DOI: 10.5061/dryad.jsxksn0k6
title: Data from: Regional-scale disturbances drive long-term decline of inshore coral reef fish assemblages in the Great Barrier Reef Marine Park

description: Anthropogenic pressure is increasing the variety and frequency of
 environmental disturbance events, limiting recovery and leading to
 long-term declines in wild plant and animal populations. Coral reefs and
 associated fish assemblages are inherently dynamic due to their
 susceptibility to a host of disturbances, but regional-scale nuances in
 the drivers of long-term change frequently remain poorly resolved. Here,
 we examine the effects of multiple potential drivers of change in coral
 reef fish assemblages across 4 inshore regions of the Great Barrier Reef
 Marine Park (GBRMP), Australia, over 12-14 years (2007-2021). Each region
 had a unique disturbance history, in conjunction with and long-term
 changes in physical habitat variables. Phases of recovery were apparent in
 the years between disturbance events at all locations, but these were not
 long enough to prevent substantial declines in reef fish density (by
 33-72%) and species richness (by 41-75%) throughout the study period. The
 main drivers of change in fish assemblages varied among regions, however
 the most rapid changes followed cyclone and flood events. Limited recovery
 periods resulted in temporal shifts in fish species composition from
 typically coral-associated to algae-associated. Most trophic groups
 declined in density except farmers, grazers, omnivores, and parrotfish.
 No-take marine reserves (NTMRs) had small and inconsistent effects on
 total fish assemblages, but delivered benefits for fishery-targeted
 piscivores. Our findings suggest that coral reef responses to local
 stressors and cumulative escalating climate change impacts are highly
 variable at regional scales., and that small NTMRs are unlikely to
 mitigate the impacts of increasingly frequent and climatic disturbances.
 Nearshore coral reefs worldwide are high-value habitats that are either
 already degraded or vulnerable to degradation and the loss of important
 fish groups. Global efforts to reduce greenhouse gas emissions must be
 coupled with effective local management that can support the functioning
 and adaptive capacity of coral reefs.
description: The data were collected at four inshore island locations of the
 Great Barrier Reef, located 10 - 30 km from the mainland coast and
 spanning 4.5 degrees of latitude, from 18.603S to 23.19S. Standardised
 underwater visual census protocols were used to survey benthic and fish
 assemblages at long-term monitoring sites on fringing reefs of the Palm
 Islands (30 sites), Magnetic Island (8 sites), Whitsunday Islands (42
 sites) and Keppel Islands (20 sites) (Figure 1) between 4 and 8 times
 during the period 2007 - 2021. The Palm and Whitsunday Islands were
 surveyed in 2007, 2008, 2009, 2012, 2014, 2016, and 2018, with an
 additional survey in 2017 at the Whitsunday Islands, the Keppel Islands
 were surveyed in 2007, 2008, 2009, 2011, 2013, 2015, 2017 and 2021, and
 Magnetic Island reefs were surveyed just 4 times due to weather
 constraints, in 2007, 2012, 2016 and 2019 (Table S1). Within each island
 group, monitoring sites were evenly distributed among reefs that are open
 to fishing (General Use and Conservation Park Zones) and no-take marine
 reserves (NTMRs) that were closed to fishing in either 1987 or
 2004. At each of the 100 sites, five 50 m transects
 were deployed on the reef slope along a single depth contour between 4 m
 and 12 m, depending on the reef slope depth and topography at each site.
 Fish and benthic surveys were conducted by trained and experienced
 observers on SCUBA, and all species of diurnal, non-cryptic reef fish were
 recorded. Large-bodied, mobile fishes were surveyed using a transect width
 of 6 m (i.e. 300 m<sup>2</sup> survey area) by two divers
 swimming side by side, with a third diver laying out the transect tape
 behind them. Small-bodied fishes (Pomacentrids and small Labrids) were
 surveyed by one diver during the return swim along each transect, using a
 transect width of 2 m (i.e. 100 m<sup>2</sup> survey area).
 The same three observers conducted all fish surveys throughout the
 monitoring period (DHW, DMC, RDE). All recorded fish species were assigned
 to trophic groups, and counts were converted to density (individuals per
 1000 m2) for all analyses except the Generalized Linear Mixed Model, where
 individuals per 300 m<sup>2</sup> was used to satisfy the
 requirement of integers for the preferred negative binomial
 distribution. Benthic communities were surveyed using a
 standard point-intercept survey method by one diver during the return swim
 along each transect. A single benthic point sample was recorded at every 1
 m graduation mark along each transect tape (i.e. 50 samples per transect).
