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The presence of submerged macrophytes is a desired environmental target for coastal freshwater ecosystems. Maintaining a rich community of these species can be challenging as salinisation by sea-level rise poses an increasing threat to ecosystem integrity. We tested the effect of salinisation on the growth and germination of freshwater macrophytes experimentally using field sediment. In a 56-day experiment, a macrophyte community was exposed to salinity treatments representing seasonal water management scenarios (a decreasing salinity from 1,500 to 300 mg NaCl/L, a stable salinity of 300 mg NaCl/L, an increasing salinity from 300 to 1,500 mg NaCl/L and a stable salinity of 1,500 mg NaCl/L), crossed with treatments simulating periodic turbidity pulses. All species except Elodea nuttallii grew poorly on the saline and eutrophic sediment, reflecting the challenges of growth in eutrophic coastal systems. Surprisingly, the highest community biomass was achieved in the salinity scenario of 1,500 mg NaCl/L. In a second experiment, field-collected sediments were incubated at 300 and 1,500 mg NaCl/L salinity (representing summer and winter scenarios), and the germination capacity of the existing seedbank was quantified. Most germinated seedlings did not reach maturity irrespective of salinity treatment. This indicated that sediment salinity, rather than water column salinity, determined seedling establishment success. Interestingly, the established species were characteristic of freshwater habitats, thus indicating maladaptation of the seedbank. Our results show that a mismatch between the high salinity level of eutrophic sediment and the overlaying freshwater may hamper macrophyte growth. Furthermore, target species in coastal eutrophic freshwaters should be evaluated carefully. Elodea nuttalli, which has a wide tolerance range for nutrients and salinity, outperformed other macrophyte species in our study. Thus, species with similar traits may be most successful in establishing macrophyte stands in coastal eutropic wetlands.

Datasets and R scripts for the COVID anthropause case study sites for the publication entitled "Lessons learned from the COVID-19 anthropause in the Netherlands on urban aquatic ecosystem services provisioning and management" When using the .csv files for Figure 2B (bathing waters, file: Zwemmen buiten) and Figure 2C (national parks; files: De Alde Feanen, De Biesbosch, De Groote Peel, Dwingelderveld, Lauwersmeer and Weerribben-Wieden), make sure the dates are in the following format: dd-mm-yyyy When running the Figure 2C codes (in R script "COVID_GoogleTrends_Script"), set the working directory to a folder containing only the national parks .csv files.

Fungi and bacteria are the two dominant groups of soil microbial communities worldwide. By controlling the turnover of soil organic matter, these organisms directly regulate the exchange of carbon between the soil and the atmosphere. Fundamental differences in the physiology and life history of bacteria and fungi suggest that variation in the biogeography of soil fungal and bacterial relative abundance could drive striking differences in carbon decomposition and soil organic matter formation across different biomes. However, a lack of global and predictive information on the distribution of these organisms in terrestrial ecosystems has prevented the inclusion of soil fungal and bacterial relative abundance and the associated processes into global biogeochemical models. Here, we used a global scale dataset in the top soil surface (>3000 distinct observations of soil fungal and bacterial abundance) to generate the first quantitative and spatially high resolution (1 km) explicit map of soil fungal proportion, defined as fungi/fungi + bacteria, across terrestrial ecosystems. We reveal striking latitudinal trends where fungal dominance increases in cold and high latitude environments with large soil carbon stocks. There was strong non-linear response of fungal dominance to environmental gradient, i.e., mean annual temperature (MAT) and net primary productivity (NPP). Fungi and bacteria dominated in regions with low and high MAT and NPP, respectively, thus representing slow vs. fast soil energy channels, a concept with a long history in soil ecology. These high-resolution models provide the first steps towards representing the major soil microbial groups and their functional differences in global biogeochemical models to improve predictions of soil organic matter turnover under current and future climate scenarios. Raw datasets and global maps generated in this study are available at https://doi.org/10.6084/m9.figshare.19556419 (Yu, 2022).

