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Beyond ecosystem modeling: A roadmap to community cyberinfrastructure for ecological data-model integration.

Istem Fer1, Anthony K Gardella2,3, Alexey N Shiklomanov4

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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.

Keywords:
accessibilitybenchmarkingcommunity cyberinfrastructuredatadata assimilationecosystem modelsinteroperabilityreproducibility

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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.