 Benthic biota and substrata were classified into the following categories:
 live and dead hard coral with further subdivision into morphological
 categories (branching, tabular, digitate, solitary, massive, foliose,
 encrusting), soft coral, sponge, clams (<em>Tridacna</em>
 spp.), other invertebrates (such as ascidians and anemones), macro-algae,
 coral reef pavement (covered in turf algae), rock, rubble and sand.
 Additionally, for the live hard coral categories (branching, tabular, and
 digitate), each colony was further classified as either
 <em>Acropora</em> or ‘other’. The structural complexity of the
 reef habitat at each site was estimated using a simple method that gave a
 rank (1-5) to both the angle of the reef slope and the rugosity of the
 benthos for each ten-meter section of each transect. We
 generated quantitative estimates of relative wave exposure at each
 monitoring site during each relevant cyclone. We used modelled wave height
 and direction data from NOAA WAVEWATCH III and the Commonwealth Scientific
 and Industrial Research Organisation (CSIRO) to identify which cyclones
 generated significant wave heights (Hs = average of top 1/3 of wave
 heights) of 3.5 m or more at each monitoring site. For each cyclone at
 each site, the distance to the nearest wave blocking obstacle was measured
 every 7.5 degrees around each site (fetch). These measures were weighted
 by the relative frequency at which cyclone-generated waves approached the
 site and their average magnitude. These distances were then summed and
 normalised to create a dimensionless index of relative cyclone wave
 exposure, as per previous studies. Daily Moderate
 Resolution Imaging Spectroradiometer (MODIS) Level-0 data were acquired
 from the NASA Ocean Colour website (http://oceancolour.gsfc.nasa.gov) and
 converted into RGB colour images with a spatial resolution of 500 ×500 m
 using the SeaWiFS Data Analysis System (SeaDAS). The images were then (i)
 spectrally enhanced to transform them from RGB to the
 Hue-Saturation-Intensity (HSI) colour system and (ii) classified into
 three distinct water colour categories corresponding to the three optical
 water types (primary, secondary, and tertiary) commonly found in the GBR
 during the austral wet season. We used the primary
 water type characterization to quantify frequency of exposure of the
 monitoring sites to highly turbid water from flood plumes and subsequent
 sediment re-suspension during the 2003-2017 Queensland summer wet seasons
 (December-April inclusive). The primary water type represents high
 turbidity, and high values of coloured dissolved organic matter (CDOM) and
 Total Suspended Sediment (TSS). TSS and Secchi Disc Depth (SDD) in the
 primary water type are typically around 18.3 ± 45.7 mg L-1  and 1.8 ± 1.8
 m (mean ± 1SD), respectively. The primary water type is often associated
 with low salinity from flood plumes, but not always, as high turbidity can
 also reflect re-suspended sediment from wind and tides. We created
 twenty-two weekly composite images of daily images from December 1st to
 April 30th per wet season, to minimize the amount of area without data per
 image due to masking of clouds and sun glint. We assigned each weekly
 composite a presence/absence (0/1) value of primary water type in each
 pixel (500 × 500 m resolution). Two measures of water
 quality were used: remotely sensed Chlorophyll-a, which provides an
 estimate of phytoplankton biomass and can act as a proxy for seawater
 nutrient concentrations, and Diffuse Kd490 (the Diffuse Attenuation
 Coefficient at 490 nm), which provides an estimate of turbidity.
 Chlorophyll-a and Kd490 composite monthly 4km data, collected using a
 Moderate Resolution Imaging Spectroradiometer (MODIS) satellite, from
 2003-2017 were downloaded from the ERDDAP website. (Chlorophyll-a -
 https://coastwatch.pfeg.noaa.gov/erddap/griddap/erdMH1chlamday; Kd490 -
 https://coastwatch.pfeg.noaa.gov/erddap/griddap/erdMH1kd490mday).
 <em>In-situ</em> measurements of these variables are preferred
 as there is increased uncertainty in turbid waters, however in their
 absence, remotely sensed measurements can and have been used in a number
 of other studies. The Whitsunday Islands data for both Chlorophyll-a and
 Kd490 were anomalous, so they were excluded from the Whitsundays boosted
 regression tree analyses. Degree Heating Weeks (DHW)
 values represent the accumulated thermal stress over the previous 12 weeks
 at a given pixel. DHW is calculated as the number of degrees above the
 coral bleaching threshold multiplied by the number of weeks that the
 elevated temperature persists. Coral bleaching is likely at 4 DHW, and
 this is routinely used to estimate thermal stress on coral reefs. Daily
 5km data from 1998 to 2016 were provided by NOAA Coral Reef Watch (2018).
