Beauty and the reef: Evaluating the use of non-expert ratings for monitoring aesthetic values of coral reefs
Graphical abstract
Introduction
Aesthetic values are an important driver of tourist and recreational visitation to natural areas. Natural environments which facilitate recreation and leisure contribute to peoples' aesthetic, cultural heritage and identity values (Chan et al., 2012; Comberti et al., 2015; Gee and Burkhard, 2010; Jobstvogt et al., 2014), providing inspiration and opportunities for education, enjoyment, emotional and spiritual fulfillment (e.g. de Oliveira and Berkes, 2014; Fletcher et al., 2014; Hashimoto et al., 2014; Martínez-Pastur et al., 2015; Outeiro et al., 2015). Boyd and Banzhaf (2007) suggest that ‘amenity and fulfilment’ are examples of aesthetic benefits and ‘natural land cover in viewsheds’ is the ecosystem service providing the benefits. Aesthetic experience reflects some of the most intimate links people have with ecological phenomena (Gobster et al., 2007), and the impact of the experience can vary according to the scale at which the natural environment is organised and the scale of human perception (Smith et al., 1995; West et al., 2016, West et al., 2017).
An important component of many natural World Heritage properties is their aesthetic beauty. Criterion vii of the World Heritage Convention requires eligible properties to “contain superlative natural phenomena or areas of exceptional natural beauty and aesthetic importance” (UNESCO, 2019). Challenges associated with the assessment of this criterion, in particular, of ‘exceptional natural beauty and aesthetic importance’ have been acknowledged, and ongoing evaluation and reporting against the criterion by property managers remains inconsistent (Mitchell et al., 2013). Among the challenges identified by Mitchell et al. (2013) is the limited application of recognised methods for assessing aesthetic values in natural environments.
Several methods have been developed for assessing aesthetic values of natural areas, including quantitative and qualitative approaches (Haas et al., 2015; Okey, 2018; Tribot et al., 2018b; Vercelloni et al., 2018). Most have focused on visual aspects, with other sensory aspects of properties rarely considered, despite a broad consensus that the human aesthetic response to an environment is an holistic sensory experience (Context Pty Ltd, 2013; Liu et al., 2015). Indicators of aesthetic values have also been developed for a range of terrestrial environments including mountain landscapes, such as Mt. Everest (Beza, 2010), rural landscapes (Arriaza et al., 2004; Howley, 2011; Rosley et al., 2013), and grasslands (Lindemann-Matthies et al., 2010). Such landscape assessment methods typically focus on understanding experiential preferences, the physical attributes/attractiveness of a place (Casalegno et al., 2013; Tardieu and Tuffery, 2019), landscape preferences, (Atauri et al., 2000; de la Fuente de Val et al., 2006; de Lucio and Múgica, 1994; Huang, 2013; Múgica and de Lucio, 1996), scenic quality (Frank et al., 2013; Schirpke et al., 2013), and/or the experience of the place (Bratman et al., 2015; Hauru et al., 2014; Swaffield and McWilliams, 2013).
In the marine environment, and for coral reefs in particular, the assessment and monitoring of aesthetic values is a nascent but growing field of inquiry. Notable studies that have evaluated aesthetic values in the Great Barrier Reef (GBR) include those by Fenton et al. (1998) and Dinsdale and Fenton (2006), who utilised photos and tourist's reef experiences and evaluated their idealised expectations of a healthy coral reef. Recent research to assess aesthetic values of coral reefs have involved analyses of large sets of digital photographs to quantify and correlate attributes that contribute to perceived aesthetic values (e.g. Spalding et al., 2017). Studies by Tribot et al., 2019, Tribot et al., 2018a provide insights to aesthetic preferences for coral reef fish assemblages, observing significant relationships between aesthetic scores and some biodiversity facets (e.g. species' and functional richness). New approaches involving innovative technologies such as eye-tracking (Le et al., 2019; Scott et al., 2019) and artificial intelligence/machine learning algorithms have also been trialed on coral reef imagery (Becken et al., 2018; Haas et al., 2015), and present the opportunity to analyse large quantities of images across social media platforms (e.g. Figueroa-Alfaro and Tang, 2017).
For Australia's Great Barrier Reef World Heritage Area (GBRWHA), Lucas et al. (1997) and the IUCN (2012) mission report noted a need for further work to identify and document the attributes contributing to the aesthetic values of the property. In response to the recommendations of the 2012 IUCN monitoring mission (established under the auspices of the World Heritage Committee), Context Pty Ltd (2013) undertook a study to identify, define and assess the aesthetic values of the Great Barrier Reef (GBR) World Heritage Area in Australia in relation to the aesthetic component of Criterion vii. The researchers drew from a range of assessment methodologies based on existing heritage practice within Australia and internationally and found that the attributes underpinning the aesthetic values of the GBR include environmental characteristics identified under the other natural criteria for which the property was listed. Although they established a replicable methodology, they further identified a need to account for experiential characteristics in the assessment of aesthetic values. Due to the temporal and spatial variability, assessments at scales ranging from local sites to entire GBRWHA property make comparability across many places limited. Their operational definition for aesthetic values, derived from human aesthetic responses in a natural setting, states:
“… we will define aesthetic value or significance as the response (the aesthetic response) derived from the experience of an environment or parts of an environment. Human senses – sight, touch, smell, sound, movement – are important in how humans experience an environment. And culture, knowledge, expectations and experience mediate sensory perceptions. Aesthetic response can therefore be said to be linked to:
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the characteristics of an environment
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culturally or personally derived preferences.
