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Posts Tagged ‘science story’

I’ve written some soul-searching posts here before, but the topic I’ve long held back from addressing is the one that feels most forbidden as a senior-level academic. Today I’ve relented and written on it. Well, anyway I wrote this about 4 months ago and sat on it, and now’s the time. To hell with the forbidden — it is that nature which has been a torment. In academia we hear many stories, and are encouraged to talk openly about, the trials and tribulations of securing a permanent faculty (or similar; e.g. curator) post. I could write about my experience as an early career scientist, which wasn’t easy, but it wouldn’t be as contemporary or as fraught with emotion as this one is. This post is about the next step, one we hear so little about: attempting a mid-career transition between institutions.

I’ve bottled these thoughts up long enough but realized they are a teachable moment that others may benefit from, as I will loop back to at the end. The point of the post is not to seek pity or sympathy, or convey that doom and gloom about academia that pervades the internet, or even to hope for empathy, but to simply state this how it has been for me so far (SPOILER: it’s a story of failure), if one is headed down this path it might help, or at least the tale might be of interest in some other way, even having parallels with some non-academic careers.

Stomach-Churning Rating: me 1010/10; yours will vary

It is probably a good idea, and I don’t know the statistics but I imagine it is common, to move between institutions at least once in a scientist’s career, and not uncommonly twice; thrice enters a bad dimension and four or more times is either pathological or purposefully peripatetic (which might be fun!). Sooner or later one wants a change of pace: one may seek to move up the ladder to a better institution, more salary or other benefits, more desirable geographic location, escape poor working conditions for anything else, and/or other factors. New adventure, mid-life crisis, whatever. At mid-career, the temporal window is closing to find that place you finish your career at, hoping for ultimate stability and satisfaction. The pressure begins mounting, but while the opportunities to transition at assistant professor level are small (with much competition), the opportunities to do so at associate professor, let alone full professor level, approach the nadir. It varies among fields and geographic regions (and how choosy one is), but there may be only 1-2 jobs in one’s field in a year. Competition may be smaller than at junior level, or just hard to even compare, but a qualitatively different factor emerges.

Early career scientists (ECSs) are evaluated in job interviews for faculty-level posts in terms of their potential to grow to become what the institution needs; with evidence of already being on that trajectory important. But it’s less about who you are as how you convince the institution that you can become that dream academic they need most. At a mid-career level, everything is in plain sight. You have a track record. You probably know 1+ people in the institution or they might never give your application a second look. So as a known quantity, the question switches to how the person fits what is needed now and in the immediate future. They are less malleable. They probably won’t do a major pivot to change their research or other direction; that’s hard at a senior level (and an uphill battle to convince committees of). Once the few candidates have been interviewed, it’s probably clear to the search committee who fits their needs. There is less likely to be the “what if?” mystery with the ambiguous future of ECSs that may leave the committee more uncertain. It’s like being handed a puzzle to put together, vs. handed a batch of ingredients to cook freestyle.

Now begins my personal story. It’s maybe the worst-kept secret I have, I realize. And now I’m OK with that. When I came to the RVC, I was told that I’d probably remain for 5-7 years and then move back to the USA, and that was fine — even expected. I thought as much, too, and by the end of that time period I’d been applying for jobs to make that return voyage as prophesized. 10 years later, after almost 16 years, I’m still here. I’ve hit the wall of the mid-career transition and had to come to grips with its harsh reality. With few jobs and slim odds, I worry that I’m near an event horizon. I’m an academic straddling some fields that makes me somewhat of a square peg for many jobs. What am I? Do I fit into conventional labels and needs? This has been my career-long identity struggle — an evolutionary biomechanist is a weird mix. Having a large grant, too (the DAWNDINOS one), could be seen as an impediment as I’m still set on a major research project for 2 more years. Yet who knows… the rest is personal and remains uncertain.

Before I finish I must address the forbidden nature of such concerns. As mid-career academics, we’re enormously privileged. We have a job, perhaps a family, a home, relative stability and security, and so forth. ECSs might give anything for that! But we have our own lives to live, and the existential crisis of time-is-running-out only gets more intense. The prizes of tenure and other success may not come with happiness. We may feel “forbidden” to speak of our experiences not only because of such privilege, but also because of massively complex socio-political interactions that face us when trying to move institutions. I am fortunate that my institution has had my back throughout my process — others would not be so kind. I’ve heard of some universities that will sack their academics if they mention to senior administrators that they are contemplating a move! That’s just evil.

It can cause deep anxiety, uncertainty, political chicanery and other trouble for the news of seeking a mid-career transition to reach the wrong ears at the wrong time — particularly as it tends to be a prolonged, uncertain process. Seeking a job vs. moving with a signed contract are different things! Far, far, far apart on the spectrum of certainty are they. Moreover, the choice to seek to move jobs is a personal and private one. We may not want to become the topics of idle gossip, or even misinformation and undermining. These factors make the journey a lonely and unique one, and it would be a grotesque understatement to say that the personal (e.g. family, health) dynamics involved will compound the stresses. Together these can impact not just life outside of work but performance at and enjoyment of work itself.

The learning opportunity that I most want to share is this: if you’re on this kind of career track, plan to move early and get started early. Apply to jobs sooner (i.e. as an assistant professor) than later (i.e. tenure onwards) even if you’re not sure about wanting to move. Talk to your partner, peers or those that matter most about this; have a trusted, private support network and advice. Get some irons in the fire and see what opportunities arise. Expect that it may take much longer than you thought, so be strategic. Have a plan B, C and D; think about how flexible you can be. And, while you might do well getting interviews and hear nice things about how amazing you are (cold comfort at times), get used to the answer that you just don’t fit what a search committee was looking for. “Fit” is that Swiss army knife of words we use in such situations in academia, to embrace a wide range of reasons we don’t want to (or can’t, for HR/legal concerns) get into at the time for why a job decision is made. A lack of “fit” is a hard word to hear and accept, as we might see it otherwise, but it is the reality and we must accept it. By accepting such realities, perhaps the forbidden will become bearable.

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I had the privilege and pleasure of serving for the past 2 years as Chair of the Division of Vertebrate Morphology at the Society for Integrative and Comparative Biology, and that service just ended. So I had the showerthought to briefly post about the broader messages from that experience, with the hope that other scientists might benefit. But first, a little backstory.

