Arete

How about "contrary to all observations"? Evolution can and does occur due to genetic drift, and genetic drift is present large populations. This is a non-sequitur to human populations being under genetic drift. Also, assuming that humanity is a single, panmictic population is also wrong. http://www.sciencemag.org/content/298/5602/2381.full Therefore, no assumption about unidirectional selection on the human population is either inferred or assumed. Different populations of humans can and do evolve in different ways. Additionally, not all evolution is directional. Selection pressure - you're actually the one who claimed "Also it is no longer 'survival of the fittest'. It is now survival of everyone!" in the opening post. As I quoted in post #2, the Framingham population is becoming shorter, stouter, to have lower blood pressure, and longer reproductive times. This strongly infers selection for a lower risk of heart disease, and for a longer period of fertility in females. So human populations appear to be actually evolving rapidly in response to selection, rather than the opposite.

A large population is still subject to evolution via genetic drift. To claim otherwise is simply false.

This is categorically false. In fact, in small populations, drift can actually overwhelm selection in driving the evolution of a population. E.g. http://onlinelibrary.wiley.com/doi/10.1111/evo.12464/abstract http://www.genetics.org/content/194/1/235.short http://onlinelibrary.wiley.com/doi/10.1111/mec.12524/full

No, you're not right. Even a population in perfect Hardy Wienberg Equilibrium and the complete absence of selection will evolve via genetic drift. In the case of humans, a comprehensive study of human evolutionary trajectories was undertaken as a part of the Framingham heart study and showed rapid evolution in a human population. This study showed that women in the Framingham population had evolved to be slightly shorter and stouter, to have lower total cholesterol levels and systolic blood pressure, to have their first child earlier, and to reach menopause later. http://www.citeulike.org/group/13436/article/6436046

Apart from being just plain wrong - this statement is confusing; biological evolution is defined as being a change in allele frequency, through generations over time. Given it's been observed in virtually every population ever observed (e.g. http://evolution.berkeley.edu/evolibrary/misconceptions_faq.php#e1) ,this is like saying "scientists and mathematicians who have proven beyond any question that evolution that the sky is purple." As the rest of the post follows such a blatant and thoroughly incorrect fallacy, it becomes irrelevant.

Back in post #115 you said this: "That won't work, according to the professional understanding given us on this forum. You have to discover and subtract the influence of stochastic events - and no, a null model does not do that automatically." So you told us that measuring changes in allele frequency and comparing them to a null distribution would not allow us to detect selection. You've never demonstrated why this is true, and now you're saying that a request to demonstrate that is untrue is irrelevant... leading this - To be about the only thing I would agree with that you've posted.

I think at the NIH/NSF level of reviewing, the process is pretty good. Grants are judged by a panel, and panelists have to physically be in attendance at the review, so there is no chance of it being unofficially palmed off to a subordinate like a paper review. The elephant in the room is always that there isn't enough money. The number of proposals/scientists keeps going up, with funding rates remaining stagnant or decreasing. What ends up happening is that you have many more perfectly appropriate, important and viable proposals from capable scientists than you have money to fund. As a result, it becomes somewhat subjective as to which of these grants you will actually fund. Sometimes the reasons for not funding a grant can be extremely trivial and flimsy, because in reality, they probably are. This means there is a significant element of luck/stochasticity in what does and doesn't get funded, which is extremely frustrating for a scientist investing considerable effort in writing long and involved grant applications. It can seem like a considerable waste of time/effort/resources to have all these scientists writing applications when ~95% will not result in any return. However, on the other side, I think the likelihood of public money being spent on frivolous/flawed research is pretty low. Ultimately, I think the big issue is that since the GFC (and even before it) there's less money to go around, so deciding who gets it can come down to unimportant details.

What? That's specifically what you're saying we cannot do; i.e. separate the genetic effects of selection vs stochastic change. That's specifically what it does do.... You have this backwards. Tajima's D statistic (and MK tests, Dn/Ds ratios, etc) apply to populations, not across taxonomic groups.

