Bio 1130 Lecture Notes PDF

Topic 1 THE SCIENTIFIC METHOD 1 Learning objectives Define science and explain what the scientific method entails and why it is important Distinguish the types of science, and types of reasoning, and outline both of their roles in the scientific method Differentiate between hy...

Topic 1 THE SCIENTIFIC METHOD 1 Learning objectives Define science and explain what the scientific method entails and why it is important Distinguish the types of science, and types of reasoning, and outline both of their roles in the scientific method Differentiate between hypothesis vs. prediction vs. theory Explain why science proceeds via rejecting, not proving, hypotheses Summarize the characteristics that distinguish science from non-science Explain confounding variables and the role of controls in addressing them Explain the concept of inferential strength and extrapolation, and how these relate to observational vs. manipulative studies Outline the four requirements for science to result in knowledge acquisition Demonstrate concepts from above via the case study on the evolution of human skin colour 2  Definitions Biology: the intellectual and practical activity encompassing the systematic study of the structure and behaviour of the natural world through observation and experimentation Scientific method: an approach to knowledge acquisition that seeks to ensure that our understanding is based on evidence (i.e., data acquired through observation and experimentation) 3 Two types of science Descriptive: seeks to characterize ‘patterns’ (i.e., to describe the physical and/or natural world) Hypothesis-testing: concerned with testing one or more causal explanations for an existing pattern (i.e., to explain observations of the physical and/or natural world) 4 Both types of science are important to the scientific method descriptive science provides the grist for the hypothesis-testing science mill (i.e., it provides patterns and may suggest possible explanations) hypothesis-testing science interprets patterns and, in doing so, provides direction as to where to look for other patterns Descriptive science Hypothesis-testing science 5  Example: eutrophication in freshwater lakes 1) Descriptive study reveals a pattern: 3) An experiment manipulating [K] finds no effect, rejecting this hypothesis. Primary production 4) Characterize more patterns; Is primary production correlated with something else? Is [K] correlated with this? Potassium [K] concentration 2) Hypothesis: [K] is a limiting nutrient such that increasing availability fosters increased algal growth. 6  The scientific method Descriptive science Biological hypothesis Deduction Descriptive Induction Hypothesis-testing science science Predictions Study Inference Data Conclusions (statistical (patterns) (support or reject biological hypothesis) hypothesis testing) 7  Induction Specific observations (patterns) are synthesized to produce a general statement or conclusion (reasoning from the particular to the general) Even if all the axioms are true, the conclusion is not necessarily true. Inductive reasoning is often the source of biological hypotheses, but is ideally not used to test them This bird is a swan & it is white. And this bird is a swan & it is white. ∴ All swans are white 8  The scientific method Descriptive science (biological) hypothesis Deduction Descriptive Induction Hypothesis-testing science science Predictions Study Inference Data Conclusions (statistical (patterns) (support or reject biological hypothesis) hypothesis testing) 9  Deduction in hypothesis-testing science Hypothesis: a causal explanation for a given pattern Prediction: a statement of what will be observed under specified conditions (i.e., those of the study we’re going to do) if the hypothesis is true. A prediction only exists within the context of a hypothesis and a particular study The scientific method uses deduction to derive predictions and hence to test hypotheses 10  Deduction A form of reasoning from one or more general statements (premises) to a logical conclusion There is no uncertainty: if the premises are true then the conclusion necessarily follows (i.e., it must be true) It can be represented by a syllogism: – Premise 1: All birds have feathers. – Premise 2: All robins are birds. – Deduction: Therefore, all robins must have feathers. 11  Deduction With respect to testing a scientific hypothesis, predictions must follow deductively from hypotheses Syllogisms can also be presented as if…then statements – If hypothesis X is true, – and a study of type Y is performed, – then result Z will be observed. 