15. 2017-July-27 Day 5- Duff

15. 2017-July-27 Day 5- Duff

While I'll get around to putting the prompts in later, here is my answers to the final batch of questions.

Part 1

To the readers of the International Grandma Herald,

This letter is a response to the video titled Natural Selection found at answersingenesis.org/natural-selection/.

This video presents an argument, even if it seems more like a series of questions and answers in response to a simple prompt. Countless similar videos and articles both on the answers in genesis website and others, present this same argument, one based upon the claim that evolutionary theory is unfounded. Successful communication between individuals necessitates shared understanding of the facts at hand, and so in any debate, it must be established that both sides are arguing with the same language, the same meaning. However, in this video, we can see use of what can only be described as using semantic (relating to the meaning of language) smoke and mirrors, combine with a willful reinterpretation and/or ignorance of evidence in preference to religious dogma.

Dr. Purdom begins her video by stating that the short answer to the question, of whether natural selection is the same as evolution, is no. She begins with providing definitions of the two scientific terms in the source question. Her definition of natural selection is mostly correct. However, she ends it with, “and there is a loss of information in the DNA. Genetic information decreases as a result of this process”. But what does information mean? If we’re talking about DNA, the suggested meaning here is that genes, or chromosomes, or sections of DNA, are being destroyed. And if this were to occur, then yes, it would be a loss of information. But this is not what occurs in Natural selection. Some of the variation in versions of genes (sets of DNA) may be lost as organisms which are less fit (in biology, fitness refers to organisms’ ability to reproduce in relation to one another; more fit organisms are more likely to survive to reproductive age and produce more offspring), but the total amount of “genetic information” in any given organism is not changing due from natural selection alone (more on this later).

She goes on, “Evolution is defined as an unobservable process which has occurred over long periods of time in which a single-celled organism has become all the organisms that we have today and have had in the past.”. However, yet again, if we examine actual definitions (drawing here from the simple English wikipedia article to make its meaning very clear) Evolution is “a scientific theory used by biologists. It explains how living things change over a long time, and how they have come to be the way they are”. The theory of evolution makes no implicit statements about the results of evolution (single-celled organism has become all the organisms), but rather the processes which explain them; nor is it implicitly unobservable, the science behind the theory of evolution is, like all science must be, based on observations.

Dr. Purdom then states “So, as you can see from the definitions they are very very different.” This is the capstone of this article’s semantic smoke and mirrors, the source of the visceral disagreement between biologists and skeptics: she provides definitions, different from those used by her opponents, and then uses her definitions for arguments about the nature of natural selection and evolution as they relate to one another. So, before we even come close to the later portion of the video where she brings up dogmatic conflicts, she is making an argument against evolution using definitions that are not the same as those used by evolutionary biologists. In this way the foundation of the science involved is being intentionally weakened by dissenting from using shared meaning as her opponents. She then considers the initial question satisfactorily answered, and leaves it behind to use her particular definitions in her continuing arguments.

Dr. Purdom then uses the occurrence(s) of antibiotic resistance in bacterial populations as an example of natural selection complete with a loss of “information”. She describes antibiotic resistance as occurring, due to mutations, with an intrinsic “cost”, “Genetic information has been lost as a result of this process”. In many real instances, this cost is not the loss of genetic information, as she would have you believe, but rather the metabolic (energy) cost of producing the factors involved in the resistance. In addition, there is also the process of biased mutations, wherein there is no intrinsic difference in cost between two versions of a gene (such as one involved in resistance), and so whichever version is most common will naturally occur more frequently in a population. This is why in normal bacterial population (one free of antibiotics) you see mostly sensitive bacteria; they are either spending less energy than those that are antibiotic resistant or simply occur in smaller numbers until selective pressures are applied (antibiotics are introduced).

