Monday, June 11, 2012

Scientific misconceptions, publication stress and criticism of molecular ecology as a research field

Posted by Erik Svensson

At Juha Merilä's research group blog, EGRU-blog, one often finds very interesting and provocative posts, that stimulates self-reflection and critical thinking. Here is one such post, which raises some critical questions about the field of molecular ecology and the lack of rigour among some of the scientists defining themselves as belonging to this novel field.

This short post actually refers to a recent Invited Review, which is likely to upset some molecular ecologists, as it is very provocative and questions much of the research practices in this very young and technologically-oriented discipline. I do not necessarily endorse everything in this article, and some points that are discussed are beyond my expertise and research interests. As for myself, I do not get very upset or feel very threatened by the message, because I am not a molecular ecologist (and will never become one), even though we have used molecular techniques in our research lab for several years now, and published several papers in the journal Molecular Ecology as well (e. g. this, this and this).

But using molecular techniques, like we have done in these studies, and even endorsing them, is not the same thing as being a molecular ecologist, in my opinion. It is not even enough to publish in the journal Molecular Ecology, I think. I, for myself,  would never define myself as molecular ecologist. Rather, I define myself as an old-fashioned evolutionary biologist interested in the ecological aspects of evolutionary change. Or sometimes I simply define myself an evolutionary ecologist, who is prepared to use observations, field and lab experiments, quantitative genetics and molecular techniques, depending on what is needed and what question that is being adressed.

In contrast, molecular ecology as a field, as I perceive it, is a primarily a discipline defined by techniques and the use of molecular markers, rather than being defined by research questions. And that is why I have never been very interested in this field, as I tend to be more interested in conceptual problems in ecology and evolution, while not being hostile towards new techniques, when they help to solve these classical problems (which is not always the case, however). Molecular Ecology partly grew out from behavioural ecology during the eighties and nineties, as new molecular methods for determining paternity in birds and other animals were developed (first DNA-fingerprinting and later microsattelites). Later, the field came to include many other research questions being adressed by the use of molecular markers, such as phylogeography and molecular population genetic structure etc.

The current review is - interestingly - published in Molecular Ecology - which I think is to the benefit of this outlet as it shows some self-criticism of the same field that the journal is built upon. Hopefully, this article will help to promote self-reflection and critical thinking, both among molecular ecologists (the main target), but also other biologists using molecular techniques. The paper is Open Acess and can be downloaded here. 

 Here are some excerpts, and quite critical and provocative quotations from the paper (Abstract and full reference given below this post):

"Many misconceptions in the various subdisciplines of molecular ecology arise as a consequence of the huge amount of data that can be relatively easily and rapidly generated and analysed. There are many more automated DNA sequencers than classes in population genetic theory, and as self-educated molecular ecologists contribute in professional service, we sometimes see misconceptions perpetuated by journal authors, reviewers and editors."


"At the end of this review, many readers will still believe that if they can properly format data for mega (Tamura et al. 2011) or arlequin(Excoffier et al. 2005), they do not need population genetic theory, they can pick it up along the way, or all the information they need is in the manual. Considering the high error rate (49.9%) in publications of a simple calculation of a population genetic parameter revealed bySchenekar & Weiss (2011), our answer is this: about half of you are right."

Finally, here is some very harsh criticism against the data publication culture in the field of molecular ecology,  and the tendency to crank out too many papers, with too many authors and ignoring much of the classic work that has already been published and which would be relevant to cite:

Abstract: The field of molecular ecology has burgeoned into a large discipline spurred on by technical innovations that facilitate the rapid acquisition of large amounts of genotypic data, by the continuing development of theory to interpret results, and by the availability of computer programs to analyse data sets. As the discipline grows, however, misconceptions have become enshrined in the literature and are perpetuated by routine citations to other articles in molecular ecology. These misconceptions hamper a better understanding of the processes that influence genetic variation in natural populations and sometimes lead to erroneous conclusions. Here, we consider eight misconceptions commonly appearing in the literature: (i) some molecular markers are inherently better than other markers; (ii) mtDNA produces higher FST values than nDNA; (iii) estimated population coalescences are real; (iv) more data are always better; (v) one needs to do a Bayesian analysis; (vi) selective sweeps influence mtDNA data; (vii) equilibrium conditions are critical for estimating population parameters; and (viii) having better technology makes us smarter than our predecessors. This is clearly not an exhaustive list and many others can be added. It is, however, sufficient to illustrate why we all need to be more critical of our own understanding of molecular ecology and to be suspicious of self-evident truths.


  1. Hi Erik! I haven't read this review, yet, but I'll jump into this discussion anyway. =-) (I plan to read this paper in lab meeting soon.) You and I have discussed this sort of problem in other contexts before, and I don't think it is limited to Molecular Ecology. In phylogenetics, it is common for people to put their data into a program and get "the tree." I spoke with someone recently who was the first author on a paper and had no idea whosoever how the phylogeny was made (and clearly didn't care). In Evolutionary Ecology, the problem is found in statistical packages, where people put their data into the computer, do a multitude of analyses that they don't understand very well, and publish the one with the lowest P-value. I think this problem is pervasive, is difficult to detect when you read someone's paper, and damages the field. In geometric morphometrics, abuses abound. It is easy to find papers where people have done statistical analyses of individual partial warps. How many people have published a GMM analysis but don't understand the previous sentence, and what the problem with it is? In sum, I suspect I'll agree with the review in ME, but I also think this is a broader issue. We need to understand all of our analyses at a high level, or at least include collaborators that we trust do.

  2. I agree 100 %, it is a broader problem. Good that it is discussed critically though, in this article. Statistics is probably misused in a lot of different contexts, unfortunately.