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R-language scripts for RIVPACS-type predictive modeling

             A RIVPACS-type predictive model predicts the taxonomic assemblage of macroinvertebrates, fish, or periphyton that one would expect to find in an aquatic ecosystem, if that ecosystem were in a minimally-disturbed "reference" condition. The expected assemblage is then compared with the assemblage that is observed by sampling the ecosystem. Discrepancies between the two assemblages indicate the degree of ecosystem stress or impairment.

            A full discussion of predictive modeling methods is provided by the Western Center for Monitoring and Assessment of Freshwater Ecosystems, http://129.123.10.240/wmcportal/DesktopDefault.aspx.

            PREDICTIVE_MODEL_SCRIPTS_V3.ZIP contains scripts for building and applying predictive models. The scripts are written in the R computing language, which is available free from http://www.r-project.org/. 

Version 3 (June 25, 2007) includes the BC index of compositional dissimilarity between  observed and expected assemblages.

Download PREDICTIVE_MODEL_SCRIPTS_V3.1.ZIP.

            The scripts are written for use by experienced R programmers. Users will need to modify some scripts to suit their particular data sets.

Features include:

  1. Creation and manipulation of site-by-taxa data matrices, including random subsampling to a fixed count.

  2. Options for different dissimilarity measures and clustering algorithms, including flexible-beta clustering and options for dendrogram pruning..

  3. Options for all-subsets or stepwise discriminant function analysis.

  4. Predictions for new sites, including assessment of site outlier status.

  5. Calibration and predictions for null models.

  6. O/E and BC indices.

 For additional information see the following articles, available from the senior author:

Van Sickle, J., D.P. Larsen and C.P. Hawkins. 2007. Exclusion of rare taxa affects performance of the O/E index in bioassessments. Journal of the North American Benthological Society 26, 319-331.

Van Sickle, J., David D. Huff, and C.P. Hawkins (2006). Selecting discriminant function models for predicting the expected richness of aquatic macroinvertebrates. Freshwater Biology 51, 359-372.

Van Sickle, J., C.P. Hawkins, D.P. Larsen and A.T. Herlihy. (2005). A null model for the expected macroinvertebrate assemblage in streams. Journal of the North American Benthological Society 24, 178-191.

 

John Van Sickle.

US Environmental Protection Agency

National Health and Environmental Effects Laboratory, Western Ecology Division
200 SW 35th St.
Corvallis, OR 97333
ph: 541-754-4314,   fax: 541-754-4716
Email: VanSickle.John@epa.gov 

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