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Parsing human and biophysical drivers of coral reef regimes
Stockholm University, Faculty of Science, Stockholm Resilience Centre. Royal Swedish Academy of Science, Sweden.
Stockholm University, Faculty of Science, Stockholm Resilience Centre.
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Number of Authors: 182019 (English)In: Proceedings of the Royal Society of London. Biological Sciences, ISSN 0962-8452, E-ISSN 1471-2954, Vol. 286, no 1896, article id 20182544Article in journal (Refereed) Published
Abstract [en]

Coral reefs worldwide face unprecedented cumulative anthropogenic effects of interacting local human pressures, global climate change and distal social processes. Reefs are also bound by the natural biophysical environment within which they exist. In this context, a key challenge for effective management is understanding how anthropogenic and biophysical conditions interact to drive distinct coral reef configurations. Here, we use machine learning to conduct explanatory predictions on reef ecosystems defined by both fish and benthic communities. Drawing on the most spatially extensive dataset available across the Hawaiian archipelago-20 anthropogenic and biophysical predictors over 620 survey sites-we model the occurrence of four distinct reef regimes and provide a novel approach to quantify the relative influence of human and environmental variables in shaping reef ecosystems. Our findings highlight the nuances of what underpins different coral reef regimes, the overwhelming importance of biophysical predictors and how a reef's natural setting may either expand or narrow the opportunity space for management interventions. The methods developed through this study can help inform reef practitioners and hold promises for replication across a broad range of ecosystems.

Place, publisher, year, edition, pages
2019. Vol. 286, no 1896, article id 20182544
Keywords [en]
boosted regression trees, ecology, Hawai'i, interactions, management, regime shift
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:su:diva-169311DOI: 10.1098/rspb.2018.2544ISI: 000465431000015PubMedID: 30963937OAI: oai:DiVA.org:su-169311DiVA, id: diva2:1319392
Available from: 2019-05-31 Created: 2019-05-31 Last updated: 2019-05-31Bibliographically approved

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Jouffray, Jean-BaptisteNorström, Albert V.Graham, Nicholas A. J.Nyström, Magnus
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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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