An estimation of diel metabolic rates of eight limnological archetypes from Estonia using high-frequency measurements

Abstract

We employed a Bayesian model to assess the metabolic state of 8 Estonian lakes representing the 8 lake types according to the European Union Water Framework Directive. We hypothesized that long-term averages of light-related variables would be better predictors of lake metabolism than nutrient-related variables. Model input parameters were in situ high-frequency measurements of dissolved oxygen, temperature, and irradiance. Model simulations were conducted for several (5–12) diel cycles for each lake during the summer season. Accounting for uncertainty, the results from the Bayesian model revealed that 2 lakes were autotrophic for the duration of the experiment, 1 was heterotrophic, and 5 were balanced or had an ambiguous metabolic state. Cross-comparison with a traditional bookkeeping model showed that the majority of lakes were in metabolic balance. A strong coupling between primary production and respiration was observed, with the share of autochthonous primary production respired by consumers increasing with light extinction and nutrient-related variables. Unlike gross primary production, community respiration was strongly related to light extinction, dissolved organic carbon (DOC) and total phosphorus. These findings suggest that a drastic decrease in light-limited primary production along the DOC gradient counter-balanced nutrient supply in the darker lakes and thus blurred the relationship between primary production and nutrients. Thus, contrary to our hypothesis, both light and nutrient-related variables seemed to be good predictors of lake respiration and its coupling to lake primary production.