Movement patterns in populations of early academics

Sometimes of the perks of academic life are also the most difficult parts – frequent travel opportunities mean you are also frequently away from friends and family (and spend too much time in airports). The nature of the university job market provides global opportunities for work, but also means that in reality opportunities and circumstances can constrain you to places you wouldn't have chosen otherwise. Your friends will cover the world, but you will rarely be in the same room together. The apprenticeship-like nature of early academic positions means that you will move, probably many times, before you find a permanent position (if you do). 

I have a friend who grew up with diplomat parents, which meant her family moved to a new place in the world every few years. The result was that she often felt like she didn’t have a strong connection to any one place or group of people. Academia isn’t quite so extreme, but you can understand why after moving to one place for undergrad, another for a Masters and/or PhD, one or two more for postdocs, your interactions and place in the world can feel rather impermanent. It also means that, for better or worse, your social circle includes other academics, and they are also shifting from place to place. When I tell non-academic friends and family (who mostly have settled in a single place) about upcoming moves, they are often more excited than I am about the opportunity to pick up and go. No doubt this is a grass-is-always-greener situation, but I often think that the most notable and difficult aspect of academic mobility is that you end up saying goodbye a lot.

I wonder whether some of the academic ambivalence expressed is aggravated by this early, necessary transience. Certainly there is lots of evidence that residential mobility (i.e. moving) relates to higher mortality and lowered health indicators, though some studies suggest that this effect may be more true for introverts than extroverts (presumably because extroverts form new friendships more easily). Academics share this phenomenon with groups like military families and third culture kids. The commonality is that, with every move it becomes harder to define home as a particular place – it is more like an intangible connection to multiple places and people. And maybe that's not so terrible - a good friend who was raised by an academic suggested that the key is to redefine your life and friendships as being global rather than local. And eventually professors settle down (I can think of a few people who have been at one university for 30+ years). But in the interim there is always the not-insignificant tension between the costs and benefits of uprooting yourself every few years, and the slow loss of individuals who are not capable of this mobility, from the academic pipeline.

Felsenstein for SMBE president :)

A highly entertaining, somewhat relevant update to my post about Joe Felsenstein's 'dishonour roll'. Felsenstein is running for President of the Society for Molecular Biology and Evolution, and his personal statement is a must-read career retrospective. If you don't at least crack a smile, you might be taking science a bit too seriously...

For example: "[Felsenstein] has been President of the Society for the Study of Evolution, and imagines that he could be President of the SMBE, even though he has not yet learned the names of all 20 amino acids."

Honestly, I think it gives more insight than most bios into the person and their work.

Another round in Diamond vs. Simberloff: revisiting the checkerboard pattern debate

Edward F. Connor, Michael D. Collins, and Daniel Simberloff. 2013. "The Chequered History of Checkerboard Distributions." Ecology. http://dx.doi.org/10.1890/12-1471.1.

One of the most vociferous recent debates in community ecology started in the 1970s between Jared Diamond and Dan Simberloff (and colleagues) regarding whether 'checkerboard patterns' of bird distributions provided evidence for interspecific competition. This was an early and particularly heated example of the pattern versus process debate that continues in various forms today. Diamond (1975) proposed that the distribution of birds in the Bismark Archipelago, and particularly the fact that some pairs of bird species did not co-occur on the same islands (producing a checkerboard pattern), was evidence that competition between species limited their distributions. The issue with using this checkerboard pattern as evidence of competition, which Connor and Simberloff (1979) subsequently pointed out, was that a null model was necessary to determine whether it was actually different from random patterns of apparent non-independence between species pairs. Further, other mechanisms (different habitat requirements, speciation, dispersal limitations) could also produce non-independence between species pairs. The original debate may have died down, but the methodology for null models of communities suggested by Connor and Simberloff has greatly influenced modern ecological methods, and continues to be debated and modified to this day.

The original null model of bird distributions in the Bismark Archipelago involved a binary community matrix (rows represent islands, columns represent species) with 0s and 1s representing species presences or absences. Hence, all the 1s in a row represent the species present on the island. The original null model approach involved randomly shuffling the 0s and 1s, maintaining island richness (row sums) and species range sizes (column sums). The authors of a new paper in Ecology admit that the original null models didn’t accurately capture what Diamond meant by a "checkerboard pattern". This is interesting in part because two of the authors (E.F. Connor and Dan Simberloff) lead the debate against Diamond and introduced the binary matrix approach for generating null expectations. So there is a little bit of a ‘mea culpa’ here. The authors note that earlier null models captured patterns of non-overlap between species' distributions but didn’t differentiate between non-overlap between species with overlapping ranges compared to non-overlap between species which simply occurred on sets of geographically distant islands (referred to here as 'regional allopatry'). The original binary matrix approach didn’t consider spatial proximity of species ranges.

