Increasing Carbon-to-Phosphorus Ratio (C:P) from Seston as a Prime Indicator for the Initiation of Lake Reoligotrophication

Photolysis triggers multiple microbial responses: New insights of phosphorus compensation for algal blooms

Photolysis and microbial degradation enabling the rapid mineralization of organic phosphorus constitute the crucial mechanism for phosphorus compensation during algal bloom outbreaks in shallow lakes. This study explored the key pathways of microbial degradation of algae-derived organic phosphorus (ADOP) exacerbated by photolysis through molecular biology techniques. The results showed that photolysis could exacerbate microbial degradation, and the effects on microbial degradation were multifaceted. The photolysis process changes the composition of dissolved organic matter (DOM) in the environment and generates DOM components required for microbial activity, among which the saturated compounds significantly promote the increase of microbial biomass. Differential analysis showed that the photolysis process mainly affected the distribution of bacteria and fungi. The saturated compounds and highly aromatic compounds accompanying the photolysis process stimulated the increase of the abundance of phosphorus-cycling functional bacteria and related functional genes. Simultaneously, photolysis also promoted the growth of extracellular reactive oxygen species (ROS)-producing bacteria, and enhanced biological metabolism by stimulating the significant upregulation and differentiation of multiple enzyme protein subunits in cells. In summary, various changes in microorganisms caused by photolysis enhanced their mineralization of ADOP. These results bring new insights into the mechanism of the persistence of algal blooms.

Differential Adsorption of Dissolved Organic Matter and Phosphorus on Clay Mineral in Water-Sediment System

Lake sediments connection to the biogeochemical cycling of phosphorus (P) and carbon (C) influences streamwater quality. However, it is unclear whether and how the type of sediment controls P and C cycling in water. Here, the adsorption behavior of montmorillonite (Mt) with different interlayer cations (Na+, Ca2+, or Fe3+) on dissolved organic matter (DOM) and P was investigated to understand the role of Mt in regulating the organic carbon-to-phosphate (OC/P) ratio within freshwater systems. The adsorption capacity of Fe-Mt for P was 3.2-fold higher than that of Ca-Mt, while it was 1/3 lower for DOM. This dissimilarity in adsorption led to an increased OC/P in Fe-Mt-dominated water and a decreased OC/P in Ca-Mt-dominated water. Moreover, an in situ atomic force microscope and high-resolution mass spectrometry revealed molecular fractionation mechanisms and adsorptive processes. It was observed that DOM inhibited the nucleation and crystallization processes of P on the Mt surface, and P affected the binding energy of DOM on Mt through competitive adsorption, thereby governing the interfacial P/DOM dynamics on Mt substrates at a molecular level. These findings have important implications for water quality management, by highlighting the role of clay minerals as nutrient sinks and providing new strategies for controlling P and C dynamics in freshwater systems.

Non-photochemical quenching estimates from in situ spectroradiometer measurements: implications on remote sensing of sun-induced chlorophyll fluorescence in lakes

Quantum yield of fluorescence (ϕ_F) is key to interpret remote measurements of sun-induced fluorescence (SIF), and whether the SIF signal is governed by photochemical quenching (PQ) or non-photochemical quenching (NPQ). Disentangling PQ from NPQ allows using SIF estimates in various applications in aquatic optics. However, obtaining ϕ_F is challenging due to its high temporal and physiological variability, and the combined measurements needed to enclose all relevant optical paths. In inland waters, this type of data is scarce and information on diurnal and seasonal ϕ_F dynamics are almost unknown. Using an autonomous hyperspectral Thetis profiler in Lake Geneva, we demonstrate how to estimate ϕ_F using an ensemble of in-situ measurements acquired between 2018 to 2021. We use vertical and temporal changes in retrieved ϕ_F to determine NPQ and PQ conditions. We observed NPQ in 36% of the total daytime profiles used in the ϕ_F analysis. While downwelling irradiance is a significant contributor to ϕ_F, its role cannot be easily interpreted. Other factors such as phytoplankton photoregulation and assemblages also likely play significant roles in quenching mechanisms. We conclude that an adapted approach exploiting in-situ data is suitable to determine diurnal and seasonal NPQ occurrence, and helps develop future remote sensing algorithms.

A hybrid empirical and parametric approach for managing ecosystem complexity: Water quality in Lake Geneva under nonstationary futures

This paper develops a hybrid approach to account for the complex interactions affecting lake water quality and its management in a nonlinear, changing world. The approach uses data to leverage our first-principles understanding of the mechanisms operating on dissolved oxygen in the lake. This yields a manageable, but more complete systems perspective for environmental management of the lake under climate change, where our analysis suggests that multiple modes of intervention may be necessary to achieve a healthy lake.

Severe deterioration of water quality in lakes, characterized by overabundance of algae and declining dissolved oxygen in the deep lake (DO_B), was one of the ecological crises of the 20th century. Even with large reductions in phosphorus loading, termed “reoligotrophication,” DO_B and chlorophyll (CHL) have often not returned to their expected pre–20th-century levels. Concurrently, management of lake health has been confounded by possible consequences of climate change, particularly since the effects of climate are not neatly separable from the effects of eutrophication. Here, using Lake Geneva as an iconic example, we demonstrate a complementary alternative to parametric models for understanding and managing lake systems. This involves establishing an empirically-driven baseline that uses supervised machine learning to capture the changing interdependencies among biogeochemical variables and then combining the empirical model with a more conventional equation-based model of lake physics to predict DO_B over decadal time-scales. The hybrid model not only leads to substantially better forecasts, but also to a more actionable description of the emergent rates and processes (biogeochemical, ecological, etc.) that drive water quality. Notably, the hybrid model suggests that the impact of a moderate 3°C air temperature increase on water quality would be on the same order as the eutrophication of the previous century. The study provides a template and a practical path forward to cope with shifts in ecology to manage environmental systems for non-analogue futures.