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ABSTRACT: Coastal fish populations are typically threatened by multiple human activities, including fishing pressure and run-off of terrestrial pollution. Linking multiple threats to their impacts on fish populations is challenging because the threats may influence a species directly, or indirectly, via its habitats and its interactions with other species. Here we examine spatial variation in abundance of coral reef fish across gradients of fishing pressure and turbidity in Fiji. We explicitly account for multiple pathways of influence to test the alternative hypotheses that (1) habitat moderates predation by providing shelter, so habitat loss only affects prey fish populations if there are abundant predators, (2) habitat change co-drives biomass of both prey and predator functional groups. We examined responses of 7 fish functional groups and found that habitat change co-drives both predator and prey responses to turbidity. Abundances of all functional groups were associated with changes in habitat cover; however, the responses of their habitats to turbidity were mixed. Planktivore and piscivore abundance were lower in areas of high turbidity, because cover of their preferred habitats was lower. Invertivore, browser and grazer abundance did not change strongly over the turbidity gradient, because different components of their habitats exhibited both increases and decreases with turbidity. The effects of turbidity on fish populations were minor in areas where fish populations were already depleted by fishing. These findings suggest that terrestrial run-off modifies the composition of reef fish communities indirectly by affecting the benthic habitats that reef fish use.

Coastal ecosystems can be degraded by poor water quality. Tracing the causes of poor water quality back to land-use change is necessary to target catchment management for coastal zone management. However, existing models for tracing the sources of pollution require extensive data-sets which are not available for many of the world’s coral reef regions that may have severe water quality issues. Here we develop a hierarchical Bayesian model that uses freely available satellite data to infer the connection between land-uses in catchments and water clarity in coastal oceans. We apply the model to estimate the influence of land-use change on water clarity in Fiji. We tested the model’s predictions against underwater surveys, finding that predictions of poor water quality are consistent with observations of high siltation and low coverage of sediment-sensitive coral genera. The model thus provides a means to link land-use change to declines in coastal water quality

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