Tuesday, July 31, 2018

Should I be proud of my h index?



My daughter has a hoodie that says: “Don’t let the number of likes define your art”. The basic point, of course, is that quantitative measures of popularity are not how a person’s work should be valued by others – nor especially by that person. Rather, it should be the quality of the work that person produces or – more fundamentally – the quality of the character of the person. Thus, the large number of followers that the Kardashians, or some Instagram star or Youtuber, has should not be used to evaluate how creative, intelligent, or innovative the person is – or how good of a person they are.

In academia, the same concerns arise because the formal or informal valuation of a person’s research, and therefore that person as a scientist or even as a person, is sometimes tied to quantitative metrics not so different from the “number of likes” or the “number of followers.” Of particular significance are the number of papers we publish, the number of citations they receive, and – together – the h index they generate. The immediate motivation in using these sorts of metrics for evaluation is that they provide an objective way of comparing different academics, at least within a discipline, to thereby determine their relative worthiness for grants or promotions or endowed chairs or raises. The broader hope, of course, is that the same metrics reflect not only the quantity of research but also its quality.

Recently, these social media and academic quantifiers of success and influence have converged in the consideration of the number of followers that a given academic has on twitter or Instagram or youtube or whatever. And papers now receive an "Altmetric" score reflecting its social media attention. This convergence has led some to propose a “Kardashian index” (or k-index) measuring the extent to which the social media profile of a scientist (their followers on twitter) is an outlier with respect to their academic profile (their total number of citations).


This frequent use of quantitative metrics of influence for evaluation has received many criticisms – but the most important is that volume (papers) and popularity (citations) do not reflect the quality of a person’s work. Instead, they can mostly reflect an individual’s effectiveness in self-promotion, most obviously in the form of self-citation. (See my blog post on the “Narcissist index” or N index.) Or they could reflect the tendency of that person to write review papers, which tend to be more highly cited. (See my blog post on “What if all my papers were reviews.”) Or they could largely reflect the discipline in which a scientist works (See Dan Bolnick's companion post on "Do certain subdisciplines lead to a higher H index".) The main argument is that quality is instead a more subjective evaluation achievable only by reading the person’s work and qualitatively placing it in the context of other work in the field.


These criticisms of quantitative metrics of influence in academia are so frequent and strong that it makes one wonder “should I be proud of my h index?” For instance, I can see that – in the not-too-distant future – I will have 200 papers, 20 000 citations, an h index of 100, 5000 followers on twitter, 1 000 000 views of this blog, and 250,000 views on Youtube. Should I be proud of these numbers? Should I report them in grant proposals? Should I be embarrassed to enumerate them in this blog post? The truth is, I don’t know. I have mixed feelings about it. I am proud to see that my hard work and talent for self-promotion has translated into a substantial visibility in my field and also effective communication of science to a broader audience. At the same time, I recognize that these numbers are not necessarily an indicator of the quality of my work, as they would undoubtedly be lower for someone who wrote fewer reviews, did less self-citation, joined fewer perspective papers, took fewer students and put their name of fewer of their student’s papers, and so on.

So perhaps, as I tell my daughter, her shirt might be modified to say: “Don’t let the number of likes define your art … unless maybe you have a lot of likes.” (Of course, “define” is not the optimal word either.) Maybe, in this sense, it is defensible to be proud of my quantitative numbers simply for their own sake, while recognizing that they reflect little more than the fact that they are high numbers. Stated another way, having a lot of citations and a high h index should not be a scientific goal but rather a communication goal. From this perspective, it is reasonable to appreciate and reward someone with a high h index or many twitter followers, without any sort of judgement being placed on someone with lower numbers. Many exceptional scientists who are influencing their field do not have a high h-index – but that does not make they any less important or any less of a scientist.

I encourage everyone to consider social media presence and citation rates and so on as indicators of nothing more than social media presence and citation rates. If you value such things for themselves, great – be proud of them – but realize that those numbers don’t necessarily reflect anything else. If your goal is to have high numbers, then – yes – write lots of papers, take lots of students, and write lots of review papers. If your goal is to be a good scientist; by all means do those same things if they lead you to do good work – but not if they detract from the quality of your work. And, most importantly, don’t let the pursuit of papers and citations stop you from being a good colleague, collaborator, and person. And, most of all, never let any of this come in the way of family and the things you value as a high quality of life.

