A data-driven approach to multiple-stressor impact assessment for a marine protected area

The coastal environment is not managed in a way that considers the impact of cumulative threats, despite being subject to threats from all realms (marine, land, and atmosphere). Relationships between threats and species are often nonlinear; thus, current (linear) approaches to estimating the impact of threats may be misleading. We developed a data-driven approach to assessing cumulative impacts on ecosystems and applied it to explore nonlinear relationships between threats and a temperate reef fish community. We used data on water quality, commercial fishing, climate change, and indicators of recreational fishing and urbanization to build a cumulative threat map of the northern region in New South Wales, Australia. We used statistical models of fish abundance to quantify associations among threats and biophysical covariates and predicted where cumulative impacts are likely to have the greatest impact on fish. We also assessed the performance of no-take zones (NTZs), to protect fish from cumulative threats across 2 marine protected area networks (marine parks). Fishing had a greater impact on fish than water quality threats (i.e., percent increase above the mean for invertivores was 337% when fishing was removed and was 11% above the mean when water quality was removed inside NTZs), and fishing outside NTZs affected fish abundances inside NTZs. Quantifying the spatial influence of multiple threats enables managers to understand the multitude of management actions required to address threats.