Ongoing anthropogenic and climatic pressures on inland waters have made water quality management a challenge of the 21st century. A holistic catchment-scale approach to water management which includes stakeholder participation will be a key in maintaining lake health. A first step toward community engagement is to bolster environmental literacy on lake management, ecology, and eutrophication concepts of stakeholders now and in future generations. However, communicating with nonwater professionals about effects of pollution on water quality and catchment-scale interactions across space and time can be difficult. Here, we present “Flipping Lakes,” a games-based method for lake professionals to communicate and educate about catchment-level water quality management to diverse audiences. In Flipping Lakes, the players take on the role of water managers in a catchment and are tasked to prevent a lake from “flipping” from a clear to a turbid state. During the game, the catchment slowly becomes polluted by a range of sources of which the effects are exacerbated by societal or climatic scenarios. Players need to implement measures while taking into consideration the intrinsic properties of the catchment in order to keep lakes clean. The game was tested with a diverse range of user groups and was well-received. With its entertaining and accessible content, Flipping Lakes can lower communication barriers and increase understanding of difficult water quality concepts. The game is highly customizable, making it applicable to a variety of settings to support education and engagement of stakeholders and the broader community in order to address local water challenges around the globe.

Fungi and bacteria are the two dominant groups of soil microbial communities worldwide. By controlling the turnover of soil organic matter, these organisms directly regulate the cycling of carbon between the soil and the atmosphere. Fundamental differences in the physiology and life history of bacteria and fungi suggest that variation in the biogeography of relative abundance of soil fungi versus bacteria could drive striking differences in carbon decomposition and soil organic matter formation between different biomes. However, a lack of global and predictive information on the distribution of these organisms in terrestrial ecosystems has prevented the inclusion of relative abundance of soil fungi versus bacteria and the associated processes in global biogeochemical models. Here, we used a global-scale dataset of >3000 distinct observations of abundance of soil fungi versus bacteria in the surface topsoil (up to 15 cm) to generate the first quantitative and high-spatial-resolution (1 km2) explicit map of soil fungal proportion, defined as fungi/fungi + bacteria, across terrestrial ecosystems. We reveal striking latitudinal trends where fungal dominance increases in cold and high-latitude environments with large soil carbon stocks. There was a strong nonlinear response of fungal dominance to the environmental gradient, i.e., mean annual temperature (MAT) and net primary productivity (NPP). Fungi dominated in regions with low MAT and NPP and bacteria dominated in regions with high MAT and NPP, thus representing slow vs. fast soil energy channels, respectively, a concept with a long history in soil ecology. These high-resolution models provide the first steps towards representing the major soil microbial groups and their functional differences in global biogeochemical models to improve predictions of soil organic matter turnover under current and future climate scenarios. Raw datasets and global maps generated in this study are available at https://doi.org/10.6084/m9.figshare.19556419 (Yu, 2022)., Earth System Science Data, 14 (9), ISSN:1866-3516, ISSN:1866-3508

1. Parasites are generally considered the most commonly occurring type of consumers, yet their biomass and population dynamics are rarely quantified at community level. 2. Here, we used 12 years of weekly or fortnightly monitoring data (518 time points) to determine the occurrence of chytrids, fungal parasites of phytoplankton, to assess their seasonality and long-term (seasonally-detrended) dynamics in the pelagic plankton community of a temperate, eutrophic, and polymictic lake. 3. Chytrid infections were observed in c. 75% of all samples with recurrent infections in multiple host taxa. Infection prevalence was highest in spring, but infections occurred throughout the entire year with an average of 2.3 host taxa infected per time point (ranging from 0 to 10 host taxa) and an average infection prevalence of 2.78% (ranging from 0% to 47.35%). Infected host biomass equalled that of the carnivorous zooplankton and decreased over time, while infection prevalence remained unchanged. Seasonal infection prevalence increased with phytoplankton biomass, but decreased with increasing temperature and phosphorus concentrations, reflecting that peak prevalence occurred in spring when temperature and phosphorus concentrations were relatively low. In contrast, seasonally-detrended prevalence increased with temperature, but decreased with increasing phosphorus concentrations. 4. Chytrids are a common component of the pelagic plankton community with sizeable biomass and removing an—at times—substantial proportion of the primary production, challenging the long-standing underrepresentation of parasites in ecological studies. 5. Chytrids responded differentially to seasonal variation and long-term trends in host density, water temperature and nutrient availability, highlighting the need to disentangle seasonal signals from long-term changes.