This is compounded by her insistence that such antibiotic resistance occurs directly and solely through mutation, again, carrying with it her definition of mutations coming at a “cost”, which she implies to again be this “loss of information”. Mutation is the source of novel genetic variation as genes are reproduced with a small chance of errors in copy sequence. Genes can also move between populations through gene migration. As an example, we can imagine one rancher’s herd of cattle meeting another, and some members of each group breeding, passing their genes along to the offspring in another herd (this can be called vertical gene transfer, from parent to offspring). In bacterial systems, where they do not have genetic recombination through sexual reproduction, we do see the transfer of genes laterally (from one individual to another, as opposed to vertical gene transfer) from bacteria to one another; thus, a bacteria which has antibiotic resistance can provide a copy of the relevant genes to other bacteria, not losing its own, and adding, not replacing genes in the other bacteria. Mutations as well can lead to duplications, additions to, and changes in genes; mutation can generate new “genetic information”; Purdom’s assertions that natural selection cannot produce more complexity is correct, but it neglects the important role of naturally occurring mutations in populations producing new variability.

It is worth noting here, that the short and long answer to her prompt, “Is natural selection the same thing as evolution?” is still no. Natural selection is one of many processes that together produce the patterns of change and development underlying evolutionary theory.

“The pattern of evolution is descent with modification from common ancestors. The principle mechanism that drive this change is natural selection.” (Freeman & Herron, 2004).

A recurring motif throughout both this and other media concerning evolution skepticism is again this idea of semantic smoke and mirrors. Arguments frequently involve the circular logic that public often consider natural selection and evolution to be the same, and thus determining that natural selection is not, entirely in and of itself, evolution, somehow disarms the theory of evolution of its validity. Evolution is not in and of itself a force, a singular process, it is the description we use for the cumulative result of a number of different processes, including natural selection, mutation, gene migration, and genetic drift. Purdom and others like her are altering their interpretation of words to allow them to dismiss them based off of these misinterpretations.

By using smoke and mirrors to test the concept of evolution by different parameters than they are described to do, it is only natural that the theory of evolution would seem to be on shaky ground.

The remainder of the video then takes her personal framing of the nature of evolutionary theory and natural selection as a possible process contributing to it (she believes it does in fact not) and conjoins it to the dogma of the Young Earth Creationist movement. The Young Earth Creationist movement’s model of the Earth’s history, simply, is that the universe was created between 5,700 and 10,000 years ago, over the course of six 24 hour days, based off of the doctrine of biblical inerrancy, a literal interpretation of the bible.

It is here that one can recognize a functional purpose of the way Purdom has reinterpreted and spun her definitions to help bolster a specifically contrary dogmatic belief system using altered forms of scientific concepts. Scientists labor to understand the systems, mechanisms, and processes by which the world around us operates; they have no agenda for or against religious belief systems. However, when our observation- and evidence-based understanding of the universe produces conflict with religious writings and beliefs, we cannot defer to dogma. It is the preference of persons such as Dr. Purdom that scientists be perceived to be trying to disprove religious ideas and destroy faith, when in fact they are pursuing knowledge of the world with no theistic or atheistic biases. The arguments that Purdom are founded on a presumption of biblical inerrancy, which plays no role in the nature of science. Her assertions not only misframe the definitions of words in the contexts of their use, but reframes the arguments themselves to be those with which scientific exploration has no desire to participate in.

Sincerely,

-Thomas Beatman, PhD Student, University of Akron, Department of Biology, Integrated Biosciences Program

Postscript:

I have included here the web address for the Simple English Wikipedia entry for “Evolution” as a useful starting reference for anyone interested in understanding the ideas which actually underlie evolutionary theory. The Simple English version of wikipedia avoids overly technical language, and by extension, much of the semantic fog and mirrors that can be used to misrepresent complex concepts.

https://simple.wikipedia.org/wiki/Evolution

I have also included a link to a free pdf of the last of Darwin’s revised editions “On the Origin of Species”. Reading even just a few of the introductory chapters will rapidly illustrate the observations Darwin utilized to support the notion that natural selection can result in changes in populations, contributing to the larger idea of evolutionary theory. The book can be readily found for free online, as it is within the public domain, and can also be acquired relatively cheaply anywhere books are sold.

