Thursday, December 11, 2014

Retracing the legacy of guppy introductions past: local differentiation maintained despite high and rapid gene flow

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

When populations adapted to different environments come into contact through range expansions, invasions, or by human-assisted migration, the outcome is often unknown. How will immigrant individuals fare in the new environment and will they hybridize with native populations? If so, what impact does gene flow with non-native individuals have on the local populations? The question of whether gene flow between adaptively divergent populations promotes or constrains local adaptation is a long-standing puzzle in evolutionary biology and is increasingly relevant for designing effective conservation strategies.

In our recent study (Fitzpatrick et al., 2015) published in Ecology Letters, we turned to Trinidadian guppies, a model system for studying evolution in the wild, to ask questions about how gene flow affects fitness and local adaptation. The guppy system has proved powerful for understanding a diverse set of questions in ecology and evolution, but these rapidly evolving freshwater fish are perhaps most famous for the series of transplant experiments conducted in the streams of Trinidad. Caryl Haskins initiated the first introduction experiment in 1957, moving guppies from an environment where they experienced high mortality from predation to a site in a separate drainage where waterfall barriers limited the upstream colonization of most fish, including predators and native guppies. The introduction site thus represents a release from predation. John Endler and David Reznick and his colleagues have since repeated this transplant scenario in multiple independent drainages, and their studies of rapid adaptation and eco-evo feedbacks focusing on the introduced populations are iconic in evolutionary ecology.

In each of these introduction streams, native guppies existed downstream from introduction sites, and although the introduced populations were initially maladapted to their new environment, gene flow is expected because adaptive divergence has not led to reproductive isolation in guppies (Crispo et al., 2006). In fact, we expected much higher levels of downstream gene flow from introduction sites than what is observed in natural streams due to the fast life history of the introduced fish and female preference for novel males (Fig. 1; click to see at larger size).

Figure 1. Conceptual diagram illustrating the expected differences in amount of gene flow between natural streams and streams with introduced populations. In both hypothetical streams, predation level is colour-coded based on the species listed in the bottom key, and increases in the downstream direction. Black rectangles indicate waterfall barriers that limit upstream fish dispersal. The colour of fish indicates traits matched to a certain level of predation (e.g., the blue fish has traits that are adaptive in a low-predation environment). In the hypothetical natural stream, fish are perfectly matched to their level of predation and gene flow among populations is low, based on biological factors listed in the grey box. In the hypothetical introduction stream, guppies from high-predation (HP) environments were translocated upstream of naturally occurring low-predation (LP) populations. Gene flow is expected to increase relative to natural levels for the reasons listed in the grey box, and the effect of elevated gene flow on locally adapted traits remains unknown (indicated by grey fish and question marks).

Our team, from Colorado State University, asked what the effects of elevated levels of gene flow from an initially phenotypically divergent population would be on locally adapted phenotypes in downstream populations. Following the footsteps of Haskins, Endler, and Reznick, we sampled guppies from six historic introduction sites, from each of their source populations, and from multiple sites downstream from each introduction. We genotyped all individuals at ten microsatellite loci and quantified a suite of known fitness-related traits, such as male color, body shape, and some female life-history traits that tend to differ based on the level of predation experienced. We also included individuals from two native populations prior to the onset of gene flow, providing a powerful opportunity to compare pre- versus post-gene flow phenotypes and allele frequencies. At each site we classified the predator community as either low, medium, or high based on the complexity of the fish community observed.

Clockwise from back left: Jed Smith (undergrad researcher, CSU); Chris Funk (asst. prof, CSU); Sarah Fitzpatrick (PhD student, CSU); Lisa Angeloni (asst. prof, CSU).

We found that the genetic signature of introduced guppies swept throughout all downstream distances, indicating high levels of gene flow downstream from all introduction sites on a rapid timescale (Fig. 3a; click to see at larger size). However, despite genetic uniformity caused by introductions, guppies sampled from different predation communities along the streams maintained phenotypic traits that best allowed them to survive and reproduce, given the local predator community. In other words, genetic homogenization did not cause the loss of locally adapted phenotypes.

Figure 3. (a) Comparison of genetic differentiation (pairwise-FST) among all sites in natural streams vs. among all sites in streams after introductions took place. (b) Within-stream STRUCTURE plots and average pairwise-FST values for all six streams that experienced an upstream introduction. Each line in the plots corresponds to an individual with colours representing the proportion of an individual’s genotype assigned to a given genetic cluster. Old introductions show fine-scale genetic structure despite low genetic divergence (low FST). All sites from the three recent introductions conducted in the Guanapo drainage were included in the same analysis because they share the 5000 m and source sites. These recent introductions are more genetically homogeneous, with the exception of pre-introduction 0 m sites in Taylor and Caigual (shaded in blue) that are very distinct and genetically divergent (high FST) from the rest of the sites. Colored circles on the x axes indicate the predation level at each site: blue = low, green = mid, red = high, as defined in Fig. 1. All plots represent the (k) number of genetic clusters with the highest support (see Appendix S1).

We used the exchangeability analysis described in Hendry et al. 2013 to compare neutral genetic and phenotypic exchangeability among the common source site and two native low-predation sites that were sampled before and approximately 12 generations after gene flow. A major take-home message from our study can be gained from the results of this analysis. Namely, we found phenotypic divergence associated with the local predation regime despite neutral genetic homogeneity with the source of the introductions (Fig. 5; click to see at larger size).

Figure 5. Ordination plots and group classification based on discriminant analysis of principal components (DAPC) for neutral genetic loci (a) and phenotypic traits (b). Colours correspond to a priori groups based on population origin: native low-predation in purple, the same sites post-introduction in blue, and introduction source in red. Bar graphs below the dashed line show the mean (and 95% CIs) proportion of individuals from each population classified into each population. Each bar represents the classification of the population on the x axis, as labelled for one set of bars in (b). The bottom-left insets show eigenvalues of the four principal components in relative magnitude.

Phenotypes were measured from wild fish, so we are unable to separate the relative roles that phenotypic plasticity and adaptive evolution play in causing the observed phenotypic divergence, but we argue that both processes are likely involved. Ongoing work that includes common garden assays conducted before and several generations after the onset of gene flow, and wild pedigree reconstruction throughout the initial pulse and longer-term wave of gene flow, will add to our understanding of the mechanisms by which gene flow impacts adaptive evolution and population growth.