Aesthetic value or aesthetic significance is therefore defined in this project as including sensory, experiential and emotional response to place.”
(Context Pty Ltd., 2013, p.33)
Although Context Pty Ltd (2013) established a replicable methodology for assessing GBRWHA aesthetic values, repeat assessments will depend on the availability of data and evidence at appropriate temporal and spatial scales. To date, World Heritage reporting on the state and trend of ‘aesthetic heritage values’ for the GBR has been inferred, based on the property's natural heritage values (Great Barrier Reef Marine Park Authority, 2019) and as yet there is no dedicated monitoring of aesthetic values.
Recent attempts have been made to evaluate an appropriate method to implement in a monitoring program to enable environmental managers to consider, assess and report on aesthetic condition and trend at varying scales. Marshall et al. (2019a) utilised non-expert ratings of coral reef imagery on a ten-point scale to indicate relative aesthetic value, establishing significant correlations with particular attributes present in coral reef scenes. They found that water clarity, fish abundance, and coral topography (i.e. the complexity of coral formations) were statistically reliable predictors of aesthetic response ratings. The Marshall et al. (2019a) study propounds the implementation of their non-expert rating method to enable scalable monitoring for informing management decisions (e.g. environmental assessments and permissions), as well as for benchmarking the recovery of impacted sites (i.e. for aesthetic values), including those undergoing coral restoration works. In our study, we examine the suitability (i.e. sensitivity of the measurement to detect change) and limitations (e.g. error and observer biases) of such ratings being used for monitoring and management decision making purposes and discuss implications.
The value in monitoring programs lies in their ability to record trends over time using reliable, consistent measures through the collection of data at regular intervals to enable measurements of changes (McIntosh et al., 2019). Other appealing features of methods which use non-expert rating scores of aesthetic beauty include simplicity and scalability, which ideally reflect environmental attributes associated with environmental health (Haas et al., 2015). Before any method can be implemented and used in a management context, managers need to understand its sensitivity, extrapolative power, and any potential inter-observer biases. Using the GBR as a case study and further analysing the data set collected by Marshall et al. (2019a), we evaluated: (a) the sensitivity of the visual, non-expert aesthetic rating scores used to compare underwater coral reef scenes, (b) the sample sizes needed to establish appropriate confidence levels in statistical comparisons between sites/scenes and over time, and (c) the potential observer biases that can be associated with demography and other social factors. Our study seeks to provide coral reef managers with information about the use and interpretation of such monitoring data, to inform potential guidelines for monitoring design, and to assist their assessments of the state and trends in GBR aesthetic values for coral reef habitats.
Section snippets
Dataset
The primary dataset analysed was the aesthetic rating scores collected and described by (Marshall et al., 2019a, Marshall et al., 2019b). This dataset contains 1417 individual aesthetic ratings of 181 underwater coral reef photographs, where each photo was rated on a ten-point Likert scale (ranging from 1 = “really, really ugly”, to 10 = “really, really beautiful”) by at least 381 respondents. Photos were rated via an online survey, delivered by a social research provider with the ability to
Assessing sensitivity
The mean aesthetic score (on a scale of 1 to 10) for the 181 photos was 6.86 and ranged between 4.35 and 8.34. The mode was 7.42. All 181 photos received ratings along the whole spectrum from 1 to 10; however, the 95% confidence intervals were approximately ±0.4 on the 1–10 scale, primarily due to each image being rated by at least 381 respondents (Fig. 1).
Sample size analysis
Results of the sample size analysis allowed us to determine the minimum sample size required to detect an effect of a given size with a
Discussion
For many natural World Heritage properties including the Great Barrier Reef (GBR), aesthetic values represent a vital part of their iconic status and international appeal (Curnock et al., 2019; Gurney et al., 2017). In an era of rapid environmental change and unprecedented threats to coral reefs globally (Heron et al., 2017) and the GBR specifically (Great Barrier Reef Marine Park Authority, 2019), it is increasingly important that reef managers have the best available information on the state
Conclusion
There are numerous potential management (and other) uses of aesthetic assessments and monitoring, each with information needs that are likely to vary (e.g. permit assessments, coral restoration benchmarking, and World Heritage reporting). The non-expert rating assessment method we have evaluated offers a useful monitoring tool for some of these purposes, with the statistical design requirements and limitations now better understood. As citizen science programs in the GBR have grown in recent
Funding and acknowledgements
This research was funded by CSIRO and the Australian Government's National Environmental Science Program (NESP), through the Tropical Water Quality Hub, under Project 5.6: “Designing an Aesthetics Long-term Monitoring Program (ALTMP)”. We thank Nadine Marshall (ex-CSIRO), Paul Marshall, Adam Smith and Nathan Cook of Reef Ecologic for their contributions to this project. LT and JC also thank Agence Nationale de la Recherche (ANR-14-CE03-0001-01) for financial support.
Credit authorship contribution statement
Petina L. Pert: Conceptualization, Writing - original draft, Writing - review & editing, Data curation, Formal analysis. Lauric Thiault: Methodology, Software, Visualization, Formal analysis, Writing - review and editing. Matthew I. Curnock: Conceptualization, Writing - review and editing, Project leadership. Susanne Becken: Writing - review & editing. Joachim Claudet: Methodology, Formal analysis, Writing - review & editing, Supervision.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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