Environmental drivers alter PUFA content in littoral macroinvertebrate assemblages via changes in richness and abundance.

Shallow littoral areas in lakes are productive and highly diverse ecotonal zones, providing habitats for both invertebrate and vertebrate species. We developed a Bayesian modeling framework to elucidate the relationships between environmental drivers (lake typology, habitat, water chemistry, and latitude) and taxon richness, abundance, as well as the content of polyunsaturated fatty acids (PUFAs) in littoral macroinvertebrate communities in 95 boreal lakes. PUFAs, particularly arachidonic acid (ARA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA), are critical micronutrients to maintain normal physiological functions in consumers. Lake typology was a significant predictor for PUFA content in the invertebrate assemblages, which was connected to taxon richness and/or abundance. Benthic communities in large humus-poor or nutrient-rich lakes displayed higher abundance, taxon richness, and more PUFA-rich taxa, whereas those in medium- and large-sized humic (color 30-90 mg Pt/L) and humus-rich lakes (color >90 mg Pt/L) were characterized by decreased abundance and subsequently low PUFA content. The abundance, taxon richness, and nutritional quality of the communities were also strongly related to latitude. Lakes with lower pH were characterized by lower benthic invertebrate diversity and low frequency of taxa with high somatic EPA and DHA content. The complexity of littoral habitats dominated by various macrophyte assemblages creates an environment that favors higher benthic abundance and increased presence of taxonomic groups with high PUFA content. Nutritional quality of benthic invertebrates for upper trophic levels can be modulated by a complex interplay between external stressors and abiotic factors that typically shape the structure of littoral benthic communities. Supplementary Information: The online version contains supplementary material available at 10.1007/s00027-023-00996-2.

Characterizing the river water quality in China: Recent progress and on-going challenges.

Food production systems, urbanization, and other anthropogenic activities dramatically alter natural hydrological and nutrient cycles, and are primarily responsible for water quality impairments in China's rivers. This study compiled a 16-year (2003-2018) dataset of river water quality (161,337 records from 2424 sites), watershed/landscape features, and meteorological conditions to investigate the spatial water quality patterns and underlying drivers of river impairment (defined as water quality worse than Class V according to China's Environmental Quality Standards for Surface Waters, GB3838-2002) at a national scale. Our analysis provided evidence of a distinct water quality improvement with a gradual decrease in the frequency of prevalence of anoxic conditions, an alleviation of the severity of heavy metal pollution, whereas the cultural eutrophication has only been moderately mitigated between 2003 and 2018. We also identified significant spatial variation with relatively poorer water quality in eastern China, where 17.2% of the sampling sites registered poor water quality conditions, compared with only 4.6% in western China. Total phosphorus (TP) and ammonia-nitrogen (NH3-N) are collectively responsible for >85% of the identified incidences of impaired conditions. Bayesian modelling was used to delineate the most significant covariates of TP/NH3-N riverine levels in six large river basins (Liao, Hai, Yellow, Yangtze, Huai, and Pearl). Water quality impairments are predominantly shaped by anthropogenic drivers (82.5% for TP, 79.5% for NH3-N), whereas natural factors appear to play a secondary role (20.5% for TP, 17.5% for NH3-N). Two indicator variables of urbanization (urban areal extent and nighttime light intensity) and farmland areal extent were the strongest predictors of riverine TP/NH3-N levels and collectively accounted for most of the ambient nutrient variability. We concluded that there is still a long way to go in order to eradicate eutrophication and realize acceptable ecological conditions. The design of the remedial measures must be tailored to the site-specific landscape characteristics, meteorological conditions, and should also consider the increasing importance of non-point source pollution and internal nutrient loading.

The magnitude and drivers of harmful algal blooms in China's lakes and reservoirs: A national-scale characterization.

Harmful algal blooms (HABs) can have dire repercussions on aquatic wildlife and human health, and may negatively affect recreational uses, aesthetics, taste, and odor in drinking water. The factors that influence the occurrence and magnitude of harmful algal blooms and toxin production remain poorly understood and can vary in space and time. It is within this context that we use machine learning (ML) and two 14-year (2005-2018) data sets on water quality and meteorological conditions of China's lakes and reservoirs to shed light on the magnitude and associated drivers of HAB events. General regression neural network (GRNN) models are developed to predict chlorophyll a concentrations for each lake and reservoir during two study periods (2005-2010 and 2011-2018). The developed models with an acceptable model fit are then analyzed by two indices to determine the areal HAB magnitudes and associated drivers. Our national assessment suggests that HAB magnitudes for China's lakes and reservoirs displayed a decreasing trend from 2006 (1363.3 km2) to 2013 (665.2 km2), and a slightly increasing trend from 2013 to 2018 (775.4 km2). Among the 142 studied lakes and reservoirs, most severe HABs were found in Lakes Taihu, Dianchi and Chaohu with their contribution to the total HAB magnitude varying from 89.2% (2013) to 62.6% (2018). HABs in Lakes Taihu and Chaohu were strongly associated with both total phosphorus and nitrogen concentrations, while our results were inconclusive with respect to the predominant environmental factors shaping the eutrophication phenomena in Lake Dianchi. The present study provides evidence that effective HAB mitigation may require both nitrogen and phosphorus reductions and longer recovery times; especially in view of the current climate-change projections. ML represents a robust strategy to elucidate water quality patterns in lakes, where the available information is sufficient to train the constructed algorithms. Our mapping of HAB magnitudes and associated environmental/meteorological drivers can help managers to delineate hot-spots at a national scale, and comprehensively design the best management practices for mitigating the eutrophication severity in China's lakes and reservoirs.

