Picture: Quarry Lake. Credit: Ivan Bandura (Unsplash).

In an era of rapid global change, our ability to understand and predict Earth’s natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Our capacity to predict these changes relies on our ability to introduce the growing volume and variety of real-world data into our models. Unfortunately, a range of obstructions have created data bottlenecks that mean much of this new data remains inaccessible to those modelling these natural systems.

An international group of researchers performed a critical review of the information infrastructure that connects ecosystem modelling and measurement efforts. This group has now proposed a roadmap to community cyber-infrastructure development that can reduce the divisions between empirical research and modelling, accelerating the pace of discovery.

The team has called for investment into a new era of data-model integration that is accessible, scalable, and includes transparent tools that integrate the expertise of the whole community – including modellers and empiricists.

The team presented a roadmap focused on five key components that will improve community tools:

  1. the underlying foundation of community cyber-infrastructure;
  2. data ingest;
  3. calibration of models to data;
  4. model data benchmarking;
  5. and data assimilation and ecological forecasting.

This community-driven approach is key to meeting the pressing needs of science and society in the 21st century.

Paper: Fer, I., Gardella, A. K., Shiklomanov, A. N., Serbin, S. P., De Kauwe, M. G., Raiho, A., Johnston, M. R., Desai, A., Viskari, T., Quaife, T., LeBauer, D. S., Cowdery, E. M., Kooper, R., Fisher, J. B., Poulter, B., Duveneck, M. J., Hoffman, F. M., Parton, W., Mantooth, J., Campbell, E. E., Haynes, K. D., Schaefer, K., Wilcox, K. R. and Dietze, M. C. (2020) Beyond Modeling: A Roadmap to Community Cyberinfrastructure for Ecological Data-Model Integration. Global Change Biology, in press.