Tuesday, May 12, 2015

The challenging interface of science, policy, and politics

Last week I went to an interesting talk What are the effects of dredging on the Great Barrier Reef?
by Laurence McCook, at the Global Change Institute at UQ.

I went because I knew Laurence in my undergraduate days at ANU. In first year we had all the same lectures, tutorials, and labs. (I guess groups were assigned based on the alphabet.) We became friends and he introduced me to many beautiful places for bushwalking [backpacking] and cross country skiing near Canberra.

There is a piece on the Conversation that gives a brief summary of the issues associated with the report from the expert panel that Laurence and  Britta Schaffelke co-chaired. Basically, it involved a "cat herding" exercise with 17 experts from industry, government, and universities. I am always impressed by people who manage such enterprises and can produce concrete useful outcomes. I think it requires considerable patience, political skills, and leadership. 

A helpful figure is below.
Aside: it would be interesting to try and do an exercise like this for topics such as cuprate superconductors, topological quantum computing, water, glasses, quantum molecular biophysics......

So what effect does dredging have?
Specifically, which of the effects is most likely to do the greatest environmental damage?

It seems that the ongoing turbidity [cloudy water] and sedimentation associated with sediment dynamics could be the biggest problem. But, this is also one of the most poorly understood processes. 
The figure below summarises some of the complex processes involved. Modelling this presents a major challenge (and some interesting science).

A problem with these exercises where science meets policy meets politics, particularly on controversial issues, is that they can highlight uncertainty and the general public does not like that. Science is meant to be certain. People want black and white answers. "Dredging is harmless and we should not worry about it vs. Dredging is an environmental disaster and should be banned".

It is interesting that of "10 scientific ideas that scientists wish you would stop mis-using" the first is Proof.

1 comment:

  1. In the helpful figure, I think that the "Known • and Agreed" circle of knowledge should be broken into 2 parts: (1) Known * and Agreed and * Empirically Valid and (2) Known * and Agreed and * Empirically Invalid. The worst mistakes in science might occur when 99.9 % of the experts "know" and agree but happen to be wrong.