Using biological traits to develop an ecosystem condition assessment of rocky reefs in the Natal bioregion of South Africa

To promote ecosystem-based approaches to marine spatial planning (MSP), we need to be able to measure the ecological condition of marine systems. This requires that we use credible and defensible indicators for ecosystem... [ view full abstract ]

To promote ecosystem-based approaches to marine spatial planning (MSP), we need to be able to measure the ecological condition of marine systems. This requires that we use credible and defensible indicators for ecosystem condition assessments. South Africa lacks a data-derived approach to assess the condition of marine ecosystems. It is extremely challenging to collect ecological data from multiple ecosystem components at a national scale with such diversity of biota, habitat types and complex physical environments. In order to ground truth current estimated condition assessments, and to identify indicators that can be used for ecosystem condition assessments, this project aims to determine the effectiveness of a trait-based approach to measure ecosystem condition of rocky reef habitats. We used demersal fish and benthic invertebrate community data to identify and test key indicators of condition, and to develop quantitative indices that can be used to spatially assess the condition of rocky reef ecosystems. We also measured the effects of multiple anthropogenic pressures on ecosystem structure and function. Preliminary results highlight the differences in fish functional structure between protected and exploited reef sites, emphasising which functional traits and indices are indicative of reefs in good ecological condition. Furthermore, this study models the response of various taxonomic and functional indices to a gradient of cumulative anthropogenic pressures, to determine the main drivers of rocky reef structure and function. This is the first step to establishing a standardised method to assess the condition of marine ecosystems in South Africa using an ecological data-derived approach.