http://darwin-online.org.uk/converted/pdf/1876_Origin_F401.pdf

Part 1 Reflections

As stated by Fischhoff (2017), “The goal of science communication is not agreement, but fewer, better disagreements.” While this statement has a particularly broad application to all forms of science communication, it becomes especially pertinent when addressing the arguments of skeptics, whether they be of evolutionary theory or global climate change. Climate change and evolution skeptics rely frequently on what I have referred to throughout my letter as “semantic smoke and mirrors” or, to put a less pejorative tone to it, semantic fog. In either case, obscuring or denying consensus on the topics at hand allow them leeway to entrench their ideas in seeming facts (I hate to feel a need to use the term “alternative facts”, but when the shoe fits..). Both within these camps and the general public there is a growing distrust, or at least growing lack of reliance, on expert opinion, in preference to whatever rhetoric is seen most often, or most loudly. Where scientific communication may have been at one point confined to the realm of mere education, it now is more and more frequently faced with the hurdles of, to be hyperbolic, deprogramming misconceptions first before new information can be learned.

It has been shown that education, particularly education outside of formal class environs, is mostly effective at building upon and reinforcing preexisting knowledge and understanding of topics (Rennie & Williams, 2004), while the construction of new knowledge and mental models is far more difficult. This is particularly so when learners are aware, or made aware, of realms of knowledge that will produce cognitive dissonance with their mental models (Mckeachie et al, 2002; Wiles & Alters, 2011), and especially when they can decide to avoid such dissonance (Glaze & Goldston, 2015). This can make scientific communication difficult, as generating cognitive dissonance is one of the more effective ways to address misunderstandings (Bybee et al, 2006). This all results in the compounding of psychological, educational, and sociocultural factors which all make redressing changes in thought and understanding far more complex than merely presenting facts or data to support the truth of an idea.

All of the above elaborates the principles that underlay the rationale for the mental models approach to developing communication (de Bruin & Bostrom, 2017). To me, the challenge of modern science communication is to enable recognition of the value and use of cognitive dissonance as a means to improve learning. This is why the importance of “semantic stasis” (to borrow a term from evolution that almost assuredly is already used in linguistics, considering their phylogenetic similarities) is the major point of focus in my letter. I not only highlight the disconnect between Purdom’s definitions and the actual, but further elaborate why these differences both improve the perceived strength of her argument, and are the fatal flaws at use. In many ways, an important factor for science literacy is the ability to recognize the misuse of scientific language to communicate alternative facts. It will never suffice to explain merely why such sources are wrong without explaining why the sources are providing incorrect information to begin with. Just as the didactic content of any informal material will not be intrinsically interpreted correctly unless it’s expected outcomes are explicitly defined (Afonso & Gilbert, 2005), the accuracy of “facts” will not be questioned unless the motives and intent of science “miscommunicators” is laid bare.


 

Part 2 (I may have finally ran out of charge working on this one)

Science is, in many ways at its core, focused on determining not merely why things happen, or how things happen, but the mechanisms underlying them, the pieces and processes that in conjunction produce the resultant universe as we know it, with all its complexities. As creatures of story and metaphor, our understanding of such things is framed in those very narratives and analogies, and appreciating the state of many ideas as expressions rather than overly literal semantic units. It is through the use of such expressions, in their form as much models as they are narratives, that we can construct strong scientific theories (Ruse, 2005). Most importantly, in science, is that while we use metaphor as a tool, the metaphors themselves are constructed by statistics (Fodor, 1996).

There exists some layer of contention regarding what have been called the “historical sciences”, namely those sciences which concern themselves with studying and understanding events which have occurred in the past, utilizing evidence contained intrinsically in the present. This includes geology, evolution, ecology, astronomy, archaeology, and forensic science (Jeffares, 2008). One of the central premises of examining historical sciences and constructing hypotheses and theories is the idea of dispersal of of effects, the notion that a single event, a common cause, can produce numerous consequences, and as such, evidence of its occurrence. As these traces are left, we can use them to infer the state of the past and construct models (historical reconstruction).

