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

Purpose:

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
       decades
   •   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
       thresholds 
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
       thresholds
   •   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