### The Mysterious Taylor’s Power Law – Part III

Taylor’s power law regards the statistical relationship between population variance and population abundance, V = aM b . I refer to Parts I–II for background information. Whether V(M) is studied at a given spatial resolution or from varying abundance M in a sample by changing grid resolution the still unresolved problem is that animal populations (covering a wide range of taxa) upon re-scaling tend to show b≈2. Typical range is 1.5<≈b<≈2.2 rather than b≈1. In other words, due to the power law structure population dispersion seems to be scale-invariant; also called self-similar and thus compliant with a statistical fractal (aggregations within aggregations within…). In this post, I illustrate how V(M) in the Zoomer model becomes compliant with real-life V(M) patterns when the model is parameter-tuned towards its default condition – scale-free population dynamics! Many model proposals exist for V(M) when sampling at a given spatial resolution, but despite thousands of papers ov