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Towards generalised reference condition models for environmental assessment: a case study on rivers in Atlantic
D G Armanini1, W A Monk, L Carter
1Environment Canada @ Canadian Rivers Institute, Department of Biology, University of New Brunswick, 10 Bailey Drive, PO Box 4400, Fredericton, NB, E3B 5A3, Canada. d.armanini@protheagroup.com
Environmental Monitoring and Assessment
|December 20, 2012
Summary
A new model predicts river ecological status in Atlantic Canada using the River Invertebrate Prediction and Classification System (RIVPACS) approach. It integrates diverse data, enabling robust national-scale river biomonitoring despite data challenges.
Area of Science:
- Environmental Science
- Ecology
- Water Resource Management
Background:
- Ecological status assessment of Canadian rivers relies on reference condition models.
- National-scale monitoring is hindered by geographical and data limitations, especially in Atlantic Canada.
- No current ecological assessment system exists for Atlantic Canadian rivers.
Purpose of the Study:
- To develop a regional-scale reference condition model for Atlantic Canada.
- To adapt the River Invertebrate Prediction and Classification System (RIVPACS) for broader applicability.
- To overcome data scarcity and interoperability issues in river biomonitoring.
Main Methods:
- Utilized biological monitoring data from wadeable streams across Atlantic Canada.
- Integrated freely available, nationally consistent Geographic Information System (GIS) environmental data.
- Developed a predictive model using GIS-based environmental variables, accommodating data from different studies and sampling methods.
Main Results:
- Successfully generated a robust predictive model using diverse, multi-study datasets.
- Demonstrated the model's improved performance compared to a null model.
- Showed that derived ecological quality ratio data responded to observed stressors in a test dataset.
Conclusions:
- It is feasible to create robust predictive models from varied biological monitoring data.
- GIS-based environmental variables can effectively drive regional-scale river ecological assessment.
- The developed approach offers a standardized method for large-scale river biomonitoring with global potential.
