Impact prediction then leads to an evaluation of the significance of impacts based on factors such as level of public concern; scientific and professional judgement; measure of disturbance to ecological systems; and impacts on social values and quality of life.
Environmental predictions generate significant public benefits. For example, the value of seasonal climate forecasts to agriculture is estimated at more than $1500 million per annum7. The integration of environmental observations with predictive modelling would ultimately lead to improved environmental management and knowledge and would benefit Australia.
The Final Report of the Review of the EPBC Act (Samuel, 2020)8 stresses the need for improvements in the information used in environmental assessment, stating “… governments need the capability to model the environment, including the probability of outcomes from proposals, drawing on predictive modelling capabilities” and “to do this well, investment is required to improve knowledge of how ecosystems operate and to develop the capability to model them.”
According to the implementation plan, sustaining natural assets requires on-going monitoring, assessment and fore-sighting of changes in environmental conditions and Australia is missing a point of focus for environmental prediction; a brand that is known and respected for quality, independence and authority. There is currently no platform that brings together the following dispersed expertise: data and models to support rich transdisciplinary integration and foster new capabilities; short-term forecasting; and longer-term identification of risks. The environment research domain lacks the additional networking and technical linkages that are necessary to ensure that all researchers (and government, industry and wider society) can readily find, review and contribute to improve data and models for prediction. There is no single model that conceptualises complexities of ecosystem function; instead, ensembles of models from different disciplines are required to investigate any complex issue. This creates the need for a modelling infrastructure that can harness domain expertise, models and data assets from diverse environmental modelling communities. Figure 2, depicts some of the sub-optimal researcher community impacts arising from a lack of predictive research capability in ecosystem science.