Localized events tend to be causally connected in time in an asymmetric manner. As an example, the eruption of a volcano has many different effects . . ., but only a small fraction of this material is required in order to infer that it occurred; put dramatically one doesn’t need every minute particle of ash. (Cleland, 2001, p.989)

Our understanding of these “causal-chains” allow us to build interlinked histories out of disparate elements of chronology, regularities, with which we can further elaborate and examine models. These models often then allow for the establishment of additional regularities. Using these these regularities, we can also assess the common causes by examining the available modern evidence.

The concept of common causes, traces, and regularities is most familiar in the framework of phylogenetic analysis (which is, naturally, also a historical science) and the usage of outgroups. Whereas in phylogenetics one uses an outgroup to aid in defining plesiomorphic traits that are unlikely to have recurred convergently, individual traces can be used as “smoking-guns” to support the action of one hypothesized common cause more than another (Cleland, 2011). Meanwhile, in this more broad system of common cause, we examine modern traces using established theory. This allows for reciprocal illumination: sources of replicable data data allowing science to refine and revise theory to better inform interpretation of both old and new data (Smith 2008). Thus, common cause hypotheses can be tested and supported by finding traces to support the hypothesized common cause connected by regularities, and establishing regularities based on generalities of known dispersed effects (from previous testing) in conjunction with observed traces (Erwin, 2006). Bringing the framework of historical sciences into that of “experimental sciences”, one, can use pairings of sets of theories of events (dispersal effects/common cause), patterns (regularities), and present evidence (traces) to elucidate the remaining piece.  

To the extent that independent inferences from extant data converge onto a single relatively precise range for a hypothesized quantity, they provide strong evidence that there is some definite quality being measured; the probability that the inferred quantity is indicative of some actual past event or process increases as the number of independent inferential paths taken to the inferred value rises. (Forber & Griffith, 2010)

This statement, reconfigured to its various permutations of common cause, regularities, and traces, allows for a robust understanding of how historical sciences and experimental sciences share large overlap in the nature of their construction and investigation. Experimental sciences utilize inferences about the past to construct theory that underlays their experimental determine what causes effects, and historical sciences hypothesize causes to best explain evidence. Thus while the ordering of their components in ways are mirrored, the processes and ideas involved are the same; background theory is utilized to explain connection between cause and effect.

Jeffares (2008), compares these processes to “classic Sherlock Holmes”, and in this way I personally find the presentation of historical science and experimental science sharing common, valid principles particularly lucid.


Reflections (and personal examples of historical science in action):

When I first glanced over the reading list you gave me for comps and I saw the phrase “historical sciences” my brain thought of science, historically (namely, bad science, historically). So when I first started reading these papers, and realized what was actually going on, I was rather pleasantly surprised; I quite like history, the threads (or as I’d call them now, causal chains) interweaving between events, cause and effect, etc, but it didn’t seem super relevant (which is why I was glad to see that I had misunderstood on first glance). I find particularly interesting that there is this pseudo-schism between historical and experimental science. From my knowledge of both, perhaps in part due to my unfamiliarity with the history of historical science, I never really thought of historical science as being intrinsically different, or having possible philosophical/metaphysical deficits. I suspect that this may have something to do with the fact that I’ve been thinking, in the past decade, about phylogenetics from a very hypothesis driven level, conjecturing primarily on the mechanisms/transitions involved in the evolution of spider silk glands from.. Whatever it is they are derived from.

