On retraction

Prologue: The subject of scientific retraction has been very much on my mind in the past year, as an editor, a co-author, and a member of the scientific community watching retractions (or demands for retraction) play out at other journals. Most recently, I had a stimulating Oxford style debate with Dr. Elisabeth Bik, for the annual meeting of the Council of Science Editors, which had me thinking at length about the procedures we follow and decisions we make. This culminated over the weekend in a stimulating conversation about science, law, and ethics of retraction while on a hike with a friend who is a lawyer. Inspired by that conversation, by the past year and a half, and by my own experience retracting a paper, I feel driven to share some of my personal perspective about scientific retraction. I want to note that in this essay I am expressing my personal opinions. These opinions do not necessarily reflect my behavior or decisions as Editor: in that role I am bound by traditions and procedures that may differ from my personal preferences. I also want to emphasize that I will be speaking in broad generalities of ideas in this essay, and not about particular cases. The following text is meant to be thought-provoking, stimulate debate, and is not a definitive statement of editorial policy.

    - Dan Bolnick

Let's begin by considering what retraction is for. They say science is 'self-correcting', meaning new findings get published that may contradict and eventually eclipse old misconceptions. So why do we issue retractions at all, when we could just let new papers lead us forward? I see two distinct motives (there may be more, but I think these are the two major principal component axes, so to speak).

1.  Removing information from the public record that we now know to be false. Sure, new papers may later get published that correct our view. Self-correcting science and all that. But, like an old land mine from a forgotten war, the incorrect paper is still there for some unwitting reader to stumble across and, not knowing about the newer work, cite and believe.

2. Punishment for misdeeds. The retraction itself may be viewed as a form of public censure, a slap on the wrist.

I want to do a bit of a deep dive into each of these, because each seems simple at first glance, but has complexities and caveats once we delve into them. To start, it helps to recognize that we can have concerns about papers for many distinct reasons. Sure, there are obvious and egregious cases of fraud where the data and conclusions are fundamentally false - duplicated or altered images that are central to the conclusions of the paper, for instance. But it can be more subtle than that, so let's do something analogous to the classic table we all learn about type I and type II error in statistics (false positive, false negative). The rows of are table concern validity of the conclusions: a paper can report results that are factually correct, debatable, or incorrect. The columns are about the evidence, which can be rigorous, flawed/low quality, or unethical in part, or fraudulent at heart.

Conclusions are:	Rigorous evidence	Flawed evidence	Unethical in part	Fraudulent at heart
Valid	Great paper!	Right, but for the wrong reasons	Fruit of the poisoned tree	Falsifying to reach a true inference
Dubious	Over-reaching	Debatable & unclear	Bad scientist!	Why bother?
False	False positives happen. In good faith.	Honest mistake. Luckily, science is ‘self-correcting’	Really bad scientist!	Falsifying to reach a false inference

I won't take the time to consider every single permutation, but let's start with a case study. On my hike yesterday, my lawyer friend asked whether Charles Darwin's Origin of Species was correct on all points. Clearly not, I responded. In particular, Darwin had a deeply incorrect understanding of genetics, that led him astray on a few points. We know better now. Science being self-correcting and all that. So, my friend pressed, why don't we 'retract' Origin of Species (nevermind that it wasn't published in a journal)? It contains errors. We know that unambiguously. But it is correct in the main, and of historical value.

Let's proceed to a trickier one - Wilhelm Johanssen published a paper in The American Naturalist in 1911 expounding the genotype concept of heredity, a revolutionary paper that defined 'genotype' and (to quote a recent historical paper :"the theory must be recognized as a creation that provided the theoretical foundations or the framework for the upcoming reductionist material science of genetics, quite beyond the perception of its instigator." But, towards the end of the foundational paper Johanssen makes fun (rather harshly) of the notion that genes have anything to do with chromosomes. 

So, now we have a classic paper in a journal (hence amenable to retraction, unlike Origin of Species) that makes a false claim. Should we retract it? Well, my first instinct is that it is old and part of the historical record. We make mistakes in science, and we advance beyond those mistakes, and it is valuable to historians of science to leave our tracks in the sand as we stumble towards (the mirage of?) some truth. There's a legal idea of a statute of limitations - a time period beyond which someone cannot be charged with an old crime. The time frame varies with the severity of the crime (in the eyes of the law), and some have no such limit. So is there a statute of limitation on being wrong? In that case, how old must a paper be to be retraction-proof when proved wrong? Nested Clade Analysis was wildly popular among phylogeographers when I was a beginning graduate student, but we now know the emperor had no clothes, and nobody uses it anymore (I hope). Is that old enough to escape retraction? How old is too old to bother? The answer depends on the severity of the crime, the culture and nation. It also matters a great deal whether the action was illegal at the time it was committed. Today the standard is to judge past actions by the contemporary rules of their era.

Or  is it not about age, but intent? Do we tolerate good-faith error? Johanssen had his reasons, and reached a reasonable and honest conclusion by the standards of the day with the evidence available to him at the time, and we should not judge him harshly for not knowing what we know now. Templeton was sincere in his desire to reach phylogeographic inferences and at the time we lacked the toolkit for approximate bayesian computation (ABC) methods that can test complex biogeographic genetic models. He meant well, he did the best he could with the tools at the time, and if it didn't work as well as he thought, it was honest and well-meaning, and so no retraction is needed. As an even more obvious case, I might set out to test a null hypothesis with a statistical significance threshold of alpha = 0.05. Like, maybe I want to know whether drinking carbonated water cures COVID (hint - it won't though luckily its harmless), the null is that carbonated water has no effect on COVID. And let's say the null is genuinely true (carbonated water won't fix COVID). I do my experiment, and by sheer bad luck I am one of the 5% of such studies that find a P < 0.05, and I publish a paper rejecting the null. I'm wrong, but I followed standard procedures. Should that fictional example result in a retraction following other studies? Do we generally retract all significant results when subsequent more powerful studies reach the contrary conclusion? Or vice versa? Currently I think the standard is very much that errors made in good faith don't warrant penalties at least. If they are recent, then a correction is certainly called for. Maybe even a retraction if the core conclusion is wrong. 

I did a retraction for this reason myself - a reader noted he couldn't reproduce a result with my data. I looked back at R code I wrote in 2007 while first learning R, and found a one line error based on a misunderstanding of how tails of probability distributions were being reported. It affected the core result. So even though it was in good faith, I retracted the paper (this was a few years ago). Knowing what I know now, I might have urged my past self to a less knee-jerk extreme reaction. I was driven by emotional horror. What I ought to have done was to publish a Correction. The data are still factually valid. The question is still interesting. It's just that a positive result (morphological differences between individuals affects diet overlap between them) is now a negative result (no, it doesn't). That's still a useful result that I would cite, just for different reasons. This falls into the second column bottom row - I had published flawed evidence for something that was false, and I self-reported the flaw.

There's a related tricky issue particular to theory papers. I'm not aware of many cases (any) of fabricated algebraic solutions or model results. But there are plenty of cases where authors made honest mistakes in their math, stating somewhere that x = y when in truth x != y. These can be simple typos made during writing (not analysis). Or, they can be part of the calculations and, when changed might have little to no impact on the paper's conclusions, or could radically alter them. The former clearly merit correction to the equation, the latter teeter between correction and retraction, depending on the severity of the error. But again, intent matters here. It is easy for math to be demonstrably wrong and to prove errors, compared to data analysis and experimental designs that can be critiqued but are more a matter of judgement. Yet we don't often retract math errors because corrections suffice and errors made in good faith are typically treated more leniently. 

So on the whole, I lean towards the personal opinion that good-faith errors, whether a coding problem or a random false positive or false negative (they happen!), are best corrected as science builds on past results, rather than penalized. Positive results might be corrected into Negative results. And as a field we want that to be made public freely and openly. 

We want to encourage self-correction. When Corrections (or even Retractions) have a powerful negative connotation, scientists who find (or are told of) an error in their own work will naturally hesitate to Correct or Retract. I sure stressed about it. I shouldn't have. When I retracted and publicly explained why, I received incredible positive support from the community. We want science to be self-correcting, to more rapidly reach true inferences. If we penalize self-correction, if we put an onus on it, it will happen less. People respond to incentives. If you want something to be done, reward those who do it, not punish them.

