BIOL3045 Lecture Notes - Lecture 1: Industrial Revolution, Strong Inference, Atlantic Cod
3 Jul 2018
School
Department
Course
Professor
Animal Ecological Physiology BIOL3045 460381099
Lecture 1: Introduction.
Environmental change
• Correlation is not sufficient enough to explain cause and effect.
• Need to understand physiology, evolution and ecology to determine how an organism will
respond to an environmental change. Too simple to assume only one possible explanation.
• Correlations of animal population shifts with increasing temperature can suggest climate change
is the cause, however this may be due to other factors such as fishing, hunting, introduced
species, etc.
• Need to use experimental manipulation to explain cause and effect (experimental biology).
• Example: Atlantic cod moved north and disappeared from the south, correlated with increase in
north sea temperature however, was actually due to removal of fish from humans; English
butterfly moved north, correlated with them chasing the climate they evolved in however, was
actually due to them escaping the urbanisation (soot created from coalmines) during the
industrial revolution.
Reading: Platt, J. R. 1964. Strong inference. Science 146, 347-353.
• What is strong inference? The designing of experiments and the suggestion of alternate
hypotheses. They need to be rational and based on the hypothesis you have accepted or
excluded.
• What are its advantages? Based on strong intellectual basis, process is sped up and is more
specific. A method for reaching firm inductive conclusions one after the other, as rapidly as
possible to limit bias and erratic behaviour.
• Does that fact that “no two cells are alike” prevent inference? No, can be used to discover
something great and unknown, just like how other simplified models have been used to uncover
ground breaking information.
• Do you agree with the idea that: “If you have a hypothesis and I have enough hypothesis,
evidently one must be eliminated”? No, disproving something is very hard to do. There can be
multiple reasons for one explanation. It is too simplistic to assume that there can be only a single
explanation, most processes have multiple causes and their interactions.
