Riegl B et al. (2013), Coral population trajectories, increased distur...

ECB-ART-42854

Ecol Evol 2013 Apr 01;34:1050-64. doi: 10.1002/ece3.519.

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Coral population trajectories, increased disturbance and management intervention: a sensitivity analysis.

Riegl B , Berumen M , Bruckner A .

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Coral reefs distant from human population were sampled in the Red Sea and one-third showed degradation by predator outbreaks (crown-of-thorns-starfish = COTS observed in all regions in all years) or bleaching (1998, 2010). Models were built to assess future trajectories. They assumed variable coral types (slow/fast growing), disturbance frequencies (5,10,20 years), mortality (equal or not), and connectivity (un/connected to un/disturbed community). Known disturbances were used to parameterize models. Present and future disturbances were estimated from remote-sensing chlorophyll and temperature data. Simulations and sensitivity analysis suggest community resilience at >20-year disturbance frequency, but degradation at higher frequency. Trajectories move from fast-grower to slow-grower dominance at intermediate disturbance frequency, then again to fast-grower dominance. A similar succession was observed in the field: Acropora to Porites to Stylophora/Pocillopora dominance on shallow reefs, and a transition from large poritids to small faviids on deep reefs. Synthesis and application: Even distant reefs are impacted by global changes. COTS impacts and bleaching were key driver of coral degradation, coral population decline could be reduced if these outbreaks and bleaching susceptibility were managed by maintaining water quality and by other interventions. Just leaving reefs alone, seems no longer a satisfactory option.

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Genes referenced: LOC100887844 LOC115925415 LOC590297

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	Figure 1. Sampling sites in the Red Sea. Red stars = transect sites for this study; blue circle = comparative site from the literature.
	Figure 2. Mean cover over all transects in Saudi Arabia. The dominant genera are Acropora, Porites, and Pocillopora.
	Figure 3. (a) Dendrogram of transect similarity, cluster levels optimized by maximizing cophenetic index (not shown). Euclidian distance and Ward's method of linkage. Three clusters correspond to coral communities dominated by fast-growers (Acropora and Pocillopora) or slow-growers (Porites). (b) geographic location of transects in clusters. No geographic separation of samples occurred, so community differentiation is similar across study area. (c) Box-and-whisper plots of relative cover by dominant coral types in each cluster (color-coded).
	Figure 4. Seven genera made up ∼75% of all recruits encountered on the Farasan Banks. Data pooled across all depths.
	Figure 5. Relative bleaching incidence (y-axes) at Thuwal in 2010. Mortality in Table 4.
	Figure 6. A) winter minimum B) summer maximum sea surface temperature in the Red Sea. C,D) Chlorophyll levels 4–6 months prior to surveys with COTS outbreaks. It takes COTS about this time to switch to corals as diet (Yamaguchi 1974; Houk et al. 2007). Inset in (C) shows elevated chlorophyll levels in Yanbu-Wajh region, 5 months prior to observed COTS infestations. Datasource: coastwatch.pfeg.noaa.gov.
	Figure 7. Spatial distribution of coral cover on sampled reefs. The four panels show the geographical spread of sites in the four sampled regions. Size of the bubble is relative to percent coral cover in the site. Several concentric circles show overlapping sites (overlap is due to coarse geographic resolution) with different cover. No systematic differentiation of high- and low-cover sites is observed, suggesting that disturbances leading to low cover act locally. Transects are from equivalent environments and comparable depth. The small inset graphs show the semivariograms of spatial autocorrelation, which show disorganized scatter.
	Figure 8. Temperature data showing warming of the Red Sea. (a) Annual means of summer monthly anomalies (July–September, the period in which bleaching is observed) of air temperatures in Jeddah. Since 1994, virtually all annual anomalies are positive. (b) Annual anomalies of sea-surface temperatures (HadISST2 data, data under Crown copyright) across the sampled area. Also here, since 1994 virtually all anomalies are positive, indicating warming of the Red Sea. This pattern is concordant with findings by Raitsos et al. (2011). The warming trend is strongest in the northern Red Sea.
	Figure 9. Model sensitivity to disturbance severity and frequency. Outcome cones based on model parameterization shown in Table 1 (upper line representing equal mortality, lower line higher mortality in fast growers). Unless mortality is preferentially in fast-growers, they increasingly dominate reefs. In mild and moderate disturbance scenarios, slow-growers can become dominant. Under severe disturbance frequency and severity, a weedy community of fast-growing small corals is established, but in mild and moderate disturbance and severity, slow-growers persist or even dominate. The y-axes were truncated at FG-index 50 for reasons of graphical clarity and since clear dominance was established.

References [+] :

Bruno, Regional decline of coral cover in the Indo-Pacific: timing, extent, and subregional comparisons. 2007, Pubmed