Using structural equation modeling to better understand microcystis biovolume dynamics in a mediterranean hypereutrophic reservoir

Integrating partial least square structural equation modelling and machine learning for causal exploration of environmental phenomena

Understanding the causes of environmental phenomena is crucial for promoting positive outcomes and mitigating negative ones. Partial least squares structural equation modelling (PLS-SEM) is becoming a valuable tool for evaluating causal relationships in ecological environment studies (EES). However, many studies using PLS-SEM often overlook nonlinear relationships and interactions between environmental factors, and have not fully utilized the powerful capabilities of machine learning. Using Gaoyang Lake in the Three Gorges Reservoir Region as a case study, this research presents a framework combining several techniques to better understand the causes of Spring Harmful Algal Blooms (Spring HABs) from 2019 to 2023. The framework uses PLS-SEM to compare and select the optimum causal structure among alternatives, Bayesian Networks (BN) to identify alternative causal pathways, Multivariate Adaptive Regression Splines (MARS) and Polynomial Regression (PR) to uncover interactions and non-linearities among predictors. Our findings indicate that, the BN-generated structure implemented in PLS-SEM had an improved Bayesian Information Criterion (BIC) score compared to the initial PLS-SEM. No interactions between latent variables were observed using MARS. However, significant non-linearities were identified using PR, and when integrated into the initial PLS-SEM, they produced the optimal model with Q2predict of 0.177, RMSE of 0.967, R2 of 0.421, and BIC of -23.497. Euphotic depth emerged as a critical factor influencing the occurrence of Spring HABs, due to its interaction with the epilimnion depth. Surface nutrient levels (indicated by total phosphorus loadings) and meteorological elements (mean air temperature and sun hours) were identified as the second and third most important latent variables, contributing 25.5 % and 13.5 % to Spring HABs, respectively. This framework is recommended for improving the causal understanding of other site-specific environmental phenomena, providing a scientific basis for more effective environmental management.

Disentangling the main factors influencing spring algal blooms in the Three Gorges Reservoir using partial least square structural equation modelling

Eutrophication and the associated algal blooms is a pervasive problem affecting global health, aquaculture, agriculture, water-related industries, and freshwater ecosystems. Spring algal blooms (SABs), which are less common than summer blooms, occur during a time that is thought to be less advantageous due to mild winds, little precipitation, and a relatively small amount of NPS pollutants being transported. Thus, It is pertinent to understand further the factors influencing SABs directly and/or indirectly for improved management. Consequently, Partial least square structural equation modelling (PLS-SEM) was employed to measure the direct and indirect effects of nutrients, lake hydrodynamics (Lake HD), meteorological elements (ME), stratification, Lake Bio-Optics, and Bottom Sediment-Water interaction (BSWI) in Gaoyang Lake of the Three Gorges Reservoir which is characterized by SABs. Based on our findings, total phosphorus (TP) and total nitrogen (TN) together slightly outperformed TP alone in explaining variations in chlorophyll a (chl-a), but the difference was not statistically significant. Thus the parsimonous PLS-SEM model with TP was chosen, and it explained 66.8%, 54.0%, 21.4%, and 59.7% variation in stratification, Lake Bio-Optics, nutrients, and chl-a, respectively. Surprisingly, ME and Lake Bio-Optics had a negative total effect on chl-a during the study. The magnitude of factors influencing SAB occurrence was of the order Lake Hydrodynamics > nutrients > Bottom Sediments-Water Interphase > Lake Bio-Optics > Meteorological Elements > Stratification. This study successfully decoupled and quantified several latent variables' complex simultaneous causal effects on chl-a.

