Cinner, Joshua E., Zamborain-Mason, Jessica, Maire, Eva, Hoey, Andrew S., Graham, Nicholas A.J., Mouillot, David, Villéger, Sébastien, Ferse, Sebastian and Lockie, Stewart (2022) Linking key human-environment theories to inform the sustainability of coral reefs. Current Biology . DOI

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Effective solutions to the ongoing “coral reef crisis” will remain limited until the underlying drivers of coral reef degradation are better understood. Here, we conduct a global-scale study of how four key metrics of ecosystem states and processes on coral reefs (top predator presence, reef fish biomass, trait diversity, and parrotfish scraping potential) are explained by 11 indicators based on key human-environment theories from the social sciences. Our global analysis of >1,500 reefs reveals three key findings. First, the proximity of the nearest market has the strongest and most consistent relationships with these ecosystem metrics. This finding is in keeping with a body of terrestrial research on how market accessibility shapes agricultural practices, but the integration of these concepts in marine systems is nascent. Second, our global study shows that resource conditions tend to display a n-shaped relationship with socioeconomic development. Specifically, the probabilities of encountering a top predator, fish biomass, and fish trait diversity were highest where human development was moderate but lower where development was either high or low. This finding contrasts with previous regional-scale research demonstrating an environmental Kuznets curve hypothesis (which predicts a U-shaped relationship between socioeconomic development and resource conditions). Third, together, our ecosystem metrics are best explained by the integration of different human-environment theories. Our best model includes the interactions between indicators from different theoretical perspectives, revealing how marine reserves can have different outcomes depending on how far they are from markets and human settlements, as well as the size of the surrounding human population.

Document Type: Article
Programme Area: PA1
Research affiliation: Science Management > Office for Knowledge Exchange
Affiliations > Not ZMT
Refereed: Yes
Open Access Journal?: No
DOI etc.:
ISSN: 09609822
Date Deposited: 20 May 2022 10:20
Last Modified: 20 May 2022 10:20

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