This dataset shows larval connectivities between reefs that exceeded, and did not exceed, thermal thresholds for damage
during the 2016/2017 Great Barrier Reef bleaching events. The loss of reproductive adult colonies during bleaching events
has the implication that coral cover recovery will require the supply of coral larvae from external sources (other reefs).
Two heat-exposure analyses were performed using the two DHW thresholds of 6 DWH and 3DWH, which have been established to
indicate the threshold that causes major loss of coral cover(6 DHW), and loss of the most heat sensitive coral species (3
DHW). The cumulative intensity of thermal stress is expressed as DHW in units of °C-weeks, which accumulates any thermal
anomalies > 1°C above the maximum monthly mean at a location over a 12-week window.
The first was an analysis to identify important source reefs for overall coral community recovery. For this analysis, all
reefs on the GBR with exposure that was above 6 DHW for ?25% of their surface area were considered to have been sufficiently
damaged by bleaching to require external larval supply for recovery (calculated from indicative reef boundaries as defined
in GBRMPA zoning plan (GBRMPA, 2004)). Any reefs in this group were immediately ruled out as being a potential source reef.
The second analysis identified source reefs important for recovery of the most heat-sensitive coral species. For this analysis,
all reefs on the GBR with exposure that was above 3 DHW for ?25% of their surface area were considered to have been sufficiently
damaged by bleaching to require external larval supply for recovery, and any reefs in this group were immediately ruled
out as being a potential source reef.
For both heat-exposure analyses, we used DHW measurements derived from satellite measured daily sea-surface temperature
layers at 5 x 5 km resolution for the years 2016 and 2017, provided by NOAA Coral Reef Watch v3.
Connectivity patterns over seven years for which the oceanographic patterns were available (summers of 2008-09, 2010-11,
2011-12, 2012-13, 2014-15, 2015-16, 2016-17) were used to estimate the connectivity relationships among the reefs. The
larval dispersal simulations used Connie2 dispersal tool (Condie, Hepburn, & Mansbridge, 2012), which uses eReefs hydrodynamics
to displace simulated larval particles. In general, the simulations followed protocols previously published by Hock et al.
In the current batch of simulations, key components of larval dispersal such as spawning times and pelagic larval duration
were designed so as to match dispersal of broadcast spawning Acropora (Hock et al. in prep., life history parameters based
on Connolly and Baird (2010)). The resulting connectivity matrices were added to obtain a single matrix representing the
cumulative supply potential over the modelled spawning seasons. The reefs have then been divided into two sets, the first
set consisting of those reefs that exceeded the respective thermal stress threshold in 2016 and/or 2017, and the second
set consisting of those that did not exceed the threshold. The resulting connectivity matrices were then used to identify
reefs that both had the largest potential to supply larvae to each reef that exceeded the thermal stress threshold (i.e.,
they were important sources to damaged reefs) and at the same time also did not exceed the thermal stress threshold (i.e.,
their breeding stocks avoided bleaching damage caused by heat exposure above the threshold).
Limitations of the Data:
The Coral Reef Watch SST data layer has a resolution of 5 km2 , which is larger than many reefs on the GBR. Higher-resolution
products, such as ReefTemp Next Generation, a high resolution (approximately 2 km2 ) daily product developed by the Australian
Government's Bureau of Meteorology and used in Hock et al. (2017), could be better suited to reveal locations of potential
thermal stress refugia. Moreover, field observations have shown that the relationship between thermal stress and subsequent
mortality tends to be imperfect, as some reefs exhibited low mortality even in conditions of high thermal stress (Hughes
et al., 2018). Such reefs may therefore serve as important larval sources, but cannot be identified by only taking into
account SST anomalies, as was the case here. Such reefs may harbour thermally resistant corals, and/or may have had environmental
cues such as pulses of warm water early in the season that prepared them to better cope with subsequent levels of thermal
stress (Ainsworth et al., 2016).
Shapefile of important source reefs and thermally damaged reefs at 3 DHW and 6 DHW, openable in the GIS program ArcMap
(Esri) or other GIS software. This is the current file of GBR reef outlines (publicly available through GBMRPA), with each
reef annotated with the following categories (in the columns named DHW6 and DHW3 of the attribute table).
Numerical categories in DHW6 and DHW3 columns of the attribute table of the “Key_Source_Reefs_2016-17” Shapefile.
Category 2 - Reef did not experience DHW above threshold (3 or 6) in 2016 and/or 2017, and is the best source to at least
one of the reefs that experienced DHW over that same threshold
Category 1 - Reef experienced DHW above threshold (3 or 6) in 2016 and/or 2017
Category 0 - Reef did not experience DHW above threshold (3 or 6) in 2016 and/or 2017, but is not the best source to any
of the reefs that did
Category -1 - Reef not represented in connectivity models (usually small reefs close to the shore)
Category -2 - Feature not relevant to connectivity models (cay, rock, island or mainland
Ainsworth, T. D., Heron, S. F., Ortiz, J. C., Mumby, P. J., Grech, A., Ogawa, D., . . . Leggat, W. (2016). Climate change
disables coral bleaching protection on the Great Barrier Reef. Science, 352(6283), 338-342
Hock, K., Wolff, N. H., Ortiz, J. C., Condie, S. A., Anthony, K. R. N., Blackwell, P. G., & Mumby, P. J. (2017). Connectivity
and systemic resilience of the Great Barrier Reef. PLOS Biology, 15(11), e2003355. doi:10.1371/journal.pbio.2003355
Hughes, T. P., Kerry, J. T., Baird, A. H., Connolly, S. R., Dietzel, A., Eakin, C. M., . . . Torda, G. (2018). Global warming
transforms coral reef assemblages. Nature, 556(7702), 492- 496. doi:10.1038/s41586-018-0041-2
Connolly, S. R., & Baird, A. H. (2010). Estimating dispersal potential for marine larvae: dynamic models applied to scleractinian
corals. Ecology, 91(12), 3572-3583.
This dataset is filed in the eAtlas enduring data repository at: data\NESP2\4.5-Guidance-system-resilience-based-mgt