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As the readers of the Eco-Evo Evo-Eco blog know, wide-spread appreciation for the reciprocal feedbacks between evolution and ecology has begun to emerge. While many questions remain, evidence from various systems indicate that phenotypic evolution can indeed influence ecological phenomena. The majority of work on this topic – as judged by Andrew’s recent book – focuses on the ecological feedbacks generated by traits evolving because of their role in capturing energy and avoiding predation; think alewife gill arches and walking stick camouflage.

However, over the last few years I’ve been thinking about the eco-evolutionary dynamics of a different suite of traits - those involved with competition for mates? This curiosity began during my dissertation research on sexual signaling in Bahamian mosquitofish. Basically, I wondered how the evolution of sexually selected traits might feedback to influence ecology. So, I began thinking about how to apply an eco-evolutionary framework to this system. After a year or two of failing to come up with anything compelling, I began reading more generally about the evolutionary ecology of sexual selection (Figure 1). Essentially, I wanted to know whether traits evolved by sexual selection were ecologically consequential. And if so, which ones?

Figure 1. I began writing this paper during a short break in the Scottish Highlands (pictured above). I soon discovered that there was no place better suited for thinking about the role of sexual selection in ecology. This beautiful landscape is populated by animals well known for having strong ecological effects derived, at least in part, from sexually selected traits: Red grouse, Red deer, Soay sheep, and Common lizards, to name a few. But despite being the subject of so much relevant work (Behavioral Ecology, Sexual Selection, Demography, and Sexual Conflict), Scotland is far from exceptional in this regard. Indeed, the more I read, the more I envisioned the potential for sexual selection to have substantial ecological importance anywhere. Nevertheless, that April in the heath-covered Monadhliath mountains had a significant impact on me. It not only helped frame the eventual paper, it reshaped how I think about the evolutionary ecology of sexual selection.

My main goal was to understand how the evolution of sexually selected traits might generate ecological feedbacks. This deep dive led to a surprisingly long list of examples. Sadly, very few of these examples met what I would describe as evidence of an eco-evolutionary feedback. Interestingly, this wasn’t because sexually selected traits are understudied, nor is it because they’re ecologically irrelevant. I could speculate as to why this is the case, but I honestly don’t know for sure. Yet, what is clear, is that a wide range of traits evolve by sexual selection, and that sexually selected traits are not only ecologically relevant, they’re often quite potent.

In a recent review in The Quarterly Review of Biology (Giery and Layman 2019), I highlight some examples – especially ones that I thought could represent the range of feedbacks that occur at population, community, and ecosystem levels. I had two primary goals. First, I wanted to get ecologists thinking more about the role of sexual selection in ecology. Second, I wanted to encourage evolutionary ecologists to think more about the ecological consequences of sexual trait evolution. The resulting review, perhaps more of a literature survey, is long and fairly speculative in places. Nevertheless, I think it satisfied these goals. And if you’re thinking about what traits might be relevant to your own system, I encourage you to check it out (link).

The purpose of this blog post is to broadcast some of the insights that I gained while putting the paper together. So, I’ve structured this post in three parts. First, I review what I believe is the most well-developed outlook on the role of sexual selection in eco-evolutionary thinking. Second, I share a few thoughts on the role of sexually selected traits to ecology. And third, I end with some recommendations for future work on the topic.

I. Sexual Selection and The Evolution of Population Fitness
Condition-dependent mating success: Currently, there’s a lot of excitement about the effect of sexual selection on ecology. Much of the current work on eco-evolutionary dynamics of sexual selection deals with the evolution of population fitness via condition-dependent mate choice. In general, these researchers are trying to understand whether sexual selection can ameliorate various genetic loads (usually mutation load), when mating success is biased toward the healthiest individuals. For example, if individuals with deleterious genetic variation have lower mating fitness (because they compete poorly for mating opportunities), then sexual selection might promote local adaptation and lead to an increase in population growth rate. Specifically, does condition-dependent mating purge mutation loads if genic capture underlies mating success? This is an exciting, standing question and I hope to see more studies addressing it using natural systems.

Antagonistic sexual selection and regulation of intralocus sexual conflict: For quite a few years now there is an increasing focus on the effects of sexually selected traits on population fitness. In many cases, the evolution of sexual traits actually adds a genetic load via intralocus sexual conflict. Under this scenario, incomplete evolution of mechanisms allowing for optimal expression of sexual phenotypes can subsequently influence population fitness through what has been termed a gender load, or a sexual dimorphism load. These sex-specific fitness costs arise because the benefits of sexual ornaments are sex-specific while the viability and/or fecundity costs are not. While the theory is relatively mature, empirical research is just beginning to take an overtly ecological perspective. The eco-evolutionary dynamics of intralocus sexual conflict presents many exciting opportunities for those interested in the topics already discussed.

II. The Ecological Consequences of Sexual Traits?
As discussed above, eco-evolutionary models of sexual selection have focused on examining whether sexual selection exacerbates or ameliorates genetic loads. But what I wanted to know was a bit more elementary – do sexually selected traits mediate ecological interactions and processes. It turns out that yes, traits that evolve by increasing mating fitness are ecologically relevant. It’s also worth noting that this is a recurring sentiment among evolutionary ecologists. 

Collias seems to think that sexually selected aggression might have interspecific effects: “The role of aggressive behavior at the level of the individual, social group, and species have been suggested. It remains to discuss the relationship of aggressive behavior to the balance of density ratios of different species, in the relationship commonly known as the ‘web of life.’” Collias 1944

Chitty suggests that density-dependent evolution of behavior (male-male aggression in particular) is worth testing if you want to understand population dynamics: “…given field evidence of unexplained reductions in breeding success and survival, we can be reasonably sure that … powerful intraspecific processes of some kind are at work in the wild.” “It seems, then, that behavior, physiology, and genetics must be of increasing concern to population ecologists, who have probably spent too long already on purely descriptive studies.” Chitty 1967

Trivers knows that male fitness depends on priority access to females, not viability: “In species with little or no male parental investment, selection usually favors male adaptations that lead to increased mortality. Male competition in such species can only be analyzed in detail when the distribution of females in space and time is properly described.” Trivers 1972

And Clutton-Brock et al. seem to know that researchers are routinely overlooking the role of sexual selection in ecology: “During the last two decades, ecology and evolutionary biology have again converged, and the importance of setting explanations of ecological phenomena within the framework provided by natural selection is now generally accepted. What is less often appreciated…is that Darwin’s theory of sexual selection has direct relevance to ecology, too.” Clutton-Brock et al., 1982

Nearly 40 years since Clutton-Brock’s quote, interest in the evolutionary ecology of sexual selection remains strong. Discussion about the coevolution of female preference and male sexual phenotypes remains quite lively, and the role of sexual selection in speciation continues to generate interest. But while calls for greater attention to the ecological consequences of sexual selection have echoed through the literature for decades, these recurring references seem siloed, disconnected, and generally ineffective at stimulating and/or sustaining interest. This, I believe, is evident in the paucity of work showing ecological feedbacks of sexual trait evolution.

Obviously, reviewing the evolutionary ecology of sexual selection is a colossal task – reinforcing my respect for Malte Andersson’s wonderfully inclusive review – which still stands the test of time (crack that book to any page and you’ll find interesting biology). Anyways, out of some practical concerns, I narrowed the focus of the survey to studies of vertebrates under natural or semi-natural conditions. After reading widely to collect cases in which sexually selected traits have strong and well-documented effects on interspecific interactions, population dynamics, and ecosystem-type stuff, a few generalities emerged.

Generality 1: Not all sexually selected traits are ecologically potent. This is seen when traits are chunked up among a few different categories (e.g., behavior, intrasexually selected weapons, ornaments and displays). One could argue for a different categorization, but I think this works ok.

Figure 2. Sexually selected behaviors such as male-male aggression, infanticide, sexual harassment, and coercive copulation are ecologically relevant. These traits, and their effects on demography, are relatively well studied in rodents (e.g., Myodes) and carnivores such as brown bears (Ursus arctos). However, some terrific experimental work in common lizards (Zootoca vivipara) and red grouse (Lagopus lagopus scotica) show that sexually selected behaviors are taxonomically widespread and can have large effects on population dynamics. Photos by Hanna Knutson, Philip McErlean, Jan Rose, and Mark Hope.

Sexually Selected Behavior: Evidence that infanticide, male-male aggression, sexual harassment, and coercive mating are ecologically important appeared throughout my search and were routinely among the most ecologically impactful sexually selected traits. Along with various morphological and physiological adaptations evolved by sexual selection, behaviors seemed to be the most important. Indeed, the direct and indirect effects of those behaviors have a strong influence on population dynamics for a wide variety of vertebrates. And while sexually selected behaviors can influence interspecific interactions (i.e., reproductive interference), the ecological effects of behavior tended to be most apparent when looking at intraspecific interactions. For example, sexually selected infanticide seems to be important for immature survivorship and female fecundity – an obvious finding in retrospect (Figure 2).

Figure 3. Sexual selection by male-male combat often leads to the evolution of weapons such as tusks, antlers, and horns. It can also drive the divergent evolution of traits that have other functions. This is perhaps best seen in the case of sexual selection on male bite force. In many lizards, males have enlarged heads and greater bite force. This often translates to divergent diets with males consuming taxa that are larger and require more power to subdue and handle. For example, broad-headed skink (Plestiodon laticeps) males consume much larger prey on average and across a broader range. Photo by Edward Prenzler.

Intrasexually Selected Weapons: Enlarged teeth and large body size were also important. Unlike the behaviors discussed above, morphological adaptations evolved by male-male combat seemed to be more relevant for interspecific interactions. For example, larger heads in many male lizards translate to an ability to capture and process larger, harder prey. Corresponding differences in diet appears routinely between the sexes in lizards and a variety of other vertebrates, especially carnivores (Figure 3).

Figure 4. Sexually selected display behaviors in frugivorous birds generates clumped patterns of seeds and seedlings. Dispersal follows two modes. First, a typical endozoochorous pathway where seeds are dispersed post consumption. Second, fruits and seeds are moved and aggregated without being consumed. The former case is exemplified by lekking birds that forage widely yet spend disproportionate time at display sites. Defecating at leks aggregates seeds and generates seedling patches. Examples include the long-wattled umbrellabirds (Cephalopterus penduliger), cock-of-the-rock (Rupicola peruviana), and white-bearded manakin (Manacus manacus). An example of the other mode is seen in bowerbirds, in which males also disperse and aggregate seeds, but in an interaction not mediated by endozoochory. That is, they don't eat the fruits. Instead, males of many bowerbird species gather forest materials to construct bowers, complex structures subject to female choice. As seen in the spotted bowerbird (Ptilonorhynchus maculatus), fruits aggregated at (and disposed near) bowers from the surrounding forest subsequently germinate; altering nearby plant communities (Madden et al. 2012). The photo depicts a great bowerbird (Ptilonorhynchus nuchalis), a congener which does not include fruit or seeds but maintains a similar bower structure. Photo credits from left to right: Nick Athanas, Ricardo Sanchez, Sergey Pisarevskiy, and Julie Burgher.

