A complete overview of algal blooms in Lake Geneva: shall the past shed light on the future?

Freshwater algae exhibit complex dynamics, particularly in meso-oligotrophic lakes with sudden and dramatic increases in algal biomass following long periods of low background concentration. While the fundamental prerequisites for algal blooms, namely light and nutrient availability, are well-known, their specific causation involves an intricate chain of conditions. Here we examine a recent massive Uroglena bloom in Lake Geneva (Switzerland/France). We show that a certain sequence of meteorological conditions triggered this specific algal bloom event: heavy rainfall promoting excessive organic matter and nutrients loading, followed by wind-induced coastal upwelling, and a prolonged period of warm, calm weather. The combination of satellite remote sensing, in-situ measurements, ad-hoc biogeochemical analyses, and three-dimensional modeling proved invaluable in unraveling the complex dynamics of algal blooms highlighting the substantial role of littoral-pelagic connectivities in large low-nutrient lakes. These findings underscore the advantages of state-of-the-art multidisciplinary approaches for an improved understanding of dynamic systems as a whole.

Colloids play an important role in trace metal cycling in lakes(Morel & Gschwend 1987) due to their high sorptioncapacity and long residence times. Indeed, because of Brow-nian motion, colloids do not settle individually, even in stillwater; however, they can aggregate into larger particles andstart to settle entraining bound or embedded compounds.Aggregation, and ultimately colloid removal rates, canstrongly be enhanced during a phytoplankton bloom, particu-larly through the production of sticking exopolymers (Pas-sow 2002) released by phytoplankton (Jackson & Burd1998). Sticking exopolymers are also known to promote dia-tom aggregation in both marine (Alldregde & Jackson1995 and other references in this special issue) and freshwa-ter systems (Hoffman et al. 2001).In an international project aiming to assess trace metalremoval in Lake Geneva during a phytoplanktonic bloom,colloids were extensively studied during 3field campaignsbefore, during, and after the 2006 spring bloom. Changes insize, concentration, composition, and aggregation rate of col-loids with time will be extensively presented elsewhere (V.Chanudet, unpubl.). Here we present specifically the resultsof the second campaign (bloom), in which phytoplankton wasexpected to most influence the colloidal particle size distri-bution and play a significant role in the aggregation process.To verify this assumption, we carried out experiments on col-loid aggregation using a single particle counter (SPC), aunique tool allowing measurements of colloids in the sizerange 0.1–2µm at natural concentrations. We were able todemonstrate that during an early phase of bloom in lakes,small centric diatoms settle individually rather than as aggre-gates, possibly because of a low concentration of exopoly-mers.

Advances in forecasting harmful algal blooms using machine learning models: A case study with Planktothrix rubescens in Lake Geneva

A brief period of very clear water following the spring phytoplankton bloom has been observed in many mesotrophic and eutrophic lakes. For Lake Geneva, data on water transparency from Forel (1895) demonstrate that the phenomenon of a clear-water phase did not exist when the lake was still oligotrophic in the late nineteenth century. Comparable Secchi measurements over the last three decades indicate that the clear-water phase developed along with increasing eutrophication as a result—not of clearer water in June—but of significantly lower transparencies at the time of the spring bloom, which is usually dominated by fast-growing, nanoplanktonic algae. Generally in Lake Geneva, following this spring bloom, the numbers of cyclopoid copepods decline strongly, and the Daphnia populations explode. Severe Si limitation in May was observed in 9 out of the last 14 years. Although the sharp reduction in algal standing crop at this time of year may begin by the loss of diatoms due to nutrient stress, the development of a dramatic clear-water phase is mediated primarily by grazing, and in particular, by the grazing of Daphnia.

