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Short post here– I have 4 jobs now opened on my team, 1 short-term one (~4 months or less) and 3 long-term ones (5 years; negotiable down to 2-3 minimum) as follows:

Stomach-Churning Rating: -10/10 Let’s do some SCIENCE!

  1. Research Technician in Vertebrate Anatomical Imaging; until ~1 December 2016 (some flexibility), on our Leverhulme Trust sesamoid bone grant. Lots of flexibility here and on a super fun, established project! Deadline to apply: 11 August (interviews will be 22 August)
  2. Part-time (50%) Research Administrator, on our ERC dinosaur evolution/locomotion grant until 2021. I’m hunting for someone that’s super organized and enthusiastic and not afraid of paperwork (it is EU funding, after all), but there is sure to be some involvement in science communication, too. Deadline to apply: 11 August  (interviews will be 31 August)
  3. Research Technician in Biomechanics; until 2021 as above. This post will not “just” be technical support but hands-on doing science. Some vital experience in biomechanics will be needed as the research will begin very quickly after starting. If the right person applies, we could agree for them to do a part-time PhD or MRes related to the grant research (but that’s not guaranteed in advance). Deadline to apply: 26 August (interviews will be 7/8 September)
  4. Postdoctoral Researcher in Biomechanics; until 2021 as above. This second postdoc on the project will join Dr. Vivian Allen and the rest of my team to push this project forward! I am keenest on finding someone who is good at biomechanical computer simulation, i.e., has already published on work in that general area. But the right person with XROMM (digital biplanar fluoroscopy), other digital imaging and biomechanics experience might fit. Deadline to apply: 23 August (interviews will be 7/8 September)

Update: all jobs have closed for applications.

Update 2: BUT not all the jobs are 5-year contracts. Some may open up again for new people in the future (but not very soon). Stay tuned…

Note that on the bottom of each page linked above, there are Person Specification and Job Description documents that explain more what the jobs are about and what skills we’re looking for in applicants. I strongly encourage any applicants to read these before applying. If those documents don’t describe you reasonably well, it is probably best not to apply, but you can always contact me if you’re not sure.

The project for jobs 2-4 is about testing the “locomotor superiority hypothesis”, an old idea that dinosaurs gained dominance in the Triassic-Jurassic transition because something about their locomotion was better in some way than other archosaurs’. That idea has been dismissed, embraced, ignored and otherwise considered by various studies over the past 40+ years but never really well tested. So in we go, with a lot of biomechanical and anatomical tools and ideas to try to (indirectly) test it! As usual for projects that I do, there is a healthy mix of empirical (e.g. experiments) and theoretical (e.g. models/simulations) research to be done.

Please spread the word if you know of someone right for any of these roles. I am casting a broad net. The next year (and beyond) is going to be a very exciting time on my team, with this big ~£1.9M ERC Horizon 2020 grant starting and lots of modelling, simulation, experiments, imaging and more. Non-EU/EEA/UK people are very welcome to apply– “Brexit” is not expected to affect this project. If you’re not familiar with my team, check out my “mission statement” for what we stand for professionally and as a team. Join us!

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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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Last year we finally, after about 14 years of slow work, released our biomechanical model of an ostrich’s hindleg. We showed how it informed us about the potential leverages (moment arms; contributions to mechanical advantage of the joints) of all of the muscles. It was a satisfying moment, to understate it, to finally publish this work from my postdoc at Stanford. Today, we begin to deliver on that model’s promise. And it only took 4 years or so, roughly? The journal Royal Society Interface has published our study of how we used this musculoskeletal model to simulate walking and running dynamics. Those simulations join an intimidatingly broad and complex literature using similar models to study human (and some other primate) locomotion or other functions at the level of individual muscles (for whole limbs/bodies) in vast detail and growing rigor. I have Dr. Jeffery Rankin, a research fellow finishing up his post with me after ~6 years of hard work on many projects, to thank for driving this work forward, and Dr. Jonas Rubenson (now at PennState) for his patient collaboration that has continued since the early 2000’s.

