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Ecological Informatics and Modelling

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To advance the science of ecology, Harvard Forest researchers employ an iterative process of building quantitative models that represent our best understanding of how ecosystems work, then testing those models with long term data collected in the field. Once the models can reliably reproduce observed data they are used to help increase our understanding of complex systems, for scaling results to larger geographical areas, for reconstructing events in the past, and for forecasting in the future. Models may improve both our theoretical understanding of ecology and our ability to make good policy and management decisions. Researchers at the Harvard Forest have created or utilized a wide range of models, including: models of ecophysiology (PnET), soil microbial processes (SCAMPS, MIMICS), forest growth and carbon exchange (EDII), hurricane wind disturbance (Hurrecon), forest landscape processes (Landis-II), hydrology (RHESSys) and earth systems (CLM5).

Ecological informatics is the science of information in ecology. A central problem in this emerging field is the fact that our ability to collect and analyze large datasets (due to recent advances in computer, network, and sensor technologies) has outpaced our ability to document these analyses and to ensure that results are reproducible. The Analytic Web project, a long-term collaboration between ecologists at Harvard Forest and computer scientists at UMass Amherst, is developing methods and tools to address this problem.

Examples of Ecological Informatics & Modeling programs led by the Harvard Forest:


Associated Researchers

Jeffrey Blanchard (UMass Amherst)
Emery Boose
Mark Friedl (Boston University)
Barbara Lerner (Mount Holyoke College)
Paul Moorcroft (Harvard Department of Organismic and Evolutionary Biology)
Lee Osterweil (UMass Amherst)
Kristina Stinson (UMass Amherst)
Jonathan Thompson

Related Data & Publications

Publications - Published papers from Harvard Forest research related to ecological informatics and modelling.

Datasets - Data and metadata for ecological informatics and modelling at the Forest.

Abstracts for Current Research - Summaries of ongoing ecological informatics and modelling projects at the Forest.