Now let's delve into a grey area: sometimes scientists collect data and reach a conclusion that is actually valid in real life. But, the evidence that they use to support their conclusion is flawed. I don't have a specific case in mind, but hypothetically imagine a researcher sequences a population of fish to look for the presence of a particular allele. It turns out their sample was contaminated, or swapped for another sample, so they aren't sequencing what they think they are.  But by happy (?) chance, the contamination or wrong sample actually has the allele, as does the population they think they are sequencing. So they correctly conclude that the allele is present, but they do so for a wrong reason. This is maybe especially likely in ancient DNA research, where cross-contamination (and absence of DNA in focal samples) is a common problem. I like to think of this hypothetical case because it highlights the role of truth / falsehood in our judgements. As an editor or author, I would be very tempted to retract such a paper, and at a minimum a correction is needed. Their published report cannot in fact prove what they claim, because the evidence marshaled for it is fundamentally irrelevant or incorrect. Yet, this is done entirely in good faith, and the outcome is factually true.  This is the "Right but for the wrong reasons" cell in the grid above. So retraction isn't simply about being correct or incorrect.  Nor is it simply about malicious fraud / conscious misleading.

Just below this in the "Flawed evidence column" I put "debatable". This is for cases where scientists are maybe tackling a difficult subject and the data are simply not definitive. It may be hard to collect good data and the results may be ambiguous. The end result might look promising to one person (who favors the idea being tested) but sloppy and unconvincing to a skeptic. This is the stuff that scientific debates are made of. My favorite these days is the unnecessarily vitriolic debate over evolutionary neutral (or nearly neutral) theory. There are strongly held differences of opinion and each side genuinely believes the other is deeply wrong. This is a scientific work in progress,  that  may be resolved with further data or theory. It is definitely not the journal's job to retract something that is in this debatable category, even if it may eventually prove to be wrong as agreed upon by all parties in the future. We are a platform for vigorous informed debate, not partisans in it. And when the debate is eventually settled, we keep the record of that process, rather than deleting the losing side via sweeping retractions.

So to recap mid-way, I started by saying one reason to retract is "Removing information from the public record that we now know to be false." That's appealing and obvious. Except that we don't usually retract things that we now know to be false, if they are old, or if the error was arrived at in good faith. And sometimes we might retract things that are actually true, if they were arrived at for the wrong reasons. 

Let's explore this latter point some more, by considering true conclusions reached in bad faith. What if a published paper reports a true conclusion, with rigorous valid data and large sample sizes (sounds great, right?), but having obtained the true data through unethical means. Maybe they didn't have a collecting permit to sample the focal species, or do the experiment in the field. Maybe they didn't have IACUC (animal care) approval, or IRB (human subjects) permission? They smuggled permitted-collections out of the country? We are moving into the "Unethical" column of the table above. Scientists sadly are sometimes overeager to do their work and adopt unacceptable methods. What do we do in this case?  As an Editor (and in general as a member of the scientific community), I think a paper should not be accepted for publication if it didn't follow proper legal and ethical procedures. Let's go with a problematic hypothetical example. A researcher discovers a miracle cure for cancer. And in their eagerness to test it they skip IRB approval, they skip informed consent, they administer it to unknowing, non-consenting individuals... and they cure their cancer. Should that paper be published? It is tempting to say, hell yes we want a cure for cancer. But we got there through procedures we cannot condone. What to do? One might be tempted to keep the paper and result, but levy some penalty on the researcher. But ultimately, it is the duty of a journal to retract papers that are arrived at via unethical means, regardless of the validity of the outcome. That miracle cure for cancer? It'll have to wait for someone else to replicate the initial study via ethical and permissible means. That means a delay in treating people with cancer, and loss of life, which feels deeply wrong. 

(Note afterwards - one twitter reader noted that if the work was done unethically and in secret do we really trust the results to be true? A fair question, but for the purpose of exploring this ethical conundrum please suspend disbelief for a second and accept that in this fictional situation the actual scientific conclusion is documented rigorously enough that we can trust its veracity).

(Note afterwards - thanks to @SocialImpurity for pointing out this real life case that is relevant to this ethical dilemma)

There's a fascinating analogy here. In US courts, there is a legal metaphor known as "The fruit of the poisoned tree". (Note, this is derived from British Common Law, and is not a universal doctrine globally). Say there is a burglary. A cop catches an accomplice, and in order to find the ringleader of the gang, tortures the accomplice (that's not ok) into revealing the location of the getaway car. Finding the getaway car, which matches the security videos, and has fingerprints all over it and the money hidden under the seat, the police identify, capture, and prosecute the ringleader. The good evidence of guilt (the fingerprints on the car with the money) is the product of a bad process (torture, the poisoned tree). And the fruit of the poisoned tree is inadmissible in court. Here's the bit that makes many people uncomfortable: the thieves go free. Not because they were innocent. They absolutely were guilty. But because the evidence of their guilt is the result of a flawed process. So we throw it all out. Much like we would throw out all scientific results (the fruit being the miracle cure) that arise from the poisoned tree (the IRB human research violations). The motive in both cases is to deter bad behavior (by scientists, or police) in pursuit of a good outcome. The consequence is that good outcomes (cancer cure, convicting the guilty) are set aside fully knowing they are good outcomes. Now, I think many of us get uncomfortable at this result, and would argue that the guilty criminals should be convicted and the police punished. But, that's not the American & British legal tradition. I should note that the Fruit of the Poisoned Tree metaphor is strictly about police behavior, and has no legal teeth that extend into other areas like scientific publishing.

Note that the fruit of the poisoned tree doctrine will probably make you squirm. I do. I'd love to see that miracle cure made available. But what ethical boundaries are you willing to waive? Experiments on people without consent. That's bad. But do the ends justify the means for you? That's the logic (I presume) that drove the syphilis experiments on the Tuskegee Airmen, or Dr. Mengele's horrific experiments on Jewish concentration camp prisoners. Are you willing to use the results of those experiments, willing to publish them, or let them remain on the books? I'm not.

But these are extreme cases. Let's turn the dial of moral outrage down, and likewise adjust the slider bar away from "cancer miracle cure" towards something more realistic. Would you publish (or, retract if already published) a paper that used stolen archaeological artifacts? Genome sequence data taken from non-consenting individuals unaware of what their drawn blood was to be used for? Currently the expectation is that Editors like myself would reject papers that used ill-gotten samples to reach a conclusion, regardless of the validity of the conclusion. And that standard makes no reference to how important the conclusions are (e.g., an interesting intellectual advance, versus the miracle cure, both are equally subject to this standard).

So, hopefully we are in agreement that a scientific result (whether true or not) arrived at through unethical means will get rejected (and maybe the experiment redone properly and ethically, if perhaps more slowly). But let's unpack this some more and ask what the statute of limitations is here. How far back does the principle apply? Institutional Review Boards for human subjects research began in 1974 (see this article for a useful history). That means no research before 1974 (the year I was born, incidentally) was IRB approved. Today we require IRB, so does that mean all journals should retract human subjects research from before 1974? Clearly we don't do that. The key difference is that the pre-1974 papers were adhering to the ethical standards of their day.

There are other kinds of unethical behavior that get caught up in scientific publishing. What constitutes retraction-worthy unethical behavior? What if the communicating author(s) left someone off the author list who contributed significant work that would normally be sufficient to warrant co-authorship. That's not cool, its not ethical, but is it retraction worthy? What if they added an author who really did nothing at all, simply to gain credibility by association, or as a bribe for some quid pro quo? Unethical, in both cases. But retraction worthy? Probably not, partly because it can be hard for editors to effectively adjudicate who did or did not earn the right to be listed as an author. And partly because there are other simpler remedies - adding an author, or publishing a statement removing an author.

