For instance, the high five.
Jacked from gifbin.com.
Update: Matt Brandley has just unearthed additional evidence courtesy of Cute Overload:
I’m about to start making a lot of posts about niche and distribution modeling as the project I’m working on for the California Department of Fish and Game nears completion. The point of this project is to build correlative models of species ecological tolerances and to use those to predict the effects of climate change on the distribution of suitable habitat for terrestrial vertebrate species that have been designated as “species of special concern”. I would really like for this work to be understandable by non-specialists as well as specialists, so I’m going to start by making some introductory posts that just explain what I’ve been doing and why.
In order to understand the effects of climate change on suitability of habitat for a species, we need to know what exactly causes habitat to be more or less suitable for that species. Does it like high temperatures or low temperatures? Is the maximum temperature more important than the average temperature? Does it like wet or dry environments? Can it tolerate higher temperatures when it’s wet than when it’s cold (i.e., are its tolerances for environmental factors correlated)? Which environmental factors are important and which are unimportant?
What we really want to know is a thing called the species’ fundamental niche. This is the range of environments within which that species can maintain a population that reproduces frequently enough that the population does not shrink. The fundamental niche does not consider interactions between species or the ability of species to disperse to different patches of habitat, it only considers what sets of environmental factors a species can tolerate. For the sake of illustration, we’re going to talk about the fundamental niche of a cartoon frog:
Here we see an environmental space in two variables: average temperature and annual precipitation. Within the set of environments circumscribed by the green ellipse, the frog is happy, so happy that it’s reproducing at a sufficient rate to persist. Outside of the green area the frog is not so happy. Far enough outside of the green ellipse, the frog is dead. In order to know whether a particular habitat is suitable for our frog, all we need to know is whether or not it falls inside that green ellipse. Easy, right?
The answer is “no, not at all”. It turns out to be a very difficult question.
One possible approach to answering this question is to grab a bunch of our frogs and bring them into the lab. We can then raise them in a range of temperatures, keeping everything else constant.
We see that our frog does okay when it’s not too hot or too cold, and we can get some idea of what the range of its temperature tolerances is. Then we can do the same for precipitation:
So what’s the problem with this physiological approach to estimating species tolerances? Well, it’s actually been a very productive area of research, but there are some issues that limit what we can do with this approach. One is that the resolution of the experiment is limited by the amount of animals you’re able to raise and your ability to maintain fine differences in the environments they experience. Despite my little cartoons here, you can’t really just do this with one frog in each box. You need quite a few so that you can average over all of the statistical noise that’s created by differences between individual frogs and the unavoidable effects of random chance. In the example above, let’s pretend that each one of those precipitation boxes corresponds to one more foot of rain per year. Zero and one foot per year are unsuitable, as is anything over seven. But how about six and a half? One and a half? We actually can’t tell where the cutoff is because the resolution is too low! Assuming we’ve got ten frogs per box, we’ve already used a hundred frogs only to find that we can only estimate their tolerances to the nearest foot.
There’s another problem, though. Remember our frog’s fundamental niche?
That ellipse has a tilt to it, such that our frogs can handle higher temperatures when there is more precipitation. By examining one environmental variable at a time, there is no way that we can detect this correlation. Essentially our study looks like the following figure:
We’ve fixed the precipitation at some value, and then we’ve seen that the frog can handle a range of temperatures given that value of precipitation. However, we can’t necessarily extrapolate that to the entire range of values that the frog could tolerate. If we had fixed the precipitation value lower, our frog would have been less able to tolerate high temperatures and more able to tolerate low temperatures than what we observed. If we had fixed the precipitation value higher, the opposite would have been true! In order to really understand the species’ tolerance for temperature, we have to examine it over a range of precipitations at the same time. Something like this:
Notice the big problem? With even the coarse resolution of our experiments (ten treatments per environmental axis), we’ve now got a hundred experiments to conduct! If we’re doing ten frogs per experiment, we now have a thousand frogs to take care of. The addition of more variables compounds the problem – with three variables we’d need a thousand treatments and ten thousand frogs, four variables requires ten thousand treatments and a hundred thousand frogs, etc. We’re going to run out of frog chow and research assistants fairly quickly at this rate.
So far we’ve been talking about frogs. Frogs are relatively easy to keep in boxes, but that’s not true of every animal. Picture the above discussion with elephants substituted for frogs and you quickly see that the enterprise is over before it begins – we simply don’t have enough elephant-sized aquaria to make even a low resolution study practical. There’s also the fact that these experiments may require more individuals than a natural population can spare – if you want to know the environmental tolerances of a species that is only represented by 500 surviving individuals, no governing body is going to give you license to catch half of the extant population and raise them in the lab, particularly in a set of experiments that may result in some of them dying or at the very least failing to reproduce to their maximum capacity. Finally, consider that some environmental variables that are relevant to a species may be very difficult to manipulate in a laboratory setting.
