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

Abstract

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 non‐linear, 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 apply it to explore non‐linear relationships between threats and a temperate reef fish community. We use data on water quality, commercial fishing, climate change, and indicators of recreational fishing and urbanisation to build a cumulative threat map of the Northern Region in New South Wales, Australia. Using statistical models of fish abundance, we quantified 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, to protect fish from cumulative threats across two marine protected area networks (marine parks). We found that fishing has a greater impact on fish than water quality threats (i.e., percent increase above the mean for invertivores was 337% when fishing was removed c.f. 11% when water quality was removed inside no‐take zones), and that fishing outside of no‐take zones affects fish abundances inside no‐take zones. Quantifying the spatial influence of multiple threats enables managers to understand the multitude of management actions required to address threats.This article is protected by copyright. All rights reserved