Ornaments, signals, and display behaviors: Interestingly, while there has been a lot of research on the evolution of signals and ornaments, there appears to be very little linking the evolution of these traits to ecology. For example, you might expect limitation of pigments such as carotenoids to drive compensatory increases in foraging on carotenoid-rich foods. But from what I could find, there’s little indication that this is widespread. Indeed, the only case I could find was a study showing that male hihi - a bird expressing yellow, carotenoid-containing nuptial plumage - seem to consume more carotenoid-rich fruit than females. In general, it seems that the evolution of signals and ornaments has a rather limited influence on ecological systems (happy to be proven wrong here). An exception might be made in cases in which display behaviors such as lek formation influences other species. For example, in several species of lek-forming birds a tendency to center activity around display sites seems to lead to an aggregated pattern of seed dispersal that could potentially influence community structure (Figure 4). Nevertheless, ornaments and signals themselves don’t seem particularly consequential.

Generality 2: Sexual selection can have indirect effects on trait-mediated ecology. This point is a bit more complicated, but the essence of this generality is that sexual selection shapes a range of traits not typically imagined to be under sexual selection. In part this is because they’re not – at least not directly. This point is perhaps best illustrated by the extreme sexual difference in ecology seen between males and females. While much of the divergent life history and ecology of vertebrates can be attributed to selection on fecundity and/or viability, signatures of sexual selection on the evolution of sexual dimorphism is often quite clear. For example, take the divergent diets of red deer. Sexual size dimorphism in red deer is well known and presumably evolves by male-male competition – larger males have higher mating fitness. But males and females also eat different foods – why? One hypothesis is that sexual selection for large body size indirectly influences the digestive physiology of ungulates. This hypothesis, based on the Jarman-Bell principle, was originally developed to explain the tendency for larger ungulates to consume less-nutritious plant material, has been adapted to intraspecific variation as well. Indeed, the larger body size of males confers an ability to digest and gain energy from rougher forage. Therefore, sexual selection has an indirect effect on the trophic ecology of sexually size dimorphic critters (Figure 5).

Figure 5. Indirect effects of sexually selected traits are common. For example, a positive allometric relationships between body size and digestive physiology in ungulates and some other large herbivores such as elephants contribute to sex- specific diets and sexual segregation. Photo by Jan Rose.

Essentially, the indirect ecological effects of sexual selection result from selection on functionally integrated traits. That is, selection on body size influences digestive physiology, predation risk, thermal performance, locomotion performance, etc. In turn, these traits have their own ecological effects. Accounting for the relative influence of sexual selection on functionally integrated phenotypes is a challenge. Nevertheless, such indirect effects of sexual selection appear to be quite strong in some cases.

III. Take Home
This review was really about getting others to try and view the evolutionary ecology of natural populations through the lens of sexual selection. Ultimately, if we want to integrate sexual selection into and eco-evolutionary framework there is a lot of work left to do. First, evidence for ecological feedbacks of sexual trait evolution are generally lacking despite evidence that sexually selected traits can evolve on contemporary timeframes (Svensson 2019). Second, we need to spend more time thinking about the role of sexual selection in intraspecific ecological diversity (De Lisle 2019, Fryxell et al. 2019). And third, development of eco-evolutionary frameworks that integrate sexual selection will require advancement of fitness-based perspectives as well as trait-based ones.

I don't see conceptual or practical impediments to this integration of sexual selection and ecology. How then, might we promote a fuller view of evolutionary ecology? I suppose the quote below offers some insight:

Even if one strongly believes in the action of natural selection it is exceedingly difficult as Darwin has pointed out, to keep it always firmly in mind. Neglect of natural selection in ecological thinking is, therefore understandable though regret[t]able. However, its deliberate exclusion…would seem to be exceedingly unwise.” Orians 1962

Here, Orians reminds ecologists that natural selection is ubiquitous and that the wise ecologist would be in error to infer the function of the natural world without its due consideration. As we know, the farsighted sentiment Orians articulates is now rather familiar. Indeed, it seems to me that most recognize natural selection as pervasive and relevant for  ecological inference. Now, I don't think that keeping evolutionary processes such as sexual selection in mind is exceedingly difficult. While it's probably not the most common way ecologists think about the world, many ecologists do pay keen attention to sexually selected traits. Nevertheless, I wouldn't hesitate to say that a broader inclusion of sexual selection in ecological thinking would be welcome.

Some recent papers worth a read:
De Lisle, S. P. 2019. Understanding the evolution of ecological sex differences: integrating
      character displacement and the Darwin-Bateman paradigm. EcoEvoRxiv:         
      https://doi.org/10.32942/osf.io/e2ahg. (link)

Fryxell, D. C., D. E. Weiler, M. T. Kinnison, and E. P. Palkovacs. 2019. Eco-evolutionary  
      dynamics of sexual dimorphism. Trends in Ecology & Evolution xx:1–4. (link)

Giery, S. T., and C. A. Layman. 2019. Ecological consequences of sexually selected traits:  
      an eco-evolutionary perspective. The Quarterly Review of Biology 94:29–74. (link)

Svensson, E. I. 2019. Eco-evolutionary dynamics of sexual selection and sexual conflict. 
      Functional Ecology 33:60–72. (link)

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"Hey, we should write a review paper!"

Raise your hand if you have said, or heard, this sentence....  Or, the close cousin of this sentence: "You should write a review paper and submit it to ___journal_name____", sometimes spoken by Editors seeking to game the citation and impact factor system. (Publishing more reviews is an easy way for journals to boost their IF).

We (Dan Bolnick and Andrew Hendry) recently collaborated on a review paper. We are honestly excited by the topic, and feel like we had something useful to say that would help shape people's view of the topic (especially newcomers to the field). But the process of wrangling 20 people's opinions - authors and reviewers and editors - into a coherent text was like the proverbial herding-cats, but with really big cats.  Big grumpy cats. That's not the fault of any one (or group) of co-authors, it's just what happens when people with many different views and time constraints and agendas try to work together on something that is nobody's number-one-priority.

RIP GrumpyCat, Patron Saint of Writing Review Papers
And, at the same time, we are both involved in multiple other review papers simultaneously. Some of these are papers we really feel convey a new idea in a compelling way. Some of them were aggressively solicited by journals. We started emailing back and forth to commiserate about the joys and headaches of review papers. We both feel like we are probably overdoing the review paper thing. Which led us to wonder, when is it good, versus bad, to dive into writing a review? What are the pros and cons? How do you tell which review papers are worth your time, and which are not?

It's easy to hate on review papers, and complain that they are just soap-box pontification. Just people gaming the citation-driven academic system. But then, we all can also think of great review papers we've read. Papers that helped us learn the layout of a subfield or topic outside our usual expertise.  Papers that made us think differently about a familiar topic. Papers we found valuable to assign as reading for a graduate or undergraduate class to introduce newcomers to a topic. They are also great for senior scientists making a lateral move between fields. For instance, Dan has had a shift in the past 10 years into more evolutionary immunology, and found review papers immensely helpful in learning this complex field in a semi-efficient way.

So, what makes the difference between a hot-mess herd-of-cats review, and an effective one that people want to read? When is it appropriate to write a review, and when should you cease and desist? And, how do you steer clear of the common pitfalls that make the difference between an influential citation classic, versus a waste of your time (as a writer, or reader)?

Note, there are some other blogs on the topic of review papers. For instance, Andrew did an old EcoEvoEvoEco blog about citation rates to his reviews versus other papers:

And Steve Heard wrote one too. We didn't read Steve's blog in advance of this one, to not bias our own opinions *.

(* or perhaps because we were lazy)


1) Should you write a review paper (a handy flow chart)If you have to ask this question, then the answer is probably no. Some people would say the answer is ALMOST ALWAYS no:

Other people seem to think that everyone should write a review paper, and require their graduate students, or even students in graduate courses, to write and submit review papers:

And pretty much every working group that has ever convened at NCEAS, NESCENT, NIMBioS, iDiv, or other such institutes or centers, feels an obligation to write a review.

Our view is that there are times for reviews, and times not to review. For every thing, turn, turn, turn, there is a synthesis, turn, turn turn.  The question is, what's a good reason, what's a bad reason? Well, to help you in your deliberations, here's a handy and mostly tongue-in-cheek guide:


2) Pros and Cons of writing a review paperPROS:
  • A good review can bring together existing knowledge in ways that generates a new insight. 
  • You get to make methodological recommendations for how people should move ahead to study a topic, setting a research agenda by laying out new questions or identifying more (and less) effective experimental approaches. If you can successfully define an agenda that other people actually follow, you can guide the future of your discipline. And that's rewarding.
  • You can define the standards of evidence. For example, Schluter and McPhail 1992 (American Naturalist, of course) defined a set of observations they deemed necessary and sufficient to prove an example of ecological character displacement. In hindsight, these were very stringent and few papers have measured up even almost 30 years later. Andrew Hendry weighs in here: "I am generally negative about “standards of evidence” papers as they are always un-realistically stringent – and people think that you don’t have evidence for a phenomenon even if you are nearly there. Kind of like needing to reject a null hypothesis. Such papers would be better pitched as weighing evidence for or against a given phenomenon. Kind of like levels of support for alternative models. Robinson and Wilson wrote a “Schluter was too strict paper, I think.” Others have done the same for other such papers."
  • It can be really enjoyable to attend a working group designed to brainstorm and write a review. The process can be challenging in a good way, as everyone hashes out a common set of definitions and views. Ten or twenty (diverse!) people in a room for a few days arguing over details of semantics and interpretation of data or models is a great way to reach a consensus on a subject, which you then want to convey to everyone who wasn't in the room, hopefully to their benefit (but perhaps to their annoyance).
  • Review papers also help the writer organize their thoughts on a topic – often stimulating their own empirical/theoretical research. This is why many professors encourage their PhD students to make one PhD dissertation chapter be a review of a topic. Note, however, that while this might be a good motivation to write a paper for your own edification, it isn't necessarily a good reason to publish it for other people to read.
  • Self-interested reason last: Review papers can become your most-cited work. That's certainly the case for both of us. [Dan: four of my five most-cited papers are straight-up reviews, the other is a meta-analysis. These five account for about 40% of my lifetime citations, though they are only 4% of my publications. For a more in-depth analysis, see the figure below. Overall, 19% of my lifetime papers are reviews. 65% are empirical. 16% are theory. In contrast 31% of my citations are to those 19% of my papers that are reviews, 32% to my empirical papers, 25% to meta-analyses, 7% to theory papers, 4% to methods. From this point forward in this blog, I'm going to consider meta-analyses as belonging more in the empirical study side, than as a review, because they entail both a great deal more work, and more de novo data analysis and interpretation.]

      Note, however, that Andrew and Dan may be in the minority in this regard. A twitter poll found that a majority of unscientifically sampled people had empirical papers as their most cited. 

