RIVPACS models for predicting the expected macroinvertebrate fauna and assessing the ecological quality of rivers

By R. Clarke, J. Wright, M. Furse. 2003

291 citations recorded by the source corpus.

Subfields: Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/ea4753892192ed92f61d62c37c70d61b3e87f022

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Charles P. Hawkins
2. Jodi G. McClory
3. Joshua Ladau
4. J. Sickle
5. D. Huff
6. B. Chessman
7. R. Knapp
8. J. A. Thomas

In Nature and Landscape Conservation

1. Charles P. Hawkins
2. Jodi G. McClory
3. Joshua Ladau
4. J. Sickle
5. D. Huff
6. B. Chessman
7. R. Knapp
8. J. A. Thomas

Citations in the corpus

• FAUNA OF YOSEMITE NATIONAL PARK LAKES HAS LOW RESISTANCE BUT HIGH RESILIENCE TO FISH INTRODUCTIONS (2005, background): “New sites are therefore not simply assigned to their most likely group based on their environmental attributes but are instead assigned to each of the classification groups probabilistically (Clarke et al. 2003).”
• Monitoring change in the abundance and distribution of insects using butterflies and other indicator groups (2005, result): “predicts, from the physical environment, the macroinvertebrate community expected for any site if it were in an unstressed condition, and compares that prediction with the observed community found on the site, thereby generating an index of its ecological quality status (Clarke et al. 2003).”
• Selecting discriminant function models for predicting the expected richness of aquatic macroinvertebrates (2006, methodology): “that are relatively unaltered by pollution or other anthropogenic stress (Hawkins & Carlisle, 2001; Clarke et al., 2003).”
• Biological assessments of Appalachian streams based on predictive models for fish, macroinvertebrate, and diatom assemblages (2008, methodology): “The procedures described by Moss et al. (1987) and Clarke et al. (2003) were used to determine if the predictor variable values of each test site belonged to the same statistical population as the reference sites.”
• Effects of sampling error on bioassessments of stream ecosystems: application to RIVPACS-type models (2004, methodology): “We used selected variables to create a final DF model and calculate the posterior probabilities of sites belonging to each class (see Moss et al. 1987, and Clarke et al. 2003 for calculation specifics), i.e., estimates of Pg (step 2 of Model construction procedures, above).”
• Data quality, performance, and uncertainty in taxonomic identification for biological assessments (2008, methodology): “…most often take the form of a multimetric index (Karr et al. 1986, Hughes et al. 1998, Barbour et al. 1999, Hill et al. 2000, 2003) or a predictive model based on the River Invertebrate Prediction and Classification System (RIVPACS; Clarke et al. 1996, 2003, Hawkins et al. 2000, Hawkins 2006).”
• The European Water Framework Directive at the age of 10: a critical review of the achievements with recommendations for the future. (2010, background): “…suggest that sitespecific assessments have higher sensitivity, particularly for water bodies close to typology boundaries and in the absence of undisturbed sites for a water body type (Clarke et al., 2003; Pont et al., 2006; Cardoso et al., 2007; Aroviita et al., 2009a,b; Carvalho et al., 2009).”
• Bioassessment without reference sites: use of environmental filters to predict natural assemblages of river macroinvertebrates (2004, methodology): “This method, the AUStralian RIVer Assessment System (AUSRIVAS), is a predictive modelling approach adapted from the British River InVertebrate Prediction And Classification System (RIVPACS; Clarke et al. 2003) for Australia’s National River Health Program (Davies 2000).”