been following this blog for a while, you’ll be no stranger to my views on what I believe is one of the most abused, and therefore now meaningless, words in scientific writing: ‘significance’ and her adjective sister, ‘significant’. I hold that it should be stricken entirely from the language of science writing.

Most science writing has become burdened with archaic language that perhaps at one time meant something, but now given the ubiquity of certain terms in most walks of life and their subsequent misapplication, many terms no longer have a precise meaning. Given that good scientific writing must ideally strive to employ the language of precision, transparency and simplicity, now-useless terminology should be completely expunged from our vocabulary.

‘Significance’ is just such a term.

Most interviews on radio or television, most lectures by politicians or business leaders, and nearly all presentations by academics at meetings of learned societies invoke ‘significant’ merely to add emphasis to the discourse. Usually it involves some sort of comparison – a ‘significant’ decline, a ‘significant’ change or a ‘significant’ number relative to some other number in the past or in some other place, and so on. Rarely is the word quantified: how much has the trend declined, how much did it change and how many is that ‘number’? What is ‘significant’ to a mouse is rather unimportant to an elephant, so most uses are as entirely subjective qualifiers employed to add some sort of ‘expert’ emphasis to the phenomenon under discussion. To most, ‘significant’ just sounds more authoritative, educated and erudite than ‘a lot’ or ‘big’. This is, of course, complete rubbish because it is the practice of using big words to hide the fact that the speaker isn’t quite as clever as he thinks he is.

While I could occasionally forgive non-scientists for not quantifying their use of ‘significance’ because they haven’t necessarily been trained to do so, I utterly condemn scientists who use the word that way. We are specifically trained to quantify, so throwing ‘significant’ around without a very clear quantification (it changed by x amount, it declined by 50 % in two years, etc.) runs counter to the very essence of our discipline. To make matters worse, you can often hear a vocal emphasis placed on the word when uttered, along with a patronising hand gesture, to make that subjectivity even more obvious.

If you are a scientist reading this, then you are surely waiting for my rationale as to why we should also ignore the word’s statistical meaning. While I’ve explained this before, it bears repeating. Read the rest of this entry »





Don’t torture your readers III

23 06 2014

TortureIt has been quite some time since I did one of these kinds of posts (see Don’t torture your readers and Don’t torture your readers II). However, given how popular they seem to be, I have decided to do a follow-up post on grammar problems that I tend to see far too often in science writing.

COMPOUND ADJECTIVES: This is a particularly abused component of scientific writing. Although it’s fairly straightforward, I’m amazed just how many people get it wrong. Most people appear to understand that when an adjective (that’s a qualifier for a noun, just in case you are a grammarling) is composed of more than one word, there is normally a hyphen that connects them:

  • e.g., ’10-m fence’, ‘high-ranking journal’, ‘population-level metric’, ‘cost-effective policy’

If two or more adjectives are given in a row, but none modifies the meaning of the others, then it is simply a case of separating them with commas:

  • e.g., ‘a long, high fence’, ‘an old, respected journal’, ‘an effective, enduring policy’

However, if the compound adjective is composed of a leading adverb (that’s a qualifier for a verb), then there is NO hyphenation:

  • e.g., ‘an extremely long fence’, ‘a closely associated phenomenon’, ‘a legally mandated policy’

There are other instances when no hyphenation is required, such as when the qualifiers are proper nouns (e.g., ‘a Shark Bay jetty’), from another language such as Latin (e.g., an ‘ab initio course’) or enclosed in quotation marks (e.g., ‘a “do it yourself” guide). Note in the last example, without the quotations, it would become ‘a do-it-yourself guide’).

A quick way to recognise whether a compound adjective should be hyphenated is to examine the terminal letters of the leading word; if the leading component ends in ‘ly’, then it is likely an adverb, and so the compound should not be hyphenated (although watch for sneaky exceptions like ‘early-career researcher’!). Read the rest of this entry »





How to write a scientific paper

22 10 2012

Several years ago, my long-time mate, colleague and co-director, Barry Brook, and I were lamenting how most of our neophyte PhD students were having a hard time putting together their first paper drafts. It’s a common problem, and most supervisors probably get their collective paper-writing wisdom across in dribs and drabs over the course of their students’ torment… errhm, PhD. And I know that every supervisor has a different style, emphasis, short-cut (or two) and focus when writing a paper, and students invariably pick at least some of these up.

But the fact that this knowledge isn’t innate, nor is it in any way taught in probably most undergraduate programmes (I include Honours in that list), means that most supervisors must bleed heavily on those first drafts presented to them by their students. Bleeding is painful for both the supervisor and student who has to clean up the mess – there has to be a better way.

Yes, there are books on the issue (see, for example, Day & Castel 2011, Hofmann 2009, Schimel 2011), but how many starting PhDs sit down and read such books cover to cover? Hell, I can barely get them to read the basic statistics texts.

So as is classic for Barry, he came up with his own approach that I like to call ‘La Méthode Brookoise’ (a tribute to another clever jeu de mots). This short-cut guide to setting up a scientific paper is simple, effective and intuitive. Sure, it was designed with ecology in mind, but it should apply to most scientific disciplines. It appeals to most of our students, and we have both been asked for copies by other supervisors over the years. Our original intention was to write a paper about writing papers to flesh out the full Méthode, but that has yet to happen.

Therefore, for the benefit of the up-and-comings (and perhaps to a few of those longer in tooth), behold La Méthode Brookoise for writing papers: Read the rest of this entry »





Supercharge Your Science V.2

24 11 2011

I suspect a lot of ConservationBytes.com readers will be attending the imminent 25th International Congress for Conservation Biology to be held in Auckland from 5-9 December 2011 (it was to be held in Christchurch, but the venue was changed after that city fell down). I’ve now been to 3 previous ICCBs myself, and it should prove to be a good, informative (and fun) meeting.

