Toward the development of an ecosystem model ensemble to support adaptive management in Lake Ontario

Abstract

Notwithstanding the continuing advancement of our understanding of the broader ecosystem functioning in Lake Ontario, emerging evidence suggests that there are fundamental knowledge gaps to accurately describe the relationship between exogenous phosphorus (P) loading and in-lake total phosphorus (TP) concentrations. The whole-lake load appears to frequently exceed the target of 7,000 t·year-1, although the offshore-water P concentrations are consistently below the water-quality objective of 10 μg TP·L–1. Contrasting ecological conditions can prevail in different locations of Lake Ontario, owing to the significant urban footprint along the shoreline but also the capacity of dreissenid mussels to sequester P in the littoral zone. Specifically, low ambient P levels threaten fisheries productivity in the offshore waters, while nuisance benthic algae (Cladophora) and toxin-producing cyanobacteria blooms affect the aesthetics/water quality in the nearshore zone. The present study offers a technical analysis of the recent and on-going modelling work that has been conducted in Lake Ontario, and can be potentially used to address the multitude of ecosystem management challenges. Our aim is to provide an overview of all the major models developed in the area by identifying their fundamental assumptions, structural attributes, and general consistency against empirical knowledge derived from the system. The existing modelling work opted for parsimonious representations of the lower food web coupled with granular grid configurations to effectively link hydrodynamic processes and mass transport between nearshore and offshore waters. The establishment of comprehensive ecophysiological modules that will recreate the mechanisms underlying the interplay among bioavailable phosphorus, planktonic dynamics, dreissenid mussels, and Cladophora is a critical undertaking to reproduce the water quality conditions in the nearshore zone of Lake Ontario. Striving to integrate the lower food web with fisheries and ecosystem-service modelling, we also offer a technical analysis on knowledge gaps and monitoring-assessment objectives that should be addressed to ensure that ecosystem processes of management interest are adequately measured and the local modelling enterprise is focused on suitable performance indicators.