Analyzing eutrophication and harmful algal bloom dynamics in a deep Mediterranean hypereutrophic reservoir

Excessive point and non-point nutrient loadings accompanied with elevated temperatures have increased the prevalence of harmful algal bloom (HAB). HABs pose significant environmental and public health concerns, particularly for inland freshwater systems. In this study, the eutrophication and HAB dynamics in the Qaraoun Reservoir, a hypereutrophic deep monomictic reservoir suffering from poor water quality, were assessed. The reservoir was mostly phosphorus limited, and large algal particulates dominated light attenuation in the water column. During bloom events, surface chlorophyll-a concentrations increased up to 961.3 µg/L, while surface concentrations of ammonia and ortho-phosphate were rapidly depleted; surface dissolved oxygen reached supersaturation levels and surface pH levels were up to 3 units higher than those measured in the hypolimnion. Meanwhile, measured Microcystin-LR toxin concentrations in the reservoir exceeded the World Health Organization 1 μg/L provisional guideline 45% of the times. Yet, the results showed that most of the toxins were intra-cellular, suggesting that they decayed rapidly when released into the reservoir. Results from a random forests ensemble model indicated that tracking the changes in surface dissolved oxygen levels, ammonium, ortho-phosphate, and pH can be an effective program towards predicting the reservoir's trophic state and algae blooms.

Morphological, molecular, and biochemical study of cyanobacteria from a eutrophic Algerian reservoir (Cheffia)

The cyanobacteria management in water bodies requires a deep knowledge of the community composition. Considering the reliable and thorough information provided by the polyphasic approach in cyanobacteria taxonomy, here we assess the cyanobacterial community structure of the Cheffia reservoir from Algeria. Cyanobacteria were identified on the basis of morphological traits and next-generation sequencing (NGS); toxins-related genes were localized in addition to the identification of toxins; temperature and nutrient level of water samples were also determined. The polyphasic approach was essential for cyanobacteria investigation; 28 genera were identified through 16S rRNA metabarcoding with the dominance of taxa from Microcystis (34.2%), Aphanizomenon (20.1%), and Planktothrix (20.0%), and morphological analysis revealed the association in this water body of five species within the genus Microcystis: M. aeruginosa, M. novacekii, M. panniformis, M. ichthyoblabe, and M. flos-aquae. The presence of mcyE genotypes was detected; moreover, HPLC-PDA and LC-ESI-MS/MS revealed the production of microcystin-LR. Results obtained in our study are very important since this ecosystem is used for water supply and irrigation; as a consequence, a good water management plan is essential.

Cyanobacterial community succession and associated cyanotoxin production in hypereutrophic and eutrophic freshwaters

Cyanobacterial harmful algal blooms (cyanoHABs) in freshwater bodies are mainly attributed to excess loading of nutrients [nitrogen (N) and phosphorus (P)]. This study provides a comprehensive review of how the existing nutrient (i.e., N and P) conditions and microbial ecological factors affect cyanobacterial community succession and cyanotoxin production in freshwaters. Different eutrophic scenarios (i.e., hypereutrophic vs. eutrophic conditions) in the presence of (i) high levels of N and P, (ii) a relatively high level of P but a low level of N, and (iii) a relatively high level of N but a low level of P, are discussed in association with cyanobacterial community succession and cyanotoxin production. The seasonal cyanobacterial community succession is mostly regulated by temperature in hypereutrophic freshwaters, where both temperature and nitrogen fixation play a critical role in eutrophic freshwaters. While the early cyanoHAB mitigation strategies focus on reducing P from water bodies, many more studies show that both N and P have a profound contribution to cyanobacterial blooms and toxin production. The availability of N often shapes the structure of the cyanobacterial community (e.g., the relative abundance of N₂-fixing and non-N₂-fixing cyanobacterial genera) and is positively linked to the levels of microcystin. Ecological aspects of cyanotoxin production and release, related functional genes, and corresponding nutrient and environmental conditions are also elucidated. Research perspectives on cyanoHABs and cyanobacterial community succession are discussed and presented with respect to the following: (i) role of internal nutrients and their species, (ii) P- and N-based control vs. solely P-based control of cyanoHABs, and (iii) molecular investigations and prediction of cyanotoxin production.