This relates to why you will often see multiple mushrooms of the same type blooming at the same time in a ring pattern: the edge of the ring is the periphery of the linearly, radially expanding mat of subterranean fungal fiber weave, which produces fruiting bodies at its edges.
The inside of a fairy ring dies off as it uses up nutrients.
The leading edge of the circle remains alive so that is why the fruiting bodies (mushrooms) are there. The fungus produces nitrogen which leads to the growth of a greener ring of grass.
The ring’s steady expansion is driven by growth of the underground mycelium (not spores).
>Thus, one may guess, that first distinctive poisonous mushrooms like the fly agaric developed, then most animals large enough to eat them developed an instinct to avoid all mushrooms, and then the non-poisonous freeloading mushrooms developed.
Just wanted to note that these phenomena are important enough in the study of mimicry in biology to have earned their own names:
Müllerian mimicry is when two species who are similarly well defended (foul tasting, toxic or otherwise noxious to eat) converge in appearance to mimic each other's honest warning signals.
Batesian mimicry is when a harmless or palatable species evolves to mimic a harmful, toxic, or otherwise defended species.
In The Selfish Gene, Dawkins emphasized that the primary unit of evolution was the individual gene, not whole genomes. The genes were replicators and the genomes were just collections of replicators, and the way the selection pressure math worked out, there was too much diffusion of responsibility for whole genomes that typically evolution could not work coherently at that scale, or at least that's my best recollection of the book's main theory.
Regarding intentionality being a good practical assumption, I actually don't recall Dawkins recommending that, and it seems doubtful because that can lead to all kinds of fallacious reasoning. I mostly considered Dawkins a data-based neo-darwininian, so it would surprise me that he would recommend that.
Could you recall a quote or chapter from the book that bolsters your point?
Yeah, that's not really good enough, by the author's own admission:
From wikipedia: 'In the foreword to the book's 30th-anniversary edition, Dawkins said he "can readily see that [the book's title] might give an inadequate impression of its contents" and in retrospect wishes he had taken Tom Maschler's advice and titled it The Immortal Gene.[2] He laments that “Too many people read it by title only.”' [0]
Furthermore, your concept that genes should be thought of as having a plan is just in stark contradiction with the Darwinian conception of natural selection, which Dawkins was largely a champion of.
My own recollection was that he described how genes readily had the appearance of acting in their own best interest, but he fell short of advocating that modeling them as having intention is a useful contrivance. Evolution does not have any sense for the future, there is no planning evolved, and Dawkins understands that.
That's fine, all I'm saying is that if genes don't actually have intention, then the utility of modeling them as though they do must be strictly limited, if not an outright liability in some contexts. Use the heuristic at your own risk, but don't sell it as gospel truth.
> An observer says "the infection wants to be resistant"
I can confidently claim that literally nobody says this because a google search for this exact phrase has only one result, and its this thread.[0]
Really though, I have never met a biologist who thought this way. All of the ones I've met and worked with knew that development of antibiotic resistance is not in any way like a decision process, and they usually understood on an intuitive level that bacterial cultures don't have a goal of developing the capability. Its just something that evolves, which is a distinct category of process.
Talking about it the other anthropomorphic way, like you claim is normal and acceptable, just confuses things; it is the opposite of helpful analogy. Infections don't "want" anything, they are better understood using the details of their actual biomolecular mechanics, which are about as far different from how brains work as could be imagined.
You're choice of samples is rather skewed towards ones sharing a relatively recent common ancestor. Octopus and Sea Squirts are also animals, and they don't have legs or torsos or, in the later case, heads or eyes. Octopus brains are also rather different from those of vertebrates, and they have 8 mini-brains for more distributed/localized control of each major limb.
That said, I agree with you that there is a lot of commonality in life. Even in the case of Octopus we share a lot of DNA. I just mostly think that is due to common ancestor and common environmental pressures, not to some fundamental limit in the breadth of evolutionary potential itself. Its probably worthwhile to wonder at how that actually works though. Maybe evolutionary potential could be improved.
Of course there is bias, the bias is provided by the natural environment where the organisms coded by the genome must thrive or die. The bias is applied after the mutation occurs, but the mutations themselves are random, or nearly so. Probably there is some differential rate between the likelihood of each of the four base pairs to mutate into each of the others, but I would guess its nearly parity, because that would probably be close to optimal (though that depends on the details of the genetic coding scheme, ie the triplet code that translates nucleotide triples into amino acid codons).
> If you calculate the pure combinatorial distance between the DNA of 2 species, you must find that you can't just brute force your way from one to the other before the heat-death of the universe.
Can you expand on this? I'm not seeing why it is implausible for one genome to mutate into another, that seems like it could be accomplished in reasonable time with a small, finite number of mutations performed sequentially or in parallel. After all the largest genome is only about 160 billion base pairs, and the average is much smaller (humans are 3 billion base pairs). So what's the difficulty in imagining one mutating into another?