Stomach-Churning Rating: 2/10; computer models of muscle actions. The underlying anatomical data are goopy, as prior ostrich-dissection-focused posts show!

Our model; in right side view (on the left) and frontal view (on the right), with muscles in red and the leg's force as the blue arrow; frozen at the middle of a step.

Our model; in right side view (on the left) and frontal view (on the right), with muscles in red and the leg’s force as the blue arrow; frozen at the middle of a running step.

Simulations like these predict things that we can’t easily measure in living animals, such as how much force muscles and tendons generate, how quickly those tissues change length, how much mechanical energy they thus contribute to the joints, limbs and whole body, how much metabolic energy their actions cost, and much more. There are more ways to use these tools than I have space or time to explain, but simply put we forced our ostrich simulation to match experimental measurements of the motions and forces of a representative walking and running ostrich stride, from contact of one foot until the next time that foot hit the ground. It then used optimization methods (minimizing target criteria like muscle stress) to estimate how the muscles and tendons were used to generate those motions and forces. This is a ways ahead of some prior ostrich simulations such as this one that I recall from classes during my PhD studies.

Any modeller worth their salt knows that their models and simulations are wrong at some level. This is much as most science is “wrong”; i.e. a simplification of reality with some errors/noise introduced by assumptions, variation, methods and such. But generally these kinds of musculoskeletal dynamic simulations hold up pretty well against experimental data. A standard “validation” is to test how closely the simulations’ predictions of muscle activity match the “real” (measured in life, also with some uncertain error) activity of muscles. Science still lacks those data for ostriches, but fortunately measurements from other birds (by Steve Gatesy and colleagues) indicate that muscles tend to follow fairly conservative patterns. Grossly speaking, avian leg muscles tend to either be active mainly when the foot is on the ground (stance phase) or off the ground (swing phase). Some studies acknowledge that this is an oversimplification and other muscles do act across those two phases of a stride, either in multiple pulses or as “transitional” (stance-to-swing or swing-to-stance) switch-hitters in their activations. Our ostrich predictions matched the qualitative patterns for avian muscle activations measured to date, so that’s good. The results also reinforced the notion of transitional or multi-phasic muscle activation as still having some importance, which bears more study.

Yet what did the simulations with our ostrich model tell us that other ostrich experiments or other bird species didn’t? Three main things. First, we could calculate what the primary functions of muscles were; they can act as motors (generating energy), brakes (absorbing energy), springs (bouncing energy back and forth) or struts (just transmitting force). We could then sum up what whole muscle groups were doing overall. The image below shows how these broad functions of groups vary across the stance phase (swing phase is harder to condense here so I’ve left it out).

Positive work can speed things up; negative work can slow things down.

Positive work can speed things up; negative work can slow things down. Solid bars are running; striped bars are walking. (from our Fig. 13) You may need to click to em-broaden this image for the gory biomechanical details.

There’s a lot going on there but a few highlights from that plot are that the hip extensor (antigravity) muscles (biarticular hip/knee “hamstrings”) are acting like motors, the knee extensors (like our quadriceps) are mainly braking as in other animals and the ankle is fairly springy as its tendons (e.g. digital flexors; gastrocnemius) suggest. We often characterize birds as “knee-driven” but it’s more accurate biomechanically to say that their hips drive (power; i.e. act as motors) their motion, whereas their knees still act as brakes — in both cases as in many other land vertebrates. Thus in some ways bird legs don’t work so unusually. Birds like ostriches are, though, a little odd in how much they rely on their hamstring muscles to power locomotion (at the hip) rather than their caudofemoral muscles, which are reduced. Zooming in on some particular muscles such as parts of the hip or knee extensors, the functions sometimes weren’t as predictable as their similar anatomy might suggest. Some muscles had parts that turned on during swing phase and other parts used during stance phase. Neural control and mechanics can produce some unexpected patterns.