Stomach-Churning Rating: 0/10

I’d only done some minor service before this, in scientific societies. At the time I ran for Chair-Elect 5 years ago, I felt it was time to try something new; to give back to science, as one should do. And so I did. It was a challenging and thus rewarding experience of learning the ropes- the Chair position is fairly open-ended to allow one to contribute what new things and leadership one envisions and can manage. In a short 2 years I felt I gained just enough momentum that I could have run the role more smoothly if I’d had a 3rd year, but that’s hindsight. The details don’t matter here but they lead to the messages of this post.

wink-wink musical interlude 1

First, the simple message that service, like the Holy Ghost, is the oft-forgotten third component of the trinity of professional science/academia; teaching and research being the other two (and science communication, to me, bridging all of these). As one moves along in one’s career, service tends to become increasingly expected—and the wisdom accumulated aids its conduct.

Second, service should be done because:

  • It’s the right thing to do
  • You learn things about your professional society, discipline, colleagues, leadership and self (skills and limits)
  • It’s not necessarily just boring bureaucracy (more about that below)
  • It will aid your career (CV, promotion, connections, future service, etc.) and you can aid others along the way

I think a common misconception is that service is boring. Yes, hearing the minutes of prior meetings read to you, or a long screed about minutia of health-and-safety, can be boring at times. But pay attention and find things that interest you and new vistas can open. This depends on the position one serves in and how it fits you. In my case, I found it a fun challenge to run meetings (i.e. try to follow the standard protocol of devising an agenda, checking minutes, etc.; standard bureaucracy) – especially the key activity of raising and voting on issues to consider taking the division in new directions. That allowed some creativity and made for energetic discussions on issues that mattered.

Another contrast to “boring” is resolving crises that arise (in my case, quite a few arose that felt serious to me). Yes, they’re stressful, but they also teach you things about how to handle crises, and you learn about your own ability to do so; and how others interface with that dynamic process. As I tend to emphasize on this blog, doing science is HUGELY about human interactions and foibles, and in service, as everywhere, such things are especially prominent and complex.

wink-wink musical interlude 2

Service comes in many forms. Students and postdocs can and should take part—many societies such as SICB tend to allow or encourage early career researcher participation. At a minimum, scientists should vote on elections (participation tends to be low among student/postdoc members) and attend their societies’ business or other meetings to see how the machine of a professional society works inside. It may even learn to serendipitous outcomes! And lessons learned will serve you well in many forms of future career.

One can do many other forms of service. Minimally in research, one is expected to participate in peer review; and that experience can lead to editor roles at journals, which I’ve found very interesting. Certainly in academic and other departments, there are numerous committee and other roles analogous to those in professional societies that are opportunities to serve.

I’ve surely left out other important lessons learned from serving. I’m still processing my experiences, reflecting and thinking forward. Now I’ve moved on to new service at SICB as Chair of the Student-Postdoc Affairs Committee, so there’s lots more for me to learn and share in that role.

What have you learned from serving? Do you have questions about service in science? Please chime in below.

More links of interest:

DVM-DCB Twitter feed

DVM Facebook page (members+affiliates)

SPDAC Facebook page (anyone!)

SPDAC Twitter feed

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As a person who has transitioned from the “simple life” (haha) of a grad student to postdoc to younger and then more experienced faculty member in academia/science, I constantly ponder how I spend my time. This is more so true lately, thanks to social media keeping me aware of how others spend their time (e.g. conversations about overwork and unrealistic expectations in academia/science), and thanks to my own experiences managing a moderate-to-large-sized group of 5-15ish scientists in the past ~10 years. I’ve had to learn to juggle a lot more than I did before and my life also has changed a lot (family, health, etc), some of which I’ve blogged about here before. Some of that excessive juggling is why there haven’t been so many blog posts here recently!

But today I want to turn the lens on the post’s title topic. What does a “typical” weekday in my life look like, with a focus on the academic/science aspects? There is no such “typical” ideal; every day is very different, but a Platonic abstraction will be heuristic. Let the clock tell the tale…

Stomach-Churning Rating: opinions may vary but I say it’s 0/10 (no gory photos).

0600-0700 I wake up and rush for the 2 big mugs of coffee that get and keep me moving, overcoming some huge side effects from medications I’m on. I feed the cats and check my email whilst having my coffee (and cereal + yoghurt). I deal with several simple messages from USA colleagues, or UK colleagues up late. Emails requiring more mindpower are saved for later. I tweet/retweet a little while skimming social media.

Nectar of the gods!

0730-0900 After shower etc. I begin my commute. 90 mins walk-train-train-walk (if no delays) and I can fit in another 60 mins or so of emails and some higher-functioning work (e.g. writing; editing papers; catching up on literature) on the train if I am feeling up for it. If I’m still too sluggish I listen to a (not-strictly-science but intellectual) podcast; e.g. RadioLab or Invisibilia; or (worst case) some rockin’ music.

0900-1000 Catching up on things in my office, with a few more emails, some organizing, quick chats with people around my office, and my day takes shape as I near my peak level of energy (and busy-ness).

1000-1200 Full steam ahead! I try to schedule my most demanding meetings to give them my full attention, or do my most challenging work if on my own.

1200-1230 John infamously gets hungry every ~5 hours and there is no stalling his need for fuel. Off to the campus restaurant he goes, for a hot meal and a little quiet time away from his office, to think/chat.

1230-1300 I like to leave this time as very flexible “me time”, whether spent on social media or whatever. I just do what suits me, maybe tidying up loose ends with smaller tasks, or just chilling (relatively) in contemplation.

1300-1400 A maybe less demanding meeting or a seminar (or a committee); in the latter case my powerful post-prandial somnolence becomes a battle now (and I don’t do caffeine >0800ish! Too sensitive). But I keep pushing on, and stuff gets done.

1400-1500 Another research-type meeting or data collection session, or writing, to fill some final, very valuable, on-campus time.

1500 Run for the train home, trying to stealthily escape campus without having any impromptu meetings that make me miss my train. My work day is not over but the commute is tiring so 6 hrs on campus and a bit more before and after are plenty!

1515-1645 Train ride and a bit of work where I feel able (50% of the time?).

1700-1800 Some catch-up emails (e.g. USA colleagues are waking up by now) and catch-up with family; juggling a lot. My activities vary a lot here: I may be inspired (even catching a second wind) to get some final work done or I may be totally wiped out and need a break. I listen to what my body tells me and also try to ensure I give myself time for non-work from here on.

1800-2100 Quality non-work time.

2100-2200  A bit of non-science reading before I fall asleep.

