Environmental water comes at significant economic cost and requires many political, social and cultural trade-offs. Accordingly, managers are being held increasingly accountable for demonstrating tangible outcomes from flow management strategies. Monitoring programs generally focus on population level responses in iconic, higher-order consumers. however, these 'flow-ecology' relationships do not specifically investigate the mechanisms underlying the observed responses.
The production and transfer of energy within an ecosystem (energetics) is a fundamental driver of ecosystem structure and function. We know that patterns of biodiversity and trophic interactions change in response to altered hydrological regimes. Energetics provides a framework to map and quantify the changes in energy resources underlying these responses. Energetics has been applied in fisheries management to estimate carrying capacity for target species but has rarely been applied in environmental management. We propose that the application of an energetics approach to environmental flow monitoring in a near-terminal inland wetland will inform and improve environmental flow management for that system.
Our study will combine biodiversity sampling of primary producers through to secondary consumers through several phases of inundation events to investigate community structure responses and construction of food webs to investigate trophic pathways within the wetland. Attributes measured will include taxonomic and functional richness, abundance, density and biomass. The study will encompass two distinct wetland vegetation communities, representative of long-term hydrological patterns and explore the connectivity and patterns of energy production and consumption within and between communities.
We expect that the two vegetation communities will display different carbon assimilation pathways - one microbial, the other algal. The source, abundance and nutritional quality of basal resources will be investigated to assess the relative 'value' of each community. We aim to produce empirical food webs that can be used to inform predictive models of the trophic carrying capacity of the wetland under different inundation scenarios.