Second, we looked at one important methodological issue. Simulations of musculoskeletal dynamics can vary from simple static (assuming each instant of a motion is independent from the others; e.g. ignoring acceleration, inertia, tendon effects, etc.) to more complex grades of fully dynamic flavours (e.g. assuming rigid or flexible tendons). We looked across this spectrum of assumptions, for both walking and running gaits, with the expectation that more static assumptions would work less well (vs. more dynamic ones; by various criteria) for running vs. walking. This also showed us how much tendons influence our simulations’ estimates of muscle mechanics—a fully rigid tendon will make the muscle do all of the work (force times length change) whereas a flexible tendon can literally take up some (or even all) of that slack, allowing muscles to remain closer to their isometric (high force-generating, negligible length change) quasi-optimum.

Nicely, our predicted muscle functions weren’t influenced much by these methodological variations. However, static assumptions  clearly were in some ways less appropriate for running than for walking, as were flexible tendons. Somewhat surprisingly, making the simulations more dynamic didn’t lower the levels of activation (and thus presumably the metabolic costs) of muscles, but actually raised those levels. There are good reasons why this might be realistic but it needs further study. It does muddy the waters for the issue of whether assuming that rapid locomotion can be modelled as static is a “bad” thing such as for estimating maximal speeds—yes, tendons can do more (elastic energy storage, etc.) if more dynamic models are used, but co-contraction of antagonistic muscles against each other also brings in some added costs and might lead to slower speed estimates. We’ll see in future work…

Finally, one often overlooked (sometimes even undiscussed!) aspect of these simulations is that they may silently add in extra forces to help muscles that are struggling to support and move their joints. The justification is typically that these extra “reserve actuators” are passive tissues, bony articular forces and other non-muscular interactions. We found that the hip joint muscles of ostriches were very weak at resisting abduction (drawing the thigh away from the body) and this needed resisting during the stance phase, so our simulations had very high reserve actuators switched on there. That fits the anatomy pretty well and needs more investigation.

Want to know more? Happily, not only is the paper free for anyone to view but so are all of the data including the models (modified slightly from our last paper’s). So, although the software (Opensim) isn’t ideal for 4-year-olds to play with (it is fancy engineering stuff), if you have the interest and dilligence it is there to play with and re-use and all that. But also watch this space for future developments, as there is more to happen with our steadily improving models of ostriches and other beasties. Anyway, while this paper is very technical and challenging to explain I am not too bashful to say it’s one of the finer papers from my career; a big stride forward from what we’ve done before. I have been looking forward for a long time to us getting this paper out.

P.S. Our peer reviewers were splendid- tough but constructive and fair. The paper got a lot better thanks to them.

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My Summer in the SML

Excellent post by a summer research student on my team!

Luke Grinham

I spent this summer, the second of my undergraduate degree, in the Royal Veterinary College’s Structure and Motion Laboratory, as I undertook a BBSRC-funded Summer Research Experience Placement. The purpose of the REP is to give undergrad students a taste of what research would be like as a career. In my case, I was given the fantastic opportunity to study giraffe locomotion. Mentored by Christopher Basu, a PhD student in the SML, and Professor John Hutchinson, my ten-week project began at the start of July.

First things first, I had some ground work to do. All the data had been collected prior to my placement, though I will be joining Chris next week to collect fresh data for his future work. Giraffes were recorded using high speed video cameras walking parallel to the edge of their enclosure, over concealed force-plates measuring ground reaction forces. I was provided with 3 days’…

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Maybe it’s uncool to talk about heroes in science these days, because everyone is poised on others’ shoulders, but “Neill” (Robert McNeill) Alexander is undeniably a hero to many researchers in biomechanics and other strands of biology. Our lab probably wouldn’t exist without his pervasive influence- he has personally inspired many researchers to dive into biomechanics, and he has raised the profile of this field and championed its importance and principles like no other one individual. Often it feels like we’re just refining answers to questions he already answered. His influence extends not only to comparative biomechanics and not only around his UK home, but also –via his many, many books on biology, anatomy and related areas, in addition to his research, editorial work and public engagement with science– to much of the life sciences worldwide.