With this fact in mind, the authors re-analyzed checkerboard patterns in the Bismark Archipelago, but in such a way as to control for regional allopatry. True checkerboarding was defined as: “a congeneric or within-guild pair with exclusive distribution, co-occurrence in at least one island group, and geographic ranges that overlap more or significantly more than expected under an hypothesis of pairwise independence”. This definition appears closer to Jared Diamond's original definition and so a null model that captures this is probably a better test of the original hypothesis. The authors looked at the overlap of convex hulls defining species’ ranges and when randomizing the binary matrix, added the further restriction that species could occur only within the island groups where they were actually found (instead of being randomly shuffled through any island, as before).

Even with these clarified and more precise null models, the results remain consistent. True checkerboarding appears to rarely occur compared to chance. Of course, this doesn't mean that competition is not important, but “Rather, in echoing what we said many years ago, one can only conclude that, if they do compete, competition does not strongly affect their patterns of distribution among islands.” More generally, the endurance of this particular debate says a lot about the longstanding tension in ecology over the value and wealth of information captured by ecological patterns, and the limitations and caveats that come with such data. There is also a subtle message about the limitations of null models: they are often treated as a magic wand for dealing with observed patterns, but null models are limited by our own understanding (or ignorance) of the processes at play and our interpretation of their meaning. 

The slippery slope of novelty

Coming up with a novel idea in science is actually very difficult. The many years during which smart people have, thought, researched, and written about ecology and evolution means that there aren’t necessarily many easy openings remaining. If you are lucky (or unlucky) enough to know someone with an encyclopedic knowledge of the literature, it becomes quickly apparent that only rarely has an idea not been suggested anywhere in the history of the discipline. Mostly science results from careful steps, not novel leaps and bounds. The irony is that to publish in a top journal, a researcher must convince the editor and reviewers that they are making a novel contribution.

There are several ways of thinking about the role of the novelty criterion - first, the effect it has had on research and publishing, but also more fundamentally, how difficult it is to even define scientific novelty in practice. Almost every new student spends considerable effort attempting to come up with a completely "novel" idea, but a strict definition of novelty – research that is completely different than anything published in the field in the past - is nearly impossible. Science is incrementally built on a foundation of existing knowledge, so new research mostly differs from past research in terms of scale and extent. Let's say that extent characterizes how different an idea must be from a previous one to be novel. Is neutral theory different enough from island biogeography (another, earlier, explanation for diversity which doesn’t rely on species-differences) to be considered novel? Most people would suggest that it is distinct enough as to be novel, but clearly it is not unrelated to works that came before it. What about biodiversity and ecosystem functioning? Is the fact that its results are converging with expectations from niche theory (ecological diversity yields greater productivity, etc) take away from its original, apparent novelty? 

Then there is the question of scale, which considers the relation of an new idea to those found in other disciplines or at previous points in time. For example, when applying ideas that originate in other disciplines, the similarity of the application or the relatedness of the other discipline alters our conclusions about its novelty. Applying fractals to ecology might be considered more novel than introducing particular statistical methods, for example. Priority (were you first?) is probably the first thing considered when evaluating scientific novelty. But ideas are so rarely unconnected to the work that came before them, so then we evaluate novelty as a matter of degree. The most common value judgment seems to be that re-inventing an obscure concept first describe many years ago is more novel than re-inventing an obscure concept that was recently described.

In practice, then, the working definition of novelty may be that something like ‘an idea or finding doesn't exist the average body of knowledge in the field’. The problem with this is that not everyone has an average body of knowledge – some will be aware of every obscure paper written 50 years ago, and for them nothing is novel. Others have a lesser knowledge or more generous judgement of novelty and for them, many things seems important and new. A great deal of inconsistency in the judgement of papers for a journal with a novelty criterion results simply from the inconsistent judgement of novelty. This is one of the points that Goran Arnqvist makes in his critique of the use of novelty as a criterion for publishing (also, best paper title in recent memory). Novelty is a slippery slope. It forces papers to be “sold” and so overvalues flashy and/or controversial conclusions and undervalues careful replication and modest advances. And worse, it ignores the truth about science, which is that science is built on tiny steps founded in the existing knowledge from hundreds of labs and thousands of papers. And that we've never really come up with a consistent way to evaluate novelty.

(Thanks Steve Walker for the bringing up the original idea)