12  What makes a “scientific” hypothesis? According to Sir Karl Popper, in addition to being causal all scientific hypotheses must also be refutable, at least in principle A refutable hypothesis is one for which there are possible outcomes that are inconsistent with it I.E., it can be falsified (in theory) The ‘hypothesis’ that the fossil record of life on earth was created by god is not falsifiable. There is no observation that could refute the existence of a supernatural being. It is therefore not a scientific hypothesis. Why must hypotheses be refutable? 13  Science proceeds by falsifying hypotheses Popper argued that science best proceeds by eliminating hypotheses, not proving them, because you cannot prove a hypothesis “When you have eliminated the impossible, Watson, whatever remains – however improbable – is the truth.” Sherlock Holmes, Hypotheses The Sign of Four Pattern we want to explain 14 A logical fallacy: you can’t prove a hypothesis If H then P Humidity is high this morning because it rained last night (H). P observed If it rained last night, the garden will be wet (P). The garden is wet (i.e., P is observed). ∴ H true Therefore, the high humidity is because it rained last night. This argument is invalid because the conclusion can be incorrect even if P follows deductively from H and P is observed. Why? Because H is not the only potential cause of P. So, observing the prediction SUPPORTS, but does not prove, the hypothesis. 15  But you CAN disprove a hypothesis If H then P Humidity is high this morning because it rained last night (H). P NOT observed If it rained last night, the garden will be wet (P). The garden is NOT wet (i.e., P is not observed). ∴ H false Therefore, the high humidity is NOT the result of rain last night. This argument is valid because the prediction follows deductively from the hypothesis. So, a failure to observe the prediction falsifies the hypothesis. 16  Example: why the bathroom light doesn’t work Hypotheses Power What we want off to house to explain Bulb burnt out Light switch is on, but there’s no light Short in circuit 17  Hypotheses and predictions Hypothesis: a statement about the cause of some pattern Prediction: the pattern one will see in the results of a particular study if the hypothesis is true Inference: – if predicted pattern is observed, hypothesis is supported (but not proven) – if predicted pattern is not observed, the hypothesis is rejected (falsified). 18  The scientific method Descriptive science (biological) hypothesis Deduction Descriptive Induction Hypothesis-testing science science Predictions Study Inference Data Conclusions (statistical (patterns) (support or reject biological hypothesis) hypothesis testing) 19 Type of study Separate from the type of science, there are two types of study: 1) Observational - researcher observes/measures/characterizes, but does not alter, the system 2) Manipulative (aka an ‘experiment’) - the researcher changes something and compares what happens to a control (i.e., unmanipulated) treatment, or one or more other treatments with different values of the manipulated variable The type of study is independent of the type of science. Don’t confuse them! 20 Examples of the two types of study 2) Manipulative (experiment) 1) Observational study Primary production Phosphorous concentration 21 All combinations exist for types of science and study Type of science Type of study Descriptive Hypothesis-testing When do hummingbirds Measure the correlation between arrive in the spring? chlorophyll content and phosphorus Observational Where are the areas of across many lakes to test the highest biodiversity? hypothesis that P is limiting Fun science. What Classic experiment to test happens when I…? predictions of a hypothesis. Manipulative Treatments are compared to each other or to a control. 22  Practice Hyperlink (click here), or: Q1: Correlates of marijuana use among under undergraduate students. 23 23  Observational vs. manipulative studies: why do we care? Inferential strength is a measure of how strongly the results support the conclusions. All else equal (caution, it never is), manipulative studies have greater inferential strength than observational studies Why? Because manipulative studies better control for confounding variables. This is why you often hear that “correlation doesn’t imply causation”. 24  Confounding variables A separate, often unknown, variable that may be responsible for the observed pattern. Statistically, a third variable that is correlated with the independent variable and which may be causing the association between the dependent and independent variables. Lake primary productivity (dependent variable) Potassium conc. Phosphorous conc. (independent variable) (confounding variable) 25 Consider a manipulative experiment The independent variable (e.g., potassium conc.) is actively changed by the researcher, so confounding differences are FAR less likely When a potential confound exists, it can be addressed via appropriate controls A control is an experimental procedure or treatment level designed to minimize the effects of confounding variables. 