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Ecosystem restructuring along the Great Barrier Reef following mass coral bleaching

Naturevolume 560pages9296 (2018) | Download Citation

Abstract

Global warming is markedly changing diverse coral reef ecosystems through an increasing frequency and magnitude of mass bleaching events1,2,3. How local impacts scale up across affected regions depends on numerous factors, including patchiness in coral mortality, metabolic effects of extreme temperatures on populations of reef-dwelling species4 and interactions between taxa. Here we use data from before and after the 2016 mass bleaching event to evaluate ecological changes in corals, algae, fishes and mobile invertebrates at 186 sites along the full latitudinal span of the Great Barrier Reef and western Coral Sea. One year after the bleaching event, reductions in live coral cover of up to 51% were observed on surveyed reefs that experienced extreme temperatures; however, regional patterns of coral mortality were patchy. Consistent declines in coral-feeding fishes were evident at the most heavily affected reefs, whereas few other short-term responses of reef fishes and invertebrates could be attributed directly to changes in coral cover. Nevertheless, substantial region-wide ecological changes occurred that were mostly independent of coral loss, and instead appeared to be linked directly to sea temperatures. Community-wide trophic restructuring was evident, with weakening of strong pre-existing latitudinal gradients in the diversity of fishes, invertebrates and their functional groups. In particular, fishes that scrape algae from reef surfaces, which are considered to be important for recovery after bleaching2, declined on northern reefs, whereas other herbivorous groups increased on southern reefs. The full impact of the 2016 bleaching event may not be realized until dead corals erode during the next decade5,6. However, our short-term observations suggest that the recovery processes, and the ultimate scale of impact, are affected by functional changes in communities, which in turn depend on the thermal affinities of local reef-associated fauna. Such changes will vary geographically, and may be particularly acute at locations where many fishes and invertebrates are close to their thermal distribution limits7.

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Acknowledgements

We thank the Reef Life Survey (RLS) divers and boat skippers who assisted with field surveys, including D. and J. Shields, I. Donaldson and S. Griffiths, and A. Cooper, J. Berkhout and E. Clausius at the University of Tasmania for logistics and data management; J. Stuart-Smith, S. Baker, A. Bates and N. Barrett for further support in the development of RLS, fieldwork and concepts explored in the paper. Development of RLS was supported by the former Commonwealth Environment Research Facilities Program, and analyses were supported by the Marine Biodiversity Hub, a collaborative partnership supported through the Australian Government’s National Environmental Science Programme (NESP), and by the Australian Research Council. Funding and support for the GBR and Coral Sea RLS field surveys was provided by The Ian Potter Foundation and Parks Australia. Permits were provided by Parks Australia and the Great Barrier Reef Marine Park Authority. C.J.B. was supported by a Discovery Early Career Researcher Award (DE160101207) from the Australian Research Council.

Reviewer information

Nature thanks J. Bruno, R. Ferrari and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Affiliations

  1. Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia

    • Rick D. Stuart-Smith
    •  & Graham J. Edgar
  2. Australian Rivers Institute, Griffith University, Nathan, Queensland, Australia

    • Christopher J. Brown
  3. ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland, Australia

    • Daniela M. Ceccarelli

Authors

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  2. Search for Christopher J. Brown in:

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Contributions

G.J.E. and R.D.S.-S. collected the data with the assistance of other Reef Life Survey divers; C.J.B. undertook the data analysis and preparation of figures with assistance from R.D.S.-S.; D.M.C. analysed the photoquadrats for benthic cover data; R.D.S.-S. drafted the paper with input from all other authors.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Rick D. Stuart-Smith.

Extended data figures and tables

  1. Extended Data Fig. 1 Results of GLMMs for changes in coral and algal cover during the 2016 bleaching event.

    a, Changes in coral cover. b, Changes in algal cover. Change in cover is modelled as a function of the influences of starting cover (of corals and algae, respectively), wave exposure, thermal anomaly (DHD), the interaction between DHD and starting cover, depth category (depths between 4 and 10 m and >10 m modelled in comparison to <4-m depth), and the interaction between depth category and DHD (n = 211 site–depth combinations). All continuous predictors were normalized to mean = 0 and s.d. = 1 for comparative purposes.

  2. Extended Data Fig. 2 Changes in algal and coral cover spanning the 2016 bleaching event.

    a, Coral- and algal-cover change were negatively correlated (ρ = −0.56). b, The greatest algal-cover increases occurred at sites with the lowest coral cover after the bleaching event (ρ = −0.28). n = 211 site–depth combinations.

