Projects‎ > ‎

Habitability Metrics for Astrobiology (AbSciCon 2012 Special Session)

The NASA Astrobiology Institute will have its Astrobiology Science Conference 2012 next April 16-20, 2012 in Atlanta, Georgia. As part of this conference we will have a special session on the Development of Quantitative Habitability Assessments for Earth, the Solar System, and Exoplanets (short title Habitability Metrics for Astrobiology). The main objective of this session is to start the discussion toward the development of standard procedures for habitability assessments within the astrobiology field. Such procedures should focus on terrestrial extreme environments, planetary environment (i.e. Mars), or extrasolar planets. This session is open to contributions from any scientists with an interest in this effort. Ecologists are particularly encouraged to participate.

The Habitability Metrics for Astrobiology session is under the main Extrasolar Worlds
 Session of the AbSciCon 2012 Program If you have any question please contact the organizers Abel Méndez, Alfonso Davila or Dirk Schulze-Makuch.

General Session Description

An interdisciplinary session to help establish the first steps toward the identification and integration of those relevant habitability assessments from ecology to the astrobiology field. This session requests the contribution of ecology experts on habitat relationship models together with astrobiologists studying and modeling the past or present habitability of Earth and planetary bodies such as Mars, Europa, Enceladus, Titan, and exoplanets. We expect that this session will help to advance and standardize habitability assessments within astrobiology and other disciplines.

Presentations: Thursday, April 19, 2012 @ 3:45 PM



3:45 PM - 5:45 PM

Energy and habitability: A case study of methanogenesis in serpentinizing systems
Tori Hoehler; M J. Alperin; T M. McCollom




3:45 PM - 5:45 PM

Bioenergetics and Body Size: general models for predicting the metabolism and growth of diverse organisms
Christopher Kempes; M J. Follows; M Girvan; G B. West; S Dutkiewicz; K Crowell




3:45 PM - 5:45 PM

A Generalized Framework for Quantitative Habitability Assessments
Abel Mendez




3:45 PM - 5:45 PM

One Plot to Rule Them All: Multiple Habitable Zones on a Single Graph
Shawn Domagal-Goldman




3:45 PM - 5:45 PM

Dwell Time Index – a new habitability metric for Astrobiology.
Andrew J. Rushby; A J. Watson



3:45 PM - 5:45 PM

Metrics to Assess Planetary Habitability: The Earth Similarity Index and the Planetary Habitability Index
Dirk Schulze-Makuch; Abel Mendez; A G. Fairen; P von Paris; C Turse; G Boyer; Alfonso Davila; M Resendes de Sousa Antonio; D Catling; L N. Irwin




3:45 PM - 5:45 PM

Metrics for Predicting Biological Complexity on Other Worlds
Louis N. Irwin; Abel Mendez; A G. Fairen; D Catling; Dirk Schulze-Makuch




3:45 PM - 5:45 PM

Polarimetric Signatures of Habitable Planets
Svetlana Berdyugina


The following text describes the session purpose and motivation in more details. An example of a quick and generalized procedure to create habitability assessments is described here and will be presented on the session.

Habitability Metrics in Astrobiology

Astrobiology is the science that studies the origin, evolution, distribution, and destiny of life. One of its main goals is to understand the nature and distribution of habitable environments in the universe. This requires the in situ or remote sensing exploration of potential habitable environments not only on Earth, our baseline for comparisons, but also in the Solar System and extrasolar planets. After many years of studies related to planetary habitability there is still no agreement by the astrobiology community on how to quantify and measure habitability. Only in the last years, a few astrobiology-motivated studies are starting to solve this problem by developing frameworks for habitability assessments. However, astrobiologists have been ignoring the over 40 years of experience on habitability assessments of the ecology field. Ecology is the science that studies the interaction of life with its environment. The relationship between an organism and its habitat is of theoretical interest because it is related to the distribution and abundance of species.

    Current efforts by the astrobiology community are comparable to the status of the ecology field in the late 1970’s. There was little coordination and connections between different studies as everyone was using their own definitions and method to define and measure habitability. It was until the U.S. Fish and Wildlife Service (1980 & 1981) organized and integrated the state of knowledge in a series of white papers that guided the community and advanced the field. Since then, habitability assessments in ecology have rapidly evolved incorporating more advance mathematical and computer tools, remote sensing techniques, and Geographical Information Systems (GIS).