You keep repeating this, however it contradicts population genetics quite comprehensively. As a result, you'll need to do more than simply state it. You could start with something simple, like explaining why Tajima's D does not adequately account for stochastic variation. Here's the method: http://www.genetics.org/content/123/3/585.full.pdf+html and here's the paper where Tajima explicitly explores the impact of fluctuations in Ne on the statistic: http://www.genetics.org/content/123/3/597.full.pdf+html N.B. these papers are 25 years old, so there are more sophisticated methods out there, but proving inherent bias in Tajima's D would be a good starting point. The scientific method goes to great lengths to avoid absolute claims, however, when a theory allows for predictions to be made, and observations confirm those predictions, we are able to provide support for a theory. You don't just observe things and make up a story to explain them - you have to quantify how well they fit your predictions, and thus how well they support the theory behind them - and there's always probabilistic room left for the observations to fit the predictions through chance. Lengths are usually gone to through replication to minimize this chance, until we're pretty certain we have the best explanation for observed data. Again, the former. The invocation of natural selection allows us to make detailed predictions about the genetic makeup of populations. We then make observations of natural populations, and use statistical methods to quantify how well the observations match our predictions. In the case of quantifying selection in population genetics, the use of current methodology has been thoroughly validated with both theoretical and empirical approaches. In the words of xkcd - it works, bitches... If you wish to make the claim that a prediction other than selection explains the observations more comprehensively, you'd need to validate that; you can't point at a p value of >0.001 and say "Hey look it might be wrong, so I reject it" objectively, unless you have a more probable explanation. In the case of selection and deviations from HWE, we have an extremely good fit of countless datasets, and no better explanation for the overwhelming majority of them. There are special cases where the assumptions of HWE are met and deviation is not caused by selection, but these cases are the rare exception, rather than the rule.

A change in temperature on a thermometer is a change in the volume of the mercury inside it... what causes the change in volume? Who knows? [/sarcasm] The use of HWE deviation as a measure of the strength of selection is observationally validated e.g. http://www.pnas.org/content/98/16/9157.short http://library.wur.nl/WebQuery/clc/1925471 Much like the use of a thermometer to measure temperature. The argument that we don't actually know what causes deviations from HWE is about as relevant as arguments that we don't know for sure that Zeroth's Law explains variations in the volume of a fluid, etc.

No, I meant no. By definition, the stochastic elimination of alleles from a population is random, thus over time, it is predictable, thus can be modeled quite accurately using a distribution. Each allele has a frequency in a population, and scaled to frequency, an equal chance of persisting to the next generation, or being eliminated. That does not require any specific knowledge of specific events, even in the event of fluctuating Ne. An event which as a higher chance of eliminating certain alleles from a population than others is selective, not stochastic. It would rightfully show up in a selection test as selection. Again, an event which as a higher chance of eliminating certain alleles from a population than others is selective, not stochastic. I believe it's a problem of basic definitions rather than semantics - a founder effect and a bottleneck describe specific effects which are certainly not selection, but affect the evolution of a population in specific ways. I'm also confused by your implication that large scale, stochastic events have to be considered "selection" in order for diversification to make sense - could you give an example? At the moment, the suggestion seems nonsensical to me, but it could be a lack of comprehension, unless you're making the same mistake as starlarvae and neglecting to take into account that a large scale modification of an environment (e.g. elimination of a predator, creation or destruction of a habitat, etc) results in a change in selection pressure.