What does a kneecap (patella) do? Alexander and Dimery 1985, they knew. My team is still trying to figure that out!

What does a kneecap (patella) do? Alexander and Dimery 1985, they knew. 30 years later, my team is still trying to figure that out!

Sure, one could (and with great humility I’m sure Alexander would) mention others like Galileo and Marey and Muybridge and Fenn and Gray and Manter who came before him and did have a profound impact on the field. Alexander can, regardless, easily be mentioned in the same breath as luminaries of muscle physiology such as AV Hill and even Andrew + Julian Huxley. But I think many would agree that Alexander, despite coming later to the field, had a singular impact on this young field of comparative biomechanics. That impact began in the 1970s, when Dick Taylor and colleagues in comparative physiology were also exploding onto the scene with work at the Concord Field Station at Harvard University, and together biomechanics research there, in the UK, elsewhere in Europe and the world truly hit its stride, with momentum continuing today. I’m trying to think of some women who played a major role in the early history of biomechanics but it was characteristically a woefully male-dominated field. That balance has shifted from the 1970s to today, and my generation would cite luminaries such as Mimi Koehl as key influences. There are many female or non-white-male biomechanics researchers today that are stars in the field, so there seems to have been progress in diversifying this discipline’s population.

Hence, honouring Alexander’s impact on science, today our college gave Neill an honorary doctorate of science (DSc). Last year, I also helped organize a symposium at the Society for Vertebrate Paleontology’s conference in Berlin that honoured his impact specifically on palaeontology, too- compare his book “The Dynamics of Dinosaurs and Other Extinct Giants” to current work and you’ll see what fuelled much of that ongoing work, and how far/not far we’ve come since ~1989. Even 10 years later, his “Principles of Animal Locomotion“, with Biewener’s “Animal Locomotion“, remains one of the best books about our field (locomotion-wise; Vogel’s Comparative Biomechanics more broadly) , and his educational CD “How Animals Move“, if you can get it and make it work on your computer, is uniquely wonderful, with games and videos and tutorials that still would hold up well as compelling introductions to animal biomechanics. Indeed, I’ve counted at least 20 books penned by Alexander, including “Bones: The Unity of Form and Function” (under-appreciated, with gorgeous photos of skeletal morphology!).

1970s Alexander, with a sauropod leg.

1970s Alexander, with a sauropod leg.

And then there are the papers. I have no idea how many papers Neill has written –again and again I come across papers of his that I’ve never seen before. I tried to find out from the Leeds website how many papers he has, but they’re equally dumbfounded. I did manage to count 38 publications in Nature, starting in 1963 with “Frontal Foramina and Tripodes of the Characin Crenuchus,” and 6 in Science. So I think we can be safe in assuming that he has written everything that could be written in biomechanics, and we’re just playing catchup to his unique genius.

Seriously though, Alexander has some awesome publications stemming back over 50 years. I’m a big fan of his early work on land animals, such as with Calow in 1973 on “A mechanical analysis of a hind leg of a frog” and his paper “The mechanics of jumping by a dog” in 1974, which did groundbreaking integrations of quantitative anatomy and biomechanics. These papers kickstarted what today is the study of muscle architecture, which our lab (including my team) has published extensively on, for example. They also pioneered the integration of these anatomical data with simple theoretical models of locomotor mechanics, likewise enabling many researchers like me to ride on Alexander’s coattails. Indeed, while biomechanics often tends to veer into the abstract “assume a spherical horse”, away from anatomy and real organisms, Alexander managed to keep a focus on how anatomy and behaviour are related in whole animals, via biomechanics. As an anatomist as well as a biomechanist, I applaud that.

How do muscles work around joints? Alexander and Dimery 1985 figured out some of the key principles.

How do muscles work around joints? Alexander and Dimery 1985 figured out some of the key principles.

