TY - JOUR

T1 - Parsing human and biophysical drivers of coral reef regimes

AU - Jouffray, Jean-Baptiste

AU - Wedding, Lisa

AU - Norstrom, Albert V.

AU - Donovan, Mary

AU - Williams, Gareth

AU - Crowder, Larry

AU - Erickson, Ashley

AU - Friedlander, Alan M.

AU - Graham, Nicholas A.J.

AU - Gove, Jamison M.

AU - Kappel, Carrie

AU - Kittinger, John

AU - Lecky, Joey

AU - Oleson, Kirsten

AU - Selkoe, Kimberly

AU - White, Crow

AU - Williams, Ivor

AU - Nystrom, Magnus

N1 - Mistra supported this research through a core grant to the Stockholm Resilience Centre. J.-B.J. was supported by the Erling-Persson Foundation and the Swedish Research Council Formas (project no. 2015-743). The study was part of the Ocean Tipping Points project, funded by the Gordon and Betty Moore Foundation (grant no. 2897.01) and the NOAA Coral Reef Conservation Program (grant no. NA14NOS4820098).

PY - 2019/2

Y1 - 2019/2

N2 - 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.

AB - 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.

KW - Hawai'i

KW - boosted regression trees

KW - ecology

KW - interactions

KW - management

KW - regime shift

U2 - 10.1098/rspb.2018.2544

DO - 10.1098/rspb.2018.2544

M3 - Article

VL - 286

JO - Proceedings of the Royal Society B: Biological Sciences

JF - Proceedings of the Royal Society B: Biological Sciences

SN - 0962-8452

IS - 1896

M1 - 20182544

ER -