My old mentor Dr. Tillinghast gave me a copy of Endless Forms Most Beautiful by Sean Carroll in I believe late 2007, and so since reading that and taking a course on developmental biology, I’ve had the basic concept of evo-devo and its astonishing complexity as a sort of “regularity” (I still don’t feel as confident as I’d like that I’m using that term correctly) to build my own personal hypotheses. Spiders produce their silk from a sets of what are typically called “spinning apparatuses”, comprised of the glands within the body which produce the silk, the spigots from which the silk is extruded, and the spinnerets upon which the spigots are mounted, allowing for mobility of deployment of the spigots and precision placement of silk fibers (and glues, as appropriate). A classic (one of my all time favorites) paper, The Origin of the Spinning Apparatus in Spiders (Schultz, 1987), is one of the last broad and deep examination of the possible evolutionary origins of the spinning apparatus, and it is, of course, woefully out of date.

There are a number of different hypotheses and ideas that feed into my own personal model(s) of spider silk evolution, some of them are individual observations from evo-devo literature, such as the fact that just as wings are derived from the biramous appendages in early arthropods, spiders too feature similar genes in play in the development of their silk glands (Damen et al, 2002). Similarly, the spigots of the silk glands are well established to be homologous to some manner of spider setae (Bond, 1994); which kind remains unclear (the presence of lymph containing chemosensory hairs, once mistaken for silk producing setae on the feet of tarantulas, may or may not be an explanatory red herring; Perez-Miles et al, 2009, 2012; Rind et al, 2011; Foelix et al, 2012, 2013). Finally there is the fact that in more “primitive” (I had a whole question on “primitiveness” in Gavin’s exam, so I’ll just concisely use quotation marks and move on) spiders, one pair of spinnerets are segmented, innervated, and muscled just like the spider’s legs. This piece of the puzzle to me is one that is yet to be well clarified, but is made particularly complex, in my mind, since all other arachnids, and in fact all other chelicerates, for that matter, lack any appendage-like structures on their opisthosoma (abdomen), and there are even early ancestors of spiders (Uraraneidae, Selden & Shear, 2008) that feature spigots, but no spinnerets.

So from where did these leg-like spinnerets (assuming that these are in fact representative of an ancestral state for spiders) come from? Well, there seems to be a number of possible explanations, but from what I can figure, they all involve evo-devo mechanisms, namely ones responsible for producing leg-like structures:, either the elimination of an inhibitory genetic element preventing abdominal appendages after hundreds of millions of years of activity, a novel activation of the appendage forming gene toolkit in this one lineage or possibly that, that the sclerotized ventral abdominal plates found in more “primitive” arachnids are not in fact plates, but greatly reduced abdominal limbs, and so in our spiders we are not seeing what amounts to denovo growth of appendages, but rather the reversal of an ancestral reduction.

While the difference between the two theories is mostly metaphysical or semantic (and I suspect, impossible to differentiate even with the full suite of genetic techniques available; evolutionary time I suspect has eroded such fine traces), it would seem to me that with all of these individual traces, partial regularities, and evolutionary developmental theory, that there remains insight to be had in our understanding of such a significant evolutionary adaptation, and to do so requires this very same blend of the seemingly distinct historical and experimental sciences outlined in the various historical science papers cited above.

References

  • Afonso, A. S., & Gilbert, J. K. (2003). Educational value of different types of exhibits in an interactive science and technology center. Science Education, 91(6), 967–987.

  • Bond, J. (1994). Seta-spigot homology and silk production in first instar Antrodiaetus unicolor spiderlings (Araneae: Antrodiaetidae). Journal of Arachnology.

  • Bruine de Bruin, W., & Bostrom, A. (2013). Assessing what to address in science communication. Proceedings of the National Academy of Sciences, 110(Supplement_3), 14062–14068.

  • Bybee, R. W., Taylor, J. A., Gardner, A., Van, P., Powell, J. C., Westbrook, A., … Knapp, N. (2006). The BSCS 5E Instructional Model : Origins and Effectiveness. A Report prepared for the Office of Scienc

  • Cleland, C. E. (2011). Prediction and explanation in historical natural science. British Journal for the Philosophy of Science, 62(3), 551–582.

