ASFB Home > Potential Changes in Prey Population Structure Following Removal of Predators by Fishing

Multivariate Demographic Indices Used to Measure the Performance of Marine Protected Areas on the Increased Sustainability and Productivity of Exploited Coral Reef Fish Stocks

Gavin Begg, Bruce Mapstone, Samantha Adams, Ashley Williams, Campbell Davies and Dong Lou

CRC Reef Research Centre, TOWNSVILLE, AUSTRALIA

Theme: TH4

Increasing impacts on natural resources of marine ecosystems, coupled with ineffective fisheries management and the need for maintenance of species biodiversity and their habitats in perpetuity, has recently led to the global implementation of marine protected areas (MPAs). In particular, MPAs have been established to protect and conserve complex reef ecosystems such as those in the Great Barrier Reef World Heritage Area (GBRWHA) of Australia, where precautionary principles of conservation are rated very highly. However, there is limited empirical evidence to evaluate the performance of MPAs in achieving the desired outcomes of these management strategies. We investigate the performance of MPAs with respect to sustainability and productivity of several exploited coral reef fish stocks throughout the GBRWHA using a range of multivariate demographic indices. Spatial and temporal patterns in multivariate population dynamics, age diversity, and multi-species abundance indices were estimated for fish stocks sampled on reefs open and closed to fishing as part of the large-scale experimental manipulations of the CRC Reef Effects of Line Fishing Project. We assess the relative effects of MPAs on changes in life-history characteristics and population dynamics of target species based on these multivariate indices. We discuss the utility of these indices in evaluating the performance of MPAs, and propose strategies for applying them to monitor the relative success of MPAs for conservation and sustainability of exploited reef fish stocks. The concurrent use of several of these performance indicators will maximise our potential to differentiate MPA-induced changes from that of background natural variation.