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Ipimar Palestra 04.02.1999. How do we test models? Do “validation” and “falsification” mean anything? Bill Silvert Emeritus Research Scientist Bedford Institute of Oceanography. Summary, Part 1.
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Ipimar Palestra 04.02.1999 How do we test models? Do “validation” and “falsification” mean anything? Bill Silvert Emeritus Research ScientistBedford Institute of Oceanography
Summary, Part 1 The first question that comes up about a model is, “has it been validated?” It is not always clear that this is a meaningful question. For example, if we falsify a model based on conservation of energy, does this mean that we falsify the assumption that energy is conserved?
Summary, Part 2 Several examples taken both from physics and fisheries science show that what really matters is whether a model gives useful results, and that models which appear to be valid may not be very useful, while models that are demonstrably false or that cannot even be tested can still be useful.
Outline, Part 1 • Background – in physics models are good or bad, not valid or false. • Examples for the talk will be taken from physics and marine biology.
Outline, Part 2 • Newton’s theory of motion consists of his 3 laws of motion (F=ma) plus principle of gravity. • Newton’s theory was published in 1636, thoroughly tested, not questioned (except by philosophers) until Einstein in 1905.
Outline, Part 3 • Critical tests falsified Newton’s theory, confirmed Einstein’s. • But we still use Newton’s theory more than Einstein’s. It is much more useful.
Outline, Part 4 • Ecologists are different. Consider Gauss’ competitive exclusion principle, that two species cannot be functionally equivalent (occupy the same niche). David Lack used this principle to find zonation in warblers (passarinhos). So the theory is useful, but cannot be falsified.
Outline, Part 5 • Whereas physicists will use a theory that has been falsified, ecologists reject theories that may be correct, but cannot be falsified.
Outline, Part 6 • Was Newton falsified before 1905? His theory failed in predicting the motion of two planets. Precession of perihelion of Mercury, perturbation of orbit of Uranus. In first case precession really did falsify theory, in second, theorists questioned data and found Neptune.
Outline, Part 7 • Turning to marine biology, consider population cycles in fish. (Silvert & Crawford, 1986). This model was later falsified - or was it? • Amphipod example (amphipods that are starved still grow!) is obvious example of data that are clearly invalid on theoretical grounds.
Outline, Part 8 • What does this mean for testing of theories? When a theory is obviously correct, we need very good reasons to falsify/reject it. Growth of starved amphipods (Corophium volutator) does not falsify conservation of energy.
Outline, Part 9 • Empirical theories (statistical models) need to be tested. They only predict the past. We need to be sure that the assumptions of the models are correct, and make sure that the conclusions make sense – e.g., S. Gulf of St. Lawrence mackerel eggs/larvae regression predicts that larvae can come from zero eggs.
Conclusions, Part 1 of 2 • The most important attribute of models is that they must be useful. Models do not have to be valid, or falsifiable, to be useful. • We should not automatically demand that every model be validated before it is used.
Conclusions, Part 2 of 2 • When theory and experiment do not agree, we should not assume automatically that it is the theory (model) that is wrong. • Modelling should not be treated as a final process that completes an experimental program. It is an integral part of research, and modelling should be carried out in conjunction with experimental work.
