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Patterns in nature are visible regularities of form found in the natural world. These patterns recur in different contexts and can sometimes be modelled mathematically . Natural patterns include symmetries , trees , spirals , meanders , waves , foams , tessellations , cracks and stripes. [ 1 ]
The science of pattern formation deals with the visible, (statistically) orderly outcomes of self-organization and the common principles behind similar patterns in nature. In developmental biology , pattern formation refers to the generation of complex organizations of cell fates in space and time.
It describes how patterns in nature, such as stripes and spirals, can arise naturally from a homogeneous, uniform state. The theory, which can be called a reaction–diffusion theory of morphogenesis, has become a basic model in theoretical biology. [2] Such patterns have come to be known as Turing patterns.
Top: A male ornate boxfish (aracana ornata). Bottom left: a close-up of the boxfish’s natural hexagonal pattern. Bottom center: fish pattern simulation based on Turing’s reaction-diffusion theory.
Three examples of Turing patterns Six stable states from Turing equations, the last one forms Turing patterns. The Turing pattern is a concept introduced by English mathematician Alan Turing in a 1952 paper titled "The Chemical Basis of Morphogenesis" which describes how patterns in nature, such as stripes and spots, can arise naturally and autonomously from a homogeneous, uniform state.
Many patterns in nature are formed by cracks in sheets of materials. These patterns can be described by Gilbert tessellations, [85] also known as random crack networks. [86] The Gilbert tessellation is a mathematical model for the formation of mudcracks, needle-like crystals, and similar structures.
Defining structure and detecting the emergence of complexity in nature are inherently subjective, though essential, scientific activities. Despite the difficulties, these problems can be analysed in terms of how model-building observers infer from measurements the computational capabilities embedded in non-linear processes.
The nerves of the cornea (this is, corneal nerves of the subepithelial layer terminate near superficial epithelial layer of the cornea in a logarithmic spiral pattern). [12] The bands of tropical cyclones, such as hurricanes. [13] Many biological structures including the shells of mollusks. [14]