The ecology of lakes and rivers in the southern boreal shield: water quality, community structure, and cumulative effects

Abstract

Cumulative effects are the collective ecological effects of multiple human activities. Cumulative effects assessment (CEA) is concerned with quantifying effects of natural environmental factors and human activities. CEA has not lived up to its promise as a precautionary instrument for sustainability, in part because our knowledge of stressors and their effects is elementary; monitoring systems (needed to characterize ecological condition and how it changes over time) are insufficient; and numerical methods for associating stressors and effects, and for forecasting development outcomes, are lacking. This thesis reviews the environmental appraisal literature to synthesize CEA’s theoretical underpinnings, articulate its impediments, and establish that ecological monitoring and modelling activities are critical to success. Three research chapters overcome several scientific barriers to effective CEA. Data from spatial and temporal surveys of lake and stream water chemistry and benthic community structure are used to evaluate candidate monitoring indicators, identify minimally impacted reference waterbodies, characterize baseline water quality and biological condition, and quantify cumulative effects of land use and natural environmental variation (spatial survey: 107 lakes and 112 streams sampled in 2012 or 2013; temporal survey: 19 lakes sampled between 1993 and 2016). The research was conducted in Canada’s Muskoka River Watershed, a 5660 km2 area of Precambrian Shield that drains to Lake Huron. This area’s combination of extensive remaining natural areas and pervasive human influence makes it ideal for studying cumulative effects. It is also characterized by many lakes and their connecting stream and river channels, which integrate effects of stressors in their catchments and constitute logical focal points for CEA. Moreover, the local planning authority (District Municipality of Muskoka) is striving to implement CEA and establish a cumulative effects monitoring program centered on water as its foremost resource; therefore, practical applications of the research have, been identified. Universal numerical methods, which are transferrable to other study areas, are used. Random forest models (an extension of the algorithm used to produce classification or regression trees) are shown to model the singular and collective effects of land-use and natural factors on water chemistry and benthic community structure, and to quantify the sensitivities, and identify the important drivers of various chemical and biological indicators of aquatic ecosystem condition. Partial dependencies from the random forests (i.e., the mean predicted values of a given indicator that occurred across the observed range of a selected predictor) are paired with TITAN (Threshold Indicator Taxa Analysis) to investigate biological and chemical “onset-of-effect” thresholds along gradients of human development. Declining calcium concentrations and amphipod abundances are demonstrated in lakes, and generalized linear models forecast an average 57% decrease in the abundances of these animals to occur by the time lakewater calcium concentrations reach expected minima. As its key findings, the thesis highlights sensitive indicators that should be included in a cumulative effects monitoring program, and are to be preferred when forecasting outcomes of changed land-use or environmental attributes. Empirical breakpoints, where effects of stressor exposures become detectable, are also identified. These thresholds can be used to distinguish reference and impacted conditions, so that normal indicator ranges and associated assessment criteria (important CEA precursors) can be objectively derived. In addition, the potential severity of cumulative effects is exemplified by marked declines in the abundances of lake dwelling amphipods, which could propagate through food webs to substantially alter soft-water Boreal ecosystems.