  3. Extended Data Fig. 3 Ecological changes on surveyed reefs most clearly affected by coral bleaching (red) versus un-impacted reefs (blue).

    Reefs categorized as bleached were those with >20% pre-bleaching live coral cover, that experienced >40 DHD and that lost >40% of pre-bleaching coral cover (see Methods for rationale). The un-impacted reefs were those that had >20% pre-bleaching live coral cover and experienced >40 DHD, but did not show a reduction in coral cover. The vertical axis is the percentage change of each metric across the reefs in each category (n = 6 bleached, n = 5 unbleached reefs), and horizontal lines on box plots show median, first and third quartiles, with the range indicated by the error bars. Crosses indicate means and circles indicate individual reefs within quartiles. Values for corallivores, browsing herbivores and scraping herbivores describe change in densities of species in these groups. Densities and species richness are means per 500 m2 (fishes) or 100 m2 (invertebrates). Bleached and unbleached reefs each include reefs from both northern and southern regions. Only coral cover differed noticably between these two groups of reefs (mean difference = −72%, with 95% credible intervals of 25–107%), although there was a small decline in corallivore densities post-bleaching (mean difference = 42% with 95% credible intervals from −0.24 to 78.0).

  4. Extended Data Fig. 4 Effect sizes from GLMMs of regional change for each ecological metric.

    Median additive effects of each covariate on the linear expectation for each metric (with 95% credible intervals as error bars) (n = 233 site-by-depth-category combinations). Effect sizes are on a log scale for all metrics, except for sea urchin presence, which gives the effect on the log-odds of presence versus absence. The influences of latitude, and its change from before to after the bleaching event (the interaction between latitude and bleaching (Latitude * bleaching)), are modelled in relation to differences between the GBR and Coral Sea reefs (GBR), wave exposure (Exposure), depth of the survey (depths between 4 and 10 m and >10 m modelled in comparison to <4-m depth), the percentage cover of live hard corals in the survey (Coral cover) and before versus after the bleaching event (After bleaching). Effects for which credible intervals do not overlap zero are indicated with black, rather than grey, points and error bars.

  5. Extended Data Fig. 5 Non-metric multidimensional scaling plots for reef fish and mobile invertebrate communities along the GBR and Coral Sea.

    Fish biomass data (top) and invertebrate abundance data (bottom) were averaged across surveys within 2° latitudinal bands, with number labels representing the northern latitude (that is, 21 represents the 2° band from 21° to 23° south). Coral Sea reefs are distinguished from those in the GBR by a ‘C’ in the label. Symbols have been colour-coded for data collected before and after the bleaching event (n = 13 latitudinal bands each before and after).

  6. Extended Data Fig. 6 Changes in the trophic structure of reef fishes following the 2016 mass bleaching event on the GBR and Coral Sea.

    Bars represent the proportion of total biomass made up by each trophic group, averaged across surveys on each reef, and reefs ordered by latitude. Cleaners and algal farmers were removed owing to their small contributions to biomass.

  7. Extended Data Fig. 7 Local species richness of juvenile fishes (per 500 m2) before and after the 2016 mass bleaching event on the GBR and Coral Sea.

    Species richness is shown before (blue) and after (red) the 2016 mass bleaching event on the GBR (left) and Coral Sea (right). ‘North’ reefs were north of 12° S (n = 10 reefs), and ‘south’ reefs were south of 19° S (n = 19 reefs). Juveniles were classified as any individuals 10 cm or less, for species that exceed 12.5 cm in maximum size. A Bayesian linear model indicated juvenile richness differed between the GBR and Coral Sea, but not between north and south or before and after the bleaching event (mean difference = 1.70 with lower and upper 95% credible intervals of −0.6 to 4.0). The distribution of raw data is shown in box plots, with crosses indicating means and circles indicate individual reefs within quartiles.

  8. Extended Data Fig. 8 The distribution of sampling effort through space and time.

    The temporal gap between pre- and post-bleaching surveys (n = 768 surveys total) between GBR and Coral Sea, along the latitudinal gradient, and locations experiencing different heating anomalies. For the box plot, the box shows the interquartile range and whiskers are 1.5× interquartile range.

  9. Extended Data Table 1 Categories of coral and algal cover scored from photoquadrats

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https://doi.org/10.1038/s41586-018-0359-9

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