Beyond ecosystem modeling: A roadmap to community cyberinfrastructure for ecological data-model integration
Istem Fer1, Anthony K Gardella2,3, Alexey N Shiklomanov4
1Finnish Meteorological Institute, Helsinki, Finland.
Global Change Biology
|October 19, 2020
Summary
Bridging the gap between ecological data and models is crucial for understanding global change. Developing community cyberinfrastructure will accelerate scientific discovery by integrating empirical research and modeling efforts.
Area of Science:
- Ecology
- Environmental Science
- Computational Science
Background:
- Current Earth system science struggles to integrate vast biosphere data with ecological models.
- Data-model integration is hindered by insufficient information infrastructure, limiting scientific progress.
Purpose of the Study:
- To critically assess the information infrastructure connecting ecosystem modeling and measurement.
- To propose a roadmap for community cyberinfrastructure development to enhance data-model integration.
Main Methods:
- Analysis of existing information infrastructure linking empirical research and ecosystem modeling.
- Development of a roadmap focusing on five key community cyberinfrastructure opportunities.
Main Results:
- Identified bottlenecks in data-model integration that limit the exploitation of available biosphere data.
- Proposed five key areas for community cyberinfrastructure development: foundations, data ingest, calibration, benchmarking, and data assimilation.
Conclusions:
- A community-driven cyberinfrastructure approach is essential for integrating ecosystem modeling and empirical data.
- Investment in accessible, scalable, and transparent tools is needed to accelerate ecological discovery and forecasting.
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