To push this line of questioning into an even more uncomfortable realm, what if the lead or senior author on a manuscript, or a published paper, was guilty of sexual assault? Does unethical behavior that is entirely decoupled from the paper in question, impact the editorial board's view of a scientific text and conclusion? Should we decline to publish, or retract, papers by individuals whose behavior the Editor finds abhorrent? Publishing their paper promotes their name and role in the scientific community, and we might not want to do that. But, the technical conclusions of the paper are (in this hypothetical case) entirely unaffected by the authors' behavior. If we open the door to editorial decisions based on abhorrent behavior, who gets to determine that criterion? Something that is abhorrent and unethical to one person might be celebrated by another (not sexual assault mind you, but other forms of sexual behavior, or political or religious belief perhaps). How much evidence must be given to the journal's Editor to reach an informed decision about whether or not the abhorrent behavior took place? This particular issue ties me in knots, and I confess I don't know what I would do in such a situation, and am simply glad that it hasn't come up in my role as Editor handling new paper submissions, to my knowledge (I wouldn't be at all surprised if some current or past authors have been guilty of such offenses). What would you do? 

Speaking of abhorrent, what about racist and eugenicist research of the past? The American Naturalist has plenty of articles by Charles and Gertrude Davenport, leaders at the Cold Springs Harbor lab for eugenics. Should we retract their papers from the 1900's through 1940's? Or, one of the first women to publish in The American Naturalist wrote a horribly racist rant that is offensive enough that, when I quoted from it in a lecture (to drive home the point forcefully and openly that AmNat published awfully racist stuff), a audience member subsequently admonished me for showing it. Should I go back and retract that paper, which I suppose I have the power to do as Editor? I wouldn't, simply because I think that would be whitewashing an ugly past that we are better off acknowledging and confronting openly rather than making it as if it never existed.

We are almost done, I swear. But I'm having fun posing these questions.

The last column in my table, above, concerns downright fraud.   Image manipulation. Data alteration or fabrication. Changes to data or misreporting results with the intent to mislead. The italicized bit can be hard to prove without mind-reading, so often we content ourselves with evaluating whether data or an image are biologically plausible. If not, the results are false and data are not trustworthy regardless of intent. In effect, we say that (not knowing an authors intentions or actions) a paper could either be in the right hand column (fraud) or the bottom row (falsehood), and either one could be retracted. In recent cases, decisions to retract reflected patterns in data that appear to be fraudulent, but we cannot with certainty discern whether there was bad intent, or simply large-scale and recurrent accidents in data management. The latter seems deeply unlikely, but from the standpoint of journal decisions (retract or not) the distinction is irrelevant.

So to recap this second part of my musings, I started by saying the second reason to retract is "Punishment for misdeeds." Certainly the 'Fruit of the Poisoned Tree" doctrine I described represents a punishment, because the scientific conclusions may be really true and valuable yet we'd still retract - as a penalty and as a deterrent to future scientists considering the same misbehavior to get data. As editors and a community, we would walk away from true knowledge if it was ill-gained. But I expressed discomfort at the thought of using retractions as a stick to punish some other forms of unethical behavior. And actual fraud we might argue that the retraction is for biological falsehood (or lack of trustworthy evidence at least), rather than as punishment per se.

Note that I'm absolutely not saying that misbehavior should go unpunished. Sexual assault, for instance, should be prosecuted in court. Sexual harassment as well, or at the very least pursued seriously and in good faith by the university or institution where the harassment took place. What I am saying though is that punishment may not be the journal's primary role. The journal serves to communicate information, and (to the best of our abilities) to check that the information is good. We can decide to stop communicating something that we no longer trust. But our capacity for punishment is very limited. At most, I could retract papers from an author who committed systematic fraud. But I'd check each paper separately rather than assume the fraud was universal. Perhaps I could refuse to consider any further submissions from that author. But what if they learned their lesson and now pursued an honest and careful path to new science? Should we forgive and forget (and verify)? Ultimately, journals only have the ability to punish using the limited tools at their disposal - the papers they publish. It is the employer (the university, institute) that has the power to fire, or reassign duties away from research to teaching, or put on unpaid leave, etc. The employer provides money, and money has a leverage the rest of us lack.

There's another reason why I generally am wary of using retraction as a form of punishment. I noted earlier that we want to encourage people to self-correct - that helps clean up our literature faster. When retractions are systematically equated with punishment, authors who find errors will be more hesitant to self-retract. One solution would be a linguistic one - if we adopted two different terms for two different kinds of retraction. Honorable self-correcting retraction, and dishonorable retraction for fraud or unethical behavior. Call them subtraction and detraction, respectively (I'm open to alternatives). But I think it is crucial that we punish, and crucial also that we reward honest self-correction. These need to be kept separate in the sociology of science.

   

So, back to my original premise: when is it appropriate to retract?

Are we removing information from the public record that we now know to be false? Are we punishing? The answer is subtle, because we don't want to conflate punishment with retraction. Because journals have the power to retract but limited power to punish, which is better done by employers (who journals can and should notify). Because we sometimes retract things that are true (fruit of the poisoned tree) but often don't retract things that are false (in good faith, or old). 

This subtlety is made even more challenging by a whole other set of questions: is the false or fraudulent information central, or peripheral, to the conclusions of the paper in question? Obviously if the primary point of a paper turns out to be fundamentally incorrect (as in my own retraction for a coding error), retraction is a fair outcome. But what if it is a minor aside? Let's say Matt Daemon describes a detailed experiment on how the proportion of feces in dirt affects plant growth on Mars. And he says in the paper that he was wearing a blue space suit when in fact it was green. That's a falsehood, but irrelevant to the biology. It should be corrected, but has no bearing on the conclusions. Or, he falsely reports that feces helped grow potatoes on Mars, then builds and obtains analytical solutions for a set of ordinary differential equations that correctly establish that nutrient addition would help. The math is true. Do you retract it? Doing so would be leveling accusations at an innocent equation by assuming guilt-by-association.

The last thing I want to comment on is the role of the journal, and those who volunteer time for it, in publicizing retractions. If the point of a retraction is to correct something we now know is false, we must reach out to people who previously read the paper and notify them of the retraction. Otherwise, they will continue to hold a false belief based on their original reading of the paper before retraction. Furtive retraction is no retraction at all. And, if the point of a retraction is punishment (which, again, is not my core belief), again the punishment has the most impact if it is public. Either way, retractions need to be clearly conveyed with the original paper on the journal website, with corresponding changes to Jstor, PubMed, Google Scholar, etc. Using social media to disseminate the fact of a retraction is entirely reasonable as a means to connect to readers who use that channel. The drawback of social media of course is the ease with which it tips into personal rather than professional. But any procedure that disseminates the announcement of one (or more) retractions will invite gossip, speculation, extrapolation, and personal judgements, especially when misconduct (or the strong suspicion thereof) is involved. 

The other interesting side of social media dissemination of Correction / Retraction decisions, is that it invites armchair editors to inveigh. I've been called a "coward" and "lazy" on social media for a decision to issue a Correction rather than Retraction, by someone who didn't know the paper, hadn't read it, didn't understand the negligible role that the data played, or the nature of the model being reported (not parameterized with or testing data). If there's one thing I hope the essay above has taught, is that retraction and correction span a diverse set of complex considerations. There are considerations of scientific fact or error. These may be central or peripheral to the paper. They may be reached by ethical or unethical means. They may be old errors or new ones, satisfactory by the standards of their day but not today. And each of these dimensions is a continuum ranging from totally-fine to absolutely-bad with grey areas in between. Sometimes, questions of fraud or retraction are unambiguous. Editors should engage fully with these and do the right thing. But challenges to papers can also fall into grey areas, or be good by one criterion and bad by another. The Editor's challenging job (supported by their editorial board and reviewers in consultation with authors) is to reach a final judgement. These are, in my experience, sometimes easy and sometimes hard. So, if an Editor simply ignores critiques, that's bad. But if they don't act exactly the way you would like, consider that they are weighing many themes and may have a justifiable (not necessarily cowardly / lazy) rationale for their decision.

Thanks to J. Shukla for inspiring conversation.

PS, added after: For some reason this site isn't allowing me to reply to comments. My apologies. So a couple of responses here.

1. I remain horrified that Google Scholar and WebofScience don't pair retractions with their targets so when a paper comes up in a search you immediately see it is retracted.

2. I haven't ever received a request to retract a paper because the author was engaged in personal misconduct (e.g., sexual harassment, etc), so the scenario mentioned there is hypothetical, meant to be thought provoking and ask, what are the boundaries between misconduct that warrant retraction, and misconduct that does not. The Committee on Publication Ethics standard is that it should be pertinent to the conclusions of the paper, but that has fuzzy boundaries.