Don’t let your h index define your science … but you can be proud of it nonetheless.


Friday, July 20, 2018

Some thoughts on the ownership of ideas starting from an evolutionary ecology paper


Five years ago, I landed in Montréal for a PhD in the Faculty of Education, bringing with me my experience from the Greek rendition of environmental education. During my first term at McGill, I discovered that I was allowed to enroll in any graduate course (was this a glitch in the system?), so I registered to a graduate course taught by Andrew Hendry under the name Advanced Evolutionary Ecology. The course went well except from some awkward moments like the day when I took off my wet shoes in Andrew’s office during lecture time -- I was caught unprepared by the speed with which winter had succeeded fall at the McGill downtown campus.

Nevertheless, those days were intellectually rewarding and full of new ideas. One day in that course, I sensed the scholarly need to expand the concept of the adaptive landscape in order to incorporate environmental change, and I thought that I have found a way to do that. Soon, I presented the idea to the class, got an A for the course, and Andrew encouraged me to work on the idea and gave me a couple of literature suggestions to explore. I didn’t really understand why why I needed to keep reading. For all I knew it sounded like an interesting idea that once laid out, it would receive its criticism and people could just decide whether it was useful or not. Nevertheless, I complied and did my homework. After a while, I returned to the professor and declared: I checked the literature, I’ve found nothing like it. The idea was apparently mine and we ought to spread the word. The sage professor responded with a couple of sibyllic words. He said something like: I don’t think the idea is yours, but even if it is, people will take offence in you claiming this. In any case, he continued to encourage me to learn more on the topic and seek reviews from specialists on the field. Hence, I got some pleasing reviews from renowned Swedish professors, including Erik Svensson from Uppsala University who commented that “My initial attitude was not to expect much new, given that so much has already been written about this topic. However, what I found, after reading through the MS was a creative paper where the author has clearly worked hard to “think out of the box”, and has – to some extent – been able to think along new lines.” He also suggested the paper be revised and rewritten in a more ‘scientific’ way.

These were good news but the problem was I didn’t really know how to write a scientific paper since I wasn’t even a scientist. At that point, I asked from classmate and Andrew’s PhD student, Victor Frankel, to help me out. Luckily, he accepted and he did help me rewrite the paper in a more scientific fashion. As we were ready to submit (already 3 ½ years after the initial draft), Victor decided to send our paper to Ben Haller asking for a review. Indeed, Ben studied the paper and sent it back to us with ample feedback: his comments were knowledgeable, specific, and incisive. I thought I had learned to appreciate hard criticism by then, but when I saw Ben’s comments on one of our diagrams, I thought that it went too far: “It is striking just how much this looks like one of the diagrams in Simpson 1944. I would say the conceptual model you’re presenting here goes back at least that far”, and “This doesn’t even feel like sufficient credit to him [Simpson] though, given his actual figure that I mentioned above, which is virtually identical to your 5b in all important details.” Now, that does it, I thought. I dropped everything else and went straight to the Schulich Library looking for the single copy of the 1944 Tempo and Mode in Evolution by George Gaylord Simpson trying to see what he was talking about. As I browsed the book in disbelief, I was sure that Ben (whom I had never met) recalled an irrelevant part of the book and was just trying to be mean. But it turned out that Ben was right. There it was: In a short passage accompanied by a diagram in the old book, Gaylord Simpson was proposing an environmental expansion of his ‘selection landscape’. The terminology in the book was very different than ours, the axes in the graph were inversely placed, and the whole perspective was unlike ours, but the central idea was virtually the same. So, it turned out that our ‘new’ idea was outdated by 70 years, it was already proposed by one of the founders of the adaptive landscape. In the following moments, my thoughts went down a twisted and sinister path. Gaylord is long dead, I thought, his book isn’t online, so maybe I could travel, find the few remaining copies at the world’s libraries, and tear out that single page. My instantaneous impulse was to destroy this fragment of knowledge that deprived me of the paternity of my idea. My reaction was absurd, but this instantané helped me understand something about myself and how I was taken over by ambition, thinking that it wouldn’t do much harm to steal away a late man’s credit. A fault confessed is half redressed, as they say.