> how to square the idea that evolution produces knowledge with the idea that it doesn't optimize even for reproductive fitness
Its really fairly simply: natural selection requires two things: heritable genetics and a source of variation in the genetics between individuals. Mutation is the most basic source of variation, and that produces new information. But new information isn't necessarily knowledge. Assuming a scientific testing gloss, each new genetic code variation X can be considered as a hypothesis, that "variant X is fit", and then natural selection events that act on copies of X (for or against) serve as experiments testing the hypothesis. Through iterative experiments, we weed out the copies of the variants where the hypothesis of them being fit was proved by natural selection to be false, and what remains should be those copies of genetic variants which have (mostly) proven to be true. Learning and understanding which variants are fit (where the hypotheses are true) is knowledge, and in this way evolution produces knowledge while not having any optimization goal (in the intent sense, which I agree is a requirement for something to be meaningfully "optimizing" anything, because you can't aim in a direction without a sense for that direction).
> Assuming a scientific testing gloss, each new genetic code variation X can be considered as a hypothesis, that "variant X is fit", and then natural selection events that act on copies of X (for or against) serve as experiments testing the hypothesis
this is the problem i have with natural selection... it has no predictive power. You can never use natural selection theory to say if an organism is "fit" before it exhibits its fitness. what good is this?
This may be more a problem with how "fit" is defined and used than with natural selection theory itself. Fitness can be hard to define beyond the trivial "these organisms which survived the selection event must be the fit ones," and natural systems are usually so noisy with inputs that its hard to figure out what was actually important in retrospect, or likely to evolve in the future.
Only in situations with a powerful selection pressure (like an asteroid strike causing a nuclear winter, or antibiotic applied to a petri dish) can one have a hope of reliably predicting which variants will be selected for or against.
However, these situations are not irrelevant, especially if we can predict the likelihood of those situations developing. Real predictions of the theory of natural selection can be applied to managing antibiotic resistance in populations of bacteria. For example, we know that antibiotic resistance mechanisms that bacteria evolve will often have an energy metabolism cost to their maintenance. This means that, absent pressure to be resistant to antibiotics, we'd expect a population to gradually lose individuals with the genes for the resistance mechanism, because they would be incurring a metabolic penalty for possessing those genes. So natural selection theory accurately predicts that if you remove the selection pressure of the antibiotic, the bacteria will evolve to lose the resistance mechanism, and become susceptible to the antibiotic again over several generations of natural selection. Using this knowledge, some rural regions will discontinue use of a given class of antibiotics in agriculture to allow for resistant strains to decline, and then resume their use when they are again effective. By intelligently rotating use of antibiotics in this way, we can enjoy their benefits without incurring too much inefficiencies and worse tragedies from antibiotic resistance.
There is no broader context wherein natural selection can be considered to be an optimization process, that is a pernicious misconception of evolutionary theory. Fortunately, people with a computer science background have a distinct advantage towards correcting this fallacy, because their training affords them an understanding of information as a working concept that lay people rarely attain.
The key insight is that any algorithm implementation for a process which has an objective must, as an absolute minimal requirement, possess an encoding of that objective in its implementation. That is, a real representation of the goal must be in the process's make-up so that the goal can be pursued at all, because correct navigation requires assessing actions for whether they work towards the goal or not, and any such assessment requires meaningful reference to the goal. Without such a definition to refer to, differentiation between desirable and undesirable outcomes is impossible.
This goal encoding may be explicit (ie readily understandable by observers studying the implementation) or implicit (hard to parse), but either way, it must be instantiated in the make-up of the implementation, in some medium with the capacity to hold the goal definition, ie a way of storing the requisite number of bits within the implementation itself (or readily reading it from elsewhere, or constructing it from some combination thereof). This definition of the goal must be implemented in a manner that can be read and acted upon by the rest of the algorithm implementation, so that the system as a whole can pursue states that better match the goal. ie so that it can optimize.
With regards to evolution, how could nature select without having an idea of what it was selecting for? A reference definition of fitness must be available to nature if it is to measure each individual organism's fitness and select accordingly.
For a natural-selection-as-optimization-process algorithm implementation, there would need to be a component that encodes natural selection's optimization objective into the implementation's very make-up (or a ready way to read that goal from an external source).
What is the make-up of the natural selection algorithm's implementation? It is the entirety of nature itself, in whole and in part. Nature is literally everything in the universe, and literally anything in the universe, from the most massive galaxy to the smallest particle, can participate in natural selection events. And no part of nature, save for some animal brains, seems to contain a representation of a goal for natural selection.
