Abstract
Integrated pest management (IPM) leverages our understanding of ecological interactions to mitigate the impact of pest species on economically and/or ecologically important assets. It has primarily been applied in terrestrial settings (e.g., agriculture), but has rarely been attempted for marine ecosystems. The crown-of-thorns starfish (CoTS), Acanthaster spp., is a voracious coral predator throughout the Indo-Pacific where it undergoes large population increases (irruptions), termed outbreaks. During outbreaks CoTS act as a pest species and can result in substantial coral loss. Contemporary management of CoTS on the Great Barrier Reef (GBR) adopts facets of the IPM paradigm to manage these outbreaks through strategic use of direct manual control (culling) of individuals in response to ecologically based target thresholds. There has, however, been limited quantitative analysis of how to optimize the implementation of such thresholds. Here we use a multispecies modeling approach to assess the performance of alternative CoTS management scenarios for improving coral cover trajectories. The scenarios examined varied in terms of their ecological threshold target, the sensitivity of the threshold, and the level of management resourcing. Our approach illustrates how to quantify multidimensional trade-offs in resourcing constraints, concurrent CoTS and coral population dynamics, the stringency of target thresholds, and the geographical scale of management outcomes (number of sites). We found strategies with low target density thresholds for CoTS (≤0.03 CoTS min-1 ) could act as "Effort Sinks" and limit the number of sites that could be effectively controlled, particularly under CoTS population outbreaks. This was because a handful of sites took longer to control, which meant other sites were not controlled. Higher density thresholds (e.g., 0.04-0.08 CoTS min-1 ), tuned to levels of coral cover, diluted resources among sites but were more robust to resourcing constraints and pest population dynamics. Our study highlights trade-off decisions when using an IPM framework and informs the implementation of threshold-based strategies on the GBR.
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