So, as it turned out, my original idea was not original at all. Interestingly enough, this revelation didn’t have a great impact on the paper itself. The paper was still publishable, yet we ought to give to Simpson more credit than we already did and explain that our paper was actually a revisit to his original ideas. It turns out that people rediscover ideas and methods all the time, and there is always room for updated renditions of old ideas. The bulk of intellectual progress comes from the translation, rendition, application, and interpretation of old ideas. However, that did not answer the question: Why on earth did no one return to this particular idea, even though Simpson’s 1944 book was so widely read and referenced? The feedback we got for the eco-evolutionary expansion showed that there was an actual need for such a method. My explanation is that Simpson was way ahead of his time, trying to sow a seed in a field that did not exist back then. In 1944, an overlap or convergence between ecology and evolution was nowhere to be seen; ecology did not even exist as a field. Today, the niche between evo and eco is no longer an epistemological terra incognita. The science has progressed since then, and a number of scholars are pioneering the synthesis between eco and evo. Exposed to the teaching and writings of these scholars, basically Andrew Hendry’s, we rediscovered the eco-phenotypic landscape in response to the need for a representation that brings ecology closer to evolution. In this process, nothing is really created ex nihilo. Our teachers were in turn influenced by their teachers, and carry on their set of ideas and problematics from generation to generation. However, save Ben and a few historians of science, we usually don’t read the old stuff all too carefully. We sometimes rely on secondary sources, or trust more modern renditions of the classic literature, because these are closer to the contemporary needs and scientific ethos. Yet, information is lost in this conveyor belt.

On a personal level, this has been a humbling experience. I now see the self-indulgence in thinking I was able to produce original ideas. Not that it’s impossible to produce new ideas, especially when you are newcomer in a field. It’s just that, when a problem was standing out there for enough time, most probably someone else has solved it before you even knew. This is just because so many intelligent people have been thinking on the same problems, for such a long time. To cut to the chase, it’s hard to have new ideas in an old world. So, yes, it is imperative to scrutinize the literature before making any claims. It’s also a good idea to moderate any claims one decides to make. At the same time, these humbling realizations just meant that my education was working. Authentic education can’t be about inflating our egos. Conversely, the process of learning, of taking stock of the volume of knowledge accumulated over the ages, is meant to be a humbling experience.

All these have also given me an idea about how science works. I do no longer believe that ideas can be owned. Instead, we are more like hosts of ideas, which seem to be having a life of their own, jumping from mind to mind. Ideas are sometimes transmitted in dormant states, following their own life cycles, in many cases outliving us. Dawkins has effectively described this process in his memes metaphor. As individuals, do we get something out of this? What is our drive for contributing to the body of knowledge? According to Lonnie Aarssen, editor of Ideas in Ecology and Evolution, we are driven by an “attraction to delusions of being able to project an ‘extension of self’—a memetic legacy—into the indefinite future” (Aarssen 2017). 

Following is a link to the paper itself, an extract from the paper discussing sympatric speciation, and a part on heterosis that we took out of the final text since one of the reviewers found it problematic. We did not have the courage or time to rewrite the part on heterosis, but there might be some value in sharing it, as indicated by Ben Haller’s comments below. Many thanks to Ben for allowing us to share his feedback.

 




Figure 2. A qualitative representation of Bergman’s rule on the unconstrained adaptive landscape (individual fitness peaks shift under the influence of environmental change).

Figure 3. A qualitative representation of Bergman’s rule in an eco-phenotypic landscape. It is important to note that the phenotype of the population (represented as the horizontal axis in this landscape) can shift in response to change in the environmental dimension (vertical axis) that drives the strength of natural selection. On the diagram, organisms will follow an upward-left movement for rising climatic temperatures (leading to smaller body sizes), and a downward-right movement for falling climatic temperatures (leading to larger body sizes).