Although we expected to find high gene flow from the introduced populations, we were surprised by the near-extinction of native alleles, especially downstream from the set of recent introductions. However, differential rates of introgression across the genome may result in homogenizing effects of gene flow at neutral loci, while locally adapted native loci or genomic regions are maintained by selection.

Whether the loss of native genetic signatures at neutral loci represents a true detriment is an intriguing philosophical debate. The costs of gene flow between populations of the same species may be outweighed by the benefits in cases where selection for a local ecotype is strong, or where recipient populations are inbred. This study reveals how model systems that can be manipulated in the wild have the potential to inform smart management decisions for threatened populations.

Indeed, we have pioneers of model systems like Haskins, Endler, and Reznick to thank for building foundations that continue to generate creative questions and provide a deeper understanding of nature.


Crispo, E., Bentzen, P., Reznick, D.N., Kinnison, M.T., and Hendry, A.P. (2006). The relative influence of natural selection and geography on gene flow in guppies. Mol. Ecol. 15, 49–62.

Fitzpatrick, S.W., Gerberich, J.C., Kronenberger, J.A., Angeloni, L.M., and Funk, W.C. (2015). Locally adapted traits maintained in the face of high gene flow. Ecol. Lett.

Hendry, A.P., Kaeuffer, R., Crispo, E., Peichel, C.L., and Bolnick, D.I. (2013). Evolutionary inferences from the analysis of exchangeability. Evolution 67, 3429–3441.

Figures are cited based on the numbering in the manuscript.

Wednesday, December 3, 2014

Where to submit your paper – response to reviews.

My blog posted in open access Where to submit your paper. Or “If at first you don’t succeed, fail fail again … then try open access” has been viewed 2771 times in 5 days and has now been subject to some post-publication reviews. It seems appropriate to do a quick follow up in which I respond to those comments.

The original post made several points:
  1. If you have some great work, submitting to high-impact journals like Science/Nature is fine – even though the chances of acceptance are low. The whole process usually makes for a better paper.
  2. Traditional society-based journals are great outlets: they are well respected in the community and are frequently scanned for papers by many scientists. If you publish there, folks know you have received a rigorous and critical evaluation of your science from the perspective of its rigor AND importance.
  3. Rejection is an ever-constant companion for ALL scientists trying the above routes and it is good idea to find a coping mechanism that works for you.
  4. Open access journals are not good options (except as a last restort) because they don’t have the above properties.
Of the numerous comments on twitter and in personal emails, only item 4 seems to have - perhaps predictably - raised hackles, specifically in relation to citation rates. So let’s look at some of those comments and see what new insights they can bring.  
This statement is totally correct. Most of us think of PLoS ONE as the archetypal open access journal, which is why I didn't think to initially draw the distinction with "better" open access journals. I therefore added the follow comment after the post.

To make sure my opinion is clear, I am FOR open access PAPERS (in whatever journal) and even for open access journals as long as they are selective (e.g., PLoS Biology, Evolutionary Applications). What I am not for is for-profit open access journals where you pay your way to publish pretty much whatever you want. Those are merely profit making machines for publishing houses - they only make money when they publish your paper. PLoS ONE is non-profit but the problem there is that it is (rightly) viewed as a dumping ground for papers that people couldn't get published elsewhere. Thus, it is not good for exposure of your paper, for the influence of your paper (citations), or for your career. It should be a last resort when you are in a hurry or you (or your student) are sick of trying other places. Indeed, that is how many people already view it and you should too or people will think that was the case for your paper even if you submitted there first.

By far the best option as far as everyone (except for many publishers) is concerned is to publish in a respected traditional (often society based) journal and pay for the paper to be open access. Everyone wins. 

A number of other comments were along the lines that I had N = 2 for my PLoS ONE papers, which thus doesn't say much beyond my own limited personal experience. This is also entirely true given that the post was from my personal perspective and speaks only to my own experience.
But, wait, it turns out I have more experience than I thought (it seems I even ignore my own PLoS ONE papers). While reviewing another manuscript today, I remembered that I had another PLoS ONE paper - this one published in 2010. Yeeha: N = 3. I figured I better update my stats accordingly. I was a bit worried this time as I quite like the paper and know it has been cited at least a few times, so I was thinking that my new data point would mess up my story. Nope. Same thing - the worst cited of all my papers in that year.
Updated stats (adding 2010) for citations (Web of Science) to my PLoS ONE papers in comparison to citations to all my other papers in those years.
So, at this point, I can say with confidence that PLoS ONE is not working for me. In fact, it seems that I wasted three awesome papers by publishing them in an outlet where no one sees them or wants to cite them. I did receive a lot of comments from other people about their PLoS ONE papers also being very poorly cited (although at least one person said they had not noticed a difference). Then I was pointed (by a PLoS ONE senior editor) to something more quantitative.
The paper referred to here collected data on citations to 30 empirical ecological papers (selected in a "stratified" manner) published in 2009 in PLoS ONE, in some traditional ecology journals (Ecology, Oikos, Functional Ecology), in Ecology Letters, and in the big boys (Nature, Science). The results were that citations to ecology papers in PLoS ONE were roughly equivalent to those in Ecology and Functional Ecology and higher than those in Oikos. However, the citation rates in PLoS ONE were much lower than in Ecology Letters and the big boys.

From Wardle (2012 - Ideas In Ecology and Evolution)
These results run counter to my own experience and seem to suggest that PLoS ONE is a good target journal. The results were so different from my own that I decided to take a quick closer look at the question. For each of the three years in which I published a PLoS ONE paper, I used Web Of Science to search for all papers in PLoS ONE and Ecology (the sort of target journal I suggest shooting for) that had the word "ecology" as a topic (an objective way of comparing ecology papers from the two journals). I then used "citation report" to calculate all citations to those papers and, from that, calculated the mean citation rate (total citations divided by total papers).