This manuscript presents an exhaustive analysis of a physicochemical dataset collected from Lake Geneva since 1957, offering a detailed exploration of its long-term environmental evolution. This study encompasses an array of cycles and trophic states that the lake has undergone. A critical finding is the significant influence of human activities within the catchment area, notably the introduction of substantial quantities of nutrients, especially phosphorus, into the lake’s ecosystem. This anthropogenic impact culminated in a marked ecological decline between the 1960s and 1970s, characterized by a phase of eutrophication. This period saw a surge in algal blooms and a consequent decrease in water transparency. In the 1970s, strategic interventions were implemented to address this environmental challenge. These measures, including the enhancement of phosphorus treatment at sewage facilities in the catchment area and the nationwide ban on phosphated detergents in Switzerland, proved instrumental in reducing the influx of nutrients. Consequently, a significant reduction in the lake’s phosphorus levels was observed by the 1980s. The lake is currently undergoing a re-oligotrophication process, with phosphorus concentrations indicating a mesotrophic state. However, it is noteworthy that the biological components of the lake are exhibiting a slower recovery rate in adapting to reduced nutrient levels, in contrast to the more immediate response noted during the eutrophication phase. Despite the progress achieved, ongoing vigilance and efforts are essential to continuously monitor, identify, and manage potential sources of phosphorus pollution. This proactive approach is vital for maintaining the lake’s ecological balance and ensuring it remains free from significant algal proliferation.

Nutrient loading, in combination with climate change are important drivers of primary productivity in lakes. Understanding and forecasting future changes in primary production (PP) in response to local and global forcing are major challenges for developing sustainable lake management. The objective of this study is to understand and characterize the mechanisms underlying the large differences in observed PP rates and nutrient concentrations between two consecutive years (2012 and 2013) in Lake Geneva, Switzerland. For this purpose, we apply a one-dimensional (1D) physical–biogeochemical model system. The Framework of Aquatic Biogeochemical models (FABM) interface is used to couple the General Ocean Turbulence Model (GOTM) with a biogeochemical model, the Ecological Regional Ocean Model (ERGOM). We calibrated GOTM, by adjusting physical parameters, with the observed temperature profiles. A model calibration method is implemented to minimize model-data misfits and to optimize the biological parameters related to phytoplankton growth dynamics.According to our results, the simulated surface mixed layer depth is deeper and heat loss from the lake and turbulent kinetic energy in the water column are much higher in winter 2012 than that in 2013, pointing to a cooling-driven, deep mixing in the lake in 2012. We found significant differences in internal phosphorus loads in the epilimnion between the two years, with estimates for 2012 being higher than those for 2013. ERGOM predicts weak nutrient limitation on phytoplankton and higher growth rates in 2012. Apparently, the deep mixing event led to high turnover of nutrients (particularly dissolved inorganic phosphate) to the productive surface layers, and a massive algal bloom developed later in the productive season. In contrary, the turnover of nutrients in 2013 was weak and consequently the PP was low. Our findings demonstrate the utility of a coupled physical–biological model framework for the investigation of the meteorological and physical controls of PP dynamics in aquatic systems.

In December 2006 blooms of Oscillatoria rubescens were found in the reservoir Prizzi in Sicily. Oscillatoria is a genus of filamentous alga comprising approximately 6 species, between these the O. rubescens is sadly famous since this organism produces microcystins which are powerful hepatotoxins. Firstly found in Europe in 1825 on Geneva lake, recently (2006) those algae has been find out in Pozzillo, Nicoletti e Ancipa reservoirs (Enna Province), as well as in Prizzi (Palermo Province) and Garcia reservoirs (Trapani Province). Toxins produced by those bacteria (usually called microcystine LR-1 and LR-2) are highly toxic since they can activate oncogenes cells causing cancer pathologies on liver and gastrointestinal tract. Even if water treatment plants should ensure the provision of safe drinking water from surface waters contaminated with those toxic algae blooms, the contamination of reservoirs used for civil and agricultural supply highlights human health risks. International literature suggests a threshold value of 0.01 μgl-1 to avoid liver cancer using water coming from contaminated water bodies for a long period. Since O. rubescens activities is strongly related to phosphate and nitrogen compounds as well as to temperature and light transmission within water, the paper presents the comparison between optical properties of the water of an infested reservoir and those of a reservoir characterized by clear water. Field campaigns were carried out in February-March 2008 in order to quantify the spectral transparencies of two water bodies through the calculation of the diffuse attenuation coefficient, measuring underwater downwelling irradiance at different depths as well as water spectral reflectance. Results show that diffuse attenuation coefficient is reduced by approximately 15% reducing light penetration in the water column; coherently reflectance spectral signature generally decreases, exhibiting a characteristic peak around 703 nm not present in uncontaminated waters. Latter findings highlight the possibility to detect O. rubescens infestations using their spectral characteristics by means of multitemporal remote sensing techniques.