Nutrients are essential resources for food production but are used inefficiently, and thereby they pollute inland and coastal waters and are lost into the oceans. Nutrient conservation by retention and consecutive reuse would prevent nutrient losses to the atmosphere and downstream ecosystems. We present Smart Nutrient Retention Networks (SNRNs) as a novel management approach to achieve nutrient conservation across networks of connected waterbodies through strategic water quality management. To present the key features of SNRNs, we review existing knowledge of nutrient retention processes in inland waters, water quality management options for nutrient conservation, and nutrient retention models to develop SNRNs. We argue that successful nutrient conservation, even at a local level, through SNRN management strategies requires clearly formulated goals and catchment-wide system understanding. Waterbody characteristics, such as hydraulic residence time and the presence of macrophytes, shape local nutrient retention with potential network-wide cascading effects of improved water quality and are therefore key targets of SNRN management strategies. Nutrient retention models that include the self-reinforcing feedback loop of ecological water quality, nutrient retention, and nutrient loading in networks of inland waters in relation to management options can support the development of SNRNs. We conclude that SNRNs can contribute to sustainable use of nutrients in human food production.

Ecological thresholds are useful indicators for water quality managers to define limits to nutrient pollution. A common approach to estimating ecological thresholds is using critical nutrient loads. Critical nutrient loads are typically defined as the loads at which the phytoplankton chlorophyll-a exceeds a certain concentration. However, national policies, such as in China, use chemical indicators (nitrogen and phosphorus concentrations) rather than ecological indicators (phytoplankton chlorophyll-a) to assess water quality. In this study, we uniquely define the critical nutrient loads based on maximum allowable nutrient concentrations for lake Baiyangdian. We assess whether current and future nutrient loads in this lake comply with the Chinese Water Quality standards. To this end, we link two models (MARINA-Lakes and PCLake+). The PCLake+ model was applied to estimate the critical nutrient loads related to ecological thresholds for total nitrogen, total phosphorus and chlorophyll-a. The current (i.e., 2012) and future (i.e., 2050) nutrient loads were derived from the water quality MARINA-Lakes model. Nitrogen loads exceeded the nitrogen threshold in 2012. Phosphorus loads were below all ecological thresholds in 2012. Ecological thresholds are exceeded in 2050 with limited environmental policies, and urbanization may increase nutrient loads above the ecological thresholds in 2050. Recycling and reallocating animal manure is needed to avoid future water pollution in Lake Baiyangdian. Our study highlights the need for effective policies for clean water based on policy-relevant indicators.

Harmful algal blooms are symptomatic of eutrophication and lead to deterioration of water quality and ecosystem services. Extreme climatic events could enhance eutrophication resulting in more severe nuisance algal blooms, while they also may hamper current restoration efforts aimed to reduce nutrient loads. Evaluation of restoration measures on their efficacy under climate change is essential for effective water management. We conducted a two-month mesocosm experiment in a hypertrophic urban canal focussing on the reduction of sediment phosphorus (P)-release. We tested the efficacy of four interventions, measuring phytoplankton biomass, nutrients in water and sediment. The measures included sediment dredging, water column aeration and application of P-sorbents (lanthanum-modified bentonite - Phoslock® and iron-lime sludge, a by-product from drinking water production). An extreme heatwave (with the highest daily maximum air temperature up to 40.7 °C) was recorded in the middle of our experiment. This extreme heatwave was used for the evaluation of heatwave-induced impacts. Dredging and lanthanum modified bentonite exhibited the largest efficacy in reducing phytoplankton and cyanobacteria biomass and improving water clarity, followed by iron-lime sludge, whereas aeration did not show an effect. The heatwave negatively impacted all four measures, with increased nutrient releases and consequently increased phytoplankton biomass and decreased water clarity compared to the pre-heatwave phase. We propose a conceptual model suggesting that the heatwave locks nutrients within the biological P loop, which is the exchange between labile P and organic P, while the P fraction in the chemical P loop will be decreased. As a consequence, the efficacy of chemical agents targeting P-reduction by chemical binding will be hampered by heatwaves. Our study indicates that current restoration measures might be challenged in a future with more frequent and intense heatwaves.