Reduction of industrial iron pollution promotes phosphorus internal loading in eutrophic Hamilton Harbour, Lake Ontario, Canada.

Diagenetic sediment phosphorus (P) recycling is a widespread phenomenon, which causes degradation of water quality and promotes harmful algal blooms in lakes worldwide. Strong P coupling with iron (Fe) in some lakes is thought to inhibit diagenetic P efflux, despite elevated P concentrations in the sediment. In these sediments, the high Fe content leads to P scavenging on ferric Fe near the sediment surface, which increases the overall P retention. Reduced external Fe inputs in such lakes due to industrial pollution control may lead to unintended consequences for sediment P retention. Here, we study sediment geochemistry and sediment-water interactions in the historically polluted Hamilton Harbour (Lake Ontario, Canada) which has undergone 30 years of restoration efforts. We investigate processes controlling diagenetic P recycling, which has previously been considered minor due to historically high Fe loading. Our results demonstrate that present sediment P release is substantial, despite sediment Fe content reaching 6.5% (dry weight). We conclude that the recent improvement of wastewater treatment and industrial waste management practices has reduced Fe pollution, causing a decrease in diagenetically reactive Fe phases, resulting in the reduction of the ratio of redox-sensitive P and Fe, and the suppression of P scavenging on Fe oxyhydroxides.

The re-eutrophication of Lake Erie: Harmful algal blooms and hypoxia.

Lake Erie supplies drinking water to more than 11 million consumers, processes millions of gallons of wastewater, provides important species habitat and supports a substantial industrial sector, with >$50 billion annual income to tourism, recreational boating, shipping, fisheries, and other industries. These and other key ecosystem services are currently threatened by an excess supply of nutrients, manifested in particular by increases in the magnitude and extent of harmful planktonic and benthic algal blooms (HABs) and hypoxia. Widespread concern for this important international waterbody has been manifested in a strong focus of scientific and public material on the subject, and commitments for Canada-US remedial actions in recent agreements among Federal, Provincial and State agencies. This review provides a retrospective synthesis of past and current nutrient inputs, impairments by planktonic and benthic HABs and hypoxia, modelling and Best Management Practices in the Lake Erie basin. The results demonstrate that phosphorus reduction is of primary importance, but the effects of climate, nitrogen and other factors should also be considered in the context of adaptive management. Actions to reduce nutrient levels by targeted Best Management Practices will likely need to be tailored for soil types, topography, and farming practices.

Delineation of the role of nutrient variability and dreissenids (Mollusca, Bivalvia) on phytoplankton dynamics in the Bay of Quinte, Ontario, Canada.

The Bay of Quinte, a Z-shaped embayment at the northeastern end of Lake Ontario, has a long history of eutrophication problems primarily manifested as spatially extensive algal blooms and predominance of toxic cyanobacteria. The purpose of this study was to identify the structural changes of the phytoplankton community induced by two environmental alterations: point-source phosphorus (P) loading reduction in the late 1970s and establishment of dreissenid mussels in the mid-1990s. A combination of statistical techniques was used to draw inference about compositional shifts of the phytoplankton assemblage, the consistency of the seasonal succession patterns along with the mechanisms underlying the algal biovolume variability in the Bay of Quinte over the past three decades. Based on a number of diversity and similarity indices, the algal assemblages in the upper and middle segments of the Bay are distinctly different from those typically residing in the outer segments. Our analysis also identified significant differences among the phytoplankton communities, representing the pre- and post-P control as well as the pre- and post-dreissenid invasion periods. Recent shifts in phytoplankton community composition were mainly associated with increased frequency of occurrence of toxin-producing Microcystis outbreaks and reduced biovolume of N2 fixers, such as Aphanizomenon and Anabaena. Bayesian hierarchical models were developed to elucidate the importance of different abiotic factors (light attenuation, water temperature, phosphorus, and ammonium) on total cyanobacteria, Microcystis, Aphanizomenon, and Anabaena relative biovolume. Our modelling exercise suggests that there is significant spatial heterogeneity with respect to the role of the factors examined, and thus total phosphorus alone cannot always explain the year-to-year variability of cyanobacteria succession patterns in the system. The lessons learned from the present analysis will be helpful to the water quality criteria setting process and could influence the management decisions in order to delist the system as an Area of Concern.