Citations to "ecology" papers in PLoS ONE and in Ecology in each of three years.
 Of course, this analysis is still crude: I didn't actually read the papers, I didn't examine other journals, and I didn't examine more years. Nevertheless, these larger sample sizes than in Wardle (2012) seem more in line with my argument that citations are lower in PLoS ONE than in the canonical society-based journal. My papers, which are more evolution than ecology, are cited below these PLoS ONE rates. I wanted to do a similar analysis for PLoS ONE versus my own target journal Evolution but the "topic" "evolution" pops up too many other things in PLoS ONE that are not organismal evolution and I was too lazy to sort through them all. My suspicion (and that is all it is) is that the difference will be more severe in evolution than in ecology, where PLoS ONE is perhaps more accepted as a reasonable outlet. It would be awesome if someone did a proper analysis - but not my students - they need to be working on papers and not blogging.

Of course, none of this stuff is definitive in any way but these post publication reviews of the original blog have lead to revisions that bolster my original findings and thus strengthen my general conclusions. I hope that my blog is now acceptable for publication in your journal, whether open access or otherwise.

More just for fun:

Monday, December 1, 2014

Carnival of Evolution #77: The Carnival is Dead, Long Live the Carnival

Carnival of Evolution #77 is now up at… the Carnival of Evolution blog.

Apparently, Eco-Evo-Evo-Eco had the unanticipated honor of hosting the very last independently hosted CoE, Carnival of Evolution #76, on 2 October 2014.  I guess Felipe P. J. did such an amazing job hosting that nobody wanted to try to follow his act; Bjørn was unable to find a host for November.  So Bjørn will now be hosting the CoE locally, on the CoE blog itself; he has apparently gotten tired of pleading for hosts.  It’s a bit sad, but not really unexpected; blog carnivals used to be more of a thing, but apparently kids nowadays have moved on to Twitter and such.  Case in point: you can follow Andrew at @EcoEvoEvoEco (but he has not yet announced his Snapchat handle).  CoE actually lasted much longer than most blog carnivals did.

But since Bjørn has apparently decided to keep it limping along on his own, it’s not actually dead yet (just pining for the fjords), and we’ll keep participating in it for as long as Bjørn keeps running it.  In #77, we have three posts; I’m not sure how that happened, since I always nominate just one, but there they are.  :->  First off is Andrew writing about how to choose a study system; second is Erik Svensson responding to the kerfuffle about the proposed Extended Evolutionary Synthesis; and third is Yoel Stuart writing about his fascinating work on character displacement in Anolis. I’m glad all three ended up in the Carnival; they’re all great posts!  Check out Carnival of Evolution #77 for lots more cool stuff.

Bjørn is referring to the new, local-hosted carnival as the “Phoenix Edition”, so in honor of his ongoing commitment to the Carnival of Evolution, here is a phoenix.  Thanks Bjørn.

Art credit: Enigma.

Saturday, November 29, 2014

Where to submit your paper. Or “If at first you don’t succeed, fail fail again … then try open access”

The confluence of two experiences motivated this post. First, I was involved in a conversation on Twitter (below) that was reacting to suggestions (in a commentary in Nature) that the high volume of open-access papers was the cause of the reviewer fatigue that so often bedevils journals and editors (such as myself). At one point in this thread, someone pointed to a blog post titled “Why I Published in PLoS ONE. And Why I Probably Won’t Again for Awhile.” The main point of that post was to contrast the desire of young scientists to better the world by publishing in open-access journals with the perception that senior scientists don’t view a paper published in open-access journals as equivalent to a paper published in a more traditional journal. This latter sentiment was similar to my own experience on search committees in which candidates would be considered less impressive if they published too much in open-access journals.

The second motivation came from our weekly lab meetings. Near the start of each meeting, we go around the room asking “Who had a paper or proposal accepted or published this week?” And then, after a hopefully long discussion, we ask, “Who had a paper or proposal rejected this week?” I kind of like this two-part question because it enables us to get excited about our successes while also making the failures seem more acceptable. (“Oh, it happened to her too, so my own rejection is OK.”) And we can also complain about reviewers and can discuss how we will make our papers better in response. It just so happens that, over the past few months, no one has been able to speak up for the first question and pretty much everyone has spoken up for the second. One lab member even noted that rejection seemed to be a recent trend in the lab.

These two experiences led me to consider the question: “Should you – as a young scientist – take the easy route and publish in open-access journals, or the hard route (likely entailing multiple rejections) of trying more traditional journals, either the big boys or the classic society-based journals?” First, let’s consider the benefits of open access. The basic idea is, of course, that everyone will see the paper and you won’t waste your time cycling through journals that don’t think your paper is “important enough.” Moreover, citation rates are pretty decent for open-access journals, right? At least, that’s what everyone says. I would like to put this presumption to the test based on my own experiences.

I have published three papers in PLoS ONE (and several in other open-access journals). I quite liked all three papers and first tried traditional journals, but the papers were rejected a few times and the students wanted to move on with their lives and research, so we sent them to PLoS ONE, which accepted them quickly. So I decided to ask: How well have these papers been cited relative to papers I published in the same year in other journals? It turned out that I had a decent sample size because my two early PLoS ONE publications (2007 and 2009) happened to occur in years when I published a good number of papers (10 in 2007 and 17 in 2009). So I simply tallied the cumulative number of citations (here always from Web of Science simply for convenience; Google Scholar tells the same story) for each paper I published in those years, ranked them in order of citations, and asked where the PLoS ONE papers fell in relation to the others.

My previous two PLoS ONE papers are cited (Web of Science) least among all my papers published in those two years.
The graph tells the whole story. For my papers published in each of the two years, the PLoS ONE paper ranked DEAD LAST in terms of citations. I did have an a priori expectation that these papers hadn’t been heavily cited, but I had no idea it would be this bad. Moreover, I want to reiterate that I felt these two papers were interesting, well conducted, and potentially important – here and here they are for your citation convenience. Indeed, both were long included in a list of my favorite 15 papers. Of course, the alternative is simply that they really weren’t that good and I just can’t see it. Perhaps so but it remains clear that publishing in PLoS ONE will not enhance your citation rate for a given level of paper quality. So much for one of the supposed benefits (or at least lack of costs) of open access – at least in my case, which I am sure you will agree is what matters here. Of course, this general point is also clear intuitively: How many of us routinely check the papers coming out in Evolution or Ecology versus Evolution and Ecology (or PLoS ONE or PeerJ or Scientific Reports or anything starting with International Journal of …)?

