Space-for-time substitution to assess likely response of aquatic ecosystems to future climate-related change

Predicting and managing ecological response to a changing climate is often limited by an incomplete understanding of response thresholds and biogeographic differences. For example, step changes in rainfall and runoff, and threshold dynamics and hysteresis in ecological response make projection of future conditions difficult. To combat these constraints we propose that biophysical data across exiting climatic gradients can be used in a space-for-time substitution to predict climate-related ecological response elsewhere. This method builds on previous attempts at space-for-time substitution by using patterns in physical and physicochemical data to explain biological differences across the spatial gradient, then using those patterns to formulate hypotheses of temporal ecological response and finally testing those hypotheses on temporal data available in a second, similar region of interest. 

History's motion : on absolute time and space in Tibet

On-going contestations to establish the hegemonic narrative of Tibet's history rest on the shared assumption that a true narrative, or history's motion, exists. This essay suggests that history's motion is a continuing legacy of Newton's concepts of absolute time and space, even while the current disputes over Tibet's history point to the limitations of these concepts in practice.

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.