Mike Riddle: Does Evolution Have a . . . Chance?

It's all very well to have a degree in mathematics and try and calculate the probability for proteins forming, but if you don't know - or choose to ignore - the current models of how new proteins are made, and instead use your own naîve model involving everything at random, then no wonder you get a very small probability.

But I'm getting ahead of myself. I just read (don't know why, really) an article by Mike Riddle, President of the Creation Training Initiative:

Does Evolution Have a . . . Chance?

Here's the whole things with my comments in red.

One has only to contemplate the magnitude of this task to concede that the spontaneous generation of a living organism is impossible. Yet we are here—as a result, I believe, of spontaneous generation.1
—George Wald, Nobel Laureate

In today’s culture, molecules-to-man evolution is being taught as a fact, even though it is known to “go against the odds.” But few realize the odds they are up against! And they are immense! 

The Bible teaches that God is the Creator of all things (Genesis 1; Colossians 1:16; John 1:1–3; Revelation 4:11). While these passages rule out any possibility of Darwinian evolution, they do allow for variation within a created kind. But there is much opposition to what the Bible teaches. People holding to evolution would argue that random chance events, natural selection, and billions of years are sufficient to account for the universe and all life forms. The fact they they rule out evolution merely means that they are wrong. Evolution - including macroevolution - has been observed.

Do You Believe in “Magic”?

Most people recognize “magic” as an illusionary feat or trickery by sleight of hand. But how far are you willing to go to believe something can happen by “dumb luck” or chance? For example, if I were to role a die and have it come up six three times in a row, would you consider that lucky? How about if I rolled six ten times in a row? Now you might suspect that I am using some trickery or that the die is weighted. It is much more incredulous to believe chance as an explanation than the magic of creationism. (Also, [sic]).

How far are we willing to go to accept something as a chance occurrence or before we recognize that it was just an illusion? We can test this by measuring our credulity factor. Credulity is the willingness to believe something on little evidence.

Measuring Our Credulity Factor against Evolution

Evolutionists state that life originated by natural processes about 3.8 billion years ago. Is there any evidence for this happening? Freeman Dyson, theoretical physicist, mathematician, and member of the U.S. National Academy of Sciences states:

Concerning the origin of life itself, the watershed between chemistry and biology, the transition between lifeless chemical activity and organized biological metabolism, there is no direct evidence at all. The crucial transition from disorder to order left behind no observable traces.2

Since the origin of life has never been observed, this is a major hurdle! Yes, true. It is a darned annoying fact that we cannot directly observe anything that happened in the past. If only we could directly observe murderers in the act, then detective work would be much easier. We are left with the question, “Is the origin of life by naturalistic processes possible?” This can, in part, be tested by examining two areas:

1. The success of scientists in creating life or the components of a living cell.
2. The probability that such an event could occur.

We are not really "left with the question" of the origin of life (aka abiogenesis) if we are concerned with evolution. Suppose for a moment that God created life initially - this doesn't rule out evolution following that. Those two things are quite distinct, and even though natural selection plays an important role in abiogenesis, the scientists who work on abiogenesis are different that those who work on evolution, because they require very different areas of expertise. So, if we could never find a scientific solution to abiogenesis, that wouldn't mean that we cannot understand evolution as a natural process (which we do).
The Structural Unit of Living Organisms—The Cell

Cells are made up of thousands of components. One of these components is protein. Proteins are large molecules made up of a chain of amino acids. In order to get a protein useful for life, the correct amino acids must be linked together in the right order. There are of course many different ways to put together proteins that are useful for life. How easy is this and does it happen naturally? It turns out that this is not an easy process. No, not if your "process" is random chance with nothing else. There are large hurdles that evolutionary processes must overcome in order to build a biological protein.

Protein molecules contain very specific arrangements of amino acids. Even one missing or incorrect amino acid can lead to problems with the protein’s function. Yes, some amino acid changes will mess with protein function, but many changes are neutral and do not change protein function.

Making Mathematics Painless

Before applying mathematics and probability to the origin of life, we need to consider seven parameters that will affect the formation of a single protein.

First, there are over 300 different types of amino acids. However, only 20 different amino acids are used in life. This means that in order to have life, the selection process for building proteins must be very discriminating. But it didn't necessarily have to be this discriminating in the beginning. 

Second, each type of amino acid molecule comes in two shapes commonly referred to as left-handed and right-handed forms. Only left-handed amino acids are used in biological proteins; however, the natural tendency is for left- and right-handed amino acid molecules to bond indiscriminately.

Third, the various left-handed amino acids must bond in the correct order or the protein will not function properly.3 Again, there is not one correct protein, but a lot of variation, and proteins that doesn't work for one thing can work for another.

Fourth, if there was a pond of chemicals (“primordial soup”), it would have been diluted with many of the wrong types of amino acids and other chemicals available for bonding, making the proper amino acids no longer usable. This means there would have been fewer of the required amino acids used to build a biological protein. But there could have been enough. Plus, the twenty that are currently used could have been a function of those being to most abundant ones. 

Fifth, amino acids require an energy source for bonding.4 Raw energy from the sun needs to be captured and converted into usable energy. Where did the energy converter come from? It would require energy to build this biological machine. However, before this energy converter can capture raw energy, it needs an energy source to build it—a catch-22 situation.5 See the video below. 

Sixth, proteins without the protection of the cell membrane would disintegrate in water (hydrolysis), disintegrate in an atmosphere containing oxygen, and disintegrate due to the ultraviolet rays of the sun if there was no oxygen present to form the protective ozone layer.6

Seventh, natural selection cannot be invoked at the pre-biotic level. The first living cell must be in place before natural selection can function. No, selection works on anything that replicates. Self-replicating molecules like ribozymes are used in laboratory experiments. They are affected by natural selection.

Considering all seven of these hurdles, how probable is it that a single protein could have evolved from a pool of chemicals? Probability outcomes are measured with a value ranging from zero through one. The less likely an event will happen, the smaller the value (closer to zero). The more likely an event will occur, the larger the value (closer to one). Wow, talk about dumbing it down! If you know nothing about the natural processes that are involved, then it does seem very unlikely. But do watch this video to learn one or two things about those processes:

Let’s practice this using a coin. What are the chances of getting a heads when we flip a penny? The answer is 50 percent, or one chance in two (written 1/2). What is the chance of getting two heads in a row? Since each toss is 1/2 we can multiply each occurrence to get the final probability. This would be 1/2 x 1/2 which would equal 1/4 (or one chance in four). Now let’s use some bigger numbers.

When we flip a coin we have two possible outcomes, heads or tails. In this problem, we want to calculate the probability of getting all heads every time we flip a coin. We can use this exercise to test our credulity factor. How many heads in a row are we willing to accept as a chance occurrence? At what point would we suspect an illusion or some form of magic (trickery)? We wouldn't expect magic. Ever. Only godbots do that. We would instead expect some other natural process being involved.

The objective of using probabilities is to demonstrate the probability or chance of getting a certain result. On average, how many times and how often will we need to flip the coin to achieve 100 heads in a row? Over 300 million times a second for over one quadrillion years! If you could only do one trial at a time, then that would take a long time. But if you can do many at the same time in parallel, then you could get one hundred heads very quickly. If we could run just a billion such trials in parallel, then it would only take a million years, which is not long on geological time-scales. (Also, that number is slightly wrong. Only a little over 40 million times per second is needed for a quadrillion (10¹⁵) years. - My math is better than yours so I win!!! ;P)

The chances of getting all heads 100 times in a row is similar to the chance of getting 100 left-handed amino acids to form a biological protein. Proteins range in size from about 50 to over 30,000 amino acids. To get a small protein of 100 left-handed amino acids from an equal mixture of left- and right-handed amino acids, the probability would then be 1030 or 1 followed by 30 zeros (1,000,000,000,000,000,000,000,000,000,000). But but but, this is assuming that the process is random (again, it isn't - see the video above). How believable (credulity factor) is it that this could happen by random chance? Also, consider that this has never been observed! We all agree that it hasn't been observed, but we all agree that things that haven't been observed have taken place, right? Like a fallen tree in the forest is assumed to have fallen, even though no one were there to observe it. Chance protein formation has always been accepted as a matter of faith by evolutionists. No, not chance formation. Again, again, see the video. You are ignoring the natural processes that can explain these things.

