Long-term ecological and environmental data represent one of the keys to understanding many, if not most, of the multiple stressors currently impacting aquatic ecosystems. My research uses biological (from phytoplankton to fish) as well as physical and chemical long-term and large-scale monitoring data to:
improve the early detection of environmental problems
understand ecosystem responses to multiple stressors
investigate interactions and feedbacks in aquatic systems
Another aspect of my research focuses on understanding the interactions and feedbacks between a lake's biology and its physical and chemical attributes as well as the environmental context in which it is embedded. One way to understand biological patterns and processes are via an examination of their spatial and temporal variability - a fundamental property of nature and one that is interdisciplinary in its scope. Ultimately, incorporating variability will improve our attempts to monitor, manage, and understand aquatic ecosystems. I combine experimental studies, paleoecology, and long-term monitoring to:
quantify baseline variabilty
predict the response of variability to disturbance events
develop variance-based metrics to detect and predict environmental change
Automated Sensing of Lakes
We are currently developing Dorset’s capacity for acquiring automated high-frequency monitoring data in Muskoka area lakes and elsewhere. These data offer insight into processes occurring over short periods of time (minutes to hours) and can be used to investigate a variety of phenomena in lakes, such as:
lake turnover, stratification and internal mixing dynamics
oxygen depletion and lake metabolism
GEISHA (Global Evaluation of the Impacts of Storms on freshwater Habitat and structure of phytoplankton Assemblages)
Storms are expected to become more intense and more common as a result of climate change. Because storms influence environmental characteristics of lakes important to phytoplankton (e.g., temperature, light, and nutrients), storms may represent significant environmental disturbances which could alter phytoplankton niche-space and thus community dynamics. However, our understanding of linkages among storms, lake physics, phytoplankton traits and ecosystem function is limited. The international collaboration, GEISHA, is conducting analyses on traditional long-term and novel high-frequency datasets from lakes across the globe to better understand the patterns, mechanisms, and ecological implications of storms on phytoplankton communities.
The Canadian Lake Pulse Network
This NSERC-funded Strategic Network will assess lake health across the country, developing better metrics to quantify ecosystem function and using the past and present to develop future scenarios of change in aquatic ecosystem in different ecoregions. The network is focussed on addressing 4 major themes:
Where, by how much and why have Canadian lakes changed during the Anthropocene?
How do taxonomic, molecular and biochemical features of planktonic, benthic and microbial communities change with lake alteration and which ones can most effectively be used as indicators of the health of Canadian lakes?
What are the optical, morphometric and watershed properties of Canadian lakes that can be applied to “scale up” assessments of health to groups of lakes through remote sensing and spatial modelling approaches?
How will lake ecosystems and their services respond to different scenarios of environmental change?
Sensing the America's Freshwater Ecosystem Risk (SAFER) from climate change
The connections between climate change/variability and threats to aquatic ecosystems are poorly understood and difficult to assess because they depend on regional responses to both global and local factors. Furthermore, because the value of ecosystems services will also vary regionally, assessing (and mitigating) these threats will require a multi-disciplinary approach - one that addresses scientific, socioeconomic and cultural aspects - in a tightly coupled natural-human system. As such, SAFER's objectives are to:
employ freshwater ecosystems as "sentinels"or "sensors" of climate variability and watershed processes and investigate their interaction with other multiple stressors to assess risks to ecosystem services across the Americas, and
determine management and mitigation strategies which are both technically and economically feasible as well as culturally acceptable.
B.Sc., Marine Biology, University of Guelph, Guelph, ON, Canada.
M.Sc., Biology, Lakehead University, Thunder Bay, ON, Canada.
Ph.D., Biology, York University, Toronto, ON, Canada.
Postdoctoral Fellow, Limnology Laboratory, University of Regina, Regina, SK, Canada.
Research Scientist / NTL-LTER Site Manager, Center for Limnology - Trout Lake Station, University of Wisconsin - Madison, Boulder Junction, WI, USA
Tiegs, S., Costello, D., Isken, M., Woodward, G., McIntyre, P., Gessner, M., et al. (2019). Global patterns and drivers of ecosystem functioning in rivers and riparian zones. Science Advances, 5. http://doi.org/10.1126/sciadv.aav0486
Barth, L., Shuter, B., Sprules, G., Minns, C., & Rusak, J. A. (2019). Calibration of the zooplankton community size spectrum as an indicator of change in Canadian Shield lakes. Canadian Journal Of Fisheries And Aquatic Sciences, null. http://doi.org/10.1139/cjfas-2018-0371
Azan, S., Yan, N., Celis-Salgado, M., Arnott, S., Rusak, J. A., & Sutey, P. (2019). Could a residential wood ash recycling programme be part of the solution to calcium decline in lakes and forests in Muskoka (Ontario, Canada)?. Facets, 4, 69-90. http://doi.org/10.1139/facets-2018-0026
Woolway, I., Carrea, L., Merchant, C., Dokulil, M. T., De Eyto, E., DeGasperi, C. L., et al. (2018). Lake surface temperature [in State of the Climate in 2017]. In (Vol. 99, pp. 13-15). AMS100. http://doi.org/10.1175/2018BAMSStateoftheClimate.1
Leach, T. H., Beisner, B. E., Carey, C. C., Pernica, P., Rose, K. C., Huot, Y., et al. (2018). Patterns and drivers of deep chlorophyll maxima structure in 100 lakes: The relative importance of light and thermal stratification. Limnology And Oceanography, 63, 628-646. http://doi.org/10.1002/lno.10656
Bruce, L. C., Frassl, M. A., Arhonditsis, G. B., Gal, G., Hamilton, D. P., Hanson, P. C., et al. (2018). A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network. Environmental Modelling & Software, 102, 274-291. http://doi.org/10.1016/j.envsoft.2017.11.016
Hewitt, B., Lopez, L., Gaibisels, K., Murdoch, A., Higgins, S., Magnuson, J. J., et al. (2018). Historical Trends, Drivers, and Future Projections of Ice Phenology in Small North Temperate Lakes in the Laurentian Great Lakes Region. Water, 10, 70. http://doi.org/10.3390/w10010070
Velez, M., Conde, D., Lozoya, J. P., Rusak, J. A., Garcia-Rodriguez, F., Seitz, C., et al. (2018). Paleoenvironmental Reconstructions Improve Ecosystem Services Risk Assessment: Case Studies from Two Coastal Lagoons in South America. Water, 10, 1350. http://doi.org/10.3390/w10101350