Water quality improvement to avoid excessive phytoplankton blooms often requires eutrophication management where both phosphorus (P) and nitrogen (N) play a role. While empirical eutrophication studies and ecological resource competition theory both provide insight into phytoplankton abundance in response to nutrient loading, they are not seamlessly linked in the current state of eutrophication research. We argue that understanding species competition for multiple nutrients and light in natural phytoplankton communities is key to assessing phytoplankton abundance under changing nutrient supply. Here we present GPLake-S, a mechanistic model rooted in ecological resource competition theory, which has only eight parameters and can predict chlorophyll-a to nutrient relationships for phytoplankton communities under N, P, N+P colimitation and light limitation. GPLake-S offers a simple mechanistic tool to make first estimates of chlorophyll-a levels and nutrient thresholds for generic lake properties, accounting for variation in N:P ratio preferences of phytoplankton species. This makes the model supportive of water management and policy.

Highlights • Catchment pollution limits water-related ecosystem services such as food production. • Water flow transports energy, substances and organisms downstream. • Organism behaviour causes bidirectional transport across the catchment. • Humans are modifiers of water and organismal transport. • Coupled transport-ecosystem models are essential for water quality assessment. Food production for a growing world population relies on application of fertilisers and pesticides on agricultural lands. However, these substances threaten surface water quality and thereby endanger valued ecosystem services such as drinking water supply, food production and recreational water use. Such deleterious effects do not merely arise on the local scale, but also on the regional scale through transport of substances as well as energy and biota across the catchment. Here we argue that aquatic ecosystem models can provide a process-based understanding of how these transports by water and organisms as vectors affect – and are affected by – ecosystem state and functioning in networks of connected lakes. Such a catchment scale approach is key to setting critical limits for the release of substances by agricultural practices and other human pressures on aquatic ecosystems. Thereby, water and food production and the trade-offs between them may be managed more sustainably.

Datasets and R scripts for the COVID anthropause case study sites for the publication entitled "Lessons learned from the COVID-19 anthropause for water quality management"

SUMMARY: As human mobility decreased in 2020, the interaction between humans and nature changed significantly. On one hand, water clarity improved in the Amsterdam canals because boat traffic was reduced. On the other hand increased use of fishing water and national parks formed potential threats to the aquatic ecosystems. It is important to use these experiences to foster a more eco-centric mindset, building up to handling handling climate change and future pandemics. ABSTRACT: The anomalous past two years of the COVID-19 pandemic have been a test of human response to global crisis management as typical human activities were significantly altered. The COVID-instigated anthropause has illustrated the influence that humans and the biosphere have on each other, especially given the variety of national mobility interventions that have been implemented globally. These local COVID-19-era restrictions influenced human-ecosystem interactions through changes in accessibility of water systems and changes in ecosystem service demand. Four urban aquatic case studies in the Netherlands demonstrated shifts in human demand during the anthropause. For instance, reduced boat traffic in Amsterdam canals led to improved water clarity. In comparison, ongoing service exploitation from increased recreational fishing, use of bathing waters and national parks visitation are heightening concerns about potential ecosystem degradation. We distilled management lessons from both the case studies as well as from recent literature pertaining to ecological intactness and social relevance. Equally important to the lessons themselves, however, is the pace at which informed management practices are established after the pandemic ends, particularly as many communities currently recognize the importance of aquatic ecosystems and are amenable to their protection.