Number of desired heads in a row	Probability	Number of flips	Credulity factor (chance)
1	1/2 have	2	Yes / No
2	1/4 (1/22)	4	Yes / No
3	1/8 (1/23)	8	Yes / No
4	1/16 (1/24)	16	Yes / No
5	1/32 (1/25)	32	Yes / No
8	1/256 (1/28)	256	Yes / No
10	1/1024 (1/210)	1024	Yes / No
20	1/1,048,576 (1/220)	1,048,576	Yes / No
100	1/1030(1/2100)	1 followed by 30 zeros	Yes / No

Ten is pretty good! We can work with ten. Not that we thereby admit that Riddle's puerile model here is the correct one (cause it isn't), but suppose to have a bunch of string of ten heads in a row, then those could be assembled together three at a time to make strings of 30 heads in a row.

But wait, there is more! This number, 1030, only measures the possibility of getting all left-handed amino acids. It does not say anything about their order. In our example, we have a chain of 100 amino acids. Each position can be occupied by any 1 of 20 different amino acids common to living things, and these must be in a specific order to form a functional protein. What is the probability that the correct amino acid will be placed in position number 1 of the chain? It will be 1/20. What is the probability that the first two positions will be correct? This can be calculated by multiplying the two probabilities together (1/20 x 1/20 = 1/202). Therefore, the probability of getting all 100 amino acids in the correct position would be 1/20 multiplied by itself 100 times or 1/20100 (this equates to 1/10130). This is 1 followed by 130 zeros! Which is not how proteins are thought to have formed. See the video above. This is like me saying that the process by which the Bible is written is by randomly stringing letters together. There are 3,566,480 letters in the bible (Bing it yourself), so with 26 different letters that gives a chance of one in 26^3566480. This is 1 followed by more than 5 million zeros! Therefore the Bible could not have been written by random chance. - Point here being that that is of course not the process by which the Bible was written, just as proteins of length 100 are not assembled by chance.

Large numbers can be hard to visualize or even comprehend. To put this in picture format we can use a smaller number 1021 (1 followed by 21 zeros). If we were to take 1021 silver dollars and lay them on the face of the earth; they would cover the entire land surface to a depth of 120 feet.7

Are there upper limits for which we can logically expect an event will not occur by random chance? The mathematician Emile Borel proposed 1/1050 as a universal probability bound. This means that any specified event beyond this value would be improbable and could not be attributed to chance.8 Repeat after me: scientists do not attribute random chance to the formation or proteins.

As we can see, the probability of getting a single small protein (1/10130) far exceeds this limit. Even if the protein can interchange amino acids at various positions (such as in the case of the protein cytochrome a),9 the resulting probability still exceeds the limit of 1/1050. So far we have only looked at the probability of getting a single small protein by random chance. What are the chances of getting all the proteins necessary for life? By chance? Negligible. Relevance...? 

No matter how large the environment one considers, life cannot have had a random beginning . . . there are about two thousand enzymes, and the chance of obtaining them all in a random trial is only one part in (1020)2000 = 1040,000, an outrageously small probability that could not be faced even if the whole universe consisted of organic soup.10

Let our conclusion be that life did not have a random beginning (that is, completely random, as described here). 

This number is so large (1 followed by 40,000 zeros) that it staggers the imagination how life could have evolved by natural, random processes. Yet, people continue to hold onto their belief that life did evolve by random chance (high credulity factor). Yes, staggering, I tell you. If you only rely on random processes, which scientists do not. Watch the video above!

Time is in fact the hero of the plot. . . . What we regard as impossible on the basis of human experience is meaningless here. Given so much time, the “impossible” becomes possible, the possible probable, and the probable virtually certain. One has only to wait: time itself performs the miracles.11

This statement attributes supernatural qualities to time! It also allows for anything to happen. This means we are no longer bound by the laws of science or any other natural limits. The statement thus becomes meaningless. You are the one not bound by the laws of science when you think the science says it is all random chance.

Tricks of the Trade

Since scientists have been unable to create life, they are forced to speculate through research and sometimes “sleight of hand” how it might have arrived on earth. Below are some of the tricks of the trade used to avoid the obvious—that God is the Creator of all things (Colossians 1:16). God or Allah or Odin or Zeus or Baal, or whatever. False dichotomy. Also, "speculate though research." *chortle* No, even if we understand natural processes that can create life, we can never know for sure how it actually happened, because all evidence of it has been erased. There are no fossils or anything else left from back then that we can take a direct look at. Too bad. But we can make very informed models by which we can understand abiogenesis. Sorry if this offends your religious sensibilities.

1. It happens naturally

“The formation of biological polymers from monomers is a function of the laws of chemistry and biochemistry, and these are decidedly not random.”12 This is a link to a great discussion on the probability of abiogenesis on TalkOrigins. It is also from 1998, and we have learned a lot since then. See, for example, the video above.

Explanation

This is an incorrect statement. I see nothing incorrect about it! Those laws are really not random!!! If it happens naturally, then why can’t scientists duplicate this in the lab? See video above. Amino acids do not spontaneously bond together to make proteins. First, it takes a source of energy to do this. The Sun or geothermal energy. Second, the natural tendency is to bond left- and right-handed amino acids, but life requires all left-handed amino acids. Third, they must be in the correct order or the protein will not function properly. Fourth, it requires the instructions of DNA to get the right amino acids. Where did DNA come from? Fifth, protein molecules tend to break down in the presence of oxygen or water. For answer to all of these, see the video above.

2. The deck of 52 cards

In a deck of 52 playing cards there are almost 1068 possible orderings of the cards. If we shuffle the deck we can conclude that the possible ordering of the cards having occurred in the order we got is 1 chance in 1068. This is certainly highly improbable, but we did come up with this exact order of cards. Therefore, no matter how low the probability, events can still occur and evolution is not mathematically impossible.

Explanation

In this example the math is correct but the interpretation is wrong. Your interpretation of your math is what's wrong here. If the arrangement had been specified beforehand, then the actual outcome would be surprising. By shuffling the cards, the probability is one that a sequence will occur. The fallacy is that the order is predicted after the fact. Your fallacy is that you assumed that there is just one correct protein, and is contains a hundred amino acids. That is false.

3. All the people

We are in a room of 100 people. What is the probability that all 100 people would be here in this room at this exact time? The probability is enormous, but yet we are all here.

Explanation

Two things are wrong with this reasoning. First, the people were not pre-specified. This is another example of an after-the-fact prediction. Second, each person made a decision to attend; therefore, this is not a chance gathering. This turns out to be a misunderstanding between a chance event and intelligent choice. Right! Just like proteins are not chance gatherings. There are natural non-random processes involved. I think you are getting it now.

4. Probability is not involved

Probability has nothing to do with evolution because evolution has no goal or objective.

Explanation

This statement disagrees with modern biology textbooks. Agreed. Probability does have something to do with it. I don't know where the quote in point 4 comes from (it isn't in the TalkOrigins article). It's just your probability calculations that have the wrong premises, namely ignoring lots of natural processes.

When there is more than one possible outcome and the outcome is not predetermined, probability can become a factor. In the case of evolution there is no pre-assigned chemical arrangement of amino acids to form a protein. Right again! (Yeah!) There are indeed not only one possible outcome, but many proteins that could work. Therefore, the formation of a biological protein is based on random chance. No, that really doesn't follow. I thought for a moment you were with us, but science lost you again. Scientists know today that it is only because of the instructions (information) in DNA that only left-handed amino acids are linked in the proper order. 