Is it even conceivable that everything in the universe, down to the smallest particle, could encode a common goal? Does a volcano encode the goal of maximizing reproductive fitness for the populations living around it? Can a shower of cosmic rays encode the goal of making sure the creatures who's DNA it disrupts are the ones who should be removed from the populace? They don't appear to encode any such evolutionary goals, nor do they have the capacity to maintain any goal at all beyond following the physical laws of matter -- Volcanos are disordered piles of rock and churning lava, and cosmic rays are singular fundamental particles that are subject to wholesale transformation with every impact -- neither has any way of encoding a common objective for natural selection, nor is there evidence for them being able to collectively maintain one.
We can illustrate the paradox of an optimizing nature using your water molecule analogy. A collection of water molecules acting under a gravitational field will demonstrate downwards fluid dynamics which single molecules in space would not, but no matter how much H2O you put together, it will never spontaneously develop any concept of evolutionary fitness.
And yet a flash flood is a very real natural selection event that can reshape the genepool of a coastal town, but all the same it has no means of representing any goal of optimizing the population's fitness through who it drowns and who it spares; its just water. Flowing water performs natural selection, but it isn't optimizing for any goal, no matter how you try to spin it, because it has no way of maintaining a representation of a goal in its disordered and inconstant structure. It flows, yes, but it has no goal in doing so, its not pursuing any optimization objective, all the while it is a real instance of natural selection. It doesn't have or need any way of determining who is more or less fit than another, so how could it be optimizing for it? It's just flooding.
Whether its by deluge, an erupting volcano, a congenital heart attack, or a pack of rabid dogs, the processes making up natural selection events do not possess an encoding of a goal for natural selection. They do not possess the necessary information structure required to pursue a common optimization objective, and so they cannot be optimization processes in any meaningful sense.
> The key insight is that any algorithm implementation for a process which has an objective must, as an absolute minimal requirement, possess an encoding of that objective in its implementation.
I don't agree with this in any way, or perhaps more accurately, I don't agree that we know (and perhaps could know) the scope of the implementation even if this claim was true, which I don't think it is.
The idea that "people with a computer science background have a distinct advantage" is also plainly wrong to me. I have a background (as in, I quit my PhD in) computational biology, have been a software engineer for more than 35 years, and there are just as many people with as without computer science backgrounds who fall for the fallacy.
What part of it don’t you agree with? That an algorithm implementation must encode the goal that it pursues? How can something pursue a goal it has no access to a definition of? If you have an alternative way it could work, please propose it.
I’m not asking rhetorically, I’m truly interested in learning the flaws in my argument for why natural selection cannot be modelled as an optimization process. So if you have the time to reply with a more detailed rebuttal, I’d much appreciate it.
edit: Addendum: I recognize my claim that computer scientists might have an advantage in understanding this is contentious, and I was not implying that they (we) as a group have a better record of understanding evolution’s subtlety than biologists (which I studied in uni) or the average lay person. I just think they could have an advantage in understanding the version of the argument that I gave above, and I am interested in improving it for that purpose.
What is the algorithm implementation when it comes to the physical world? Does the implementation extend to remote galaxies? Is the strong force part of the implementation? We don't know ... there appears to be no way to know.
But even if you could know, it is just demonstrably wrong that the implementation must encode the goal. If you create selection pressure, and have a reproductive system that allows for mutations, then you may end up an "implementation" that encodes the goal implicit in the selection pressure. But anyone who messed around with genetic algorithms or artificial life in the 90s knows that you can trivially start out with no resemblance to "the goal" at all. Where life on earth in aggregate or any specific example of it in particular might be along that pathway is similarly impossible to say.
Finally, even defining "the goal" is tricky. Consider the well-documented case of moth evolution in industrial (and later, post-industrial) northern England. Their camouflaging wing tones changed to respond to the typical color on vertical surfaces, twice within a human generation or three. Was "the goal" flexible coloration across generations, or was it "light, then "dark" and then "light" again? That's a philosophical question as much as anything ...
> What is the algorithm implementation when it comes to the physical world?
It is the physical world, nature is the implementation of the natural selection algorithm. Yes, the strong force is part of the implementation, because the strong force can play a role in selection events, cf nuclear bombs and radiation. The gravitational pull of remote galaxies can also influence selection events by changing planetary orbits minutely.
I don’t see these as problems for my argument because I am not the one claiming they encode an objective, I just see them as natural forces which can influence selection without any overarching purpose or goal. It is those claiming natural selection is an optimization process who must show how it could work. The onus is on them to show where their supposed objective of natural selection is encoded in its implementation.
> If you create selection pressure, and have a reproductive system that allows for mutations, then you may end up an "implementation" that encodes the goal implicit in the selection pressure.
What goal are you referring to?