Alexander has researched areas as diverse as how fish swim, how dinosaurs ran, how elastic mechanisms make animal movement more efficient, how to model the form and function of animals (see his book “Optima for Animals” for optimization approaches he disseminated, typifying his elegant style of making complex maths seem simple and simple maths impressively powerful) and how animals walk and run, often as sole author. In these and other areas he has codified fundamental principles that help us understand how much in common many species have due to inescapable biomechanical constraints such as gravity, and how these principles can inspire robotic design or improvements in human/animal care such as prosthetics. Neill has also been a passionate science communicator, advising numerous documentaries on television.

~1990s Alexander, with model dinosaurs used to estimate mass and centre of mass.

~1990s Alexander, with model dinosaurs used to estimate mass and centre of mass.

Alexander’s “Dynamics of Dinosaurs” book, one of my favourites in my whole collection, is remarkably accessible in its communication of complex quantitative methods and data, which arguably has enhanced its impact on palaeontologists. Alexander’s other influences on palaeobiology include highly regarded reviews of jaw/feeding mechanics in fossil vertebrates (influencing the future application of finite element analysis to palaeontology), considerations of digestion and other aspects of metabolism, analysis of vertebral joint mechanics, and much more.  Additionally, he conducted pioneering analyses of allometric (size-related) scaling patterns in extant (and extinct; e.g. the moa) animals that continue to be cited today as valuable datasets with influential conclusions, by a wide array of studies including palaeontology—arguably, he helped compel palaeontologists to contribute more new data on extant animals via studies like these.

Neill Alexander did his MSc and PhD at Cambridge, followed by a DSc at the University of Wales, a Lecturer post at Bangor University and finally settling at the University of Leeds in 1969, where he remained until his retirement in 1999, although he maintains a Visiting Professorship there. I had the great pleasure of visiting him at his home in Leeds in 2014; a memory I will treasure forever, as I had the chance to chat 1-on-1 with him for some hours. He has been Secretary of the Zoological Society of London throughout most of the 1990s, President of the Society for Experimental Biology and International Society of Vertebrate Morphologists, long championing the fertile association of biomechanics with zoology, evolutionary biology and anatomy. More recently, he was a main editor of Proceedings of the Royal Society B for six years.

Many people I’ve spoken to about Neill before have stories of how he asked a single simple question at their talk, poster or peer review stage of publication, and how much that excited them to have attracted his sincere interest in their research. They tend to also speak of how that question cut to the core of their research and gave them a facepalm moment where they thought “why didn’t I think of that?”, but how he also asked that question in a nice way that didn’t disembowel them. I think that those recalling such experiences with Neill would agree that he is a professorial Professor: a model of senior mentorship in terms of how he can advise colleagues in a supportive, constructive and warmly authoritative, scholarly way. For a fairly recent example of his uniquely introspective and concise, see the little treasure “Hopes and Fears for Biomechanics”, a ~2005 lecture you can find here. I really like the “Fears” part. I share those fears- and maybe embody them at times…

My visit with RMcNeill Alexander in 2014.

My visit with RMcNeill Alexander in 2014.

Perhaps I have gushed enough, but I could go on! Professor RMcNeill Alexander, to summarise the prodigious extent of his research, is to biomechanics as Darwin is to biology as a whole. One could make a strong case for him being one of the most influential modern biologists. He is recognised for this by his status as a Fellow of the Royal Society (since 1987), and a CBE award, among many other accolades, accreditations and awards. And, if you’ve met him, you know that he is a gentle, humble, naturally curious and enthusiastic chap who instils a feeling of awe nonetheless, and still loves to talk about science and keeps abreast of developments in the field. And as the RVC is honouring Neill today, it is timely for me to honour him in this blog post. There can never be another giant in biomechanics like Alexander, and we should be thankful for the broad scientific shoulders upon which we are now, as a field, poised.

I hope others will chime in with comments below to share their own stories.

 

 

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