OK, so clearly I am going to argue that you should forego open access and publish in traditional journals – but what of the annoyance, time consumption, and stress of rejection? Well, it is certainly true that rejection is common – for everyone. Many young scientists are stressed out when a paper gets rejected and feel that this somehow reflects on the quality of the work. They also often feel they are getting rejected more often than other scientists. The reality is that even established scientists get rejected all the time. A first proof of this maxim comes from a review paper by Cassey and Blackburn (2004) in Bioscience (cited only 15 times!) that surveyed the most successful ecologists (those with many publications in major society-based journals) and asked them how often their papers were rejected. The answer is often - as shown in the graph below. Indeed, many of these successful ecologists have had the same paper rejected multiple times and some of them still had at least one paper that they had failed to publish despite many tries.

Acceptance rates for papers submitted by the most successful ecologists. From Cassey and Blackburn (2004).
The above data are for the most successful ecologists and are from the good old days when rejection rates were not so high. How about some more recent data from a more mediocre (but established) ecologist (or, more precisely, evolutionary biologist)? 

I am a compulsive record-keeper. In this context, I have recorded every single submission of a paper on which I have been an author, as well as the outcome of those submissions. The sample size is pretty large now and allows me to illustrate the frequency of rejection and some factors that influence it, as summarized in the table below. I have been involved in a total of 275 submissions to journals (including multiple submissions of the same paper to different journals), of which 148 led to acceptance – an acceptance rate of 54%. However, some of those submissions were invited papers or commentaries, or appeared in special issues for which I was an editor. Taking away those near-sureties, my acceptance rate decreases to 43%. On the other hand, I have submitted 45 manuscripts to “big” journals (Science, Nature, PNAS, Current Biology, PLoS Biology) and only 1 was accepted – the first one I submitted. (I realize this looks crazy – 45 such submissions – but more about that later.) Removing these submissions from the tally as well, the acceptance rate jumps back up to 53% for the remaining “real submissions.” Finally, considering only “real submissions” on which I was first author, the rate jumps up again, to 68%. Whew, lots of stats that all simply say: rejection is an ever present companion in science.

Rejection/acceptance stats for my own submissions. 
I am not ashamed of these numbers, nor my relatively low number of open-access publications – because both facts reflect sending papers to the very best journals with low acceptance rates that then subject them to extremely rigorous and critical review, not just for the methods but also for their importance. Of course, it means that one needs to develop a mechanism to cope with rejection. My own mechanism – and the one that I try to tell my students – is that as soon as I submit a paper, I ask myself “OK, where will I submit this paper when it gets rejected.” (Hope for the best, prepare for the worst.) That way, a rejection simply means that I am days away from submitting a paper – turning a bad feeling into a good one. I also tell my students (and myself) that journals reject papers for all sorts of arbitrary reasons and it really doesn’t mean the work isn’t any good. 

While letting this post mature for a few days, I came across a great video of famous failures by people that went on to become wildly successful. This video also reminded me of a story about Tim Mousseau failing (or at least not immediately passing) his qualifying exam at McGill and having to write a remedial paper that has gone on to be cited more than 1000 times. How’s that for turning failure into success? I have heard of many other instances of papers getting rejected from a journal only to be greatly improved, some so much so that they end up getting published at a much “better” journal, such as Science/Nature.

So how high should one shoot? I have been a part of 45 submissions to big journals and all but one failed. Yet I don’t regret them (at least not all of them) – for several reasons. First, analyses (published in Science, of course) have shown that papers submitted to, and rejected from, Science/Nature end up receiving more citations than those that were first submitted elsewhere. Perhaps these were good studies to begin with and were written in a general way, and perhaps the review process improved them. Second, I think a number of my own papers submitted to Nature/Science were very good studies. (Perhaps better than many other papers published there – but then this is the sentiment of everyone that gets rejected from those journals, otherwise they wouldn’t have submitted there in the first place.) Indeed, at least five of my papers rejected from Nature/Science (some from both) have been cited more than 50 times. Three of the rejected papers ended up in Molecular Ecology and each is doing well: one published in 2012 already has 67 citations and two published in 2014 have received considerable attention (one of these was previously rejected from 8 other journals). So, if you have a great study, it is fine – good even – to submit it to Nature/Science. You will write it better and more succinctly, and you might even get some great reviews.

Articles published on their first submission (first intents) are cited less often than articles published in the same journal/year that were first rejected from elsewhere (resubmissions). Data from Calcagno et al. (2012 - Science.)

My favorite route, though, is society-based journals, like Ecology, Evolution, American Naturalist, Proc Roy Soc B, J Evolutionary Biology, J Animal Ecology (I still haven’t cracked the last of these nuts), and so on. These journals are where I want all of my work to end up (and you should too) – it looks good on your CV, and many more people see it and cite it. But, wait, I hear you saying: those papers won’t be accessible to the rest of the world because it requires an expensive subscription. Nonsense. Anyone can get access to any paper from any journal – many papers are posted on someone’s website and, for those that aren’t, all you have to do is email the author to ask for a copy! (I admit getting papers is harder – but certainly not impossible – without institutional access.) Moreover, you can pay for open access in those journals at a cost that isn’t much higher than at PLoS ONE or many other open access journals.

In summary, I suggest you work toward publishing in traditional and well-respected general or society-based journals as your goal, learn to deal with rejection, and only when you are so sick of the paper that you vomit (actually vomit, that is, not just feel nauseous) send it to PLoS ONE or another open access journal. (Or if you need really quickly publications to graduate.) Someone is bound to cite it someday – probably anyway. With this in mind, perhaps you might like to cite the cool new paper we just published this year in PLoS ONE.


Note added Dec 3: see my follow-up post (Where to submit your paper - response to reviews.) that responds to post-publication comments on the present post. 

Just for fun:
Speaking of tongue-in-cheek, see my parody of open access journals here: 

Monday, November 24, 2014

PITCHFORK SCIENCE: Guppies, Stickleback, and Darwin’s Finches.

[This is a cross-posting with the EXEB blog at Lund - thanks for the reciprocal opportunity Erik. And thanks for your earlier post here on Eco-Evo-Evo-Eco.]

