Tracking Extensive Portfolio of Cyanotoxins in Five-Year Lake Survey and Identifying Indicator Metabolites of Cyanobacterial Taxa.

Cyanobacterial blooms require monitoring, as they pose a threat to ecosystems and human health, especially by the release of toxins. Along with widely reported microcystins, cyanobacteria coproduce other bioactive metabolites; however, information about their dynamics in surface waters is sparse. We investigated dynamics across full bloom successions throughout a five-year lake monitoring campaign (Greifensee, Switzerland) spanning 150 sampling dates. We conducted extensive suspect screening of cyanobacterial metabolites using the database CyanoMetDB. Across all 850 samples, 35 metabolites regularly co-occurred. Microcystins were present in 70% of samples, with [d-Asp3,(E)-Dhb7]MC-RR reaching concentrations of 70 ng/L. Anabaenopeptins, meanwhile, were detected in 95% of all samples with concentrations of Oscillamide Y up to 100-fold higher than microcystins. Based on LC-MS response and frequency, we identified indicator metabolites exclusively produced by one of three cyanobacteria isolated from the lake, these being [d-Asp3,(E)-Dhb7]MC-RR from Planktothrix sp. G2020, Microginin 761B from Microcystis sp. G2011, and Ferintoic acid B from Microcystis sp. G2020. These indicators showed distinct temporal trends and peaking seasons that reflect the variance in either the abundance of the producing cyanobacteria or their toxin production dynamics. Our approach demonstrates that selecting high LC-MS response and frequent and species-specific indicator metabolites can be advantageous for cyanobacterial monitoring.

Phytoplankton and cyanobacteria abundances in mid-21st century lakes depend strongly on future land use and climate projections.

Land use and climate change are anticipated to affect phytoplankton of lakes worldwide. The effects will depend on the magnitude of projected land use and climate changes and lake sensitivity to these factors. We used random forests fit with long-term (1971-2016) phytoplankton and cyanobacteria abundance time series, climate observations (1971-2016), and upstream catchment land use (global Clumondo models for the year 2000) data from 14 European and 15 North American lakes basins. We projected future phytoplankton and cyanobacteria abundance in the 29 focal lake basins and 1567 lakes across focal regions based on three land use (sustainability, middle of the road, and regional rivalry) and two climate (RCP 2.6 and 8.5) scenarios to mid-21st century. On average, lakes are expected to have higher phytoplankton and cyanobacteria due to increases in both urban land use and temperature, and decreases in forest habitat. However, the relative importance of land use and climate effects varied substantially among regions and lakes. Accounting for land use and climate changes in a combined way based on extensive data allowed us to identify urbanization as the major driver of phytoplankton development in lakes located in urban areas, and climate as major driver in lakes located in remote areas where past and future land use changes were minimal. For approximately one-third of the studied lakes, both drivers were relatively important. The results of this large scale study suggest the best approaches for mitigating the effects of human activity on lake phytoplankton and cyanobacteria will depend strongly on lake sensitivity to long-term change and the magnitude of projected land use and climate changes at a given location. Our quantitative analyses suggest local management measures should focus on retaining nutrients in urban landscapes to prevent nutrient pollution from exacerbating ongoing changes to lake ecosystems from climate change.

A brief guide for the measurement and interpretation of microbial functional diversity.

The importance of functional diversity for the functioning and behaviour of microbial communities is clear, yet the widespread incorporation of functional diversity measurements into environmental microbiology study designs remains surprisingly limited. This may, at least to some extent, be a consequence of the unique conceptual and methodological challenges to measuring functional diversity in microbial communities. To facilitate the increased incorporation of functional diversity measurements into environmental microbiology study designs, we review here the process and some key caveats for measuring functional diversity and provide specific examples. We highlight three main decision points and provide guidance to making these decisions based on the underlying mechanisms for how functional diversity relates to an ecosystem process or property of interest. We discuss the selection of an appropriate type of functional trait, selection of the specificity at which functional diversity will be measured, and selection of an appropriate metric for estimating functional diversity from quantitative measures of those traits. We further discuss decisions regarding the use of one- or multi-dimensional measures of functional diversity and how advances in the field of trait-based community ecology could be applied or adapted to address questions in environmental microbiology.

