Ecological forecasting – the prediction of ecological processes and states across a variety of spatial and temporal scales – can help resource managers make informed decisions that minimize the adverse impacts of a changing and increasingly variable environment. To provide useful, applied ecological forecasts, the scientific community must identify the forecast products that are both needed and amenable to skillful forecasting, and must develop the capacity (i.e., information and human infrastructure) required to operationalize (i.e., produce and deliver) forecasts to appropriate stakeholders. Iterative ecological forecasting requires a “big-data” approach to all aspects of the data life-cycle, including dynamic use of data to not only model processes, but also to evaluate – preferably in near real-time – model predictions and to improve model precision through data-model fusion.
Results/Conclusions
In 2019, we conducted a multi-Agency workshop to discuss potential approaches for building capacity for applied ecological forecasting within the federal research and management community. Workshop participants developed a traceable workflow – including standardized rubrics of criteria and attributes – to identify and prioritize potential forecasting products that represent the opportunity for researchers to work with partners on modeling, data delivery and data integration in direct support of resource management decision-making. This poster will also describe workshop outcomes including (1) processes for the identification of potential forecast products with direct application to decision-making, (2) a standardized set of criteria and attributes to guide the evaluation and prioritization of potential forecast products, (3) a standardized set of requirements for the description of a potential forecast products including data and model availability, and (4) a set of potential near-term, iterative ecological forecast products of mutual interest to land managers and researchers.