 The Maximum DHW reported between sequential surveys was used for each
 year, however if the period between surveys exceeded one year, the maximum
 DHW within the two previous years was used in the following year of the
 study. Annual average SST and SST anomalies were
 calculated from multi-scale, ultra-high resolution (MUR), SST, and sea
 surface temperature anomaly (SSTA) data. Monthly 1km data from 2002-2017
 were downloaded from the NOAA ERDDAP website
 (https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41mday.html and
 https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41anommday.html). The data were analysed with generalised linear mixed models, non-metric multidimensional scalin,g and boosted regression trees.
description: # **Data from: Regional-scale disturbances drive long-term decline of
 inshore coral reef fish assemblages in the Great Barrier Reef Marine
 Park**
 [https://doi.org/10.5061/dryad.jsxksn0k6](https://doi.org/10.5061/dryad.jsxksn0k6) **Description of the data and file structure** `Ceccarelli_et_al_site_coordinates.csv`: coordinates of sites `Selected_fish_benthic_physical_sitelevel_2021.csv`: These data are at the level of sites, situated at various locations around the island groups (region). Five transects were used to collect data at each site. Variables from “lut.arge” to “Labrichthys” are fish species, and values in the cells are mean density per 1000m2. | **Variable label** | **Description** | | :-------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | YEAR | Year of survey (range: 2007-2021) | | REGION | Island group: Palm Islands, Magnetic Island, Whitsunday Islands, Keppel Islands | | EXPOSURE | Categorical exposure to prevailing southeasterly trade winds. | | NTR | No-take reserve status, Fished, NTR declared in 1987, NTR declared in 2004. Later renamed NTMR for plotting | | NTR Pooled | Pooled NTR status: Fished, NTR. Later renamed NTMR for plotting | | SITE | Locations around the island groups that were repeatedly surveyed using UVC methods. Site coordinates provided in “Ceccarelli et al site coordinates.csv” | | lut.arge | Lutjanus argentimaculatus | | lut.carp | Lutjanus carponotatus | | lut.flma | Lutjanus fulviflamma | | lut.fulv | Lutjanus fulvus | | lut.kas | Lutjanus Kasmira | | lut.lemn | Lutjanus lemniscatus | | lut.lutj | Lutjanus Lutjanus | | lut.mono | Lutjanus monostigma | | lut.quin | Lutjanus quinquelineatus | | lut.rivu | Lutjanus rivulatus | | lut.russ | Lutjanus russellii | | lut.seba | Lutjanus sebae | | lut.vitt | Lutjanus vitta | | mac.macu | Macolor macularis | | pagrus | Pagrus spp. | | sym.nema | Symphorus nematophorus | | par.barb | Parupeneus barberinus | | par.boides | Parupeneus barberinoides | | par.bifa | Parupeneus bifasciatum | | par.indi | Parupeneus indicus | | par.multi | Parupeneus multifasciatus | | par.cili | Parupeneus ciliates | | upe.trag | Upeneus tragula | | platax | Platax spp. | | Platycephalus spp. | Platycephalus spp. | | let.atki | Lethrinus atkinsoni | | let.hara | Lethrinus harak | | let.lati | Lethrinus laticaudis | | let.lent | Lethrinus lentjan | | let.mini | Lethrinus miniatus | | let.nebu | Lethrinus nebulosus | | let.oliv | Lethrinus olivaceus | | let.obso | Lethrinus obsoletus | | let.orna | Lethrinus ornatus | | gym.spp | Gymnocranius spp. | | mon.gran | Monotaxis grandoculis | | sco.bili | Scolopsis bilineata | | sco.marg | Scolopsis margaritifer | | sco.mono | Scolopsis monogramma | | sco.line | Scolopsis lineata | | any.leuc | Anyperodon leucogrammicus | | ath.roga | Aethaloperca rogaa | | cep.argu | Cephalopholis argus | | cep.boen | Cephalopholis boenak | | cep.cyan | Cephalopholis cynaostigma | | cep.micr | Cephalopholis microprion | | cro.alti | Cromileptes altivelis | | epi.caer | Epinephelus