Rejection and how to deal with it.

Rejection is a part of life – a big part. In science, it is a huge part.

For many scientists, publications are really the only criterion on which we – and our careers and contributions – are judged. We offer up our papers to journals and ask for them to be published. Often, the reviewers and editors say no. Such rejection can be a soul-crushing experience for new scientists, feeding the “imposter syndrome” and sometimes chasing them from science altogether. On this background, the current post will make several points. First, even established scientists are frequently rejected, and so a rejection should not be considered an indictment of your paper or your research ability or your future in science. Second, rejection sometimes leads to a better paper published in a better journal. Third, strategies exist to reduce the sting of rejection – hopefully to the point where it becomes only a minor annoyance.

In 2004, Cassey and Blackburn published a paper in BioScience titled “Publication and rejection among successful ecologists.” They surveyed 155 authors who had published at least 10 papers in core ecology journals (their criterion for “successful”), of whom 61 respond to a questionnaire. Of the 2907 papers published by those authors, 450 (15.5%) had been rejected at least once by a different journal and 224 (7.7%) had been rejected at least twice. In short, even the most successful ecologists have to deal with at least some rejection. And what of today, when rejection is – seemingly – so much higher, at least at journals that are not open access. Since no more recent study has repeated the survey of Cassey and Blackburn, I will have delve into my own experience (which might or might not be representative).

From Cassey and Blackburn (2004 - Bioscience).

I have submitted a total of 308 papers to peer-reviewed journals. This tally includes multiple submission of the same paper to different journals but not re-submissions to the same journal following “reject with the possibility of resubmission” or “reject without prejudice”. Of  those 308 total submissions, 144 (47%) were ultimately rejected from the journal without the possibility of further resubmission. If you count only the first submission of a given paper (to any journal), 71 out of 165 (43%) were rejected without the possibility of resubmission – a higher number than the above 15.5% experienced by “successful ecologists” in the 1990s. Perhaps my rejection rate is higher because the 2000s have seen higher overall rejection rates than did the 1990s (indeed, my first 6 papers in the 1990s were all accepted at the journal to which they were first submitted), perhaps I am submitting to journals with higher rejection rates (more about Nature/Science later), perhaps my work is less good than that of “successful ecologists”, perhaps rejection rates are higher for evolutionary biologists than ecologists, perhaps …

However, considering all 308 submissions might be misleading because some were notes/comments/responses, some were invited by editors, and some were submitted to special issues where I was an editor. Rejection was presumably less likely in such cases, so let’s remove them and recalculate. This removal leaves 251 total submissions of which 143 (57%) were rejected and of which 70 (60%) were rejected on their first submission. No matter what happens next, it is clear that a lot of my papers are rejected!

But wait, my coauthors and I often submit to general journals with very high rejection rates, such as Nature (~92%), Science (~93%), PNAS (~82%), Current Biology, and PLosBiol. Indeed, I have made 55 total submissions to the big five. All 6 reviews/comments/responses/News&Views/Dispatches/etc. were accepted, whereas only 1 of the 48 “real” submissions was accepted. It was my first such submission, subsequently followed by 47 straight rejections – and counting. Of course, I didn’t actually submit 48 separate papers to these journals, instead it was more like 15 or so papers submitted to multiple journals within the big five.

Rejection rates are generally higher at "high impact" journals. (From Aarsen et al. 2008. Open Ecology Journal.)

We might call these general journals the “big five” and assume they shouldn’t really count to the “normal” rejection rate for journals in my discipline. Removing them from the above already-winnowed list leaves 203 total submissions with 96 rejections (47%), 54% on their first submission. In short, I still have lots of rejections even within disciplinary journals in my field.

But, actually, the journal with the highest rejection rate (100%) also has the lowest impact factor (undefined).

Some other interesting tidbits come out of my rejection list. One paper was rejected from 8 journals (none of them in the big 5) before finally being published. It has since been cited a respectable 27 times. A number of others were rejected from 4 journals before we simply gave up or, more accurately, moved on –  and published them in PLoS ONE or Ecology and Evolution or the like. Interestingly, several papers were rejected from low-impact journals only to be later published in high-impact journals, including Ecology Letters.

