Friday, August 7, 2009
Thursday, August 6, 2009
The word extinction means we have fewer plants and animals than we did before. So we're going to need to count things. But what are we counting? Species? Here's a dirty little secret: Paleontologists don't really have a good species concept. Biologists have a pretty good one.
The biological species concept defines a species as members of populations that actually or potentially interbreed in nature, not according to similarity of appearance.To that we probably need to add that the offspring can, themselves, reproduce but you get the idea. Here's the problem.... "similarity of appearance" is really all we have in Paleontology. You take two fossils, put then on a water bed, give them some privacy and cue the Barry White. Come back a month later and there are still just going to be two fossils there. FOSSILS DON'T REPRODUCE. In fact we can't be really sure those two fossils were the opposite sex. (not that there's anything WRONG with same sex fossils) . So what do we do about the species concept in paleontology?... basically we muddle through as best we can mainly relying on appearance.
The diversity curve we've been looking at is a family level curve not a species level curve. For those of you who are taxonomically challenged remember that species' group into genera and genera group into families. Not all families have the same number of species. A family of insects may have hundreds of species. The family we belong to, Hominidae contains us, gorillas, chimpanzees and orangutans. So taking out a family of insects takes out a whole lot more species than taking out a family of primates.
So you've got a bunch of biologists out there defining extinction by counting species and you've got paleontologists counting what are basically morphoptypes. And really most of our work on broad patterns in extinction and radiation is done two taxomic levels up. Comparing those is gong to be very very tricky.
Next up: Taphonomy. Because if you don't understand that you don't understand anything.
Wednesday, August 5, 2009
The point of this really though (you knew there had to be a real point somewhere didn't you) is that I'm about to post up another entry on modern versus ancient extinction and RSS feeds don't usually show past posts. So if you care, go back and read the first two again so you know what the heck I'm talking about. I know I'm going to have to.
The first is here
the second is here
And just random bit. If you're not reading Isis the scientist you should be.
Thursday, July 30, 2009
There is no big surprise here. What most people consider “Science” is often glorified Voodoo Artistry. Even the “hard sciences” like Physics and Math have plenty of unsolved mysteries. The soft sciences (Biology) have plenty too. Stuff like Oceanography and Meteorology (silly science) are almost totally librarian, i.e. they are really detailed observations without much of what Scientists consider “science”, that is, they have almost no predictive power.
It should surprise very few hard thinking people that much of what mass media considers “science” is often lame. How is it that so many “smart people” have bought into the Global Climate Crisis when our “weather scientists” can hardly predict (accurately) the weather a few weeks out. And, “they” expect us to believe that 20 years out we will be subject to catastrophic climate change.
Here’s the deal : lots of people who study “science” want to be considered “scientists” so they can feel good about their work. Maybe we should consider a stronger definition of what we can call science. If your body of work cannot accurately predict 99% of it’s claims, it cannot be considered science. If your work has no definable experimental framework, it is not science. If your work opens more questions than it answers, it is not science.
... and no reading the original post doesn't really help. The original post is here and was on some anomalously high tides they've been having on the east coast. It would be difficult to fit more misconceptions about science into such a short space. I addressed some of the problems in a response in the comments. But it seems a shame to keep it buried in some comments so here it is.
Ok, I really don’t have the time or inclination to address what you have written in any detail, and I rather suspect it wouldn’t matter just because your mind seems to be made up no matter what the facts are. But for the benefit of anyone reading who might actually think you know what you’re talking about let’s cover some things. (and yes I did this very quickly and I’m sure there are typos… sorry)
”How is it that so many “smart people” have bought into the Global Climate Crisis when our “weather scientists” can hardly predict (accurately) the weather a few weeks out. And, “they” expect us to believe that 20 years out we will be subject to catastrophic climate change.”
Weather versus climate, they’re not the same go learn the difference
“lots of people who study “science” want to be considered “scientists” so they can feel good about their work.”