2200-0600 I need my 8 hrs sleep or I am a slow(er) grumpy John.

I’ve listed a “typical” day for non-teaching weeks. Currently my teaching load isn’t large by any measure, nor do I have many committee duties, and I am paid by my DAWNDINOS grant to spend 70% of my time (thru 2021) on that one project. So other than my October-November teaching I am mainly doing that 70% DAWNDINOS work, in various forms, plus a 30% that is some kind of science: a HUGE array of collaborations, some still stretching back to circa 2001 and still alive, some social media of course (although less these days than in ~2011-2012’s heyday, you may notice), and a potpourri of “other stuff”.

That “other” category is vast — travel to far-off places is a big time-sink lately, such as with 4 trips to the USA’s west coast in the past 4 months for seminars and conferences (although much of that involved DAWNDINOS presentations too). I am glad it’s all done, much as it was valuable science communication and meetings with friends/colleagues. Emails of sundry sorts fall into that “other” category too: I am not sure how many emails per day I field but I am the type of person that likes to handle a lot via email. Thereby I have a written record (my memory is patchy at times even though it can be excellent) that helps me organize my thoughts and actions. Maybe it’s 50 emails/day? Plus another 50 emails of fake conference/journal spam that seem to take more time deleting than they should (hello, spam filter)? Hosting visitors, talking on the phone/Skype with science writers, and certainly doing journal editorial/peer review duties are other big chunks. And so on; I won’t list it as most of it is normal academic life stuff. (Aside from the occasional elephant post-mortem)

Now, I got into academic life for what I feel are very good reasons, for me. A bit of context: I started working as a newspaper delivery boy at age 12, and continued that until I was maybe 15, then did odd jobs such as washing biochemistry dishes in my dad’s lab or fast food cashier/restaurant busboy & dishwasher until college. Then I kept up some intermittent part-time jobs like selling music CDs at Sam Goody, mixing margaritas as a “blender jockey” at Chi-Chi’s Mexican restaurant or tending snails at a marine ecology lab (thanks, Dianna Padilla!) until grad school. The point is, my parents had the wisdom to inculcate a work ethic into me, and that was VERY good, although I also got a strong taste of what it was like to work in a typical business, punching the clock in and out each day. And I HATED that clock-punching. It still provokes a deep visceral reaction from me. (Aside: ironically, that generous DAWNDINOS grant requires me to log my daily hours, and I hate that too but it must be done!)

In Sarasota, Florida where we spent winters with grandparents and I gleefully chased Anolis lizards (one blurry one here, I promise!).

To tie the story up, academic life attracted me (and I saw enough from my dad’s life as a professor to know) because it offered an escape from that punch-clock, 9-to-5 Monday-Friday life. The 9-to-5 strict schedule is just not for me, although I have plenty of respect those for whom it is; the world needs all kinds. I need flexibility; I need to be able to do science when Athena’s muse strikes me, not feeling chained to a rigid schedule and suffocating bookkeeping of how time is spent. In reality, in academia/science I feel now that it is impossible for me to realistically quantify how much time I spend on particular things – I may get a good idea while on the toilet, and that counts as science time doesn’t it? I am probably juggling a dozen things at once in my mind and efforts; work/other life/bullshit; at any one time, so partitioning my time is subjective nonsense. I prefer to be judged (when I must be judged) on what I do and its quality, and to be trusted to do this right by some “fair” standard rather than hours. To me, that’s what academia/science should be… (current reality be damned)

I blame the 80s.

That brings me to, how does a weekend look? In grad school I didn’t mind devoting some of my weekends – and plenty of late evenings – to work. Now, especially with a family, I do mind it. Living in Europe has helped me appreciate that quality-of-life mentality as well. It can still be a struggle within me, as I love science and sometimes I just want to do it; it may not matter if it is 6am on a Tuesday, 1pm on a Thursday or 7pm on a Saturday. Often I say “no” and don’t, and that can feel good, but sometimes I let myself enjoy after-hours work, because I live for enjoyment in all its forms in my life. That is a privileged position to be in and I do not forget that privilege. However, I’ve worked since 1989 to get here, so 29+ years of university life has to have been for some non-disposable purpose in my life. I’ve posted before about work-life integration and how I don’t personally recognize a rigid divide between these in my life, but with 24 hours in a day there is a real zero-sum game at play, so I prioritize what I do (or go with the moment).

In non-work mode: Reggie Regent (I’m the lion on the left; not the dog, who was beloved Daisy); high school mascot. A very sweaty one in that suit!

One failure I am working on is to return to fitting in ~2 gym workouts/week into my weekday schedule; that was good when I was doing it a couple of years ago. I have no great excuses for that. Nor would I rely on the “too busy” excuse for anything above — I find the “cult of busy” in academia to be tedious and repugnant (the post linked there is mainly about PhD students but at the faculty academic level such genitalia-sizing-up talk is rife). We all do what we can with our limited time, yet our life-goals are probably not identical, and we probably don’t understand what others do with their time or what constraints they work under.

Dealing with encroaching age and disability has thrown new challenges into my time-budgeting that I am still grappling with. I may want to work (or even need to, beyond the level of overcommitment I’m already in) but sometimes I simply do not have the energy. I don’t give myself guilt and grief for this if I can help it, while I expect that once I do have more energy I’ll devote it appropriately. I respect my limits, much as I confess I still don’t understand them.

As a lifelong learner, I am still learning how to live my life, one day at a time. Everyone lives their life differently. My life now is lived so incredibly differently from how I lived it 20 years ago as a young grad student that I can have a hard time recognizing myself in that scared, scarred, lost, naïve yet still very excited man.

One day that young grad student went into San Francisco, bought a huge teddy bear, and brought it home to cuddle with because he felt so alone. A blues musician on the street saw him carrying that bear and improvised a song mocking him, and he didn’t mind because it was the truth that was captured in that parody, and he was a student of the truth. It was a dark period in that man’s life—a void that was filled with work.

“How, then, can we fail to take the importance of factuality and reality seriously? How can we fail to care about truth? We cannot.”

But now my daughter has inherited that bear and it was worth every dime, every lonely tear, and every hour worked to become the person I am; the only person I can be at this moment, flawed yet ever in flux. Tomorrow will be another day and I will be grateful for those new hours, awake to their prospects and alert to their tribulations.

That was a condensed day in my scientific life and some backstory to it. Thanks for taking your time to read it.

We’ve been through a lot together.

