What is a species?

Alligator snapping turtle (Macrochelys temminckii)

Before you read any further, I want you to take a minute and try to answer the question in the title. Go ahead and write down (or at least think about) the definition that scientists use to determine whether or not two organisms are members of the same species. Now that you have hopefully done that, I am going to burst your bubble and tell you that if you wrote down a definition, then no matter what definition you wrote, you’re wrong, or at the very least, incomplete. You see, there is no one universally agreed upon definition of a species. Rather, there are numerous “species concepts” and scientists debate endlessly about what constitutes a species. Further, taxonomic revisions happen constantly and it is extremely common for one “species” to get split up into multiple “species” while other “species” get lumped together into a single “species.” For example, the alligator snapping turtle (Macrochelys temminckii) was historically thought of as a single species, but in 2014, Thomas et al. proposed that it should be split into three species: M. temminckii, M. apalachicolae, and M. suwanniensis. Then, in 2015, Folt and Guyer argued that M. apalachicolae and M. suwanniensis were not actually different enough to be considered distinct species and should, therefore, be lumped back together, resulting in just two species of alligator snapping turtle (M. temminckii and M. suwanniensis).

These types of revisions happen frequently, and scientists routinely disagree about how to separate species. Indeed, when you get right down to it, the whole concept of distinct species is an artificial one that we use to categorize things. It is not an actual property of nature, which is why it is so amorphous. Nevertheless, discussions about what constitutes a species are important, and they have strong implications for topics like GMOs and evolution. Therefore, I want to discuss several of the more common species concepts, how scientists go about deciding what to call a species, and why the concept of a species is artificial and ultimately somewhat arbitrary.

The biological species concept

Let’s start with what is probably the most well-known species concept: the biological species concept. This concept defines species based on the inability of different groups to breed with each other. In other words, if two natural groups of organisms can interbreed, then, according to this concept, they are the same species, whereas if they can’t interbreed, they are considered to be members of different species. Unfortunately, this is probably the concept that you learned in high school, and I say “unfortunately,” because this is a pretty terrible species concept, and scientists don’t really use it much anymore.

One of the most obvious problems is simply that it cannot deal with asexual species (i.e., species where a single individual can clone itself rather than relying on a mate). Asexual species are actually pretty common in nature, and even occur in various groups of vertebrates (e.g., some lizards), but according to this concept, every single asexual individual should be its own species because it cannot interbreed with other individuals, or, at best, this concept simply has no way to define asexual species.

The second problem is that hybrids are extremely common in nature, even among organisms that everyone agrees represent different species. Plants are infamous for their ability to hybridize across species (this happens in nature, not just in horticulture) but animals frequently do it as well. For example, consider the Mallard (Anas platyrhynchos). This is the ubiquitous green-headed duck that you can find at ponds, lakes, and rivers throughout the US. Everyone agrees that it is its own species, but it can hybridize with multiple other species of duck (e.g., American Black Ducks [Anas rubrics], Pacific Black Ducks [Anas superciliosa], Northern Pintails [Anas acuta], etc.). Further, in many cases, those hybrid offspring are not sterile and can reproduce (as can their descendants). Thus, according to the biological species concept all of those ducks should be one species, but based on every other species concept, they should be different species, and no scientist (or birder) in the world would suggest that we should lump them all together. Finally, I need to emphasize that this is not an isolated example. Hybrids are everywhere in nature, and I could show you examples of hybrids in other birds, snakes, lizards, frogs, turtles, fish, mammals, etc. This is a very common phenomenon.

The morphological species concept

This is another very old species concept, but it is still sometimes used today. It proposes that species should be defined based on whether or not they can be distinguished morphologically. In other words, if scientists can look at two groups of organisms and visually distinguish them (or distinguish them by their calls) then they are different species, but if they are indistinguishable, then they are the same species. So, for example, all of the ducks that I mentioned earlier can be visually distinguished, thus, based on this concept, they are different species.

This concept sounds good, but it has multiple problems. First, there are quite a few “cryptic species” (reptiles have tons of these). These are species that are impossible (or at least extremely difficult) to distinguish visually or audibly, yet when we look at things like genetics, it is clear that they are very different from each other and represent different groups (i.e. species). It is also worth mentioning that in many cases, we may not be able to distinguish them, but the organisms themselves may be able to distinguish each other based on traits like pheromones that we are pretty bad at picking up.

The other problem with this species concept is that many species have tremendous amounts of variation across their range. Take the Northern Flicker (Colaptes auratus), for example. This woodpecker is found all over the US, and in eastern half of the country it has beautiful yellow feathers. In the western half, however, those feathers are red. In other words, there are two morphologically distinct groups of this species, yet we consider it to be a single species. As with the biological species concept, I could give you tons of examples like this, and I would even go as far as saying that regional variations within a species are the norm, not the exception. A good way to think about this problem may be simply to ask the question, “how different do two groups need to be before we consider them to be different species?” There is obviously no objective answer to that, which makes the definition rather arbitrary.

Two color morphs of the Northern Flicker (Colaptes auratus): Red-shafted (left) and Yellow-shafted (right). They are morphological distinct, but are still considered to be the same species.
Images are from BioQuick News and Ewebarticle.

The genetic species concept

This concept is in many ways just a modern version of the morphological species concept, but instead of morphology, it uses genetics. Thus, two groups that are genetically distinct are considered to be different species. As with the morphological species concept, however, the key question is, “how different is different enough to be separate species?” Once again, the answer is, “no one knows, and it is arbitrary.” Various levels of genetic similarity have been proposed and applied, but there is no one universally accepted answer. Further, there are frequently disagreements between the morphological species concept and the genetic species concept. As a result, as I mentioned earlier, it is extremely common for scientists to disagree about whether or not two groups are different species, and species frequently get lumped and split. Indeed, I was recently at a conference where one researcher somewhat facetiously suggested that we should start using the terms “gecies” to refer to genetic species, and “mecies” to refer to morphological species.

The phylogenetic species concept

The final species concept that I want to talk about (though there are many of lesser importance that I did not discuss) is basically an extension of the genetic species concept. Once again, it uses genetic patterns, but this time, instead of simply using the degree of difference among groups, it attempts to look at evolutionary history. Thus, a species is a genetically distinct group with a shared evolutionary history that differs from the other groups. This is certainly useful, and is probably the most widely used concept today, but as with the other concepts, it is still largely arbitrary because there are no universally accepted criteria for determining when an evolutionary history is divergent enough to constitute a separate species.

Which concept is correct?

As you’ve hopefully gathered by now, scientists disagree about the answer to this question. In practice, we tend to try to look for a convergence of multiple species concepts, but again, scientists frequently disagree about whether two things are different enough to be considered distinct species, and proposed taxonomic revisions are often highly contested.

To add another layer of complexity to this, scientists often add additionally sub-categories. For example, many species contain multiple “subspecies.” These are geographical subgroups of a species that are different enough to be noteworthy, but similar enough that they don’t merit species status (the two flickers that I mentioned earlier are subspecies). Here again, however, scientists often disagree about the boundary between species and subspecies, and it is common for subspecies to get elevated to full species and for multiple species to get lumped and demoted to subspecies.

In other cases, scientists prefer to talk about “evolutionarily significant units” rather than dwelling on the species/subspecies distinction. These are simply groups (usually populations) that are genetically (usually phylogenically) distinct enough that they need to be discussed and managed separately, regardless of whether you want to label them as separate species. Similarly, in the world of microbiology, it is common to abandon the label “species” altogether and instead use OTUs (operational taxonomic units) which are narrow taxonomic groups that are distinguished by an arbitrary threshold of similarity (97% similarity is often used).

Why isn’t there a universally accepted species concept and how does this relate to evolution and GMOs?

Finally, and I think most importantly, I need to explain why scientists disagree about how to define a species. It’s not simply that scientists are an argumentative and ornery bunch (though that plays into it). Rather it is because there is actually no such thing as a species. The concept of a species in an entirely artificial one that we invented to help us make sense of the world. It is not an actual construct of nature.

You see, as I have explained before, evolution is a spectrum, not a series of distinct blocks. Thus, nature does not immediately form distinct and obvious species. Rather, a group of organisms splits and gradually evolves in separate directions with each generation resulting in more and more differences. At some point, those two groups become different enough that we consider them to be different species, but where we draw that line is arbitrary. It is a judgement call that we are making, rather than an actual property of nature.

Further, it is important to realize that this also applies to other levels of taxonomic classifications (especially genera and families). Like species, it is often not clear how to demarcate these, and taxonomic revisions are common. For example, a few years ago, the frog genus Rana was split into multiple different genera, with most of the ranids in the USA moving into the new genus Lithobates. Also, just like with species, there are subcategories (subfamilies, supergenera, etc.) and scientists often disagree about where to draw the line. Again, this is because these taxonomic divisions are artificial. They are useful tools for us to understand life on planet earth, but evolution produces a spectrum, not distinct blocks, and when we see distinct blocks, they only exist because the rest of that spectrum died out. Imagine, for example, looking at a rainbow and picking the point where the red stops and the yellow begins. You can’t really do it.

In addition to everything that I have said so far, it is also worth noting that nature is kind of a freak, and it does some really weird things that are nigh impossible to categorize. One example that I am quite fond of is the fact that several thousand years ago, sweet potatoes stole DNA from a bacteria and incorporated that DNA into their own genome (thus essentially making them a natural GMO). Similarly, some butterfly species incorporated viral DNA into their genomes (Gasmi et al. 2015). What do you do with that as far as assigning taxonomy? What do you do when a species forms by stealing DNA from a totally different group of organisms?

Further, those examples aren’t even the most extreme. There is, for example, a salamander in the genus Ambystoma that does something known as kleptogenesis (Bogart et al. 2009). This salamander is unisexual (i.e., only has females), but it is not asexual (i.e., it isn’t capable of reproducing on its own). Rather, they take sperm from up to four other Ambystoma species and use that sperm to fertilize their eggs. Thus, each generation is formed by stealing sperm from a different species (sometimes multiple species) and incorporating part of their genome. What do you do with something like that? It defies classification, which brings me back to my central point that taxonomic classifications are simply imperfect constructs for helping us to understand the world, rather than actual properties of nature.

So, what does all of this have to do with evolution and GMOs? Well, when it comes to evolution, I think that the implications are pretty clear. Evolution predicts a spectrum, and that is exactly what we see. I often hear creationists talk about species or families as totally distinct obvious groups, but that’s just not reality. The distinctions are extremely fuzzy and often arbitrary.  For GMOs, the implications are a bit more nuanced, but important nonetheless. Like creationists, anti-GMO activists often make a big deal about species being distinct and find the notion of moving a gene from one species into another to be abhorrent, but as you can hopefully now see, that view makes little sense once you understand how nature actually works. Organisms exist as a spectrum, not as extremely distinct units, and we all share the same DNA. To be clear, something like a fish and a tomato are obviously distinct, but that is only because they are far apart on the spectrum. Go back to the rainbow analogy for a minute. The pure yellow and pure red are clearly distinct from each other, but you’d do yourself a disservice by treating them as if they are totally separate and detached from one another, because they both fall along the same spectrum. Further, as I explained above, nature does not respect the arbitrary labels that we put on things, and it even moves genes between highly divergent groups (e.g., a sweet potatoes and bacteria).

My point in all of this is simple, organisms exist as a spectrum, not distinct blocks, and categories like “species” and “family” are artificial constructs that we created to help us understand the world around us. So before you make a big deal about different families and species for topics like GMOs and evolution, keep in mind that those categories are simply tools that we use, not actual properties of nature.