Storm impacts on phytoplankton community dynamics in lakes.

In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short-term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well-developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short- and long-term. We summarize the current understanding of storm-induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.

Second-order phase transition in phytoplankton trait dynamics.

Key traits of unicellular species, such as cell size, often follow scale-free or self-similar distributions, hinting at the possibility of an underlying critical process. However, linking such empirical scaling laws to the critical regime of realistic individual-based model classes is difficult. Here, we reveal new empirical scaling evidence associated with a transition in the population and the chlorophyll dynamics of phytoplankton. We offer a possible explanation for these observations by deriving scaling laws in the vicinity of the critical point of a new universality class of non-local cell growth and division models. This "criticality hypothesis" can be tested through new scaling predictions derived for our model class, for the response of chlorophyll distributions to perturbations. The derived scaling laws may also be generalized to other cellular traits and environmental drivers relevant to phytoplankton ecology.

Biodiversity Drives Micropollutant Biotransformation in Freshwater Phytoplankton Assemblages.

Biotransformation of chemical pollutants is an ecological process requiring multifunctionality (multiple metabolic pathways) and, potentially, high biodiversity. Phytoplankton communities are highly diverse functionally and taxonomically and co-occur with complex mixtures of organic pollutants in aquatic environments. Here, we investigated how phytoplankton species richness (SR) and class richness (CR) determine the biotransformation of a mixture of 37 structurally diverse pollutants using laboratory experiments and analysis of high-resolution mass spectrometry data. Laboratory phytoplankton communities were assembled from pure cultures by creating a gradient from one to five taxonomic groups, and 5 to 11 total species, in defined medium. The biotransformation of pollutants over 6 days and the total number of transformed chemicals increased with CR for 13 considerably transformed compounds. The total number of transformation products (TPs, up to 42) was positively affected by both CR and SR: CR had a positive effect on stable TPs found, and SR led to more transient TPs. Our data indicate that both taxonomic and functional diversity are important for biotransformation of anthropogenic chemicals in phytoplankton and suggest that plankton biodiversity could play a role in the remediation of pollutant loads in aquatic ecosystems.

The predictability of a lake phytoplankton community, over time-scales of hours to years.

Forecasting changes to ecological communities is one of the central challenges in ecology. However, nonlinear dependencies, biotic interactions and data limitations have limited our ability to assess how predictable communities are. Here, we used a machine learning approach and environmental monitoring data (biological, physical and chemical) to assess the predictability of phytoplankton cell density in one lake across an unprecedented range of time-scales. Communities were highly predictable over hours to months: model R2 decreased from 0.89 at 4 hours to 0.74 at 1 month, and in a long-term dataset lacking fine spatial resolution, from 0.46 at 1 month to 0.32 at 10 years. When cyanobacterial and eukaryotic algal cell densities were examined separately, model-inferred environmental growth dependencies matched laboratory studies, and suggested novel trade-offs governing their competition. High-frequency monitoring and machine learning can set prediction targets for process-based models and help elucidate the mechanisms underlying ecological dynamics.

Seasonal Dynamics of Glyphosate and AMPA in Lake Greifensee: Rapid Microbial Degradation in the Epilimnion During Summer.

Occurrence and fate of glyphosate, a widely used herbicide, and its main metabolite AMPA was investigated in Lake Greifensee, Switzerland. Monthly vertical concentration profiles in the lake showed an increase of glyphosate concentrations in the epilimnion from 15 ng/L in March to 145 ng/L in July, followed by a sharp decline to <5 ng/L in August. A similar pattern was observed for AMPA. Concentrations of glyphosate and AMPA in the two main tributaries generally were much higher than in the lake. Simulations using a numerical lake model indicated that a substantial amount of glyphosate and AMPA dissipated in the epilimnion, mainly in July and August, with half-lives of only ≈2-4 days which is ≫100 times faster than in the preceding months. Fast dissipation coincided with high water temperatures and phytoplankton densities, and low phosphate concentrations. This indicates that glyphosate might have been used as an alternative phosphorus source by bacterio- and phytoplankton. Metagenomic analysis of lake water revealed the presence of organisms known to be capable of degrading glyphosate and AMPA.

