Grant: Strategic Projects - Group

Ecosystems are being lost incrementally to development (urbanisation, agriculture, forestry, etc.) across the landscape. Habitat loss is especially obvious for the small tributary streams that provide the water, nutrients and materials to sustain habitats, water supply and ecosystem services downstream. Although we know that tributaries are cumulatively altered in many stream networks, we are not yet able to predict downstream consequences on water quality, biodiversity, and ecosystem services. And we know very little about how such losses impact conservation of habitats critical to headwater species themselves. Agencies that protect our natural environments struggle with ways to conserve stream ecosystems, both in the headwaters and to protect downstream environments. Assessment of cumulative effects from multiple stressors on large streams is problematic for many reasons, but especially including the very large scaling issues, dilution effects, lag times, and non-additive and non-linear effects. Cumulative effects also occur at the scale of habitat loss across a landscape for headwater specialists. Headwater streams provide an excellent place to begin to combine empirical and modelling studies to understand the impacts of cumulative effects and how best to predict and measure the contribution of losses of headwater streams to downstream conditions. Our proposal includes four objectives. 1. Using two unique datasets, and additional data to be collected, we will study the spatial and temporal patterns of the community structure of headwaters and larger streams innested catchment designs. This will also use landscape context, e.g., the degree of alteration of neighbouring headwaters, as an environmental gradient affecting persistence of local headwater communities. We will also add measures of select ecosystem functions to the field studies. 2. We will use detailed, process-based models to generate predictions of how changes might scale across catchment sizes as one progresses downstream. 3. We will use data to test the model predictions downstream at nested scales through fluvial networks. 4. We will develop GIS-based decision tools to assist evaluation of risks associated with the loss of headwater streams.