Parsing human and biophysical drivers of coral reef regimes

Jouffray, Jean Baptiste, Wedding, Lisa M., Norström, Albert V., Donovan, Mary K., Williams, Gareth J., Crowder, Larry B., Erickson, Ashley L., Friedlander, Alan M., Graham, Nicholas A.J., Gove, Jamison M., Kappel, Carrie V., Kittinger, John N., Lecky, Joey, Oleson, Kirsten L.L., Selkoe, Kimberly A., White, Crow, Williams, Ivor D., and Nyström, Magnus (2019) Parsing human and biophysical drivers of coral reef regimes. Proceedings of the Royal Society of London Series B, Biological Sciences, 286 (1896). 20182544.

[img]
Preview
PDF (Published Version) - Published Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview
View at Publisher Website: https://doi.org/10.1098/rspb.2018.2544
 
8
29


Abstract

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.

Item ID: 59305
Item Type: Article (Research - C1)
ISSN: 1471-2954
Keywords: Boosted regression trees, Ecology, Hawai'i, Interactions, Management, Regime shift
Copyright Information: (C) 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
Funders: Mistra, Erling-Persson Foundation, Swedish Research Council FORMAS, Gordon and Betty Moore Foundation (GBMF), NOAA Coral Reef Conservation Program
Projects and Grants: FORMAS project no. 2015-743, GBMF grant no. 2897.01, NOAA grant no. NA14NOS4820098
Date Deposited: 20 Apr 2020 02:01
FoR Codes: 05 ENVIRONMENTAL SCIENCES > 0501 Ecological Applications > 050101 Ecological Impacts of Climate Change @ 100%
SEO Codes: 96 ENVIRONMENT > 9605 Ecosystem Assessment and Management > 960503 Ecosystem Assessment and Management of Coastal and Estuarine Environments @ 100%
Downloads: Total: 29
Last 12 Months: 16
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page