    Quantitative techniques for evaluating habitats were first initiated by the ecology field in the late 1960’s and early 1970’s. Most of these initial models were used to establish habitat-species relationships for wildlife animals and later efforts included plants but rarely used for microbial life. The first widely used habitat quality assessments was the Habitat Suitability Index (HSI) developed as part of the Habitat Evaluation Procedures (HEP) of the U.S. Fish and Wildlife Service (1980 & 1981). The HSI is also one of the simplest models in ecology to quantify habitat quality mostly for wildlife. It compares in a 0 to 1 scale, existing habitat conditions with an optimum habitat conditions for the species of interest using the same key habitat components. Optimum conditions are those usually associated with the highest potential population densities (i.e. linearly related to carrying capacity). The basic assumption of habitat suitability models is that high-quality habitats (i.e., habitats that confer high fitness) are also able to maintain a large population.

    Various reasons can explain why the astrobiology community ignored previous ecology efforts. Astrobiology is a relatively new science and ecology scientists are underrepresented. Habitability assessments in ecology is also a very specialized field with a different tradition and terminology. What astrobiologists call quantitative habitability models or habitability metrics are formally called Habitat Relationship Models (HRM) in ecology. Other names include Habitat Quality Models (HQM), Habitat Capability Models (HCM), or Habitat Selection Models (HSM). Even the word habitability is seldom used, and the term habitat suitability is preferred. Therefore, a literature search might give the wrong impression that there are few studies in this problem. Besides, it might seem that the ecology efforts are not relevant to astrobiology as they mostly deal with complex life and not microbial life.

    The use of habitability assessments in astrobiology offer a very important tool to advance the understanding and interpretation of potential habitats in the universe. More important, habitability assessments are a mechanism to reduce the complexity of habitat-life interactions. This helps to identify and characterize potential habitable environments, prioritize and optimize search for life efforts compare habitable environments in space and time (i.e. Earth past and present), assess life-environments interactions, integrate planetary habitability studies, create classification systems, simplify the interaction between astrobiology and other fields, and even help the communication between astrobiologists and the general public. As was done in the late 1970’s with ecology, now is the time to consolidate habitability assessments efforts in the astrobiology field.

Habitability from Ecology to Astrobiology

Although originally develop for complex life, many of the ideas and methods of the ecology field can be adapted and extended to the needs of the astrobiology community. There is a need to adapt and expand previous habitat relationships models not only to microbial life but also to other spatial and temporal scales. These methods provide the connection between life and the environment that will help integrate and connect studies between and within astrobiology and other disciplines. The approaches behind the construction of habitability assessments in ecology provide a series of guidelines and methods extensible to any type of life or spatial and temporal scales.

    A basic requirement, often neglected, in any habitability model is the selection of a proxy for habitability, which is tied to a set of environmental variables and a specific species or community. The proxy should be a variable for which its functional form with the habitability is known. The easiest assumption is a proportional or allometric relationship between the habitability and the proxy. Another option are the Resource Selection Functions (RSF), which are used as simple but powerful statistical methods to model de potential distribution of species.

    Any habitability assessment requires an understanding of the effects of the environment on life. One way to study this process is by analyzing the compounded respond of individual environmental variables (i.e. temperature, light, and water availability) in the occurrence, physiology, or abundance of life. The usual approach is to combine the effects of many parameters into habitability indices. Indices are not only of interest to the specialist to reduce complex information but also of great value to the general public (i.e. heat index, moment magnitude scale, stock market indices, biodiversity index, citation index, climate-change index).

    Indices are generally defined as the ratio of a value of interest divided by a standard of comparison. The main problem with any habitability index is finding an appropriate standard of comparison for the environmental variables, the species, and the spatial and temporal scales under consideration. Typical function shapes to describe these relationships include linear, gaussian and logistic. Various aggregation methods can be used to describe the combined relationship between many parameters into indices. Examples include limiting factor, cumulative, compounded, compensatory (arithmetic, geometric, or harmonic), spatial, bayesian, fuzzy, set theory, multivariate (regression or discriminatory analysis).