Results of hierarchically-nested ANOVAs to test for spatial variation in prevalence of injury (proportion of injured colonies per site) for each coral taxa.

<p>Results of hierarchically-nested ANOVAs to test for spatial variation in prevalence of injury (proportion of injured colonies per site) for each coral taxa.</p

Mean (± SE) percentage partial mortality per colony (severity of partial mortality) in <i>Acropora hyacintus</i>, <i>Porites</i> massive, <i>Montipora</i> encrusting and <i>Pocillopora damicornis</i>, in the three latitudinal sectors: the northern, the central and the southern sector.

<p>Partial mortality was calculated as the proportion of dead to live tissue within the overall physical extent of each coral colony.</p

Size-frequency distributions (percentage of colonies) and percentage partial mortality for each size class in each latitudinal sector for encrusting <i>Montipora</i>, and <i>P. damicornis</i>.

<p>Size classes were log10 transformed estimates of colony surface area.</p

Linear regression outcomes to investigate the effect of colony size on the severity (extent of injury) and on the prevalence (proportion of injured colonies) of partial mortality in each coral taxa.

<p>Linear regression outcomes to investigate the effect of colony size on the severity (extent of injury) and on the prevalence (proportion of injured colonies) of partial mortality in each coral taxa.</p

Map of the three study sectors (northern, central and southern) along the Great Barrier Reef, Australia.

<p>Within each latitudinal sector, three mid-shelf reefs, each with three sites on the exposed reef crest, were sampled. Figure adapted from Trapon and co-workers <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100969#pone.0100969-Trapon2" target="_blank">[18]</a>.</p

Number of injured colonies versus number of total colonies surveyed at each site, within each reef and sector for the four coral species.

<p>Number of injured colonies versus number of total colonies surveyed at each site, within each reef and sector for the four coral species.</p

Analysis of deviance table for hierarchical comparisons of log-linear models to test for patterns of complete dependence and conditional independence of variables inducing spawning response in crown-of-thorns starfish.

<p>‘Spawning’ was considered to be a response variable, so all fitted models included the ‘Treatment’ by ‘Sex’ interaction term.</p

Size-frequency distributions (percentage of colonies) and percentage partial mortality for each size class in each latitudinal sector for <i>Porites</i> massive, and <i>Acropora hyacinthus</i>.

<p>Size classes were log10 transformed estimates of colony surface area.</p

Proportion of starfish that spawned in response to cues.

<p>(<b>a</b>) seawater temperature, (<b>b</b>) water quality, (<b>c</b>) phytoplankton, (<b>d</b>) conspecific gametes, (<b>e</b>) sperm and phytoplankton. FSW = 0.2-μm filtered seawater; LS-FSW = low salinity filtered seawater; NE-FSW = nutrient-enriched filtered seawater; PP = combination of three phytoplankton species. Bars traversing the dashed lines represent spawning of more than 50% of individuals exposed to a given treatment.</p

Response time and cumulative probability of spawning in male and female crown-of-thorns starfish after exposure to environmental and biological cues.

<p>(<b>a</b>) seawater temperature, (<b>b</b>) water quality, (<b>c</b>) phytoplankton, (<b>d</b>) conspecific gametes, (<b>e</b>) sperm and phytoplankton. Solid circles are individual spawning events and different letters indicate significant differences based on multiple comparisons (Holm-Šídák) after Log-rank analyses. FSW = 0.2-μm filtered seawater; LS-FSW = low salinity filtered seawater; NE-FSW = nutrient-enriched filtered seawater; PP = combination of three phytoplankton species.</p