Maximizing colonial waterbirds' breeding events using identified ecological thresholds. and environmental flow management

Global wetland biodiversity loss continues unabated, driven by increased demand for freshwater. A key strategy for conservation management of freshwater systems is to maintain the quantity and quality of the natural water regimes, including the frequency and timing of flows. Formalizing an ecological model depicting the key ecological components and the underlying processes of cause and effect is required for successful conservation management. Models linking hydrology with ecological responses can prove to be an invaluable tool for robust decision-making of environmental flows. Here, we explored alternative water management strategies and identified maximal strategies for successful long-term management of colonial waterbirds in the Macquarie Marshes, Australia. We modeled fluctuations in breeding abundances of 10 colonial waterbird species over the past quarter century (1986-2010). Clear relationships existed between flows and breeding, both in frequencies and total abundances, with a strong linear relationship for flows >200 GL. Thresholds emerged for triggering breeding events in all 10 species, but these varied among species. Three species displayed a sharp threshold response between 100 GL and 250 GL. These had a breeding probability of 0.5 when flows were >180 GL and a 0.9 probability of breeding with flows >350 GL. The remaining species had a probability greater than 0.5 of breeding with flows >400 GL. Using developed models, we examined the effects of five environmental flow management strategies on the variability of flows and subsequent likelihood of breeding. Management to different target volumes of environmental flows affected overall and specific breeding probabilities. The likelihood of breeding for all 10 colonial waterbirds increased from a regulated historical mean (+/- SD) of 0.36 +/- 0.09 to 0.53 +/- 0.14, an improvement of 47.5% +/- 18.7%. Management of complex ecosystems depends on good understanding of the responses of organisms to the main drivers of change. Considerable opportunity exists for implementing similar frameworks for other ecosystem attributes, following understanding of their responses to the flow regime, achieving a more complete model of the entire ecosystem.