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Complexity of Models

Complexity of Models

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Complexity of Models

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  1. Complexity of Models Part of a short course by William Silvert Senior Research Fellow IPIMAR / DAA Lisboa, Portugal

  2. Scale and Complexity • Ecological models can cover a wide range of spatial scales, from the microscopic to an entire continent or even the whole biosphere. • The complexity of models can also range from one or two simple equations to massive computer simulations. • There is no relationship between the spatial scale and the complexity!

  3. Marine Examples • My model of the Grand Banks of Newfoundland, a huge marine ecosystem, is actually very simple. • Our model of the Cumberland Basin in the Bay of Fundy was much more detailed. • Models of Harmful Algal Blooms (HABs) in even a small basin can be incredibly complicated.

  4. Information Theory • The complexity of a model depends more on the amount of information that it processes than the spatial scale, number of species, or other more intuitive factors. • Information content depends both on the number of variables and the precision with which they are specified.

  5. How Complex? • When constructing a model, it is worth keeping in mind the wise words of D. B. Lee, Jr. (1973): • “Bigger computers simply permit bigger mistakes.” • Millions of dollars have been spent proving that Lee was right!

  6. Big Models • Let us take a look at the “advantages” of really big ecological models.

  7. Big is Good - #1 • They are straightforward to construct. • The challenging part of modelling is knowing what to include and what to leave out, and if you include everything, no judgement is required. Building such a model is like making a pile of bricks – it is hard work, but so simple that anyone can do it.

  8. Big is Good - #2 • They are relatively immune to criticism. • Because everything is included, the modeller cannot be accused of leaving anything out. Because they are so massive, sometimes with thousands of equations, no one can understand them, so it is hard to find fault.

  9. Big is Good - #3 • They attract funding. • Large models that require vast amounts of computing power are a safe bet for funding agencies and provide good public relations for supercomputer centres that spend most of their time developing missile shields and nuclear reactors.

  10. Big is Good - #4 • They are easy to publish. • Referees are reluctant to admit that they do not understand a paper, so unless they can find a concrete flaw (usually something from their own speciality that got left out), they just shrug and approve.