  • Cleland, C. E. (2002). Methodological and Epistemic Differences between Historical Science and Experimental Science*. Philosophy of Science, 69(3), 447–451.

  • Damen, W., Saridaki, T., & Averof, M. (2002). Diverse adaptations of an ancestral gill: a common evolutionary origin for wings, breathing organs, and spinnerets. Current Biology.

  • Dodick, J., & Orion, N. I. R. (2003). Geology as an Historical Science: Its Perception within Science and the Education System. Science & Education, 12, 197–211.

  • Erwin, D. H. (2006). Extinction. How life on earth nearly ended 250 million years ago. Princeton: Princenton University Press. Fischhoff, B. (2013). The sciences of science communication. Proceedings of the National Academy of Sciences, 110(Supplement_3), 14033–14039.

  • Fodor, J. (1996). Peacocking. London Review of Books, 18, 19–20.

  • Foelix, R., Erb, B., & Rast, B. (2013). Alleged silk spigots on tarantula feet: Electron microscopy reveals sensory innervation, no silk. Arthropod Structure & Development.

  • Foelix, R., Rast, B., & Peattie, A. (2012). Silk secretion from tarantula feet revisited: alleged spigots are probably chemoreceptors. Journal of Experimental Biology.

  • Forber, P., & Griffith, E. (2011). Historical Reconstruction: Gaining Epistemic Access to the Deep Past. Philosophy and Theory in Biology, 3(May), 1–19.

  • Freeman, S., Herron, J., & Jon, C. (2004). Evolutionary analysis. Retrieved from

  • Glaze, A. L., & Goldston, M. J. (2015). U.S. Science Teaching and Learning of Evolution: A Critical Review of the Literature 2000-2014. Science Education, 99(3), 500–518.

  • Mckeachie, W. J., Lin, Y.-G., & Strayer, J. (2002). Ceationist vs . Evolutionary Beliefs: Effects on Learning Biology. The American Biology Teacher, 64(3), 189–192.

  • Miller, J. D. (1998). The measurement of civic scientific literacy. Public Understanding of Science, 7(3), 203–223.

  • Pérez-Miles, F., & Ortíz-Villatoro, D. (2012). Tarantulas do not shoot silk from their legs: experimental evidence in four species of New World tarantulas. Journal of Experimental Biology.

  • Pérez-Miles, F., Panzera, A., & Ortiz-Villatoro, D. (2009). Silk production from tarantula feet questioned.

  • Rind, F., Birkett, C., & Duncan, B. (2011). Tarantulas cling to smooth vertical surfaces by secreting silk from their feet. Journal of Experimental.

  • Ruse, M. (2005). Darwinism and mechanism: Metaphor in science. Studies in History and Philosophy of Science Part C :Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2

  • Selden, P., & Shear, W. (2008). Fossil evidence for the origin of spider spinnerets, and a proposed arachnid order. Proceedings of the.

  • Stoltzfus, A., & Yampolsky, L. Y. (2009). Climbing Mount Probable: Mutation as a Cause of Nonrandomness in Evolution. Journal of Heredity, 100(5), 637–647.

  • Weber, J. R., & Schell Word, C. (2001). The Communication Process as Evaluative Context: What Do Nonscientists Hear When Scientists Speak? BioScience, 51(6), 487–495.

  • Wiles, J. R., & Alters, B. (2011). Effects of an Educational Experience Incorporating an Inventory of Factors Potentially Influencing Student Acceptance of Biological Evolution. International Journal of Science Education, 33(18), 2559–2585.

  • Wilson, K. M. (2000). Drought, debate, and uncertainty: measuring reporters’ knowledge and ignorance about climate change. Public Understanding of Science, 9(1), 1–13.

  • Yampolsky, L. Y., & Stoltzfus, A. (2001). Bias in the introduction of variation as an orienting factor in evolution. EVOLUTION & DEVELOPMENT, 3(2),

14. 2017-July-26 Day 4- Barton

14. 2017-July-26 Day 4- Barton