Hence the existence of P values, confidence intervals, false discovery rates... in fact, really, the existence of statistics to limit type I and II errors. No, you need to know what the alellic frequencies of a population are expected to look like in the absence of selection. As a theoretical technicality, - no population is in absolutely perfect HWE. However, the purpose of a selection test is to detect statistically significant deviations from the HWE (As in "We're X% sure this population is not in HWE and thus under selection") - thus a quantifiable estimation of the impact of selection on a population. To do so categorically does not require you to know about individual stochastic events. No, it would not - and I'm not following your reasoning as to why you came to that conclusion. A reduction in overall allelic diversity does not cause the same genetic signal as selection. The only reasoning I can come up that's even close with would be that substantial population bottlenecks or founder effects can result in a heterozygote deficiency which can look like selection. However, there are specific statistical tests, e.g. http://www1.montpellier.inra.fr/CBGP/software/Bottleneck/pub.html to seperate the effect of bottlenecks from selection. Such tools will tell you if the observed change in allele frequency statistically deviates from a null model. If observed changes in allele frequency deviate from a null model (barring some caveats) the population is, by definition, under selection at the genetic loci which are being tested. That's not a confusion of causality and correlation, that's measurement. As an analogy, if readings on a thermometer are going up over time, it's getting hotter. If what you're saying is the detection of selection doesn't immediately allow one to determine the source of selection, that's quite right - and I don;t think anyone has suggested that. You're describing changes in environmental selection - i.e. the creation of a dam, either by landslide, beaver or human is a change in the aquatic environment which can subsequently alter selective pressures on species living in such an aquatic environment. In relation to your previous discussion of epigenetics, this is quite a confounding example.

A regulatory change is not necessarily an epigenetic change, in fact most are heritable changes in regulatory regions and transcription factors.

Yes, that is correct. If a force favors the survival or reproduction of one phenotype/genotype over another, it is selective.

A population exposed only to stochastic elimination of alleles IS the null model. This is what is referred to as genetic drift. Hence the distinction between selection and drift. Stochastic effects on allele frequency are generally always considered separately. 1) Well, no. Generally, one would look to see if the observed data deviated from a drift model to a statistically significant degree. A population genuinely deviating from a drift model while only experiencing drift would be a statistically anomalous type 1 error. 1a) No again, it demands that you know what a stochastic model of genetic data looks like (i.e. Hardy-Weinberg equilibrium) 2) Yes, that is what I stated - the elimination of a genotype from a population via drift is proportional to the frequency of the genotype in a population: rare alleles are more likely to be lost than common ones. 3) I don't see the relevance - or the blanket applicability of the statement; many populations are panmictic. However significant population structure within a sample or significant non-random mating will generally violate the assumptions of a selection test and potentially yield an erroneous result, sure. Often HWE tests are used to determine deviations from these assumptions, rather than to look for selection. Drift is distinguishable from selection - in fact that is precisely what the aforementioned tests achieve. Drift can cause changes in a population and extinction events, sure. But it's distinct and definable outside of the effects of selection. Yes, the other major force we are discussion here is stochastic events, which are generally defined as genetic drift. The issue I think is that it's fairly basic population genetics to statistically separate the effects of both selective and stochastic forces when assessing the evolution of a population, and to say that you can't would seem to contradict basic population genetics.

Epigenetics is a very loose term for a wider range of more specific processes which are heritable, but not directly attributable to non-synonymous changes in coding DNA . To infer that evolutionary biologists have not been considering regulatory functions, secondary RNA/DNA structure, methylation, etc. would simply be wrong - some of these have been studied for a long time, and their roles in evolution have been considered for just as long. The reason that most scientists wouldn't consider their advent to herald a "new paradigm" is both due to their gradual inclusion in evolutionary study, and the fact that they don't overthrow the traditional model of expression, phenotype, selection - in fact the very word "epigenetics" implies that they overlay the existing genetic model. Additionally, epigenetic changes are subject to environmental selection themselves, so are consistent with existing evolutionary theory. In fact, there's a rapidly growing body of literature on the entwined roles of natural selection and epigenetic gene expression regulation in tumor growth. As such, most people actively researching and thinking about contemporary evolutionary theory have long incorporated "epigenetic" changes in their interpretations.

If an event has an equal probability of eliminating all genotypes in a population, it will not cause the population to deviate from Hardy-Weinberg equilibrium - barring certain demographic changes which violate selection tests such as population subdivision. Therefore such an event will not show up in a test for selection, and is not generally considered a selective pressure. If all genotypes have an equal chance of being eliminated, none are being selected for. Stochastic events can and do change the allelic frequency of a population and thus drive evolution. However, the result is stochastic via the random elimination of certain alleles, relative to their frequency in the population. This is generally why rare alleles have to have high fitness coefficients to persist in a population. If an allele has no effect on fitness, stochastic events are likely to eliminate it from the population. Conversely, if an alelle has a net negative/positive consequence on fitness, and thus is selected for/against, the probability of it being eliminated from a population changes accordingly. Thus, selection will either favor the prevalence or elimination of the allele above and beyond simple chance. This is what is tested for when population geneticists look for the signature of selection in genes and genomes.

