Ecological Modeling Guide for Ecosystem Restoration and Management

Abstract

Ecological models are important tools for planning ecosystem restoration and management activities. Models help to organize our thinking, conceptualize our understanding of complex systems, and forecast environmental benefits that may result from proposed restoration and management actions. This report provides information to guide environmental planers in selection, development, evaluation and documentation of ecological models. A number of critical issues are addressed, including specifying objectives and formulating a sound conceptual model, choosing among types of models, deciding when to develop a new model, systematically evaluating the quantitative model, addressing parameter and model uncertainty, developing sections of the model through iteration, analyzing alternatives and documenting results. Quantitative modeling is shown to be a dynamic process that is best served using an iterative approach. In practice, individual parts of a conceptual model are quantified and evaluated in a stepwise fashion until the entire model is captured quantitatively. This iterative approach creates transparency in model development, which can remove the black-box stigma that has been associated with the use of models in the environmental sciences.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2012
Accession Number
ADA572123

Entities

People

  • David J. Tazik
  • J. Craig Fischenich
  • Todd M. Swannack

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Addressing
  • Army Corps Of Engineers
  • Birds
  • Business Administration
  • Complex Systems
  • Computational Science
  • Delphi Method
  • Ecology
  • Ecosystems
  • Environment
  • Geographic Information Systems
  • Habitats
  • Mathematical Models
  • Mathematics
  • Scientific Literature
  • Statistical Analysis
  • Test And Evaluation

Fields of Study

  • Environmental science

Readers

  • Coastal and Marine Engineering/Sediment Transport/Hydraulic Engineering
  • Computational Modeling and Simulation
  • Systems Analysis and Design