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A personal story here for Darwin Day 2018. I knew about as much about Charles Robert Darwin as any typical science-interested student when I was growing up. But eventually I had the good fortune of taking a history of science class at the University of Wisconsin as an undergrad, and it inspired me with the story of Darwin as a human being, not just some clever scientist with a long argument that changed the world.

Stomach-Churning Rating: 0/10 unless you have Darwin’s gut-wrenching problems.

I devoured Desmond & Moore’s amazing biography of Darwin “the tormented evolutionist”, which was the transformative event for me. At the time I was experiencing the beginnings of some health problems that didn’t seem that far from problems Darwin suffered for much of his life, and then, as I read more about his life, I saw more features of this man that brought him vividly to life. I still think about those traits and how some parallel my life in certain ways (not that I am in any way a giant of science like him!!). And so this blog post was born, thusly:

I’m writing this post early on Darwin Day and entirely from memory, rather than doing my usual research into the post while I go; to keep the post more personal and less academic (e.g. just quick Wikipedia links below). I feel connected to Darwin’s life experience because, like him, I wandered about as a student, unsure about my direction in life and causing my parents some consternation early on. He tried medical school (Edinburgh; too bloody) and theology (Cambridge; faith just was not his thing) but found hunting for beetles on the heaths more exciting. In high school I played with ideas such as Hollywood screen-writing (too risky), radio DJ (I had no skills) and truant or criminal (I hung out with some shady characters even though I still had some morals; despite transgressions and convictions).

I then took a standardized “what is your best career fit?” test in biology class which conclusively told me that biology was best for me as a career; and that rang true. I’d always loved nature and so that was the idea I had when I went to undergrad. I signed up for the wrong college (Agriculture & Life Sciences, not Letters & Science; confusing divisions!) at the UW. I got some early research experience in that first college: I tried my hand at raising colonies of Indian mealmoths (Plodia interpunctella; I can still identify them!) and their parasitoid wasps. At that same agricultural lab I got to do my own experiments in a basement wind tunnel over my summer holiday, in which I released those pesky moths to fly down the tunnel toward various kinds of pheromone-based lures, finding that one kind seemed to work best. But I didn’t like that and frankly found agricultural science boring, for me. We didn’t connect, nor did some other lab experiences I had. But I grew from them and still value them (and respect the science and people involved) very much.

I took Evolution and also Functional Morphology courses, didn’t do great (I was young for the classes), and then finally took that history class—boom! Aha, scientists can be human! Not just hypothesis-robots! Darwin was a man of great privilege, having his estate and wealth handed down from his funky grandpa Erasmus and stern father Robert. But, in addition to his meanderings that eventually forced him (via his father’s impatient urgings) to become the Beagle’s naturalist for a five year voyage, he suffered in quite human ways throughout much of his life. The greater trials commenced during that voyage, with still-mysterious health problems and the fractious relationship with eccentric Captain Fitzroy. They continued with his marriage to cousin Emma Wedgwood (yes, of that pottery-famed lineage) in which they lost four of ten children at young ages (most critically, beloved Annie at 10 years old) and in which they struggled with Darwin’s diminishing faith and Emma’s stalwart beliefs.

Finally, Darwin struggled famously with his “big book” for >20 years, afraid of its impact and its reception, and of its need to have a watertight, evidence-based argument from many perspectives, with his hand forced by Alfred Russel Wallace’s converging ideas. Along the way, with his health and family problems, he had to contend with his mentors’ and peers’ reactions to his ideas—although one could call the acceptance of much of his main arguments to be a “happy ending” (the post-mortem eclipse of Darwinism, and its eventual resurrection + syntheses, aside). These trials that Darwin faced as a human are all relatable, and the more one learns about him the more complex, flawed, emotional and yes, tormented he becomes. He can be both a hero and a tragic figure or a cautionary tale.

When I get the chance, I like to teach students about this human side of Darwin. It is a way into the heart of the science, to show a person’s journey along with the wonder of discovery, and how such a journey is not necessarily a simple or even joyful one. I can feel the many facets of Darwin in my own life—the intensely curious, peripatetic, enthusiastic young man who loved experiencing nature in all its raw forms, the chronically suffering disabled person who sometimes could not enjoy the work or other aspects of life that he treasured, the family man who loved time at home, the explorer who treasured roaming the local heath or far-flung foreign terrain, the meticulous scientist who exhaustively gathered tiny bits of data in isolated studies to slowly build toward grander ideas, and much more.

But Darwin is a different human, too. We live in such different times, when there the world of science is far larger but the world feels far smaller, more interconnected. Naturalists today are not simply landed noblemen who can play with science in their luxurious spare time, nor do they work alone at their pursuits. Anyone can be a scientist, and a career scientist can, if they are fortunate and skilled enough, assemble their own laboratory in which they lead a team to tackle their big questions that captivate them. The individual questions in science tend to be smaller (more incremental and specialized) today, yet can overall (across career(s)) be bigger because we can tackle -and have tackled- some of the bigger ones; Darwin’s big questions being among the giant ideas we are now poised upon.

It’s not all about science, though. Darwin’s story, which I think about so often, reminds me of how we all struggle in our lives and amidst the joy of discovery in everyday life there can be considerable suffering and regret. It is a bittersweet story; an ever-so-human story. And today is a good day to reflect on that, and to celebrate life while we lament what has been lost.

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This week we conducted wallaby leg dissections for a study of the kneecaps of marsupials (pouched mammals). Placental (non-pouched) mammals like us almost all have bony kneecaps but many marsupials do not. Kneecaps do important things, acting like gears around the knee joints (e.g. this old post), and yet it is unclear why some marsupials have lost, kept or even re-evolved them as bones. So we’re investigating that and already noticed that one of our wallabies has bony kneecap(s) whereas the other doesn’t, so we’re checking out why and taking tissue samples to do histology (sectioning for microscopic imaging of tissue composition and structure) on so we can see what the knee tendon/kneecap tissues are made of. Some marsupials turn their kneecaps into fibrocartilage rather than bone or tendon and that can be impossible to identify without histology.

The wallabies are small, about 20lbs or so and just take a day or so. Like a turkey. And it’s Thanksgiving today, so here I am with a post about thawing specimens for science, rather than for food. Maybe the title will make sense now.

Stomach-Churning Rating: 7/10; thawed wallaby bits from the get-go.