Although the publishing journal is usually "lower impact" than the first submission, you can sometimes move up the scale. From Colcagno et al. (2012 - Science).

OK, so lots and lots and lots of rejection no matter how you slice it. What should we take from this outcome: that my research sucks or is at least – more charitably – not very important? I suggest not, for two reasons. First, my work (including several repeatedly rejected papers) is actually cited quite frequently and seems to have had some influence on the field. Second, having served as an editor for a number of journals over a number of years, it is clear that the primary reason for rejection is simply “fit.” For instance, the paper isn’t thought to be of general enough interest to the readership of a journal, or the editor doesn’t think it can “compete with other papers for limited space in the journal.” Papers are almost never rejected simply because they are scientifically “bad” somehow, which is reflected in the much lower rejection rate of “pay-to-publish” open access journals like PLoS ONE (~30%) or Ecology and Evolution.

Some of my frequently rejected highly cited papers.

So, rejection is just a part of life – like stop signs and traffic lights –  that we just need to “get over” and get on with life. Easy enough to say but the reality is that rejection can hurt, especially for a young scientist. So can one find a way to deal with rejection so it becomes a mosquito buzzing in the background rather than a wasp stinging us?

My own way of dealing with rejection is to be pre-emptive: I merely assume even BEFORE submission that the paper will be rejected wherever I am submitting it to. Thus, I make a short list of the sequence of journals to which I will submit the paper. That way, when the paper comes back with a rejection, I am just on the cusp of submitting to the next journal I had targeted. Of course, if the paper isn’t rejected, then all is well and I don’t have move down my list. In addition, I don’t read the reviews of a paper (rejected or otherwise) until I am actually sitting down ready to make revisions. Otherwise, I can stew over the “idiot reviewers” and capriciousness of the editors for weeks (see Butch Brodie's examples here) before I can get around to doing something about it. Of course, this is only the approach that works for me and I am sure that other approaches will work better for others.

Everybody's doing it - re-submission patterns among journals. From Calcagno et al. (2012 - Science).

Summary and closing thoughts

Rejection is something that all scientists have to deal in the currently scientific enterprise.

Rejection is not an indictment of the quality of your research or yourself as a scientist. By far the most frequently cause of rejection is simply that the paper isn’t considered a good fit for the journal but that it is publishable elsewhere in a “more specialized” journal. Indeed, the low rejection rates at “pay-to-publish” open access journals prove this point.

Frequent rejection means that you are not under-selling your work. Journals with the highest rejection rate are often the highest profile (highest impact – for better or worse)  journals.

Rejection rates tend to higher for scientists who publish more papers, which can be viewed as bad (minimum publishable units) or good (no publication bias).

Rejection doesn’t mean your paper is bad and that it won’t be cited. Indeed, many papers rejected from one journal go on to be highly cited at some other journal.

Rejection can be used to improve a paper, especially if you revise according to (useful) reviewer suggestions. This is generally a good idea anyway as it might well go to the same reviewer at the next journal. Indeed, this is common. And, once a paper is revised according to good suggestions, it can often be traded-up to an even better journal. I know of several people rejected from disciplinary journals who entirely revamped their paper and had it published at Nature/Science.

Importantly, rejections such as "reject with the possibility of resubmission" or "reject without prejudice" or "reject in present form" ARE NOT REJECTIONS. They are simply a way for the journal to reset the clock on you paper making it seems as though they have a shorter time from submission to publication. In fact, I would say that 90% of the papers that I have had with the above decisions on an initial submission were ultimately published in that journal. Thus, these apparent rejections should be considered "reconsider after revision" and a very careful revision should be made - here is my advice on responding to reviewers.

Rejection isn’t fun – but neither need it be paralyzing or depressing. It is simply a part of life and, like all such parts, can be made less painful and (sometimes) useful. Good luck.

Or you could just submit to my new journal. 

