No abstract

Summary Cyclical outbreaks of pests can impact the functioning of entire ecosystems. An eminent example is outbreaks of crown‐of‐thorns starfish (COTS; Acanthaster planci) that cause substantial coral mortality on the Great Barrier Reef (GBR). We analyse COTS abundance and outbreaks with a Bayesian spatiotemporal model applied to a long‐term survey of the GBR (1985–2014). We assess the relative increase in COTS abundance beyond that explained by a reef's location and explanatory covariates, and thereby incorporate local reef characteristics into the identification of outbreaks, while allowing for both randomness and predictable patterns in the development of outbreaks. The model results confirm that waves of COTS outbreaks originate near Lizard Island (14·67⁰S) and progress in a northwesterly or southeasterly direction, with the southward wave progressing about 60 km year−1. The model reveals several previously unidentified hotspots with high average COTS abundance. The abundance of COTS may also have decreased on reefs protected from fishing after an expansion of protected areas within the GBR Marine Park in 2004, which suggests that closing reefs to fishing may help control COTS. Synthesis and applications. In this study, we use 30 years of data from the Great Barrier Reef to show that the timing and geographic location of crown‐of‐thorns starfish (COTS) outbreaks can be modelled by incorporating covariates, spatial and spatiotemporal dependence within a single coherent framework. The model can be used to identify areas of high average COTS abundance, to assess the impact of fishery management actions such as no‐take areas and to identify areas where waves of outbreaks may originate. The identification of outbreaks from noisy long‐term spatially extensive data may help managers choose appropriate control strategies. This modelling approach is applicable to other ecosystems where outbreaks of damaging pests occur.

Ecological predictions and management strategies are sensitive to variability in model parameters as well as uncertainty in model structure. Systematic analysis of the effect of alternative model structures, however, is often beyond the resources typically available to ecologists, ecological risk practitioners, and natural resource managers. Many of these practitioners are also using Bayesian belief networks based on expert opinion to fill gaps in empirical information. The practical application of this approach can be limited by the need to populate large conditional probability tables and the complexity associated with ecological feedback cycles. In this paper, we describe a modeling approach that helps solve these problems by embedding a qualitative analysis of sign directed graphs into the probabilistic framework of a Bayesian belief network. Our approach incorporates the effects of feedback on the model's response to a sustained change in one or more of its parameters, provides an efficient means to explore the effect of alternative model structures, mitigates the cognitive bias in expert opinion, and is amenable to stakeholder input. We demonstrate our approach by examining two published case studies: a host-parasitoid community centered on a nonnative, agricultural pest of citrus cultivars and the response of an experimental lake mesocosm to nutrient input. Observations drawn from these case studies are used to diagnose alternative model structures and to predict the system's response following management intervention.

Aim: Marine protected areas (MPAs) are increasingly implemented to conserve or restore coral reef biodiversity, yet evidence of their benefits for enhancing coral cover is limited and variable.Location: 30 MPAs worldwide and nearby sites (within 10 km).Taxa: Cover of key functional groups for coral (total, branching, massive and tabular), and algae (total, filamentous, foliose) and total biomass of reef fish trophic groups (excavator, scraper, browser, higher carnivore). Methods:We used a global dataset obtained using standardized survey methods at 465 sites associated with 30 MPAs in 28 ecoregions to test the effects of five key MPA attributes (>10 years old, well-enforced, no-take, large and isolated) on coral cover, algal cover and reef fish biomass. We also tested the direct (reducing disturbance by human activities) versus indirect pathways (increasing grazing potential through recovering populations of herbivorous fishes) by which MPAs can influence coral and algal cover. Results:Only well-enforced, no-take and old (>10 years) MPAs had higher total coral cover (response ratio 1.08-1.19×) than fished sites, mostly due to the increased cover of massive coral growth forms (1.34-2.06×). This effect arose through both the direct influence of protection and indirect benefits of depressed algal cover by recovering herbivorous fish biomass. Neither the direct (standardized coefficient = 0.06) nor indirect effects (standardized coefficient = 0.04) of no-take protection on coral cover were particularly strong, likely reflecting regional differences in fishing gear, targeted species and trophic webs. Conclusions:MPAs promote the persistence of some functional groups of corals, and thus represent an important management tool, globally. K E Y W O R D Salgal cover, fish biomass, herbivorous fishes, impacts of fishing, marine reserves, predatory fishes, Reef Life Survey, trophic interactions 10 | STRAIN eT Al.