Shifts of community composition and population density substantially affect ecosystem function despite invariant richness.

There has been considerable focus on the impacts of environmental change on ecosystem function arising from changes in species richness. However, environmental change may affect ecosystem function without affecting richness, most notably by affecting population densities and community composition. Using a theoretical model, we find that, despite invariant richness, (1) small environmental effects may already lead to a collapse of function; (2) competitive strength may be a less important determinant of ecosystem function change than the selectivity of the environmental change driver and (3) effects on ecosystem function increase when effects on composition are larger. We also present a complementary statistical analysis of 13 data sets of phytoplankton and periphyton communities exposed to chemical stressors and show that effects on primary production under invariant richness ranged from -75% to +10%. We conclude that environmental protection goals relying on measures of richness could underestimate ecological impacts of environmental change.

Sedimentary DNA Reveals Cyanobacterial Community Diversity over 200 Years in Two Perialpine Lakes.

We reconstructed cyanobacterial community structure and phylogeny using DNA that was isolated from layers of stratified sediments spanning 200 years of lake history in the perialpine lakes Greifensee and Lake Zurich (Switzerland). Community analysis based on amplification and sequencing of a 400-nucleotide (nt)-long 16S rRNA fragment specific to Cyanobacteria revealed operational taxonomic units (OTUs) capturing the whole phylum, including representatives of a newly characterized clade termed Melainabacteria, which shares common ancestry with Cyanobacteria and has not been previously described in lakes. The reconstruction of cyanobacterial richness and phylogenetic structure was validated using a data set consisting of 40 years of pelagic microscopic counts from each lake. We identified the OTUs assigned to common taxa known to be present in Greifensee and Lake Zurich and found a strong and significant relationship (adjusted R2 = 0.89; P < 0.001) between pelagic species richness in water and OTU richness in the sediments. The water-sediment richness relationship varied between cyanobacterial orders, indicating that the richness of Chroococcales and Synechococcales may be underestimated by microscopy. PCR detection of the microcystin synthetase gene mcyA confirmed the presence of potentially toxic cyanobacterial taxa over recent years in Greifensee and throughout the last century in Lake Zurich. The approach presented in this study demonstrates that it is possible to reconstruct past pelagic cyanobacterial communities in lakes where the integrity of the sedimentary archive is well preserved and to explore changes in phylogenetic and functional diversity over decade-to-century timescales. IMPORTANCE: Cyanobacterial blooms can produce toxins that affect water quality, especially under eutrophic conditions, which are a consequence of human-induced climate warming and increased nutrient availability. Lakes worldwide have suffered from regular cyanobacterial blooms over the last century. The lack of long-term data limits our understanding of how these blooms form. We successfully reconstructed the past diversity of whole cyanobacterial communities over two hundred years by sequencing genes preserved in the sediments of two perialpine lakes in Switzerland. We identified changes in diversity over time and validated our results using existing data collected in the same two lakes over the past 40 years. This work shows the potential of our approach for addressing important ecological questions about the effects of a changing environment on lake ecology.

Cyanobacteria Affect Fitness and Genetic Structure of Experimental Daphnia Populations.

