An integrated approach to estimate aesthetic and ecological values of coralligenous reefs

Abstract

Assessing non-material nature contributions to people has become one major challenge in biodiversity sciences. Among them, the aesthetic value of biodiversity is of strong importance as it contributes to human well-being and increases the collective willingness to engage in conservation efforts. Using the endangered coralligenous reefs along the French Mediterranean coastline as a case study, we propose a quantitative approach to estimate the aesthetic and ecological values of a marine ecosystem. We combined human image evaluation and deep learning algorithms to provide a quantitative estimation of the aesthetic value of 7692 photographic quadrats among 160 stations located between 20 and 90 m depth and gathered on 95 sites. To understand how aesthetic value is related to biodiversity metrics, environmental variables and anthropogenic pressures we used a structural equation modelling approach. We found that taxonomic diversity and species composition explained a significant part of the aesthetic value of the coralligenous reefs. Taxonomic diversity showed a net positive effect and species composition analysis highlighted both positive and negative effects of some species on the aesthetic value. Net negative effects of functional and phylogenetic diversities were found, which illustrates an aesthetic bias in human perception of ecological value. The aesthetic and ecological values were mapped along the French Mediterranean coastline in three dimensions (longitude, latitude, depth); this synthetic visualization could be of strong interest for conservation and communication purposes about this endangered benthic key-ecosystem of the Mediterranean Sea. Overall, our approach provides a geographically scalable estimate of the aesthetic value of biodiversity which is still an underestimated facet of nature contributions to people. It could be transposed to other marine ecosystems such as coral reefs but also to terrestrial landscapes for which an increasing number of images evaluated for human preference are becoming available.

Keywords

• Aesthetic perception
• Coralligenous reefs
• Ecological value
• Deep learning
• Nature contribution to people