Note: The GMO tomato with “fish genes” never went to market.

Literature Cited 

  • Bogart et al. 2009. Sex in unisexual salamanders: discovery of a new sperm donor with ancient affinities. Heredity 103:483–493.
  • Folt and Guyer. 2015. Evaluating recent taxonomic changes for alligator snapping turtles (TestudinesL Chelydridae). Zootaxa 3947:447–450.
  • Gasmi et al. 2015. Recurrent domestication by Lepidoptera of gens from their parasites mediated by bracoviruses. Plos Genetics 11:e1005470.
  • Thomas et al.. 2014. Taxonomic assessment of Alligator Snapping Turtles (Chelydridae: Macrochelys), with the description of two new species from the southeastern United States. Zootaxa 3786:141–165.
Posted in GMO, Science of Evolution | Tagged | 19 Comments

Most anti-GMO papers contain serious flaws

Unfortunately, bad papers sometimes get published, and those faulty results often get hailed by members of the anti-science community as evidence for their positions. As a result, it is extremely important to both look at the entire body of literature on a topic and critically examine the papers themselves. More often than not, when you look at the literature for a scientific topic, you will find that most studies have converged on a consistent conclusion, while a few outliers have reached the opposite conclusion, but those outliers are usually riddled with problems and published in minor journals. Thus, it is foolhardy to latch onto the handful of papers that agree with you, while disregarding the vast majority of papers that disagree with you.

This is a prevalent problem and one that I write about frequently (for example, I have previously written about how to evaluate scientific papers, Tenpenny’s cherry-picked “vaccine library,” the supposed lists of papers showing that vaccines cause autism, etc.). In this post, however, I am going to focus on GMOs. I’ve talked about this before, and explained that the anti-GMO position is, in fact, a form of science denial that is based on ideology, not evidence. As with topics like vaccines and climate change, the evidence that GMOs are safe for both humans and the environment is overwhelming, yet activists rally around the tiny subset of papers that agree with them. When you critically examine those papers, however, it quickly becomes clear that they are junk science. Indeed, that was the conclusion of an intriguing new review that was published in the journal Plant Biotechnology Journal, and I want to spend a few minutes talking about it.

Note: This paper was specifically on human health implications, not environmental implications, but the same story holds true when you look at the environmental papers.

The paper in question is titled, “Characterization of scientific studies usually cited as evidence of adverse effects of GM food/feed,” and I encourage you to read the whole thing. It is a very accessible, easy to follow paper. Nevertheless, I will talk about a few highlights. In a nutshell, this study reviewed the literature, identified 35 studies that reported negative health effects associated with GMOs, then it evaluated the quality of those studies and placed them in the context of the wider literature. Unsurprisingly, it found that the quality of most of those 35 studies was quite low, and they often contained blatant flaws.

Small proportion of studies

5% anti-GMO studies health safetyFirst, it is important to note that these 35 studies represent a tiny fraction of the literature (only around 5% of the GMO papers the authors were able to identify). Right of the bat, that is a huge red flag. If the results of those studies were correct, then they should be what the majority of studies are finding, not what a tiny minority are finding. Indeed, because of the way that statistics work, we expect about 5% of experiments to produce false positives just by chance (details here). So even if these studies were flawless, they would still be indistinguishable from statistical noise when you look at the entire body of literature.

Few labs and authors

The next thing to note is that these 35 papers were produced by a handful of researchers. Indeed, one researcher was an author on 11 of those papers. So what you have is a few labs that are repeatedly publishing papers that support the previous findings of those same labs. This is another problem. If their results were real, then other independent scientists from around the world should have found corroborating results, but they haven’t. That strongly suggests that something wrong is happening in these few labs, and, indeed, in some cases, there is clear evidence of fraud (more on that in a minute).

Low ranking journals

When evaluating a paper’s claims, it is always a good idea to consider the quality and reach of the journal that published it (this is often measured by an “impact factor” which is based on how widely cited a journal’s publications are). Whenever you have a really important, novel result, you try to publish it in a high impact journal. In contrast, if you have a fairly uninteresting result that everyone already expects or a result that is very specific to a narrow field, you generally publish it in a low-ranking journal. Thus, if the science is solid for claims like, “GMOs cause cancer” then you expect those papers to appear in very high impact journals, and you should be very suspicious when they show up in tiny journals that no one has ever heard of. Ask yourself, “why wasn’t a result that is this important and interesting published in a high ranking journal?” The answer is usually that it couldn’t pass their more rigorous standards.

So, getting back to this list of 35 papers, what did the authors find? Perhaps unsurprisingly, nearly all of those papers were in minor journals. Indeed, eight of those papers were published in journals that are so minor they don’t even have an impact factor (that is another huge red flag), and an additional six had an impact factor less than one (which is a really low impact factor). In fact, only one of those 35 papers (Ewen and  Pusztai 1999) was published in a high ranking journal. This paper was, however, the source of great controversy. One of its reviewers found that it was flawed and should not be published, and another expressed serious doubts over the paper, but thought that, for the sake of openness, it would be best to publish the paper and let the general scientific community evaluate it, rather than risking the appearance of a conspiracy or cover-up (see the article for more details). I personally disagree with that decision, but it is, nevertheless, evidence that the crazy conspiracy theories about scientists supressing evidence are just as insane as they sound. Additionally, The Lancet (the journal that published it) also published an editorial stating that some of the reviewers took issue with the paper.

Note: It’s worth mentioning that this review was published in a well-respected journal with an impact factor of 7.443.

Conflicts of interest

I’m not personally super concerned over conflicts of interest (e.g., funding sources and employment by companies or activist groups), but it is, nevertheless, worth mentioning them. They found that 21 of the papers (60%) had conflicts of interest, which is higher than than the rate of conflicts of interest in the general body of GMO literature (Sanchez 2015 found that 58.3% of GMO studies had no conflicts of interest, 25.8% had clear conflicts of interest, and the remaining 15.9% could not be assessed [the authors were not linked to companies, but did not declare their funding sources]). The only point that I really want to make here is that this isn’t a situation where all 35 papers are free from conflicts of interest and all the papers saying that GMOs are safe are loaded with conflicts of interest. Rather, you have some of both in each group, which leaves you with 14 anti-GMO papers that have no conflicts of interest and 406 pro-GMO papers that have no conflicts of interest (see original paper for details).

Note: The authors of the review paper did acknowledge that they themselves have conflicts of interest, but that does not invalidate their results, and it does not give you carte blanche to ignore their findings. As always, when a conflict of interest is present, you should apply greater scrutiny, but you should not blindly disregard the study.

 Problems with the papers themselves

Finally, and most importantly, the authors found that problems abounded with the studies themselves. They summarized this nicely in table 1 (as well as providing more details in the text), but the problems included things like, “Flawed statistics (fishing for significance)” (de Vendomois et al. 2009), “No use of non-GM soybean as control” (El-Kholy et al. 2014), “No information on crop source; inadequate sample size” (Yum et al. 2005), “No biological relevance” (Tudisco et al. 2007), etc.

Further, the review talks about some of the more well-known examples of flawed GMO research. For example, there is Seralini’s infamous rat study which was so flawed that it was retracted (Seralini then submitted it to a predatory journal where it is currently published). Similarly, there are multiple papers by Federico Infascelli. If you pay attention to news in science at all, then his name might sound familiar, because last year it was discovered that he had manipulated the data on at least two of his papers, resulting in both of them being retracted. His entire body of work is now under close scrutiny and his reputation has been forever tarnished (more details at Retraction Watch and Science-Based Medicine).

Finally, it is worth mentioning that this is not the first paper to address this issue. A previous study (Panchin and Tuzhikov 2016) also found that anti-GMO papers were full of problems (namely, statistical problems), and that when you used the correct statistical tests, the reported negative effects of GMOs vanished.

Conclusion

So where does this leave us? The answer seems pretty clear: anti-GMO studies represent a tiny portion of the literature, they are usually published in low-quality journals, they are riddled with statistical and methodological problems, several of them have been retracted (sometimes because of scientific fraud), and they are refuted by a vast body of literature. Further, before you baselessly suggest that the pro-GMO papers were all bought off by big companies, please note that less than half of the general body of GMO literature contains conflicts of interest, whereas 60% of the anti-GMO papers contain conflicts of interest. In short, the anti-GMO papers are, at best, statistical noise, and they do not, in any way shape or form represent compelling evidence that GMOs are dangerous. Most of them are junk science and should be rejected as such.

Note: A similar paper on climate change papers reached the same conclusion. Namely, the handful of papers arguing against anthropogenic climate change are filled with problems. (Benestad et al. 2016; the supplemental information is particularly useful)

Literature cited

  • Benestad et al. 2016. Learning from mistakes in climate research. Theoretical and Applied Climatology 126:699–703.
  • de Vendomois et al. 2009. A comparison of the effects of three GM corn varieties on mammalian health. International Journal of Biological Sciences 5:706–726.
  • El-Kholy, et al. 2014. The effect of extra virgin olive oil and soybean on DNA, cytogenicity and some antioxidant enzymes in rats. Nutrients 6:2376–2386.
  • Editors of the Lancet. 1999. Health risks of genetically modified foods. The Lancet 353:1811.
  • Ewen and Pusztai. 1999. Effects of diets containing genetically modified potatoes expressing Galanthus nivalis lectin on rat small intestine. Lancet. 354:1353–1354.
  • Panchin and Tuzhikov 2017. Published GMO studies find no evidence of harm when corrected for multiple comparisons. Critical Reviews in Biotechnology 37:213–217.
  • Sanchez 2015. Conflict of interests and evidence base for GM crops food/feed safety
    research. Nature Biotechnology 33:135-137.

    Sanchez and Parrott 2017. Characterization of scientific studies usually cited as evidence of adverse effects of GM food/feed. Plant Biotechnology Journal.

  • Tudisco et al. 2007. Investigation on genetically modified soybean (Roundup Ready) in goat nutrition: DNA detection in suckling kids. Italian Journal of Animal Science 6:380–382.
  • Yum et al. 2005.  Genetically modified and wild soybeans: and immunological comparison. Allergy and Asthma Proceedings 26:210–216.
Posted in GMO | Tagged , , , | 7 Comments

“It’s morally wrong to patent food:” Inconsistent reasoning at its finest

This is one of the most common arguments against GMOs that I encounter (as well as related attacks on Monsanto), and it is frequently accompanied by claims like, “I am not anti-GMO, but…” or “I accept that GMOs are safe, but…” In reality, however, this argument is usually nothing more than an excuse designed to protect people’s ideology, misplaced fears, and, yes, denial of science. This argument is so riddled with problems and so completely inconsistent with how people behave on any other topic that it is difficult to accept that it is truly the reason that people oppose GMOs, and in my experiences debating GMO opponents, it usually turns out that it is just a symptom of an underlying ideology (generally rooted in appeal to nature/emotion fallacies). As I will explain, if you are truly motivated out of ethics and a concern for feeding the hungry, then you should be embracing GMOs, not opposing them (or, at the very least, you should be very selective about which GMOs you oppose). So, if you are someone who frequently uses this argument, then, as always, all that I ask is that you hear me out and rationally consider whether or not you are being logically consistent.

Note: I have been somewhat reluctant to write a post on this because it is not actually an argument about the science. However, I am sick and tired of explaining it to people in comments, and it is such a prevalent argument that it seems worth taking the time to discuss.

