Trophic status and lake depth play important roles in determining the nutrient-chlorophyll a relationship: Evidence from thousands of lakes globally

A fundamental problem in lake eutrophication management is that the nutrient-chlorophyll a (Chl a) relationship shows high variability due to diverse influences of for example lake depth, lake trophic status, and latitude. To accommodate the variability induced by spatial heterogeneity, a reliable and general insight into the nutrient-Chl a relationship may be achieved by applying probabilistic methods to analyze data compiled across a broad spatial scale. Here, the roles of two critical factors determining the nutrient-Chl a relationship, lake depth and trophic status, were explored by applying Bayesian networks (BNs) and a Bayesian hierarchical linear regression model (BHM) to a compiled global dataset from 2849 lakes and 25083 observations. We categorized the lakes into three groups (shallow, transitional, and deep) according to mean and maximum depth relative to mixing depth. We found that despite a stronger effect of total phosphorus (TP) and total nitrogen (TN) on Chl a when combined, TP played a dominant role in determining Chl a, regardless of lake depth. However, when the lake was hypereutrophic and/or TP was >40 μg/L, TN had a greater impact on Chl a, especially in shallow lakes. The response curve of Chl a to TP and TN varied with lake depth, with deep lakes having the lowest yield Chl a per unit of nutrient, followed by transitional lakes, while shallow lakes had the highest ratio. Moreover, we found a decrease of TN/TP with increasing Chl a concentrations and lake depth (represented as mixing depth/mean depth). Our established BHM may help estimating lake type and/or lake-specific acceptable TN and TP concentrations that comply with target Chl a concentrations with higher certainty than can be obtained when bulking all lake types.

Water depth and land-use intensity indirectly determine phytoplankton functional diversity and further regulate resource use efficiency at a multi-lake scale

Biodiversity-ecosystem functioning relationships under multiple pressures have recently been the subject of broad studies. For the key primary producer in aquatic ecosystems, phytoplankton, several studies have focused on trait-based functional diversity (FD) and the related functioning (e.g., resource use efficiency, RUE), and their linkages. However, investigations of the effects of environmental factors at different levels (e.g., land use, lake morphometry, climate and nutrients) on FD and RUE are sparse. We developed a data-driven-model framework to simultaneously elucidate the effects of multiple drivers on FD (functional diversity based on dendrograms, FDc and functional richness, FRic) and RUE (of nitrogen and phosphorus) of phytoplankton based on data from 68 Yunnan-Guizhou Plateau lakes, Southwest China. We found that the concentration of total phosphorus, which is mainly affected by land-use intensity and influenced by water depth, was the primary (positive) driver of changes in both FDc and FRic, while RUE was mainly explained by phytoplankton FD (i.e., FRic). These results indicate that water depth and land-use intensity influence indirectly phytoplankton FD and further regulate RUE. Moreover, nonlinear correlations of RUE with FRic were found, which may be caused by interspecific competition and niche differentiation of the phytoplankton community related to nutrient levels. Our finding may help managers to set trade-off targets between FD and RUE in lake ecosystems except for extremely polluted ones, in which the thresholds derived from the Bayesian network, of total phosphorus, total nitrogen and land-use intensity were approximately 0.04 mg/L, 0.50 mg/L and 244 (unitless), respectively. The probability of meeting the RUE objectives was lower in shallow lakes than in deep lakes, but for FRic the opposite was observed.

Strong turbulence accelerates sediment nitrification-denitrification for nitrogen loss in shallow lakes

Due to energy dissipation, turbulent energy reaching bed sediment greatly differs in lakes with different depths, which potentially affects sediment denitrification and thereby nitrogen loss. In this study, we explored the impacts of turbulent energy reaching sediment on sediment nitrification rate using turbulence simulation experiments, and analyzed its role in determining sediment nitrogen loss in global lakes by investigating the relationship between denitrification rate with lake depth. Results demonstrated that sediment denitrification rate is affected by water depth in lakes with a depth of <~10 m, in which the rate was negatively correlated with lake depth, and maintained stably at low levels of <2.4 mg N m^-2 day^-1 in lakes with a depth of >~10 m. In shallow lakes, stronger turbulence reaching on sediment yielded higher nitrogen loss rate. Compare with the control, cumulated nitrogen loss from sediment increased by 10% at the turbulent velocity of 4.33 cm s^-1 upon sediment. It is possibly because turbulence promoted faster transport of oxygen to surface sediment and enhanced the mineralization of buried organic matters to feed nitrification, which subsequently accelerated denitrification and thereby nitrogen loss. This study can add to our understanding of the role of lake morphology in nitrogen biogeochemical cycles.

Performance trade-off across a natural resource gradient

An important environmental factor determining both phytoplankton and zooplankton community composition is lake depth and thermal stratification. However, there is little information on how the interaction between zooplankton grazers and their phytoplankton food changes along an environmental gradient of lake depth. We contrasted resource availability for daphniid zooplankton populations living in two shallow, unstratified lakes and in two deep, stratified lakes using a novel growth bioassay. Stratified lakes had consistently lower resource richness than shallow unstratified lakes. To test whether resources were important in explaining differences in daphniid composition of shallow and deep lakes, we performed reciprocal transplant experiments. We raised daphniids typical of shallow (Ceriodaphnia reticulata) and deep (Daphnia dentifera) lakes in the resources from replicate shallow and deep lakes and monitored survival and reproduction. The two species exhibited a performance trade-off, measured by life table r and R ₀, across a gradient in natural resource richness. D. dentifera had higher relative fitness than C. reticulata when raised in the poorest resource environment from a deep lake. However, under richer resource conditions typical of shallow lakes, C. reticulata outperformed D. dentifera. We further created a gradient in natural resource quantity (by dilution) to test whether this trade-off in species relative fitness involved aspects of resource quality. No trade-off in species performance was evident across the dilution gradient, indicating that resource quality was important to the trade-off. We conclude that shifts in daphniid species composition along a gradient of lake depth involve an adaptive trade-off in ability to exploit rich versus poor resource quality.