Coral composition and bottom-wave metrics improve understanding of the patchiness of cyclone damage on reefs.

Coral reefs are likely to be exposed to more intense cyclones under climate change. Cyclone impacts are spatially highly variable given complex hydrodynamics, and coral-specific sensitivity to wave impacts. Predicting reef vulnerability to cyclones is critical to management but requires high resolution environmental data that are difficult to obtain over broad spatial scales. Using 30m-resolution wave modelling, we tested cyclonic and non-cyclonic wave metrics as predictors of coral damage on 22 reefs after severe cyclone Ita impacted the northern Great Barrier Reef, Australia in 2014. Analyses of coral cover change accounting for the type of coral along a gradient of vulnerability to wave damage (e.g., massive, branching, Acroporids) excluded cyclone-generated surface wave metrics (derived from wave height) as important predictors. Increased bottom stress wave environment (near-bed wave orbital velocity) due to Ita (Ita-Ub) explained spatial patterns of 17% to 46% total coral cover loss only when the initial abundance of Acroporids was accounted for, and only when exceeding 35% cover. Greater coral losses occurred closer to the cyclone path irrespective of coral type. Massive and encrusting corals, however, had losses exacerbated in higher non-cyclonic bottom-wave energy environments (nc-Ub). The effect of community composition on structural vulnerability to wave damage was more important predicting damage that the magnitude of the cyclone-generated waves, especially when reefs are surveyed well beyond where damaging waves are expected to occur. Exposure to Ita-Ub was greater in typically high nc-Ub environments with relatively low cover of the most fragile morphologies explaining why these were the least affected overall. We reveal that the common surface-wave metrics of cyclone intensity may not always be able to predict spatial impacts and conclude that reef vulnerability assessments need to account for chronic wave patterns and differences in community composition in order to provide predictive tools for future conservation and restoration.

Representation and complementarity of the long-term coral monitoring on the Great Barrier Reef.

Effective environmental management hinges on efficient and targeted monitoring, which in turn should adapt to increasing disturbance regimes that now characterize most ecosystems. Habitats and biodiversity of Australia's Great Barrier Reef (GBR), the world's largest coral reef ecosystem, are in declining condition, prompting a review of the effectiveness of existing coral monitoring programs. Applying a regional model of coral cover (i.e., the most widely used proxy for coral reef condition globally) within major benthic communities, we assess the representation and complementarity of existing long-term coral reef monitoring programs on the GBR. We show that existing monitoring has captured up to 45% of the environmental diversity on the GBR, while some geographic areas (including major hotspots of cyclone activity over the last 30 yr) have remained unmonitored. Further, we identified complementary groups of reefs characterized by similar benthic community composition and similar coral cover trajectories since 1996. The mosaic of their distribution across the GBR reflects spatial variation in the cumulative impact of multiple acute disturbances, as well as spatial gradients in coral recovery potential. Representation and complementarity, in combination with other performance assessment criteria, can inform the cost-effective design and stratification of future surveys. Based on these results, we formulate recommendations to assist with the design of future long-term coral reef monitoring programs.

Validation of a geographic information system model for mapping the risk of fasciolosis in cattle and buffaloes in Cambodia.

Maps showing gradations of risk of fasciolosis due to Fasciola gigantica in Cambodia were produced using geographic information systems (GIS) technology in conjunction with determinants of fasciolosis. A comparison between levels of risk predicted by the maps and field measurements of prevalence in 11 provinces (n=1406) showed general agreement, which suggested the epidemiological determinants and weightings used to produce the maps were appropriate. However, due to logistical constraints, prevalence was measured at the provincial level and animals were not randomly sampled (and thus were unlikely to be representative of variability within provinces). To address this, additional field work was carried out to measure prevalence in more detail--faecal samples were collected from a randomly selected set of animals in four districts across a representative province for areas predicted to be at high risk (n=311), moderate risk (n=268) and no risk (n=262). As with the original field survey, the results show general agreement between prevalence and risk predicted by the maps, with the best fit found for areas predicted to be at high risk.

A geographic information systems model for mapping risk of fasciolosis in cattle and buffaloes in Cambodia.

A geographic information systems (GIS) model for mapping the risk of fasciolosis in cattle and buffaloes was developed for the Kingdom of Cambodia using determinants of inundation, proximity to rivers, land use, slope, elevation, and the density of cattle and buffaloes. Determinants were subjectively weighted according to their perceived relative importance before combining them to produce a risk-map of fasciolosis. The model estimates that 28% of Cambodia is potentially at risk of fasciolosis with areas of high and moderate risk concentrated in southern and central Cambodia. The estimates of risk reflect the actual prevalence of fasciolosis in most districts surveyed, suggesting that the epidemiological determinants and weightings used to produce the model were appropriate. These results will be progressively refined as more detailed field surveys are completed to fully validate the model.