The field of population genetics will be interested in how you've proven Hardy-Weinberg exact tests, Fisher's exact tests, the MacDonald-Kreitman test, Dn/Ds ratio tests, Tajima's D, the LD likelihood ratio test, etc etc, etc to be flawed. Testing against a null model is how selection is identified in population genetics. Well, yes. If an event has an equal probability of eliminating all genotypes in a population, it will not cause the population to deviate from Hardy-Weinberg equilibrium - barring certain demographic changes which violate selection tests such as population subdivision. Therefore such an event will not show up in a test for selection, and is not generally considered a selective pressure. If all genotypes have an equal chance of being eliminated, none are being selected for. Ergo, such an event is not considered a selective force. Changes in allele frequency caused by an event which has an equal chance of eliminating all alelles from a population is rather, by definition, stochastic rather than selective.

Nope, sorry. This is basic evolution 101. Your definitions are simply incorrect. Again, selection is the force which results in differential reproductive success. Measuring a change in allele frequency and comparing it to a null model is one of the ways of identifying the impacts of selection. Analogously, you can measure a change in the speed of an object to infer the impact of wind resistance, however wide resistance is not a change in speed or vice-versa. One can cause the other, but they are distinct terms. Again, nope. You can quantify selection - actually quantifying the force of selective pressure, and the genetic/phenotypic response to selection pressure is a significant area of study in evolutionary biology. To suggest that biologists simply hand wave about selection is to ignore decades of quantitative research. e.g. http://myxo.css.msu.edu/lenski/pdf/1997,%20Nature,%20Sniegowski%20et%20al.pdf http://onlinelibrary.wiley.com/doi/10.1111/j.0014-3820.2003.tb00326.x/abstract http://faculty.virginia.edu/brodie/files/publications/Brodie%20et%20al%2095%20TREE.pdf http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1000698 http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0022881 etc.

Except "differential reproductive success" is not what natural selection is. Selective forces are environmental conditions which lead to differential reproductive success. Therefore, natural selection describes the process by which environmental phenomena result in differential reproductive success within a population, and thus, evolution. Natural selection is not superfluous - in fact it's one of the most observationally verified parameters of evolutionary theory.

Well, given I haven't made any claims, let alone claims I subsequently refuse to support, that wouldn't make very much sense. However as has been noted by several posters, evasion is a problem which permeates your argument comprehensively and significantly invalidates many of your points. My unanswered point remains the same. If something is obviously true - for example, if I claim "The sky is blue" - it's trivial to support such a claim with evidence. e.g. a peer reviewed publication that explains that the sky appears blue due to Rayleigh scattering: http://www.patarnott.com/atms749/pdf/blueSkyHumanResponse.pdf As such, a claim like "it's obvious, I don't have to prove it" is spurious. If it's obvious, it should be trivial to provide proof rather than continue to engage in evasion tactics.

If something is obvious, it's trivial to prove - is that really that difficult to understand, or are you being deliberately obtuse?

If no one understands you, by definition, you did not explain it well. If something is obvious, it should be trivial to find supporting evidence. "I'm not providing evidence because it is obvious" is a terribly unpersuasive argument.

Rather than simply slinging around insults, provide any, even one, peer reviewed source indicating that the increased severity and duration of heat waves predicted under climate change models will not have an impact on weather related mortality. You've repeatedly denied it, but never even once provided a single source. Not a one. And do you know what doesn't usually convince other people of things? Poorly spelled, logically dubious, anonymous forum rants with no citations whatsoever.

Do you recall when, presented with a peer reviewed paper outlining predicting an increase in heat wave related fatalities associated with climate change, you called it (to quote verbatim) "drivel", despite having absolutely no evidence to contradict the paper's findings? I can only hope the irony is not lost on those reading along.