Is biological adaptation and publishing papers the same thing?

 

Guest post from Pim Edelaar:

Publish or perish ... You have probably heard this “advice” before. And while there are many alternative ways to be a valuable and contributing academic, if you do research then publishing your science is indeed an important responsibility. And at the same time a daunting task. There are many books and postings about how to write a good paper (e.g. Andrew´s entry “How to write/present science: BABY-WEREWOLF-SILVER BULLET”: https://ecoevoevoeco.blogspot.com/2014/10/how-to-writepresent-science-baby.html), but here I wanted to explore whether there are underutilised strategies to get your paper published where you want to get it published. I will intersperse this with some parallel observations on organisms that face a similar ordeal but then in the eco-evolutionary arena, and to what extent we, as researchers, may have some blind spots with respect to how organisms solve this.

Two years ago Dan Bolnick and I published a paper in Trends in Ecology and Evolution (Edelaar & Bolnick 2019: https://pimedelaar.org/publications/) where we presented a classification of the processes that can increase the match between an organism and its environment. Because the better that match, the greater its ecological performance and the higher its expected fitness. And in order to explain how to apply this classification to real life, in talks I sometimes use human examples, and ask the audience for strategies that can result in the desired match. Like the publishing of a paper in a good journal. This typically results in a long list of possibilities, and it turns out that these can always be nicely categorised and understood using our classification. Interestingly enough, the audience often does not mention some additional strategies that are also viable. So we proposed that the classification of our paper can help us to focus our attention on such under-recognised strategies, not only in publishing but in biology in general.

Our classification is composed of four processes (the paper goes into the derivation and justification of these, but I will not repeat that here). The first one is “good old” natural selection. In terms of publishing, that would perhaps be equivalent to sending a randomly generated paper to a random journal, and hope for the best. If you use this strategy, then keep reading because I think you can do better. (Although some predatory publish-for-pay journals or conferences might accept virtually anything, even near-random papers: https://pdos.csail.mit.edu/archive/scigen/). For the other three processes the organism (so you as writer!) takes an active role, and either changes its phenotype (your paper) or the environment (the journal). This second option may seem a bit odd at first sight, but if what is important is the match between a phenotype and its environment to perform well (the match between a paper and the journal to be published), then it really does not matter which of the two interacting components is changed in order to improve this match. So changing the environment is a perfectly valid, and sometimes under-recognised, strategy to achieve one’s goals. 

Still, let’s first look at the thing we tend to spend most time on, the development of our manuscript. This is what we have been taught to do as researchers, and what we could perhaps compare to the development of an organism, resulting in a phenotype. What strategies do we have to make the best paper? (Important note here: I am talking about the best paper in the eyes of the journal, since we are only focussing here on getting it published. Whether it in fact is a good paper depends on what readers think. And these views don´t always align, so we may need to take this into consideration and reach some compromise. Unfortunately this is even more relevant for research proposals: you need to convince the funders, virtually the only people who will ever read your proposal.) 

So, how do we nicely “develop” a good paper? We can look for an interesting or unresolved topic, design clever or ambitious experiments, use cutting-edge methods or materials, collect or analyse valuable data, make appealing figures, write a useful or provocative discussion, write clearly and engaging (see Andrew’s really useful entry again, if you didn´t do this before: https://ecoevoevoeco.blogspot.com/2014/10/how-to-writepresent-science-baby.html). To do this better, read and think, practice and edit, get feedback from other people, collaborate with other people, etcetera. 

 My technician Fatima working with our optogenetic fruit flies – cutting-edge materials, but not that you can see that ...

Those are the usual strategies. But if our only goal is to get a paper published, then alternative strategies do come to mind, some questionable and some outright rejectable. For example, adding names of famous people to your list of co-authors, hoping for better reviews or editorial preferences. Double blind reviewing (http://robertfeldt.net/advice/double_blind_reviewing/) hopefully puts the scope for this dubious practice to rest. Or selective citation, where you misrepresent what has been written before, or you ignore citations that counter your message (one of the hardest things to spot as a reviewer). Or only presenting the statistical analyses that resulted in significant results, while ignoring equally valid approaches or models or outlying data (https://en.wikipedia.org/wiki/Researcher_degrees_of_freedom). Or even fabricating data. Of course I am not trying to give you ideas of how to get your paper published using strategies that are not accepted by the scientific community, I simply want to show that conceptually they align with the strategies for producing a good paper – it is all about producing the product that matches best with what the journal is looking for. If we think about the development of a biological organism, then indeed there is no ethics and fairness involved and the most unpleasant appearances, weapons, toxins and behaviours might appear, as long as they get the job done. 

 

Assuming you stick with accepted practices (highly recommended, for the sake of good science and yourself), then one common and useful advice here is that it helps to write the paper with a specific journal or at least a specific audience in mind, since this will increase the probability that your paper will be a good match with your target journal or a similar one. So you do all of that ... and then comes that dreaded rejection. Now what? After we have dealt with this mentally (see Andrew’s entry on this: https://ecoevoevoeco.blogspot.com/2016/02/dealing-with-rejection.html), we look for another journal, and resubmit our manuscript. But before we do that, it of course would be wise to adapt our manuscript in order to improve the match. Whereas the previous section was more about the innate development of the first submission of the paper, this response of producing a changed submission is comparable to adaptive phenotypic plasticity, where the environment (the journals) rule, and the organism (the manuscript) responds. 

What strategies do we have to adapt our paper best to the next journal? Apart from adhering to journal requirements (oh, the joy of reformatting citations ...), it is often a good thing to take reviewer comments seriously, and improve your paper where you can. Never resubmit the same manuscript unchanged to another journal! The chances are that (1) you really could have made a better product (previously rejected papers are more cited: https://www.sciencemag.org/news/2012/10/scientists-may-feel-rejected-rejection-rare-publication-study-finds), and (2) one of the reviewers for your new submission is the same as for your old submission, setting yourself up for a nice rejection again. 

Now maybe somebody noticed, above I already mentioned a strategy that is actually not about the phenotype, but about the environment: “write the paper with a specific journal in mind” and “we look for another journal”. And of course you would be wise to carefully select your journal to improve your chances of acceptance! Again, if the challenge is to obtain the best match between your paper and the journal, you should not ignore this other side of the interaction! So check which journals might be interested in publishing your paper. Going through your references might give you some ideas, and if you have read many papers or browsed many journal issue indices, you might have a feel for what different journals tend to publish (both in terms of topics and in terms of quality). Advisors and colleagues can also help with identifying a good target journal. Journal editors and potential reviewers may hate me for this comment, but if you have time to spare, you may aim a bit high in terms of journal quality in the beginning, if you think your paper has a realistic chance of getting accepted there. But be warned that “going down the ladder” can take a lot of time, energy and perseverance (or what some call stubbornness, a waste of people’s time, or stupidity). I think my personal record is with Edelaar et al. 2019 (https://pimedelaar.org/publications/), which was submitted 9 times (Nature, Ecology Letters, Science, Nature Ecology & Evolution, Nature Communications, eLife, Nature Ecology & Evolution again, Evolution, and finally Proceedings of the Royal Society B), because I was (am) convinced it is a damn good paper that deserved (and got) a good place. But that took over 3 years, and a lot of reviewer effort (so let’s hope it gets read and cited). If you follow this strategy a lot (and I think most people do to some extent?), it would be nice if you also reviewed your fair share of the manuscripts seeking their spot in the light (read: you really should ... See “The Golden Rule of Reviewing”: https://www.journals.uchicago.edu/doi/full/10.1086/598847). (You can show your contributions to science as a reviewer on Publons, e.g. see my page: https://publons.com/researcher/1175333/pim-edelaar/metrics/)

Not ignoring the environment as a target is also true for organisms: the phenotype-environment match can be improved by tweaking both components, simultaneously or independently. Indeed, there is overwhelming evidence that organisms select aspects of their environment in order to increase their expected fitness: they select habitats, prey types, sexual partners, social partners, and so on. While selecting what to eat and with whom to mate might not appear to be comparable (and should not be confused – https://www.youtube.com/watch?v=ycuzVQmVj44), it all has to do with what we called in our TREE paper’s classification “selection of the environment”, in the sense of selecting the environment with which the phenotype then has to interact. And the outcome of this choice might depend on how the phenotype is, or in our case, how our paper is. So choose wisely ...

