Three very distinct habitable environments. Puerto Rico's El Yunque Rain Forest and Guánica Dry Forest, and Chile's Atacama Desert. Credit: PHL @ UPR Arecibo
Not everywhere on Earth is equally habitable. From deserts to rain forest there is an obvious habitability gradient, from worst to best for life. We are using the presence of life as a ‘proxy for habitability’ to recognize similar pattern, assuming that a place with more life is more habitable than the other, an assumption not always correct. This type of patterns helps to correlate what environmental factors control conditions which support the presence of more life. Scientists use this type of information to create models to predict from the environment how much life they can potentially support.
A habitable environment is just an environment that might support some form of life, not necessarily one with life. Earth today is not that good for life if we consider its extensive areas of dry and cold deserts compared to rain forests. Mars is a certainly a desert planet but Earth today is more like a dry forest planet, on average. Imagine a rain forest planet, where most of its land areas support abundance life. That will be more habitable than Earth, again using the abundance for life as a proxy for habitability.
How exactly do we measure or quantify habitability? Habitability metrics is an emerging field within astrobiology, or more correctly a re-emerging field since the basis for it were established more than three decades ago. One of the most frequent questions in the astrobiology field is how to measure habitability. Some people even take the concept as difficult to define as life. The true is that biologists already tackled this problem successfully during the ’70 and ’80 but is still seldom known by the astrobiology community. There are various reasons for this.
First, habitability metrics originated within the field of ecology and population dynamics to understand the distribution of wild animals and plants. This seems to have no relation to astrobiology since it focuses more on microbial life. Second, this is a very specialized field within theoretical ecology and even not taught and used by all ecologists. Third, biologist calls it differently. We use the generic word ‘habitability’ but it is formally called ‘habitat suitability’ by biologists. So if an astrobiologist tries to look for scientific references on how to measure habitability he/she would probably miss the ‘habitat suitability’ concept or seem as irrelevant since it focus now on animal and plant life.
The definition and core mathematical framework of ‘habitat suitability models’ is something that can be extended to all forms of life, including microbial life, and to the astrobiology field. That is precisely one of the reason we established the Planetary Habitability Laboratory on 2010, to adapt and apply this framework to the astrobiology field, as we call it ‘habitability metrics for astrobiology.’ Our first application was the Earth Similarity Index (ESI), a measure of Earth-likeness for planets based on a given set of planetary parameters. This index was inspired by the diversity and similarity indices used in ecology to compare populations. Similarity indices are also used in many other applications such as pattern recognition (e.g. face recognition). Still, this approach is an indirect measure of habitability and we want more direct measures.
Habitability or ‘habitat suitability’ is defined as the suitability of an environment for life. This definition has three components, an environment, a life, and a suitability (see figure). All three need to be defined for a proper assessment of habitability. The ‘environment component’ is a description of the physical, chemical, or even biological location of life under consideration, the habitat. It is constrained by some space and time limits (e.g. surface of Earth today). This is the astronomy, planetary science, or geology part of the metric. The other two components contain the biology. The ‘life components’ requires the selection and knowledge of an individual species or community (i.e. aggregate of two or more species) as the test subject for the habitat. Therefore, given some habitat any habitability measure is always relative to the species or community under consideration. Finally, the ‘suitability component’ is the tricky part because it defines the connection between the environment and life. This is the ‘proxy for habitability’.
The suitability for life, or ‘proxy for habitability’, could be direct or indirect. An indirect suitability does not necessarily specify how exactly the environment component affects life. For example, we know that the environment requires liquid water but we don’t care about the specific differences on the quantity or quality of this water for life (e.g. salinity, temperature). This is the case of current efforts searching for habitable environments in planetary environments such as exoplanets. The occurrence of Earth-size planets in the habitable zone of stars (Eta-Earth) is in fact an indirect measure of stellar habitability, the suitability of stars for planets with life. The ESI is also an indirect measure, but of planetary habitability, the suitability of a planet for Earth-like life. Thus, indirect measures of habitability rely on occurrences (aka presence/absent in biology), a similarity, or probability of some necessary conditions for life. It is recommended that these values be expressed with a common scale as a fraction for consistency, where zero denotes a non-habitable environment and one denotes a highly habitable environment. Negative values could be used to rate the magnitude of the damaging effect of a non-habitable environment (e.g. both the surface of Mars and Venus are non-habitable, but Venus is worst). Values over one could represent super-habitable conditions.
The hardest part is to define direct measures of habitability, which are more biologically meaningful. These require much more knowledge of the interaction of life and the environment. There are some specific universal biological quantities that can be used as the ‘proxy for habitability’ such as growth rate, carrying capacity, metabolic rate, or productivity. Therefore, to construct a direct measure of habitability requires knowing how the environment affects one of these biological quantities for some species or community. We don't need to specifically estimate these quantities but only how the environment proportionally affects them. For example, we know how temperature affects the productivity of primary producers such as plants and phytoplankton. Most require temperatures between 0° to 50° C, but they do better (i.e. highest productivity) near 25°C. Their ‘thermal habitability function’ looks like a bell-shaped curve centered at their optimum productivity temperature. Direct measures of habitability are also better represented as a fraction from zero to one.
Another problem is how to combine the effect of many environmental variables into a single direct or indirect habitability index. These are called aggregation methods in theoretical ecology. There are many ways to do this. Probabilities are simple to combine since they are multiply to each other. Similarity indices are easier to construct and combine too. The use of any direct methods already defines how the environmental variables are combined since they are based on biophysical principles. In practice, we recommend biological productivity as the best ‘habitability proxy’ since we know how to calculate it for microbial to complex life, it is relatively easy to measure or estimate, and there are even ways to measure it via remote sensors. The NASA’s Terrestrial Ecology Program uses the TERRA and AQUA satellites to monitor the global land and ocean primary productivity of Earth. This is a measure of ‘global health’ or ‘terrestrial habitability’ since primary producers are the base of the food chain.
Unfortunately, most applications of habitability metrics in astrobiology are limited to indirect measures of habitability. This is especially true for exoplanets since we don't have enough information about them to appropriately weight how terrestrial life, life as we know it, could be affected by their planetary environment. There is no single quantitative measure of habitability but a collection of metrics for different types of environments and life. Nevertheless, habitability metrics are easy to compare and combine since they use the same scale and meaning (e.g. a value between zero and one). It doesn't matter the application, everybody would understand the meaning of an environment with habitability close to one. The next logical question after this statement is what are the limits of this value, in other words, what is the environment, reference life, and selected suitability under consideration.
Habitability metrics provide an excellent way to understand and compare habitable environments, and prioritize targets for exploration within Earth, the Solar System, and beyond. Biologists have been using them, as 'habitat suitability models' for more than three decades to understand the distribution of terrestrial complex life from local to global environments. It is only a matter of adapting this mathematical framework to the needs of the astrobiology science.
— Abel Méndez (First Draft, July 8, 2014)