I study Trinidadian guppies, threespine stickleback, and Darwin’s finches, surely 3 of the top 10 evolutionary biology “model” systems - for vertebrates at least. I thus fall at one extreme (or is it three extremes?) on the “pick a model system and use it to answer my question” versus “develop a brand new system all my own” continuum. Many students and postdocs find themselves facing their own decisions about where to position themselves along this continuum. Should they take the shortcut of working with an established system so they don’t have to work out the simple details and can get right to addressing the big general questions? Or should they forge their own path and become an expert in something brand new? It might seem, based on the above listing, that I consciously took the first approach but the reality is something quite different. In truth, I used a “follow your nose” coincidence-and-serendipity approach to study system choice. I here trace my own personal history in these research areas before closing with some general thoughts on how to choose a study system.

Why I study salmon: a 16 year old me with a steelhead from our cabin on the Kispiox River (BC, Canada).
I worked on salmon for my MSc and PhD, largely because I grew up with salmon fishing as my primary passion. Thus, I began studying salmon simply because I liked them and liked fishing for them. This led me to choose an institution (University of Washington - UW), department (School of Fisheries), and supervisor (Tom Quinn) ideally suited to immerse myself in salmon work. As my graduate work progressed, I very gradually became more and more interested in general questions in ecology, largely through exposure to the research of other people in the department. I even started subscribing to Ecology in addition to – of course – Fisheries. Yet my thinking remained salmon-centric: “what can ecology tell me about salmon”? Nothing wrong with that, of course. Then, when visiting home for Christmas in 1994, my mother gave me a book: The Beak of the Finch by Jonathan Weiner. When your Mom gives you a book for Christmas and you then spend the next week at home… well, you better read it.

The laboratory for my PhD: Lake Nerka, Wood River, Alaska.
The book was amazing. It described in wonderfully readable prose the research of Peter and Rosemary Grant on Darwin’s finches in the Galapagos Islands. What struck me the most, while reading beside the heater vent looking out at the blowing snow and -40 C weather (literally!), was Jonathan’s description of how the Grants had documented generation-by-generation rapid evolution of finch beaks in response to natural selection resulting from environmental change. Wow – you can actually study evolution in real time! It was my own eureka moment and, in short order, I became captivated by the idea. As soon as I got back to UW after Christmas, I went to the library and photocopied EVERY paper on Darwin’s finches (ah, libraries and photocopying – the good [and bad] old days). From then on, almost as though my brain had achieved an alternative stable state, my thinking was inverted to become: “What can salmon tell me about evolution?” 

My MSc and PhD work focused on sockeye salmon - this one in Knutson Bay, Lake Iliamna, Alaska.
Salmon did tell me a lot about evolution. I even edited a book (Evolution Illuminated, with one of my evolutionary idols, Steve Stearns) about merging evolutionary theory and salmon research. However, when one starts focusing on a topic (evolution) rather than an organism (salmon), one starts to become irked by aspects of the organisms that are not optimal for addressing the topic. Most notably, it is very hard to do experiments with salmon unless you have lots of water, lots of space, and lots of time. So, when thinking about a postdoc, I started talking to folks about which systems might allow me to better address basic evolutionary questions. I ended up moving in two directions.

The laboratory for my first postdoc. For more than a month of glorious weather, I camped on a small island in a small lake (Mackie Lake) at the end of a 4-wheel drive road. Those are my mesocosms floating in the lake and projecting from the island.
The first was the University of British Columbia (UBC) – because I didn’t want to go too far from my girlfriend (now wife) who was still at UW. I visited UBC and went from prof to prof telling them of my interest in a basic evolutionary question – the balance between divergent selection and gene flow – and asking if they knew of a system that would be good for testing my ideas. Many great suggestions were made, but Rick Taylor insisted he had the perfect system: Misty lake-stream stickleback – and he was right. So I started working on stickleback not because they were a model system, but because someone suggested they would be well-suited for my question and because it let me stay reasonably near my sweetheart.

A threespine stickleback guarding his nest.
The second direction came about through a conversation with Ian Fleming, who suggested that I should work with David Reznick on guppies. I hadn’t even considered this possibility, but I knew a bit about the system (which is also described in The Beak of the Finch) and it seemed cool. So I went to UCR and met with David and talked about how we might use guppies to study the interaction between selection and gene flow. David said he would be happy to help me with this work but that he didn’t have any money for me – and so I offered to write a full NSF proposal. I was just gearing up to do so when I heard that I had received an NSERC (Canada) postdoctoral fellowship to work with Rick Taylor on the Misty system – so off I went to stickleback, leaving guppies behind.

My favorite wild guppies captured in my first year of sampling, 2002.
UBC was great, an outstanding place for nurturing interest and insight into general questions in evolutionary biology, but one must eventually move on. My next postdoc was the Darwin Fellowship (I applied because of the title) at the University of Massachusetts (UMASS) Amherst, working with Ben Letcher on salmon again (hard to shake the habitat). While at UMASS, my guilt started building about telling David I would write an NSF grant and then not having done so, so I went ahead and wrote one, which got funded on the second shot (after bringing in my salmony lab-mate from Tom’s lab, Mike Kinnison). So my work on guppies eventually developed owing to guilt about not carrying through on something I said I would do.

The laboratory for our guppy work - here the Paria River, Trinidad
While at UMASS, my office happened to be near that of Jeff Podos, who was working on Darwin’s finches. Near the end of my Darwin Fellowship, Jeff received an NSF Career grant and had money to burn – I mean invest. Jeff knew of my interests and asked if I wanted to come along to the Galapagos on the project (he recalls me asking – or perhaps begging – to come with him), and of course I immediately said yes. So my work on finches was simply a case of being in the right place at the right time. The experience was every bit as exciting as promised in my day dreams that cold winter back in 1994. Several years later, Jonathan Weiner called to talk about my salmon work and I was able to tell him how influential his book had been and how it actually brought me (without any plan) to work on finches.

The laboratory for our finch work, presided over by a marine iguana.
In short, a large amount of coincidence and serendipity determined my choice of study systems. Once in each of the three systems, I became enamored with them and never left. I have now 25 papers on stickleback, 22 papers on guppies, and 11 papers on finches, and I have no intention of ever pulling back from any of these systems. I have also published 33 papers on salmon, and I continually look for new opportunities for additional work on them.