Highlights • Reaching SDG 6 requires algal projection models applicable at a global scale. • There are currently no algal projection models similar to the ideal model. • Scientific challenges relate to spatial scales, data availability and uncertainty. • Recent developments provide opportunities for further development. • Global algal projection models will be highly relevant to global policymaking. Algal blooms increasingly threaten lake and reservoir water quality at the global scale, caused by ongoing climate change and nutrient loading. To anticipate these algal blooms, models to project future algal blooms worldwide are required. Here we present the state-of-the-art in algal projection modelling and explore the requirements of an ideal algal projection model. Based on this, we identify current challenges and opportunities for such model development. Since most building blocks are present, we foresee that algal projection models for any lake on earth can be developed in the near future. Finally, we think that algal bloom projection models at a global scale will provide a valuable contribution to global policymaking, in particular with respect to SDG 6 (clean water and sanitation).

Water bodies in the urban landscape are omnipresent, with many being small, lentic waters such as ponds and lakes. Because of high anthropogenic forcing, these systems have poor water quality, with large consequences for the provisioning of ecosystem services. Understanding of the main pressures on urban water quality is key to successful management. We identify six pressures that we hypothesize to have strong links to anthropogenic forcing including: eutrophication, aquatic invasive species, altered hydrology, altered habitat structure, climate change, and micropollutants. We discuss how these pressures may affect water quality and ecological functioning of urban waters. We describe how these pressures may interact, posing challengers for water management. We identify steps that need to be taken towards sustainable restoration, recognizing the challenges that potentially interacting pressures pose to water managers.

Assessments of river restoration outcomes are mostly based on taxonomic identities of species, which may not be optimal because a direct relationship to river functions remains obscure and results are hardly comparable across biogeographic borders. The use of ecological species trait information instead of taxonomic units may help to overcome these challenges. Abundance data for fish communities were gathered from 134 river restoration projects conducted in Switzerland, Germany and Finland, monitored for up to 15 years. These data were related to a dataset of 22 categories of ecological traits describing fish life-history strategies to assess the outcome of the restoration projects. Restoration increased trait functional diversity and evenness in projects that were situated in the potamal zone of rivers. Restoration effect increased with the length of the restored river reaches. In areas with low levels of anthropogenic land use, the peak of the restoration effect was reached already within one to five years after the restoration and effect receded thereafter, while communities responded later in areas with higher levels of anthropogenic land use. In the lower potamal zone, a shift towards opportunistic life-history strategists was observed. In the upper rhithral zone, in contrast, species with an opportunistic life-history strategy increased only in the first five years of restoration, followed by a shift towards equilibrium strategists at restorations older than 5 years. This pattern was more pronounced in rivers with higher level of anthropogenic land use and longer restored river reaches. Restoration reduced the variability in community trait composition between river reaches suggesting that community trait composition within these zones converges when rivers are restored. This study showed how ecological traits are suitable to analyse restoration outcomes and how such an approach can be used for the evaluation and comparison of environmental management actions across geographical regions. peerReviewed