Thawed lower leg and foot of wallaby. The stickers are for an old study that would take too long to explain…

This post was directly inspired by journalist Jason Bittel’s inquiry to me about my tweet on the wallaby thawing; he wondered if there might be a fun story linking thawing-for-science with thawing-for-Thanksgiving. Some highfalutin editors didn’t agree, so no printed/online story came of this, but I am not so highfalutin, hence this blog post.

Thawed wallaby forelimbs. I’m also looking into the “false thumbs” that some marsupials have (“sixth fingers”), much as elephants and other mammals may have.

Thawing is second nature for our lab’s team; we do it all the time. Avid readers will be unsurprised to learn that just about everything I’ve worked on has been frozen at some time, and thus has been thawed out at some time(s). Normally we don’t freeze if we need live tissue or undistorted tissue, e.g. to measure physiology or very fine microstructure– freezing disrupts all of that. We would instead use physiological saline solution or else a preservative like formalin. And you can only freeze and then thaw a specimen for two times or so before it becomes too useless even for anatomical study.

A small specimen like this salamander can be thawed out simply by running it under warm water for a little while or leaving it out for an hour.

We just leave specimens in a cart, or on a table or sometimes in a cold-room shelving area, for slower thawing. Space heaters tend to overdo things. We don’t do any rough calculation from some sort of thermodynamic first principles of time-to-thaw vs. specimen size (I wish we were that smart!); just seat-of-pants guessing and checking (yes, poking specimens to check their thawedness is a method of choice). Cutting things in half along the way, or skinning them, may be used to accelerate the thawing process. But it’s about as unscientific a method as we use.

The hardest specimens to thaw of course have been the largest specimens. Elephant legs can be >2 metres long and hundreds of kilograms (especially when frozen). A week at room temperature tends to work OK for getting them to a dissectable state. One has to balance the outer deterioration with the inner frigidness. We’re not so concerned about microbe growth in most cases, as one would be with a thawing turkey, and not at all about consumption. We just want to be able to dissect it and make observations, mostly via eyeballing the specimens as we dissect them,

Left hindfoot of an Asian elephant. Still frozen; this was bandthawed- I mean bandsawed- to see its internal anatomy nice and clearly. You may see this specimen again somewhere else– stay tuned! 🙂

Moisture and fluids can be a challenge: generally the rooms we thaw in are low humidity so moisture may not be an issue once the ice melts away, and we have drains nearby. We try to remove ice first or have towels to wipe/soak fluids up as thawing progresses. But if a specimen is sitting in a cart or storage bag with too much ice early on, that can thaw first and then turn the specimen into a nasty slurry of the stuff you’re interested in and the less desirable muck. So we try to avoid that.

De-thawing too early is bad. The smell gets progressively worse– and once the interior of the specimen is thawed enough, then bacteria get in there and the interior becomes a brewing ground for heat production (rather than remaining a cooler region), which accelerates decay, so we don’t want that. We have to check on thawing specimens regularly and move them to cooler storage areas, or begin dissection earlier, if the decay process is noticeably getting excessive.

Any insulation affects thawing time- so scales, feathers, thick skin, shells, fat (for a short while until it decays), and other layers will slow thawing—and may keep heat inside, if there begins to be thawing of the core. So sometimes you open up a specimen that seems dry and clean on the outside and the inside is unpleasant. But with experience that is not hard to avoid.

Thawed wallaby patella prepared for histology.

The foulest specimen I’ve thawed by far was a monitor lizard… it was shipped to me in California from Arizona when I was a PhD student. This was in August’s heat and the box of the big lizard sat thawing at the post office for 2 weeks before they contacted me and asked why a smelly box was bleeding. I came and got it and brought it back to our department but the smell was so bad it set off our building health & safety person’s alarm bells (sorry, David!) and they emailed around a “toxic alert” warning, until I bashfully made it clear that my lizard was the cause, not some toxic chemical. I got in some trouble and was very ashamed. But we put the specimen into a big tank of brine solution and the smell was reduced—the specimen may well still be preserved there 20 years later; I do wonder! Anyway, that experience was so horrendous – and I have a strong stomach—that I regularly recall it and seek to avoid a repeat. It was the most disgusting thing I’ve ever experienced. I do not recommend it.

What we tend to want to get from thawed specimens is: (1) descriptive anatomy (what connects where), and maybe (2) quantitative measurements (laborious metrics of “muscle architecture”– how much does each muscle weigh, how long is it, etc; over and over again for many muscles…). These data not only serve to tell us what makes animals different (and how this evolved) but also the data are used to test questions such as how animals work. In the case of things like wallabies, ultimately we’d love to know what their kneecaps do if they are bony or not; what difference does it make and why might there be differences? We’d spotted one wallaby already that seemed to have a bony kneecap on one leg, and a non-bony one on the other leg, so that asymmetry got us excited.

What’s surprising to learn about thawing animals for science? Well, my first thought is that it’s beautiful. I don’t tend to think of it as gross. I’ve rhapsodized about this before. Animals are wonderful inside and out, and I regularly pause during a dissection to marvel at how amazing the anatomical specializations of animals are. Simple details- shapes, colours, configurations- can be gorgeous. (Often the blood is minimal, drained out early, so that doesn’t detract from or hide the detailed imagery) The gentle yet complex path of a tendon around a joint can yield profound visual enchantment in its elegance. This is all the more true once one ponders how these complex structures evolved, and how much diversity of form and function is out there to study—and how little we know about it! We still don’t know well how to fix many problems humans have with their anatomy, and that’s orders of magnitude worst for most animals, because we don’t understand how anatomy works, or even what the anatomy is like in some cases. So that keeps me busy discovering things. Every specimen is different with surprising little variations, or big ones—sometimes there is one muscle, sometimes it is clearly divided into two muscles, in the same species or even the left vs. right legs. I love seeing those intricacies and wondering about them.

Thawed wallaby shank sliced open to show lovely digital flexors and gastrocnemius muscles. So many questions are raised by this!

If you’re thawing for Thanksgiving, or thawing for science, or thawing out family relations during a gathering, or thawing yourself out from the winter’s cold– my best wishes to you! May we all enjoy what we thaw.

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It has been almost three months since my last post here, and things have fallen quiet on our sister blog Anatomy to You, too. I thought it was time for an update, which is mostly a summary of stuff we’ve been doing on my team, but also featuring some interesting images if you stick around. The relative silence here has partly been due to me giving myself some nice holiday time w/family in L.A., then having surgery to fix my right shoulder, then recovering from that and some complications (still underway, but the fact that I am doing this post is itself evidence of recovery).