Patents aren’t limited to GMOs

First, it is vitally important to realize that the ability to patent crops is not unique to GMOs, nor is it a result of them. In the US, the first piece of legislation that made it legal to patent crops was the Plant Patent Act that was passed in 1930, over half a century before the first GMO crop. Indeed, many of our common crops are patented (or at least where patented when they were first invented; remember patents only protect intellectual material for a certain period of time). For example, seedless grapes were patented in 1934, yet I don’t hear anyone complaining about them.

The organic industry (and yes, it is a multi-billion dollar industry) also patents plants. For example, Vermont Organics owns patents on five different plants. So, if you are outraged over Monsanto patenting plants, then you had better be equally outraged over Vermont Organics doing so. The point is that attacking GMOs because they are patented makes no sense, because most crops are patented, regardless of whether they are GMOs. So, this argument holds GMOs to a different standard than all of the rest of agriculture. Further, as mentioned earlier, patents expire. For example, Round-up read soybeans are no longer protected by patent laws because those patents expired in 2015. Does that mean that anti-GMO activists are going to stop protesting them? I somehow doubt it.

Finally, it is worth making it explicitly clear that GE companies, organic companies, etc. are not “patenting Mother Nature.” They are patenting unique crops that do not occur in nature and that they invested in developing (see below). As I have previously explained, virtually none of your food is natural, and essentially all of it has been genetically modified, even if it isn’t typically described as a GMO.

Patenting a GMO shouldn’t be different from patenting anything else

Additionally, it is worth talking about why crops can be patented in the first place. Producing a new crop is very expensive, especially for a GMO. It takes millions or even billions of dollars to research and develop a new product, and that is money that company has to invest up front with the expectation that they will be able to turn a profit later. Thus, patents are a way of allowing companies to get a return on their investment. This is true for all patents, and in most areas, people have no problems with that. No one says that Apple is evil because they patent the technology for each new iPhone rather than giving its technology away freely. Similarly, no one complains that Toyota tries to make a profit off its innovations, so why should GMOs be any different? Why should Monsanto and other GE companies be held to a different standard than any other company?

I’m a big believer in the Socratic method, so let me use a series of questions to try to get you to really think about this. If Canon, Nikon, Sony, or any other camera company invested millions of dollars in developing a new camera product, then patented the result and tried to make money from it, would you consider them to be evil for doing that? Would you say that they had done something morally wrong? I’m willing to be that the answer is “no.” Now, what if Monsanto invested millions of dollars in developing a new crop, then patented the result and tried to make money from it, would you consider them to be evil for doing that? A lot of people would answer “no’ to the first question, but “yes” to the second, but that makes no sense. Why should Monsanto be vilified for doing exactly the same thing that every other for profit company does?

Additionally, it is important to realize that a lack of patents would stifle innovation. There are non-profits and independent scientists involved in the development of GMOs (more on that in a minute) but a lot of the breakthroughs come from big companies, and there is a very good reason for that. Namely, research costs money, and big companies are the ones who have money to invest. However, companies are, admittedly, after profit. So they aren’t going to invest millions of dollars into something unless they think that they can turn a profit. To be clear, I am all for independent, non-profit research, and I am actually quite progressive politically and am all for various strategies of wealth redistribution, but having said that, it is undeniable that the free market fuels innovation, and if you want agricultural developments (as you should if your goal is really to feed the hungry), then you should allow companies to make a profit, because that is the only way that they are going to invest heavily in researching agricultural advances.

Not all GMOs are about money

Next it is important to realize that although large companies dominate the development of GMOs, not all GMOs are about money. Golden rice, for example, is being developed entirely for humanitarian purposes. You see, many countries suffer from extreme vitamin A deficiencies, and many of those countries grow primarily rice. Thus, scientists and humanitarians developed golden rice, which is simply rice that produces vitamin A. That way, these countries can grow the same crop that they always have (thus they don’t need to change their agricultural practices) but they will get the vitamin that they so desperately need.

Now, if you are truly concerned about feeding the hungry, and if humanitarian concerns are really the reason that you oppose GMOs, then you should be all for golden rice, GMO bananas, and the other non-profit GMOs, but that almost never seems to be the case. Anti-GMO groups constantly attack these crops (including destroying test fields) and they lump them in with all of the other GMOs. That is why in my opening paragraph I said that this argument strikes me as disingenuous. You can’t claim to oppose GMOs out of humanitarian concerns while simultaneously opposing GMOs that are literally life-saving.

GMOs benefit the poor and the hungry

This is related to the previous point, but it is worth making saying it explicitly: GMOs help to feed the poor. Studies have repeatedly shown that using GMOs increases crop yields and reduces the amount of resources need to grow crops. Consider, for example, this 2014 meta-analysis that found (my emphasis),

“On average, GM technology adoption has reduced chemical pesticide use by 37%, increased crop yields by 22%, and increased farmer profits by 68%. Yield gains and pesticide reductions are larger for insect-resistant crops than for herbicide-tolerant crops. Yield and profit gains are higher in developing countries than in developed countries.”

Again, this should be great news if your concern is really feeding the poor. These crops will let impoverished countries greatly increase the amount of food that they can grow, so they are a huge win for fighting world hunger. Really think about this, by opposing GMOs you are trying to force poor countries to grow fewer crops than they could with GMOs. You are literally trying to deny people food. How is that moral?

GMOs benefit farmers

It is also worth mentioning that GMOs are good for farmers (that is why they have adopted them). Anti-GMO activists often try to paint farmers as the victims of evil “Monsatan,” but the reality is that farmers love GMOs, because GMOs allow them to increase their yield and/or decrease the amount of effort/resources that they have to invest. This should be obvious if you just think about it for a second. Why on earth would so many farmers switch to GMOs if they weren’t beneficial? No one is putting a gun to their heads and forcing them to use GMOs. Farmers choose their seeds from catalogues where numerous companies compete for their patronage, and Monsanto doesn’t have a monopoly on the food supply, despite what activists want you to believe. Further, farmers aren’t stupid. They wouldn’t use GMOs if better, cheaper methods were actually available. Farmers have widely adopted GMOs precisely because they are beneficial. So, stop pretending that farmers are the victims. They aren’t.

Bad counterargument 1: “But Monsanto sues farmers!”

In the remainder of this post, I want to deal with some truly awful counter arguments. The most common of which is that Monsanto sues farmers for accidentally using their seeds/cross-pollination. The rebuttal for this one is easy: no they don’t. Monsanto has never sued a farmer for accidentally using their product/cross-pollination (more here).

Having said that, there have been a few cases where Monsanto sued someone for deliberately violating the patent agreement (e.g. selling seeds). That is, however, an entirely different issue from suing a farmer over accidental contamination. A deliberate violation of the patent agreement is a theft of intellectual property, plain and simple. It is a crime. It is no different from selling bootlegged DVDs or CDs. No one complains when a company like Universal brings movie pirates to court, so why should you complain when Monsanto brings seed pirates to court? This goes back to some of my keep points early. Namely, arguments like this hold GE companies to a different standard than any other company. Monsanto invests millions of dollars in R&D, so why shouldn’t it be allowed to protect its intellectual property?

Bad counterargument 2: “But farmers can’t replant the seeds”

Do you know what group of people I almost never hear make this complaint? Farmers. The reality is that in the modern era, most farmers don’t save the seeds regardless of whether or not their crop is a GMO. One of the key reasons for this is simply that doing so results in a lower quality harvest than you would get from buying new seeds (more details here). So, as with so many anti-GMO arguments, this argument is based on a complete lack of understanding about modern agriculture.

Bad argument 3: “The real problem is food waste. If first world countries weren’t so wasteful, there would be plenty of food to feed the world.”

This is what is known as a “nirvana fallacy.” It proposes an extremely unrealistic ideal situation, then claims that any plans that fall short of that standard shouldn’t be used because they aren’t perfect or don’t address the “real” issue. To be clear, food waste is a problem, and I agree with you 100% that we should be limiting it, but limiting it to the point that we could feed the world is an incredibly difficult (probably impossible) thing that is not going to happen in the near future. Meanwhile, there are people suffering from vitamin A deficiencies who could easily be saved by implementing GMOs. People are literally dying while you sit there demanding that we wait for an unrealistic solution.

Further, even if first world countries suddenly majorly cut back their food waste, that solution has several other problems. Most importantly, we have to somehow get that food to the countries that need it (which adds massive transportation costs, increased greenhouse gas emissions, etc.), and it makes those countries entirely dependent on aid from other countries. GMOs solve both of those problems because they can be grown by local farmers in the country where they are needed, thus allowing the country to feed its own citizens without needing constant supplies of food from other countries.

 Bad counterargument 4: “But [insert conspiracy theory]”

There are a plethora of conspiracy theories out there about Monsanto depopulating the world, causing mass suicides, etc. and each one is crazier than the last, so please don’t waste my time or your intellectual integrity on them. Use impartial sources, make sure that you are basing your views on facts, not assumptions or speculation, and demand good evidence before accepting something.

Bad counterargument 5: “We’ll I just don’t think people should profit from food”

The final argument that I want to discuss is this general aversion to the notion of big, money-loving companies being involved in food production. This is important, because I think it is actually a key motivating factor driving everything that I have talked about. As I have shown, the opposition to patents and Monsanto more generally isn’t actually about facts or logic. In some cases it stems from science denial, but in many, I think it stems from this emotional connection to our food, but that is irrational for several reasons.

First, as I explained previously, GMOs benefit the poor, farmers, etc. so this argument is clearly wrong right from the start. Second, this is, once again, inconsistent with how we treat every other company (and even person) on the planet. If, for example, a family that owns a farm tries to make a profit off that farm, no one villainizes them. No one says that they are evil for profiting from the production of food. Indeed, we would applaud their industry and hard work. So if it is fine for them to make a profit off of food, when is it wrong for GMO companies to do that?

Now, you might object to that on the basis that Monsanto is a multi-billion dollar company, but that doesn’t help your inconsistencies one bit for two reasons. First, the initial argument was, “it is wrong to profit from food,” but now you are trying to implement some arbitrary threshold of profit at which it becomes immoral.  Second, organic farming is also a massive, multi-billion dollar industry. Indeed, Whole Foods (a large organic store chain) makes nearly as much money as Monsanto, and is profitable enough that Amazon just paid 13.7 billion dollars for it. So, if making billions of dollars off food makes Monsanto evil, then it must also make Whole Foods evil, but no one thinks that Whole Foods is evil, and many GMO opponents shop there! Also, by extension, it must now make Amazon evil, but I’m betting you’re still going to spend your money there. Do you see how inconsistent that is? You can’t vilify Monsanto for profiting from food, then go shopping at a multi-billion dollar food store.

Finally, this argument is inconsistent not just with organic food chains, but also with how we view companies more generally. Let me break it down this way, at its core, this argument claims that Monsanto and GMOs are evil because they aren’t feeding the hungry, but we could make that same claim about essentially every massive, for profit company. Apple could spend its vast wealth feeding the hungry, yet no one says that they evil for hoarding their wealth. Why should Monsanto be any different? Why should the fact that they are actually involved in food production make their quest for profit any less ethical than any other company’s? Why should the fact that they care more about profit than feeding the hungry make them any more evil than any of the thousands of other companies that care more about profit then feeding the hungry? Again, to be clear, I’m not a huge fan of massive companies, and I do think that they should do more to help the poor, but that reasoning has to be applied consistently rather than singling out Monsanto.