Perhaps my favorite finch photo.
Peter Grant once told me that, in conversation with Daniel Pauly at UBC, Dan told him that he (Peter) was a “point person” whereas he (Daniel) was a “line person”: a point person being someone who takes a single subject/system (finches) and looks at every aspect of their ecology and evolution, and a line person being some who takes a single subject (fisheries) and looks at it across many systems. I guess that makes me a pitch-fork person – trying to go into depth in three systems. Of course, this means that I can’t get too deep in any one system, much to my frustration. However, comparing and contrasting results from the three systems has proved fascinating. For instance, I study ecological speciation in all three systems with essentially the same methods (catching, banding/marking, measuring, recapturing, genotyping) focused on revealing the same processes (disruptive/divergent selection, adaptive divergence, assortative mating, gene flow). The similarities and differences in results obtained from the three systems has proved very instructive and motivational. In fact, my favorite research talk involves walking through a comparative story of ecological speciation in the three systems.
The title slide of my pitchfork talk.
Beyond how many systems one works in, I need to return to the question of working with model (developed) versus new (undeveloped) systems. As noted earlier, a benefit of working in a model system is that one doesn’t have to do as much background work (although every system is nowhere near as well-understood as the impression given by the literature), whereas a cost is that you are never known as the expert in that system (because the experts are the senior folks working on the same thing). The cost-benefit payoff is not easy to calculate and so the temptation for many students and postdocs is to spend a lot of time debating the pros and cons of the different approaches. I think all this angst is a mistake (or at least suboptimal) and that one should instead follow one’s nose (and Mom’s book recommendations). I think everyone should work on the systems and with the people that they find the most interesting and inspiring – not the systems that have the best-described genomes (as an example). These inspiring systems might be model systems or they might be new systems or both (I also have students who work on non-model systems), but they are – most importantly – the systems that feel right at the time, not the systems that have been rationalized based on a logical calculation of optimal career advancement. It worked out fine for me (and many others) – although I am sure my colleagues would argue I could still use considerably more career advancement.



An interesting perspective by Joe Travis on question-based versus system-based science: Is it what we know or who we know? Choice of organism and robustness of inference in ecology and evolutionary biology

Friday, November 14, 2014

Why stop there? Probing species range limits with transplant experiments

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

Understanding why species occur where they do is a fundamental goal of ecology.  Predicting where they might occur in the future is also an increasingly important goal in conservation, as invasive species spread and native species respond to climate change.  One approach to explore both issues is to study the edges of species distributions and the processes that currently limit them.

Do species stop occurring where things suck too much?
A satisfyingly simple explanation for range limits is that each species has an optimal set of conditions under which it thrives.  As it moves away from that optimum, individual fitness declines and populations dwindle.  At some point populations are unable to sustain themselves (we call this break-even point the niche limit) and the species disappears from the landscape.

Canada’s humans show a classic niche-limited northern distribution, huddling along the southern border for warmth. Statistics Canada. 

The best way to test why a species doesn’t occur somewhere is to move it there and see what happens (provided one is not dealing with humans). Transplant experiments comparing fitness within and beyond the range can test for predicted fitness declines.  Assuming experiments are adequately replicated in time and space, transplant success at the range edge but failure beyond suggests the range limit coincides with the species’ niche limit.

Adequate replication is no small feat, however, and makes good transplants labours of love (often minus the love by the end).  Since strong experiments will only ever be conducted on a small subset of species, those of us studying range limits must eventually ask ourselves, “is there any hope of predicting across species, or is it all just ‘stamp-collecting’?”.

To address this slightly uncomfortable question, we tested for patterns among transplants of species or subspecies across their latitudinal, longitudinal, or elevational range (111 tests from 42 studies).

A smattering of the 93 taxa transplanted beyond their range.  Most studies used plants, which obligingly stay where you transplant them.  

We tested how often range limits involve niche constraints by testing how often performance declined from the range edge (ideally) or interior (if there were no edge transplants) to beyond.  To compare among studies that measured everything from lifetime fitness to clam respiration, we calculated the relative change in a given performance parameter:

`(text{performance within the range } – text{ performance beyond}) / text{mean performance}`

What did we find?

Fitness declined beyond species’ ranges in
75% of 111 tests

and the average decline was significant.  The percentage was even higher when studies measured lifetime fitness (83% of 23 tests).  This strongly supports the importance of declining performance (niche constraints) in limiting species distributions.

How often do range limits coincide with niche limits?  We restricted this analysis to studies that included transplants at the range edge.  Without them one cannot tell if range limits coincide with niche limits, or exceed them via sink populations (middle vs. right panel Fig. 1).  Although most range limits involved niche constraints, only 46% coincided with niche limits.

Fig. 1. Hypothetical results comparing transplants at the range interior, limit, and beyond. Fitness declines beyond the range in all cases, but only the middle scenario suggests range and niche limits coincide.  Numbers give % of 26 meta-analysis tests that fit each RL vs. NL  pattern. Click to view at full size.

Discrepancies are generally explained by dispersal
If species fail to occupy suitable habitat beyond the range, they are dispersal limited.  If edge populations occupy unsuitable habitat (a phenomenon for which range limits have been nicknamed “the land of the living dead”; Channell 2000, Nature) they must be maintained by dispersal from the range interior to persist (Fig. 2).

Figure 2.  The full array of range limit vs. niche limit possibilities. Click to view at full size.

So, while most range limits involve niche constraints, dispersal decouples many from the species’ niche limit.  Interestingly,
while latitudinal ranges were often dispersal limited, elevational ranges were more likely to exceed niche limits via sink populations.
This makes sense given the much longer dispersal distances needed to traverse a geographic gradient than an equivalent elevational one.

Which niche constraints matter?
Amid growing concern over modern climate change, a lot of effort is spent predicting how species distributions will respond, with most models assuming range limits are imposed by climate.

Beech trees in Patagonia, Argentina don’t like cold winters either.

While climate is undoubtedly important, there are many examples of ranges limited by other factors, including interactions among species.  As species interactions are messy to include in range shift projections, it would be useful to know how important they are, and when.