caeruleopunctatus | | epi.coio | Epinephelus coioides | | epi.cora | Epinephelus corallicola | | epi.fasc | Epinephelus fasciatus | | epi.fusc | Epinephelus fuscoguttatus | | epi.howl | Epinephelus howlandensis | | epi.lanc | Epinephelus lanceolatus | | epi.hexa | Epinephelus hexagonatus | | epi.merr | Epinephelus merra | | epi.ongu | Epinephelus ongus | | epi.quoy | Epinephelus quoyanus | | epi.sexf | Epinephelus sexfasciatus | | pms.laev | Plectropomus laevis | | pms.leop | Plectropomus leopardus | | pms.macu | Plectropomus maculatus | | pte.ante | Pterois antennata | | pte.voli | Pterois volitans | | dip.bifa | Diploprion bifasciatum | | dia.pict | Diagramma pictum | | ple.chae | Plectorhinchus chaetodonoides | | ple.flav | Plectorhinchus flavomaculatus | | ple.gibb | Plectorhinchus gibbosus | | ple.less | Plectorhinchus lesson | | ple.line | Plectorhinchus lineatus | | ple.picu | Plectorhinchus picus | | ple.unic | Plectorhinchus unicolor | | bodianus | Bodianus spp. | | oxy.diag | Oxycheilinus digrammus | | che.chlo | Cheilinus chloruorus | | che.fasc | Cheilinus fasciatus | | che.tril | Cheilinus trilobatus | | che.undu | Cheilinus undulatus | | cho.anch | Choerodon anchorago | | cho.ceph | Choerodon cephalotes | | cho.cya | Choerodon cyanodus | | cho.fasc | Choerodon fasciatus | | cho.grap | Choerodon graphicus | | cho.scho | Choerodon schoenleinii | | cho.vitt | Choerodon vitta | | epb.insi | Epibulus insidiator | | gom.vari | Gomphosus varius | | hem.melt | Hemigymnus melapterus | | hem.fasc | Hemigymnus fasciatus | | psa.wai | Psammoperca waigiensis | | aca.bloc | Acanthurus blochii | | aca.duss | Acanthurus dussumieri | | aca.gram | Acanthurus grammoptilus | | aca.line | Acanthurus lineatus | | aca.nans | Acanthurus nigricans | | aca.ncus | Acanthurus nigrofuscus | | aca.nuda | Acanthurus nigricauda | | aca.xant | Acanthurus xanthopterus | | aca.thom | Acanthurus thompsoni | | aca.spp | Acanthurus spp. | | cte.bino | Ctenochaetus binotatus | | cte.stri | Ctenochaetus striatus | | nas.annu | Naso annulatus | | nas.brach | Naso brachycentron | | nas.brevi | Naso brevirostris | | nas.litu | Naso lituratus | | nas.tong | Naso tonganus | | nas.unic | Naso unicornis | | pri.spp | Prionurus spp. | | kyp.spp | Kyphosus spp. | | zeb.scop | Zebrasoma scopas | | zeb.veli | Zebrasoma veliferum | | zan.corn | Zanclus cornutus | | bol.muri | Bolbometopon muricatum | | cal.caro | Calotomus carolinus | | cet.bico | Cetoscarus bicolor | | chl.blee | Chlorurus bleekeri | | chl.micr | Chlorurus microrhinos | | chs.sord | Chlorurus sordidus | | hip.long | Hipposcarus longiceps | | sca.alti | Scarus altipinnis | | sca.cham | Scarus chameleon | | sca.dimi | Scarus dimidiatus | | sca.flav | Scarus flavipectoralis | | sca.fors | Scarus forsteni | | sca.fren | Scarus frenatus | | sca.ghob | Scarus ghobban | | sca.glob | Scarus globiceps | | sca.nigr | Scarus niger | | sca.ovic | Scarus oviceps | | sca.psit | Scarus psittacus | | sca.rivu | Scarus rivulatus | | sca.rubr | Scarus rubroviolaceus | | sca.schl | Scarus schlegeli | | sca.spin | Scarus spinus | | sca.tric | Scarus tricolor | | sca.spp | Scarus spp. | | sig.arge | Siganus argenteus | | sig.cana | Siganus canaliculatus | | sig.cora | Siganus corallinus | | sig.doli | Siganus doliatus | | sig.fusc | Siganus fuscescens | | sig.javu | Siganus javus | | sig.line | Siganus lineatus | | sig.puel | Siganus puellus | | sig.ptus | Siganus punctatus | | sig. ptiss | Siganus punctatissimus | | sig.stell | Siganus stellatus | | sig.vulp | Siganus vulpinus | | mon.arge | Monodactylus argenteus | | cha.auri | Chaetodon auriga | | cha.afas | Chaetodon aureofasciatus | | cha.baro | Chaetodon baronessa | | cha.benn | Chaetodon bennetti | | cha.ephi | Chaetodon ephippium | | cha.citr | Chaetodon citrinellus | | cha.flav | Chaetodon flavirostris | | cha.line | Chaetodon lineolatus | | cha.lunu | Chatodon lunula | | cha.ttus | Chaetodon lunulatus | | cha.mela | Chaetodon melannotus | | cha.ocel | Chaetodon ocellicaudatus | | cha.orna | Chaetodon ornatissimus | | cha.pleb | Chaetodon plebeius | | cha.rain | Chaetodon rainfordi | | cha.raff | Chaetodon rafflesi | | cha.seme | Chaetodon semeion | | cha.spec | Chaetodon speculum | | cha.tlis | Chaetodon trifascialis | | cha.ulie | Chaetodon ulietensis | | cha.vaga | Chaetodon vagabundus | | chm.rost | Chelmon rostratus | | chm.muel | Chelmon muelleri | | cor.alti | Coradion altivelis | | cor.chry | Coradion chrysozonus | | hen.acum | Heniochus acuminatus | | hen.mono | Heniochus monoceros | | hen.vari | Heniochus varius | | mct.stri | Micracanthus strigatus | | prc.ocel | Parachaetodon ocellatus | | cen.bico | Centropyge bicolor | | cen.bisp | Centropyge bispinosa | | cen.nox | Centropyge nox | | cen.tibi | Centropyge tibicen | | cen.vrol | Centropyge vrolikii | | chd.doub | Chaetodontoplus duboulayi | | chd.mere | Chaetodontoplus meredithi | | pmc.impe | Pomacanthus imperator | | pmc.semi | Pomacanthus semicirculatus | | pmc.sext | Pomacanthus sexstriatus | | pmc.xant | Pomacanthus xanthometopon | | pyg.diac | Pygoplites diacanthus | | abu.spp | Abudefduf spp. | | acn.poly | Acanthochromis polyacanthus | | amb.aure | Amblyglyphidodon aureus | | amb.cura | Amblyglyphidodon curacao | | amb.leuc | Amblyglyphidodon leucogaster | | amp.spp | Amphiprion spp. | | amp.peri | Amphiprion perideraion | | pre.spp | Premnas sp. | | chl.labi | Cheiloprion labiatus | | chr.ambo | Chromis amboinensis | | chr.alis | Chromis atripectoralis | | chr.apes | Chromis atripes | | chr.marg | Chromis margaritifer | | chr.niti | Chromis nitida | | chr.retr | Chromis retrofasciata | | chr.tern | Chromis ternatensis | | chr.webe | Chromis weberi | | chr.xant | Chromis xanthura | | chy.roll | Chrysiptera rollandi | | chy.talb | Chrysiptera talboti | | chy.flav | Chrysiptera flavipinnis | | das.spp | Dascyllus spp. | | das.reti | Dascyllus reticulatus | | das.trim | Dascyllus trimaculatus | | dis.spp | Dischistodus spp. | | hgy.plag | Hemiglyphidodon plagiometopon | | neg.mela | Neoglyphidodon melas | | parma | Parma spp. | | neg.nigr | Neoglyphidodon nigroris | | pgy.dick | Plectroglyphidodon dickii | | pgy.lacr | Plectroglyphidodon lacrymatus | | pom.adel | Pomacentrus adelus | | pom.ambo | Pomacentrus amboinensis | | pom.aust | Pomacentrus australis | | pom.bank | Pomacentrus bankanensis | | pom.brac | Pomacentrus brachialis | | pom.chry | Pomacentrus chrysurus | | pom.coel | Pomacentrus coelestis | | pom.gram | Pomacentrus grammorhynchus | | pom.lepi | Pomacentrus lepidogenys | | pom.molu | Pomacentrus moluccensis | | pom.naga | Pomacentrus nagasakiensis | | pom.phil | Pomacentrus philippinus | | pom.reid | Pomacentrus reidi | | pom.trip | Pomacentrus tripunctatus | | pom.vaiu | Pomacentrus vaiuli | | pom.ward | Pomacentrus wardi | | ste.apic | Stegastes apicalis | | ste.fasc | Stegastes fasciolatus | | ste.livi | Stegastes lividus | | ste.nigr | Stegastes nigricans | | oxy.long | Oxymonacanthus longirostris | | Anampses | Anampses spp. | | Coris | Coris spp. | | Halichoeres | Halichoeres spp. | | Labroides | Labroides spp. | | Labropsis | Labropsis spp. | | Psuedolabrus guentheri | Psuedolabrus guentheri | | Stethojoulis | Stethojulis spp. | | Thalassoma | Thalassoma spp. | | Macropharyngodon | Macropharyngodon spp. | | Labrichthys | Labrichthys spp. | | Total fish density | Total individuals per 1000m2, averaged for the site | | Total fish species richness | Number of species per transect, averaged for the site | | Prey density | Number of Pomacentridae, considered