Note: This post was set to automatically go live while I am away with only intermittent internet access. So, my responses to comments will probably take a while and be intermittent. Also, please stay on topic and don’t go off on other GMO topics (e.g., pesticides, safety, etc.). There are other posts for those topics (see Comment Rules for details).

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GMOs and natural selection: Nature doesn’t give a crap about you

Last week, I shared a meme about GMOs on my blog’s Facebook page, and several people responded by arguing that genetic engineering (GE) shouldn’t be used because “it bypasses the natural evolutionary test of fitness.” I’ve heard this argument before, and it is basically just a dressed-up appeal to nature fallacy that asserts that something that has undergone natural selection will somehow be better for us than something that has not. That notion is, of course, ridiculous. It has all the problems of a normal appeal to nature fallacy, plus it relies on numerous misconceptions about evolution, GMOs, and test of natural selection evolutionagriculture in general. So, let’s take this one step at a time and go over why this argument doesn’t work.

Nature doesn’t care about you

This first, and perhaps most obvious, problem with this argument is that it assumes that nature is somehow looking out for your best interests. It implicitly asserts that natural selection is acting on fruits and vegetables to bring about a result that is beneficial for you. In reality of course, nothing could be further from the truth.

Natural selection is nothing more than a sampling bias that operates off of two simple premises. 1). There is heritable variation for traits (i.e., different individuals have different genetic material [alleles] for a given trait, and they can pass that genetic material on to their offspring). 2). That variation affects individuals’ ability to pass genes on to the next generation. When those two conditions are met, individuals with beneficial traits will pass on more genes than individuals who lack those traits, and, as a result, those traits will be more common in the next generation. That’s it. That’s all it is. You will notice, however, that those two requirements have absolutely nothing to do with you or humans more generally. There is no third requirement that states that a given trait has to be beneficial for humans. Indeed, your needs  have no bearing whatsoever on the evolution of other organisms. You’re not that important.

This should, of course, by blatantly obvious, because nature is full of things that are utterly terrible for humans. Consider mushrooms in the genus Amanita for example. They produce chemicals known as amatoxins that are extremely toxic to humans at anything but an incredibly low dose. If you eat a single one of these mushrooms, you will spend the next 24–48 hours with agonizing abdominal cramps, as well as fluids gushing uncontrollably out of both ends of your digestive system. Your only escape from this will most likely be the sweet release of death when your liver eventually shuts down. There is currently no known antidote for amatoxins, and doctors can’t do much for you other than keep you hydrated (or if you’re really lucky, give you a liver transplant).

Now, why would nature produce something so terrible? Because it doesn’t give a flying flip about you. The genus Amanita evolved to be deadly because that is what was beneficial for it, not because of what would have been beneficial for you. Mushrooms that produced a toxin where eaten by animals less frequently than mushrooms without the toxin, and, therefore, survived longer and produced more offspring. As a result, the genes for toxicity became more and more prevalent in the population, until we eventually got the horrifying product that currently grows in our forests. That’s it. That’s how natural selection works. You’ll notice, however, that this supposed, “natural evolutionary test of fitness” had nothing to do with you. It was about the organism that was adapting (i.e., the mushroom) not the organism that was looking for food (i.e., you).

Note: I want to make it clear that although we talk about natural selection as benefiting organisms, it is only acting on the available genetic variation, and it can only adapt populations to their current environment. It does not have any foresight and it does not give organisms what they truly need. More details here and here.

Note: It is true that there are mutualistic relationships in which two organisms evolve together, but those only occur when the organisms are directly interacting, and even then, nature is not trying to adapt one in a way that is beneficial for the other, rather it is all about the organism that is adapting. For example, hummingbirds rely on nectar from flowers, and, in many cases, plants evolved to produce nectar for the hummingbirds (and other pollinators); however, that evolution did not take place because it was good for the bird. Rather, flowers that produced nectar were visited by the birds, and the birds happened to pick up some pollen while they were there, and that allowed the plant to produce more offspring. So, the plant didn’t evolve to produce nectar because it benefits the bird. Rather, it evolved to produce nectar because that ultimately benefits the plant (benefiting the bird is merely a means to that end). Further, organisms are constantly trying to “cheat” and even in these mutualistic relationships, there is usually an evolutionary arms race where each organism tries to game the system. Finally, humans do not have this type of shared evolutionary history with most of our crops (see next point). 

 Our crops didn’t come from natural selection

This is what a wild banana looks like. Nature’s version doesn’t look as tasty as ours, does it?

The next major problem is the simple fact that our crops were produced by artificial selection, not natural selection (i.e., they were made by the same process that made the Chihuahua, not the process that made the wolf). Because nature is a jerk that doesn’t care about humans, we had to step in and make the crops ourselves. We took the small barely edible products of nature, and over thousands of years of careful breading, we modified their genetic codes and transformed them into the large, delicious items that we consume today. Wild bananas, for example, are small and full of giant seeds. Similarly, wild corn (teosinte) does not produce the large cobs that we consume. Indeed, virtually none of the items on our produce shelves can be found in nature.

Artificial selection can have unintended consequences

Now, at this point, you might be tempted to assert that the fact that we have been the ones selecting the crops actually makes the argument better, because surely we would not select a trait that is harmful. However, that response ignores basic concepts of genetics. You see, when you select a trait, hybridize crops, etc. via traditional breeding techniques, you don’t just exchange the genetic code for trait that you are interested in. Rather, you exchange genetic information across the entire genome. Thus, you alter thousands of traits, not just the one that you are interested in.

Imagine, for example, that you have two crops, one of which is small but drought resistant, and the other of which is large but not drought resistant. Now, you want to get the drought resistant trait into the large crop, so your cross breed them. This succeeds, and the genes (technically alleles) for drought resistance get moved into your large crops. However, thousands of other alleles also got moved. So, while you were after the drought resistant ones, there may have also been genes for producing a deadly chemical, allergen, etc. that you just moved without ever knowing it.

Note: when I say, “deadly chemical” or “toxic chemical” I mean deadly/toxic at a low dose. The dose makes the poison, so everything is toxic at a high enough dose.

Indeed, this is essentially what happened with the Lenape potato. It was bred for traits like low sugar content, but it was eventually discovered that it also produced high levels of the chemical solanine. This chemical is normally in potatoes, but usually it is at a low enough dose to be safe (unless you eat unripe potatoes), but the levels of it were unusually high in the Lenape potato. Indeed, they were high enough to make people who ate it nauseated. How did this mistake happen? Quite simply, the potato was selectively bred for one trait, but in the process, the breeders accidentally and unknowingly selected for an additional trait (high solanine levels) that was harmful to humans.

natural corn teosinte

Even when it has been organically grown, the corn that we eat is not natural, and it is quite different from wild corn (teosinte). Our crops have been genetically modified via thousands of years of careful breeding, and the fruits, vegetables, and animals that we eat today contain novel genetic codes that are not found in nature. Image via mentalfloss.com.

This is one of the huge advantages of genetic engineering: it is precise. With GE, you could take the specific genes for drought resistance and move them without moving any other genes! As a result, GMOs should actually have fewer unintended consequences than traditional breeding methods (and studies have confirmed that they have fewer than mutation breeding methods). To put that another way, both breeding methods involve moving the DNA from one organism to another (sometimes even across species, e.g., hybrids), and the only important difference is that genetic engineering allows you to be precise and move only the genetic material that you are trying to move.

Further, we can even use GE to correct mistakes that have arisen during traditional breeding methods and/or natural selection. For example, when fried, traditional potatoes release a chemical called acrylamide, which is a suspected carcinogen (like I said, traditional breeding methods and/or natural selection can result in nasty unintended consequences for humans). Thanks to GE technology, however, we have now produced a GMO potato that doesn’t produce that chemical. Further, that technology allowed us to knock out that one specific trait without screwing with any others. By any reasonable standard, that is a good thing and makes GE far superior to traditional breeding methods.

Conclusion

To sum all of this up, nature is not your friend, and the fact that something evolved naturally does not in any way shape or form guarantee or even suggest that it is good for you. Species evolve the traits that are beneficial for them, not the traits that are beneficial for you, and natural selection has produced some of the most horrifying things imaginable. Further, artificial selection and other breeding methods (e.g. mutagenesis) also do not guarantee a safe product. All of them involve altering the genetic code, and that always has the risk of unintended consequences. Genetic engineering is different from these methods in only one important way. Namely, the changes that it makes to the genetic code are more precise. So if we are going to worry about an unintended consequence from changing the genetic code of an organism, surely we should be the least concerned about the method that makes the fewest and most precise changes (i.e., GE).

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Abiogenesis: An unsolved mystery is not evidence of a creator

“Where did life come from?” It is a question people have thought about for millennia, and it is a question that is worth trying to answer. Nevertheless, not everyone is interested in looking for that answer. Indeed, many people prefer to simply insert god as the answer rather than actually wrestling with the question. Even worse, young earth creationists, intelligent designers, and some theistic evolutionists cite the current lack of a scientific answer as evidence that there is no scientific answer. In other words, they use the gap in our knowledge as an argument for a creator, and insist that since science doesn’t currently have an answer, the answer must be god. In reality, however, this argument violates fundamental concepts of both logic and science. Therefore, I want to talk about it and explain why it is not valid to say, “science can’t explain this, therefore god did it.”

Note: As always, this post is about science, not whether or not god exists. If you are a Christian or any other form of theist, I do not want you to read this as an attack on your religion. All that I am doing is addressing one particular, flawed argument. For the sake of this blog, I don’t really care what you believe as long as it does not cause you to reject science. That isn’t to say that debates about whether or not god exists aren’t worth having, but simply that this blog isn’t the place for them.

Abiogenesis is not the same as evolution

Before I can talk about the argument itself, we need to get our terms straight. Abiogenesis refers to the formation of a living cell from non-living matter. Evolution refers to the changes that occurred to life after the first cell formed (technically speaking, evolution is simply a change in the allele frequencies of a population over time). So, abiogenesis and evolution are not the same thing, and you cannot use them interchangeably, nor can you use an argument about one as evidence against the other. To put that another way, the theory of abiogenesis deals with how life formed, and the theory of evolution deals with what happened after life formed. They are not related to each other, nor do they depend on each other. Therefore, even if you could somehow prove that it was impossible for a cell to form from non-living matter (which you can’t, btw), you would have done nothing to discredit evolution. In other words, you would have shown that a creator had to make the first cell, but you would not have shown that evolution did not take place following that initial creation (indeed, that is precisely what some groups of theistic evolutionists believe).

Argument from ignorance fallacies

Now that we have our terms straight, let’s turn to the argument itself. It is true that scientists currently do not know exactly how the first cell formed. We have made a lot of progress in understanding it, but we have yet to get all the pieces together and actually make a living cell. Keep in mind, however, that the chemistry of life is exceeding complex, so it is hardly surprising that we have yet to complete such a complicated puzzle. Nevertheless, the current lack of a scientific explanation leads to the exceedingly common argument that since science does not currently have an answer, the answer must be god. That argument is, however, fraught with problems, the most obvious of which is the blatant argument from ignorance fallacy. I realize that tossing around the names of logical fallacies tends not to convince people, so let’s talk about this. I want to explain what that means, and why it is a problem.

An argument from ignorance is basically just an argument that fallaciously uses a lack of evidence as evidence of something else. In other words, it takes a gap in our knowledge, then inserts an assumption into that gap and attempts to use the gap as evidence that the assumption is true. Let me give you a few examples.

“No one has proved that Bigfoot doesn’t exist. Therefore, it exists.”