The authors acknowledge COST Action ES 1105 "CYANOCOST Cyanobacterial blooms and toxins in water resources: Occurrence impacts and management" and COST Action Global Change Biology ES 1201 NETLAKE -Networking Lake Observatories in Europe" for contributing to this study through networking and knowledge sharing with European experts in the field. We acknowledge the members of the Global Lake Ecological Observatory Network (GLEON) for their collaborative spirit and enthusiasm that inspired the grassroots effort of the EMLS. E.M. was supported by a grant from the Swiss State Secretariat for Education, Research and Innovation to Bas Ibelings and by supplementary funding from University of Geneva. We thank Wendy Beekman for the nutrient analysis. We thank Pieter Slot for assisting with the pigment analysis. We thank Dr. Ian Jones for valuable feedback on an earlier version of the manuscript. We thank the Leibniz Institute of Freshwater Ecology and the Aquatic Microbial Ecology Group for logistic and technical support of J. Fonvielle and H.-P. Grossart, and the Leibniz Association for financial support. H.P. was supported by the US National Science Foundation (1840715, 1831096). A.C.'s work was funded by the Spanish Agencia Estatal de Investigacion and EU funds through the project CLIMAWET (CGL2015-69557-R). The collection of data for Lough Erne and Lough Neagh were funded by the Department of Agriculture, Environment and Rural Affairs, Northern Ireland. We are grateful to Kristiina Vuorio from the Freshwater Centre of the Finnish Environment institute for her help in organizing, collecting and analysing samples by the University of Jyvaskyla and to Gerald Dorflinger from the Water Development Department of Cyprus for his assistance with the sampling in Cyprus and for granting the CUT team permission to use WDD's equipment. Finally, we would like to thank the numerous other assistants that helped realizing each local survey. Open access funding provided by Universite de Geneve., To determine the drivers of phytoplankton biomass, we collected standardized morphometric, physical, and biological data in 230 lakes across the Mediterranean, Continental, and Boreal climatic zones of the European continent. Multilinear regression models tested on this snapshot of mostly eutrophic lakes (median total phosphorus [TP] = 0.06 and total nitrogen [TN] = 0.7 mg L-1), and its subsets (2 depth types and 3 climatic zones), show that light climate and stratification strength were the most significant explanatory variables for chlorophyll a (Chl a) variance. TN was a significant predictor for phytoplankton biomass for shallow and continental lakes, while TP never appeared as an explanatory variable, suggesting that under high TP, light, which partially controls stratification strength, becomes limiting for phytoplankton development. Mediterranean lakes were the warmest yet most weakly stratified and had significantly less Chl a than Boreal lakes, where the temperature anomaly from the long-term average, during a summer heatwave was the highest (+4 degrees C) and showed a significant, exponential relationship with stratification strength. This European survey represents a summer snapshot of phytoplankton biomass and its drivers, and lends support that light and stratification metrics, which are both affected by climate change, are better predictors for phytoplankton biomass in nutrient-rich lakes than nutrient concentrations and surface temperature., European Cooperation in Science and Technology (COST) ES 1105 ES 1201, Swiss State Secretariat for Education, Research and Innovation, University of Geneva, Leibniz Association, National Science Foundation (NSF) 1840715 1831096, Spanish Agencia Estatal de Investigacion, European Commission CGL2015-69557-R, Department of Agriculture, Environment and Rural Affairs, Northern Ireland

Photovoltaic (PV) technology has the potential to be integrated on many surfaces in various environments, even on water. Modeling, design, and realization of a floating PV system have more challenges than conventional rooftop or freestanding PV system. In this work, we introduce two innovative concepts for floating bifacial PV systems, describing their modeling, design, and performance monitoring. The developed concepts are retractable and enable maximum energy production through tracking the Sun. Various floating PV systems (monofacial, bifacial with and without reflectors) with different tilts and tracking capabilities are installed on a Dutch pond and are being monitored. Results of the thermal study showed that partially soaking the frame of PV modules into water does not bring a considerable additional yield (+0.17%) and revealed that floating PV modules experience higher temperature special variance compared with land-based systems. Observations showed that the birds' presence has a severe effect on floating PV performance in the short term. Electrical yield investigation concluded that due to low albedo of inland water areas (~6.5%), bifacial PV systems must have reflectors. One-year monitoring showed that a bifacial PV system with reflector and horizontal tracking delivers ~17.3% more specific yield (up to 29% in a clear-sky month) compared with a monofacial PV system installed on land. Ecological monitoring showed no discernable impacts on the water quality in weekly samplings but did show significant impacts on the aquatic plant biomass and periods of low oxygen concentrations.

Globally, many shallow lakes have shifted from a clear macrophyte-dominated state to a turbid phytoplankton-dominated state due to eutrophication. Such shifts are often accompanied by toxic cyanobacterial blooms, with specialized traits including buoyancy regulation and nitrogen fixation. Previous work has focused on how these traits contribute to cyanobacterial competitiveness. Yet, little is known on how these traits affect the value of nutrient loading thresholds of shallow lakes. These thresholds are defined as the nutrient loading at which lakes shift water quality state. Here, we used a modelling approach to estimate the effects of traits on nutrient loading thresholds. We incorporated cyanobacterial traits in the process-based ecosystem model PCLake+, known for its ability to determine nutrient loading thresholds. Four scenarios were simulated, including cyanobacteria without traits, with buoyancy regulation, with nitrogen fixation, and with both traits. Nutrient loading thresholds were obtained under N-limited, P-limited, and colimited conditions. Results show that cyanobacterial traits can impede lake restoration actions aimed at removing cyanobacterial blooms via nutrient loading reduction. However, these traits hardly affect the nutrient loading thresholds for clear lakes experiencing eutrophication. Our results provide references for nutrient loading thresholds and draw attention to cyanobacterial traits during the remediation of eutrophic water bodies.