I don’t want to be misconstrued here – physiological studies of the niche such as those presented here (albeit in cartoon form) are among the most reliable methods for estimating a species’ environmental tolerances. The above is simply to point out that there are practical limitations to the resolution and complexity of the niche estimates that can be produced this way. The traditional infomercial approach at this point would have me saying “THERE’S GOT TO BE A BETTER WAY”, at which point I would expound on the glory that is niche modeling. However, I do not want to imply that niche modeling is a better approach than physiological studies – in many ways, it is significantly inferior. However, there are some limitations of physiological studies that niche modeling does not share, and there are times when the lack of those limitations is of great importance (e.g., you can easily build a niche model for elephants using a correlational approach, while a physiological approach would be quite difficult). Niche modeling does have its own limitations, however, and I’ll talk about some of those as we go on.
In my next post, I’ll talk about what the correlational niche modeling approach is, and how it overcomes some of the issues mentioned here. In later posts I’ll talk about a whole slew of new methodological issues that the correlational approach raises.
National Geographic has a nice review of the evolution of viviparity in skinks. It summarizes a recent paper by Jim Stewart et al. investigating the morphology and histology of the egg shell and calcium-producing glands in the uterus of the skink, Saiphos equalis.
Saiphos equalis is rare because there exist both oviparous and viviparous populations. Because viviparity must have evolved very recently in this species, S. equalis is therefore a great model system to see this transition of reproductive mode in action.
The story is particularly relevant to me since I have just begun a post-doc at the University of Sydney to study the genetic mechanisms of viviparity in S. equalis with one of the paper’s co-authors, Mike Thompson.
If you think about the transition from laying eggs to giving live birth, it becomes clear that it must have involved some significant morphological and physiological changes including retention of the embryo within the mother until gestation is complete, increasing uterine blood supply to facilitate nutrient and gas exchange with the embryo, potentially suppressing the maternal immune system to prevent rejection of the embryo, and reduction of the calcareous eggshell.
The latter process is particularly interesting because it requires a significant physiological modification of the shell-producing glands. Instead of quickly dumping a bunch of calcium to form an eggshell, the glands in viviparous mothers must instead slowly secrete calcium to nourish the developing embryo during the entire period of gestation.
Stewart et al. found that the thickness of the developing eggshell in the uterus of viviparous mothers is thinner and less developed than those in the oviparous mothers at the same stage of embryonic development. However, they also found that this is not due to the size of the shell-producing glands (i.e., bigger glands = thicker shell), and therefore some other mechanism must be responsible for the physiological changes of shell glands in viviparous mothers.
In other words, we see the hypothesized first steps to viviparity – holding embryos for an extended period of time and reducing the unnecessary eggshell.
What genetic mechanisms underlie this shift in reproductive mode? Check back with me in a year or so.
One of the things Teresa and I are working on in Curacao is a study of sperm motility in bluehead wrasses (Thalassoma bifasciatum). I’ll talk about why that’s interesting eventually, once we get some of the results out. One of the hard bits of doing this study is that blueheads don’t manufacture sperm in captivity – we figured out very early on that they just shut down production after a couple of days, and fish from the pet trade therefore have no motile sperm to study.
Obviously, we need to be able to measure sperm motility in the field. There are commercial setups out there that you can buy for sperm motility, but they have several disadvantages: they’re not very portable, they’re expensive as all-get-out, and most importantly they’re (last I checked) not very flexible in the types of video you can analyze or the timing of the analysis windows. It’s been several years since I played with a Hamilton-Thorne system, but at that time you could only specify an analysis window by manually hitting “start” and “stop”. That’s worthless for my study because of the short motility period of bluehead wrasses – their sperm are motile for a very short period (~15 seconds!), and those little suckers are FAST. I need to be able to analyze very precise time slices post-activation, and the HT system just couldn’t do that last time I checked.
