In recent years, considerable efforts have been made to restore turbid, phytoplankton-dominated shallow lakes to a clear-water state with high coverage of submerged macrophytes. Various dynamic lake models with simplified physical representations of vertical gradients, such as PCLake, have been used to predict external nutrient load thresholds for such nonlinear regime shifts. However, recent observational studies have questioned the concept of regime shifts by emphasizing that gradual changes are more common than sudden shifts. We investigated if regime shifts would be more gradual if the models account for depth-dependent heterogeneity of the system by including the possibility of vertical gradients in the water column and sediment layers for the entire depth. Hence, bifurcation analysis was undertaken using the 1D hydrodynamic model GOTM, accounting for vertical gradients, coupled to the aquatic ecosystem model PCLake, which is implemented in the framework for aquatic biogeochemical modeling (FABM). First, the model was calibrated and validated against a comprehensive data set covering two consecutive 7-yr periods from Lake Hinge, a shallow, eutrophic Danish lake. The autocalibration program Auto-Calibration Python (ACPy) was applied to achieve a more comprehensive adjustment of model parameters. The model simulations showed excellent agreement with observed data for water temperature, total nitrogen, and nitrate and good agreement for ammonium, total phosphorus, phosphate, and chlorophyll a concentrations. Zooplankton and macrophyte coverage were adequately simulated for the purpose of this study, and in general the GOTM-FABM-PCLake model simulations performed well compared with other model studies. In contrast to previous model studies ignoring depth heterogeneity, our bifurcation analysis revealed that the spatial extent and depth limitation of macrophytes as well as phytoplankton chlorophyll-a responded more gradually over time to a reduction in the external phosphorus load, albeit some hysteresis effects still appeared. In a management perspective, our study emphasizes the need to include depth heterogeneity in the model structure to more correctly determine at which external nutrient load a given lake changes ecosystem state to a clear-water condition.

Climate extremes, which are steadily increasing in frequency, can have detrimental consequences for lake ecosystems. We used a state-of-the-art, one-dimensional, hydrodynamic-ecosystem model [General Ocean Turbulence Model (GOTM)-framework for aquatic biogeochemical models (FABM)-PCLake] to determine the influence of extreme climate events on a temperate and temporarily summer stratified lake (Lake Bryrup, Denmark). The model was calibrated (eight years data) and validated (two years data), and the modeled variables generally showed good agreement with observations. Then, a span of extreme warming scenarios was designed based on weather data from the heatwave seen over northern Europe in May–July 2018, mimicking situations of extreme warming returning every year, every three years, and every five years in summer and all year round, respectively. We found only modest impacts of the extreme climate events on nutrient levels, which in some scenarios decreased slightly when looking at the annual mean. The most significant impacts were found for phytoplankton, where summer average chlorophyll a concentrations and cyanobacteria biomass peaks were up to 39% and 58% higher than during baseline, respectively. As a result, the phytoplankton to nutrient ratios increased during the heat wave experiments, reflecting an increased productivity and an increased cycling of nutrients in the pelagic. The phytoplankton blooms occurred up to 15 days earlier and lasted for up to half a month longer during heat wave years relative to the baseline. Our extreme scenarios illustrated and quantified the large impacts of a past heat wave (observed 2018) and may be indicative of the future for many temperate lakes.