Frank,
I’m enjoying this exchange too. It has been a little frustrating at times, but fun. I just hope that someone out there in cyber-land is getting something out of this discussion too!
If you have a barrel full of 100 marbles with 5 purple, 5 yellow, 10 pink, 10 red, 15 brown, 15 blue, 20 orange, 20 green marbles, what is the chance that you will have at least one marble of each of the 8 colors of marbles represented in a random sample of 5 marbles? What if you take 10 marbles at random from the barrel? How about if you take 20 marbles at random? It is obvious that as the number of marbles drawn from the barrel increases, so does your chances of having all 8 colors represented in your sample population of marbles. Now let’s expand this example to some snake species that has 300,000 individuals (marbles) left in habitat (barrel) and there are 35 different phenotypes (or colors, but 5 of the phenotypes are physiological, so you can’t directly see what color they are) represented within this species. How many individuals are you going to have to remove from the 300,000 to have all 35 different phenotypes represented in a captive population? Now, how many individuals are you going to have to remove from the 300,000 to have the same frequency of genes in your captive population as there is in the wild population? And no you don’t know what the variable genes are in the wild population, so you really have no idea what the frequencies of those genes are. Now ask your self who is going to take care of all those snakes? It should be obvious that the actual numbers needed to maintain genetic diversity are very large, but how large we don’t know. On the other hand, if we chop the habitat (barrel) in half so that it will only hold half the number of individuals, what is the probability that all 35 phenotypes will be represented in the remaining population? Pretty good, because it is a large sample of the original.
This is a discussion about maintaining future possibilities, and leaving the maximum number of individuals in natural habitat has the best chance of maintaining genetic diversity. A captive population is a sub-sample of a species. If you don’t happen to get lucky enough to get all the possible phenotypes in your random sample of the species then phenotypes are lost and you can’t get them back, and the chance of loosing more phenotypes to random chance over time increases exponentially as the size of your population decreases. Preserving a relatively large number of animals in their natural habitat preserves genetic diversity and thus future possibilities. Preserving a relatively small number of animals in a captive population preserves the phenotypes you happen to draw from the natural population, which limits genetic diversity and thus limits future possibilities. Neither option has a 100% guarantee, but I’ll go for the option that gives me the best chance for success every time.
OK, now let’s discuss the Scientific method. Science, by virtue of being malleable, can “almost” never state things as absolute. If I hold the preverbal apple out in front of me, and I let it go, what is going to happen? 99.9% of the time that apple is going to fall straight down and hit the ground, BUT there is a possibility that if I drop that same apple outside, a sudden wind might blow that apple into the next County, so I can’t say 100% of the time the apple will fall strait to the ground because there is a small possibility it won’t. Now, when you have a 99% probability that the apple will hit the ground we call that a Law (i.e. the Law of gravity). The next level down is a theory where we have extremely good evidence that a particular event will occur based on countless experimental tests of hypothesis proposed to explain the phenomena. With a theory, scientists have a very good grasp of how the overall phenomena works (e.g. Global Warming), but the actual mechanics of how that process functions is still being tested and studied to increase the level of certainty as to how that process works. A hypothesis is the next level down from a theory, and it is the level where most experimental scientists do their work.
The classic example of a hypothesis is, if I take a feather and an apple, and I drop them from the same height at the same time they will hit the ground at the same time. I’ve deduced this hypothesis because I know that gravity pulls or accelerates objects toward the Earth at a rate of 9.8 meters per second squared, and that that rate of acceleration is independent of mass or weight. I then test my hypothesis by dropping the feather and apple 1,000 times and compare the results of my test. What I find is that the apple hit the ground before the feather 1,000 times out of 1,000 independent tests of my hypothesis. So much for Newton’s Law of Gravity! But wait, I wonder if air resistance might change my expected result? So I modify my original hypothesis to remove air from the experiment. My new hypothesis is, if I take a feather and an apple, and I drop them from the same height at the same time IN A VACUUM they will hit the ground at the same time. I then set up a vacuum chamber and drop the apple and feather 1,000 times, and look at my results. I find that the feather and apple hit the ground within 2 micro seconds of one another 995 times out of the 1,000 trials I conducted, but in two trials the feather hit the ground 3 micro seconds before the apple and in three trials the apple hit the ground 2.5, 3 and 3.2 micro seconds before the feather. Does this mean that my hypothesis is false and I have to throw it out and start all over again just because the feather and apple did not hit the ground at exactly the same time in every single trial? Most people would say no, and that I’ve made a pretty convincing case for my argument. A good scientist would then try and explain why there was some variability in his results (i.e. did a build up of static electricity in the chamber cause the feather to be attracted to the wall thus slowing the feather, etc). Thus, as a scientist one always has to leave open the possibility that events will occur outside a given boundary, which is why scientists often report their results in probabilities (e.g. there is a 95% probability that the feather and apple will hit the ground at the …).