This argument is an argument from ignorance fallacy because it because it takes the gap in our knowledge, and inserts an assumption as if it is a fact. Do you see how that works? The fact that we have not proved with 100% certainty that Bigfoot doesn’t exist does not in any way shape or form constitute evidence that it does exist. Indeed, this example (and many others like it) attempts to shift the burden of proof. The person making the claim is always responsible for providing evidence to back up their claim. Thus, if you want to claim that Bigfoot exists, you have to provide actual evidence for its existence. You can’t simply appeal to the fact that it has not been 100% disproven. To use a related example, if someone believes in unicorns and you ask them for evidence that unicorns exist, they clearly can’t respond by simply saying, “prove to me that they don’t exist.” A claim has to have actual evidence to support it, not just a lack of evidence against it.

Now, let’s look at an example that is a bit closer to the topic of abiogenesis.

“Scientists can’t explain dark matter. Therefore, it is being created artificially by aliens.”

Hopefully you can see why that is a problem. I obviously cannot take our current lack of understanding and just insert aliens. Rather, I would need to provide actual evidence that the aliens existed, and I would need to demonstrate that science truly can’t explain it rather than simply showing that science hasn’t explained it yet (more on that in a minute).

Now, let’s get back to abiogenesis and compare it to the examples. You should notice that it is logically identical to my absurd alien argument. Indeed, we can state it simply as,

“Scientists can’t explain abiogenesis. Therefore, life was created by god.”

The same problems that existed for the alien argument exist for this argument. You can’t insert god into our lack of understanding about abiogenesis any more than I could insert aliens into our lack of understanding about dark matter. You must provide actual evidence that god exists before you can use him as an explanation, just as I would be required to provide actual evidence that the aliens existed before I could use them as an explanation.

Indeed, this particular argument is what is known as a “God of the gaps” argument. These are just special cases of argument from ignorance fallacies where you insert god (or a supernatural force more generally) as the explanation for an unknown. In the days before science, these arguments were abundant, and almost everything had some supernatural explanation. As science gradually provided explanations for our natural world, however, these arguments slowly fell out of favor, and today, even most creationists eschew them. Or, at least, they claim to eschew them, because this abiogenesis argument is clearly nothing more than a God of the gaps argument. It takes a gap in our knowledge and it inserts god as the explanation, which makes it, by definition, a God of the gaps argument, whether creationists like it or not. This brings me to my next major point.

“No explanation” and “no current explanation” are not the same thing.

If you are struggling to understand why creationist’s argument is problematic, think about this way: for everything that science can currently explain, there was a point in time at which the explanation was unknown. Imagine, for example, someone before the discovery of DNA saying, “science can’t explain genetic inheritance, therefore god is causing it” or, before we understood tides saying, “science can’t explain the tides, therefore god is causing them.” In hindsight, those arguments are obviously flawed, and it is clear that science simply hadn’t explained them yet rather than science being incapable of explaining them. Abiogenesis is no different. The fact that we haven’t explained it yet doesn’t mean that there isn’t a scientific explanation. It just means we haven’t found it yet. Indeed, we do science precisely because there are still unknowns. If we had scientific explanations for everything, then there would be no reason to even bother doing science. Thus, you can’t make a statement like, “science can’t explain abiogenesis.” Rather, all that you can say is, “science hasn’t explained it yet.

To put all of this another way, imagine that, in the past, every time that scientists encountered something that they couldn’t explain, they simply gave up and said, “well, we can’t explain it, so I guess god must have done it.” That would obviously have been terrible, because science would never have progressed. Nevertheless, that is exactly what creationists are doing. Rather than actually looking for a scientific explanation for something that is currently unknown, they are content to attribute it to the divine.

I really like the Socratic method, so let me phrase this as a question. If you agree that it would have been logically invalid for past generations to insert the supernatural as an explanation for things that they did not understand, then why do you think it is ok to insert god as an explanation for what we don’t understand (e.g., abiogenesis)? That strategy would clearly have failed in the past, so why do you think that it is ok now?

No, scientists aren’t making an argument from ignorance

Finally, I want to address a rather creative, albeit misguided, tactic that I sometimes see people use at this point in the conversation. Upon realizing that their position commits a fallacy, they try to flip things and assert that scientists are also committing an argument from ignorance fallacy, because scientists are “assuming” that a natural explanation exists. In other words, they claim that scientists are saying, “creationists haven’t proved that god did it, therefore it is natural.” At a quick glance that might seem like a correct assertion, but if you examine it more closely, you’ll quickly realize that it is actually ignoring basic concepts about how science works.

First, science always “assumes” that a natural explanation exists. That “assumption” is fundamental to science and indeed necessary for it, because science is, by definition, the study of the physical universe. If we didn’t “assume” that natural explanations exist, then there would be nothing for us to study. We’d be back to shrugging and saying, “god did it.”

Let me give you an example. My PhD research is focused on understanding why some populations/species recover from disease outbreaks while other, seemingly similar populations/species don’t. Several previous researchers have worked on my study system, but so far, no completely clear answer has emerged. Much like abiogenesis, we have some of the pieces of the puzzle, but we haven’t put it all together yet. Now, obviously, I am operating on the “assumption” that a natural explanation exists. Am I committing an argument from ignorance fallacy? Of course not! It would clearly be crazy for someone to say, “scientists can’t explain why these populations recovered. Therefore, god performed a miracle.” I doubt that even the most ardent creationists would consider that to be a rational argument. Thus, the rational position is clearly to operate as if a natural explanation exists, and, indeed, that is how all science operates. So why should abiogenesis be any different? Creationists are holding abiogenesis to a different standard than all of the rest of science.

This brings me to my next major point. “Assuming” that a natural explanation exists should be the default, because natural explanations are all that we have ever found. Think back to my initial examples of argument from ignorance fallacies. They all assumed the existence of something that there was no actual evidence for (Bigfoot, god, aliens, etc.). In the case of science, however, natural explanations have always been the answer to every mystery that we have ever solved. That’s why I keep putting the word “assumption” in quotes. Thinking that a natural explanation exists is not an “assumption” in the normal sense of the word, because it is blatantly obvious that a physical universe exists and follows natural laws.

To put that another way, you have to provide evidence that something other the natural universe even exists before you can criticize the “assumption” of a natural explanation. It would obviously be absurd, for example, to criticize a scientist for “assuming” that that the answer wasn’t magical unicorns. You would need to provide evidence that magical unicorns exist before you could even propose them as a valid explanation. Even so, you can’t even propose god as an explanation for a scientific unknown unless you have first provided evidence that such a being exists.

 Summary

In short, using our current lack of understanding about how life formed as evidence of a creator ignores the rules of both logic and science. It is nothing more than an argument from ignorance fallacy (specifically a god of the gaps argument), and, as such, is not logically valid. The fact that science hasn’t found the answer yet simply means that science hasn’t found the answer yet. Nothing more. You can’t insert god as an explanation any more than you can insert aliens, unicorns, multi-dimensional beings, the tooth fairy, etc. You have to provide actual evidence for those things rather than simply saying, “we don’t know, therefore god.” For every mystery that science has ever solved, there was a point in time when the answer was unknown. Further, when those mysteries were solved, the answer was always a natural explanation. Therefore, a current lack of a scientific answer is clearly not evidence of the divine, and there is no reason to treat abiogenesis any differently than any of the thousands of other mysteries that scientists are currently trying to solve. For essentially all of those unanswered questions [except abiogenesis], even the most adamant creationist would agree that we are correct to assume that the answer will be a natural one. So why should abiogenesis by any different?

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Anti-vaccers, climate change deniers, and anti-GMO activists are all the same

I imagine that quite a few people were upset by the title for this post, so let me explain what I mean, and please hear me out before you sharpen your pitchforks. The arguments used by all three of these groups, and indeed by science deniers more generally, are all fundamentally the same. In other words, the underlying logical structure is identical for the arguments used in support of all three of these positions. Thus, it is logically inconsistent to criticize one of these positions while embracing another.

You see, what I have observed over the past few years of blogging is that very few people like to think of themselves as “anti-science” or as a “science denier.” Those people certainly exist, and I do encounter them, but most of the people who visit my blog/page claim to love science…at least until it disagrees with their ideology. This puts them in a difficult position, because when a scientific result conflicts with their beliefs, they have to find some excuse or justification for why they don’t accept the results of science on that particular topic, and what I see over and over again is that everyone falls back on exactly the same excuses, regardless of what anti-science position they are trying to defend. For example, on several occasions, I have seen people criticize anti-vaccers for appealing to the authority of a few fringe “experts.” Then, a few threads later, I see those same people appealing to the authority of a few fringe experts on topics like climate change and GMOs. Similarly, I see people ridicule climate change deniers for thinking that all climatologists have been bought off, but when the topic shifts to GMOs, suddenly those same people start claiming that Monsanto has bought off all of the world’s genetic engineers/food scientists. Do you see what I am getting it? You can’t criticize someone for using a particular line of reasoning, then turn around and use that same line of reasoning to support your own particular form of science denial. That’s not logically consistent, and it’s not how science operates. Science is a method. It either works or it doesn’t, and you can’t cherry-pick when to accept it.

I suspect that people are becoming more upset with me, rather than less upset, so if you are currently unhappy with me, then I want you to stop and carefully think about this before you read any further. I’m not attacking you, I’m not even ridiculing you, but I am trying to help you think rationally and consistently. If you truly love science, rather than simply liking it when it agrees with your preconceptions, then you should hear me out. You should take a good look at the arguments and examples that I am going to present, and you should make sure that you are actually being rational and logically consistent. I also want to clarify that I don’t think people who believe these views are unintelligent or even consciously denying science. As I’ve previously discussed, I used to be a creationist and a climate change denier, so I know first-hand just how easy it is for ideology to cloud your judgment and make you think that you are being rational, when you are actually jus0.555681743t denying reality.

anti-vaccers anti-vaxxers all the same science denial cliamte change global warming GMOs


It’s not about the evidence

Before I go any further, I need to make it explicitly clear that none of these positions exist because of any actual scientific evidence supporting them. In every case, they are soundly defeated by a veritable mountain of consistent scientific results. On GMOs, for example, over 1,700 studies have been conducted, and they failed to find any evidence that GMOs are worse than traditional crops for either human health or the environment, and in some cases, they are better (Nicolia et al. 2013; also see Sanvido et al. 2006, Snell et al. 2012, Van Eenennaam and Young. 2014, and the National Academies of Sciences, Engineering, Medicine report 2016). This is, of course, also the conclusion that nearly 300 scientific organizations reached after reviewing the data.

Climate change is the same story. Because of carbon isotopes, we know that we have greatly increased the CO2 in the atmosphere (Bohm et al. 2002; Ghosh and Brand 2003; Wei et al. 2009), and thanks to satellite measurements, we know that our CO2 is increasing the amount of heat energy that the earth’s atmosphere traps (Harries et al. 2001; Griggs and Harries 2007). Further, studies of past climate clearly show that CO2 is a major driver of climate change (Lorius et al. 1990; Tripati et al. 2009; Shakun et al. 2012), and we have carefully studied the sun, volcanic emissions, Milankovitch cycles, etc. and none of them can explain the current warming, but including our greenhouse gasses in the analyses does explain the warming (Stott et al. 2001; Meehl, et al. 2004; Allen et al. 2006; Wild et al. 2007; Lockwood and Frohlich 2007, 2008; Lean and Rind 2008; Foster and Rahmstorf 2011; Imbers et al. 2014). Indeed, literally thousands of studies have all converged on the conclusion that we are causing the planet to warm, and peer-reviewed studies to the contrary are virtually non-existent (but see the next major point below). As a result, this is another topic that enjoys an extremely strong consensus among actual experts.