  • A bad review can really really flop. Perhaps nobody wants to read it. Even worse, what if lots of people read it and disagree with the premise or conclusions? It can come across as narcissistic, or wasting people's time which makes them grumpy (refer back to GrumpyCat, above).
  • Saturation: some topics (I'm looking at you, eco-evolutionary feedbacks) have a high ratio of reviews to actual data. More on this later.
  • Takes your time away from 'real' science, generating and publishing data or models that really advance our collective knowledge forward. For that matter, it chews up reviewer and editor time also, so hopefully it is worth everyone's time, but it might not be.
  • Citation "theft". There's a strong argument to be made that when we write about a scientific idea, we should cite whoever first proposed that idea (and/or whoever provided the first or the strongest-available evidence for the idea). Citations are the currency by which authors get rewarded for their work, and we want to reward people who generate new insights. By citing them. But, review papers tend to attract citations. It is easier to cite a review saying that "X happens" than to locate the first published example of X. And, the review lends a greater air of generality. You could cite 10 experimental articles showing X, or just one review. Especially when writing for journals like Nature or Science, where citation space is limited, one naturally gravitates towards citing reviews. Yet, this seems undesirable from the standpoint of rewarding innovation.  The win-win good news is that most people preferentially cite a mixture of both review papers and original sources to make a point (though perhaps less so in leading journals with artificially short citation sections):
  • Some people get really annoyed by an excess of review papers. They can be seen as "fluff", as a form of gaming the system or parasitism. Michael Turelli used to tell his students and postdocs that reviews counted as negative papers. He was only half joking. Well, less than half joking. So, by his rules, we propose a modified citation and H index. The Turelli's Penalized Citations is the total number of citations to non-review papers, minus the total number of citations to review papers. By that measure (including meta-analyses as data papers), Dan loses 2/3 of his total citations. If meta-analyses were also included in among reviews, he'd be in negative territory (negative 1800). Turelli's Penalized H Index is the H index just among non-review papers, minus the H index just of review papers. Dan's TPHI is 21.  This must be why Turelli secretly harbors thoughts of disowning Dan. We assume.  Andrew Hendry adds here: from Web of Science, my Turelli’s Penalized Citations are 1865 if meta-analysis is empirical and -213 if meta-analysis is review. My Turelli’s H Index is 18 if meta-analysis is empirical and 4 if meta-analysis is review.  In short, we've clearly both benefitted from reviews.
You know who = Michael Turelli. Ironically, Michael covered the page charges for what was to become Dan's most-cited (review) paper, co-written with a group of fellow graduate students at UC Davis.


3) Do's and Don'ts of writing a review paperDO:
  • Clarify terminology in ways that are consistent with past usage.
  • Summarize existing knowledge, but this should be only a modest part of the review.
  • Derive a new conclusion that follows from, but is not presently stated in, the existing literature. As you will see from the copied tweets below from a recent thread, the overwhelming consensus is that reviews must provide a serious new insight, some value-added.
  • Easy to read and non-obvious diagrams conveying key ideas.
  • Identify gaps in our knowledge.
  • Describe specific experimental or other method innovations that allow people to advance beyond the existing knowledge.
  • Write well.
  • Think about your audience. Are you writing to experts in your field who have also read the same papers, but maybe haven't put the pieces together in your particular way? Are you writing to professionals from other disciplines to introduce them to your field? Are you writing to undergraduates or graduate students? Of course a great review paper might be accessible to everyone, but often these different audiences require different apprroaches. Most fundamentally, are you writing to fellow specialists, or to non-specialists? 
  • Provide specific examples to illustrate points, without overloading the reader with all the examples.
  • Put the topic into historical context, including bringing to light older but very relevant papers. Many excellent old papers fall off the map, but deserve credit for their pioneering insights.
  • Clearly state why a review is needed / appropriate at this juncture.
  • Provide tables of relevant examples of phenomena you describe, with some annotation. These can go in supplements, but are useful for people entering into the subject.
  • When there's enough empirical work available, make it a meta-analysis to derive quantitative conclusions.
  • Think about the diversity of authors whose work you are highlighting. Do not just mention work by your friends, and do not just mention work by older white males. 
  • Co-author with a diverse group of colleagues to ensure your review's viewpoint represents a consensus opinion not just your own. Both Dan and Andrew have looked over their own review papers and, in retrospect, find themselves wanting in this regard and are trying to do better going forwards (http://ecoevoevoeco.blogspot.com/2016/04/subtle-sexism-self-evaluation.html.
  • An exception to the "Say Something New" rule, is that review papers can do a great service if they bring an old idea to the attention of a new audience. Put another way, we can say that an idea is new to some group of people. For instance, the eco-evolutionary dynamics field saw a proliferation of review papers, some might say faster than the number of new empirical papers for a time. Partly this was because the time was right and multiple groups were converging independently on the theme. And partly, they were talking to different audiences, some to ecologists, some to evolutionary biologists, or to conservationists. So, bring something to a new audience is another option.
  • Write well, and aim for a widely-read journal. Sometimes a topic has been reviewed before, but that review didn't land its punches and people aren't really paying attention. A follow-up review in another more visible location, that is better written or better-argued, may stick with previous reviews didn't. Even just getting the same paper (writ large) in a fancy journal (Science/Nature) can have a huge positive effect on the spread of the idea – and, of course, attention to the earlier review. Without this, rapid evolution would not be so prominent in the UN Global Assessment and many other such places.

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1 pm Paris time today saw the official release of the long-awaited Global Assessment by the Intergovernmental Platform for Biodiversity and Ecosystem Services (IPBES). The product of intensive work by hundreds of people from more than 50 countries over more than three years, the document summarizes the state of biodiversity on Earth and discuss what we can do to improve it that state in the future. The assessment is hundreds of pages (with many many more pages of appendices) and the full document is therefore likely be read by only a small subset of people interested in the topic. For massive documents like this, what is much more likely to be read by many more people is the Summary for Policy Makers (SPM), in this case a 39 page document by itself. Even this SPM is much too long to be read by Important People (Presidents, Prime Ministers, Environmental Ministers) and – of course – by reporters. Hence, everything in the SPM is also distilled down to eight “Key Messages” spanning two pages at the very start of the SPM. These key messages are sure to be read by nearly everyone.

I here wish to draw your attention to Key Message #8, which reads in its entirety:

Human-induced changes are creating conditions for fast biological evolution - so rapid that its effects can be seen in only a few years or even more quickly. The consequences can be positive or negative for biodiversity and ecosystems, but can create uncertainty about the sustainability of species, ecosystem functions and the delivery of nature’s contributions to people. Understanding and monitoring these biological evolutionary changes are as important for informed policy decisions as in cases of ecological change. Sustainable management strategies then can be designed to influence evolutionary trajectories so as to protect vulnerable species and reduce the impact of unwanted species (such as weeds, pests or pathogens). The widespread declines in geographic distribution and population sizes of many species make clear that, although evolutionary adaptation to human-caused drivers can be rapid, it has often not been sufficient to mitigate them fully.

I would like to pause at this point to reflect on an astounding fact: rapid evolution is one of the eight Key Messages of the IPBES Global Assessment. This fact isn’t astounding because rapid evolution doesn’t belong as a key message; but rather because, only 20 years ago, very few people –few scientists even – would have acknowledge the practical relevance of rapid evolution.

It is with some pride that I can report that, in fact, I wrote much of Key Message #8 – with modifications resulting from many reviewers and also with final tweaks during the Plenary Discussion in Paris. I don’t profess to be responsible for, or to favor, each and every word and phrase in the key message; but I do claim to have a key role in this statement making it into the Key Messages, as well as the background material provided later in the SPM, and – of course – the numerous resonances of this “theme” across the rest of the Global Assessment.
I seem to have been relevant. How the Hell did that happen?


Many prospective graduate students start discussions with me by expressing their desire to be relevant – usually to conservation. As a memorable example, one student starting our conversation by saying “I am interested in evolutionary biology or conservation biology.” My response, of course, was “Well, in my lab, we do evolutionary biology and not conservation biology.” To such students wishing to be relevant in conservation biology, my suggestion has always been to NOT do Conservation Biology (note the capitals this second time). I then go on to argue that Conservation Biology is typically imagined to be helping species x or location y or – most commonly –helping species x in location y. Such work is important I acknowledge but we don’t often do it in my lab. The reason is that work to aid species x in location y often has no influence on anything other than species x in location y – and, often, no influence even on species x in location y. I go on to argue that simple basic science designed to understand “how the world works” is by far the best way to make an impact and be “relevant” on the largest possible scale – that is, far beyond only species x in location y. To make this case to students, I go on to give examples. One is the important work done on the effects of inbreeding on fitness, which started with general evolutionary theory and testing on organisms that were not species x in location y. Yet that general work went on to heavily influence policy for many species in many locations.
I then try another example from my personal experience. I try to argue that much of my research is based entirely on a fundamental interest in understanding of how rapid evolution shaped the world – yet it turned out that the insights gained from this research have, in fact, become very broadly relevant. That is, purely basic science at the time then later became applied in ways that influenced policy and, in fact, many species x in many locations y. As of today, I can point specifically to Key Message #8 from the Global Assessment as a concrete example of the contribution of pure basic evolutionary biology to global policy relevance.

This blog post might seem to smack, at least to some, of arrogance – that I am somehow touting my own awesomeness and importance in science and beyond. The key point, however, is not that I am somehow more intelligent or hard working or dedicated or whatever than are other researchers. Rather, the key point will be that focused interested on a basic research question has led to publications in academic journals that have precipitaed a few chance events that eventually snowballed into Key Message #8 in the Global Assessment. I tried to keep my description of this series of events short but had trouble doing so. I did consider what I might delete to make it shorter but then realized that, in fact, each step in this long chain of coincidental (or not) events was necessary to Key Message #8, or at least my contribution to it.


Part 1. Contemporary evolution …

In 1992-1993, Mike Kinnison and I both started studying rapid evolution in salmon at the University of Washington: Mike worked on New Zealand chinook salmon and I worked on Lake Washington sockeye salmon. Our choice of the overall topic (rapid evolution) and our specific study systems had nothing to do with our own insights or ideas – they were instead the suggestion of our MSc (and later PhD) supervisor Tom Quinn. At the time, we were both focus on salmon, not evolution.

Tom Quinn in 1995.
In 1995, my mother bought me a book for Christmas by Jonathan Weiner called The Beak of the Finch. This book about Darwin’s finches kindled my interest in evolution per se, as opposed to salmon evolution.

In 1998, Mike and I read a “News and Comment” articlein Trends in Ecology and Evolution (TREE), written by Erik Svensson, about two 1997 studies. One study was by Jonathan Lososin Nature and the other was by David Reznick in Science, both reporting rapid evolution – the first in Anolis lizards introduced to small islands and the secondin Trinidadian guppies introduced to predator-free environments. The key innovation of these new papers was that they calculated evolutionary rates for their studies and compared those rates to evolutionary rates estimated from the fossil record. This comparison revealed that evolution in lizards and guppies was several orders of magnitude faster (RAPID!) than rates of change observed in the fossil record.

Later in 1998, Mike and I wrote a letter to TREE, titled “Taking Time with Microevolution”, in which we criticized the current methods for estimating evolutionary rates. Exploring this question while writing the letter made us realize that much more needed to be said than we could effectively summarize in that short letter.

Also that year, I was invited by Eddie Beall to participate in salmon research at an INRA station (Saint-Pée-sur-Nivelle) in France. Without my friends and girlfriend – and before the internet was really that useful – and staying in a dorm at a small research station in a very small town in the Basque countryside, I had plenty of time. My goal to write a longer paper about evolutionary rates had been nagging at me, and one day – walking from my dorm to the small town – I simply said to myself: “Damnit, time to start writing.” A week later I had a first draft sent to Mike.

In early 1999, Mike and I submitted the paper to Evolution – a real stretch for two salmon-focused students who had never published any of our previous work in an evolutionary journal. Remarkably, Evolution published it as a “Perspective” with the start of the title being “The Pace of Modern Life.”

The paper quickly received considerable interest from the evolutionary community, as it was the first review of rapid evolution (which we argued was better called “contemporary evolution”). This interest included the editors of Genetica contacting me to ask if Mike and I wanted to edit a special issue on rapid evolution. This invitation came before the days of predatory publishers who are constantly asking you to edit special issues, and so we were shocked and agreed instantly. We then contacted all of the leaders in the field and, remarkably, nearly all of them agreed to contribute papers.