Stomach-Churning Rating: 4/10; semi-gruesome x-rays of me and hippo bits at the end, but just bones really.

X-ray of my right shoulder from frontal view, unlabelled

X-ray of my right shoulder from frontal view, unlabelled

Labelled x-ray

Labelled x-ray

So my priorities shifted to those things and to what work priorities most badly needed my limited energy and time. I’ve also felt that, especially since my health has had its two-year rough patch, this blog has been quieter and less interactive than it used to be, but that is the nature of things and maybe part of a broader trend in blogs, too. My creative juices in terms of social media just haven’t been at their ~2011-2014 levels but much is out of my control, and I am hopeful that time will reverse that trend. Enough about all this. I want to talk about science for the rest of this post.

My team, and collaborators as well, have published six recent studies that are very relevant to this blog’s theme- how about we run through them quickly? OK then.

  1. Panagiotopoulou, O., Pataky, T.C., Day, M., Hensman, M.C., Hensman, S., Hutchinson, J.R., Clemente, C.J. 2016. Foot pressure distributions during walking in African elephants (Loxodonta africana). Royal Society Open Science 3: 160203.

Our Australian collaborators got five African elephants together in Limpopo, South Africa and walked them over pressure-measuring mats, mimicking our 2012 study of Asian elephants. While sample sizes were too limited to say much statistically, in qualitatively descriptive terms we didn’t find striking differences between the two species’ foot pressure patterns. I particularly like how the centre of pressure of each foot (i.e. abstracting all regional pressures down to one mean point over time) followed essentially the same pattern in our African and Asian elephants, with a variable heelstrike concentration that then moved forward throughout the step, and finally moved toward the outer (3rd-5th; especially 3rd) toes as the foot pushed off the ground, as below.

African elephant foot COP traces vs. time in red; Asian elephant in orange. Left and right forefeet above; hindfeet below.

African elephant foot COP traces vs. time in red; Asian elephant in orange-yellow. Left and right forefeet above; hindfeet below.

Gradually, this work is moving the field toward better ability to use similar techniques to compare elephant foot mechanics among species, individuals, or over time– especially with the potential of using this method (popular in human clinical gait labs) to monitor foot (and broader musculoskeletal) health in elephants. I am hopeful that a difference can be made, and the basic science we’ve done to date will be a foundation for that.

  1. Panagiotopoulou, O., Rankin, J.W., Gatesy, S.M., Hutchinson, J.R. 2016. A preliminary case study of the effect of shoe-wearing on the biomechanics of a horse’s foot. PeerJ 4: e2164.

Finally, about six years after we collected some very challenging experimental data in our lab, we’ve published our first study on them. It’s a methodological study of one horse, not something one can hang any hats on statistically, but we threw the “kitchen sink” of biomechanics at that horse (harmlessly!) by combining standard in vivo forceplate analysis with “XROMM” (scientific rotoscopy with biplanar fluoroscopy or “x-ray video”) to conduct dynamic analysis of forefoot joint motions and forces (with and without horseshoes on the horse), and then to use these data as input values for finite element analysis (FEA) of estimated skeletal stresses and strains. This method sets the stage for some even more ambitious comparative studies that we’re finishing up now. And it is not in short supply of cool biomechanical, anatomical images so here ya go:

fig5-vonmises

Above: The toe bones (phalanges) of our horse’s forefoot in dorsal (cranial/front) view, from our FEA results, with hot colours showing higher relative stresses- in this case, hinting (but not demonstrating statistically) that wearing horseshoes might increase stresses in some regions on the feet. But more convincingly, showing that we have a scientific workflow set up to do these kinds of biomechanical calculations from experiments to computer models and simulations, which was not trivial.

And a cool XROMM video of our horse’s foot motions:

  1. Bates, K.T., Mannion, P.D., Falkingham, P.L., Brusatte, S.L., Hutchinson, J.R., Otero, A., Sellers, W.I., Sullivan, C., Stevens, K.A., Allen, V. 2016. Temporal and phylogenetic evolution of the sauropod dinosaur body plan. Royal Society Open Science 3: 150636.

I had the good fortune of joining a big international team of sauropod experts to look at how the shapes and sizes of body segments in sauropods evolved and how those influenced the position of the body’s centre of mass, similar to what we did earlier with theropod dinosaurs. My role was minor but I enjoyed the study (despite a rough ride with some early reviews) and the final product is one cool paper in my opinion. Here’s an example:

fig6a-bates-sauropod-com-evol

The (embiggenable-by-clicking) plot shows that early dinosaurs shifted their centre of mass (COM) backwards (maybe related to becoming bipedal?) and then sauropods shifted the COM forwards again (i.e. toward their forelimbs and heads) throughout much of their evolution. This was related to quadrupedalism and giant size as well as to evolving a longer neck; which makes sense (and I’m glad the data broadly supported it). But it is also a reminder that not all sauropods moved in the same ways- the change of COM would have required changes in how they moved. There was also plenty of methodological nuance here to cover all the uncertainties but for that, see the 17 page paper and 86 pages of supplementary material…

  1. Randau, M., Goswami, A., Hutchinson, J.R., Cuff, A.R., Pierce, S.E. 2016. Cryptic complexity in felid vertebral evolution: shape differentiation and allometry of the axial skeleton. Zoological Journal of the Linnean Society 178:183-202.

Back in 2011, Stephanie Pierce, Jenny Clack and I tried some simple linear morphometrics (shape analysis) to see how pinniped (seal, walrus, etc) mammals changed their vertebral morphology with size and regionally across their backbones. Now in this new study, with “Team Cat” assembled, PhD student Marcela Randau collected her own big dataset for felid (cat) backbones and applied some even fancier techniques to see how cat spines change their shape and size. We found that overall the vertebrae tended to get relatively more robust in larger cats, helping to resist gravity and other forces, and that cats with different ecologies across the arboreal-to-terrestrial spectrum also changed their (lumbar) vertebral shape differently. Now Marcela’s work is diving even deeper into these issues; stay tuned…

fig2-randau-measurements

Example measurements taken on felid vertebrae, from the neck (A-F) to the lumbar region (G-J), using a cheetah skeleton.

  1. Charles, J.P., Cappellari, O., Spence, A.J., Hutchinson, J.R., Wells, D.J. 2016. Musculoskeletal geometry, muscle architecture and functional specialisations of the mouse hindlimb. PLOS One 11(4): e0147669.

