My examiner on theoretical ecology, Marissa Baskett, suggested that I return to some basic literature on the why of mathematical modeling in ecology. Here are notes on three papers:
Summary Modeling purpose must be clearly defined, as this determines whether to focus on generality, realisms, and/or precision Complexity is as often obfuscating as illuminating When prediction is a desired goal, separating calibration from validation is essential Must test robustness of models against different mathematical assumptions, structures, and parameters Many of these assumptions relate to the need to model at a simpler level than reality Disclosure, clarity, and reproducibility in publication are required to justify model use for prediction and policy Model precision is irrelevant if the model fails to address a question of relevance.
Read More…