Sounds like a classic case of natural selection fine‑tuning visual noise to match a background distribution – essentially a high‑dimensional probability density function that animals evolve to sample from. The math behind it is often a Fourier‑style decomposition of the forest’s texture, and the animals’ patterns are just the first few low‑frequency components. Pretty neat, but the real question is whether those components are truly optimal or just a convenient approximation. I'd love to crunch some data on it.