RVC PhD student James Charles measured the heck out of some normal mice, dissecting their hindlimb muscle anatomy, and using microCT scans produced some gorgeous images of that anatomy too. In the process, he also quantified how each muscle is differently specialized for the ability to produce large forces, rapid contractions or fine control. Those data were essential for the next study, where we got more computational!

mouse-mimics

  1. Charles, J.P., Cappellari, O., Spence, A.J., Wells, D.J., Hutchinson, J.R. 2016. Muscle moment arms and sensitivity analysis of a mouse hindlimb musculoskeletal model. Journal of Anatomy 229:514–535.

James wrangled together a lovely musculoskeletal model of our representative mouse subject’s hindlimb in the SIMM software that my team uses for these kinds of biomechanical analyses. As we normally do as a first step, we used the model to estimate things that are hard to measure directly, such as the leverages (moment arms) of each individual muscle and how those change with limb posture (which can produce variable gearing of muscles around joints). James has his PhD viva (defense) next week so good luck James!

mouse-simm

The horse and mouse papers are exemplars of what my team now does routinely. For about 15 years now, I’ve been building my team toward doing these kinds of fusion of data from anatomy, experimental biomechanics, musculoskeletal and other models, and simulation (i.e. estimating unmeasurable parameters by telling a model to execute a behaviour with a given set of criteria to try to perform well). Big thanks go to collaborator Jeff Rankin for helping us move that along lately. Our ostrich study from earlier this year shows the best example we’ve done yet with this, but there’s plenty more to come.

I am incredibly excited that, now that my team has the tools and expertise built up to do what I’ve long wanted to do, we can finally deliver the goods on the aspirations I had back when I was a postdoc, and which we have put enormous effort into pushing forward since then. In addition to new analyses of horses and mice and other animals, we’ll be trying to push the envelope more with how well we can apply similar methods to extinct animals, which brings new challenges– and evolutionary questions that get me very, very fired up.

Here we are, then; time has brought some changes to my life and work and it will continue to as we pass this juncture. I suspect I’ll look back on 2016 and see it as transformative, but it hasn’t been an easy year either, to say the least. “Draining” is the word that leaps to mind right now—but also “Focused” applies, because I had to try to be that, and sometimes succeeded. I’ve certainly benefited a lot at work from having some talented staff, students and other collaborators cranking out cool papers with me.

I still have time to do other things, too. Once in a while, a cool critter manifests in The Freezers. Check out a hippo foot from a CT scan! It’s not my best scan ever (noisy data) but it shows the anatomy fairly well, and some odd pathologies such as tiny floating lumps of mineralized soft tissue here and there. Lots to puzzle over.

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I still have my original photocopy, from my grad school days circa 1996, of the 1983 Ted Garland classic paper “The relation between maximal running speed and body mass in terrestrial mammals”, festooned with my comments and highlighter pen marks and other scribblings. That paper remains the backbone of many research questions I am interested in today, and I often think about its underlying concepts. Here’s the key scatterplot from that paper, which I could almost replot by hand from memory, it is so full of implications (and can be clicked to embiggen it, perhaps even speedily depending on your internet connection):

Garland 1983- max speed

Stomach-Churning Rating: 1/10; data and their ramifications; offal-free.

The major points (IMO there are less exciting ones about which theoretical scaling model the data best fit) of the paper are: (1) the fastest-running mammals are neither the smallest nor largest, but those around ~100 kg body mass; (2) if you fit a linear equation to the data (see above; hashed line), it seems like speed increases with body mass linearly (with no limit to that increase, within the body mass range of the data), but if you analyze individual groups of mammals they either don’t change speed significantly with size or they get slower– refer back to point #1 and the polynomial regression that is shown in the figure above (curved line). That’s the biological-question-driven science at the core of the paper (with some methods-y questions at their foundation; e.g. should we use a linear or polynomial regression to fit the data? The latter fits best, and gives a different answer from the former, so it matters.).

But what also fascinates me is the question of data. As the author, who taught me Evolution as an undergrad at U Wisconsin (this had a big impact on me), fully admits in the paper, the ~3-page table of data “necessarily sacrifices some accuracy for completeness”. This paper is about a big question, how mammal speed changes with size, and so its big question explicitly allows for some slop in the data (I will return to this issue of slop later). But given that very few of the data points have very accurate measurements for speed, or for body mass for that matter, how much can we trust an x-y plot of those data, no matter what method is used? Oh there is so much opportunity here for geeky pedantry and niggling scrutiny of data points, true, but hold on…

Plenty of follow-up papers have mused over that latter question, and spin-off ones. Here are some of their plots, re-analyzing the same or very similar data in different contexts. A look at how these papers examine these data and related questions/methods leads into some avenues of science that fascinate me:

Garland 1988- max perf

Garland and Baudinette (link to pdf here) checked whether placental (i.e. most; including us) mammals could run/hop faster than marsupial (pouched; e.g. kangaroos) mammals. Their results said “not really”, as the plot intimates. Scatter in the data, especially between 0.01-10 kg, confounds the issue- there’s a lot of specialization going on (notably, animals that are very slow for their size, e.g. sloths). But marsupials are not, as had been suggested before, inferior to placentals in some basic way such as running ability.

GarlandJanis1993-Fig5

Above, Garland and Janis 1993 (link to pdf here) examined how the ratio of metatarsal (“sole bones” of the lower end of the leg/foot) vs. femur (thigh bone) length relate to speed, with evolutionary relationships taken into account. The methods (“independent contrasts” and its conceptual kin; I won’t delve into that morass more here!) did not exist for looking at phylogeny’s effects on the results in Garland’s 1983 paper. Yet “cursoriality” (relative elongation of the lower limb) had been thought to relate to running speed for over 80 years at that time, so that was what they tested: how much does limb-elongation correlate in a positive way with maximal running speed? They found that the answer was “sort of”, but that other things like home range size, energetics, ecology, etc. might explain as much/more, so caveat emptor. And by looking at the plot above, it’s evident that there’s a lot of specialization (scatter, along the x and/or y axes– check out the giraffe/Giraffa and cheetah/Acinonyx outliers, for example). While ungulates seemed to have a better relationship of speed and limb dimensions, their predatory carnivoran relatives did not.Christiansen 2002- max speed