Cells link amino acids together into proteins, but only according to instructions encoded in DNA and carried in RNA.13

Both creationists and evolutionists agree that DNA is essential for linking the correct amino acids in a chain to form a protein. The unanswered question is, “Where and how did DNA acquire the enormous amount of information (instructions) to form a protein?” There is no known natural explanation that can adequately explain the origin of life, or even a single protein. Yes there is. See the vid... The evolutionists are then left to rely on the odds (chance) that such a tremendous, improbable event occurred. No, there are other processes. zomg! Molecular biologist Michel Denton puts the event in perspective:

Is it really credible that random processes could have constructed a reality, the smallest element of which—a functional protein or gene—is complex beyond our own creative capacities, a reality which is the very antithesis of chance, which excels in every sense anything produced by the intelligence of man?14

But wait, there is still more!

The Human Body, Time, and Evolution

It is estimated that the human body is made up of 60 trillion cells (60,000,000,000,000).15 How long would it take to just assemble this many cells, one at a time and in no particular order at the rate of: What the fuck does this have to do with anything?!? Who thinks that the human body is assembled one cell at a time? Also, this doesn't seem to have anything to do with evolution, but development - a process that we can and have observed directly.

One per second	1.9 million years
One per minute	114 million years
One per hour	6.8 billion years

These ages assume no mistakes! However, the evolutionary mechanism is based upon random errors (mistakes) in the DNA. Also included in assembling all the 60 trillion cells is that they have to make the right organs which all have to interact. Relevance?

The human body contains more than 40 billion capillaries extending over 25,000 miles, a heart that pumps over 100,000 times a day, red blood cells that transport oxygen to tissues, white blood cells that rush to identify enemy agents in the body and mark them for destruction, eyes and ears that are more complex than any man-made machine, a brain that contains over 100 trillion interconnections, plus many other parts such as the nervous system, skeleton, liver, lungs, skin, stomach, and kidneys. Relevance?

The complexity and dimensions of the human body are staggering. The probability of assembling 60 trillion cells that form specific organs that all work together to form a single human being in the evolutionary time scale of 3.8 billion years is a giant leap of faith. However, an all-knowing, all-powerful Creator has told us in His Word that He is the designer. That's not how anybody thinks the human body develops!

The hearing ear and the seeing eye, The Lord has made them both (Proverbs 20:12).

Every human body is a testimony to a purposeful Creator. As Malcolm Muggeridge said:

One of the peculiar sins of the twentieth century which we’ve developed to a very high level is the sin of credulity. It has been said that when human beings stop believing in God they believe in nothing. The truth is much worse: they believe in anything.16

Nonsense! Both statements are false. I believe in many things, and God is not one of them. 

Conclusion

Probability arguments can present a strong argument for the existence of a Creator God. The probability arguments presented here - even if they were based on sound assumptions, which they aren't - argues nothing for the existence of a Creator God. Certainly not any particular God. Maybe FSM. However, even when such evidence is presented to an evolutionist there is no guarantee that he or she will be persuaded. No, immature arguments like these persuade no scientists. Creationists, maybe. The real issue is not about evidence If you admit that you think it has nothing to do with evidence, why are you going through all these exercises in the first place?; it is a heart issue. As Christians we are called to have ready answers and break down strongholds that act as stumbling blocks to the unbeliever. It is the Holy Spirit that changes lives.

But sanctify the Lord God in your hearts, and always be ready to give a defense to everyone who asks you a reason for the hope that is in you, with meekness and fear (1 Peter 3:15).

For the weapons of our warfare are not carnal but mighty in God for pulling down strongholds, casting down arguments and every high thing that exalts itself against the knowledge of God, bringing every thought into captivity to the obedience of Christ (2 Corinthians 10:4–5).

Your real creationist weapon is ignorance - something that you rely heavily on when calculating probabilities for protein formation by random chance alone.

Footnotes

1. George Wald [biochemist and winner of Noble Prize in Physiology or Medicine, 1967], “The Origin of Life,”Scientific American 191 no. 48 (1954): 46.
2. Freeman Dyson, Origins of Life (New York, NY: Cambridge University Press, 1999), p. 36.
3. “The order of the amino acids in a protein determines its function and whether indeed it will have a function at all.” Lee Spetner, Not By Chance (New York, NY: Judaica Press, 1997), p. 31.
4. “The important fact that amino acids do not combine spontaneously, but require an input of energy, is a special problem.” Charles Thaxton, Walter Bradley, and Roger Olsen, The Mystery of Life’s Origin (Dallas, TX: Lewis and Stanley, 1992), p. 55.
5. “A source of energy alone is not sufficient, however, to explain the origin or maintenance of living systems. The additional crucial factor is a means of converting this energy into the necessary useful work to build and maintain complex living systems.” Thaxton, Bradley, and Olsen, The Mystery of Life’s Origin, p. 124.
6. “What we have then is a sort of ‘catch 22’ situation. If we have oxygen we have no organic compounds, but if we don’t have oxygen we have none either.” Michael Denton, Evolution: A Theory in Crisis (Bethesda, MD: Adler and Adler, 1985), p. 262.
7. Peter Stoner, Science Speaks (Wheaton, IL: Van Kampen Press, 1952), p. 75.
8. Emile Borel, Probabilities and Life (New York, NY: Dover, 1962), p. 28.
9. A transport protein involved in the transfer of energy (electrons) within cells.
10. Sir Fred Hoyle and Chandra Wickramasinghe, Evolution from Space (London: Dent, 1981), p. 148, 24.
11. George Wald, “The Origin of Life,” p.48.
12. Ian Musgrave, “Lies, Damned Lies, Statistics, and Probability of Abiogenesis Calculations,” TalkOrigins, www.talkorigins.org/faqs/abioprob/abioprob.html.
13. G.B. Johnson, Biology: Visualizing Life (Austin, TX: Holt, Rinehart, and Winston, 1998), p. 193.
14. Denton, Evolution: A Theory in Crisis, p. 342.
15. Boyce Rensberger, Life Itself (New York, NY: Oxford University Press, 1996), p. 11.
16. Malcolm Muggeridge, “An Eighth Deadly Sin,” Woman’s Hour radio broadcast, March 23, 1966. Quoted in Malcolm Muggeridge and Christopher Ralling, Muggeridge Through the Microphone: B.B.C. Radio and Television(London: British Broadcasting Corporation, 1967).

The simulations behind the fitness landscape visualizations

We now have two videos out featuring evolving populations in two-dimensional fitness landscapes.

Using fitness landscapes to visualize evolution in action Youtube Vimeo
Visualizing coevolution in dynamic fitness landscapes Youtube Vimeo

(Best to watch the first one first for some background information about fitness landscapes.)





These movies are based on simulations of organisms evolving by reproduction, mutation and selection. Populations move around on a map that depict fitness as a function of phenotype (i.e., the biological and physical characteristics of an individual organism).

The following is a semi-technical description of the simulations, so be warned. If you have questions about some details, let me know in the comments.

Phenotype. The fitness landscapes that you see are phenotype-fitness maps. That means that for each possible phenotype there is an associated fitness value (which is a scalar - a single number). The phenotype of these simulated organisms consist of two traits. Both of these traits are numbers that range between 1 and 200. A phenotype of (10, 10) means that the organisms is situated near the lower corner of the fitness landscape, and a phenotype of (195, 3) means that the organism is situated near the right corner.

Sympatry. All simulations shown in the videos have no spatial component. The moving around in the landscape is only caused by changes in the phenotype, not geographically, and the population is therefore said to be strictly sympatric or well-mixed. If the individual organisms did move around in physical space, then where they are located relative to each other could have an influence of who they interact with, which could change things further. Structured populations are known to affect evolutionary dynamics through social interaction, competition for resources, and mating.