Similarly, vaccines have been studied thousands of times and have been shown to be extremely safe and effective. Indeed, they are the most well-studied treatment in medical history, and you can find trials that looked at pretty much whatever particular adverse event you are interested in. There are, for example, numerous studies that failed to find any evidence that vaccines cause autism, including a meta-analysis with over 1.2 million children (Taylor et al. 2014). There are studies showing that vaccines don’t cause SIDs (Hoffman et al. 1987; Griffin et al. 1988; Mitchell et al. 1995; Fleming et al. 2001; Vennemann et al. 2007a; Vennemann et al. 2007b), studies showing that they don’t cause asthma or allergies (Schmitz et al. 2011; Grabenhenrich et al. 2014), studies showing that the flu vaccine doesn’t increase fetal or infant deaths (Mak et al. 2008; Pasternak et al. 2012a; Pasternak et al. 2012b; Fell et al. 2012; Haberg et al. 2013), etc. (you can find a non-exhaustive  list of a bunch of other safety trials here).

My point here is simple: all of these topics have been extremely well studied, and they are as close to settled as science ever comes. Anyone who holds one of these positions is denying a massive body of evidence, which is why I am comfortable with calling them science deniers. This also creates the dilemma that I will focus the rest of the post on. Namely, most of the people who hold these positions don’t want to be considered science deniers, so they have to come up with some excuse for rejecting science, and interestingly, they all seem to have converged on the same excuses.

Note: Inevitably on these topics, when faced with thousands of studies, people start shifting the goal posts and going down ever narrowing side-tangents, but the reality is that these topics are so well studied, that even if you want to go down a ridiculously specific side topic, in the majority of cases, there are still studies on that. So, before you comment with something to the effect of, “but what about…” or “the real issue is…” check and make sure that it hasn’t been studied, because odds are that it has.

  Cherry-picking small, poorly conducted studies

In an attempt to counter these mountains of evidence, many people rely on cherry-picking a handful of studies that appear to support their position, but this is problematic for a number of reasons. First, these topics have been studied so many times, that it is almost inevitable that there will be a handful of studies that reached a false conclusion just by chance (even if the studies were conducted flawlessly). This is a simple by-product of the statistical tests that we use (details here). Further, it is blatantly obvious that not all studies are equal. Bad research does sometimes get published. So, whenever you approach a scientific topic, you always have to look for a consensus among studies, rather than just cherry-picking the ones that agree with you. This is why systematic reviews and meta-analyses (like the ones that I cited earlier) are so useful. They condense the results of many papers into a single work so that you can see the overarching trends, rather than being deceived by the statistical outliers.

Additionally, you need to critically examine a study before you accept it. Ask yourself questions like, did it have a large sample size? Was it controlled properly? Did it use a robust design? Did it use the appropriate statistical tests? Was it published in a reputable journal? etc. These are really important questions, and they are questions that anti-vaccers, climate change deniers, and GMO opponents rarely ask. Indeed, these positions are famous for citing truly horrible studies. Just in the past few weeks, for example, anti-vax websites were singing the praises of a “new” study that claimed to show that vaccines were harmful, but in reality, the study was not set up correctly, it did not use the correct analyses, and it was so terrible that it was quickly retracted (details here). Further, that is far from a one-off event. Sherri Tenpenny (one of the leaders of the anti-vaccine movement) created an online “library” that exists for the express purpose of cherry-picking anti-vaccine studies for you; that way you can just see the studies that agree with you, without having to be bothered with the mountain of high quality studies that disagree with you (details here). Indeed, she makes no attempt to hide the fact that her site exists to help you find information that confirms your biases rather than trying to figure out what is true. For example, one of her pages advertising her site says (the weird capitalization was in the original),

“Convinced that Vaccines are Unsafe but Need Scientific Proof? You need information that gives you ‘The Other Side of the Story.’”

Similarly, on the topic of autism, anti-vaccers eagerly share lists of 100+ papers that supposedly show that vaccines cause autism, but as I explained at length here, many of those papers aren’t on autism or aren’t on vaccines, and the ones that are on topic all used small samples sizes and weak designs that can’t establish causation. In contrast, there are several large cross-section and cohort studies and even a meta-analysis with over 1.2 million children, all of which consistently failed to find any evidence that vaccines cause autism.

It’s easy to poke fun at anti-vaxxers for this, but climate change deniers and GMO opponents are no better. They do exactly the same thing. For example, I still see anti-GMO activists citing Seralini’s infamous rat study that claimed that GMOs caused cancer in rats. You’ve almost certainly seen it at some point next to pictures of grotesque looking rats. If you look a bit closer though, you’ll see that they used a breed of rats that already has high cancer rates, and the cancer rates of the GMO-fed rats were within the expected rates for that breed. As with so many of these fringe papers, that one has been retracted for being awful, but GMO opponents have plenty of other small and equally terrible studies, some of which I have discussed here. I also recommend this study which showed that many of those anti-GMO studies failed to use the correct statistics (they didn’t control the type 1 error rate), and when you apply the correct methods, the evidence that GMOs are dangerous disappears (Panchin and Tuzhikov 2016).

Climate change denial is the same thing, but I think I’ve made my point by now, so I won’t dwell on it for long. I would, however, encourage you to read the following critique on many of the climate change denial papers (Benestad et al. 2017; the supplemental information is particularly useful). As you might have guessed, they found that the studies were riddled with problems, and their results couldn’t be replicated.

Appealing to a minority of fringe “experts”/inflating the conflict

no matter what crackpot notion you believeAppealing to authority is another common tactic among all pseudo-science positions. All of these positions have a list of “experts” who they cite as evidence that their position is legitimate (Dr. Tenpenny and Dr. Mercola for vaccines, Dr. Soon and Dr. Spencer for climate change, Dr. Seralini for GMOs, etc.). After all, if someone has an MD or PhD they must know what they are talking about, right? Wrong! Earning an advanced degree does not guarantee that you are smart, nor does it guarantee that you know what you are talking about. So the fact that you found some MDs/PhDs who agree with you does not in any way shape or form validate or legitimize your position. Further, if we are going to insist on appealing to authority, why on earth should I listen to a cherry-picked handful of scientists instead of the vast majority who disagree with them? Further, in many cases, the “experts” being cited don’t have any relevant qualifications. Dr. Tenpenny, for example, is an osteopath. That hardly qualifies here as vaccine expert. Similarly, climate change deniers love to tout the “Oregon petition,” which is a fraudulent list of over 30,000 “scientists” who signed a petition saying that climate change isn’t real (because that’s how science works, we sign petitions on what is and is not a fact [sarcasm]). When you actually look at the signatures, however, it quickly becomes clear that most of the people on the list don’t have degrees in a field that is even remotely close to climatology, many of them aren’t scientists at all, and only around 0.3% were actually climatologists.

 All of this is closely related to a logical fallacy known as an inflation of conflict. It occurs when you use a minority of experts to falsely claim that there is serious debate about a topic that is actually pretty well settled among experts. The classic news interview with one climate change denier vs Bill Nye is a great example of this. It makes it look like two even sides, when in reality, it should be one climate change denier vs. over 30 climatologists (yes, there is roughly a 97% consensus in both the literature and among climatologists; multiple studies have converged on that number). This same strategy of inflating the conflict is also at play when people cherry-pick a handful of papers while ignoring the majority of papers that disagree with them (see point above).

Finally, inflation of conflict fallacies also frequently occur when people present a minor disagreement as if it is a major one. For example, I frequently see people present the fact that climatologists and climate models disagree about the exact extent of warming that will occur as evidence that there is general disagreement about climate change, but that is totally false. Virtually everyone (and more importantly, all of the data) agrees that the planet is warming, we are causing it, and it will create problems. Similarly, people often take disagreements over precise safety levels or specific facets of GMOs and vaccines and act as if there is widespread disagreement about their general safety.

 Inventing conspiracy theories

So, if cherry-picking papers and experts won’t work, then what is a science denier to do? Obviously, you invent a conspiracy. After all, why should you believe all of the studies/experts that say you are wrong when you can dismiss all of them in one fell swoop by blindly claiming that they were all paid off as part of some massive cover-up.

That may sound crazy (and it is) but it is exactly what people do all the time. When I present papers to science deniers, whether they are anti-vaccers, climate change deniers, anti-GMO advocates, homeopaths, etc. they almost always respond by blindly asserting that the study was funded by “Big Pharma,” Monsanto, etc. That response is not, however, logically valid. You can’t just assume that a paper is biased simply because you don’t like it. Further, scientific publications require authors to declare their conflicts of interest, so you can actually check and see if the paper was funded by a source that might have biased it. When you do that, you find that there are tons of independent studies that were conducted by researchers who aren’t affiliated with companies and didn’t receive funding from them. On the topic of vaccines and autism, for example, I have previously shown that most of the papers that confirmed the safety of vaccines did not have a conflict of interest, and many of the low-quality anti-vaccine studies did have conflicts of interest. Similarly, roughly half of GMO safety trials are conducted by independent scientists. I don’t have exact numbers for climate change papers, but if you start looking at the funding sources as you will find that quite a few of them are independent as well (I talked more about the money trail for all three of these positions here).

When faced with this fact, people almost invariably go down the conspiracy route and insist that all the world’s climatologists, doctors, etc. are being paid off. This is, however, 100% an assumption. Indeed, it is what is technically known as an ad hoc fallacy. It is a logically invalid excuse that I would never accept unless I was already convinced of the position being defended. You cannot just invent conspiracy theories to get around the fact that thousands of studies demonstrate that you’re wrong.

Nevertheless, some people try to make their position sound more legitimate by claiming that it’s not actually a conspiracy, but scientists are just going along with it to get grant money. That doesn’t make sense, however, because grant agencies usually rely on a board of scientists to review applications. So, for this to work, you’d have to have every scientist in a given field agreeing to give you money to crap projects just to keep the money flowing for everyone, which means that we are back to a conspiracy (also see the point below). Further, this claim is, once again, an assumption. You can’t state an assumption as if it is a fact, and you can’t use an assumption as an argument. Ask yourself this, is there any reason to think that this type of wide-spread corruption is happening, other than an ideological desire to reject these studies? No, there isn’t. There is no evidence whatsoever to support this baseless assumption.

 Falsely claiming that scientists are going with the dogma of their fields

that's not how this works memeIf being a conspiracy theorist doesn’t suit you, you might try claiming that many scientists actually know that climate change isn’t caused by us, GMOs are dangerous, etc., but they can’t go against the “dogma of their fields” because they’ll be ridiculed, won’t get funding, etc. That is, however, simply not how science works. In fact, it is the exact opposite of how it works. If this claim was true, then science would never progress, because no one would ever question the status quo, but science does progress because we constantly question the status quo. Indeed, challenging the accepted wisdom of our fields is the job description of a scientist. That’s what we do. No one is going to give you funding to test something that everyone already knows. You get funding for new and innovative ideas, for pushing boundaries, and for questioning what we think is true.