Florida panthers, Trinidadian guppies, and genetic rescue

[ This post is by Sarah Fitzpatrick; I am just putting it up. –B. ]

In Trinidad, nicknames for guppies include "millions fish" and "drain fish" due to their plentiful abundance and unique ability to tolerate an incredible range of environmental conditions. Guppies are found everywhere from the most pristine streams in the Northern Range mountains to ditches along the side of the highway and even in highly oil-polluted environments. In other words, this species can hardly be considered one of conservation concern. But, thanks to quick generation times and decades of research on the predictable variation in traits and fitness of populations found in different environments, Trinidadian guppies have become a textbook example for studying evolution in the wild.

Our new Evolutionary Applications paper documenting genetic rescue in guppies suggests that this species could also become a model system for informing effective management of imperiled populations.

Genetic rescue is an increase in population size caused by the introduction of new alleles, by more than the numerical addition of immigrant individuals. The iconic example of successful genetic rescue is the Florida panther that nearly went extinct in the early 1990s. The few panthers that remained at this time all showed severe signs of inbreeding depression caused by mating between close relatives. Left with few options, wildlife managers introduced eight female panthers from Texas into Florida and the population has since rebounded dramatically due in large part to the recovery from inbreeding depression and high hybrid fitness.

Concerns over maladaptive effects of gene flow and outbreeding depression (reduction in fitness when divergent populations or species are crossed) have restricted the use of genetic rescue as a management tool to just a handful of extreme cases, like the Florida panther. Yet, genetic problems associated with isolation and small populations, like inbreeding depression and lack of variation to adapt to a changing environment, are major threats to fragmented species.

Making use of the wealth of background knowledge on guppies we set out to two headwater streams in Trinidad to test whether gene flow from a genetically and phenotypically divergent source population would cause genetic rescue or outbreeding depression.

We measured genetic variation and monitored population size and survival in two native focal populations of guppies for several months before non-native guppies that were adapted to a different environment were introduced upstream from our focal populations (as part of a separate experiment). Having been long-isolated in small headwater streams and likely originally colonized by only one or several individuals, the native populations started out with tiny effective population sizes (N_e = 2–10) and were likely experiencing inbreeding.

Field assistant Bret Robinson fishing for guppies in the Caigual River

Gene flow began as non-native guppies swam or were washed downstream and began mating with the native guppies. Our field team visited the two focal populations each month for two and a half years and caught all guppies over 14 mm (about the width of your thumbnail) using traps, mask and snorkel, and butterfly nets. All fish each month were weighed and photographed and all new recruits to the population were given a unique colored tattoo under a microscope and had three scales removed for genetic analyses before being returned to their exact site of capture. In total, over 10,000 guppies from the two streams were individually marked, monitored throughout their lifetimes, and could be classified using molecular markers as a pure native guppy, a pure immigrant, or a hybrid. This study was novel in its ability to capture the initial and long-term effects of gene flow on survival and population dynamics in replicated populations in the wild.

Thick black lines indicate total number of guppies > 14mm captured in each stream over time. Grey boxes correspond to the timeframe in which every individual was genotyped at microsatellite loci for classification into genetic ancestry groups. Colors show the number of individuals in each genetic group caught each month.

Despite gene flow from guppy populations that were originally divergent and adapted to a different environment, genetic rescue was documented in both streams. Monthly population sizes skyrocketed from under one hundred to over one thousand individuals, genetic diversity increased substantially, and importantly, much of the success could be attributed to hybrid guppies.

Though guppies themselves are not endangered, the small, native guppy populations in this study could be thought of as proxies for other genetically isolated, imperiled populations. Model systems in evolution might become increasingly crucial for conservation if understanding and manipulating evolutionary processes indeed proves to be one way to curb unprecedented rates of biodiversity loss.

Reference

Fitzpatrick, S. W., Gerberich, J. C., Angeloni, L. M., Bailey, L. L., Broder, E. D., Torres-Dowdall, J., Handelsman, C. A., López-Sepulcre, A., Reznick, D. N., Ghalambor, C. K. and Funk, W. C. (2016). Gene flow from an adaptively divergent source causes rescue through genetic and demographic factors in two wild populations of Trinidadian guppies. Evolutionary Applications. doi: 10.1111/eva.12356

Believe the peaks?