Christiansen was one of two studies in 2002 that looked back on those Garland 1983 data in a new way, and like the 1993 study with Janis considered these data in light of limb lengths too.  The plot above delved into how running speed changes with lengths of forelimb bones, again finding appreciable curvilinearity (indirectly supporting the non-linear scaling idea– even at large sizes, relatively longer-legged mammals aren’t faster). The plot on the right side (b) measured the relative length of the olecranon process; the “funny bone” that acts as a lever for support of the elbow joint against gravity. Again, even mammals that have stouter elbow-supporting processes aren’t faster; there’s a “happy medium” of elbow-osity for optimizing running speed (and huge scatter in the data!). Ultimately, this analysis concluded that it wasn’t speed that animal anatomy seemed to be optimizing overall, especially as size increased, but rather energetic cost, although there was a lot of variation in the data and accounting for phylogeny only muddled things up more (as it tends to do).

diaz2002

Iriarte-Diaz was the other 2002 study to tackle the speed-vs-size issue. It focused primarily on whether mammal speeds showed “differential” (i.e. non-linear) scaling with size, as per the polynomial regression in Garland’s 1983 study. It showed that smaller mammals seemed to either get slightly slower with increasing size or else not change maximal speed (depending on detailed methods/data stuff that don’t matter here), whereas bigger mammals exhibited very strong declines of speed with size past a threshold (optimal) body mass.

So, repeated analyses of Garland’s 1983 data (and modifications of those data) at least uphold the fundamental conclusion that big land mammals cannot move quickly, in an absolute sense (meters/sec or kph or mph) — and much more so in a relative sense (e.g. body lengths/second or other normalized metrics). We might then ask why, and my research scrutinizes this issue in terms of the fundamental mechanisms of movement biomechanics and anatomy that might help to explain why, but for brevity I won’t go there in this post. I want to wander elsewhere.

I want to wander back to those data used in the above (and other) studies. All of the studies discuss the quality of the data and bemoan the lack of quality. I’d agree with them that it’s hard to imagine most of the data being consistently off in a biased way that would fundamentally alter their conclusions. But I still worry. We should worry about the data points for the extreme animals- the fastest, slowest, largest and smallest. We should worry about subjectively removing “outliers” such as hippos or cheetahs, as they do change some of the results.

I worry about elephants, for example: my work has shown that they can “run” about 7 meters/second or ~25 kph; not the 35 kph used as data for African elephants (from speedometer-y anecdotal estimates)– ~1.4 times the speed we’ve been able to measure for both species. See this old “blog post” (sort of) for more information on the tortuous history of characterizing elephant speeds and gaits. And are a white rhino and hippo able to run at this same 25 kph speed as the original data in the 1983 study state, or faster/slower? No one has really nicely measured this so we can’t be sure, but I can imagine it being off by a similar 40% or so. On the other hand, if the bigger animals in the dataset are slower than the original data, that actually strengthens the conclusion that bigger animals are slower, so who cares that much, in the grand scheme of things?

We could worry about plenty of other maximal speed data points, and the “average” adult body masses assumed (although I doubt those would change the results as much as the speed errors). Maybe another question is, in doing such broad-scale analyses should we only include data points that have maximal precision (e.g. elephants, horses, cheetahs, greyhounds, humans and a few others)? We’d maybe be able to do a study of 20 or so species. I doubt it would show much that is different if we did, although I expect that sample size and noise would begin to dampen out the signal. See below.

However, a double standard begins to become evident here. In modern biomechanics (and probably the rest of biology/science), there’s a strong emphasis on data quality and technologically precise measurement. Garland’s 1983 study might be hard to get past peer review today (or maybe not). We agonize over single-species studies trying hard to measure animals’ maximal speeds (a very hard thing to be sure of in terms of motivation, but not intractable unless one takes an almost antiscientific/overly cynical view that animals could always be holding back some critical reserve unless they run for their lives– is that reserve 1%, 10% or 100%? Probably closer to the middle, in good studies). We measure multiple animals and many trials, in field and/or lab conditions, with documented video footage at high resolution and frame rate, with GPS tracking or other tools to maximize precision. We take pride in these high standards today. That’s what makes scientists wriggle uncomfortably when we look back at the data in those older maximal speed papers and ponder how few data points are verified, documented, precise and essentially trustworthy.

So should broad studies be working by the same standards as narrow studies? (I’m far, far, far from the first scientist to think about this but it’s interesting for me at least to think about it in this case and others) There is potential tension here between empiricists who want precise data and theoreticians who want to tackle those Big Questions, and that’s a pattern one can see throughout much of science. I sit on the fence myself, doing both approaches. I can think of plenty of similar examples, in “big data” palaeobiology, morphometrics, genomics, physics and so on. Some of those fields have nice databases with quality control over the data; they’ve maybe solved this problem to a large degree. This tiny area of mammalian maximal speeds hasn’t solved it, but how urgent is the need to?

On the flip side, even if the data points have some error of 10-20% or even 40% that error will probably be largely random, not biased toward assuming that bigger or smaller animals are slower than they truly are, or medium-sized animals faster. We still have the reliable cheetah data point (and racehorses, and greyhounds) showing >100 kph (and 70 kph) speeds for ~100 (and ~40, 400ish) kg animals, so there is evidence for a peak of maximal speed (the cheetah outlier, and one might also throw in pronghorn antelope or others that are pretty damn fast but not yet well measured) at medium body size. I expect there would be incremental overall progress if we did improve the data quality, and that would still be nice (comforting!) but it would be a tough, tough slog. Indeed, my team is doing its share of that, already tackling the data point for giraffes this year (stay tuned!). The potential gains are still there, especially for understanding the unique biology of individual species– that noise in the data (or specialization, if you prefer) is interesting!!! We need that kind of work, partly because the big questions, sexy as they are, still depend on having data quality as a foundation, and old questions still need revisiting from time to time as data quality is improved by those in the trenches of gathering it.

My team’s journal club has gone over the Garland paper lately and we’re hitting the others later this summer, but I wanted to throw these thoughts out there on this blog now to see if they generated any fun discussion, or they might introduce others to the science of maximal speeds and what we do/don’t know. One thing we don’t know much about is what kinds of patterns non-mammalian groups exhibit today. Chris Clemente did some great work on this with lizards, finding a pattern similar to the mammal one. I’ve struggled in my work to move toward trying to address similar questions for extinct groups, but there the data quality presents a challenge I find exciting rather than depressing, although I still have to shrug when I see limb lengths or proportions being used as a proxy for speed. We can do better.

So I’d love to hear your thoughts on any of the points here. Maybe some of the old-timers have stories from ye olden days when Garland’s work was originally published; I’d love to hear those, or other points/questions/favourite papers.

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