In the first few pages of A Biologist’s Guide to Mathematical Modeling in Ecology and Evolution by Sally Otto and Troy Day they paraphrase Albert Einstein (pg 7) who said:
“Everything should be made as simple as possible, but no simpler”
After I give a talk, I am often asked questions such as: “you assumed that space is homogeneous, but isn’t there a mountain range to the west?” or “could you expand your model to consider the influence of hunting on adult wolf survivorship?” And for a split second this thought races through my head: They’re right. I am wrong. My work is wrong! This is terrible, I must add in hunting to fix it.
It is tempting to think that a more complex model is better. Will other scientists assume that I aren’t skilled enough to include hunting in the model? Will they not understand that this was my deliberate choice – the choice not to include it?
As a final comment, if some asks “could you expand your model to consider the effect of climate change?” at the end of one of my talks, I will return the question by asking what they think would change if I had explicitly included this. The question above, without further elaboration, could imply that I didn’t include climate change because I overlooked it. Returning the question helps to draw attention to the challenges that modellers face and to highlight the types of careful considerations that go into model construction.