A mechanism for sympatric speciation
This section uses the eco-phenotypic landscape to describe a speciation model within a continuous population distribution. Numerous studies have noted gene flow as an obstacle to speciation (Kirkpatrick and Barton 1997, Rousset 2000, Hendry et al. 2009, Berner et al. 2009). Until recently, the potential of divergent selection to induce speciation in the presence of active gene flow was hotly debated. Contemporary biology holds that speciation can indeed occur in the presence of extensive gene flow between continuous, interbreeding populations as long as the drivers of disruptive selection are strong enough (Dieckmann and Doebeli 1999, Leblois et al. 2003, Benkman 2003, Rueffler et al. 2006, Rova and Björklund 2012).

In the scenario that follows, changing environmental conditions expose a population to strong divergent selection that leads to speciation. Initially, the population occupies the left lobe optimum of Figure 5a, at temperature T1. The dissection of the three-dimensional eco-phenotypic surface along four temperature values (Figure 5a) produces a set of two-dimensional fitness graphs (Figure 5b). Figures 5bI to 5bIV present the chronological order of the speciation scenario. In Figure 5bI, the peak in color represents the phenotypic distribution of the initial population; the other two fitness peaks are vacant. A series of cold winters forces the population to undergo adaptive change (Figure 5bII, 5bIII) that leads to the evolutionary bottleneck of 5bIV (T4). After that point, a climatic rebound to warmer temperatures triggers a ‘dimple’ or ‘split of peaks’ speciation scenario (Rozenzweig 1978) as in 5bV and a separated population will hence occupy the intermediate fitness peak (5bVI and 5bVII). The newly occupied peak corresponds to the right lobe of the horseshoe-shaped eco-phenotypic landscape (Figure 5a).

To sum up, this model shows that a horseshoe shaped eco-phenotypic landscape may have a special significance for sympatric speciation in continuous populations. However, the shape of the eco-phenotypic landscape is not a sufficient condition for sympatric speciation. The pace and amplitude of environmental oscillations, the strength of selection, the covariance with other environmental and phenotypic characters and the genetic variance and covariance will all have to be accounted for before an accurate prognosis can be made. The strength of the eco-phenotypic landscape is that it retains its form over phenotypic or environmental changes and can serve as a template that allows for long term heuristic projections after the integration of the aforementioned parameters.

Figure 5. (A) A horseshoe eco-phenotypic landscape (multivariate individual fitness function). (B) A scenario of sympatric speciation driven by environmental change (blue peaks represent individual fitness functions and solid magenta peaks represent phenotypic distributions).


Fitness of hybrids: Ηeterosis and outbreeding depression [this part was excerpted from the paper’s published version]

Heterosis and outbreeding depression describe crossbreeding events where hybrid fitness is, respectively, enhanced or depressed in relation to their parental forms. In populations that have had enough time to adapt to their environments, outbreeding depression is the most usual of both cases since any change would shift them away from their local optima (Nosil et al. 2005). Heterosis can be expected in the rare event that an intermediate fitness peak occupies the space between parental populations (Mallet 2007).

The fitness of hybrids is commonly measured in their parental environments by reciprocal transplant and phenotypic manipulations techniques (Edmans 1999; Rhode and Cruzan 2005). These methods, albeit indispensible on the practical level, have been criticized as having a critical blind spot. Hendry (2015) has noted that reciprocal transplants normally test hybrids and backcrosses in the parental environments, but those same hybrids and backcrosses would presumably have high fitness in intermediate environments. Thus, the experiments described above can’t reveal the presence of a fitness valley unless they also confirm the absence of intermediate environments. A similar line of argument is taken by Rundle and Whitlock (2001) who have highlighted the importance of determining the contribution of genetic and ecological mechanisms to hybrid fitness before any inferences concerning fitness valleys or speciation are to be made.

The following model presents a hybrid transplant experiment that could have leaded us to infer an adaptive valley for intermediate forms in what is actually an adaptive ridge. Consider the continuous population of Figure 3, where two parental forms (A and B) produce a hybrid form (H) which is assumed to be phenotypically intermediate. If we test the hybrid’s fitness in either of the parental environments, the outcome would be a significant fitness depression (fitness=0 in the graph) leading us to infer a fitness valley. However, in the intermediate environment the hybrid’s fitness would be equal or higher than the parental forms, indicating the presence of a continuous adaptive ridge (Rieseberg et al. 2003).