Eutrophication, global warming, and rising carbon dioxide (CO2) levels are the three most prevalent pressures impacting the biosphere. Despite their individual effects are well-known, it remains untested how oligotrophication (i.e. nutrients reduction) can alter the planktonic community responses to warming and elevated CO2 levels. Here, we performed an indoor mesocosm experiment to investigate the warming × CO2 interaction under a nutrient reduction scenario (40%) mediated by an in-lake management strategy (i.e. addition of a commercial solid-phase phosphorus sorbent -Phoslock®) on a natural freshwater plankton community. Biomass production increased under warming × CO2 relative to present-day conditions; however, a Phoslock®-mediated oligotrophication reduced such values by 30–70%. Conversely, the warming × CO2 × oligotrophication interaction stimulated the photosynthesis by 20% compared to ambient nutrient conditions, and matched with higher resource use efficiency (RUE) and nutrient demand. Surprisingly, at a group level, we found that the multi-stressors scenario increased the photosynthesis in eukaryotes by 25%, but greatly impaired in cyanobacteria (ca. −25%). This higher cyanobacterial sensitivity was coupled with a reduced light harvesting efficiency and compensation point. Since Phoslock®-induced oligotrophication unmasked a strong negative warming × CO2 effect on cyanobacteria, it becomes crucial to understand how the interplay between climate change and nutrient abatement actions may alter the, ecosystems functioning. With an integrative understanding of these processes, policy makers will design more appropriate management strategies to improve the ecological status of aquatic ecosystems without compromising their ecological attributes and functioning.

Eutrophication, global warming, and rising carbon dioxide (CO

Worldwide, eutrophication is threatening lake ecosystems. To support lake management numerous eutrophication models have been developed. Diverse research questions in a wide range of lake ecosystems are addressed by these models. The established models are based on three key approaches: the empirical approach that employs field surveys, the theoretical approach in which models based on first principles are tested against lab experiments, and the process-based approach that uses parameters and functions representing detailed biogeochemical processes. These approaches have led to an accumulation of field-, lab- and model-based knowledge, respectively. Linking these sources of knowledge would benefit lake management by exploiting complementary information; however, the development of a simple tool that links these approaches was hampered by their large differences in scale and complexity. Here we propose a Generically Parameterized Lake eutrophication model (GPLake) that links field-, lab- and model-based knowledge and can be used to make a first diagnosis of lake water quality. We derived GPLake from consumer-resource theory by the principle that lacustrine phytoplankton is typically limited by two resources: nutrients and light. These limitations are captured in two generic parameters that shape the nutrient to chlorophyll-a relations. Next, we parameterized GPLake, using knowledge from empirical, theoretical, and process-based approaches. GPLake generic parameters were found to scale in a comparable manner across data sources. Finally, we show that GPLake can be applied as a simple tool that provides lake managers with a first diagnosis of the limiting factor and lake water quality, using only the parameters for lake depth, residence time and current nutrient loading. With this first-order assessment, lake managers can easily assess measures such as reducing nutrient load, decreasing residence time or changing depth before spending money on field-, lab- or model- experiments to support lake management.