Choose wisely ...

There is one last process that organisms might employ to improve the environment they have to interact with, and we called that “adjustment of the environment”, since it does not involve the choice out of a set of available alternatives (as for selection of the environment), but the changing of the characteristics of the single option they work with. Together with selection of the environment, it is often not recognised as a distinct process of adaptation, and commonly treated as “just a behaviour”. Narrow-sense niche construction falls into this domain (making physical constructions like nests and burrows for example), but also somehow changing the characteristics of the organisms an individual might interact with: changing the perception and behaviour of a competitor or a (potential) sexual or social partner, changing the behaviour of an infected host, those kinds of things. Humans are masters in this strategy, and if you look around and compare what you see with what the undisturbed landscape and biological community would look like if there were no humans, then I hope it is clear what I mean. We adjust our environments to how we are and what we need to perform well (or at least, we think so).

Paradoxically enough, I think this is one of the more under-recognised “strategies” in publishing, where the aim is to change the journal such that its fits our paper. It is hardly ever suggested when I ask people for publication strategies in talks, so not only in biology but even with respect to our own lives it appears to be a bit of a blind spot. But the communication with the editor and reviewers falls under this umbrella: writing an appealing and convincing cover letter, responding well to editorial and reviewer comments (that does not mean doing everything they ask for, but at least politely explain why some changes have not been implemented), and perhaps even talking to an editor at a conference or via a pre-submission inquiry. One of the comments editors keep making in public, is that they want to work with authors to get the best paper possible, but I think this interaction also involves (perhaps unconsciously) movement (understanding) from the editor’s part on what the paper is about. Alternatively, the writer takes up the role of the journal: editing a special issue usually means that you can publish one or more of your own papers in that issue. I don´t think this is the main motivation for people editing special issues, but I do think people see that as a nice side effect for their hard work as editors, and it may swing the balance towards undertaking this endeavour. More questionable practices also fall under adjustment of the environment: proposing favourable colleagues as reviewers (how many people regularly suggest their worst critics?), excessive citing of papers written by the handling editor and reviewers, or even blunter types of bribing (for which I don´t know examples, but I am pretty sure it has been done or attempted) or threatening and bullying of editors or reviewers. (Please don´t do these things.) And again, for biological organisms nothing is out of bounds, so the most intricate ways to manipulate their abiotic and biotic environments have evolved. Like a parasite that manipulates an infected ant to swell up and change colour and to perch motionless at the top of a plant, such that it might get eaten by a bird that mistakes it for a juicy ripe berry – all of that so the parasite gets into the bird, its vector for dispersal (https://www.nationalgeographic.com/animals/article/parasite-transforms-ants-into-berries).

A normal and an infected ant

Where does this exercise of revising our goal of publishing our paper in a desired journal using the classification framework leave us? Perhaps you picked up an extra suggestion on how you can increase the chances of getting your paper published – in an honest way. Perhaps you know of a strategy that I missed, and it would be great if you could write these in the comments. My prediction is that it can always be classified as one of these three processes: somehow changing the paper to match with the journal, some sort of selective process regarding the journal to match with the paper, or some sort of adjustment of the journal to match with the paper. (What do you think, is this still true in a new world with Open Access, public repositories, Peer Community In (PCI) journals, self-publishing, etc.?). The same is true if we consider the phenotype-environment match in biology: I think that anything adaptive that individuals do can be classified by these three processes (changing the phenotype, selecting the environment, adjusting the environment). Likewise, I think that this classification can help us to recognise specific behaviours and strategies for what they are, and how they compare with other seemingly unrelated strategies (e.g. choosing what to have for breakfast, and with whom to have it, involve similarities in choice and constraint). And perhaps most of all (or at least I hope so), it can help us recognise that adaptation is not only about the organism adapting to its unmoveable and ever-demanding environment: organisms have tons of ways to adapt their environment to themselves. Even though we know this, it is not always something we take into account when designing research projects or interpreting results, so doing that more often in your papers should be interesting and valuable. And that happen to be two traits that help getting your papers published ...

 

Admission essays rebooted

There is a lot of excellent discussion these days about how we diversify our organismal biology community (ecology, evolution, behavior, etc). One of the keys needs is to admit more students from more diverse backgrounds into our training programs, whether at the undergraduate or graduate level. But often applicants from diverse backgrounds have a disadvantage in the application process, because they may not be as well connected to people in our field who can advise them on *how* to apply. There is an art to applying for a graduate program, which involves knowing the many things that admission committees and professors are on the lookout for, and red flags we are tuned to avoid. Having a good network of well-informed and dedicated mentors is crucial to help students know what topics to cover and how to approach things like direct contact with potential mentors. If applicants from underrepresented groups are less likely to receive this mentorship, their applications aren't as strong. So an important step in diversifying our scientific community is to rethink the application process. 

Many graduate schools are engaged in application-reboots. I briefly describe one such reboot, which I have been involved with at two different universities - first the University of Texas at Austin, and then the University of Connecticut. I do this both to get feedback, and to perhaps inspire other departments to consider following suit, if you feel it is a good idea. 

Specifically, I want to focus on the admissions essay. Anyone who has reviewed graduate school applications in EEB is familiar with the formulaic application essay opening, in which an applicant waxes eloquent about how they love nature, or turtles, or biodiversity. The "I grew up searching the local stream for critters" style opening story may often be heartfelt for the author, but to the admissions committee it often feels trite - they've seen variants on that theme before many many times.  But what follows that opening statement is... variable, to say the least. Each applicant has their own guess as to what we want to hear about. Sometimes this is spot on and they weave an engaging story about their motivations, past research experiences, future research goals, career aspirations,  strengths (what they will add to the lab & program) and weaknesses (what topics they need to learn more of). But all too often we get a subset of these topics, and different subsets from different applicants. The result is an apples-to-oranges comparison problem for the admissions committee. Students who don't deliver on the full set of topics we'd like to know about (e.g., those from underserved backgrounds often) are put at a disadvantage. 

A solution I'm fairly passionate about is to replace the application essay (which is very open-ended) with a series of more precisely targeted short answer questions. These specify the topics that we want to know about, directly conveying to the applicant what they should tell us about. For specifics, see the templates at UConn EEB and UT Austin EEB. For example, at UConn we ask questions like:

• Describe your reasons for going to graduate school and your long-term career goals. (approximately 100 words)
• Describe your research interests, the scientific questions that you hope to address as a graduate student, and your motivations for choosing this topic. If you have ideas about specific hypotheses you would like to test, study systems you think might be suitable, or approaches you would take, please provide that information as well. The Admissions Committee recognizes both that not everyone will know these details when they apply, and that research directions often change once a student enters graduate school. (approximately 400 words)
• Describe any prior research experience, including the research teams you worked with, the topics studied, your role in the research, the skills you gained, any math or computing skills learned, and any papers or other products that you were directly involved in creating. It is not necessary to repeat everything that is in your CV (see below); use this section to highlight the points that you think are most relevant to your planned graduate research. (approximately 400 words)
• Describe any other relevant work or teaching experience that you believe has helped prepare you for graduate work. This could include non-academic work experiences, for example those that demonstrate commitment, a strong work ethic, ability to work in a team, ability to work independently, etc. Also use this section to describe non-research skills that might be relevant to your planned graduate work. (approximately 150 words)
• Describe one obstacle you have faced in research, work, or life and how you either overcame it, or used the experience to inform your future outlook or actions. (approximately 150 words)
• Describe any activities you have engaged in that demonstrate a commitment to enhancing diversity and inclusion in science. (approximately 150 words)
• Please tell us anything else you would like the Admissions Committee to know. (approximately 200 words)

If a student has nothing to say on a topic (e.g., they never taught before in any context), we try to make it clear that its fine to leave some areas blank. For instance at UConn we specifically state: "Provide what information you can for each and note that the Admissions Committee recognizes that not everyone will have detailed answers to every question." 