In vivo, the convergence of parents and the upbringing of their offspring in an intermediate environment provide a plausible physical mechanism for heterosis. Evidently, the shape of the eco-phenotypic landscape will play a defining role: A horseshoe of the likeness of Figure 5 is more likely to induce outbreeding depression than heterosis for intermediate forms. Overall, the eco-adaptive landscape may prove useful both for the conceptualization of naturally occurring hybridization processes and identification of the analytical scope of hybrid fitness experimental designs. 



We decided to omit this latter part on heterosis from the published version of the paper, since one of the reviewers identified some weaknesses in this section. However, we are citing Ben Haller’s comment on this part for anyone wishing to take it up from here:

This is one place where I think you can actually go a bit further than you do, by pointing out that plotting experimental results on your proposed type of landscape plot would immediately make the error described by Hendry 2015 obvious; the graphical exercise would expose the conceptual flaw. And therefore everybody ought to use your diagrams when presenting such work.  :->  You hint at that here, but don’t quite say it outright.


Lastly, here is Ben’s concluding comment for our paper, effectively describing an opening for future research:

In the end, I find that you didn’t go as far as I expected you to go. If you really want to fuse ecology and evolution, then you need to get into things like multispecies dynamics (how does one species affect the fitness landscape experienced by another species?), coevolutionary dynamics (how might two coevolving species be visualized using your sort of plots?), and eco-evolutionary dynamics (does that fit somehow into your scheme?).


Well, this is flattering, but I don’t think I can do that. It’s like asking from a high school physics teacher to fuse relativity with quantum mechanics. But I wish someone else does it; you will need someone who has spent a big part of their life in this, not just a passer-by who only stayed for a short while. From my part, I’m happy if I stirred some conversation. It is almost certain that I will never return to evolutionary biology for anything more than an occasional reading; it is not practical to invest more time in staying updated in a field as distanced from my own field. Also, from a career perspective, it does not make sense to strive for a publication in biology, then another in political science, another in epistemology, and so on. It needs a substantially greater effort to acquaint oneself with the body of knowledge and terminology of a new field each time, let alone to produce work that meets the standards of an academic publication. However, I can’t help being all over the place since I suffer from what I’m sure is a form of greed: I want too to explore, in depth, many different fields. You can call it shifting intellectual curiosity. Anyway, I want to thank you for having me here, especially Andrew. I feel that I’ve learned a lot out of this process. Science is cool. Keep it up!



References

Aarssen, L. 2017. The sapiens advantage. Ideas in Ecology and Evolution 10: 6–11.

Benkman, C. W. 2003. Divergent selection drives the adaptive radiation of crossbills. Evolution 57: 1176–1181.

Berner, D., Grandchamp, A. C., and A. P. Hendry. 2009. Variable progress toward ecological speciation in parapatry: stickleback across eight lake-stream transitions. Evolution 63: 1740–1753.

Dieckmann, U. and M. Doebeli. 1999. On the origin of species by sympatric speciation. Nature: 400 (6742): 354.

Edmands, S. 1999. Heterosis and outbreeding depression in interpopulation crosses spanning a wide range of divergence. Evolution 53:1757–1768.

Hendry, Α. 2016. Eco-evolutionary dynamics. Princeton university press

Hendry, A. P., Bolnick, D. I., Berner, D., and C. L. Peichel. 2009. Along the speciation continuum in sticklebacks. Journal of Fish Biology 75: 2000–2036.

Kirkpatrick, M. and N. H. Barton. 1997. Evolution of a species' range. The American Naturalist 150: 1-23.

Leblois, R., Estoup, A., and F. Rousset.  2003. Influence of mutational and sampling factors on the estimation of demographic parameters in a “continuous” population under isolation by distance. Molecular biology and evolution 20: 491–502.

Mallet, J. 2007. Hybrid speciation. Nature 446: 279-283.