I’ll be giving a talk or two, as will some of my students and postdocs, but I’m not spruiking those here (but you’re all invited, of course).

The main reason for this short post today is to advertise for Version 2 of our (i.e., Bill Laurance and me) popular ‘Supercharge Your Science‘ workshop. Yes, the organising committee of the ICCB decided it was a good idea to accept our application to repeat our previously successful series of presentations extolling the virtues of positive and controlled media interactions, social media and good writing techniques for ‘supercharging’ the impact of one’s science. You can read more about the content of this workshop here and here.

The description of the workshop (to be held from 19.00 – 21.00 on 6 December in the SkyCity venue) on the ICCB website is: Read the rest of this entry »





The conservation biologist’s toolbox

31 08 2010

Quite some time ago I blogged about a ‘new’ book published by Oxford University Press and edited by Navjot Sodhi and Paul Ehrlich called Conservation Biology for All in which Barry Brook and I wrote a chapter entitled The conservation biologist’s toolbox – principles for the design and analysis of conservation studies.

More recently, I attended the 2010 International Meeting of the Association for Tropical Biology and Conservation (ATBC) in Bali where I gave a 30-minute talk about the chapter, and I was overwhelmed with positive responses from the audience. The only problem was that 30 minutes wasn’t even remotely long enough to talk about all the topics we covered in the chapter, and I had to skip over a lot of material.

So…, I’ve blogged about the book, and now I thought I’d blog about the chapter.

The topics we cover are varied, but we really only deal with the ‘biological’ part of conservation biology, even though the field incorporates many other disciplines. Indeed, we write:

“Conservation biology” is an integrative branch of biological science in its own right; yet, it borrows from most disciplines in ecology and Earth systems science; it also embraces genetics, dabbles in physiology and links to veterinary science and human medicine. It is also a mathematical science because nearly all measures are quantified and must be analyzed mathematically to tease out pattern from chaos; probability theory is one of the dominant mathematical disciplines conservation biologists regularly use. As rapid human-induced global climate change becomes one of the principal concerns for all biologists charged with securing and restoring biodiversity, climatology is now playing a greater role. Conservation biology is also a social science, touching on everything from anthropology, psychology, sociology, environmental policy, geography, political science, and resource management. Because conservation biology deals primarily with conserving life in the face of anthropogenically induced changes to the biosphere, it also contains an element of economic decision making.”

And we didn’t really cover any issues in the discipline of conservation planning (that is a big topic indeed and a good starting point for this can be found by perusing The Ecology Centre‘s website). So what did we cover? The following main headings give the general flavour: Read the rest of this entry »





Don’t torture your readers II

22 02 2009

The second instalment of “Don’t torture your readers” (an attempt to stimulate better writing in conservation science) follows with some more mistakes, bad grammar and personal pet peeves.

  • DECIMATE (as in ‘… the population was decimated following…’) – I’ve seen this one used way too often. It is usually invoked by the author to imply some devastating reduction in population size (somehow it sounds bad); for this reason alone, the emotive language should be avoided. However, ‘decimate’ has a specific meaning: to reduce by every ‘one in 10′ (hence the ‘deci’ prefix). If you really mean the population was reduced by 10 %, use ‘decimate’. If you are just stating the population was reduced, state by how much and avoid emotive and incorrect terms.
  • DRAMATIC(ALLY) (as in ‘… we observed a dramatic decline in…’) – another meaningless, emotive word that belongs in the theatre, not in scientific writing. Quantify your meaning instead of relying on subjective terms.
  • CRITICAL(LY) (as in ‘… highlights the critical importance of…’ – This term is generally meant to communicate some urgent need or absolute necessity. While most authors would like to think their chosen topic is ‘critical’, many neither define to whom or what the results are ‘critical’, or even what the lack thereof would entail. In some circumstances it is used to infer some sort of threshold beyond which another state dominates, so I question the need for ‘critical’ at all in conservation writing. If you are trying to inflate the importance of your work, ‘critical’ is the word to use; if you mean a threshold, then simply state so.
  • FEW versus LESS - I’m amazed this still stumps so many people. ‘Few’ should be used to define a small number of countable (discrete) items (e.g., individuals, quadrats, plots). ‘Less’ should be applied to a measurable, continuous variable (covariate) that cannot be easily discretised (e.g., water, biomass, carbon). If you ever see someone write ‘less individuals’, get out the big red pen.
  • DATA - While on the subject of quantification, the word ‘data’ should always be followed by plural forms of the verbs (e.g., ‘… the data are…'; ‘… the data were…’). A singular ‘datum’ is one measurement and requires the singular form. A ‘dataset’ is a single group of data, so it too can use the singular form. If you want to communicate that your sample size was too small (for your intended purposes), you need to write ‘too few data’.
  • MIGHT/CAN versus MAY - I’ve often got this one wrong too. ‘May’ implies doubt or permission, so it is most often better to use ‘can’ or ‘might’ (where appropriate) when you expressly mean ‘under certain circumstances’.
  • THAT versus WHICH - This is not an easy one, and for a full discussion, visit this link. In the most basic description of the difference, ‘that’ usually introduces essential information in a restrictive clause, whereas ‘which’ introduces additional information in a non-restrictive clause. Quoting from the link given above provides some more clarity:

“What is FASCINATING to me is that . . . one way to determine . . . the correct word . . . is to ask the question, ‘Does the clause clarify which of several possibilities is being referred to?’ If the answer is yes, then the correct word to use is that. If the answer is no, the correct word to use is which.”

Seems somewhat counter-intuitive, but it’s correct (hence the confusion).

CJA Bradshaw

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