The unfortunate result of this scientific honesty is that as the number of possible variables in the system being studied increase, so does the margin of possible outliers in experiments. Simple physics is used as the classic example because it is all based on physical parameters you can, for the most part, directly measure. However, when you enter the realm of biology the number of variables jumps through the roof, which makes it that much more difficult to show clear cut results from a particular hypothesis, particularly when you are dealing with phenomena that may take years to develop such as adaptation to a particular habitat patch.
OK, so how is all of this relevant to our discussion? It is simply this; science is not 100% by design because our understanding of the world around us changes largely because we increase our understanding of the fine details. Before Louis Pasteur people thought you could take a box, add a raw steak and after a week the steak would turn into flies! We now know this to be false because our understanding of how life functions is much greater today than it was a couple of centuries ago. The problem is, because science does not exclude all possibilities and it builds on its mistakes by refining the hypothesis, people take this as meaning science is filled with a bunch of half baked ideas with no real understanding because look at all the problems with science in the past. This is not really a fair criticism, because with out science we would not have airplanes, computers or even modern medicine. In other words, science has a track record of many more successes than failures, but public perception of science remains jaded.
Take for example global warming. Open any recent issue of Science, Nature, or any one of the hundreds of scientific journals dedicated to the study of the environment (including the journal “Climate Change”) and you are bound to find articles about how global warming will affect some aspect of human lives or how it will affect a particular ecosystem. Scientists, or I should say about 98% of scientists, accept global warming as fact. What scientists debate about is how quickly temperatures will rise, will all ecosystems experience the same shift in temperature, how will weather patterns be altered by a mean temperature increase and what is the predicted end point for the increase in temperature. One of the hot topics in climate research right now is how fast the polar ice caps are going to melt at the current rate of global temperature increase, and how fast will sea level rise as the water from the ice caps is added to the oceans. Why is this so important? Because Venice has already lost the first floor of many of it’s buildings and an increase in sea level of only a couple of feet when combined with a storm surge could wipe out the entire city! Further, something like 25% of the world’s population lives within 10 feet of sea level, so this is a big issue! However, open a news paper and your more likely to see an article about Joe Blow wana-be scientist who analyzed the mean annual temperatures of three major cities in the US and Canada for the past 10 years and did not find an increase in temperature, so therefore, global warming is a figment of hair brained scientists imagination. Oh yeah, the paper forgot to mention the 35 studies looking at changes in temperatures over the past 1,000 years at 100,000 locations throughout the globe, or the 75 or so major studies examining polar and glacial ice core samples representing the past 10,000 years that were all published, not in the local paper, but in peer reviewed journals. In other words, the discussion in the scientific community is about the mechanisms driving a given event, whereas the public seems to think this is an academic discussion of a hair brained idea, global warming, based on the opinions of a very few people who refuse to actually look at the data because headlines about whackos sell a whole lot more papers than head lines about why you should sell your beach front property while you still have something to sell. There is a group called the Flat Earth Society that claims to have scientific proof that the Earth is flat. People don’t put much credence to their views, but then they don’t have the oil and chemical companies pouring millions of dollars a year into programs aimed at poking holes in global warming studies to continue making money at the expense of the environment.
Once again, how does this relate? Science is based on probabilities of a particular event occurring, and yes, it acknowledges that exceptions to the general trends do occur, so you can draw conclusions from the 10,000 or so examples of local populations becoming extinct due to isolation and the resultant reduction in genetic diversity, or you can draw conclusions from the 20 or so examples of outlying populations that survived in isolation despite their reduced genetic diversity. The choice is yours, but science dictates that 95% of the time a population with limited genetic diversity will become extinct in 50 to 100 years. I would rather have a 95% chance of a particular species surviving for a 100 years in it’s natural environment than only a 5% chance it will survive 100 years in captivity, wouldn’t you?
Finally, I’m glad to hear you think that “Government Types” seem to go along with science most of the time! Unfortunately, from my experience, politicians only listen to scientists when the poll numbers agree with the science, and the rest of the time decisions are made based on the public perception of the issue rather than the cold hard facts. This “hypothesis” could be used to explain why there are so many laws restricting ownership of “dangerous” herps and so few laws restricting the ownership of “man’s best friend”. You have got to look at the big picture, not just the fine details.
Big Brother