RCN: Forecasts Of Resource and Environmental Changes: data Assimilation Science and Technology (FORECAST)

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There is an urgent need to develop the capability to forecast changes in our living environment and natural resources. This is a period marked by rapid climate change, profound alteration of biogeochemical cycles, excessive depletion of natural resources, extensive proliferation of exotic species, changes in frequency and spread of disease, and severe deterioration of air and water quality. Human populations are increasing at an alarming rate and society is becoming more dependent on extraction and utilization of natural resources to support regional and global economies. Continuous and accelerated supply rates of food, fiber, freshwater, and clean air are necessary to maintain healthy human societies. To effectively mitigate climate change impacts, manage natural resources, and curb environmental deterioration, we need to develop robust methods for forecasting ecosystem services. This project promotes networking activities that will develop, apply, and promote ecological forecasting using techniques that assimilate information from process-based models, prior knowledge, data and other sources (in short, data assimilation). The FORECAST network will organize a series of conferences and working groups to achieve those objectives. Overall, FORECAST has the potential to develop a multi-disciplinary community of scientists with expertise in data assimilation and ecological forecasting. Ecological forecasting is critical for resource management and climate change mitigation. The ability to forecast changes in natural resources and ecological properties, such as ecosystem production, biodiversity, and infectious diseases, will directly benefit the society. In addition, the FORECAST network will (i) involve many students, post-docs, and early-career scientists to enhance the development and propagation of new methodologies, (ii) develop web-based data portals for scientists to share techniques and ideas, (iii) stimulate interactions among ecologists, computer scientists, statisticians, and mathematicians, and (iv) provide broad multidisciplinary training for minority students and post-docs on data assimilation and ecological forecasting.