While, unlike you, I cannot speak for “lots of people who study “science”” I can speak for myself and a few of my colleagues. I can honestly say that how we feel about our work has nothing to do with what you or anyone else calls us.
“If your body of work cannot accurately predict 99% of it’s claims, it cannot be considered science. “
Did you read that sentence after you wrote it? How do you predict a claim? I’m Paleontologist. If I claim that an asteroid killed the dinosaurs how then, do I predict it? I might predict we’ll find a crater but if we don’t am I wrong or have we just not found it yet?
But let’s back off of the semantics and look at the broader point. You seem to be claiming that science should be predictive. To some degree it should be, but 99%? The hallmark of science it not that it’s predictive, it’s that scientific ideas are tested. This means that sometimes we get stuff wrong. When that happens we get rid of what doesn’t work and, hopefully, replace it with what does, then that idea is tested etc etc. What this means in the cumulative sense is that we get better at stuff. By your definition if, right off the bat, if we can’t make predictions with 99% accuracy then, apparently, we’re not doing science. If I desperately cared whether of not you were calling me a scientist then the solution would be to simply gather data until I could predict things with 99% accuracy. Two problems: First predictions are very useful at well below your 99% benchmark. Hurricane track predictions are nowhere near 99% accurate (depending on how you define accuracy) but they’re still very useful. If we wait to be 99% accurate we’ll be waiting a very long time. And in the case of hurricane track predictions people will be dying while we wait for that 99%. Second, we actually learn a lot by predicting stuff and being wrong, that’s how we test our ideas. If we never predicted something and were wrong how would we know whether or not our ideas were correct? Learning what doesn’t work is sometimes as valuable as learning what does.
“If your work has no definable experimental framework, it is not science.”
Why? I’m a paleontologist. I do some experimentation but most of my data are collected in the field. Why are data collected through observation in the field less valid than data collected through experimentation?
“If your work opens more questions than it answers, it is not science.”
Once again: why? So if your answer to one question leads to more, of it your work shows is that we really don’t understand something as well as we thought we did then it’s not science? Once again if we’re unwilling to take on what we think we know then how will we ever know if what we think we know is wrong?
Update: He responded in the comments. Go read if you want it's.... interesting?
Tuesday, June 16, 2009
Ok let's think a little more about Jack's curve.
Remember we're counting fossils here. The number of fossils you have is going to depend on the amount of rock that you have. The younger the rock, the more of it there is. So there is a lot more Tertiary (the "T" on the graph) rock out there than say Cambrian (the "C" with a line through it) so there are more Tertiary fossils than Cambrian fossils. You can compensate for this but it's always going to be very tricky. So that huge run up of in diversity that you see at the end of Jack's curve might not be "real" just because we have so much more rock for those more recent time periods. So the general shape of the curve is a little suspect. With respect to extinction, I'm not saying that extinction events in the paleontoloogical record are simply a result of not having rock for those time periods, but certainly the volume of rock is going to affect how severe we view the extinction as being.
Next time: taphonomy and counting issues
Monday, June 8, 2009
The fifth, the end-Cretaceous event, which occurred sixty-five million years ago, exterminated not just the dinosaurs but seventy-five per cent of all species on earth. Once a mass extinction occurs, it takes millions of years for life to recover, and when it does it’s generally with a new cast of characters. In this way, mass extinctions have played a determining role in evolution’s course. It’s now generally agreed among biologists that another mass extinction is under way.What these biologists are doing is jumping from ancient extinction events to a modern "extinction". This is much trickier than most people think so lets look at it. Let's begin, as Anton Ego would say, with some
This is Jack Sepkoski's Family diversity curve with all five of the major extinctions numbered. Jack generated this curve by going into the literature and tabulating the number of taxonomic families through time. Paleontologists spend a great deal of time pouring over curves like this one so we can understand the broad sweep of life's evolution. We also spend a great deal of time looking at extinction events in great detail. So with that sort of perspective it is certainly fair to ask what can paleontologists or the paleontological record tell us about the current biological crisis.
The answer.... not much.
Why next time.