I’ve said this before, but it is worth saying again: every great scientist was great precisely because they discredited the common views of their day. As a scientist, just going along with the “dogma” of your field guarantees that you will have an unremarkable career and history will quickly forget you. If you want to get the big grants and go down in the history books, then you need to start discrediting some common views. Indeed, for me personally, as a young biologist, nothing could possibly be better for my career than discrediting evolution. It would win me a Nobel price and my choice of universities to work at, and the same thing would be true for a young climatologist who discredited climate change, an immunologist who demonstrated that vaccines do more harm than good, etc. So, why aren’t eager young graduate students publishing these revolutionary data? Because those data don’t exist! Extraordinary claims require extraordinary evidence, and if you want to overthrow a common view, you are going to need some really solid evidence, and there simply is no extraordinary evidence to support positions like climate change denial.

Finally, this argument is an assumption, and you cannot use an assumption as evidence. Unless you can actually prove that scientists are doing this, you simply don’t have an argument.

Note: To be clear, I’m not suggesting that one study would change things overnight. Scientists are a critical bunch, and we would want several labs to confirm a major finding before we overturned our fields, but being one of the scientists involved in that overturn would guarantee you a place in the history books. As a result, any scientists would be crazy to sit on those data and not publish them.

 Relying on secondary sources (blogs, Youtube videos, etc.)

At this point, we have exhausted anything even approaching a legitimate line of evidence or reasoning, but don’t worry, there’s always the internet. I’ll keep this one brief: if you want to claim that a massive body of scientific evidence is wrong, then you have to argue against it using the peer-reviewed literature. Nothing else will suffice. Nevertheless, anti-vaccers, GMO opponents, and climate change deniers all love to direct people to blogs, videos, etc. as evidence that their position is correct.

 Appeal to anecdotes, personal experience, etc.

In keeping with the point above, anecdotes, isolated news reports, personal experiences, etc. simply don’t matter. I, quite frankly, do not care if you feel healthier when you don’t eat GMOs, observed an adverse event after a vaccine, don’t think it feels warmer now than it did in the past, etc. Science says you’re wrong (well, more specifically, scientific studies provide evidence showing that you’re wrong, since science itself is a method, but I digress). As I said above, for scientific topics, only scientific studies count as evidence. You simply cannot use an anecdote as evidence against a study.

 General cherry-picking

I’ve talked about several specific cases of cherry-picking throughout this post, but it is probably worth mentioning that this is also employed as a more general strategy. In other words, people will cherry-pick isolated facts or instances and totally ignore the big picture. For example, anti-vaccers love to cite particular instances when a vaccine failed or when a problem was detected, while totally ignoring all of the times that they worked wonderfully and saved millions of lives. Similarly, anti-GMO activists will cite particular cases where a GMO hybridized with a wild plant or a pesticide had some negative effect on the environment, while totally ignoring all of the times that these things didn’t happen with GMOs or did happen with traditional crops. Yes, traditional crops (including organic) can be quite harmful for the environment as well. They can kill non-target species, damage the soil, hybridize with wild plants, etc. Indeed, when you look at the big picture, GMOs actually have fewer and less-severe impacts on the environment than traditional crops (see the sources in the first section, and also realize that I am necessarily speaking in crude generalities for the sake of writing a post rather than a book; there are lots of traditional crops and lots of GMOs and some are better than others, so I am talking about a general average effect, but it’s really better to compare two specific crops). Climate change deniers, of course, do exactly the same thing. They delight in pointing to blizzards or the Antarctic Sea ice, while totally ignoring the mean temperatures, heat waves, receding glaciers globally, etc.

 Appealing to nature

This one is admittedly a bit more of a mixed bag. Anti-vaccers and GMO opponents do this very blatantly by claiming that vaccines/genetic engineering are bad because they are unnatural (which of course is a logical fallacy, because the fact that something is natural tells you absolutely nothing about whether or not it is good), but climate change deniers have their own form of appealing to nature as well. This occurs when they make the baseless and logically invalid assertion that the climate has changed naturally in the past, therefore the current warming is natural (see the sources in the first section for why we know it isn’t natural).

Again, for this one, the climate change denial argument is admittedly a bit different from the anti-vaccine/anti-GMO argument, but it is similar enough that I thought it was worth mentioning, and, indeed, I frequently see climate change deniers argue that global warming isn’t a problem because it is natural (which is a proper appeal to nature fallacy).

 Claiming that science is flawed/science has been wrong in the past

When backed into a corner by the evidence, even those who claim to love science will frequently resort to some variation of the “science has been wrong in the past/they laughed at Galileo and Columbus/science said the earth was flat” argument. I’ve dealt with this argument several times before (here, here, and here), so I’ll be brief.

First, of course science has been wrong before. That’s how it works. It is a gradual process of testing ideas and replacing old ones with new, better ones. If science was never wrong, science would never advance. This brings me to the second point: every time that a scientific result has been shown to be wrong, it was discredited by scientists doing science, not by someone on Youtube, a personal anecdote, etc. As I have said several times now in this post, for scientific topics, you must present evidence from peer-reviewed studies.

Third, most of the common examples of science being wrong (e.g., a flat earth) pre-date modern science by quite a bit. Indeed, it is really hard to come up with an example in the modern era where something as well established as climate change, GMOs, or vaccines has been discredited. Oh sure, there have been plenty of times when a popular idea was debunked, but none of those had the literally thousands of studies that these three topics have (no, the idea that smoking was safe was never strongly supported by scientific evidence). About the best example you can come up with is Einstein’s theory of relativity replacing Newtonian physics, but that wasn’t really a replacement as much as an expansion (i.e., Newtonian physics still work under most circumstances, they just weren’t complete).

Finally, the fact that science has been wrong before does not in any way justify your particular brand of science denial. Again, you need actual evidence. Also, if you accept science on some topics, then you are being logically inconsistent. In other words, if you can use the fact that science has been wrong before as an argument against climate change, for example, then why can’t I use it as an argument against gravity or against the shape of the earth?

But science is never settled/I’m just asking questions

Finally, many people like to appeal to the inherent uncertainty that is built into science and claim that the fact that science is never truly “settled” somehow justifies their denial of the current body of evidence. Or, they might claim to be “just asking questions” or “asking for more studies.”

That sounds fine at first, but it is actually just disguised denialism, and here’s why. It is technically true that science is never “settled” in that any result can technically be overturned by future evidence. In other words, science tells us what is most likely true given the current evidence, not what is absolutely true. However, that does not mean that it is valid to reject the current evidence whenever you want to. For example, it is technically possible that we are wrong about gravity, but it would be crazy to assert that since science is never settled, I am justified in rejecting the concept of gravity. Even so, topics like vaccines, GMOs, and climate change (I’ll throw evolution in there as well) have been so thoroughly studied that it is extraordinarily unlikely that we are wrong about them. To put all of this another way, it is logically invalid to assume that the current evidence is wrong just because it technically might be wrong (that is an argument from ignorance fallacy). You have to provide actual scientific evidence that it is wrong, otherwise you are not adhering to the rules of logic.

Similarly, there is nothing wrong with asking questions. In fact, I encourage it, but, you have to use good sources to answer those questions, and you have to be willing to accept the answers. In other words, there is nothing wrong with someone who has never studied climate change asking questions like, “is there good evidence that we are causing it?” but, when they are presented with the mountain of studies that clearly show that we are causing it, at that point, they can no longer claim ignorance. If you continue to act like the evidence isn’t there after you have been shown the evidence then you are, by definition, a denier. The same thing is true for those who claim to just want additional studies. The reality is that these topics have been so thoroughly studied from so many angles that if the current evidence can’t convince you, then nothing will. If the current evidence isn’t enough for you, then the problem isn’t the evidence, the problem is your adherence to ideology.

Summary

As I have tried to demonstrate thought this post, climate change denial, the anti-vaccine movement, the anti-GMO movement, and pseudoscientific positions in general are all fundamentally the same. They all ignore a large body of evidence while citing a few, cherry-picked, low-quality studies. Further, they all try to cast doubt on that evidence by appealing to a minority of “experts,” and they all invent baseless conspiracy theories and accuse scientists of blindly following the dogma of their fields. When you get right down to it, all of these positions are based on ideology, not facts. Again, to be clear, I am not attacking or even criticizing anyone. Rather, this is a plea for rational thought. A large portion of my readers seem to fully embrace the science on at least one of these topics, while rejecting the science on the other(s), but that is logically inconsistent. You can’t, for example, criticize an anti-vaccer for ignoring studies and inventing conspiracies, then turn around and ignore studies and invent conspiracy theories about climate science or GMOs. As I’ve said before, science is a method. It either works or it doesn’t, and you can’t cherry-pick when you do and do not want to accept the results that it gives.

Note: Inevitably someone is going to comment with something like, “I accept that GMOs are safe for humans and the environment, but I oppose them because food shouldn’t be patented, Monsanto is evil, etc.” (similar arguments exist for the other topics as well). If you are thinking about writing a comment like that, please don’t. If you truly fully accept the science, then for the sake of this post, I don’t have a problem with you. Most of those arguments do have countless logical inconsistencies and I think they are absurd, but for the sake of a post about denying the science itself, I don’t feel like discussing them here.

 Note: Someone may be tempted to accuse me of a fallacy fallacy. This occurs when you say that a position is wrong because of the arguments that are used to support it (i.e., it happens when you reject the conclusion of a bad argument, rather than rejecting the argument itself). That is not, however, what I am doing. Climate change denial, GMO opposition, etc. are wrong because of the mountain of scientific evidence showing that they are wrong. So I am not saying that they are wrong because of the bad arguments. Rather, I am simply trying to explain why the arguments are bad.

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Another terrible anti-vaccine study bites the dust

Lately, anti-vaccers have been touting a “new” vaccinated vs. unvaccinated study that purportedly shows that vaccines are associated with all manner of detrimental health conditions. I put the word “new” in quotes, because this study was actually accepted for publication once before, but the journal that had accepted it (Frontiers in Public Health) retracted it before it actually came out. Following that retraction, the authors managed to get it published in the Journal of Translation Science as, “Pilot comparative study on the health of vaccinated and unvaccinated 6- to 12-year-old U.S. children.” That journal has now also retracted it, but I somehow doubt that is going to matter to anti-vaccers. This is, after all, the group that continues to praise Andrew Wakefield, despite his work being retracted due to extremely clear evidence that he falsified data, violated ethical rules, and was in it for the money. Therefore, I want to actually go through this study and explain why it is absolutely terrible. As usual, my goal is provide a worked example of how to critically analyze scientific papers, rather than simply addressing this one study (see my previous posts here, here, here, and here).

Note: I started writing this post several days ago, then became busy with my actual research, and by the time I got back to it, several excellent blogs/sites had already dealt with it, but since I had already started it, I figured I might as well finish it and add my two cents to the discussion.

Biased sampling design

Before I talk about the methods used in the paper itself, I need to talk about some basic concepts in designing studies. The first rule of experimental design is that you need to get representative samples, because failing to get a proper representation of the population will give a biased result. Imagine, for example, that I conducted a poll to see how popular Donald Trump was, and to do that, I sent the poll to multiple Republican organizations and asked them to distribute it among their members. Obviously, I would get a very biased result, because my sampling was not representative of the entire population (i.e., I sampled a group that predominately likes Trump, rather than sampling the population as a whole). Conversely, if I had sent that poll to liberal groups, I would have gotten a result that was biased in the opposite direction. Do you see the point? If you use a biased sampling method, you will get a biased result. That is why it is so important to randomize your sampling rather than doing what is known as “convenience sampling.” This is where you get your data from a group that is convenient, rather than a group that is representative. For example, if I wanted to conduct a study on how people felt when eating organic vs traditional food, it might be convenient for me to stand outside of a Whole Foods and poll people as they exit, but that would obviously be an extremely biased design. Of course, they are going to say that eating organic makes them feel healthier, that is why they are there. So whenever you are reading a paper, take a good look at how they did their sampling, and make sure that it wasn’t biased (note: when I said that this was rule #1, I was being literal, this is literally the first thing that I was taught in the first stats course I ever took).

