Predicting the likely response of data-poor ecosystems to climate change using space-for-time substitution across domains.

Predicting ecological response to climate change is often limited by a lack of relevant local data from which directly applicable mechanistic models can be developed. This limits predictions to qualitative assessments or simplistic rules of thumb in data-poor regions, making management of the relevant systems difficult. We demonstrate a method for developing quantitative predictions of ecological response in data-poor ecosystems based on a space-for-time substitution, using distant, well-studied systems across an inherent climatic gradient to predict ecological response. Changes in biophysical data across the spatial gradient are used to generate quantitative hypotheses of temporal ecological responses that are then tested in a target region. Transferability of predictions among distant locations, the novel outcome of this method, is demonstrated via simple quantitative relationships that identify direct and indirect impacts of climate change on physical, chemical and ecological variables using commonly available data sources. Based on a limited subset of data, these relationships were demonstrably plausible in similar yet distant (>2000 km) ecosystems. Quantitative forecasts of ecological change based on climate-ecosystem relationships from distant regions provides a basis for research planning and informed management decisions, especially in the many ecosystems for which there are few data. This application of gradient studies across domains - to investigate ecological response to climate change - allows for the quantification of effects on potentially numerous, interacting and complex ecosystem components and how they may vary, especially over long time periods (e.g. decades). These quantitative and integrated long-term predictions will be of significant value to natural resource practitioners attempting to manage data-poor ecosystems to prevent or limit the loss of ecological value. The method is likely to be applicable to many ecosystem types, providing a robust scientific basis for estimating likely impacts of future climate change in ecosystems where no such method currently exists.

The development of biological objectives for streams in a single catchment: a case study on the catchment of Western Port Bay, Victoria, Australia.

Government environment protection policies for waterways have traditionally relied on water quality indicators and their objectives. In this paper we describe the development of biological objectives based on invertebrate indicators for inclusion in a government policy for the catchment of Western Port Bay, Victoria. The first step of defining segments (areas with streams in which the same objectives are applied) was problematic, requiring two different approaches, as follows. Site groups initially based on invertebrate community composition derived using multivariate techniques (ordination and classification) proved to be unsuitable for policy segments. Segment boundaries were subsequently defined using topographical (e.g. boundary of foothills and lowland plains), climate (e.g. rainfall) and land-use (e.g. urban) features. We used information and data from reference sites inside as well outside the catchment to derive specific biological objectives based on aquatic invertebrates for these segments. Objectives were specified for the following four indicators--number of invertebrate families, the SIGNAL index, the AUSRIVAS predictive model and the number of key families.