Continuous Bayesian network for studying the causal links between phosphorus loading and plankton patterns in Lake Simcoe, Ontario, Canada.

An ecosystem perspective to restoring beneficial uses in Areas of Concern can be interpreted as a shift from the traditional elucidation of simple cause-effect relationships to a multicausal way of thinking that more effectively accommodates ecosystem complexity. This holistic management paradigm has also pervaded the contemporary ecological modeling practice, making compelling the adoption of more sophisticated ecosystem modeling tools. In this study, our primary objective is to develop a Bayesian hierarchical network of simple ecological models for Lake Simcoe, Ontario, Canada, aiming to establish a realistic representation of the causal connections among exogenous nutrient loading, ambient nutrient conditions, and epilimnetic plankton dynamics. In particular, we used a spatially explicit simple mass-balance model forced with idealized sinusoidal loading to predict total phosphorus concentrations. A structural equation model was then used to delineate the interplay among nutrients, ambient light conditions, phytoplankton, and herbivorous biomass. Our analysis highlights the strength of the causal linkages between total phosphorus and water clarity with phytoplankton as well as the capacity of zooplankton grazing to modulate the algal standing crop. Our Bayesian network is also used to examine the exceedance frequency of threshold values for total phosphorus (15 µg/L) and chlorophyll a (4 µg/L) concentrations under scenarios of phosphorus loading reduction. Our study suggests that a 15% phosphorus loading decrease will still result in >25% violations of the 4 µg chla/L value in the two embayments of Lake Simcoe (Cook's Bay and Kempenfelt Bay). The TP levels will decrease in response to the exogenous loading reductions and this improvement will be primarily manifested in the northcentral segments of the system.

Non-point-source impacts on stream nutrient concentrations along a forest to urban gradient.

We conducted statistical analyses of a 10-year record of stream nutrient and sediment concentrations for 17 streams in the greater Seattle region to determine the impact of urban non-point-source pollutants on stream water quality. These catchments are dominated by either urban (22-87%) or forest (6-73%) land cover, with no major nutrient point sources. Stream water phosphorus concentrations were moderately strongly (r2=0.58) correlated with catchment land-cover type, whereas nitrogen concentrations were weakly (r2=0.19) and nonsignificantly (at alpha<0.05) correlated with land cover. The most urban streams had, on average, 95% higher total phosphorus (TP) and 122% higher soluble reactive phosphorus (SRP) and 71% higher turbidity than the most forested streams. Nitrate (NO3), ammonium (NH4), and total suspended solids (TSS) concentrations did not vary significantly with land cover. These results suggest that urbanization markedly increased stream phosphorus concentrations and modestly increased nitrogen concentrations. However, nutrient concentrations in Seattle region urban streams are significantly less than those previously reported for agricultural area streams.

A daily time series analysis of stream water phosphorus concentrations along an urban to forest gradient.

During a 1-year period, we sampled stream water total phosphorus (TP) concentrations daily and soluble reactive phosphorus (SRP) concentrations weekly in four Seattle area streams spanning a gradient of forested to urban-dominated land cover. The objective of this study was to develop time series models describing stream water phosphorus concentration dependence on seasonal variation in stream base flows, short-term flow fluctuations, antecedent flow conditions, and rainfall. Stream water SRP concentrations varied on average by +/- 18% or +/- 5.7 microg/L from one week to another, whereas TP varied +/- 48% or +/- 32.5 microg/L from one week to another. On average, SRP constituted about 47% of TP. Stream water SRP concentrations followed a simple sine-wave annual cycle with high concentrations during the low-flow summer period and low concentrations during the high-flow winter period in three of the four study sites. These trends are probably due to seasonal variation in the relative contributions of groundwater and subsurface flows to stream flow. In forested Issaquah Creek, SRP concentrations were relatively constant throughout the year except during the fall, when a major salmon spawning run occurred in the stream and SRP concentrations increased markedly. Stream water SRP concentrations were statistically unrelated to short-term flow fluctuations, antecedent flow conditions, or rainfall in each of the study streams. Stream water TP concentrations are highly variable and strongly influenced by short-term flow fluctuations. Each of the processes assessed had statistically significant correlations with TP concentrations, with seasonal base flow being the strongest, followed by antecedent flow conditions, short-term flow fluctuations, and rainfall. Times series models for each individual stream were able to predict approximately 70% of the variability in the SRP annual cycle in three of the four streams (r2 = 0.57-0.81), whereas individual TP models explained approximately 50% of the annual cycle in all streams (r2 = 0.39-0.59). Overall, time series models for SRP and TP dynamics explained 82% and 76% of the variability for these variables, respectively. Our results indicate that SRP, the most biologically available and therefore most important phosphorus fraction, has simpler and easier-to-predict seasonal and weekly dynamics.