prey for fishery target species, per 1000m2, averaged for each site. | | Prey biomass | Kg of Pomacentridae, considered prey for fishery target species, per 1000m2, averaged for each site. | | Plectropomus total density | Number of Plectropomus spp, primary fishery target species, per 1000m2, averaged for each site. | | Plectropomus total biomass | Kg of Plectropomus spp, primary fishery target species, per 1000m2, averaged for each site. | | Plectropomus legal density | Number of Plectropomus spp of legal size (&gt;38cm), primary fishery target species, per 1000m2, averaged for each site. | | Plectropomus legal biomass | Kg of Plectropomus spp of legal size (&gt;38cm), primary fishery target species, per 1000m2, averaged for each site. | | BE | Benthic invertivores | | GRAZ | Grazers | | GRAZ2 | Grazers minus the parrotfishes, subfamily Scarinae | | Parrot | Subfamily Scarinae | | COR | Corallivores | | OM | Omnivores | | PL | Planktivores | | CA | Carnivores | | PI | Piscivores | | FA | Farmers | | slope | Index of slope steepness (see Table 1) | | rugosity | Index of 3-dimensional habitat complexity (see Table 1) | | SCI | Structural complexity index (slope x rugosity) | | LCC\_% | Percent cover of live corals | | LHC\_% | Percent cover of live hard (reef-building) corals | | SC\_% | Percent cover of live soft corals | | MAC\_% | Percent cover of macroalgae | | SPO\_% | Percent cover of sponges | | Turf\_% | Percent cover of turf-forming algae | | Unconsolidated\_% | Percent cover of rubble and sand | | Benthic richness | Sum of all benthic types | | Coral\_Morph Diversity | Sum of all coral morphologies | | ChlA | Chlorophyll-a concentration, from [https://coastwatch.pfeg.noaa.gov/erddap/griddap/erdMH1chlamday](https://coastwatch.pfeg.noaa.gov/erddap/griddap/erdMH1chlamday) | | kd490 | A measure of turbidity, from [https://coastwatch.pfeg.noaa.gov/erddap/griddap/erdMH1kd490mday](https://coastwatch.pfeg.noaa.gov/erddap/griddap/erdMH1kd490mday) | | SSTmean | Mean sea surface temperature in degrees Celsius, from [https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41mday.html](https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41mday.html) | | SSTanom | Sea surface temperature anomaly in degrees Celsius, from [https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41anommday.html](https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41anommday.html) | | wave exposure index | (Not used in this study) | | Corrected depth | Depth of each site in m, corrected to Lowest Astronomical Tide | | maxDHW | DHW is calculated as the number of degrees above the coral bleaching threshold multiplied by the number of weeks that the elevated temperature persists. The unit of measurement in C-weeks. | | Cyclone | Modelled wave height and direction data from NOAA WAVEWATCH III and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) to identify which cyclones generated significant wave heights (Hs = average of top 1/3 of wave heights) of 3.5 m or more at each monitoring site. | | LT F primary | Frequency of exposure of the monitoring sites to highly turbid water from flood plumes and subsequent sediment re-suspension during the Queensland summer wet seasons, measured in weeks. | | Exposure to turbidity | Frequency of exposure of the monitoring sites to highly turbid water from flood plumes and subsequent sediment re-suspension during the Queensland summer wet seasons, measured in weeks. | | Density noPoms | Total individuals per 1000m2, averaged for the site, excluding the family Pomacentridae | | SR noPoms | Species richness per transect, averaged for the site, excluding the family Pomacentridae | | PCO1 no poms | Scores of the first Principal Components axis, excluding the family Pomacentridae |