I edited this special issue during my postdoc at UBC, where “ecological speciation” was all the rage. All of the discussion I was hearing on this topic inspired me to re-examine my Lake Washington salmon studies for evidence of whether rapid evolution was leading to reduced gene flow between populations: i.e., the rapid evolution of reproductive isolation. Recruiting my friend John Wenburg and his supervisor Paul Bentzen, (then both at the University of Washington) to conduct genetic analyses, I submitted the findings to Science and – remarkably – the paperwas accepted. (I have since had dozens of submissions rejected from Science & Nature – more about that here.)

Based on the above work on rapid evolution – probably especially the Science paper – I received the American Society of Naturalists Young Investigator Prize in 2001. Winners of this prize all give a talk in a symposium at the Evolution meeting. I did so and was afterward approached by the editor of TREE (Catriona MacCallum) who asked if I wanted to write a paper for them. I agreed and she asked me to send her some possible topics that I thought might be appropriate.

Part 2. … might be relevant for conservation biology …

One of the other people studying rapid evolution in the late 1990s was Craig Stockwell – and his work focused on endangered desert fishes. I had discussed this work with him several times and, on a whim, suggested to TREE that we could write about the relevance of contemporary evolution for conservation biology. This was the least favorite of my suggestions at the time (you know nothing Andrew Hendry!) and yet it was the one that TREE asked for.

Not knowing much about conservation biology, Mike and I invited Craig to lead the paper for TREE – and we are very thankful to have done so as Craig was able help position our shared basic knowledge of contemporary evolution into a solid conservation framework. The result, published in 2003, was the first review paper talking about the importance of contemporary evolution for conservation biology. Just last week it passed 1000 citations.

Citations are not the only, or perhaps even the best, indicator of scientific importance. Still, 1000 citations! And, in fact, this paper did have an influence on bringing evolutionary thinking to conservation & policy. @IPBES @FutureEarth @mcgillu @BioMcGill @Trends_Ecol_Evo pic.twitter.com/ttKu2MCcJi
— Andrew Hendry (@EcoEvoEvoEco) May 1, 2019

In 2004, I was invited to interview for a job at Yale University – I was then an Assistant Professor at McGill University where I had started in 2002. One person I met on the interview was Michael Donoghue. Surprisingly, he didn’t talk about my research specifically but rather invited me to bring my contemporary evolution perspective to a group called bioGENESIS, which he outlined was a “core project” of a biodiversity-focused NGO called DIVERSITAS. At that point, I had never heard of DIVERSITAS – and had no knowledge about, or interest in, NGOs in general. I just wanted to study rapid evolution as a basic question. However, I agreed to join bioGENESIS, perhaps because I thought it might help me get the job (it didn’t) and perhaps because I was flattered to be asked and have a hard time saying no to direct requests for such help. Afterall, how much time could it take?

Dinner after my first bioGENESIS meeting.

The first bioGENESIS meeting I can remember attending was held in Paris in 2007. Sitting around the table with a bunch of evolution-focused Professors, I listened to endless discussions the importance of injecting evolutionary thinking into conservation policy at the national and international levels. Countless NGO acronyms were used and I really had no idea what was going on; yet I could see that, perhaps, if I could eventually figure out what was going on, I might be able to contribute something new: everyone else around the table focused on past evolution, not contemporary evolution. I do also remember spending an inordinate amount of time debating the specific logo that would be used for bioGENESIS – and it is a nice logo!

I attended many subsequent bioGENESIS meetings – Brazil (twice), New York, Montreal, Paris again, and many others. My role in these meetings was generally to help inject contemporary evolution into various discussions and documents, such as the bioGENESIS Science Plan and a paper for Evolutiontitled “Evolutionary biology in biodiversity science, conservation, and policy: a call to action.”

In 2006, I was invited by Louis Bernatchez and Michelle Tseng to join the inaugural editorial board of the new journal Evolutionary Applications. I remain an Associate Editor at the journal, which has been extremely successful. I have also published a number of my own papers there

I eventually became Chair of bioGENESIS and started to attend the broader DIVERSITAS meetings, where I rubbed elbows with many movers-and-shakers in the international science-policy interface, such as DIVERSITAS Chairs Georgina Mace of University College London and Hal Mooney of Stanford University. I was also through these contacts invited to give talks at various general events, such as Darwin’s 200th birthday celebration at the National Academy of Science in Washington, DC – events at which many of these movers-and-shakers were again present.

Many global change programs, including DIVERSITAS, had long been funded by governments to provide advice and guidance to the Convention on Biological Diversity (CBD) and other governmental and intergovernmental programs. Around 2012, however, governments – especially the US – decided this piece-meal was too chaotic, expensive, and time consuming, and so they asked that all of these programs unite under a common banner, which came to be called FutureEarth. I continued to work with bioGENESIS under the new aegis of FutureEarth.

Part 3 … and IPBES.

For several years in bioGENESIS, I had been hearing about IPBES, the new IPCC-like organization that would be focused on biodiversity and ecosystem services. Some members of bioGENESIS were involved in IPBES as advisors or “observers” but I had not been.

Then, in 2016, I was contacted by Sandra Diaz with a request to participate in the upcoming Global Assessment to be conducted by IPBES. Although Sandra had herself done a lot of work on contemporary evolution, she was very busy as one of co-Chairs of the assessment and wished to invite the help of another expert on the topic. I presume my name come up through a combination of my previous papers and probably also my visibility to the movers-and-shakers I had encountered during interactions at DIVERSITAS, FutureEarth, and so on. Indeed, Hal Mooney and Georgina Mace were both involved in the Global Assessment as advisors/reviewers, and Anne Larigauderie – whom I knew as Executive Director of DIVERSITAS – was now Executive Secretary of IPBES.

I missed the first authors’ meeting for the IPBES Global Assessment owing to a previously-planned family trip and also the second meeting owing to a broken leg. However, I was able to attend the third (Cape Town) and the fourth (Frankfurt) authors’ meetings at which I worked, especially with Andy Purvis, on Chapter 2 – Nature, again always..
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I just got back from three consecutive 7-10 day trips into the field: Trinidad, Galapagos, and Argentina. Much of my research life has been in the field. I spent 10 consecutive summers in the Bristol Bay Region of Alaska. I have worked in Trinidad in 16 different years. I have made 14 research trips to Galapagos. I have worked on northern Vancouver Island in more than 10 years. I have done research in Chile, Argentina, Uganda, Panama, Kenai, Haida Gwaii, California, and many other places. Some of these are depicted in the videos that intersperse the suggestions.

From this experience over more than 30 years, I have picked up a few things that can help make field work pleasant and productive – or not. Many posts have been written on important field work topics such as preparation, equipment, and safety. What I will try to do here is focus on other, less often explored, topics in hopes of supplementing the advice of others.

Plan – but be flexible.
Field work can be easy or it can be hard – but most of the time it is hard. It can go according to plan or not – but most of the time it doesn’t. Yet one thing is certain: what seems like it will work on paper back in your office will almost certainly need to be changed when you go to implement it in the real world – even if you are already experienced at your field site. Thus, it is perhaps best to think of your pre-departure plan (including back-ups) as merely a first draft of a plan. That way when you get to the field and the things you planned don’t work out, you won’t feel like your project has failed. Instead, you will enthusiastically work to modify the plan into a second draft or a third draft and so on. Sometimes you even need to start over. But this is field work – and sometimes the complete redo of the plan leads to something better than what you had initially intended.

Journeys in Search of (guppy) Parasites - YouTube

Be positive – always!
If you spend enough time in the field, things are almost certain to go way south at some point: hurricanes, floods, droughts, difficulties catching (or even finding) the target species, missing supplies, broken equipment, stranded vehicles, power-outages, personality conflicts, etc. These problems can cause small to large destruction of plans. Thus, as noted above, you will often need to throw yourself whole-heartedly into some exciting new plan that you develop on the spot if needed. But what will NEVER help is being outwardly negative about the project. Never complain about it to other people on the team. Never be defeatist. Never – to be blunt – be negative about your experience. This attitude will never help – ever – and it can sometimes deeply infect an entire field crew and cause problems that ramify far beyond the initial problem. Instead, be positive. Seek a solution. Collect new data. Focus on another species. Publish a paper on the effects of hurricanes or floods. Countless examples exist of this nimbleness that works around, or even takes advantage of, what initially seems a disaster.

A Finch-Eye View of Galapagos - YouTube

Don’t restrict/dictate a person’s food
Some people are extremely uptight about their food. Unless supplies are severly limited, let people eat what they want. Nothing rankles and sets some people against each other more than trying to dictate what they eat. (Of course, under extreme conditions of food shortage, this suggestion might not apply.)

Journeys in Search of Howler Monkey (microbiomes) - YouTube

If others are working – you should be too.
If someone on your team is working, then you should be too. It can rankle others (and is bad form regardless) if – for example – you sit and read a novel while someone else on the team is processing samples. Ask if you can help. If not, cook dinner, do the dishes, sweep the floor, prepare for tomorrow, write down protocols, look up relevant papers, etc. Only read your book if the person working insists multiple times that there isn’t any work for you to do. Stated another way: try to work harder than everyone else on the team.

Alaska Stickleback Field Work 2018 - YouTube

Share equally in the cooking and/or other chores.
If someone loves to cook, fine – let them cook as often as they like. But make sure you offer to cook too – or help with the preparation – or do the dishes (this is me!) – or process samples while they cook. Don’t just assume someone else is cooking.

Journeys in Search of Threespine Stickleback - YouTube

Bring earplugs!
My experience in Latin America is that the dogs bark until 2 am and then the chickens start crowing at 4 am. And my experience everywhere is that people snore. When I discovered earplugs, I was a lot more sanguine about such things.

Journeys in Search of African Fish - YouTube

Make a list of daily equipment – and make sure someone is responsible.
In Trinidad, we once drove 1.5 hours only to find out that we had forgotten the nets – necessitating another 3 hours of driving just to get them. In Galapagos and Trinidad, people have forgotten their field shoes. Probably everywhere, people have forgotten to charge the batteries to this or that piece of equipement. Make a list of the equipment that is needed each day and tape it beside the door. Then assign different types of equipment to particular people. If a person knows they are in charge of the nets, then they are much less likely to be forgotten. Ditto for any other type of equipment.

Finch versus Tribulus - YouTube

And  of course:
Don’t be abusive – in any way or under any circumstance
Don’t be outwardly obnoxious – even if you can’t stand the person
Don’t be passive aggressive – it is obvious to everyone
If you drink, drink responsibly

Journeys in Search of Tiny Fish - YouTube

The points noted above are important not just from the perspective of getting the work done but even more so from enjoying the field. And field work is what many of us are in this field for. Best of luck!

Journeys in Search of Darwin's Finches - YouTube

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When starting a new lab, from scratch, it is easy to begin to contemplate the question of what I might do differently as a PI. I'd run a lab for >13 years at UT Austin, and you get into a bit of a rut, where it is hard to change the culture, hard to introduce new habits. People have been in place long enough that creating a new style of lab meeting, or suddenly initiating a "put everything on GitHub" rule doesn't necessarily take root. But with a brand new lab, it's a clean slate, tabula rasa. But how to articulate all of the many things that make for an effective lab culture - welcoming, curious, ambitious, supportive, and efficient? I decided to try articulating my expectations in a document, a "Lab culture" file.
To begin, I did what comes naturally these days: I tweeted looking for advice / examples. And I got some great feedback. You can see the thread here, with replies from many disparate PIs with different styles of lab culture documents. Using these ideas, I built my own version, for my own style.  Its not a finished product. There are things I may decide don't belong, or things I need to add. Maybe entirely new categories not covered. But its a start. You can see the current version below. 
I hope that by sharing, I can (1) get feedback, (2) inspire others to do the same, (3) give you a template you might find useful yourself.

