Seasonal Patterns of Phytoplankton Taxon Richness in Lakes: Effects of Temperature, Turnover and Abundance

Phytoplankton in Deep Lakes of the Dinaric Karst: Functional Biodiversity and Main Ecological Features

Phytoplankton is a polyphyletic group of organisms that responds rapidly to environmental conditions and provides a reliable response to changes, making it a good ecological indicator for water quality monitoring. However, a gradient is almost essential for a reliable relationship between pressure and impact. In a low-gradient environment, ingenuity is required to outsmart the limitations of the commonly used linear relationship. Here, we examine changes in biomass and functional biodiversity by analysing larger data sets (2013-2022) in six ecologically diverse, natural, deep Croatian karst lakes with low nutrient gradients using nonlinear correlation coefficients and multivariate analyses in 209 samples. We found that phytoplankton biomass was most strongly influenced by nutrients, salinity and alkalinity, while light availability and total nitrogen strongly influenced phytoplankton functional biodiversity. An additional analysis of the TN:TP ratio revealed that the oligotrophic Lake Vransko is nitrogen-limited, and lakes Kozjak and Prošće are phosphorus-limited. This further clarified the relationship of phytoplankton to nutrients despite the low gradient. The complex analysis in this study provides a new perspective for predicting changes in the structure and succession of phytoplankton in deep karst lakes for successful management under apparent anthropogenic pressure and climate change.

Water turbidity dynamics using random forest in the Yangtze River Delta Region, China

Turbidity is a water quality indicator that is essential for the sustainable development of aquatic ecosystems and the protection of biodiversity. The turbidity of different water surfaces and its response mechanisms to regional climatic factors and human activities in the Yangtze River Delta Region (YRDR), an important rapid economic development region in China, remain poorly understood. To enhance the knowledge of turbidity variations and dominant drivers of YRDR water surfaces, a complete long-term turbidity series was obtained using Landsat images from 1990 to 2020. The results show that the turbidity trend differed from -1.3 NTU/yr to 0.7 NTU/yr in different water surfaces. Turbidity decreased significantly in the mainstream of the Yangtze River (MYR), aquaculture ponds (AP) and other water bodies, whilst increasing significantly in the medium lakes (ML) and mainstream of the Qiantang River (MQR). Meanwhile, no significant changes in turbidity were observed in the great lakes (GL) and small lakes (SL). Rather than climatic factors, urbanisation and decreasing wastewater discharge were the dominant drivers of turbidity trends during the study period. In addition, ecological engineering in AP increased water transparency. The Three Gorges Dam also decreased turbidity in MYR. Increasing turbidity in the downstream of MQR was driven by increasing seasonal water surfaces and reclamation projects near Hangzhou Bay. GL faced no significant increase in turbidity due to the offset of afforestation to urbanisation-induced turbidity increase. These findings provide important information for government decision-making for subsequent aquatic environmental protection and restoration in the YRDR.

Early warning signals have limited applicability to empirical lake data

Research aimed at identifying indicators of persistent abrupt shifts in ecological communities, a.k.a regime shifts, has led to the development of a suite of early warning signals (EWSs). As these often perform inaccurately when applied to real-world observational data, it remains unclear whether critical transitions are the dominant mechanism of regime shifts and, if so, which EWS methods can predict them. Here, using multi-trophic planktonic data on multiple lakes from around the world, we classify both lake dynamics and the reliability of classic and second generation EWSs methods to predict whole-ecosystem change. We find few instances of critical transitions, with different trophic levels often expressing different forms of abrupt change. The ability to predict this change is highly processing dependant, with most indicators not performing better than chance, multivariate EWSs being weakly superior to univariate, and a recent machine learning model performing poorly. Our results suggest that predictive ecology should start to move away from the concept of critical transitions, developing methods suitable for predicting resilience loss not limited to the strict bounds of bifurcation theory.

Assessment of cyanotoxins in water and fish in an African freshwater lagoon (Lagoon Aghien, Ivory Coast) and the application of WHO guidelines

In comparison with northern countries, limited data are available on the occurrence and potential toxicity of cyanobacterial blooms in lakes and ponds in sub-Saharan countries. With the aim of enhancing our knowledge on cyanobacteria and their toxins in Africa, we performed a 17-month monitoring of a freshwater ecosystem, Lagoon Aghien (Ivory Coast), which is used for multiple practices by riverine populations and for drinking water production in Abidjan city. The richness and diversity of the cyanobacterial community were high and displayed few variations during the entire survey. The monthly average abundances ranged from 4.1 × 104 to 1.8 × 105 cell mL-1, with higher abundances recorded during the dry seasons. Among the five cyanotoxin families analyzed (anatoxin-a, cylindrospermopsin, homoanatoxin, microcystins, saxitoxin), only microcystins (MC) were detected with concentrations ranging from 0 to 0.364 μg L-1 in phytoplankton cells, from 32 to 1092 μg fresh weight (FW) kg-1 in fish intestines, and from 33 to 383 μg FW kg-1 in fish livers. Even if the MC concentrations in water and fish are low, usually below the thresholds defined in WHO guidelines, these data raise the issue of the relevance of these WHO guidelines for sub-Saharan Africa, where local populations are exposed throughout the year to these toxins in multiple ways.

Heavy Metals Exacerbate the Effect of Temperature on the Growth of Chlorella sp.: Implications on Algal Blooms and Management

With the accelerated urbanization and rapid development of the industrial and agricultural sectors, concern about the pollution of water environments is becoming more widespread. Algal blooms of varying sizes are becoming increasingly frequent in lakes and reservoirs; temperatures, nutrients, heavy metals, and dissolved oxygen are the factors that influence algal bloom occurrence. However, knowledge of the combined effect of heavy metals and temperature on algal growth remains limited. Thus, this study investigated how specific concentrations of heavy metals affect algal growth at different temperatures; to this end, two heavy metals were used (0.01 mg/L Pb2+ and 0.05 mg/L Cr6+) at three incubation temperatures (15, 25, and 30 °C) with the alga Chlorella sp. A higher incubation temperature contributed to a rise in soluble proteins, which promoted algal growth. The density of algal cells increased with temperature, and catalase (CAT) decreased with increasing temperature. Chlorella sp. growth and catalase activity were optimal at 30 °C (algal cell density: 1.46 × 107 cell/L; CAT activity: 29.98 gprot/L). Pb2+ and Cr6+ significantly promoted Chlorella sp. growth during incubation at 25 and 30 °C, respectively. At specific temperatures, 0.01 mg/L Pb2+ and 0.05 mg/L Cr6+ promoted the production of soluble proteins and, hence, the growth of Chlorella sp. The results provide a useful background for the mitigation and prevention of algal blooms.