So, in the great scientific tradition, I bodged something together. This setup is the fourth such that I’ve put together, and is by far the nicest. Earlier versions involved CCDs and video capture direct to the laptop, but the data produced by those setups was nowhere near as nice as what I’m getting with this arrangement. So, without further ado, here we are:
The first thing we need is a microscope. I chose a fairly cheap model from AmScope for a couple of reasons: theft is rampant in Curacao and I don’t feel like losing a really nice scope, for one. More to the point, though, I’m setting this up out of my own very limited funds and AmScope makes astonishingly nice hardware for the money. Certainly sufficient for my needs. This particular scope is their T400A-30W-DK model. They have another model that looks better on paper, as it has an adjustable photo port. However, the adjustable port is only adjustable within a range of distances that vary from “useless” to “uselesser”: the focal distance is only suitable for cameras where the CCD is actually down inside the photo port, and I didn’t own a single CCD that worked. In fact, I don’t know of a good video camera that does have a CCD that will fit in there. The 400A can also fit into this kickass aluminum case:
Which the other model can’t. Just look at that case. I want to handcuff it to my wrist and walk around with sunglasses on. It also does a great job of keeping the scope in working order despite being kicked around aiports, fondled by security guards, and bashed into all sorts of things (including my face on the return trip).
Okay, we’ve got a scope and a case, we can look at some sperm. However, what we really need is some really good video. As mentioned above, I was initially getting video to my laptop using a variety of CCD cameras and a USB video capture device. This works, but there are several issues to deal with. For one thing, the resolution and framerate of most of the affordable CCDs is awful for sperm motility. Sure, you can buy an HD CCD if you want to shell out the dough, but then you have to buy an HD capture solution for your laptop and those are (a) hard to find and (b) damned expensive. The low-res solutions are also usually putting out interlaced video, which is problematic for sperm motility analysis – it adds uncertainty to the motility parameters if you use the video raw, and all of the deinterlacing programs I tried led to positional artifacts that were worse than the interlacing itself (e.g., I’d get a nice deinterlaced picture, but the sperm was jumping back and forth between frames).
On this trip we decided to leap off of the purpose-built CCD train and try something off the shelf. We’re taking advantage of the fact that Canon’s new T2i DSLR camera allows users to capture hi-def video. The T2i is just an awesome camera all around, but what’s particularly nice for our purposes is that you can buy decent Canon EF -> microcope photo port adapters on Ebay for about $100. By attaching the camera to the adapter and then to the scope, we can shoot hi-def video at a better framerate (720p, 59.94 fps) than the CCD solutions with less fuss and no f*&%ing video capture hardware. Here ’tis:
But there’s one more issue to deal with. This microscope head does not allow users to use the eyepieces and photo port simultaneously. But hey, not a problem! The T2i has an AV out, and we can use a really cute little off-the-shelf portable DVD player as a video monitor. This is the Sony DVP-FX950. It has a higher screen resolution than most portable DVD players, as well as an RCA video input jack. Here it is, waiting for me to shoot some video:
We are getting really excellent results with this setup. The one drawback compared to my old video capture systems is that I don’t have control over the filenames at the time of recording. Because of this, I have to verbally announce the identifying information for each take so that the camera’s microphone will pick it up. That means I’m going to have to go back and rename about 500 video files before I can start analyzing data, but it’s a small price to pay. Speaking of small prices to pay, here’s the rundown for the whole rig:
Amscope microscope model 400A-30W-DK: $419
Aluminum case: $90
Canon T2i camera: $900
Canon EF->photoport adapter: $95
Sony DVP-FX950 portable DVD player: $140
This comes to a grand total of $1644. While that’s a significant dent in my pocketbook, it’s about 3% of the price of one of the Hamilton Thorne systems which, last time I checked, were going for something like $50,000.
Obviously there’s something missing here – the HT systems aren’t just video scopes, they’re analysis packages with software and everything! Never fear, the amazing contributions of the open source scientific software community will come to our rescue there. But that’s another post for another day.
I have no idea. There’s an interesting story about it on Boing Boing, though.
We acquired three new housemates today: Peter Wainwright, Lars Schmitz, and Ron Eytan. There are four or five separate projects going on here right now that have little to do with one another – we’re basically just all doing our own thing and sharing the cost of lodgings. The field station in Willemstad (Carmabi) is not the most comfortable place to stay, but by splitting the rent at Sunshine’s place in Westpunt we can stay in relative comfort for about the same price. It’s a little cramped, but we all like each other.
I’m way behind now, but I’m going to make an effort to catch up. These pics are from Playa Martha, which is located in an abandoned (and wrecked) resort. We’re doing a lot of behavioral observations and catching fish on these dives, so there’s not a lot of time to snap pictures.
Here’s a funny and somewhat sobering infographic about the Ph.D. process, although it could apply just as easily to an entire scientific career. While it’s easy to look at something like this and feel a little insignificant, it’s amazing to think about how many people are simultaneously making their little dents in the big circle of human knowledge, and what the net effect of all of those contributions has been. We may be moving a mountain with a teaspoon, but there are a lot of us with teaspoons!