Impaired recovery of the Great Barrier Reef under cumulative stress

Abstract

Corals of the Great Barrier Reef (GBR) have declined over the past 30 years. While reef state depends on the balance between disturbance and recovery, most studies have focused on the effects of disturbance on reef decline. We show that coral recovery rates across the GBR declined by an average of 84% between 1992 and 2010. Recovery was variable: Some key coral types had close to zero recovery by the end of that period, whereas some reefs exhibited high recovery. Our results indicate that coral recovery is sensitive to chronic but manageable pressures, and is suppressed for several years following acute disturbances. Loss of recovery capacity was partly explained by the cumulative effects of chronic pressures including water quality, warming, and sublethal effects of acute disturbances (cyclones, outbreaks of crown-of-thorns starfish, and coral bleaching). Modeled projections indicate that recovery rates can respond rapidly to reductions in acute and chronic stressors, a result that is consistent with fast recovery observed on some reefs in the central and southern GBR since the end of the study period. A combination of local management actions to reduce chronic disturbances and global action to limit the effect of climate change is urgently required to sustain GBR coral cover and diversity.

Fig. 1. A schematic to illustrate how recovery trajectories were defined for each of the six coral groups.

Points represent observed coral cover through time. Green points are samples within recovery periods, and blue points are observations outside of recovery periods. Recovery trajectories begin at either the beginning of the time series or after a significant break (decline). Recovery trajectories end with either an acute disturbance (COTS, cyclones, or thermal stress), a significant break, or the end of the time series. The IGR for each recovery trajectory is calculated. Note that not all significant breaks were explained by acute disturbances. The examples of coral cover trajectories for each coral type are shown in the Supplementary Materials. COTS, cyclone, and sun symbols are from T. Saxby (Integration and Application Network, University of Maryland Center for Environmental Science; http://ian.umces.edu/imagelibrary/). COTS, crown-of-thorns starfish.

Fig. 2. Temporal trends in the IGR of major coral taxa on the GBR.

Solid lines represent the mean, and blue areas indicate the SE. Dashed lines denote mean midpoints of the recovery trajectories. n values represent the number of trajectories before and after the mean trajectory midpoint. Note different scales on the y axes.

Fig. 3. Spatial distribution of change in reef recovery rates (IGR) for tabular corals of the genus Acropora.

We chose tabular Acropora here because it is the dominant coral group (by abundance and frequency) and alone represents 30% of mean total coral cover of the groups we include. In addition, it has the largest number of recovery trajectories. Colors represent change in IGR between the first half and second half of the data set. Recovery trajectories were divided between two time periods, so temporal differences could be calculated: The earlier half included 131 recovery trajectories that all ended by 2003 with a mean trajectory midpoint of year 1995; the latter half included 132 trajectories that all ended after 2005 with a mean midpoint of 2007. Temporal change in IGR was calculated per reef [(later − earlier)/earlier] using mean IGR for cases where a reef had multiple trajectories per time period. In the cases where a reef did not have a value for the before or after period, inverse distance weighted interpolation was used to obtain the corresponding value. An autocorrelation analysis that evaluates the appropriateness of the interpolation is shown in the Supplementary Materials.

Fig. 4. Predicted sensitivity of recovery rate (IGR) to reduced coral recruitment and net growth.

(A) tabular acroporids and (B) massive corals. IGR values (y axis) were calculated based on results of simulations using specific values of somatic growth and recruitment (x axis).

Fig. 5. Projected recovery after the study period under different disturbance scenarios.

We use here Penrith Reef (a mid-shelf reef in the southern GBR) as example (see fig. S2 for examples from other reefs). Lines show the projected coral cover at the reef based on the IGR predicted from the statistical model. Shaded ribbons shows variability when the parameters are varied by 5%.