26  Example: effects of an oncolytic virus on tumour growth in mice Biological question: can a tumour-killing virus effectively reduce tumour growth rate in vivo? Procedure: inject a virus suspension into spontaneous tumour mouse model and track tumour growth Design question: what are the appropriate controls? – A second set of mice that don’t receive the virus injection? – Something better? 27  All else is often not equal: extrapolation Studies, especially manipulative experiments, are almost always conducted on ‘model' systems that are smaller in scale, and/or simplified, compared to the system of interest Drawing inferences from results of studies on model systems requires that we assume that the model system behaves similarly to the actual system of interest This is called extrapolation, and the more extrapolation that is required, the lower the inferential strength Observational studies often involve far less extrapolation than manipulative studies 28  Common types of extrapolation Extrapolation is common and often extreme: Interspecies (very common in biomedical studies – e.g., rates as models for humans) From experimental indicators (that which we measure or estimate) to system properties of real interest (e.g., from expression levels to protein levels, from species richness to “biodiversity”, etc.) Spatial and temporal scales In vitro to in vivo 29 29 Practice Hyperlink (click here), or: Q2: Which of the following affect(s) the inferential strength of a study? 30 30  The scientific method Descriptive science (biological) hypothesis Deduction Descriptive Induction Hypothesis-testing science science Predictions Study Inference Data Conclusions (statistical (patterns) (support or reject biological hypothesis) hypothesis testing) 31  Statistical hypothesis testing In almost every study, we want to know if a pattern in the results is real (i.e., is it the result of chance – i.e., random sampling variation – or is it a repeatable, biological phenomenon?) This is the field of statistical hypothesis testing Don’t confuse this with scientific hypothesis testing. Descriptive science also often include statistical hypothesis testing to determine if any observed patterns are real It’s very important but poorly named. It should be called something other than hypothesis testing (e.g., ‘statistical inference’) 32  Summary – the scientific method Falsifiable hypotheses are derived (often inductively) from patterns arising from previous observation and experimentation Deductive predictions are tested via observational and/or manipulative studies with appropriate controls Statistical inference is used to determine whether predicted patterns are present in the results Inference is made to support or reject hypothesis based on this evidence 33  Science and knowledge acquisition Knowledge acquisition requires researchers to be: Rational (i.e., guided by reason): employ the scientific method to ensure inference are based on the evidence Remain always skeptical of hypotheses and evidence: – seek to repeatedly and carefully scrutinize patterns (i.e., are they real?) and hypotheses (Are they reasonable? Consistent with data?) – be willing to reject or modify hypothesis based on the evidence Strive to be objective: unbiased by preconceived notions, beliefs, ideologies, experiences, etc.) Be methodologically materialistic: restrict assumptions and explanations to the material world (i.e., the supernatural is not considered because it is not falsifiable and hence not scientific) 34  Science vs. Pseudo-science Studies that seek only to confirm beliefs are not science (Popper called them pseudo-science) Consider the hypothesis the world is flat: – One seeking to confirm this hypothesis could find (apparent) evidence in support of it, and if this fits with your preconceived notion there may be little incentive to do an exhaustive search for additional evidence that might refute it – But one seeking to disprove this hypothesis would only need show that one deductive prediction it makes is false to reject it – Observations interpreted as evidence of a flat earth are also consistent with a spherical earth (i.e., they don’t reject a spherical earth) 35  Hypothesis vs. theory A hypothesis that has survived many attempts at falsification is referred to as a theory (e.g., the theory of evolution) A scientific theory is an explanation of some aspect of the natural or physical world that has been repeatedly tested via the scientific method. It has withstood this rigorous scrutiny such that it constitutes accepted scientific knowledge This is very different that the everyday usage of theory as ‘speculation’ 36  Case study: skin colour evolution in humans Casual observation and more rigorous descriptive studies show geographic variation in skin colour. Why? What’s causing this? Biasutti (1941) By en:User:Cburnett, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=2866948 37 Modified from “The Evolution of Human Skin Color” by A. Prud’homme-Généreux. 