Combining monitoring, models and palaeolimnology to assess ecosystem response to environmental change at monthly to millennial timescales: the stability of Blue Lake, North Stradbroke Island, Australia

Human-induced environmental change threatens freshwater ecosystems, and knowing how these systems have responded to past variability can inform management decisions. Palaeoenvironmental reconstructions provide insight, although their low temporal resolution may mask short-term responses. Hence, a combination of short-term, high-resolution contemporary data and long-term, low-resolution palaeoenvironmental data can offer greater understanding of system behaviour. We demonstrate this approach by examining the response of a lake on North Stradbroke Island, Australia, to environmental change, by investigating hydrological and water quality variation at different temporal scales. The data include daily lake discharge, monthly water quality, modelled annual lake discharge over a 117-year period and comparisons of aerial photographs and lake bathymetry over the past 65years. A palaeoenvironmental reconstruction of the last c. 7500years used pollen, stable isotopes, macrofossils and diatoms to provide a long-term perspective. Despite variability in regional climate over recent decades, the depth and water chemistry of Blue Lake displayed little variation. At millennial timescales, there is clear evidence of catchment change in response to a marked shift in climate around 4500years ago. However, diatom analysis indicates that Blue Lake has exhibited exceptional stability and resistance to change, compared to other Australian Holocene lake records. This suggests that Blue Lake has been an important climate refuge for aquatic biota in the past and, with appropriate management, should continue in this capacity into the future. This study highlights the benefits of a combined, multi-temporal approach to inform understanding of the structure and function of freshwater ecosystems and their responses to environmental change. Such scientific understanding of system requirements is critical to achieving sustainable management objectives.