Nosil, P., Vines, T. H., and D. J. Funk. 2005. Reproductive isolation caused by natural selection against immigrants from divergent habitats. Evolution 59: 705-719.

Rhode, J. M., and M. B. Cruzan 2005. Contributions of heterosis and epistasis to hybrid fitness. The American naturalist 166: 124–139.

Rieseberg, L. H., Raymond, O., Rosenthal, D. M., Lai, Z., Livingstone, K., Nakazato, T. et al. 2003. Major ecological transitions in wild sunflowers facilitated by hybridization. Science 301 (5637): 1211-1216.

Rozenzweig, M.L. 1978. Competition speciation. Biol. J. Linn. Soc. 10: 275–289.

Rousset, F. 2000. Genetic differentiation between individuals. Journal of Evolutionary Biology 13: 58–62.

Rova, E., and M. Björklund 2012. The influence of migration on the maintenance of assortative mating. Animal Behaviour 83(1): 11-15.

Rueffler, C., Van Dooren, T. J., Leimar, O., and P. A.  Abrams. 2006. Disruptive selection and then what? Trends in Ecology & Evolution 21: 238–245.


Rundle, H. D., and M. C. Whitlock. 2001. A genetic interpretation of ecologically dependent isolation. Evolution 55(1): 198-201.

Monday, July 2, 2018

The benefits and costs of academic travel. Or "there and back again; again and again"


As I sit here in an airport lounge en route to yet another far-flung destination, it seems appropriate to finally write a long-planned blog post – about my carbon cost. Like nearly all other academics, I feel strongly that climate change is perhaps the most pressing problem of our time, requiring serious societal change to reduce and offset carbon emissions. Yet, like many of those very same academics, I travel an insane amount – usually on airplanes. Thus, I – and many other academics – are potentially subject to the criticisms summarized recently in a Huffington Post opinion piece “The Climate Change Hypocrisy of Jet Setting Academics.” This year will be my most extreme travel year yet, involving 25 discrete trips from my home in Montreal to somewhere outside the province of Quebec. The result is obviously a huge carbon cost on a per-individual basis. So why do I do it from the perspective of a cost-benefit analysis.

My 2018
Benefits – professional and personal

Travel generates a huge professional benefit on numerous levels. First, it increases exposure and visibility of your research, which is important in this day-and-age of “vastly more papers published than one could possibly read” in which it is hard for any one researcher to stand out. Traveling to give talks and seminars makes more people aware of your work, which can increase citations and facilitate recruitment of new students to your laboratory. Second, travel often leads to new collaborations and group perspective papers and the like. Third, in a number of research fields including mine, travel for field work is obviously essential for conducting high-quality research and for helping one’s students to do the same. Fourth, much academic travel provides a service to the community. Invitations to travel somewhere are nearly always because a group of students or professors sincerely wants to meet you and hear about your research. Participating in grant evaluation panels and editorial board meetings are a way of giving back to the academic community. And, of course, personal benefits can accrue through the enjoyment of seeing different places, engaging with different cultures, and experiencing different parts of the environment.

Costs – personal and professional

Travel can have considerable costs that are not directly environment-related. First, it takes time away from family, which can be hard on relationships in any number of ways. (Although I try to bring my family when possible.) Second, it means time away from academic duties at your home institution, which can be hard on your students and colleagues. (Although I try to travel when such costs are minimal.) Third, it is difficult physically as prolonged confinement to airplane seats can lead to a number of either serious or simply annoying physical problems. (Nowadays I usually upgrade to “preferred seating.”) Fourth, travel can be expensive and can take away from your ability to invest in other types of research costs. (Although most of my travel is paid for by third parties.) However, the main motivation for this post was to consider the environmental costs of extensive travel – most obviously carbon inputs to the atmosphere.

Rationalizations for carbon footprints

A simple “bean-counting” rationalization for not worrying too much about the environmental costs of extensive travel is the argument that – as an individual – I will not have any impact on the environment even if I were to fly constantly for the rest of my life. That is, the amount of carbon that I am personally responsible for adding to the atmosphere is such a small part of the whole that subtracting it would not have any measurable impact.