The goal here is to lay out specific expectations, so the students aren't left to guess what we are looking for, and don't forget to leave out key elements we might wonder about. The result is a set of essays that are much more parallel between applicants, which helps to compare them more effectively and to better recognize the multi-dimensional nature of people's strengths. We might have some applicants with stellar research experiences, others with exceptional teaching, and still others who don't stand out as much in either area but had exceptional obstacles to overcome to achieve the things they have managed. Personally, at both UT Austin and UConn, after implementing these changes, I felt much better able to compare applicants. I get the sense my colleagues feel the same (at least, neither department has yet abandoned these formats).

So what are the drawbacks? For one, I worry that having an atypical application process might deter applicants. If many other departments we 'compete' with for applicants have a standard one or two page essay format, where the contents are up to the applicants, then a student might write an application once, and submit it to multiple institutions. Then they come to us and realize there's a whole other format, and decide maybe to not bother. So far I don't think we've seen a drop in application rates associated with this new format. And students who are genuine in their interest in coming here won't be deterred (I think). But, it worries me a bit. Luckily, there's a solution: the more institutions that shift to a comparable format, the less of a burden it becomes on the applicants. I'd love to see a variant of this become more common. Because I really do think it aids under-served applicants in knowing what we are looking for, and it aids the faculty in comparing candidates in a multivariate sense.

Another worry is that by making everyone shoehorn their lives into a few pre-specified questions, we actually obscure some of the diversity of perspective, approach, experience, and make it hard to really see a creative mind at play. I don't really buy that, because I've seen great and creative answers to these pre-fixed questions, and we make a point of leaving something open-ended (e.g., the last question from the UConn list above). 

This experiment in reframing application questions is recent, and I'll be interested to see how this plays out. I'd also welcome comments, ideas, and others' attempts to crack similar challenges in other ways.

Oh, and if you are wondering about whether we require GRE scores, UConn dropped those this year. That's a whole other topic, for another time.

_____

Added later:

Theresa Rueger commented and for some reason I couldn't reply directly so I'll write my reply here:

Great question. I honestly don't know. I can't speak for how members of underrepresented groups might or might not feel about this question, and would *greatly* appreciate feedback on that one in particular. Note, though, that even a privileged white cis-male 3rd generation college student such as myself can engage with diversity and equity issues in proactive constructive ways. Its not necessarily who you are, but should expand to include what you do. As a department, EEB at UConn is really devoted to DEI issues, and my colleagues felt strongly about including such questions in grad admission, as we also do in faculty applications (requiring a DEI statement that plays a strong role in distinguishing among otherwise equally excellent research applicants).

In praise of double-dipping from data.

 

There’s a widely held view in biology that one dataset should equal one paper. Using the same data in two papers is often viewed with suspicion. To readers, it may appear that the authors are trying to get twice the academic credit for a given amount of work. This even has a name, ‘double-dipping’.  (Note, this is distinct from publishers’ ‘double-dipping’ to get both author open access fees, and also institutional subscriptions).

 

I recently double-dipped. Triple-dipped, Quadruple-dipped, and more really. I was both very hesitant to do so, and yet happy with the result. I’m writing this post to explain what I did, why I did it, and why I think double-dipping can be an excellent choice for authors, readers, and funding agencies. So much so, that I think funding agencies should consider fellowships to support salaries of students, postdocs, and perhaps even faculty to revisit published data to squeeze more insights.

 

What I did.

In 2009, I obtained funding from the Howard Hughes Medical Institute to pursue a study of how stickleback immune genes evolved across complex landscapes of populations connected by varying degrees of gene flow (for hosts and parasites). The focus initially was meant to be on MHC.  Our very first order of business was to set the stage for the evolutionary genetics work by learning the basic natural history of the host-parasite system I intended to study. What parasites are present in the area I worked in on Vancouver Island? To what extent do they differ from one stickleback population to the next? To what extent is this parasite community variation attributable to abiotic variables, biotic communities, fish population traits, or fish genotypes? By answering such basic natural history questions, we get a foundation to choose the most interesting populations for evolutionary genetic contrasts. 

 

To collect such data, we conducted a field survey in May 2009. “We” included my graduate student Will Stutz (who helped conceive of the project to begin with), a grad student collaborator Travis Ingram, a new PhD student Yuexin Jiang, two undergraduates (Chris Thompson and Todasporn Rodbumrung), UBC graduate student Travis Ingram, and a high-school biology teacher Kim Hendrix (most of us pictured, above)
. Over the course of 4 weeks on Vancouver Island we sampled ~100 stickleback from each of 45 populations, a mix of lake and stream and estuary sites. Then from fall 2009 through 2013 I employed Julie Day then Kim Ballare as research technicians to count parasites, characterize stomach contents, measure ecomorphology for ~3500 fish specimens. From 2013-2014, Hollis Woodard worked as a technician in my lab to genotype a couple thousand stickleback for MHC, and Yoel Stuart helped her do ddRADseq on a subset of individuals to get neutral genetic markers. The result was an enormous natural history dataset on diet, morphology, infection, MHC, >100,000 SNPs, all set within a geographic context of varying lake sizes, elevations, etc scattered across watersheds on north-eastern Vancouver Island.

 

The resulting data set was enormous, and intimidating. I had all the data in had by sometime in 2014, and it took me nearly a year of on-and-off-again work just to organize and curate the data to check for errors, odd outliers, misspelled population IDs, and all those little things that can creep into a dataset that has been handled by many separate people. For several years in a row, the data would lie fallow for months on end, then I would find a bit of time to work on analyses, only to set it aside and start over half a year later. The problem was this was nobody’s primary dataset. It was meant to be exploratory (with some a priori predictions to be sure), and there was much to explore, and I was the sole person delving into these explorations for a long time. Each summer I’d spend a couple weeks on Cape Cod with my family and I’d sneak in some time at a great French Patisserie spending a few hours analyzing these data while my kids were in summer camp (photo below). Over time I built up a set of analyses that answered my a priori questions and went a step further to describing the spatial structure of the parasite metacommunity in great detail.

 

Thousands of lines of R code later, it was time to write. But I pretty quickly found that the writing built up to over 100 pages of text. I was writing a book, and not even I want to read a book-length document on the natural history of stickleback parasites on Vancouver Island. The trick was, there are so many distinct questions that can come from a dataset of this size. Do we analyze parasite species richness? Or multivariate composition? Do we analyze each species of parasite separately, or via ordination in one group? Do we include genetics, or host diet, or lake abiotic conditions? These all are interesting, all tell us something different, but to do them all simply took way too much text, it would strain the interest of any but the most dedicate readers.

 

At some point, in stepped Emlyn Resetarits (a PhD student with Mathew Leibold and myself), who helped convince me to split this up into bite sized parts. The result:

1)    A paper focused on parasite metacommunity composition – which species are found where, and which species are found together or apart, and what predicts this variation? We throw in a big GWAS study of many parasites in the appendix, which might have been a paper unto itself. Bolnick et al 2020 Ecology

2)    A paper focused on parasite metacommunity diversity – not so much who is found where, but how diverse they are, which revealed a richly different story than species composition alone. Bolnick et al 2020 Ecography

3)    A third paper set aside the parasite information to focus on the evolutionary ecology of stickleback diet and individual specialization. This was revisiting a topic that was core to my academic beginnings, which I hadn’t touched in a few years. But the dataset on stickleback diets (collected to understand infection patterns) was also exactly something I’d hoped to achieve for years. This turned out to give a beautifully clean and intuitive result that generalist populations (eating roughly equal mixes of benthic and limnetic prey, in mid-sized lakes) had the greatest dietary and phenotypic diversity. But, these functional variances were unrelated to genomic heterozygosity, which increased steadily with lake size. In short, neutral genomic diversity and functional ecological diversity were unrelated, and responded to entirely different features of the populations’ environments (Bolnick and Ballare, 2020, Ecology Letters).

4)    That Ecology Letters paper happened to include, in passing, a GWAS analysis of SNPs related to lake size. Are there loci whose allele frequency varies predictably between smaller versus larger lakes, and whose heterozygosity was largest in mid-sized lakes? Well, at an American Naturalist conference right around when this paper came out, Diana Rennison and I compared notes. I had this GWAS between benthic versus limnetic allopatric lake populations, and she had population genomic data for benthic versus limnetic species pairs in symatry. Why not compare these? Harer et al 2020 Molecular Ecology was the result. Remarkably, the benthic-limnetic species pairs show both more repeatable evolution, and greater divergence, than allopatric populations.

