Daisy Worlds

Daisy World is a computer model of hypothetical world orbiting a sun whose temperature, as typical for most stars, is slowly increasing. The model was introduced in [Watson & Lovelock, 1983; Biological homeostasis of the global environment: the parable of Daisyworld; Tellus B, 35(4): 286–9] to illustrate the plausibility of a self-regulating system emerging from physically realistic coupling between life and its abiotic environment.

The model planet contains only two types of life forms: black daisies and white daisies. The flowers of white daisies reflect light and its energy and thus have a cooling effect of their environment; the flowers of black daisies absorb light and thus have a warming effect of the environment. The albedo of the unpopulated bare ground of the planet is assumed to be roughly in-between the white and black daisies’ albedo.

The Daisy World model demonstrates that life adapted to certain optimal environmental conditions may be able to regulate its own environment toward these optimal living conditions. The living conditions in the model are represented by the planet’s surface temperature: both types of daisies best reproduce at some given temperature. As the planet is subjected to increasing solar luminosity (as has been experienced by the Earth and is probably the case for the vast majority of planets), the temperature of the planet is regulated by competition between the two daisy types. When the solar luminosity is low, the black daisies, which are warmer than their white counterparts, spread, and thus darken and warm the planet. As the luminosity of the sun increases, white daisies gradually take over, lightening and cooling the planet. As the star brightens over a threshold that would normally heat a bare planet to uninhabitable temperatures, the daisies keep it well within a few degrees of the optimum growth temperature.

Numerous extensions to the basic Daisy World model have been explored over the years.
To date, Daisy World continues to be a useful model for studying feedback and self-control in complex systems.

Simulations