What is the standard modus operandi in adaptation genomics? We pick populations occurring in habitats expected to be selectively different, perform marker-based genome scans, and develop narratives based on differentiation profiles (slightly simplified). And we are generally willing to believe these interpretations without evidence that genomic differentiation is ecologically consequential, or at least without a direct estimation of these consequences… wouldn’t it be interesting to know more about the fitness correlates of the patterns our genome scans reveal?

Performing experiments in the wild using lake and stream stickleback populations from the Lake Constance watershed in Central Europe led my student Dario and me to such an investigation connecting genomic differentiation to fitness differences. It all began with an experiment on phenotypic plasticity, in which we transplanted juvenile lab-bred lake and stream stickleback into enclosures built in multiple streams (Moser et al. 2015 Evol. Biol.). We observed that lake stickleback now expressed life history characters typical of the resident stream fish; so body size divergence, the perhaps most striking phenotypic difference between lake and stream stickleback from that region, turned out to be plastic. Moreover, our recent high-density SNP-based genome scans indicated very weak genomic baseline differentiation between lake and stream stickleback in the Lake Constance region (Roesti et al. 2015 Nat. Commun.). Hmm… are these lake and stream stickleback populations really locally adapted?

Well, at the end of the plasticity experiment, it seemed to us that many lake fish were missing from the enclosures, whereas the local stream (control) fish still seemed to be around. But the study design of the plasticity experiment precluded more than speculating about differential survival between the populations, so we decided to test this formally in a new experiment. Fortunately, we could reuse the enclosures (which were hard to build; Fig. 1). However, we wanted to perform the new experiment using lab-reared individuals to test for genetically-based fitness differences, hence breeding a fresh experimental stickleback cohort in the lab still took a year of work. Once the new lab cohort was generated, we released an equal number of juvenile lake fish (i.e., foreigners), stream fish (locals), and their F1 hybrids into the stream enclosures, allowing them to compete, and tracked survival over more than half a year.

  Fig. 1: Dario during enclosure construction (in his irresistible wet suit from the 80s), the resulting product, and maintenance work.

The outcome of the experiment was as clear as in a textbook on local adaptation: in all three replicate streams, the local stream fish survived better than the foreign lake fish, and survival of the F1 hybrids was intermediate. Intriguingly, this even held in the one replicate in which the stream population was known from our genomic work to exhibit negligible overall genomic differentiation (Fst = 0.005) from the lake population because of strong gene flow (Fig. 2). However, genomic differentiation is heterogeneous, hence it appears that moderate allele frequency shifts (Fst up to 0.67) maintained at a number of spots in the genome are sufficient to cause strong adaptive divergence.

 

Fig. 2: Survival of stream (light gray), lake (black), and F1 lake-stream hybrid stickleback (dark gray) over 29 weeks, averaged across the replicate field enclosures at one experimental stream site (left). The resident population in this stream displays trivial overall genomic differentiation from the adjacent lake population, although the distribution of Fst values across >55k genome-wide SNP markers indicates more substantial divergence in many regions of the genome (the tail of the Fst distribution is enlarged in the insert).

The main lesson to us was that in the presence of heterogeneous genomic differentiation between populations, weak overall baseline differentiation does not imply weak adaptive divergence – many small peaks, reflecting highly incomplete allele frequency shifts, really make a difference. Of course this is what we are generally assuming in genomics, but it is reassuring to have this quantified and confirmed. Moreover, we now know for sure that adaptive divergence, by causing selection against migrants and hybrids, is a potent reproductive barrier in lake and stream stickleback. I expect this barrier to be devastatingly strong in those lake-stream systems in which phenotypic and genomic divergence is way more striking than among the populations from the Lake Constance watershed (e.g., some lake-stream pairs from Vancouver Island, Canada). If interested in this transplant study, see Moser et al. 2016, JEB: Fitness differences between parapatric lake and stream stickleback revealed by a field transplant. http://onlinelibrary.wiley.com/doi/10.1111/jeb.12817/abstract