Zooplankton communities can be strongly affected by cyanobacterial blooms, especially species of genus Daphnia, which are key-species in lake ecosystems. Here, we explored the effect of microcystin/nonmicrocystin (MC/non-MC) producing cyanobacteria in the diet of experimental Daphnia galeata populations composed of eight genotypes. We used D. galeata clones hatched from ephippia 10 to 60 years old, which were first tested in monocultures, and then exposed for 10 weeks as mixed populations to three food treatments consisting of green algae combined with cyanobacteria able/unable of producing MC. We measured the expression of nine genes potentially involved in Daphnia acclimation to cyanobacteria: six protease genes, one ubiquitin-conjugating enzyme gene, and two rRNA genes, and then we tracked the dynamics of the genotypes in mixed populations. The expression pattern of one protease and the ubiquitin-conjugating enzyme genes was positively correlated with the increased fitness of competing clones in the presence of cyanobacteria, suggesting physiological plasticity. The genotype dynamics in mixed populations was only partially related to the growth rates of clones in monocultures and varied strongly with the food. Our results revealed strong intraspecific differences in the tolerance of D. galeata clones to MC/non-MC-producing cyanobacteria in their diet, suggesting microevolutionary effects.

Warming underpins community turnover in temperate freshwater and terrestrial communities.

Rising temperatures are leading to increased prevalence of warm-affinity species in ecosystems, known as thermophilisation. However, factors influencing variation in thermophilisation rates among taxa and ecosystems, particularly freshwater communities with high diversity and high population decline, remain unclear. We analysed compositional change over time in 7123 freshwater and 6201 terrestrial, mostly temperate communities from multiple taxonomic groups. Overall, temperature change was positively linked to thermophilisation in both realms. Extirpated species had lower thermal affinities in terrestrial communities but higher affinities in freshwater communities compared to those persisting over time. Temperature change's impact on thermophilisation varied with community body size, thermal niche breadth, species richness and baseline temperature; these interactive effects were idiosyncratic in the direction and magnitude of their impacts on thermophilisation, both across realms and taxonomic groups. While our findings emphasise the challenges in predicting the consequences of temperature change across communities, conservation strategies should consider these variable responses when attempting to mitigate climate-induced biodiversity loss.

Assessing triclosan-induced ecological and trans-generational effects in natural phytoplankton communities: a trait-based field method.

We exposed replicated phytoplankton communities confined in semi-permeable membrane-based mesocosms to 0, 0.1, 1 and 10 µg L(-1) triclosan (TCS) and placed them back in their original environment to investigate the occurrence of trans-generational responses at individual, population and community levels. TCS diffused out of mesocosms with a half-life of less than 8 h, so that only the parental generation was directly stressed. At the beginning of the experiment and after 7 days (approximately 2 generations) we analysed responses in the phytoplankton using scanning flow-cytometry. We acquired information on several individually expressed phenotypic traits, such as size, biovolume, pigment fluorescence and packaging, for thousands of individuals per replicated population and derived population and community aggregated traits. We found significant changes in community functioning (increased productivity in terms of biovolume and total fluorescence), with maximal effects at 1 µg L(-1) TCS. We detected significant and dose-dependent responses on population traits, such as changes in abundance for several populations, increased average size and fluorescence of cells, and strong changes in within-population trait mean and variance (suggesting micro-evolutionary effects). We applied the Price equation approach to partition community effects (changes in biovolume or fluorescence) in their physiological and ecological components, and quantified the residual component (including also evolutionary responses). Our results suggested that evolutionary or inheritable phenotypic plasticity responses may represent a significant component of the total observed change following exposure and over relatively small temporal scales.

Disruption of ecological networks in lakes by climate change and nutrient fluctuations.

Climate change interacts with local processes to threaten biodiversity by disrupting the complex network of ecological interactions. While changes in network interactions drastically affect ecosystems, how ecological networks respond to climate change, in particular warming and nutrient supply fluctuations, is largely unknown. Here, using an equation-free modelling approach on monthly plankton community data in ten Swiss lakes, we show that the number and strength of plankton community interactions fluctuate and respond nonlinearly to water temperature and phosphorus. While lakes show system-specific responses, warming generally reduces network interactions, particularly under high phosphate levels. This network reorganization shifts trophic control of food webs, leading to consumers being controlled by resources. Small grazers and cyanobacteria emerge as sensitive indicators of changes in plankton networks. By exposing the outcomes of a complex interplay between environmental drivers, our results provide tools for studying and advancing our understanding of how climate change impacts entire ecological communities.

Reducing contrast agent residuals in hospital wastewater: the GREENWATER study protocol.

