Fault fictions: systematic biases in the conceptualization of fault-zone architecture

Mental models are a human's internal representation of the real world and have an important role in the way a human understands and reasons about uncertainties, explores potential options, and makes decisions.However, they are susceptible to biases.Issues associated with mental models have not yet received much attention in geosciences, yet systematic biases can affect the scientific process of any geological investigation; from the inception of how the problem is viewed, through selection of appropriate hypotheses and data collection/processing methods, to the conceptualisation and communication of results.This article draws on findings from cognitive science and system dynamics, with knowledge and experiences of field geology, to consider the limitations and biases presented by mental models in geoscience, and their effect on predictions of the physical properties of faults in particular.We highlight a number of biases specific to geological investigations and propose strategies for debiasing.Doing so will enhance how multiple data sources can be brought together, and minimise controllable geological uncertainty to develop more robust geological models.Critically, we argue that there is a need for standardised procedures that guard against biases, permitting data from multiple studies to be combined and communication of assumptions to be made.While we use faults to illustrate potential biases in mental models and the implications of these biases, our findings can be applied across the geoscience discipline.What do you think of when you think of a geologist?In a study of the representations of scientists in 222 Hollywood films, Weingart et al. (2003) found that scientists were predominantly white (96%), male (82%), American (49%), and middle aged (40% between 35 and 49 years old).They found interesting variations in the characters of scientists based on discipline.Medical researchers, physicists, chemists, and psychologists were most likely to be portrayed as 'mad scientists', whereas anthropologists, astronomers, zoologists, and geologists were more likely to be depicted as 'good' or 'benevolent'.Further, 'benevolent' scientists were often portrayed as naïve!The stereotypical portrayal of scientists in movies is an example of analogous thinking; that is, people's 'mental models', which are internal representations of something in the real world (Johnson-Laird 1983).Such analogous thinking helps people to interact with and make sense of a (complex) external reality, often by allowing them to solve problems or make judgments quickly and efficiently.However, mental models are developed from biased input information and are thus inherently limited.This can be both beneficial and problematic.Every model is a simplification of reality and therefore every model is wrong (Sterman 2002;Poeter 2007).Increasing the complexity of a mental model does not necessarily make the model more useful, however overly simplified models can omit key factors.For humans, models are the foundation of decision making, and so these models need to be useful -i.e. they must be a sufficient approximation to reality, striking a balance between simple and complex (Pidd 2009).Geological rock formations and the processes that happen to them are the result of complex dynamic systems that vary in space and time, and are formed over time frames that can range from tens of millions of years to essentially instantaneous events.Therefore, constructing a mental model of any geological process is challenging, particularly if we cannot observe that process in situ.This is due in part to difficulties traditionally encountered by individuals in trying to understand dynamic systems (Sterman 2008).It is compounded by the super-human timeframes separating geological processes of interest and human observations of them.Additionally, exposures are often limited to the near surface of the Earth and data often have to be extrapolated from a small sample.Geologists in the field are physically embedded within their research context, and as such geologists' perception and understanding are often tied in with sensorimotor experiences (Raab & Frodeman 2002;Petcovic & Libarkin 2007).Further, geologists must often combine multiple studies, with differing perspectives and approaches, to create a fuller picture of geological processes that can advance geological understanding and result in robust, unified models.To do so successfully, the thinking, methodology, and critically the assumptions underpinning each model must be explicated, and the input and output information organised in a way that allows for model interconnectivity (Loudon 2012).This process should include recognising and accounting for different biases in each approach, since these biases will introduce artificial variation into the studies.In this paper, we draw on cognitive science and system dynamics research, and reflect on research and experiences within field geology, to highlight common biases that geologists and geological data may be subjected to, and how this may influence geological models of fault systems.First, we review the literature regarding mental models which are typically understood as internal representations of external events.We then consider key systematic biases in geological thinking, how the resulting uncertainties may be processed, and the impact on model outcomes.We do not intend to test or validate the existence of these biases but rather, in the context of this special issue, we wish to explore biases that are relevant to the interpretation of geological data and therefore the development of models of the hydraulic and/or mechanical behaviour of fault zones.We close by recommending ways to manage these biases, and so to improve geological understanding and modelling of complex processes, such as fault seals.Faults and fault properties are an ideal topic to explore because faults are nearly ubiquitous in the Earth's upper crust, have numerous impacts on the formation and utilisation of natural resources and are important controls on a number of natural hazards, yet they are complex, their exposures are limited, and there is a myriad of different approaches taken for gathering data on faults to elucidate and quantify their physical properties.1 Assuming that a geologist represents a typical human. 2 Google Scholar search (excluding patents) using terms: "fault zone" + [term] + [type].Where term = architecture, properties, or mechanics; type = normal, strike slip, reverse, or thrust.