2011. National Center for Case Study Teaching in Science, Univ. at Buffalo, State Univ. of New York  A biological hypothesis Humans and chimpanzees shared a common ancestors 6-7 Mya Chimpanzees are light-skinned but covered by dark hair Evidence suggests that early humans left the cover of trees for the open savannah where there is little shade Humans lost much of their body hair (possibly because of selection to facilitate evaporative cooling to dissipate heat) UV light causes DNA mutations Melanin, a pigment produced by skin cells, absorbs UV light, shielding cells from UV-induced DNA damage Hypothesis: variation in human skin colour evolved from selection for increased melanin in areas of high UV exposure because this reduces UV- induced DNA damage (i.e., skin cancer) 38  Testing the hypothesis: an observational study Global UV Index Lighter skin Darker skin National Oceanic and Atmospheric Administration. Retrieved 18 Oct 2009 Barsh (2003) from Relethford (1997) Evidence is consistent with (i.e., supports) the hypothesis It remains possible that another hypothesis makes the same prediction As scientists, we remain skeptical and objective 39 Problem Skin cancer generally arises late in life, long after reproduction, and is usually not fatal Jablonski & Chaplin (2000) argued that selection for increased melanin resulting from decreased cancer risk will therefore be very weak Prof. Nina Jablonski …and that the cancer-protecting function of melanin is unlikely to be the primary selective agent favouring increased melanin (i.e., it may have contributed weakly or not at all) 40  Folate Folate (folic acid) is an essential nutrient for DNA synthesis and is especially important during pregnancy when DNA replication rates are very high in the fetus Blood folate in people exposed (‘Patients’) or Folate deficiency causes anemia in not (‘Normals’) to UV light for 9h/d for 3 mothers, serious neural defects in the months. developing fetus, and increases risk of Correction to video: miscarriage melanin reduces the loss of FOLATE due to UV- Melanin protects against UV-induced induced degradation. breakdown (i.e. photolysis) of folate in the skin 41 Branda & Eaton (1978) Science New hypothesis Hypothesis: humans evolved increased melanin (and hence darker skin) in areas of high UV exposure because this protected them from UV- induced degradation of folate This can explain the evolution of darker skin in humans following hair loss, but it CANNOT, on its own, explain the evolution of light skin (i.e., there is no advantage of light skin, so darker skin should eventually evolve everywhere) 42 Vitamin D3 UVB is critical for the synthesis of vitamin D3 which starts in the skin D3 is needed for calcium absorption and hence bone growth; deficiencies can lead to immobilization, developmental deformities, and death In northern latitudes, dark skin can cause D3 deficiency Hypothesis: selection in more extreme latitudes favours lighter skin to increase vitamin D production Vitamin D3 43  Jablonski & Chaplin (2000) Insufficient UVB to synthesis in D3 in light, moderate and dark skin Sufficient UVB to synthesis Insufficient UVB to synthesis D3 in even dark skin in D3 in moderate to dark skin 44 Support Previously observed broad association between skin colour and latitude is consistent with this hypothesis Additional support: Females require more D3 than males during pregnancy and while breast feeding. And across human populations, females consistently have slightly lighter skin colour than males on average. D3 can also be obtained through certain foods including fisher liver oil. Indigenous populations at extreme latitudes (e.g., Inuit) have darker skin but historically also had diets rich in such foods. 45 Overall Current evidence strongly supports this hypothesis that skin colour has diverged evolutionarily among human populations in response to selection arising from environmental differences A trade-off exists between selection for darker skin to reduce folate photolysis and selection for paler skin to facilitate vitamin D3 synthesis (when D3 cannot be obtained through diet) Effects of melanin in reducing skin cancer by protecting from UV-induced mutation probably contributed little to the evolution of current differences in skin colour 46 Topic 1: Additional resources Textbook: Campbell Biology, Concept 1.3 – 3rd edition: pp 16-21 – 4th edition: pp 15-21 Excellent Crash Course video about K. Popper and the scientific method: https://www.youtube.com/watch?v=-X8Xfl0JdTQ&t=397s Evolution of human skin colour: Howard Hughes Medical institution video (with transcripts): https://www.biointeractive.org/classroom- resources/biology-skin-color 47