Mutations in these simulations work like this: Each of the two traits mutate at a set mutation rate. Every time an organisms reproduces, the new organism has a chance to mutate which is equal to the mutation rate. This is true for each trait, so that a mutation rate of 0.05 means that trait 1 has a 5% chance of changing, and trait 2 also has a chance of changing. These two events are independent of each other. When a trait mutates, the trait value is either increased or decreased by one. In other words, if the trait value of the parent was 142, the offspring will have a value of 141 or 143 with equal probability. There is no underlying genetics in these models, and the phenotype is directly inherited.

Selection.  Organisms reproduce asexually. Every offspring is a clone of the parent, except for any mutations. Every computational update some organisms die and some reproduce. Death is completely random, so that every organism has an equal chance or being removed every update. Who gets to reproduce is also random, but fitness affects this chance. For example, an organism that has twice the fitness of another organisms has a probability of reproducing that is twice as high. This doesn't guarantee that it will have twice as many offspring - but on average it will be approximately so.

Population size. Competition in these simulations is for space. Some simulations have a constant population size. In this case, a small percentage of the population is killed every update, and those empty spots are filled by selecting among the survivors. Other simulations have variable population sizes. In these vases every surviving organism has a chance to reproduce once every computational update that is equal to their normalized fitness. The variable population size simulations results in stable populations where the population size fluctuate around a value which is ultimate given by the average fitness. For example, when the population climbs a peak the average fitness of organisms increases, and the average chance of reproducing goes up. This means that the population grows in size. The way this is implemented is such that there is a carrying capacity set to 2,000 individuals. If the population reaches this size, 50% are moved next update, and the other 50% then has a chance to reproduce. If they all had the maximum fitness (a set value), then they would all reproduce, and the population size would be back to 2,000. This doesn't happen, because mutations would make some individuals have a fitness lower than the maximum. If the population size gets very low, the number than is killed every update is set to less than 50%, so that more than half of the organisms survives. The precise fraction killed goes from zero at population size zero linearly through 50% at 2,000. This most often results in population of around 1,600 organisms. Most published simulations studies of evolution use constant population sizes.

Dynamic landscapes. In the second video of coevolution systems the fitness landscape of one population changes over time because they are affected by another population. In the moth-orchid simulation, the length of the moth proboscis needs to be longer than the orchid spur length to be able to get to the nectar at the bottom. If every individual orchid has a spur that is longer than the proboscis, then moth fitness is low (but non-zero). Having a proboscis that is as long as the spurs of half of the orchid population will give the moth an intermediate fitness. The fitness landscape of the orchids is similarly affected by the moth population, with the orchids needing spurs that are longer than the proboscis in order for the feeding moth to get pollen on their faces. This drives the evolution of longer proboscises and spurs as dictated by the two changing fitness landscapes. In the rock-paper-scissors simulation, the fitness landscape of each population is affected by the phenotype values of the other two populations.

How the woman got her period

Guest post by Suzanne Sadedin. This is reposted from Quora.

Suzanne got her PhD in biology from Monash University, and has done postdoctoral research at Monash University, University of Tennessee, Harvard University, and KU Leuven.

What is the evolutionary benefit or purpose of having periods?

 I'm so glad you asked. Seriously. The answer to this question is one of the most illuminating and disturbing stories in human evolutionary biology, and almost nobody knows about it. And so, O my friends, gather close, and hear the extraordinary tale of:

HOW THE WOMAN GOT HER PERIOD

Contrary to popular belief, most mammals do not menstruate. In fact, it's a feature exclusive to the higher primates and certain bats*. What's more, modern women menstruate vastly more than any other animal. And it's bloody stupid (sorry). A shameful waste of nutrients, disabling, and a dead giveaway to any nearby predators. To understand why we do it, you must first understand that you have been lied to, throughout your life, about the most intimate relationship you will ever experience: the mother-fetus bond.

Isn't pregnancy beautiful? Look at any book about it. There's the future mother, one hand resting gently on her belly. Her eyes misty with love and wonder. You sense she will do anything to nurture and protect this baby. And when you flip open the book, you read about more about this glorious symbiosis, the absolute altruism of female physiology designing a perfect environment for the growth of her child.

If you've actually been pregnant, you might know that the real story has some wrinkles. Those moments of sheer unadulterated altruism exist, but they're interspersed with weeks or months of overwhelming nausea, exhaustion, crippling backache, incontinence, blood pressure issues and anxiety that you'll be among the 15% of women who experience life-threatening complications.

From the perspective of most mammals, this is just crazy. Most mammals sail through pregnancy quite cheerfully, dodging predators and catching prey, even if they're delivering litters of 12. So what makes us so special? The answer lies in our bizarre placenta. In most mammals, the placenta, which is part of the fetus, just interfaces with the surface of the mother's blood vessels, allowing nutrients to cross to the little darling. Marsupials don't even let their fetuses get to the blood: they merely secrete a sort of milk through the uterine wall. Only a few mammalian groups, including primates and mice, have evolved what is known as a “hemochorial” placenta, and ours is possibly the nastiest of all. 

Inside the uterus we have a thick layer of endometrial tissue, which contains only tiny blood vessels. The endometrium seals off our main blood supply from the newly implanted embryo. The growing placenta literally burrows through this layer, rips into arterial walls and re-wires them to channel blood straight to the hungry embryo. It delves deep into the surrounding tissues, razes them and pumps the arteries full of hormones so they expand into the space created. It paralyzes these arteries so the mother cannot even constrict them.

What this means is that the growing fetus now has direct, unrestricted access to its mother's blood supply. It can manufacture hormones and use them to manipulate her. It can, for instance, increase her blood sugar, dilate her arteries, and inflate her blood pressure to provide itself with more nutrients. And it does. Some fetal cells find their way through the placenta and into the mother's bloodstream. They will grow in her blood and organs, and even in her brain, for the rest of her life, making her a genetic chimera.

This might seem rather disrespectful. In fact, it's sibling rivalry at its evolutionary best. You see, mother and fetus have quite distinct evolutionary interests. The mother 'wants' to dedicate approximately equal resources to all her surviving children, including possible future children, and none to those who will die. The fetus 'wants' to survive, and take as much as it can get. (The quotes are to indicate that this isn't about what they consciously want, but about what evolution tends to optimize.)

There's also a third player here – the father, whose interests align still less with the mother's because her other offspring may not be his. Through a process called genomic imprinting, certain genes inherited from the father can activate in the placenta. These genes ruthlessly promote the welfare of the offspring at the mother's expense.

How did we come to acquire this ravenous hemochorial placenta which gives our fetuses and their fathers such unusual power? Whilst we can see some trend toward increasingly invasive placentae within primates, the full answer is lost in the mists of time.

Uteri do not fossilize well.

The consequences, however, are clear. Normal mammalian pregnancy is a well-ordered affair because the mother is a despot. Her offspring live or die at her will; she controls their nutrient supply, and she can expel or reabsorb them any time. Human pregnancy, on the other hand, is run by committee – and not just any committee, but one whose members often have very different, competing interests and share only partial information. It's a tug-of-war that not infrequently deteriorates to a tussle and, occasionally, to outright warfare. Many potentially lethal disorders, such as ectopic pregnancy, gestational diabetes, and pre-eclampsia can be traced to mis-steps in this intimate game. 

What does all this have to do with menstruation? We're getting there.

From a female perspective, pregnancy is always a huge investment. Even more so if her species has a hemochorial placenta. Once that placenta is in place, she not only loses full control of her own hormones, she also risks hemorrhage when it comes out. So it makes sense that females want to screen embryos very, very carefully. Going through pregnancy with a weak, inviable or even sub-par fetus isn't worth it.