The short version:
# 1   Be kind & supportive.
# 2   Have fun doing science!
# 3   Be productive.

A Mentoring Plan is at the end of this document.


 Challenge yourself
  • Be self-motivated. You are here to advance your career, not mine.
  • Be ambitious. Identify your personal definition of success, and aspire to exceed that.Discuss your definition of success with your mentors and peers.
  • We are here to challenge ourselves to learn new ideas. Be curious.
  • If you don’t understand, ask questions, don’t just be silent!
  • Practice asking questions. Write down > 1 question per seminar talk you see
  • Take intellectual risks, but have a “plan B” that is safe. A really ground-breaking experiment might fail, so have another study you could do instead for a reliable publication.

  • We value a supportive work environment where everyone is treated with respect and dignity and is able to work towards their aspirations.
  • We value and support diversity in the workplace.
  • We do not tolerate bigotry, abuse, or harassment.
  • Seek out frank but constructive and kind criticism. Return the favor.
  • Communicate openly with your colleagues.
  • Leave the lab, food area, office, cleaner than you found it.
  • You are a member of a community; contribute to it, and draw upon it when needed.
  • Meet visitors. At conferences make a point of introducing yourself to strangers.

  • Honesty is essential for correct science
  • We prefer to avoid mistakes, but mistakes do happen. Take a deep breath, acknowledge them and fix it.
  • Conserve, reduce, reuse, recycle.

  • Be productive: set clear goals and meet them.
  • A core part of this job is to publish good science in a timely manner. If it’s not published, nobody will know it ever happened except us.

  • Outreach is a key part of our job. Find “your” outreach style and pursue it. Education, science communication, art… there are many strategies. Pick one and do it well.
  • Mentoringundergraduates or other kinds of trainees helps you, and helps them.

  • Health and personal challenges, including mental illness, are common hurdles people in academia face, as in any other walk of life. Engaging with the problem by discussing it with your peers and supervisors can go a long way towards getting help and accommodations. We can’t help if we don’t know.
  • Find a work-life balance that lets you do your job to the level you aspire to and lets you be happy
  • Be safe. In the lab, and in the field:
  • Seek the training you need to avoid, and respond to, emergencies, including First Aid.
  • Plan carefully to avoid emergencies.
  • Find your work schedule that works for you. I work long & late; that does not mean you are required to do so. Whatever your choices about work schedules, be aware of its costs and benefits.

  • Discuss authorship expectations before embarking on a project.
  • You earn first authorship if you do most of the data collection, analysis, and writing.
  • You earn co-first-authorship if you and someone else either did equal amounts of work or each contributed most of different stages (collection, analysis, writing)
  • You earn co-authorship if you contribute essential effort to getting a substantial fraction of the data or writing the paper. There should be some distinct result or intellectual idea that you were the primary source for.
  • You must have read, understood, and approved any paper you are co-author on and be able to defend it.

The PI’s obligations to everyone in the lab:
  • My job is to help you achieve yourcareer and life goals, to the best of my ability.
  • Rapid feedback on ideas, manuscripts, etc.
  • Financial support for salary and research and travel to the extent I am able
  • Regular meeting to discuss science, and careers.
  • I write your recommendation letters. You can take this for granted, but please give me enough advanced warning.
  • I help you network with other scientists
  • We should discuss your aspirations, and realistic ways of realizing your goals.
  • Frank and constructive feedback on your science and career advancement.
  • Conflict resolution is my job. If people aren’t getting along, or something is wrong, talk to me.
  • I never ask about personal problems, because I don’t want to intrude. But, if there are issues at home, or especially with health (mental or otherwise) that are affecting your work, you are always free to talk to me.

Your obligations to the PI:
 Tell me when there is a problem, in the lab, with your data, or with other people.
  • Be independent to the extent you can, teaching yourself skills, solving problems. But, don’t get stuck doing this: talk to me before you are in a rut. Find a happy balance between independence and the preceding point.
  • Be creative and productive. That involves working efficiently, rather than super-long hours.
Obligations to yourself:  self-education
  • Attend seminars to learn what others are doing
  • Read science papers or books (almost) every day. If you don’t want to read extensively and intensively, then examine whether you are doing the kind of science that really engages you.
  • Keep a lab notebook with ideas, observations, and data.
  • Go to a conference & practice public speaking
  • Read about scientific ethics, philosophy of science, and history of science.
  • Learn to keep a budget of research expenses
  • Take time to read about personnel management
  • Set up literature auto-alerts

Obligations to yourself:  Data habits & repeatable science
  • Back up your data!!!!!!!
  • Everyone generating/analyzing data and papers should have a GitHub account or equivalent to share data, code, and text.
  • Write up Standard Operating Protocols (SOPs) for any commonly-used method so people who follow after you can replicate your methods exactly.

Obligations to yourself:  Self-care
  • None of the above are any good if you are too stressed or unhappy or depressed to benefit from them. Take care of your physical and mental well-being. That includes sleep, exercise, and activities that make you content.
  • If you are having difficulty with health (mental or otherwise), seek help.
  • You can talk to me about problems you are having so we can seek solutions together.
  • I have experience and some limited training in counseling people at risk of suicide, suffering from depression, or having experienced sexual harassment, so please don’t think that you can’t talk to me.

  • We will start you with a basic task to evaluate your reliability and dedication, then as we get a feel for your skills and interests we will start to talk with you about independent project ideas.
  • You should aspire to get co-authorship or even first authorship from your time in the lab.
  • Be punctual and reliable
  • Attend lab meeting to learn the gory details
  • Do some independent reading on the topic you are studying
  • Ask questions
  • Ask more questions
  • Keep copious notes in meetings and in lab.
  • Start to learn statistics, computation, and to embrace applied math

 You are the lynchpin of the lab, making sure core functions keep running.
  • Keep a daily lab notebook of what you do
  • Communicate regularly with me about what you should be doing next.
  • If you have down-time and aren’t sure what to do, ask me.
  • Ask questions & more questions

Graduate students:
  • Your PhD and career goals are yours, not mine. That means you should be self-motivated, and are responsible for your own research ideas.
  • Always ask yourself, “why is this interesting and important?” Be prepared to answer that.
  • Read more than you think you can. Your success is proportional to your mastery of the literature. You are a scholar training to be a world expert on a specific topic.
  • Know the history of the ideas you are studying. This includes reading the old classic papers, and reading theory. Become comfortable with the math in theory papers.
  • Study the natural history of some habitat or group of organisms.
  • Read some history & philosophy of science
  • Develop a thick skin. Your papers and grants will be rejected, and it will not always be kindly phrased. It happens to everyone, its not personal. The sooner you learn coping strategies, the happier you will be.
  • Just because someone says it won’t work doesn’t make them right.
  • Write regularly
  • Learn to code, and learn principles of reproducible code and data including database management and metadata.
  • Make a website
  • Meet with visiting speakers
  • Publish early and often, don’t wait till the end of your PhD
  • Master statistics
  • I encourage external collaboration. Talk to me about it first, though.

  • You are in the final stages of training to be a professor. What do you need to do/learn to succeed?
  • Have a website
  • Write a mock job application, and go over it with other people to both improve the text and identify weaknesses you need to fill before you go on the market.
  • Teach something
  • Get a grant
  • Learn about personnel management and budgeting.
  • I’m not so concerned about WHEN you work, as I am with output.
  • Go to conferences & network more than you feel comfortable doing.
  • I encourage external collaboration. Talk to me about it first, though.
  • Papers!!!!

Training resources for specific topics include:
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The ongoing impassioned debated about work-life balance recently reminded me of something a McGill Professor, Joe Rasmussen, send to me soon after my arrival at McGill. “I never work at work,” he said. By this what he meant was that “work” was writing research papers, and he never did that “at work” – meaning at McGill. Instead, while at McGill, he would simply talk to people and do other administrative tasks, meet with students, BS with colleagues, teach, and so on. As a brand new Professor with relatively few responsibilities at McGill and a young child at home, this flabbergasted me. McGill (“work”) was where I went to WORK – meaning write and think. Now, 17 years later, I find that – like Joe – I almost never work at work. Instead, the real work happens at home where I have plenty of peaceful quality time to think and write. When I go to “work” now, I mostly do those same things as Joe: teach, have meetings with students and colleagues, attend seminars, do administration, and so on. All of the real “work” happens at home in evenings after everyone else has gone to bed, or on weekend mornings when the kids are off at sports (while my wife visits her horse), or on those 1-2 days a week when I don’t book anything at work and so can stay home to do some work.

Image from here.
Perhaps this work-at-home time sounds like a recipe for an unhealthy “work-life” balance – the kind you hear criticized all the time on social media, with respect to both hyper-prolific scientists or, simply, everyone that is an academic. Yet I don’t think working at home means I work more. Sometimes I don’t even go in to work at all, and most days I schedule all my meetings during the middle of the day, so I can go to work later in the morning and leave earlier in the afternoon. So, presumably, to calculate how many hours I work, I would have to keep a closer accounting and sum up the time I spent at work and the time I spent working at home. Yet all of this begs the question “what is work”?

From work-life balance …

If you work Nine-to-Five at some job you don’t “bring home”, then I suppose the accounting is simple. When you were at work you are working – apart from formal coffee breaks and lunch hour. When you are at home, you were not working – you are “living.” The commuting time is a bit trickier, of course, because one could count it as work (because you wouldn’t do it if you didn’t work) or life (because you might read a book or watch a video or whatever on your way to work). Many jobs, however, aren’t Nine-to-Five because the work you do at work benefits from additional work you do at home – so people bring their work home and are now presumably advancing at work at the expense of their life. I certainly bring my work home, so perhaps I have this problem.

Yet I obviously don’t work all of the time at home, so I suppose I would need to count only the specific time I was working at home – and then add that on to my time at work. But that hardly sounds like a fair accounting given that – at work – sometimes I am not working. I might be taking a walk, or checking the news, or checking up on sports, or simply BSing with colleagues. Should that “life at work” be subtracted from the time I work at work? And what about the time I am “working” at home but, depending on the task, intermittently watching a comedy program or a new video by my favorite band, or whatever. Considering this mosaic work-life partitioning, the accounting gets pretty fine to the point of absurdity.

And what about when “work” and “life” overlap in the same activities. My work involves a lot of field work – and that is something I love doing. If I wasn’t “working” in Alaska or BC or Trinidad or Galapagos or Uganda or Chile or Argentina, I would be outside in the “field” anyway – and, without work, I would probably not be able to visit those places that I love to visit. So, do I count field work as “work” or “life”? (People I know outside of work often ask me if my latest destination was “work” or “holiday” and I always hesitate because nearly every trip is both in one way or other.) For me, then, field work for work IS life and how would I divide time between the two. And what about those activities at McGill that I really enjoying, like discussing ideas with students and colleagues, attending very cool seminars, and so on. Should these fun work activities count as work? The point of all of this “what if” postulation is that I think the traditional accounting of “work-life” balance is not helpful and we need a new way of thinking about balance – or, in fact, optimization.

… to Like-Hate Optimization.