> But anyone who messed around with genetic algorithms or artificial life in the 90s knows that you can trivially start out with no resemblance to "the goal" at all. Where life on earth in aggregate or any specific example of it in particular might be along that pathway is similarly impossible to say.
I am one of these people, but I don’t know what goal you are saying these systems came to demonstrate. Are you saying these artificial evolution systems had objectives they pursued? What caused them to follow these objectives? What is this “pathway”?
>Consider the well-documented case of moth evolution in industrial (and later, post-industrial) northern England. Their camouflaging wing tones changed to respond to the typical color on vertical surfaces, twice within a human generation or three. Was "the goal" flexible coloration across generations, or was it "light, then "dark" and then "light" again?
There was no goal at any point in the process. Moths with colors that matched their contemporaneous environment were less likely to be eaten by predators than those which stood out. Calling it a goal is a confusion, its trying to add a conceptual framing that isn’t necessary and adds nothing to the understanding of the system. Neither the soot levels in the air nor the birds hunting for moths have a goal of adjusting the balance of moth coloration phenotypes. They are just the context, along with everything else in their environment, in which evolution of moth coloration may occur.
In what sense is there any goal in the example? And if it is a goal, why is it not optimization? I claim there is no goal, no optimization objective to natural selection. Its not just a philosophical side question, it is the question.
> It is the physical world, nature is the implementation of the natural selection algorithm.
But you don't know (and to some degree, cannot know) which parts of it. So you cannot really know if the implementation encodes a goal or not.
> What goal are you referring to?
Whatever goal was being used in the case of genetic algorithms or artificial life systems. Those systems have goals, but the early stages do not embody the goal in any way you could recognize.
> There was no goal at any point in the process.
So in the case of natural evolution, we happen to agree. However, I don't agree with your claim that "the implementation must embody the goal" is a useful way to think about this, and I also have some sympathy for the idea that there could be huge-time-scale teleology associated with evolution that we cannot discern.
Its conceivable that the universe could encode a goal somehow, after all its so vast, but that conceivability alone is not evidence for the existence of an encoded goal any more than the conceivability of extra-terrestrial intelligence, or of a higher design to reality, is proof of their existence. What science tells us is that the only goal nature seems to embody is following the physical laws we've been able to determine, and nothing more. I'd apply the same interesting hypothesis status to huge-time-scale teleology that we cannot discern, and perhaps it is both real and we will never be able to discern it. Personally I find the notions very interesting, but I don't see reason to believe in them. If there were good evidence for them, they'd be the subject of scientific study already.
But we seem to agree that natural selection doesn't have a goal. In my observation, any purported overarching goal that is ascribed to natural selection, including the measure of inclusive fitness[0], can be reduced to some function of the context in which it is being observed, like moth coloration was influenced by soot levels.
As to my main claim, I do believe it is necessary that an encoding of a goal is necessary for choice among actions in pursuit of a goal, because some kind of reference to a goal is necessary to compare options in a decision algorithm. In the case of a-life systems which have goals, that encoding is somewhere in the algorithm of evolution rules combined with the initial state of the simulation. In the case of nature, I don't see a place where that encoding could exist, except the trivial "goal" that all elements will follow the laws of physics.
Please note though that I never put it that "the implementation must embody the goal," I was more careful with my language by saying that it must have an accessible or working encoding of the goal, one its decision process or evolution rule would need to reference in order to make decisions that favored it. The encoding need not be internal (so embody is definitely not necessary), and none of these things are necessarily explicit or well partitioned (e.g. an evolution rule can implicitly encode a goal).
edit: addendum: [0] On inclusive fitness being reducible to situational factors, I'm just following the direction of M.A. Nowak, C.E. Tarnita and E.O. Wilson on this: https://www.nature.com/articles/nature09205
If I'm standing near (but not directly on) the pointy part of the lemon shaped planet, do I feel like I'm standing on level ground, or am I on a slant?
The surface shape of the planet is pretty much defined by what feels gravitationally flat at that point, so it would feel flat. If it wasn't flat, the gas would flow "downhill" until it did. (Oh, yeah, by the way, gas, so you're not going to be "standing" per se.)
Makes sense, thanks. I guess it would only feel like a slant if the "force" causing the odd shape, the gravity of the pulsar, was removed. Then all the extended gas would fall back towards the center, while a solid planet might be able to maintain its odd shape. Then that pointy end would be like a giant mountain, in terms of how it would feel to be on.
Now I'm wondering if the planet is tidally locked, otherwise the forces on the extended and retracted bits of the lemon would shift widely as the planet rotates. Actually we could then model the extended bit as a giant tidal wave, er, tidal cloud. What a world.
The "solid" planet actually wouldn't keep its shape either. :D Part of the definition of a planet is being in "hydrostatic equilibrium". Even rock is basically a liquid at the scale of, say, Ceres. But yeah, you've got the idea.