That's where the endometrium comes in. You've probably read about how the endometrium is this snuggly, welcoming environment just waiting to enfold the delicate young embryo in its nurturing embrace. In fact, it's quite the reverse. Researchers, bless their curious little hearts, have tried to implant embryos all over the bodies of mice. The single most difficult place for them to grow was – the endometrium.

Far from offering a nurturing embrace, the endometrium is a lethal testing-ground which only the toughest embryos survive. The longer the female can delay that placenta reaching her bloodstream, the longer she has to decide if she wants to dispose of this embryo without significant cost. The embryo, in contrast, wants to implant its placenta as quickly as possible, both to obtain access to its mother's rich blood, and to increase her stake in its survival. For this reason, the endometrium got thicker and tougher – and the fetal placenta got correspondingly more aggressive.

But this development posed a further problem: what to do when the embryo died or was stuck half-alive in the uterus? The blood supply to the endometrial surface must be restricted, or the embryo would simply attach the placenta there. But restricting the blood supply makes the tissue weakly responsive to hormonal signals from the mother – and potentially more responsive to signals from nearby embryos, who naturally would like to persuade the endometrium to be more friendly. In addition, this makes it vulnerable to infection, especially when it already contains dead and dying tissues.

The solution, for higher primates, was to slough off the whole superficial endometrium – dying embryos and all – after every ovulation that didn't result in a healthy pregnancy. It's not exactly brilliant, but it works, and most importantly, it's easily achieved by making some alterations to a chemical pathway normally used by the fetus during pregnancy. In other words, it's just the kind of effect natural selection is renowned for: odd, hackish solutions that work to solve proximate problems. It's not quite as bad as it seems, because in nature, women would experience periods quite rarely – probably no more than a few tens of times in their lives between lactational amenorrhea and pregnancies**.

We don't really know how our hyper-aggressive placenta is linked to the other traits that combine to make humanity unique. But these traits did emerge together somehow, and that means in some sense the ancients were perhaps right. When we metaphorically 'ate the fruit of knowledge' – when we began our journey toward science and technology that would separate us from innocent animals and also lead to our peculiar sense of sexual morality – perhaps that was the same time the unique suffering of menstruation, pregnancy and childbirth was inflicted on women. All thanks to the evolution of the hemochorial placenta.

Links:
The evolution of menstruation: A new model for genetic assimilation
Genetic conflicts in human pregnancy
Menstruation: a nonadaptive consequence of uterin... [Q Rev Biol. 1998]
Natural Selection of Human Embryos: Decidualizing Endometrial Stromal Cells Serve as Sensors of Embryo Quality upon Implantation
Scientists Discover Children’s Cells Living in Mothers’ Brains

Credits: During my pregnancy I was privileged to audit a class at Harvard University by the eminent Professor David Haig, whose insight underlies much of this research. Thanks also to Edgar A. Duenez-Guzman, who reminded me of crucial details. All errors are mine alone.

*Dogs undergo vaginal bleeding, but do not menstruate. Elephant shrews were previously thought to menstruate, but it's now believed that these events were most likely spontaneous abortions.

**One older published estimate for hunter gatherers was around 50, but this relied on several assumptions that suggest it's a significant overestimate. In particular, it includes 3 whole years of menstruation before reproduction (36 periods) for no obvious reason.

We can make an estimate from studies of the Hadza of Tanzania, who reach puberty around 18, bear an average of 6.2 children in their lives (plus 2-3 noticeable miscarriages) starting at 19, and go through menopause at about 43 if they survive that long (about 50% don't). Around 20% of babies die in their first year; the remainder breastfeed for about 4 years. So this is 25 years of reproductive life, of which about 20 are spent lactating, and 4.5 pregnant. That would leave only about 6 periods, but amenorrhoea would cease during the last year of lactation for each child, so this figure is too low. On the other hand, this calculation ignores the ~50% of women who died before menopause, miscarriages, months spent breastfeeding infants who would die, and periods of food scarcity, all of which would further reduce lifetime menstruation. Stats from: http://www.fas.harvard.edu/%7Ehb...

Not dead yet: When do we give up on an idea?

Guest post by Carina Baskett written in response to Angela Moles and Jeff Ollerton's post on Dynamic Ecology: Is the notion that species interactions are stronger and more specialized in the tropics a zombie idea?

Carina Baskett is a PhD candidate at Michigan State University in the Department of Plant Biology and the Ecology, Evolutionary Biology, and Behavior Program. She posts photos from her fieldwork and occasional articles about tropical natural history, among other things, at Wandering Nature.

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If you’ve traveled to the tropics, you know the drill. Get your shots for typhoid and yellow fever, and your meds for malaria (try to avoid the one with psychotic side effects). Don’t drink the water, and avoid the lettuce.

This over-abundance of diseases and parasites in the tropics is not just because sanitation is lacking in developing countries. Both diversity and severity of human parasites are higher in the tropics (Cashdan 2001; Guernier, Hochberg et al. 2004).

Could the same be true for plant enemies? What about other biotic interactions, like predator-prey relationships, and plants and pollinators? And why?

The first person to suggest that biotic interactions are somehow different in the tropical and temperate regions was Alfred Russell Wallace. Not only did he independently conceive of natural selection around the same time as Darwin (during a malarial fever in Malaysia, speaking of tropical diseases!), he was also a great tropical naturalist.

In the book Tropical Nature in 1878, he said, “Equatorial lands must always have remained thronged with life; and have been unintermittingly subject to those complex influences of organism upon organism, which seem the main agents in developing the greatest variety of forms and filling up every vacant place in nature.”

The “biotic interactions hypothesis” to explain high tropical diversity* is a descendent of Wallace’s beautifully stated explanation, with contributions from Dobzhansky (1950), Fischer (1960), and Schemske (2009). At its core, skipping over tangents about coexistence and specialization, today’s conception has three testable parts:

1. The relative contribution of biotic interactions to variation in relative fitness of organisms is greater at lower latitudes.
2. Biotic selective agents drive faster divergence of allopatric populations than abiotic selective agents due to coevolution.
3. Therefore, isolated populations speciate faster when the main selective agents are biotic.

For parts B and C, I’ll just tease you with some references that explore or show evidence for these hypotheses in very different ways: Farrell, Dussourd et al. 1991; Schemske 2009; Paterson, Vogwill et al. 2010; Jablonski, Belanger et al. 2013.

I’ll focus the rest of this on part A, which was recently labeled a “zombie:” false, dead, disproven. I’ll try and convince you that it’s nowhere near dead yet. I’m NOT trying to convince you that the hypothesis is true, because I think the answer is very much up in the air, but rather that it’s plausible and that we need more data.

First, the dissection. Part A is represented graphically in Figure 1 (Schemske 2009). Each arrow is the proportion of variation in fitness for the focal species caused by different selective agents: mutualists, antagonists, and the abiotic environment. A wider arrow is a greater proportion. A solid line shows a positive effect on fitness, while a dashed line is negative. (Note that the arrows go both ways for the biotic agents. They coevolve, while abiotic agents do not, which gets into parts B and C of the hypothesis.)

Here’s what this abstract figure would look like on the ground. This past winter here in Michigan was, to put it lightly, a doozy. Two years ago, it was so mild that I was told that my first Michigan winter didn’t even count. It’s not hard to imagine that even after lineages have evolved to tolerate freezing (which is a big deal—it kills cells!), there can still be a lot of variation in fitness depending on the weather.

Think of a plant that lives for a few years, flowering in the summer, producing fruit in the fall, and dying back over winter. Let’s assume that there’s a resource tradeoff between manufacturing antifreeze and producing fruits.** This past winter, plants that invested a lot in antifreeze would have had high relative fitness in the population, because they alone survived. Two years ago, that same strategy would have had low relative fitness, because plants that produced less antifreeze would have survived the winter too, but had higher fruit production. In this hypothetical situation, there is some variation in fitness due to herbivores and pollinators etc., but most of it is due to the wildly variable weather.