I propose that instead of worrying about work-life balance, we should worry about maximizing time investment into activities that we enjoy – both at work and in life (which can be the same). With respect to work, I have some very clear duties that I do hate: making multiple choice exams, grading exams, dealing with students who are whining about their grades, filing in activity reports, preparing expense reports and travel advances (and then fixing and resubmitting them, and then fixing and resubmitting them yet again), checking/printing/signing/scanning/emailing financial reports, anything associated with Animal Use Protocols or collection permits, attending administrative meetings just because I am supposed to, and so on. I think we should stick these types of onerous – sometimes soul crushing –activities in a “things I hate” bin that we try to minimize without shirking our duties too much. 

At home, I also have a set of things I hate, such as vacuuming, washing floors, doing taxes, meeting with banks or financial planners, GOING TO THE DENTIST or doctor, waiting in lines or on hold, arguing with my family about anything, and so on. Of course, most of these things must be done, and so I will do them; but only because I have to do them. (Again, part of the reason is to avoid shirking responsibility that someone else in the family would then have to take up.) I suggest that all of these “things I hate”, whether at work or home should be in a single bin that we will seek to minimize.

The juxtaposed bin is then, of course, “things I like” both at work and at home. These things I like include doing things outside (field work, hiking, fishing, photography, climbing, diving, kayaking) and inside (lecturing, writing papers, climbing in a gym, attending awesome seminars, talking about science, reading about science or Middle Earth, watching movies about science or Middle Earth, reading to my kids, and so on). For this bin, I can sometimes make what amounts to extra time by creating an intersection between multiple activities: next week I am taking my students and kids in the field where we will do and talk about science while taking pictures and watching wildlife.

Cedar and Aspen helping with field work (and camping and hiking and wildlife watching and photography) in Haida Gwaii. My earlier post about "Work-Life Fusion".

Between the “things I hate” and the “thinks I like” bins is a intermediate bin of “things that are OK” but must be done either to minimize things I hate or maximize things I like. For me, we here have raking leaves or shoveling snow, writing research grants, sitting on planes or in cars, reviewing manuscripts for journals, attending boring seminars, etc. This bin can be viewed as the route by which we maximize the transition away from “things I hate” and into “things I like.”

Accounted for time in this new way, I would say that I have a great Like-Hate Optimization. Indeed, I suggest that many academics who would seem to have a bad Work-Life Balance do, in fact, have a good Like-Hate Optimization. Since much of my work overlaps with my personal interests – field work and reading and watching videos (every BBC Earth video – over and over) are good examples – much of what a cynic might call “work” is, for me, “life” – and I therefore like both. Moreover, some people just like to work: getting things done makes them feel good about themselves or puts them in a position to do other activities they might not otherwise be able to do. Who are we to gainsay them?

The key point I am trying to make is that tabulating hours of WORK per day, from which hours of LIFE are calculated by subtracting from 24, is not the right way to think about your activities. Instead, the right way is instead to think about how much of your time falls into the “Things I like” versus “Things I hate” versus “Things that are OK” bins. Then try to minimize things in the hate bin and maximize those in the like bin. There is no need to feel guilty (or to make others feel guilty) when they work a lot – as long as they like it.


Notes and caveats:

Of course, I am not saying that it is easy to achieve Like-Hate Optimization, just as it isn't easy to achieve Work-Life Balance. Sometimes the things you hate simply must take up a lot of time - and some people have more unpleasant responsibilities or constraints than others. I am simply saying that - when possible - we should seek - lives and jobs (BOTH) that we like; and, for a given life and job, we should seek - to the extent possible to spend more time doing the things that make us happy and less time doing the things that make us unhappy.

Also, it is sometimes (often?) the case that optimization isn't just an immediate concern. That is, long-term "like" optimization sometimes requires a bit more of the "hate" and "OK" stuff in the short term.
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By Steven Cooke


I am fortunate to deliver a fair number of research seminars at various institutions and in that capacity seem to find myself having lots of “pizza lunches” with grad students and post docs.  After hearing about what they are up to, it is inevitable that someone will ask me a question like this… “How can you publish so many papers - I can only assume that you don’t sleep?”  I also read the paper published on hyper-prolific scientific authors, and found it (especially the appendix) interesting and alarming.  Some of the most productive (in terms of paper output) researchers were very willing to share that they credit such productivity to getting little sleep and working virtually non-stop.  Having a large research group and other things like that fed into it too but in general one walked away with the idea that all of these individuals lacked any level of reasonable (a subjective term) work-life balance.  My concern is that such a message would be exactly what would be remembered by early career researchers and in doing so go down a similar path.  That was the basis for my tweet that has been variably considered to be an audacious humble brag, an entirely tone-deaf statement, or perhaps a genuine statement regarding the importance of work-life balance.  

Tired of people assuming that I don't sleep becuz our lab publishes 60+ papers/yr.  Guess what: reason our lab kicks butt is becuz we DO sleep & have balance in our lives. More time DOESN'T = > "productivity". Failed relationships, depression & crappy parenting is NOT success. pic.twitter.com/MWgYDzd4TR
— Steven J. Cooke (@SJC_fishy) January 27, 2019

Everyone can judge as they will but it was done with genuine hopes of dispelling the myth that the only way to “do more” is to “put in more time” and in doing so trade-off one’s health, wellness and relationships among other things.  A few tweets only gives one so much space to dig into what is surely more complex than what I initially tweeted and I am grateful to Andrew for giving me a platform to reflect on the last few weeks of twitter banter share a few more thoughts here.  Beyond the twittersphere, I have also engaged in extensive off-line discussion with friends and colleagues regarding these topics which I have found useful.  I think it is fair to say that my tweet generated more discussion than I could have imagined which I will take as not a pat on the back but rather an interest within our community to discuss a variety of topics I touched on in the tweet.  So – let’s keep the conversation going!

Andrew asked me to think about trade-offs – what am I trading off to achieve the “productivity” judged by paper output.  A few things about me…  I study fish and got into science because I loved fishing.  I continue to be an avid angler and thus there is an inherent blurring of work and pleasure.  I read fishing magazines for enjoyment but it also helps me to understand what is happening in the real world.  I go fishing for fun and almost always take a data book with me.  However, I also get to spend many days a year fishing for research and therefore, in effect, get paid to do so.  I can take my kids to work and hand them a fishing rod and they are in heaven (and I am collecting data; in this picture they are catching bluegill off our dock that we subsequently tagged as part of a spatial ecology study). 

My family is my life – I spend most of my spare time doing the things we all do – being a taxi driver, getting groceries, tidying the house, fixing things that are broken, cooking, and of course playing with my kids.  I don’t watch sports on TV and aside from the odd binge-watching session I don’t watch much TV at all.  My favourite hobby is cooking (which also is useful activity for feeding the family and my biggest creative outlet) and I also like running and cross-country skiing.  So – Back to what I am trading off…  Well, along with being active in research comes lots of travel and so I do spend significant time away from home.  I try to avoid being away over weekends and when I am away I work my butt off.  When colleagues at a meeting go on sightseeing tours I often pass and instead look forward to coming back with my family in the future.  So, I often sacrifice taking in all of the touristy sites on my work travels and would rather hunker down and get my “work” done so that when I get home I am fully present and engaged.  Admittedly, when at home (or wherever) I am a daydreamer so I could be playing with my kids and then suddenly have an idea for a project or paper that I have to jot down before I forget – but I suspect I am not alone. 

Having a big team does mean that I have to keep my eye on email when on vacation (to deal with safety issues, mental health issues, thesis roadblocks, etc.) but I also do an awful lot of vacationing where I combine work and play.  My wife is a teacher so we enjoy spending our summers together with our kids.  Cottage life means I get up and check emails in the morning, have a few phone calls with team members, and might do an hour of writing in the heat of the day when the kids nap or read.  That is my balance – rarely disconnecting totally but rather having extended summer holidays (2 months) but with the cost being a few hrs of work each day.  I consider that a win and love that type of balance.  Swimming, fishing, cooking, playing games, exploring the forest, exploring the shoreline, catching frogs… and a little bit of work.  Maybe I would be better off if I entirely disconnected but I would rather have most of the summer with family and have to spend some time each day dealing with essentials to keep the ship afloat. 

I am sure there are other things I trade-off subconsciously.  For example, I wish I had more time to troll the literature.  I do love finding and reading new material but my reading list is long so I am often forced to scan.  Relatedly, I wish I also had more time for “fun reading”.  The reality is that I spend so much time looking at a computer screen or paper (e.g., thesis, report, grant) that I don’t really like to stare at more pages at the end of the day.  I also wish I could spend more time in the field with my team. I think I am pretty decent at this (I refuse to accept the idea that I am only an administrator) but it is still difficult to live vicariously through my team.  I want to be there to help them – to experience new environments with them – to understand the cultural context for our work.  I am always a phone call away but wish I could still spend 100 days in the field as I did when I first joined the professoriate.  Realistically this has been more constrained by having kids than publishing a bunch of papers or having a big lab but nonetheless – is something I wish I had more time for.

As raised during twitter debates after my tweet, unequitable access to resources can underpin one’s ability to publish a high number of papers while having reasonable work-life balance.  All I can do here is humbly note that I am fortunate to have a lab that is well supported and won’t pretend that this is an easy issue to address.  I do my best to ensure that we celebrate outstanding scholars and don’t judge them solely on their number of papers.  I take this role seriously and make sure we focus on the full picture when thinking about tenure, promotion, hiring, awards and grantsmanship. 

In terms of context – I am in privileged position – I have an incredibly supportive and loving partner (who has her own professional career) – this is core to everything.  I should also add that we support each other – I work hard to minimize traveling during her report card writing periods.  We respect each other immensely and work as a team – a partnership.  I should be clear that one can also do it alone but I can imagine that there are different struggles, especially if a single parent.  I am also a tenured full professor with a Canada Research Chair (CRC) position such that my in-class teaching load is relatively small.  To be clear, it is not that I dislike teaching, but I don’t have to do much of it (that is the spirit of the positions).  So – I have more of my work time that I can devote to various aspects of research including writing and mentoring.  This privilege begets productivity and productivity reinforces privilege – a feedback that is certainly in itself worthy of further discussion. 

I also have an AMAZING team as I’m sure we all like to proclaim as mentors – dedicated learners and problem-solvers.  Their creativity and passion inspire me and I love nothing more than to celebrate their many achievements.  Over the years as a lab we have discussed whether we are too focused on publications but every time we conclude the papers are needed to formalize and share what we have done. However, we also recognize that publishing papers is insufficient if we are to influence others with our work.  For that reason we consider peer reviewed papers to be the foundation for #scicomm and even engage in research (with social science collaborators) about knowledge mobilization (see here). 

I am also incredibly fortunate that I work at an institution where it doesn’t ever feel like one has a “boss”.  I have never had an administrator sit me down and try to influence my research in any way (e.g., do more of X) nor have I done so with other faculty members when I have held academic leadership roles.  I am used to working in an environment where there is room for everyone to excel – whether it be in teaching, mentoring, outreach, service, research, etc.  Moreover, we celebrate people who are good at these things – not just those doing research.  We don’t have merit-based pay – we have a collective agreement guiding financial compensation with it simply being a function of time in the trenches (save any special retention packages if one has an offer from other institution).  I hear about the high pressure and toxic work environment experienced by colleagues at other institutions and it is foreign to me (again, a blessing).  There is so much mutual respect within my institution that we lift each other up and recognize that we are all different and give in different ways.  I am so proud of all of my colleagues and make it a habit to acknowledge and congratulate people who have done good things – especially things that do not have to do directly with research.  When I think of the real change-makers of our time, I don’t go to the people with the most papers, the most students, or the most citations – I go to the people who I think have the best idea and are accomplishing great things – whether in the classroom, in #scicomm, in research, and in knowledge application.