5)    Most recently, we finally got to the original motive for this data collection: Major Histocompatibility Complex genetic diversity. MHC (here MHC IIb) is among the most diverse genes in the vertebrate genome, frequently said to be under balancing or frequency-dependent selection to maintain this diversity. The whole point of this survey was to determine the diversity of MHC, and its association with parasite load and diversity. Well, with help from Stijn de Haan we finally ran the bioinformatics pipeline to identify alleles and genotype individuals (using a bioinformatics protocol developed by Will Stutz, the PhD student who first planned this study with me). Then Foen Peng adopted the dataset to run statistical analyses and write. The resulting paper just posted to Molecular Ecology a few days ago: Peng et al 2021 Molecular Ecology.  Disappointingly, (e.g., contrary to our starting motives) very little about the parasite community tells us anything about MHC. Instead, MHC diversity seems to be best predicted by neutral genomic diversity, not parasite diversity. And MHC divergence between populations is best predicted by genomic Fst, and not parasite or ecological differences. This only deepens the puzzle of MHC diversity for us, because it certainly is insanely diverse, yet we twice now have failed to find a clear adaptive explanation for this variation (see also Stutz et al 2017 Molecular Ecology, which used a different set of populations and different analytical approach).

6) Ultimately, I am glad to say we mostly moved away from the MHC focus, which seems to not matter for the parasite that engages us most, the cestode Schistocephalus solidus (pictured below), and instead started doing QTL mapping, expression, and GWAS analyses. The data set collected in 2009 for some basic natural history proved to be extremely useful in motivating and guiding our genetic mapping studies (manuscripts in prep, and also Weber et al 2017 PNAS).

 

Why I did it: the benefits of N-dipping

Now, apologies for what must seem like a lengthy advertisement for a facet of my lab’s recent work (okay, it sort of is an advert). But I have a broader goal with this post. Here we had one survey, one dataset, that has yielded five papers (and more in queue). That’s some serious data recycling. So is it ethical? Absolutely yes, indeed I’d say it is morally preferable. 

 

Here’s why. First, each of the papers cited above asks an entirely different question of the data. The biggest overlap is between Peng et al 2021, and Stutz et al 2017, but those used two different datasets, and different analytical approaches, to ask the same question. Stutz et al used parapatric populations to take advantage of gene flow, Peng et al used allopatric populations but far more of them, with the added bonus of ddRADseq genomic data.  And the MHC data analyses don’t really make sense until you have grappled with covariation between parasite species, and described their diversity, so we had to tackle that Ecology and Ecography paper first. So, the papers support each other, but they certainly aren’t redundant conceptually.

 

Second, we could have put all this into one paper but it would have been a 150 page behemoth. You don’t want to read that, and I don’t want to write it. In fact, I did write it. At least, the Ecography and Ecology and Ecology Letters papers were all mashed into one >100 page manuscript at one point, and the MHC data would have added another >50. And it was so hard to keep clear threads of which analyses when with which results. Breaking it up made it easier to read and understand.

 

Third, funding agencies put significant funding into this dataset, which required salary for four technicians and two postdocs to pull together. Aren’t we morally obligated to wring every bit of insight out of that hard-won data?

 

A call to funds

This last question leads me to a suggestion. Many of us accumulate datasets as our careers progress. Often these data sets have a rich multi-layered nature, but we publish the most exciting bit of information then move on. This is partly because we prioritize publishing the highest-impact work we can, and for career advancement are better off setting aside less exciting findings, to spend time on the splashiest stuff. But there is also a financial angle. Data analyses, and re-analyses, and writing, take time. Which takes money. Most Associate Professors and Professors have sedimentary layers of unpublished or incompletely published analyses. These took funds to generate. It is a shame to have their results only partly published, with important elements gathering dust. The reason is, when I apply for my next grant the review panel will want to see evidence of a new plan of action. What data will I collect next, what experiment will I conduct, what survey or model will I design? Revisiting older data to wring out more precious drops of insight? Not fundable. Well, it should be. Those data contain more insights. They are hard-won, costly to obtain, and carry more than one paper’s worth of knowledge and lessons. So I think it would be great if NSF or other funding agencies would support fellowships, whether for grad students, postdocs, or faculty, to revisit and repurpose existing data to achieve new ends. The data are there, we just need the time to delve deeper.

So to conclude, I think we need to encourage people to use their hard-won data more efficiently and thoroughly. That requires funds, and the social support for the practice. It also has the interesting side-effect that we end up with interconnected papers strewn across many different journals, that build a much larger holistic story when viewed together. I'm intrigued by the notion of bundling published papers to create a story arc that transcends a single paper in one journal. Consider the above description of a set of papers to be such a bundled set.

Susan Foster - Memories

Susan Foster of Clark University passed away recently. Here we collate and compile memories of some Susan's contributions to science, education, and collegiality. She will be sorely missed. This is a living document - please add your own thoughts in the comments.

1. In Remembrance of Susan Adlai Foster (1953 – 2021), ABS Fellow and Past President. Written by Matthew A. Wund, with input from John Baker, Christine Boake, Zuleyma Martinez, and Dale Stevens. This obituary is modified from text that will be published in the March newsletter of the Animal Behavior Society.

Dr. Susan Foster passed away at her home in Petersham, MA from complications associated with cancer on January 16, 2021. She was in the company of her loving husband, John Baker, and their two children, Patrick and Dylan. Susan devoted her career to the study of behavioral plasticity and evolution, and is best known for her extensive work using threespine stickleback fish as a model to understand these processes.

Susan earned her B.S. in Botany and Zoology from the University of Wisconsin, Madison, and in 1984, earned her Ph.D. in Zoology from the University of Washington under the mentorship of Robert T. Paine. Her graduate work investigated group foraging behavior in coral reef fish of Panama. She is most well-known for her extensive research on the plasticity and evolution of behavior in threespine stickleback fish. She began her stickleback research as a postdoctoral fellow working with Michael A. Bell at Stony Brook University. From 1990-1995, she continued this work as an Assistant Professor of Biology at the University of Arkansas. In 1995, she moved with her husband and collaborator, Dr. John Baker, to Clark University in Worcester, MA, where she spent the remainder of her career until her retirement in 2020. She continued mentoring her students and conducting research until her final days. Susan served Clark University with as much dedication and enthusiasm as she served the ABS, including in her position as the Warren Litsky Endowed Chair in Biology, and in her leadership on a variety of institution-wide committees and councils. She was also instrumental in establishing Clark University’s very successful Environmental Science Program, in which she served in several capacities.

Susan served the scientific community in many capacities throughout her career. She was exceptionally fond of the Animal Behavior Society, which spanned her nearly four decades of membership. The highlights of her service to the ABS include multiple terms as Secretary (1993-1999), Second President Elect (08-09), First President Elect (09-10), President (10-11), and Past-President (11-12). Susan was elected an ABS Fellow in 2004. More recently, she served as Executive Editor of Animal Behaviour, and served for more than a decade as the North American Editor of Ethology. Susan also served on numerous NSF review panels, and participated in several working groups sponsored by the National Evolutionary Synthesis Center (NEScent).

Susan’s body of work is exceptional for its breadth and depth. In more than sixty peer reviewed articles and book chapters, as well as four edited volumes, her research beautifully married natural history, extensive field observations, exquisite laboratory experiments, and evolutionary theory. She did not view herself as either a field biologist, or as an animal behaviorist, or as an evolutionary biologist, but rather as all of these things simultaneously. She had a wonderful ability to comprehend the interplay among multiple scales of biological organization: appreciating how the nuances of individual behavior related to complex evolutionary processes. She was fascinated by threespine stickleback fish as an individual species, while simultaneously leveraging their value as a model system for studying general processes of behavioral evolution and adaptive diversification.