In contrast, imagine a similar plant in a tropical habitat, growing in full sun. It experiences temperature stress too. The sunshine is actually more intense in the tropics because it’s hitting the Earth straight on instead of at an angle, so its energy is concentrated in a smaller area. It’s HOT! But it’s hot almost every single day of the year, so all the plants in the population invest in tolerating the heat to the same degree. Temperature isn’t contributing much variation in fitness in this population.

Life here is more like the Hunger Games. Who can grow the fastest? Who can avoid death by enemy herbivores and diseases? Who can form the strongest alliances with pollinators and fruit dispersers? Competition, antagonism, and mutualism is what determines fitness here, not the weather.***

Now that I’ve painted a picture of what Figure 1 could hypothetically look like in the real world, how can we figure out whether or not it’s true?

Ideally, you would pick a focal species and do an observational or experimental path analysis (e.g., Schemske and Horvitz 1988) to determine the relative contributions of various selective agents at different latitudes. Make sure you have an army of assistants, because you’ll need massive sample sizes. Did I mention you’ll have to do it for many years? You won’t want to miss important events like unusually bad winters or pest outbreaks. By the way, even though this kind of study would probably be impossible in animals, it’s also nigh-impossible to find an abundant plant species whose native range encompasses tropical and temperate latitudes, avoiding really dry places and high altitude. (If you know of one, please let me know!!)

Needless to say, filling in Figure 1 with real data has not yet been done, and given our funding climate, it probably never will. But, there are other ways to approximately test the hypothesis (Schemske, Mittelbach et al. 2009).

What we CAN ask is, what is the “intensity” of the interaction today? What do today’s traits tell us about selection in the past? And what is the frequency of an interaction in the community?

To illustrate each question in terms of pollination, we can ask how much do tropical plants rely on self-pollination vs. outcrossing; do tropical plants invest more in pollinator attraction and reward; and, do tropical plant communities show a higher frequency of animal vs. wind pollination? Fill in the blanks with your favorite interaction.

To build a relatively complete approximation of Figure 1, we should be asking these questions in many systems, across many types of interactions, and at many spatial and phylogenetic scales. For example, asking these questions within widely-ranging species (Salazar and Marquis 2012) is quite different from asking them at the community level, with disparate habitats, community membership, and growth forms (Moles, Wallis et al. 2011). Both approaches are needed, because each has huge advantages and severe limitations.

The most comprehensive review of the available data is a 2009 Annual Reviews paper by Schemske et al. (see their Table 1). They noted that the data was insufficient for meta-analysis. Nevertheless, they found that most interactions show greater “importance” at lower latitudes; that is, the interaction is more intense currently, the traits show that it was more intense in the past, or it is more frequent. None of the interactions shows greater importance at higher latitudes.

For example, in the tropics, predation rates on birds’ nests are higher. Ant predation rates on insect bait are higher. Parasite pressure is higher. Palatability of marine worms, salt marsh plants, leaves, and butterfly larvae is lower. The frequency of animal pollination, animal seed dispersal, ant-plant mutualisms, endophytes, and cleaning symbioses is higher. The review also finds that herbivory rates are higher and plants are better defended at lower latitudes, but a recent meta-analysis on herbivory came to different conclusions (Moles, Bonser et al. 2011).

Although the results are necessarily qualitative and we can’t put a p-value on this statement yet, this review shows that looking across many types of interactions, many ways of quantifying their importance, and over many spatial and phylogenetic scales, the weight of the available evidence supports Figure 1.

But I would be the last person in the world to tell you that we’re done testing part A of the biotic interactions hypothesis. Much of the available data was not generated to explicitly address it, so there’s always something missing. For example, herbivory rates could be the same at different latitudes, but tropical plants may be better defended, indicating that greater herbivore pressure has selected for stronger defense. You need both pieces of the puzzle, preferably measured at the same time on close relatives, to be able to say whether herbivore pressure is greater in the tropics.

I’ve spent the last three years thinking about how we can fill in the missing gaps. There are so many ways to test these questions, so many interactions and species to choose from. Each approach is limited in some key way; otherwise, the end-all, be-all experiment would have already been done! One could easily spend a lifetime chipping away at this question from different angles, without even addressing the bigger picture of whether this has anything to do with the latitudinal diversity gradient. (I’m working on that too though!)

Therefore, I was dismayed when I woke up on Tuesday to a post on a widely-read ecology blog that claimed that the hypothesis that biotic interactions are stronger in the tropics is a “zombie idea.” Meaning that it’s dead, it’s been disproven, we can all go home now, and anyone who studies it is just wasting their time.

Whoa. Not enough data for a meta-analysis, but we’re done with this question? A recent review concluded that there is support for the hypothesis, but now it’s been totally debunked? Did I miss something here?

In fact, I haven’t missed anything. As with any scientific controversy worth its salt, there are contradictory reviews, there are people who are highly skeptical, there is massive confusion about what the hypothesis is and how to properly test it. That’s all fine and good. It’s exciting, even.

What is not fine and good, in my book, is to proclaim from the rooftops that we’re done with a question that we’ve barely begun to address. To claim that a handful of publications on latitudinal gradients in herbivory are the end-all, be-all, period end of story of decades of research. To claim that any one of us has the final authority on how to define, test, and interpret an area of science.

A debate about an idea can be constructive and fun. But both my scientific and journalistic selves cry fowl when a story is presented hyperbolically from one point of view. I believe that it’s irresponsible and polarizing to instigate a debate by claiming that the problem is solved and there is no debate.

I’m glad that people are talking about the topic, though I wish it had been inspired by less inflammatory language. I hope the conversation inspires us to clarify what our questions are and how we can test them. I hope also that you agree that we don’t need more catchy metaphors (zombies, old clothes, lemmings, sheep). We need more data and more conversation. Period. But not the end of the story.


*There are so many species in the tropics! There are over 22,000 tree species in the Amazon, compared to 620 in temperate North America (Currie and Paquin 1987; Fine and Ree 2006). This pattern of higher species diversity in the tropics is remarkably consistent across different types of organisms and through time and space. How can the same underlying processes of ecology and evolution produce such different outcomes? We don’t really know! Sure, there are ideas. In fact, Palmer (1994) lists 120 hypotheses to explain it! But given the massive scale of space and time, it’s really hard to test these hypotheses, so a definitive answer remains elusive. See Mittelbach, Schemske et al. (2007) for a great review.

**For any of this to matter for evolution, we are also assuming that allocation strategies are not very plastic; that they are heritable; and that there is genetic variation for these strategies in the population.

***Why am I focusing so much on temperature? Lots of studies show that climatic variables, especially temperature, are tightly correlated with global diversity patterns (e.g., Currie, Mittelbach et al. 2004). In my opinion, for a few reasons, the biotic interactions hypothesis is the only latitudinal diversity gradient hypothesis that provides a plausible mechanism by which temperature can affect diversity. But actually, the hypothesis is generalizable to any gradient in abiotic stress. Although it was proposed to address the LDG, it applies to other gradients in abiotic stressors that covary with species diversity: altitude, ocean depth, precipitation, etc (Schemske, Mittelbach et al. 2009). This is a practical strength because components of the biotic interactions hypothesis can be tested in other systems, which may be more tractable than latitude. More importantly, it is a theoretical strength because confirming this hypothesis could revolutionize our approach to studying the origins of diversity in many systems.

References:

Cashdan, E. (2001). "Ethnic diversity and its environmental determinants: Effects of climate, pathogens, and habitat diversity." American Anthropologist 103(4): 968-991.

Currie, D. J., G. G. Mittelbach, et al. (2004). "Predictions and tests of climate-based hypotheses of broad-scale variation in taxonomic richness." Ecology Letters 7(12): 1121-1134.