The “60+” papers led to the assumption that this was all output from my lab.  I did a quick look at the papers from last year and about half come from collaborations with researchers at other institutions and many of those do not involve my lab members.  When I reflect on how those collaborations came to be, it has often been over a shared approach to science – the ability to go from idea to paper without it getting derailed.  I think people that like to write (and I LOVE TO WRITE) end up attracting (or being attracted to) collaborators who also like to write.  Being an active and responsive collaborator is critical.  Too often it is assumed that collaboration is easy – a notion I disagree with.  There are a number of folks I only collaborate with once and others that become “regulars”.  The reasons for either outcome are varied but the ways I judge are 1) was it fun/stimulating; and 2) did we achieve something worthwhile (training a student, solving a problem, writing a paper, creating a website – whatever)?  It needs to be both or I am out! 

There is an assumption that with a big lab, one must not be able to give the same attention to trainees as someone with a small lab.  That may be true if time is a useful indicator of mentoring ability or quality.  The reality is that there are some small labs where the mentor is horrible and big labs where the mentor is excellent.  I will leave it to my peeps to weigh in re the quality of the mentoring I provide but I will comment on my approach.  It is very personalized – some students have no interest in sitting down together for a 1 hour formal meeting once per week and reach out as needed.  Some reach out when they hit a wall and that may be on a Sunday evening.  By understanding individual learning styles, motivations, and other quirks (some need carrot, some need stick) I can customize the mentoring to their needs.  I will also add that I am not the only mentor or supporter in the lab.  Encouraging team members to share, collaborate and socialize is a great recipe for creating a broader support structure for all team members.  Mentoring of big teams could easily be an entire blog so I am going to stop there! 

My thoughts on “productivity” have been greatly influenced by Chris Bailey and I hope you check him out at A Life of Productivity Chris graduated with a business and marketing degree from my institution (I have never met him) a few years ago and took one “off” year post graduation to conduct a series of experiments on himself to understand what factors influenced his productivity (called “A year of productivity”).  The idea has since morphed and grown into “A life of productivity” and Chris now coaches others on how to be more productive.  I routinely visit his website and find myself nodding my head in agreement with everything I read. 

One of my favourite posts is one where he summarizes the top 10 things he took away from his year of productivity (here).  In particular, I fixated on Tip # 9 which he calls “boring” and I call “life-changing”.   Quoting Chris, “Over the last year I experimented with integrating countless habits and productivity techniques into my life, but at the end of the day, the three productivity techniques that worked the best for me were: Eating well; Getting enough sleep; Exercising.”  And there you have it.  I do my very best to do all of those things.  When I don’t, things fall apart at work AND at home.  This is something that I have experienced in very real ways during my studies and career yet it really only gelled and became one of my “mantra’s” upon following Chris.  I will note that Tip #9 does not say that one has to have balance in other ways (e.g., maintaining positive relationships with family and friends) so it needs to be merged with ones like his Tip #4 where he describes how working too much or too hard will shatter productivity.  My life is such that when I do have time to write or think I have to have laser focus and be productive in that time, so I very much subscribe to the notion of working smart, not long.  For what it is worth, post-kiddos this has really become a truth! 

His tip #1 is a doozie – one I think we all need to consider. That tip states that “Productivity isn’t about how much you produce, it’s about how much you accomplish”.  I can’t think of a more meaningful statement and in fact this mirrors some of my own thinking in a paper in which  a colleague and I wrote about abandoning the quantity-quality debate regarding publications and instead think about “influence”.  I work along the entirety of the fundamental-applied spectrum and I train problem-solvers.  Sure,  I am proud of the work we produce and share but I am more proud of the influence that the research has had.  I fully subscribe to the idea that we need science that is blue-sky/discovery/fundamental which may or may not lead to tangible “applications”.  However, I am an applied ecologist so if I am pretending to do applied work, it better be relevant to end users.  This comes full circle in terms of how we “assess” each other.  Our assessment tools for research “productivity” are flawed and focused largely on the quantity-quality issues with it being difficult and uncommon to consider broader impact (or using Chris’s working – accomplishments).  

Here are a few other “tips” to complement those provided by Andrew (How To Be Productive) and Chris Bailey.  For the purposes of this discussion I am using “writing output” (papers or grants) as the measure of productivity which is solely to provide more focus to the tips but fully recognize the flaws in doing so.

Don’t force it.  If you are not in the mood to write, forcing it will rarely be fruitful.  Of course, you can’t put off writing that thesis or grant application forever but just because you identified a window of time to do writing doesn’t mean that will be an effective use of that time. 

Don’t spend too much time AT work (and find your writing zen spot).  The more time I spend on campus, the more behind I get with my work.  I obviously need and want to be there for interactions with my team members and colleagues.  To that end, I use my time on campus to interact with people.   Writing (even collaborative papers and grants) is an individual activity and for me I can’t do so on campus.  I bet I have not written 100 words of a paper or proposal on campus in the last decade.  I do edit the work of others while “at” work but I do not write.  My zen spots include a favourite chair at home, airplanes, early mornings at the cottage in the summer, and the back corner of a wine bar or pub (writing from a riverside pub during trip to Australia in fall 2018 depicted in photo).

Beat to your own drum. What works for Andrew and I may not work for you.  Don’t compare yourself to others.  Do great science.  Share your work.  Figure out what you love to do.  I have sat on enough hiring committees and grant selection panels to know that there is no formula to success and no simple or singular way to measure or assess productivity.  Yes, some people will count papers and look at impact factor, but what I see is efforts focused on scholars doing great stuff – not just writing papers, not just teaching, not just outreach (etc.) – some balance and combination of the above.   What I do see is that people with piles of papers and nothing else not ending up with interviews (at least for academic positions).  Maybe this is influenced by the amazingly positive work environment I have at my institution but I have also seen the same play out elsewhere.  It is about the intangible “fit” and it is about WAY more than papers.  I also would like to think we are in an era where hiring committees are looking for people with a semblance of work-life balance to serve as role models for their mentees. 


Each January I start the new year with sending an email to my team with some personal reflections on the year-gone-by and the year ahead.  Here are a few excerpts which highlight well the trade-offs I consider sufficiently worthy to discuss with the team.

(Sent January 4 2018 – I cut out the first part where I gush about their passion and accomplishments).

… As time goes on I think of myself more as “the synthesizer” – I take what you do, and work done by the broader learned community, and try to weave it together with some of my own creative juices into a meaningful story (sometimes with lessons for others…).  I also find that through time I am learning MORE from you than I did when I first started out as a prof.  I suspect this is for several reasons – one being that we now have the financial resources to be able to stray more widely from my “core”.  I also suspect that as I age and take on more leadership roles (plus family duties – I am now officially a hockey, gymnastics and x-country ski taxi driver) and have a larger lab that I am not there for as much of the day to day of field research (early on I was). This is something I struggle with – especially because I LOVE field work so much.  But – this is also a natural progression which I know has occurred with all of my mentors (Dave Philipp is an obvious exception as he is doing more field work that most of you and he is in his 70s…).  Although I can’t be as hands on, I do need to be accessible to you and this year I endeavour to do a better job of keeping up with all of your field activities through VERY regular calls even if I can’t be there.  There have been a few field projects that have gone sideways over the last few years and that is on me for not providing sufficient support (which might mean a more senior field person to assist).  I look forward to ongoing conversations re how I can BEST support YOU!

One area of improvement I am looking for as a lab (me included) is to be less last minute…  We seem to always be making a dash to the finish line – whether it be a thesis, a conference presentation, a scholarship application, a letter of reference, etc…  I would like all of us to do a better job of looking ahead and planning so that we can reduce the stress that comes with having things pushed up against deadlines.  You will see more pokes and prods from me (especially for students re thesis progress)  this coming year.  From experience I can assure you that there is nothing more stressful than having to write an entire thesis under the gun.  I also think we need to do this to be fair to our partners – especially the great adjunct profs and collabs who support us.  They should not have to suffer because we are throwing things at them last minute.  So – this is both for your personal sanity but ALSO as a courtesy and out of respect for our collaborators. 


FINALLY - I will end with a tweet from one of my favourite..
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A kerfuffle recently broke out – as kerfuffle's often do – on social media when fisheries scientist Steve Cooke tweeted about how high productivity was not mutually exclusive with a happy and healthy family life. The tweet was an indirect response to the recent analysis by Nature regarding “hyper-prolific scientists” and how they were so – and whether they should be so. Steve is without question a hyper-prolific scientist in his field, publishing 60+ papers per year. His basic point in the tweet was that his hyper-productivity did not mean he was somehow a bad parent or didn’t have proper work-life balance.

Tired of people assuming that I don't sleep becuz our lab publishes 60+ papers/yr.  Guess what: reason our lab kicks butt is becuz we DO sleep & have balance in our lives. More time DOESN'T = > "productivity". Failed relationships, depression & crappy parenting is NOT success. pic.twitter.com/MWgYDzd4TR
— Steven J. Cooke (@SJC_fishy) January 27, 2019
Tired of people assuming that I don't sleep becuz I tweet 350+ popgengoogles/yr.  Guess what: reason this account kicks butt is becuz i DON'T do any actual work and just think up dumb popgen jokes all day.
— PopGenGoogling (@popgengoogling) February 2, 2019

Twitter was outraged (or entertained) in various ways, with some saying a tradeoff must be present somewhere (maybe he is a bad supervisor) and others saying that perhaps a tradeoff wasn’t evident because Steve was just “better” and the rest of us shouldn’t strive to be hyper-productive because, even if Steve could do it, the rest of us couldn’t and shouldn’t. These two criticisms basically boiled down to the classic arguments about tradeoffs in the evolutionary literature: either they must exist (put more effort into reproduction and you can’t live longer) or they don’t exist because individuals vary in “quality” (some individuals have more energy and so can put more effort into reproduction AND live longer). Theoretical and empirical studies have variously supported both ideas.

High variation in quality among individuals (top) makes the otherwise tradeoff (bottom) disappear. From Reznick et al. 2000 TREE 

This post will not be an effort to explain Steve in one way or the other. Different people work in different ways and whatever is working for Steve is great for him. Whatever works for other people is great for them. Rather, my hope will be to help people who consciously want to be more productive without a greater time investment (don’t sacrifice your work-life balance). Given that each of us inherently works differently, a first important question might be “is it possible for advice from someone to actually make someone else more productive?” My first response might have been “no – it is mostly just intrinsic (over or under) confidence or intrinsic metabolic rate or the type of science or whatever that makes the difference.” But then this response would immediately be checked by the realization that I have received advice in the past that was, in fact, helpful with regard to productivity. Hence, I will attempt some bits of advice that might help some folks (who want to be) to be more productive – without implying that productivity is necessarily a good thing or a thing that one should attempt to maximize. (In fact, I am really encouraged by the stories surrounding how Ghent University in Belgium will entirely change its faculty evaluation system.)