Interactions with other species are important
We compared transplants in natural environments to those that softened potential biotic interactions (e.g. reduced competition or herbivory).  Beyond-range fitness declines were more severe when transplants were subject to all possible biotic interactions (Fig. 3).

Figure 3. Allowing all possible biotic interactions results in bigger fitness declines beyond species range limits (P = 0.0097). Click to view at full size.

We also tested an old hypothesis that biotic interactions are especially important at a species’ low-elevation and low-latitude range limits (click to view at full size):

We compared the drivers of high vs. low elevation limits and high vs. low latitude limits.  As predicted, most high-elevation range limits were imposed by purely abiotic factors (e.g. climate), whereas
> 50% of low-elevation limits
were imposed at least partially
by species interactions
(Fig. 4).  The same pattern exists for equatorial vs. polar limits, but there were too few studies to test it statistically.

Figure 4. Interactions among species are more important in imposing low-elevation (and low-latitude) range limits. Analyses included only transplants into natural environments that provided enough data to assess the causes of the range limit studied. Click to view at full size.

Not just stamp collecting
Our meta-analysis of transplant experiments revealed broad geographic patterns in the relative importance of niche constraints and dispersal, and in biotic vs. abiotic constraints (it also revealed that really good experiments are rare and sorely needed, if you’re tempted).

Implications for predicting climate-driven range shifts
First, we might expect faster relative shifts of high-elevation vs. polar range limits.  Dispersal is better at keeping range and niche limits in equilibrium across elevation gradients, and sink populations common at elevational range limits may provide a head start.  At the other end, ranges limited primarily by other species will respond less predictably to climate change, so we should not be surprised to see a mess of contrasting responses at lower limits.

Anna Hargreaves, Queen’s University

Monday, November 10, 2014

Plasticity in mate preferences and the not-so-needed Extended Evolutionary Synthesis (EES)

[ This post is by Erik Svensson at Lund University; I am just putting it up.  –B. ]

Andrew Hendry at McGill was kind enough to invite me to write a guest post at his blog, where I would explain why odonates (“dragonflies and damselflies”) are great study organisms in ecology and evolution, and I happily grabbed this opportunity. I will also re-publish this post at our own blog, Experimental Evolution, Ecology & Behaviour. Here I will try to put our research and our study organisms in a somewhat broader context, briefly discuss the role of plasticity in evolution and whether we would need a so-called “Extended Evolutionary Synthesis” or EES, as has recently been argued by some.

I am writing this from Durham (North Carolina), where I am currently at a so-called “catalysis-meeting” at NESCent (the “National Evolutionary Synthesis Centre”). The title of our meeting is “New resources for ancient organisms – enabling dragonfly genomics”. Briefly, we have gathered a fairly large group of researchers working on various aspects of odonate biology (including ecology, evolution, behaviour, systematics, population genetics, etc.) to create a genomics consortium, with the long-term goal of making genomic resources available for these fascinating insects so that we can recruit new talented postdocs and PhD students to our research community. This would be needed – I think – as evolutionary biology is suffering from somewhat of a low diversity in study organisms. A few classical model systems tend to attract a disproportionate number of researchers, such as Drosophila, sticklebacks, Anolis lizards, guppies, etc. But odonates are cool too! Please consider joining us, if you read this and are a young scientist who is looking for some relatively unexploited research organisms.

As an example of research in this group and in my laboratory, I would like to highlight our recently published paper in Proc. R. Soc. Lond. B.  entitled “Sex differences in canalization and developmental plasticity shape population divergence in mate preferences”. This is a study that contains experimental field data that were first collected back in 2003 – over a decade ago! – which has later been complemented with population genetic analyses and laboratory experiments.

Our study organism is the banded demoiselle (Calopteryx splendens; male in A above, female in B), which co-exists with its congener the beautiful demoiselle (Calopteryx virgo; male in C, female in D, above) in a patchy network of sympatric and allopatric populations in southern Sweden. What we show in this paper is that there is pronounced population divergence in both male and female mate preferences towards heterospecific mates, in spite of these weakly genetically differentiated populations being closely connected through extensive gene flow. Whereas females learn to recognize mates, males do apparently discriminate against females already when being sexually naive, revealing differential and sex-specific plasticity in mate preferences. Males are therefore more canalized and females more plastic in their mate preferences.

Interestingly, these sex-differences in developmental plasticity and canalization are also scaled up and shown at the between-population level: females show strong population divergence in mate preferences compared to males, presumably related to their higher plasticity. This suggests that plasticity can and does play some role in population divergence, even in the face of gene flow, which is of some principal interest to evolutionary biologists, and fits with ideas proposed by Mary Jane West-Eberhard in her book “Developmental plasticity and evolution”, but also with a recent population genetic model by Maria Servedio and Reuven Dukas on the population genetical consequences of learned mate preferences.

Given our results in this study, one could perhaps expect me to show some enthusiasm for the recent opinion-paper by Laland et al. in Nature entitled “Does evolutionary theory need a rethink?” But, as a matter of fact, I do not like the opinion piece by Laland et al., and I think it is one of those opinion articles that would fit better as a blog post. As it stands now, the opinon article by Laland et al. gives a misleading impression of a very divided scientific community and results in a confusing discussion for discussion’s sake.

Laland et al. argue that developmental plasticity, niche conservatism and some other factors are important in evolution, and so far I agree with them. They then go on to make various strong (but in my opinion very biased and sometimes unsubstantiated) claims that evolutionary theory needs to be changed substantially and radically. They argue for an “Extended Evolutionary Synthesis” that should replace the current Modern Synthesis. It is a bit unclear to me, first why we need an EES, second to what extent the current paradigm stops anyone from doing the research he or she wants, and third, what this EES would actually contain that makes it so urgently needed. The authors are quite vague on this point. In my opinion, far too many opinion articles have been published about the need for an EES, and far too little rigorous empirical or theoretical work has been performed, in the form of critical experiments, formal theory or mathematical modelling.

The EES is actually not an invention of Laland et al.; the term was first coined by former evolutionary biologist Massimo Pigliucci, who is today a professor in philosophy, after he has left evolutionary biology. During his relatively brief career as an evolutionary biologist, Pigliucci produced a steady stream of opinion articles and edited volumes in which he constantly questioned and criticized what he saw as “mainstream evolutionary biology” or “The Modern Synthesis”. His efforts culminated in a meeting he organized entitled “Altenberg 16”.

