Abstract
The increased availability of powerful computers over the last few decades has facilitated the development of in silico experiments. In this chapter, I discuss why quantitative models may be useful in landscape ecology along with best practices for experimenting via in silico models. I describe four different types of in silico models that landscape ecologists frequently make use of: statistical, mathematical, cellular automata and agent-based models. I describe what each type of model is, and illustrate with examples, highlighting the advantages and disadvantages of each. Researchers use computer simulation models to test model assumptions, characterize the properties of statistical estimators, and to apply models to real systems. In silico models can be considered experiments, and can meet the standards of experimental design. They are especially useful when combined with other types of experiments. I show how in silico experiments have addressed a wide range of landscape ecology questions – from species distributions to individual-level responses to disturbance and landscape change.
I do not fear computers. I fear lack of them.
Isaac Asimov
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Wiersma, Y.F. (2022). In Silico Experiments. In: Experimental Landscape Ecology. Landscape Series, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-030-95189-4_10
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