Integrated Modelling of Spatial and Temporal Heterogeneity in Trophic Shifts: A Bayesian Network Approach Based on Empirical Data Collection

Abstract

The biogeochemical cycles of carbon (C), nitrogen (N) and phosphorus (P) have been significantly altered by anthropogenic nutrient enrichment in catchments. The concentrations of nutrients in aquatic systems are closely linked to complex interactions between catchment attributes that vary with space and time such as land use, rainfall, flow velocity, riparian vegetation and geology. In aquatic systems, a shift from a mesotrophic or oligotrophic state to a eutrophied trophic state occurs when nutrient concentrations exceed the assimilation capacity of the ecosystem, leading to increased rates of primary production and microbial processes. Trophic shifts can significantly alter ecosystem processes and threaten ecosystem services in freshwater and estuarine systems. The ratios of C, N, and P within aquatic systems can regulate primary production when one or more of these nutrients are present in concentrations below that required for the growth and accumulation of primary producers. Detecting and predicting trophic shifts is difficult as a result of high spatial and temporal heterogeneity in water column nutrient concentrations and insufficient information on the thresholds of, and interactions among the biophysical and chemical drivers of trophic shifts. This limited knowledge of threshold concentrations and stoichiometric ratios of nutrients, in addition to the drivers that regulate a shift to a eutrophied state limits the large scale application of efficient management strategies.