This meeting at Altenberg gathered a selected group of (self-proclaimed) scientific “revolutionaries” and resulted in a book entitled “Evolution – The Extended Synthesis”. What struck me, as an experimental evolutionary ecologist, was the rhetorical tone of the whole effort, the grandiose worldview of  put forward by the group and the seemingly naïve belief that scientific synthesis can be organized and commanded from above, and thus be declared, rather than growing naturally from below. The meeting at Altenberg was also quite biased in terms of who were invited – further strengthening the impression of an old boys network with a very biased view of evolutionary biology, mainly grounded in philosophical, rather than empirical arguments.

However, even if we accept that science in general, and in evolutionary biology in particular, evolves and changes over time, and even if we believe philosopher Thomas Kuhn’s theory about “paradigm shifts” and “scientific revolutions”, it does not follow that a revolution will happen just because there are willing revolutionaries. This is not how political revolutions happen either, such as the French, the American, or the Russian Revolutions. Having dedicated revolutionaries is not enough; such revolutionaries are only a subjective factor. What is also needed is the objective factor: the material (or scientific) conditions necessary for a revolution (political or scientific).

Neither Laland et al. nor their predecessor Massimo Pigliucci have have convinced me that they are the leaders we should follow, or that the time for the scientific revolution or a substantial paradigm shift is waiting around the corner. Although I do not consider myself an orthodox population geneticist at all, in this case I tend to agree with population geneticist Jerry Coyne, who has previously criticized Pigliucci for being committed to BIS – Big Idea Syndrome. One symptom that somebody is suffering from BIS is initiating debates for debate’s own sake. I  feel that the same criticism can be directed to Laland et al. Their rather rethorical opinion piece contains very few concrete suggestions of how to do research differently than we do today. This gives me the impression that this is mainly a debate about how to interpret the history of science, rather than being useful or providing practical advice to evolutionary biologists in their daily work.

Both Laland et al. and Pigliucci have painted a picture of evolutionary biology and the Modern Synthesis as a monolithic and dogmatic scientific paradigm that prevents researchers from asking heretical questions, such as addressing problems about plasticity. The Modern Synthesis clearly did not stop me and my co-workers from initiating our study on mate preference plasticity in damselflies. Neither is it clear to me that an EES (if it had it existed) would have helped us in any way to design our study differently than we actually did in the end. Given these considerations, I am quite convinced that the debate about the EES is truly academic (in the negative sense), as it will not lead us anywhere or provide us with any new analytical tools, tools being either empirical or theoretical. I therefore do not think that the proposed EES will have any long-lasting effect on the field of evolutionary biology – at least not as much as its proponents wish.

I am also quite frustrated by the poor scholarship of Pigliucci and Laland et al. regarding the history of the Modern Synthesis. Their rather negatively biased view of the Modern Synthesis strikes me as being a good example of a straw man argument wherein they set up the scene by making a caricature of something they do not like in the first place, and then go on to criticize that caricature. But their caricature is far from the more complex reality, richness and history of the Modern Synthesis.

A few years ago Ryan Calsbeek and I edited a book entitled “The Adaptive Landscape in Evolutionary Biology”, in which we and many others discussed the contrasting views between the population geneticists Sewall Wright and Ronald Fisher, and their legacy which still influences evolutionary biology and population genetics today. It is simply wrong to claim that was a monolithic paradigm that did not allow for radically different views on genetics, plasticity, and micro- and macroevolution. Had Pigliucci and Laland et al. read the various contributions in our book, many of which had radically different views, some of their misleading arguments could have been avoided. Critical views similar to those I have expressed in this post can be found on the blog “Sandwalk”, such as here and here.

However, I would say that there might already be an ongoing synthesis  in evolutionary biology – but it is not led by Laland et al. To see what I mean here, Steve Arnold published an interesting paper earlier this year in the American Naturalist entitled “Phenotypic Evolution: The Ongoing Synthesis”. In this article, Steve argued that evolutionary biology is now in the midst of a true synthesis, wherein micro- and macroevolution are finally coming together through the integration of quantitative genetics with comparative biology, largely driven by the explosion of phylogenetic comparative models of  phenotypic trait evolution.

Unlike the case for the EES, there are many more "silent" revolutionaries in the field of comparative biology who are now busy in developing analytical methods for phylogenetic comparative methods in the form of R packages and other useful tools. These new methods enable us to directly study and infer evolutionary processes and test various models and evolutionary scenarios. This is the sign of a healthy and dynamic research field: people do things, rather than just talking about the need for revolutions. Researchers in this and other fields are busy making quantitative tests, rather than spending time on verbal reasoning on the need for new syntheses. To paraphrase  a legendary revolutionary (anarchist Emma Goldman): “If you can’t do any rigorous experimental procedures or statistical tests, it is not my kind of scientific revolution”.

In summary: science evolves over time, and so does evolutionary biology. Our field is very different from what it was in the early days of the Modern Synthesis – in spite of some of the claims by Pigliucci and Laland et al. Without a doubt, plasticity, niche construction, and many other phenomena mentioned by Laland et al. are worthy of study and certainly very interesting. The mistake Laland and other proponents of EES make is that they think that they are the only ones who have realized this, and that other folks outside the EES camp are not thinking deeply about these problems. I end this blog post by citing another true revolutionary (quote taken from Jerry Coyne’s blog “Why Evolution is True”):
I close with a statement by my old mentor, Dick Lewontin, who of course as an old Marxist would be in favor of revolutions: “The so-called evolutionary synthesis – these are all very vague terms. . . That’s what I tried to say about Steve Gould, is that scientists are always looking to find some theory or idea that they can push as something that nobody else ever thought of because that’s the way they get their prestige. . . they have an idea which will overturn our whole view of evolution because otherwise they’re just workers in the factory, so to speak. And the factory was designed by Charles Darwin.”

Final note: I am fully aware that both Laland et al and Massimo Pigliucci are likely to strongly disagree with my criticisms above. The views are entirely my own and do not necessarily represent other authors of this blog.