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Overview of Canada Water Network Project:
Cumulative Effects, Muskoka River



  1. Derive a conceptual model of multiple stressors and cumulative effects for the Muskoka River Watershed.
  2. Evaluate physical, chemical, and biological stressor and response indicators, and characterize baseline conditions in the Muskoka River Watershed (underpinnings of a cumulative-effects monitoring program).
  3. Model cumulative effects of multiple stressors.


Research Projects:

  1. A geographic template for cumulative-effects assessment in the Muskoka River Watershed
    Richardson, Rachel Plewes (MSc student)
    •   Classify lakes based on chemical and biological sensitivities to key
        stressors or indicators (Ca, P, DOC, Cl)
    •   Model historical variability in lake and river physics and chemistry
  2. Assessing and modelling cumulative effects on biological communities
    Gunn, Bailey, Jones
    •   Identify normal ranges of biological condition, and describe
        biological baselines, for lakes and rivers;
    •   Evaluate bioassessment indicators, and derive biocriteria for
        promising ones;
    •   Model expected biological condition under alternate futures 
  3. Establishment of biological baselines in the Muskoka River Watershed and development of a diatom index for assessing lake and riverine health
    Paterson, Hall, Winter, Mark MacDougall (MSc student)
  4. Establishment of physical baselines and hydroclimatic assessment
    Eimers, Yao, Jason Kerr (Post-doctoral fellow)
    •   Examine hydrological and meteorological records to characterize
        the range of physical conditions observed in the Muskoka River
        Watershed, and describe any trends evident in the last several
    •   Use climate scenarios to model hydrologic futures and predict
        effects on aquatic ecosystem services
  5. Drivers of declining P and rising DOC; role of wetlands/beaver ponds
    Eimers, Watmough, Kieran Pinder (MSc student)
    •   Test the hypothesis that changes in wetland cover and hydrology
        have resulted in divergent trends in P and DOC in Muskoka lakes
        (declining P, increasing DOC)
    •   Investigate the role of beaver dams in P and DOC dynamics 
  6. Interacting effects of multiple stressors on ecotoxicological thresholds (Ca and Cl ecotoxicology)
    Yan, Arran Brown (MSc student)
    •   Understand the interactive effects on Daphniids of low (and
        declining) Ca, high (and increasing) Cl, and climate warming
    •   Quantify the effects of rising Cl and food scarcity on critical Ca
  7. Establishing sustainable harvesting intensities in the Muskoka River Watershed to sustain critical Ca levels
    Watmough, Aherne, Carolyn Reid (MSc student)
    •   Use records of logging, lake chemistry, and soil chemistry, as well
        as mineral-weathering and atmospheric-deposition estimates, to
        evaluate the impact of forest harvesting on lake calcium
    •   Identify which lakes are expected to fall below critical Ca
    •   Construct a Ca mass budget for Muskoka lakes, and use this model
        to predict future Ca levels under differing forest-harvest scenarios
  8. Long-term changes in lake nutrient stoichiometry: effects on plankton productivity and species composition
    Grigull, Yan, Samaneh Gholami (PhD)
    •   Investigate relationships between lakes’ nutrient ratios and the
        functional/taxonomic composition of plankton communities
    •   Determine if plankton biomarkers provide early warning of shifting
        nutrient availability in lakes
  9. Evaluation and application of INCA-P and HBV to surface waters in the Muskoka River Watershed
    Dillon, Aherne, Jill Crossman (Post-doctoral researcher)
  10. Evaluation and application of SWAT model to surface waters in the Muskoka River Watershed
    James, Yao
  11. Controls on algal blooms and predictive modeling of bloom occurrence in the Muskoka River Watershed
    Paterson, Winter, Dillon, Anurani Persaud (Post-doctoral researcher)
    •   Explore relationships between physical (e.g. climate), chemical (P,
        N, DOC), and biological variables (algae abundance and
        community composition) in lakes
    •   Determine the optimal spatial and temporal scale for monitoring
        phytoplankton assemblages
    •   Forecast likelihood of algae blooms in years having different
        weather patterns