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Epistemology of natural sciences

Epistemology of natural sciences. Dr Tim Daw School of International Development University of East Anglia t.daw@uea.ac.uk. Overview. Epistemology – the nature of knowledge in natural sciences The ‘scientific method’ Popper – Falsification, Deduction Fisher - Statistical Hypothesis testing

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Epistemology of natural sciences

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  1. Epistemology of natural sciences Dr Tim Daw School of International Development University of East Anglia t.daw@uea.ac.uk

  2. Overview • Epistemology – the nature of knowledge in natural sciences • The ‘scientific method’ • Popper – Falsification, Deduction • Fisher - Statistical Hypothesis testing • Quantification and statistics applied to Fisher and Popper’s ideas • A typical ‘scientific study’ • Tillman et al • Problems with Null Hypothesis statistical testing • Observational and modelling studies • Complexity science, Systems ecology, Resilience

  3. How do you know what you know?How do know whether it is right?What qualifies as Knowledge?

  4. Monkeys can evaluate the reliability of their knowledge! How do scientists do it?

  5. ‘The scientific method’ • Basically POSITIVIST • One reality is out there – there is a ‘truth’ • Objective research is possible • Results depend on and reflect the nature of reality, not the nature of the researcher • Use of quantification and statistics to objectively describe reality • Generally REDUCTIONIST • Examine the effects of one factor at a time...

  6. Should the science of nature have a different epistemology to the science of human societies or economies?

  7. Induction Empirical research Theory Y is determined by X Data What theory can explain the nature of the data?

  8. Deduction Empirical research Theory Y is determined by X Data Does this data support the theory?

  9. Induction or Deduction? • Advantages of induction... • Disadvantages • What are you using in your research? • When would induction be useful? • When would deduction be useful? Theory DEDUCTION Explanation Testing Data INDUCTION

  10. Popper – Science is... • ‘Scientific’ and ‘unscientific statements’ • Theory can’t be proved, only disproved ‘The sun will always rise’ • Scientific statements must be falsifiable • Science should be the processof trying to disprove theories • Natural selection of theories that are not disproven Karl Popper 1902-1994

  11. Applying numbers to deduction... • Ronald Fisher • Provided mathematical framework to implement Popper’s falsification • Null hypothesis, H0 • Statistical testing • ‘Significance’ Ronald Fisher 1890-1962

  12. Deduction with null hypothesis testing Experimental research Null Hypothesis H0 Theory/Hypothesis X = treatment Y = response Y is determined by X Y is unrelated to X What is the probability of data if Ho is true? e.g. P = 5% (unlikely) Data H0 is unlikely to be true... Hypothesis is supported

  13. How unlikely should the data be in order to reject the null hypothesis?Why?

  14. Tillman et al (1997) • Background: Species extinction rates are ~1000 higher than background rates • Theory: Biodiversity is important for ecosystem function • Hypothesis: Changes in diversity will affect ecological processes • Treatment variables – Spp diversity and Func diversity • Response variables – e.g. Biomass, Nutrients cycling etc • Experiment: Manually manipulate diversity (treatment variable) and measure processes (response variables) • H0 – There is no relationship between diversity and processes

  15. Hypothesis: Biomass is a function of diversity • Biomass = an effect of Diversity + base level • Biomass ~ Diversity + Intercept • Null Hypothesis (H0): • The effect of diversity is zero Response variable Treatment variable

  16. Response ~ Spp Div + Func diversity + ‘intercept’ ‘Non significant’ – H0 not rejected Probability (of the data) if H0 is true is low p < 1%, result is ‘significant’ H0 is rejected -> Theory is supported

  17. But actually experiments are difficult in ecology? Graham et al 2008

  18. What are the epistemological implications of - observational studies?- Modelling studies?

  19. Null hypothesis statistical tests dominate the ecological literature NHST Inf theoretic Other NHST onobservations Even though ecologists often have to rely on observational data

  20. Issues with H0 statistical tests • Mis-interpretation • ‘proving’ the null hypothesis • Focus on the ‘p-values’ • Incomplete reporting and publication bias • Philosophical issues • Binary approach – Significant or not Is that really the important question? Stephens et al (2006)

  21. Use of modelling • Some of the most important Qs are not even observable • What will be the effect of ocean acidification on marine fisheries? Sumaila et al 2011

  22. Alternative inferences • ‘Information theoretic’ approaches (Burnham & Anderson 2002) • Compare alternative models (theories)... Graham et al 2003

  23. ‘New Ecology’: changing epistemologies • Complexity (see Berkes et al 2003) • Multiple interacting factors • Uncertainty • non-linear relationships • Human environment linkages • Social-Ecological Systems (Berkes et al 2003) • Political Ecology • More holistic approaches • Epistemological pluralism (Miller et al 2008) • Broader range of knowledges used (e.g. Local knowledge) What are the epistemological implications for ecologists studying linked social-ecological systems?

  24. Reductionism or Holism Salvador Dalí - Nature MorteVivante (Still Life - Fast Moving) (1956) Oil on canvas Carpenter et al 2009

  25. Range of epistemological approaches in natural sciences Empirical Theoretical Observational Experimental Context specific Abstract General Reductive Holistic Reductive Holistic Where does Tillman et al fit? For the most Natural scientist in your group – where does their study fit?

  26. References • Berkes F, Colding J, Folke C (2003) Navigating social-ecological systems: building resilience for complexity and change. Cambridge Univ Pr • Carpenter SR, Folke C, Scheffer M, Westley F (2009) Resilience: accounting for the noncomputable. Ecology and Society 14:13 • KornellN, Son LK, Terrace HS (2007) Transfer of Metacognitive Skills and Hint Seeking in Monkeys. Psychological Science 18:64 -71 • Miller TR, Baird TD, Littlefield CM, Kofinas G, Chapin III FS, Redman CL (2008) Epistemological pluralism: reorganizing interdisciplinary research. Ecology and Society 13:46 • Stephens PA, Buskirk SW, Rio CM del (2007) Inference in ecology and evolution. Trends in Ecology & Evolution 22:192-197 • Sumaila UR, Cheung WWL, Lam VWY, Pauly D, Herrick S (2011) Climate change impacts on the biophysics and economics of world fisheries. Nature Clim Change advance online publication • TilmanD, Knops J, Wedin D, Reich P, Ritchie M, Siemann E (1997) The Influence of Functional Diversity and Composition on Ecosystem Processes. Science 277:1300 -1302

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