The potential enviromental impact of iodinated (ICAs) and gadolinium-based contrast agents (GBCAs) have recently come under scrutiny, considering the current nonselective wastewater treatment. However, their rapid excretion after intravenous administration could allow their potential recovery by targeting hospital sewage. The GREENWATER study aims to appraise the effective quantities of ICAs and GBCAs retrievable from patients' urine collected after computed tomography (CT) and magnetic resonance imaging (MRI) exams, selecting ICA/GBCA per-patient urinary excretion and patients' acceptance rate as study endpoints. Within a prospective, observational, single-centre, 1-year framework, we will enrol outpatients aged ≥ 18 years, scheduled to perform contrast-enhanced CT or MRI, willing to collect post-examination urine in dedicated canisters by prolonging their hospital stay to 1 h after injection. Collected urine will be processed and partially stored in the institutional biobank. Patient-based analysis will be performed for the first 100 CT and 100 MRI patients, and then, all analyses will be conducted on the pooled urinary sample. Quantification of urinary iodine and gadolinium will be performed with spectroscopy after oxidative digestion. The evaluation of the acceptance rate will assess the "environmental awareness" of patients and will aid to model how procedures to reduce ICA/GBCA enviromental impact could be adapted in different settings. Key points • Enviromental impact of iodinated and gadolinium-based contrast agents represents a growing point of attention.• Current wastewater treatment is unable to retrieve and recycle contrast agents.• Prolonging hospital stay may allow contrast agents retrieval from patients' urine.• The GREENWATER study will assess the effectively retrievable contrast agents' quantities.• The enrolment acceptance rate will allow to evaluate patients' "green sensitivity".

Reversal in the relationship between species richness and turnover in a phytoplankton community.

Negative relationships between species richness and the rate of compositional turnover are common, suggesting that diverse communities have greater stability than depauperate ones; however, the mechanistic basis for this pattern is still widely debated. Species richness and turnover can covary either because they are mechanistically linked or because they share common environmental drivers. Few empirical studies have combined long-term changes in community composition with multiple drivers of environmental change, and so little is known about how the underlying mechanisms of species coexistence interact with changes in the mean and variability of environmental conditions. Here, we use a 33 year long time series (1976-2008) of phytoplankton community composition from Lake Zurich, to examine how environmental variation influences the relationship between richness and annual turnover. We find that the relationship between richness and annual turnover reverses midway through the time series (1992-1993), leading to a hump-shaped relationship between species richness and annual turnover. Using structural equation modeling we show that annual turnover and diversity are independently associated with different drivers of environmental change. Furthermore, we find that the observed annual sequences of community assembly give rise to rates of species accumulation that are more heterogeneous through time than expected by chance, likely owing to a high proportion of species showing significant autocorrelation and to strong positive covariation in the occurrences of species.

Biological pump control of the fate and distribution of hydrophobic organic pollutants in water and plankton.

The goal of this study was to experimentally assess the coupling between primary producer biomass dynamics and the distribution and fate of persistent organic pollutants (POPs) in a lake pelagic ecosystem. This was done by following the short-term evolution of polychlorinated biphenyl (PCB) concentrations in water and biota (phytoplankton and zooplankton) and the variability of bioconcentration (BCF), biomagnification (BMF), and bioaccumulation (BAF) factors during the development of a typical spring ecological progression in which the phytoplankton bloom is followed by a peak in the zooplankton abundance. The bulk of compounds with log K(OW) > 6.5 in the lake epilimnion was mainly associated with primary producer biomass. The phytoplankton biological pump was a major driver of POP export from the epilimnion, causing the decline of dissolved-phase concentrations. The BCF of phytoplankton for the more hydrophobic PCBs showed minima during the period of biomass climax. The concentration in the zooplankton of all selected PCBs sharply declined from March to May, with BAFs having minima in the post algal bloom phase. Biomagnification occurred during the pre algal bloom and algal bloom phases but appeared to be absent during the post algal bloom. This study highlights the occurrence of a prompt and complex response in the fate and distribution of POPs to dynamic biogeochemical control. Within the frame of the ecological succession, phytoplankton and zooplankton biomass dynamics produced bioaccumulation metrics varying over 1-2 orders of magnitude in the time frame of a few weeks and resulted in reduced trophic web exposure.