A “zero-sum” rationalization is that, for most of my travel, I am filling a slot that – if I didn’t go – would simply be filled by someone else. That is, seminars will be given by someone, working groups will be populated by someone, and so on. If I don’t go, someone else will simply travel and take my place. IN such cases, staying home would not change the average environmental cost as it would just be attributed to someone else.

A “bigger picture” justification would be that academic travel often relates to study and understanding the environment, in which case the carbon cost of travel is more than offset by the benefit to the environment. For instance, a decent amount of my travel is associated with environmental NGOs where we provide advice on biodiversity science to governments and through which we promote the understanding of biodiversity to the public. Some of my colleagues who study global warming actually travel an incredible amount in efforts to reduce carbon inputs to the environment, with the argument being that their own contribution to carbon emissions is more than offset by their global contribution to carbon emission reductions.

Which brings us to the “hypocrisy” criticism. That is, even if all of the above rationalizations valid, they don’t account for the fact that it just “looks bad.” That is, how can a person advocating for everyone on Earth to reduce their carbon footprint not do so themselves. It reduces their credibility and seems elitist and selfish. Of course, this criticism does not have a clear defense except in light of the above three arguments: bean-counting, zero-sum, and bigger-picture.

In the end

So how does all of this pan out for me personally. For starters, I would love to travel less as I would rather spend more time at home. So why do it then? In point of fact, most of my travel falls into the “service” and “zero-sum” categories, where I am giving seminars, participating in workshops, helping NGOs, evaluating grants, visiting my students in the field, teaching and administering programs, helping friends and colleagues with symposia and conferences, and so on. The simple truth is that someone wanted my help, asked nicely for it, and I felt obliged (in a non-resentful way) to participate. Once committed to a new trip, I try to make the most of it.

I first try to maximize the professional benefits, especially by participating fully in the activities; and also the personal benefits, often by tacking a day onto the end of the trip to go see penguins or gorillas or elephants or whatever. I am also “collecting” rock climbing gyms around the world – and have now been to 33 of them. Recently, I have started taking my teenage daughters with me on trips to foster their enthusiasm for science and nature – this year’s trip to the Galapagos has them both talking about wanting to be biologists. MY hope, then is to try to minimize the costs and maximize the benefits. One might argue that such costs would be much lower through remote participation in workshops and meetings and so on. I also often take this approach, as do all academics (thank you Skype!) but many of the benefits require face-to-face interaction.


In closing, I want to sincerely thank everyone who has invited me for a seminar or workshop or meeting. I have enjoyed each one immensely – and this post should not be construed as a complaint in any way. In fact, I look forward to interactions on every one of my upcoming trips. (Although next year I will do a short sabbatical and will try to travel less – we shall see.) I also want to point out that while travel helps professionally, it is not NECESSARY for a successful career in academia. Many well known academics actually travel very little, and so no one should feel compelled to engage in professional travel at the expense of personal wellbeing and family harmony.

Andrew’s 2018 travel schedule – in temporal order
Asilomar (California) -  conference
Santa Barbara (California) – working group
Corvallis (Oregon) – seminar
Gamboa (Panama) – teaching and administration
Halifax (Nova Scotia) – seminar
Galapagos – field work
Oulanka (Finland) – workshop/symposium
Trondheim (Norway) – seminar
Fayetteville (Arkansas) – seminar
Kingston (Rhode Island) – seminar
Lexington (Kentucky) – seminar
Millbrook (New York) – seminar
Victoria (British Columbia) – family trip
Kenai and Anchorage (Alaska) – field work
Brussels (Belgium) – grant evaluation panel
Kyoto (Japan) – conference
Guelph (Ontario) – conference
Waimea (Hawaii) – symposium
Frankfurt (Germany) – working group
Smithers (British Columbia) – family trip
Montpellier (France) – conference
Brussels (yes, again) – grant evaluation panel
Smithers (British Columbia) – family trip
Oeiras (Portugal) – symposium
Philadelphia (Pennsylvannia) – seminar

Mistakes were made

We make mistakes. Just look at a search for GIFs using the keyword "mistake" . Its worth it. When you are a graduate student, an...