So, how did this paper do its sampling? You probably guessed it; it used convenience sampling.

“the object of our pilot study was not to obtain a representative sample of homeschool children but a convenience sample of unvaccinated children of sufficient size to test for significant differences in outcomes between the groups.”

That’s not how this works. Statistical tests are not magic wands. They rely on strict assumptions, one of which is that your sampling was done correctly. If you put garbage in, you are going to get garbage out. So, saying that you used convenience sampling so that you could run statistics makes no sense, because the usage of convenience sampling prevents you from drawing valid statistical inferences.

To give you some more details about what this study did, it sent a survey to homeschool groups and asked them to distribute it among their members. This survey asked various questions about the children’s vaccination status, health, conditions during pregnancy, etc. This is obviously a huge problem, because, as the paper itself admits, there is a disproportionate number of anti-vaccers among homeschoolers. Indeed, it is not at all difficult to imagine anti-vaccers eagerly sending the survey to their anti-vax friends and telling them to fill it out (I have seen this behavior on similar online surveys). Thus, the paper clearly had a biased sample, so of course it found that vaccines cause problems. When you use an extremely biased sampling design like this, you expect to get a biased result, just as I would expect to find that Trump is popular if I used a biased sample of Republicans. Given this design, it would have been shocking if the paper found anything other than “vaccine injuries.”

We could actually stop right here and be done with this paper, because this biased sampling design completely precludes any meaningful comparisons. We can already see that the results are meaningless, but wait, there’s more.

All the results were self-reported

Not only did this study bias the people that it sampled, but it also used an extremely unreliable method of getting data from them. You see, the survey was entirely, 100% self-reported. Parents never had to send in any medical documents. Rather, they simply reported the vaccines their child received, the health conditions, etc. This is a terrible data collection design because memories are notoriously easy to influence, and self-reporting like this frequently fails to give reliable results (especially when using a biased sample).

The authors described several ways that they tried to eliminate these biases and control the reliability issues, but they were not at all adequate. First, they said that parents were instructed to consult their actual medical records, rather than relying on memories. There is, however, absolutely no guarantee that parents actually did that. People are lazy and generally bad at following instructions, so it is really hard to believe that all the parents in this study actually looked up their child’s medical records. Similarly, the authors told parents only to report conditions that were actually diagnosed by a physician, but once again, there is no way to know if parents actually did that, and, in fact, it is extremely likely that parents didn’t follow that. Imagine that you have an anti-vaccine parent who is convinced that vaccines are dangerous and injured their child, but since they don’t trust doctors, they never actually had the condition diagnosed. Do you honestly think that this parent isn’t going to jump at the chance to report their child’s “vaccine injury” even though they never got an official diagnosis? People lie on medical forms all the time, why should this be any different? Further, even if we assume that no parents deliberately lied, that doesn’t address the issue of “alternative” health practitioners. A parent may have had a condition “diagnosed” by a naturopath, which in their mind, counts as a medical diagnosis even though it’s actually nothing of the kind.

Now, you may say that this is all very speculative and I can’t actually prove that parents didn’t strictly obey the rules set out by the authors, and you are correct, but you’re missing the point. Reliability is one of the requirements for a good scientific study, and I shouldn’t have to assume that parents reported the data accurately. The fact that I am forced to make that assumption makes this study unreliable. In other words, I don’t know that parents relied on memories, lied, used the diagnoses of pseudo-physicians, etc., but I also don’t know that they didn’t do any of those things, and that is the problem. It means that we have no reason to be confident that these data are accurate. In contrast, if actual medical records had been supplied by the parents, then we would know that the reports are accurate. Additionally, it is worth mentioning that it would not take many dishonest and/or lazy parents to bias the study. Their sample sizes were quite small (especially for the children who had certain conditions), so just a handful of parents who provided bad info could seriously skew the results.

To be fair, the authors state that they chose not to collect actual records simply because after talking to several homeschool groups, the realized that doing so would result in a much smaller sample size and, therefore, prevent them from doing the study. It is probably true that they had no choice but to do it this way, but that doesn’t automatically make this method valid. In other words, given the choice of either not doing the study at all or doing the study by using an extremely unreliable method, they should have chosen the former. Unreliable data are often worse than not having any data at all.

Finally, the authors said, “Dates of vaccinations were not requested in order not to overburden respondents and to reduce the likelihood of inaccurate reporting,” but this seems totally backwards and nonsensical to me. Think about it. They already instructed the parents to look at the medical records rather than relying on memories, so if the parents already have the forms in hand, how is it an “overburden” to ask them to write down the date? Indeed, asking for a date seems like it should make parents more likely to actually consult their records, rather than going from memory. It’s almost like the authors tried to make this study as terrible as possible.

Differing numbers of doctor visits

There is one final flaw in their sampling/data collection that needs to be addressed. Namely, anti-vaccine parents and pro-vaccine parents generally differ in the frequency with which they take their children to the doctor. Indeed, this study even found that these groups differed in how frequently they visited the doctor. This is another big problem, because if one group visits the doctor more often, then you expect them to be diagnosed with more conditions by mere virtue of the fact that they see doctors more regularly (thus maximizing the odds of detecting any problems). This automatically biases the study towards higher numbers of problems in vaccinated children.

Statistical nightmares

Finally, we get to the statistics, and they are a disaster. The first thing to note is that they compared vaccinated and unvaccinated for over 40 conditions. That is potentially problematic, because with that many tests, you expect to get some false positives just by chance. This is what is known as a type I error. I have explained this in detail elsewhere (here, here, and here), so I’ll be brief. Statistical tests give you the probability of getting a difference as large or larger than the one that you observed if there is not actually a difference between the two groups from which your samples were taken. Typically, in biology, we set a threshold at 0.05 and say that if the probability (P value) is less than 0.05, then the result is statistically significant. In other words, for statistically significant results, there is less than a 5% chance that a result that is identical or greater could arise by chance. If you think about that for a second though, it should become obvious that you will sometimes get false positives. Further, the more tests that you run, the higher your chance of getting a false positive becomes. Therefore, whenever you are using lots of different tests to address the same question (e.g., “are vaccines dangerous?”) you should adjust your significance threshold (alpha) based on the number of tests you run. However, the authors of this study failed to do this, and given the enormous number of tests they ran, some of their results are probably just statistical flukes. (on a side note, their tables are also very deceptive, because they only showed the results that were significant or nearly significant, which makes it look like vaccines were significant for almost everything, when in reality, only a handful of their 40+ conditions were significant. This is not an honest way to present the results).

Additionally, beyond testing numerous different conditions, they also went on a statistical fishing trip with how they structured the tests. For many conditions, they made comparisons among fully vaccinated, partially vaccinated, and totally unvaccinated children, then also made comparisons among all children who received at least one vaccine, and all children who receive no vaccines. That is a problem because, again, the more tests you do, the more likely you are to get false positives. You can see why this is a problem when you look at things like ADHD and ASD. When they used all three groups, ADHD was not significant, and ASD was barely significant (though it wouldn’t have been if they had controlled their type I error rate correctly), but when you jump down to the tests with fully and partially vaccinated children lumped together, suddenly you get stronger significances (if we ignore the type I error problem). Thus, by doing multiple tests, they were able to get one to be significant. That is not ok. It is what is known as “P hacking.” You can’t just keep manipulating and retesting your data until something significant falls out. The correct way to do this would have been to define the groups ahead of time (a priori) then only run the comparisons on those pre-defined groups.

Before I move on, I also want to point out that that lumping the partially vaccinated and fully vaccinated children makes little sense, because the partially vaccinated group should be all over the place. For example, surely, a child who only received one vaccine would be more similar to the unvaccinated group than the fully vaccinated group. This is yet another way in which the study was not designed reliably.

The next problem is confounding factors (i.e., things other than the trait you are interested in that differ between your groups and have the potential to influence the results). You see, the chi-square tests that the authors used are quite simplistic, and they have no mechanism for dealing with confounding factors (which is, once again, why it is so important to randomize your samples rather than using convenience sampling). The things being tested are, however, quite complex. For many learning disabilities, for example, it is well known that they are affected (or at least tied to) race, sex, genetics, etc. Therefore, unless the two groups you are comparing are similar with regards to all of those factors, your tests aren’t valid. However, the authors gave no indication of matching their groups by race, sex, medical history, etc. Indeed, the authors even acknowledged that there were differences between the two groups with regards to at least some factors (like the use of medicines other than vaccines). Therefore, we can automatically chuck out all the comparisons that used “unadjusted data.” In other words, all the results in tables 2 and 3 are totally meaningless. All those comparisons between vaccinated and unvaccinated children are utterly worthless because the experiment was confounded and the authors didn’t account for that. So even if they had sampled randomly, used actual medical records, and controlled the type I error rate, those results would still be bogus.

Next, the authors move on to look specifically at “neurodevelopmental disorders (NDD),” but to do this, they combined children with ADHD, ASD, and any learning disability. That is not a valid, reliable way to do this, because those things are quite different from each other. You can’t just lump any learning disability in with ASD then going fishing for a common cause. They aren’t the same thing, and there is no reason to put them together.

Further, at this point their methods become really unclear. They say that they used, “logistic regression analyses,” but they don’t give any details about how the model was set up. There are a lot of assumptions that need to be met before you can use this method, and they don’t state whether or not those assumptions were met. Similarly, it is very easy to set up these models incorrectly, and they give almost no information about how theirs was constructed. I need to know things like whether they tested for multicollinearity, but that information isn’t given. Further, based on what little description they do give, it seems like they almost certainly over-fit the model by including meaningless categories like religion. Things get even worse from there, because they start talking about adjusting the model based on significant patterns, but they give no explanation of how they made those adjustments. A proper paper should not make you guess about how the statistics were done. In other words, when you read a paper, ask yourself the following question, “if I had their data set, could I use the information in the paper to exactly replicate their statistical tests?” If the answer is, “no,” then you have a problem, and you should be skeptical about the paper. The type of extremely terse description that is given in this paper is totally unacceptable.

that's not good enough memeNow, at this point, you might protest and argue that I am assuming that they set up the model incorrectly. That is, however, not what I am doing. I’m not saying that they did it wrong; rather, I am saying that I don’t know if they did it right. A good paper should describe the statistics in enough detail that I know exactly what they did, and this paper doesn’t do that. It does not make it possible for me to evaluate their methods. To put that another way, extraordinary claims require extraordinary evidence, and if you want to say that vaccines cause neurological disorders, then you are going to need some extraordinary evidence, and a paper where I have to assume that the authors knew what they were doing simply doesn’t cut it. It’s not good enough. Further, given all of the other problems with this paper, it seems pretty clear that the authors did not know what they were doing, so I am not at all willing to give them the benefit of the doubt when it comes to logistic regression.

Summary

In short, this paper is utterly terrible from start to finish. It used an extremely biased sampling design, it used an unreliable data collection method, and it used bogus statistical tests that were poorly explained and failed to control confounding factors and the type I error rate. Indeed, when you look at how this study was designed, it was set up in a biased way that almost guaranteed that it would find “evidence” that vaccines are dangerous. It would have been shocking if such a horribly designed study found anything else. This isn’t science, not even close. It is a junk study that very much deserved to be retracted.

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