In addition to her brilliant mind, Susan was a loving wife and mother, an exceptional cook, an avid gardener, and had a wonderful, dry sense of humor. She also had a lifelong interest in the conservation of natural landscapes, and while at Clark University taught a course on the topic nearly every year. She was an unwavering advocate for the many students and postdocs she mentored throughout her career, many of whom came to know her as not only a mentor and friend, but as a member of their family. Susan was perhaps most in her element in her 250-year-old farmhouse in Petersham, MA, where, with her husband John, she would effortlessly move between writing research papers and grants, reviewing manuscripts for Animal Behaviour and Ethology, gardening, cooking, and entertaining guests. While home was her happiest place, Susan also enjoyed traveling, spending many field seasons studying stickleback fish behavior in Alaska and British Columbia, and traveling to conferences around the world. Her life was enriched by the many friendships she formed in her travels and through her research; indeed, news of her passing has resulted in an outpouring of love and respect from friends across the globe.

To commemorate Susan’s life and legacy, and the impact she had on her friends and colleagues, her dear friend and fellow ABS Fellow Dr. Christine Boake shared these sentiments:

“Susan and I first met due to our mutual interests in behavioral divergence between animal populations, which we recognized could lead to speciation. Her generous hospitality made it easy for us to become close friends. Our visits always combined our shared interests in science, cooking, and gardening. She had boundless energy; even after surgery imposed physical limitations, she kept up a strenuous pace both in research and at home. Her energy and enthusiasm allowed her to have her noteworthy professional success as well as having a multifaceted and rewarding life with family and friends. She had a full life.”

Susan’s professional and personal legacy includes the dozens of postdocs, graduate students, and undergraduate student researchers she mentored, as well as the hundreds of undergraduates she taught in her Evolution and Animal Behavior courses. The students and postdocs whose lives she touched were helped to be better scientists, but more importantly were inspired to be better people. She will be dearly missed by the many students and colleagues who will remember her as not only an exceptional scientist, but more importantly as a true friend.

2. From David Hibbett, Chair of the Biology Department at Clark University.

Professor Susan Adlai Foster and Research Professor John Allen Baker, Biology Department

Memorial Minute

October 27, 2021

Susan Foster passed away in January, 2021, followed less than five months later by her husband and collaborator, John Baker. Both were larger-than-life figures on the campus of Clark University, outgoing, engaging, and wildly popular with students. Their professional achievements were significant. Susan was an evolutionary biologist and ethologist. Her pioneering research using the threespine stickleback helped establish this diminutive fish as a premier model system for vertebrate biology. Among other accomplishments, Susan was President of the Animal Behavior Society, Landry University Professor of Clark University, and a National Science Foundation Presidential Faculty Fellow. She served as Chair of the Biology Department from 2006 to 2016.

John worked closely with Susan on stickleback research, including numerous field trips to Alaska with their students and postdoctoral fellows, but he had his own interests in ichthyology, conservation, and biodiversity of streams and rivers. For example, one of his last publications was on population genetics of the freshwater pearl mussel in New England. John was one of Clark’s most beloved teachers. His most popular classes included BIOL 101 - Introductory Biology and BIOL 084 – Biodiversity. Both routinely enrolled far above their caps. The last time John taught BIOL 101, in Fall 2019, there were 202 students. In 2013 John received the Teacher of the Year Award.

Susan and John came to Clark from the University of Arkansas in 1995. Over the next 25 years, they helped to revitalize the graduate and undergraduate programs in Biology, and they were central to the establishment and growth of the Environmental Science Program. But Susan and John did far more than teach classes and run programs; they created a community. The Foster-Baker universe had two centers, one in their laboratory in the Lasry Bioscience building and the other in their 250-year-old farmhouse in Petersham, where Susan died. Both were gathering places for students, family, friends, and colleagues, although the boundaries between those groups were often vague. Susan and John created possibilities, for learning, discovery, and second chances. They represented the best of Clark’s ideals, inspired fierce loyalty, and will be sorely missed

3. From Bill Cresko to his lab members

Susan Foster passed away yesterday due a rapidly progressing cancer that was only diagnosed early in 2020. She was able to be at home in Petersham MA with her husband and lifetime research partner John Baker, as well as her children Dylan and Patrick. Susan loved her colonial-era home and garden with the snow and the fireplace and the after seminar parties and the pickling of vegetables. Susan was my and Cristin’s Ph.D. advisor. She has been a professor of biology and the chair of the Biology Department at Clark University for much of the past decade, and retired in early 2020 at the first diagnosis. Susan advised numerous postdoctoral scholars, graduate students, and undergraduates over the years.

Susan was a pioneer. After her Ph.D. on Wrasse behavior at the University of Washington with Bob Paine, she did her postdoctoral work with Mike Bell at SUNY Stony Brook. In fact, I came to work with Susan after contacting Bob and telling him about my interests and he said ‘you should work with Susan instead on this amazing system’. At Stony Brook Susan helped develop the stickleback systems in British Columbia and Alaska, and through many publications helped biologists appreciate that behavior - like morphological and life history traits - could exhibit significant geographic variation that was influenced by both environmental and genetic variation. In addition to her many journal articles, Susan published two books with Mike Bell and John Endler that are now classics in the field.

Susan was a leader and role model in the fields of ethology and behavior. She help several leadership positions in the Animal Behavior Society, and she was part of an early wave of women in biology fighting for gender equity in the life sciences. Susan was a fierce advocate throughout her career for achieving the goal of having people judged by their abilities, not their chromosomal composition, skin color, or socioeconomic background. She matched these professional efforts at equity and inclusion in her private life in ways that were truly inspiring. The impacts that Susan has had on the field through her students from these diverse backgrounds (including me) is deep and broad.

In December of 2020 David Hibbett and others from Clark University and I began making plans for a virtual conference to honor the work of Susan and John. Unfortunately Susan’s cancer returned quickly at the beginning of the new year. We will continue our work to highlight Susan’s and John’s life work and educational legacy. All of you who are or have been in my lab working on stickleback have Susan to thank, and I hope that you will be able to attend.

Sincerely, Bill

4. From Jun Kitano - email to Andrew Hendry

This sad news reminds me of my old days in Kyoto, when I came to know a series of Susan Foster’s excellent works on behavioral variation in natural populations of the threespine stickleback. When I almost finished my PhD thesis on molecular neuroscience in mice, I was wondering what to do next as a postdoc. I read several papers and books and finally found that I want to study wild animals rather than laboratory mouse. One day, I came across a paper by Katie Peichel, David Kingsley and their colleagues (Peichel et al. 2001 Nature). In that paper, they investigated the genetic architecture underlying morphological variation in the threespine stickleback. I thought that I could apply the same genetic method to behavioral variation. 

Then, I started to read many papers on the behavioral variation in sticklebacks, including those by Dr. Susan Foster. She has conducted extensive field observations and characterized behavioral variation in natural populations of the threespine stickleback. A series of her papers were so exciting that I perhaps spent more time reading her papers than reading papers directly related to my thesis. Reading her papers, I was convinced that behavioral genetics in sticklebacks would be an exciting direction of research. As I decided to work on Japanese populations in collaboration with Dr. Seiichi Mori (my long-term collaborator), I had no chance to work with Susan. But, Susan is definitely one of the persons who guided me into the stickleback research.

I met Susan at a stickleback conference in Alaska, and she kindly encouraged me. She invited me to her research fields in Alaska, although it did not happen due to several reasons. It is sad that we can no longer meet her, but her works will continue to encourage not only me but also many present and future young researchers. This would be a good timing to appreciate that our recent cutting edge genomic studies are based on the extensive works done by old researchers who spent a lot of time observing nature like Susan.

R.I.P.

5. From Jeff McKinnon - email to Andrew Hendry

I ran into Susan at various times over the years. My fondest memory was visiting her and John at their beautiful old house in Mass, probably in the early 2000’s. I remember their generous hospitality and lively conversations about stickleback biology, as well as about hockey. Susan was a great fan of Steve Yzerman, if memory serves.

6. From Tom Reimchen - email to Andrew Hendry

Gone before her time. As well as her obvious contributions to behavioural evolution in stickleback,  another substantial contribution of Susan was her novel observations on coral reef fishes , particularly the importance of  cleaning stations for the repair of wounds in coral reef fish  (Foster 1985,  Copeia 875-880). I have used this in my Ichthyology courses for many years as an example of co-evolution at a community level and as one of the first examples of self-medication in fishes.

7. #SusanFosterMemories