A risk assessment of Pseudomonas aeruginosa in swimming pools: a review.

Despite routine monitoring and disinfection, treated swimming pools are frequently contaminated with the opportunistic pathogen Pseudomonas aeruginosa, which can represent a significant public health threat. This review was undertaken to identify the current understanding of risk factors associated with pool operation with respect to P. aeruginosa. The ecology and factors that promote growth of P. aeruginosa in the pool environment are complex and dynamic and so we applied a systematic risk assessment approach to integrate existing data, with the aim to improve pool management and safety. Sources of P. aeruginosa, types of infections, dose responses, routes of transmission, as well as the efficacy of current disinfectant treatments were reviewed. This review also highlights the critical knowledge gaps that are required for a more robust, quantitative risk assessment of P. aeruginosa. Quantitative risk management strategies have been successfully applied to drinking water systems and should similarly be amenable to developing a better understanding of the risk posed by P. aeruginosa in swimming pools.

An automated platform for phytoplankton ecology and aquatic ecosystem monitoring.

High quality monitoring data are vital for tracking and understanding the causes of ecosystem change. We present a potentially powerful approach for phytoplankton and aquatic ecosystem monitoring, based on integration of scanning flow-cytometry for the characterization and counting of algal cells with multiparametric vertical water profiling. This approach affords high-frequency data on phytoplankton abundance, functional traits and diversity, coupled with the characterization of environmental conditions for growth over the vertical structure of a deep water body. Data from a pilot study revealed effects of an environmental disturbance event on the phytoplankton community in Lake Lugano (Switzerland), characterized by a reduction in cytometry-based functional diversity and by a period of cyanobacterial dominance. These changes were missed by traditional limnological methods, employed in parallel to high-frequency monitoring. Modeling of phytoplankton functional diversity revealed the importance of integrated spatiotemporal data, including circadian time-lags and variability over the water column, to understand the drivers of diversity and dynamic processes. The approach described represents progress toward an automated and trait-based analysis of phytoplankton natural communities. Streamlining of high-frequency measurements may represent a resource for understanding, modeling and managing aquatic ecosystems under impact of environmental change, yielding insight into processes governing phytoplankton community resistance and resilience.

Reconciling trait based perspectives along a trait-integration continuum.

Trait based ecology has developed fast in the last decades, aiming to both explain mechanisms of community assembly, and predict patterns in nature, such as the effects of biodiversity shifts on key ecosystem processes. This body of work has stimulated the development of several conceptual frameworks and analytical methods, as well as the production of trait databases covering a growing number of taxa and organizational levels (from individuals to guilds). However, this breeding ground of novel concepts and tools currently lacks a general and coherent framework, under which functional traits can help ecologists organize their research aims, and serve as the common currency to unify several scientific disciplines. Specifically, we see a need to bridge the gaps between community ecology, ecosystem ecology, and evolutionary biology, in order to address the most pressing environmental issues of our time. To achieve this integration goal, we define a trait-integration continuum, which reconciles alternative trait definitions and approaches in ecology. This continuum outlines a coherent progression of biological scales, along which traits interact and hierarchically integrate from genetic information, to whole organism fitness-related traits, to trait syndromes and functional groups. Our conceptual scheme proposes that lower-level trait integration is closer to the inference of ecoevolutionary mechanisms determining population and community properties, whereas higher-level trait integration is most suited to the prediction of ecosystem processes. Within these two extremes, trait integration varies on a continuous scale, which relates directly to the inductive-deductive loop that should characterize the scientific method. With our proposed framework, we aim to facilitate scientists in contextualising their research based on the trait-integration levels that matter most to their specific goals. Explicitly acknowledging the existence of a trait-integration continuum is a promising way for framing the appropriate questions, thus obtaining reliable answers and results that are comparable across studies and disciplines.