The Daisy World model describes a hypothetical planet that self-regulates, maintaining a delicate balance involving its biogeochemical cycles, climate, and feedback loops that keep it habitable. It’s associated with the Gaia Hypothesis developed by James Lovelock. How can we detect these worlds if they’re out there?
By looking closely at information.
A Daisy World (DW) is inhabited by two types of daisies: white and black. They have different albedos, and the blacks absorb more sunlight and warm the planet, while the whites reflect more sunlight and cool the planet.
As the DW’s star brightens, the planet’s temperature rises. At first, black daisies thrive because they absorb more energy. However, as the planet gets hotter, absorbing more energy becomes undesirable, and the white daisies begin to outcompete the blacks and thrive. As they thrive, they reflect more sunlight and cool the planet.
The result is a delicate homeostasis where the daisies regulate the planet’s temperature and keep it in a habitable range. It can’t get too hot and it can’t get too cold. The DW model shows how life can influence a planet’s climate and create conditions favourable for its own survival.
Earth is not exactly a daisy world, but life on Earth influences the climate. The DW model simply illustrates the concept of basic climate feedback mechanisms.
The ESA’s Sentinel 2 satellite captured this image of an algae bloom in the Baltic Sea in 2015. A ship can be seen moving through it. Algae blooms interact with the climate through feedback loops. Image Credit: Copernicus Sentinel data / ESA. In new research, scientists from the Department of Physics and Astronomy and the Department of Computer Science at Rochester University wanted to find ways to analyze how planetary systems like biospheres and geospheres are coupled. If there are self-regulating “Daisy Worlds” out there, how can we detect them?
The research is “Exo-Daisy World: Revisiting Gaia Theory through an Informational Architecture Perspective.” The lead author is Damian Sowinski, a research physicist and postdoctoral associate in the Department of Physics and Astronomy at the University of Rochester. The research is awaiting publishing and is not peer-reviewed yet.
The idea is to find a way to detect agnostic biosignatures on exoplanets. Regular biosignatures are specific chemicals like oxygen or methane that can be byproducts of living organisms. Agnostic biosignatures are indications that life is present but don’t rely on identifying which types of organisms might be producing them. Instead, they’re like overarching planetary patterns that living worlds produce.
For the authors, finding agnostic biosignatures begins with information and how it flows.
“In this study, we extend the classic Daisy World model through the lens of Semantic Information Theory (SIT), aiming to characterize the information flow between the biosphere and planetary environment—what we term the information architecture of Daisy World systems,” the authors explain.
Semantic Information Theory has been around since the mid-20th century. It attempts to define meaning in different contexts, how human subjective interpretation affects it, and related concepts in the same vein. It’s taken on a new focus as artificial intelligence and machine learning become more prevalent.
There’s a drive to understand exoplanet atmospheres and environments and to have a way to differentiate between those that may be life-supporting and those that aren’t. This is a complex problem that hinges on agnostic biosignatures.
The JWST captured this atmospheric spectrum of exoplanet K2-18 b showing the presence of methane, which can act as a biosignature. The authors say that information theory can help undercover agnostic biosignatures. Rather than specific chemicals like methane, agnostic biosignatures are patterns that can only be created by a biosphere. Image Credit: NASA, CSA, ESA, R. Crawford (STScI), J. Olmsted (STScI), Science: N. Madhusudhan (Cambridge University)Agnostic biosignatures are complex patterns and structures that can’t be explained by non-biological processes. There’s also disequilibrium, novel energy transfer, unusual levels of organization at different scales, and cyclical or systematic changes that suggest a biological cause.
A search for agnostic biosignatures can involve complex molecules that need biological synthesis, chemical distributions that require metabolism, unexpected accumulations of specific molecules, and features in an atmosphere or on a planetary surface that require biological maintenance.
Some examples of agnostic biosignatures on Earth are methane and oxygen co-existing in the atmosphere, the ‘Red Edge‘ in Earth’s vegetation spectrum, and daily or seasonal cycles of gas emissions.
The Red Edge is a region of rapid change in vegetation reflectance in the near-infrared (NIR). It could be useful in detecting vegetation on exoplanets. Image Credit: Seager et al. 2024. “The search for life on exoplanets requires the identification of biosignatures, which rely on life having
significantly altered the spectroscopic properties of a planet. Thus, exoplanetary life searches focus not
on detecting individual organisms but on identifying the collective effects of life on the planetary system—what we refer to as exo-biospheres,” the authors explain.
In short, we can’t study biosignatures without studying biospheres. In doing so it’s critical to understand where and how an exo-biosphere reaches a “mature” state where they exert a strong influence on the atmosphere, hydrosphere, cryosphere, and lithosphere, collectively known as the geosphere. Once they’re mature and exert a strong influence, they’re in line with the Daisy World hypothesis.
The authors aim is to study how information flows between a biosphere and the planetary environment. To do this, they modelled potential conditions on M-dwarf exoplanets and came up with equations that describe the co-evolution of the daisies on these worlds with their planetary environments. They created what they term an ‘information narrative’ for exo-Daisy Worlds (eDWs).
Typically, the homeostatic feedback in DWs rests on physical quantities like radiation fluxes, albedos, and plant life coverage fractions. That’s the physical narrative. However, the researchers used Semantic Information Theory to derive a complementary narrative based on how information flows. In their work, SIT focuses on correlations between an agent—the biosphere—and an environment and how those correlations benefit the agent.
Their model showed that as stellar luminosity rises, the correlations between the biosphere and its environment intensify. The correlations correspond to distinct phases of information exchange between the two. This leads to the idea of rein control, a control exerted by flora through the positive and negative differences of their albedos compared to the bare ground. This is how the biosphere exerts a regulatory influence on a planet’s climate. In their informational narrative, the planetary temperatures are more constrained “at the cooler and warmer boundaries of the bearable temperature range.”
Not all of the information that flows between the biosphere and the environment is relevant. The biosphere doesn’t use all of it because some of it doesn’t help the biosphere maintain control. The authors say that by analyzing all this information according to information theory, they can determine which information, and when and how, it contributes to its own viability.
The Daisy World model is instructive, but it’s a toy model. For example, it doesn’t include stochastic events like volcanic eruptions. But the big question is how does it relate to exobiospheres?
The authors say that their work shows the potential in using approaches like SIT to understand how exoplanets and their biospheres co-evolved like they have on Earth. More realistic models will be necessary that include more of the complex networks of interactions between an exoplanet’s living and non-living systems. The biosphere processes information in ways that non-living systems don’t, so information-centric systems can undercover agnostic biosignatures in ways that physical or chemical models can’t.
“As a result, the next step in our research program will involve applying SIT and other information-theoretic approaches to more complex models of coupled planetary systems,” the authors conclude.