The Leung Principle
Some years ago, I ran into a colleague, Brian Leung, outside my building. I asked if he was going to that day’s meeting on “something or other.” He said “no.” I was surprised, responding “But aren’t you a part of that initiative.” “Yes,” Brian said, “but I divide tasks into things that will proceed without my input versus things that require my input to proceed. I do the latter first.”* I see considerable merit in this philosoph-practical division. Sometimes meetings are called just because meetings are perceived to be important. Sometimes comments are requested just out of courtesy. There really isn’t any need for you to be there. Don’t spend massive amounts of time on things that don’t require your help AT THE EXPENSE of things that do require your help.
  • * From Brian: "ha ha. I remember that. At the time, a few loud voices were trying to do stupid things at [removed to protect the guilty]"

Don’t be the bottleneck
In any collaborative project, there is always that one (or two or more) people that hold everything up. Don’t be that person. If you are a grad student, send that paper to your advisor even if isn’t perfect. If you are leading a paper, send it coauthors early on. And, if coauthors send you a paper, read it right away (I sometimes fail here) and get it back to them. Don’t be the bottleneck.

The bottleneck? Image from here

Maximize the effort-to-payoff function
In any project, the curve for effort-to-payoff is not linear. Often, the payoff is an asymptotic function. That is, an increase in effort early on leads to massive improvements but the same increase in effort later provides only marginal rewards. Don’t let the perfect be the enemy of the good! Realize when hammering your head against a problem or a manuscript is not going to lead to large payoffs – and send it to a collaborator or submit it for reviewer feedback. Get it off your desk. 

Prioritize the high-payoff projects.
First-authored papers are much more important than co-authored papers. Thus, make sure to put your maximal effort into first-authored papers. For collaborative projects, sure, “don’t be the bottleneck” but at the same time don’t put massive amounts of effort into a collaboration AT THE EXPENSE of first authored papers. And write a review paper or two – they are easier to write, they are easier to publish, they are higher cited, and they help you place your empirical work in a theoretical (or simply broader) context.

Just don’t do it
Academia is a crowded mix of competing tasks – but only some help you to be productive. Learn to (respectfully) say no to very time consuming administrative tasks, unless administration is what you want to do – or unless that administration will substantially enrich the research or teaching potential of your unit. Don’t organize every graduate student event. Don’t volunteer for every departmental committee. I realize it can be hard to say no when there is a power imbalance, such as when your supervisor asks you to do something. However, my experience is that most supervisor are quite responsive to well-reasoned and respectful denials to do some requested task or other; as they also often are to a general discussion about being over committed. 

Study something you like
If you don't like your research, you won't like doing it and you will be less productive. Don't do a project you don't like. If you aren't excited about your project, change it. Or, if you absolutely must do it, spend your free time (or your even working time) planning that cool new project you will do next. Personally, this strategy is one way that I manage work-life balance - my field research often involves my family and my personal time is also in the field (hiking, fishing, photography). I know that this approach is also part of Steve Cooke's strategy: he studies fish and he loves to fish. Work-life fusion, if you will. 

Aspen and Cedar collaborating with me on research.

Serial multi-task
By serial, I don’t mean do many things at the same time – unless that works for you. What I mean by serial is that, if you have multiple projects on the go, try to stay on the maximal effort-to-payoff area of the function. If one project is slowing, send it to coauthors, and work on the other projects. If one project looks like it will have a higher payoff overall (first authored papers), then work on that first.

Do something else
If you just can’t stomach working on that damn paper again, then you won’t do a good job and you won’t be efficient. Do something else. I haven’t written a blog recently because I just wasn’t in the mood. But tonight, the muse struck me and now I have cranked this out in short order (hence the typos) – because it was where my brain was happy at that moment. If you simply can’t work on that manuscript anymore; hell, answer those pesky emails, enter those data that must be entered, read that paper your advisor mentioned, write that research blog. But, when productively procrastinating like this, do things that you were going to have to do later anyway.

Or just do it
All of the above advice goes out the window when you absolutely must do something now – even if you don’t like it, even if is low payoff, even if, etc.  In such cases, just do it, dammit. It doesn’t have to be perfect. It just has to be done – then you can go on to what you want.

Drink less
Czech ornithologists that drink more beer publish less. Are the rest of us any different from Czech ornithologists?

From Grim 2008 in Oikos

Drink more
Some of the most inspiring and productive academic moments I have had were over drinks.

With Brian Langerhans and Katie Peichel
Dan Bolnick, me, Katie Peichel (again), and Rowan Barrett.

Fuck it
Go for a walk. Binge watch Game of Thrones. Read a book. Go to the climbing gym. Play guitar. Cuddle the cat (or dog). Play with the kids. Do the weekly ironing. These mental breaks will make you more efficient when you get back to work.

Sam working on his thesis.


Then again
Many of the above suggestions might seem like encouragement to be selfish. In some small way, they are. If you are to be productive – and if that is what you want to be – then some degree of selfishness is necessary. Otherwise, you will spend all of your time helping others and not be productive yourself. That is fine, if that is what makes you happy. Go for it. But – if you are striving to be more productive – then you have to focus on your own productive work.

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- by Dan Bolnick

It has been claimed (including on this blog site), that to get your academic job you may need to be flexible about where you live. See, for example:

Faculty jobs are few and far between, and you take what you can get. Postdocs even more so. The result is that academics move around a lot. As a kid of an academic (my father was an economics professor who sometimes went off to consulting for US AID), we lived in North Carolina, Washington DC, Jakarta Indonesia, North Carolina again, north of Boston, then Lusaka Zambia, all before I went off to college and missed my parent's sojurns in Lilongwe, Maputo (where my dad is working at this very moment on a short-term post-retirement assignment), Fairfax Virginia, and Harare, before they moved back to Massachusetts. Since leaving the nest, I moved a few times too: from Zambia to Massachusetts for college, to Tanzania for Peace Corps, to California for grad school (I did my brief postdoc at UC Davis also, so didn't move), then Austin Texas, and now just recently Connecticut. 

Moving does many things, among them separating you from family and from friends. From your support network. I've lived either on a different continent than my parents, or >1/2 way across the continent from my parents, since I left for college in 1992.  I like my parents a lot, and enjoy seeing them, but the consequences of this mobile life only really began to sink in when my wife and I had kids. Sometimes, you just need family around. Hilary Clinton famously wrote that "it takes a village to raise a child". Usually that village is your extended family. Moving leaves the village behind. That's not a reason not to move, but it is a cost. The solution: find your village, in some form. 

This post is about a time when having the village around made a difference. Not a life or death difference, to be sure. The hurdle here is minor, but real. It is a tale of dual careers, work-life (im)balance, moving and family, and the compromises we choose to make.  It is also a glass-half-full or half-empty story. You can see this as a story of why academic life is complicated, but to be fair the following story would have been at least as challenging had it involved another kind of job. I see it as a story of why academic life is wonderfully flexible... but still benefits from help.

When we lived in Texas, our nearest family was an 8 hour drive away, my own parents a half continent away. Moving to Connecticut was partly about pursuing an environment I want to live in (fall, snow, better hiking access, etc), and partly about being closer to family. My in-laws moved from Oklahoma to join us, and my parents are an hour and 3/4 drive away. Close enough (because they are retired) to drop what they are doing and come to our rescue. In return, as they age, I'll be close enough (as an only child) to return the favor. So now, for the first time as a parent of a 10- and 7-yr old, my wife and I have family right here. Its very nice, it turns out. 

Here's how that played out, in practice. My wife was away at a working group meeting in coastal Georgia, playing with lemurs on an island. And simultaneously I had scheduled to have a prospective PhD  student visit. So normally in Texas I just wouldn't do this, because I can't take care of my kids and host a prospective properly at the same time. Here, we went ahead because my in-laws could meet the kids after school, take them to dinner then a magic show in town, then home to bed around when I got home from dinner with my lab group. That's the plan. Simple enough.

This week started bad: Kid1 got the flu.  Then I did. But we had our flu shots, and the fever passed within 1-2 days and we were fine. Okay, all systems go for the prospective visit (albeit with lots of hand santizer on my part). But then Friday morning one in-law is down with the fever also. Questionable whether they can get the kids in the afternoon. At the same time, I'm on my way to get my prospective student but her plane is delayed, which squeezes my intended morning meeting with her down to just a late lunch. Would I even have time to get her to campus and get back home to meet the kids?  Then the other in-law decides he can leave his sick spouse alone okay, and watch my kids. Okay, all systems go. I get the prospective student, we have a great lunch conversation,  then I drop her off with others for some meetings on campus. We'll have more time to talk at dinner. That's when I got the phone call: kid2 isn't feeling well. 

Here's where I start thinking, is it fair to leave a healthy in-law with a flu-ridden child? Probably not. Which means sprinting home and abandoning my prospective student who spent ages in airports & planes to visit. Not a good choice.  *** to be clear, this isn't a disaster scenario, nobody's life is at risk, it's just... suboptimal ****.    Then kid2 perks up, says she's okay for dinner and the magic show. No fever apparently.  All systems go.

I stay on campus for dinner with my lab. We have a good time, good food and conversation. Then I head home, to find kid2 running a fever. 

Here's where things stood: I was now home alone with a flu-ridden kid, my wife is away. And the next morning there's the departmental grad student symposium. My prospective student will be there, and we were hoping to have some more time to talk specifics of research directions. I really should show up, it'd be bad form to miss my first EEB UConn grad student symposium, and to leave my prospective student hanging. But... sick kid and spouse away.

My mom comes to the rescue: she drives down and is here at 9 AM Saturday morning, with lots of hand sanitizer, a face shield for herself and kid2, and a risk-accepting attitude. By 11 AM I'm in the car off to the department symposium. And I have fun talking with colleagues, hearing talks, and a great 2 hour conversation with the prospective student.

Kid2 is still recovering today (Monday) at home. My mom is still here watching her, and my wife returns home this evening. I wouldn't have been able to come to campus today without my mom's help. 

So that's the story. Nothing really epic or horrible. I know people whose kids have cancer, or whose parents are ailing, who face much more serious conflicts, often without the parental support network. Really, this is a story of privilege.  I am privileged that my kids have 4 grandparents, two living in the same town and 2 less than two hours away, all retired but healthy enough to be available. That privilege isn't accidental, we uprooted our family across the country to get it. But the benefit is real.

I want to be clear here that this isn't the only solution: you don't have to live near family to make it in academia. I mean, I went 10 years as a dual-academic-couple-with-kids in Texas, and we managed. Where there's a will, there's a way. You find your support network, you make your local village however you need to. But it is absolutely true that academics move, and when we move we make compromises between the many costs and benefits that we wish to have in our lives. 

If I didn't have the multi-layered support network, this would have played out very differently... because one set of in-laws got hit with the flu, I used two layers of safety net in dealing with my spouse being out of town and having a work commitment.  Had I lacked one or both safety nets, it would have been okay-ish.  Okay, in the sense that I could have told the visiting prospective student: sorry, I've got a sick kid. I know you flew all this way. I know I spent $300 for you to visit. But I can't do this today.  The result would have been disappointing for us both, a bit expensive for me. She might have decided this wasn't a place to come for grad studies, changing her life path and my own lab group.  But in the end, it can still be okay. So my final lesson is that although work-life balance can be challenging, and sometimes events happen that destabilize a balance you thought you had figured out, overall our line of work gives us great latitude to make on-the-fly adjustments to our schedules. Sick kid so I need to work at home? Okay, can do. A few emails to rearrange meetings, and its done. There are many careers where that is far, far harder.  

So see this story as a glass half full one: academia is a career path where work-life balance is a challenge, as it is in every career. But it comes with great flexibility. That said, if you can live near family... it helps.
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