Currie, D. J. and V. Paquin (1987). "Large-scale biogeographical patterns of species richness of trees." Nature 329(6137): 326-327.

Dobzhansky, T. (1950). "Evolution in the tropics." American Scientist 38: 209-221.

Farrell, B. D., D. E. Dussourd, et al. (1991). "Escalation of plant defense: Do latex and resin canals spur plant diversification?" American Naturalist 138(4): 881-900.

Fearnside, P. M. (2005). "Deforestation in Brazilian Amazonia: History, rates, and consequences." Conservation Biology 19(3): 680-688.

Fine, P. V. A. and R. H. Ree (2006). "Evidence for a time-integrated species-area effect on the latitudinal gradient in tree diversity." American Naturalist 168(6): 796-804.

Fischer, A. G. (1960). "Latitudinal variation in organic diversity." Evolution 14: 64-81.

Guernier, V., M. E. Hochberg, et al. (2004). "Ecology drives the worldwide distribution of human diseases." Plos Biology 2(6): 740-746.

Jablonski, D., C. L. Belanger, et al. (2013). "Out of the tropics, but how? Fossils, bridge species, and thermal ranges in the dynamics of the marine latitudinal diversity gradient." Proceedings of the National Academy of Sciences of the United States of America 110(26): 10487-10494.

Mittelbach, G. G., D. W. Schemske, et al. (2007). "Evolution and the latitudinal diversity gradient: speciation, extinction and biogeography." Ecology Letters 10(4): 315-331.

Moles, A. T., S. P. Bonser, et al. (2011). "Assessing the evidence for latitudinal gradients in plant defence and herbivory." Functional Ecology 25(2): 380-388.

Moles, A. T., I. R. Wallis, et al. (2011). "Putting plant resistance traits on the map: a test of the idea that plants are better defended at lower latitudes." New Phytologist 191(3): 777-788.

Palmer, M. W. (1994). "Variation in species richness: towards a unification of hypotheses." Folia Geobotanica & Phytotaxonomica 29(4): 511-530.

Paterson, S., T. Vogwill, et al. (2010). "Antagonistic coevolution accelerates molecular evolution." Nature 464(7286): 275-U154.

Salazar, D. and R. J. Marquis (2012). "Herbivore pressure increases toward the equator." Proceedings of the National Academy of Sciences of the United States of America 109(31): 12616-12620.

Schemske, D. W. (2009). Biotic interactions and speciation in the tropics. Speciation and Patterns of Diversity. R. K. Butlin, J. R. Bridle and D. Schluter. Cambridge, United Kingdom, Cambridge University Press: 219-239.

Schemske, D. W. and C. C. Horvitz (1988). "Plant-animal interactions and fruit production in a neotropical herb: a path analysis." Ecology 69(4): 1128-1137.

Schemske, D., Mittelbach, G., Cornell, H., Sobel, J., & Roy, K. (2009). Is There a Latitudinal Gradient in the Importance of Biotic Interactions? Annual Review of Ecology, Evolution, and Systematics, 40 (1): 245-269 DOI: 10.1146/annurev.ecolsys.39.110707.173430.

Nature Communications faux pas

This article in Nature Communications

has this figure showing the phylogenetic relationship between "contemporary human populations and Neanderthals":

Basically, the contemporary "out-of-Africa" individual is in a suit and a bowler hat, and the individual of "purely African ancestry" looks like a thug.

How does something like this get published in a prestigious journal nowadays?

HT @JacobPhD

Ignored

There is a website I am ignoring.

Sometimes the best action to take is to ignore. The organization and the man leading it want to influence society in a major way, and I disagree with their agenda. If I were to share with readers who they are, some people would go to their website, and they would get even more attention (and considering the huge amounts of traffic I get, it would be a lot*).

But I wanted to say that on this website they are talking about a certain event that was much covered in the media recently. I vehemently disagree with their views in general, and I think they are misrepresenting the event in question.

Their views are factually wrong, which I know based on a lot of evidence. I'd love to share this publicly, but again, more attention probably benefits said organization, and so I think the best solution is to ignore them.

Hereby ignored.

* Ha!

Tadpole plasticity triggered by dragonfly nymph predation (video)

Professor Rick Relyea from the University of Pittsburgh gave a fascinating seminar today: "Phenotypic Plasticity: Stress-Induced Changes in Behavior, Morphology, and Life History of Aquatic Organisms".

He showed this amazing and somewhat scary video of dragonfly nymphs and tadpoles.

Rick's lab website. Movie is downloaded from here.

Pragmatic definitions in biology

Biology is littered with concepts that biologists cannot always agree on how to define or where there are special cases where the common definition have to be amended. Species. Complexity. Modularity. Evolvability. Evolution. Genes. Community. Robustness. Open-ended evolution. Fitness. Life.

Take species. The current state of affairs is that there are many different definitions, and people can't always agree which one is best. Each one of us may have a favorite. (Mine is the Ecological Species Concept by Van Valen (1976) Ecological Species, Multispecies, and Oaks. Also, best title ever.) This often leads to more or less antagonistic attitudes among people, and can have negative effects on the review process.

As far as I'm concerned John Wilkins is the man to go to for species definitions. He lists 26 of them.

In this case, "species" is the concept, and curse Ernst Mayr for being first to call a proposed definition a "concept" (i.e., the Biological Species Concept - which should also really have been the Reproductive Species definition).

What I propose is the stop calling the proposed definitions "definitions", and instead call them "criteria".

That would make it

• The Reproductive Species criterion
• The Ecological Species criterion
• The Phylogenetic Species criterion
• The Taxonomic Species criterion
• ... et cetera.

When determining if two groups of living organisms are different species, all you'd have to do is go down the list and check off those criteria that are met (easier said that done, I know). And then when talking about this, qualify the type of species by naming it according to the matching criteria. Your two closely related groups of organisms would then be ecological and phylogenetic species in the case brown bears and polar bears, and reproductive species in the case of horses and donkeys.

The reason I propose this is that this sort of pragmatic meta-definition has the potential to end unproductive arguments and replace them with clarity - a clarity that emphatically depends on people qualifying the type of species/complexity/modularity or whatever else they are talking about.

Same thing for the other difficult-to-define concepts. Open-ended evolution is the idea that evolution just keeps going, and new forms and features (species, traits, genotypes, etc.) keep appearing. But for how long? Forever? That's longer than anything, so thats not very pragmatic, i.e. it is not a definition that can be applied, because we are too impatient to wait forever. Is natural evolution on Earth even open-ended? Would life on Earth ever reach a steady state after which evolution does not produce new things? Does co-evolution count if this produces new forms that have already existed in the past? Life on Earth is very much affected by the changing fitness landscapes when meteors arrive, volcanos erupt, and solar winds fry the planet, or whatever. Can we just create an evolving computational system in which huge disasters cause mass-extinctions at arbitrary intervals, and then say that the system exhibits open-ended evolution because it keeps evolving? How about these criteria:

• System evolves in never-ending cycles (revolving open-ended evolution)
• System reaches steady-state but is reset/interrupted by disasters (reboot open-ended evolution)
• System continues to evolve new forms for as long as we could wait (temporal open-ended evolution)

The point is to move research forward, rather than letting it be mired in argument, and I think that can be done by simply being more explicit about what we mean when we say something.

Anybody feel like taking a crack at evolvability or life?

Origin of life video

I just did a reddit Science AMA today, and whenever you talk about evolution, invariably the question of the origin of life comes up. It's not my field, as I am not a chemist, but here is a great video explaining a model of how life could have formed spontaneously from chemical elements in the pre-biotic Earth. It is based on research from Jack Szostak's lab.

From now on I will be pointing to this whenever I'm asked how the first cells came about.

Evolutionary dynamics in holey fitness landscapes

What do real fitness landscapes look like? Do they look more like the image on the left, a nearly-neutral holey fitness landscape, or the one on the right, a rugged fitness landscape with many distinct peaks?

Those are only in two dimensions, so the question is also if depicting anything in two dimensions conveys intuitions that are at all correct.

Holey fitness landscapes (Gavrilets and Gravner, 1997, Gavrilets 1997) are approximations of real fitness landscapes where all genotypes are assigned a fitness value of either zero or one. After normalizing fitnesses to be between zero and one, those that are lower than one are assigned a fitness of zero¹. Because real fitness landscapes are of extremely high dimensionality², and assuming that genotypes have fitnesses that are randomly distributed³, it follows that there exist a nearly-neutral network of genotypes connected by single mutations that has fitness (effectively) equal to one.

The proposition is then that this holey landscape model is a good approximation of real fitness landscapes. It hypothesizes that the evolutionary dynamics on real fitness landscapes is similar to that on holey landscapes, and that distinct peaks like in the image on the right do not really exist. And this is a testable prediction.

Take a look at these videos. They depict populations evolving in two-dimensional fitness landscapes at a very high mutation rate. (You can also download the videos from my research website.)

In all three cases the population size is 2304 (that's (3*16)², in case you're wondering), mutation rate is 0.5, the grid is 200x200 pixels (i.e. genotypes), and mutations cause organisms to move to a neighboring pixel. Ten percent of the population is killed every computational update (which gives an approximate generation time of 10 updates), and those dead individuals are replaced by offspring from the survivors selected with a probability proportional to fitness (asexual reproduction). Top: neutral landscape where all genotypes have the same fitness. Middle: Half-holey landscape with square holes of 10% lower fitness (size of holes is 14x14 pixels). Bottom: Holey landscape where the genotypes in the holes have fitness zero.

The proposition is that the dynamics of the populations should be the same no matter how deep the holes are. The populations in the half-holey and in the holey landscapes should evolve in comparable ways if the holey landscape is a good approximation.

So what do you think?

What I think is that the evolving population in the top (neutral) and middle (half-holey) landscapes resemble each other, whereas they look nothing like the bottom (holey) landscape. In the half-holey landscape the population takes advantage of the holes all the time, meaning that many individuals who are in them reproduce, even though they have a clear fitness disadvantage. The lesson is that being disadvantaged is just okay, and populations can easily cross quite deep valleys in the fitness landscape. But obviously not when the valleys consist of genotype with zero fitness; evolution in holey landscapes is much impeded compared to rugged landscapes, which is why I think they are not a good approximation.

Caveats: These populations are evolving at a very high mutation rate. When I redid it with a much lower mutation rate (0.05), the neutral and half-holey landscapes stop resembling each other, and the half-holey and holey landscapes look more alike. However, evolution happens so slowly in this case that it is difficult to distinguish the dynamics, so the matter is unresolved so far (however, I have other evidence that lower and more realistic mutation rates do not change this conclusion - some preliminary data in Østman and Adami (2013)). A second caveat is that the whole holey landscape idea relies on the fitness landscape being multidimensional, and so how can I even allow myself to compare evolution of populations in half-holey and holey landscapes in just two dimensions? That is valid question: the intuitions we get from these animations may lead us to think we know something about evolution in multi-dimensional landscapes, while the original premise of Gavrilets' idea was that we exactly cannot. Unfortunately, while this is an empirical question - meaning that it could be tested - the holey landscape model posits that the neutral network appears at very high dimensionality. What this dimensionality is is unclear, so even if I were to evolve populations in 2,000 dimensions (which is not computationally feasible - the limit is a little over 30 binary loci), one could always claim that not even that many are enough. Sighs.


¹ Genotypes with fitness greater than 1 divided by the population size, N, are effectively the same, because selection cannot "see" differences smaller than 1/N.
² High dimensionality means a large number of genes (loci) or number of nucleotides.
³ We already know that this is not a very good assumption, as there are indications that fitness landscapes are non-randomly structured with high fitness genotypes clustered with other fit genotypes (Østman et al, 2010), but we don't know if it is enough to render the holey landscape model useless.

References
Gavrilets S, and Gravner J (1997). Percolation on the fitness hypercube and the evolution of reproductive isolation. Journal of theoretical biology, 184 (1), 51-64 PMID: 9039400

Gavrilets S (1997). Evolution and speciation on holey adaptive landscapes. Trends in ecology & evolution, 12 (8), 307-12 PMID: 21238086

Østman B and Adami C (2013). Predicting evolution and visualizing high-dimensional fitness landscapes, in Recent Advances in the Theory and Application of Fitness Landscapes" (A. Engelbrecht and H. Richter, eds.). Springer Series in Emergence, Complexity, and Computation DOI: 10.1007/978-3-642-41888-4_18

Why do you believe?

Important update April 22nd, 2014: I have been corrected on the usage of the phrases "believe in" and "believe that". In the first sentence below I wrote "believe in something", but what I really meant was "believe that something". Thus, saying "I believe in evolution" is wrong, because it is not a matter of faith. People often respond to this by saying "No, I don't believe in evolution. I accept that evolution is true based on the overwhelming evidence." I have objected to this on several occasions before, but now see the difference. I prefer to say "I don't believe in evolution, I believe that evolution is true (based on the evidence)".

If you say you believe in something, what is it that you mean by that? For example, if you say you believe you will find a hundred-dollar bill today, what is that belief built upon?

I posit that what you actually believe (as opposed to what you say you believe) is really based on probabilities. Perhaps not accurately so, but all future events are of course unknown, though some come very close to 100% certainty, and it is thus really the only way to predict anything with any kind of accuracy.

Trivial example: If you roll a die, you might say that you believe you will get a six. But if we assume this is a fair die, you must assess that the chance is about one in six, so your belief should really be that you do not get a six. In that case you really can't have a rational belief that any one side will come up, though you do of course know with almost 100% certainty (i.e., 100% probability) that one of the six numbers will come up (the die could land on an edge).

In science we make models. That is the essence of the scientific endeavor. A model is basically some explanation of something; hypotheses and theories at opposite ends of a spectrum of explanatory depth are models. So if you as a scientists say you cannot imagine how something would work, how something could have happened, etc., then you basically aren't doing your job. People who dismiss science as rigid and uncreative have not understood what it really entails. Coming up with explanations is among the most creative things people can do. If you're writing a work of fiction, it would surely be defeat if you cannot think of a way to make something click in the story. Same thing with science. If you observe something and you can't imagine how that could occur, then get to work!

Positing a hypothesis is emphatically not the same as "believing" it to be true. That I come up with one hypothesis to explain something doesn't mean that I think it is the most likely explanation, nor does it mean that I can't come up with anything else.

For example, why do I think John Travolta said Adele Dazim when referring to Idina Menzel at the Oscars?

Hyp1: He was high as a kite and just mixed up some slightly related names.

Hyp2: Someone played a joke on him and told him that was her name.

Hyp3: It was on purpose because he thinks that Adele Dazim is a prettier name for her.

Hyp4: He wanted to rock the establishment to secure a role in a new indie film.

Hyp5: He has an occasional speech impediment.

Hyp6: It's a special Scientology accent.

I can assign probabilities to each of these. It may not be accurate (they don't need to add to one, and can actually add to more than one since they overlap somewhat), but at least approximate values or perhaps just a relative ranking of them. Each of these hypotheses could be tested, and my personal belief doesn't really have much to do about anything. I don't yet have any evidence either way, and evidence is of course the only thing we can really base rational belief on, though oftentimes that evidence is reflected in theories about, say, human behavior, in which case I can say I find Hyp1 more likely than Hyp6, because I have seen evidence of only one of them happening before.

The answer is evidence. If you have none, they you have no reason to believe anything. Hypothesizing is not the same as believing, and can be done freely without repercussions. At least that is how things ought to be, everywhere and always.