“Everything changes and nothing stands still” (Heraclitus). Here we review three major improvements to freshwater aquatic ecosystem models — and ecological models in general — as water quality scenario analysis tools towards a sustainable future. To tackle the rapid and deeply connected dynamics characteristic of the Anthropocene, we argue for the inclusion of eco-evolutionary, novel ecosystem and social-ecological dynamics. These dynamics arise from adaptive responses in organisms and ecosystems to global environmental change and act at different integration levels and different time scales. We provide reasons and means to incorporate each improvement into aquatic ecosystem models. Throughout this study we refer to Lake Victoria as a microcosm of the evolving novel social-ecological systems of the Anthropocene. The Lake Victoria case clearly shows how interlinked eco-evolutionary, novel ecosystem and social-ecological dynamics are, and demonstrates the need for transdisciplinary research approaches towards global sustainability. Highlights • We present a research agenda to enhance water quality modeling in the Anthropocene. • We review adaptive responses in organisms and ecosystems to global environmental change. • We focus on eco-evolutionary, novel ecosystem and social-ecological dynamics. • These dynamics act at different integration levels and different time scales. • Lake Victoria is an iconic example of an evolving novel social-ecological system.

The lake ecosystem model PCLake is a process-based model that was developed to simulate water quality based on ecological interactions in shallow, non-stratifying lakes in the temperate climate zone. Here we present PCLake+, which extends the PCLake model to cover a wide range of freshwater lakes that differ in stratification regime and climate-related processes. To this end, the model was extended with a hypolimnion layer that can be invoked and configured by forcing functions or by simple built-in empirical relationships that impose stratification. Further adjustments to the original PCLake model have been made with respect to the calculation of 1) light irradiation in the water column, 2) evaporation processes and 3) phenology of macrophytes. The simulation output of PCLake+ for different types of lakes complies well with generally accepted limnological knowledge, thus holding promise for future contributions to ecological theory and application to lakes around the globe.

Induced bank filtration (IBF) is a water abstraction technology using different natural infiltration systems for groundwater recharge, such as river banks and lake shores. It is a cost-effective pre-treatment method for drinking water production used in many regions worldwide, predominantly in urban areas. Until now, research concerning IBF has almost exclusively focussed on the purification efficiency and infiltration capacity. Consequently, knowledge about the effects on source water bodies is lacking. Yet, IBF interrupts groundwater seepage and affects processes in the sediment potentially resulting in adverse effects on lake or river water quality. Securing sufficient source water quality, however, is important for a sustainable drinking water production by IBF. In this study, we analysed the effects of five predicted mechanisms of IBF on shallow lake ecosystems using the dynamic model PCLake: declining CO 2 and nutrient availability, as well as increasing summer water temperatures, sedimentation rates and oxygen penetration into sediments. Shallow lake ecosystems are abundant worldwide and characterised by the occurrence of alternative stable states with either clear water and macrophyte dominance or turbid, phytoplankton-dominated conditions. Our results show that IBF in most scenarios increased phytoplankton abundance and thus had adverse effects on shallow lake water quality. Threshold levels for critical nutrient loading inducing regime shifts from clear to turbid conditions were up to 80% lower with IBF indicating a decreased resilience to eutrophication. The effects were strongest when IBF interrupted the seepage of CO 2 rich groundwater resulting in lower macrophyte growth. IBF could also enhance water quality, but only when interrupting the seepage of groundwater with high nutrient concentrations. Higher summer water temperatures increased the share of cyanobacteria in the phytoplankton community and thus the risk of toxin production. In relative terms, the effects of changing sedimentation rates and oxygen penetration were small. Lake depth and size influenced the effect of IBF on critical nutrient loads, which was strongest in shallower and smaller lakes. Our model results stress the need of a more comprehensive ecosystem perspective including an assessment of IBF effects on threshold levels for regime shifts to prevent high phytoplankton abundance in the source water body and secure a sustainable drinking water supply.

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains. © 2018 by the authors. Licensee MDPI, Basel, Switzerland., The authors acknowledge COST Action ES 1105 “CYANOCOST—Cyanobacterial blooms and toxins in water resources: Occurrence impacts and management” and COST Action ES 1201 “NETLAKE—Networking Lake Observatories in Europe” for contributing to this study through networking and knowledge sharing with European experts in the field. Evanthia Mantzouki was supported by a grant from the Swiss State Secretariat for Education, Research and Innovation (SERI) to Bas Ibelings and by supplementary funding from the University of Geneva. We thank Clare Ahnlund, Ena Suarez and Irene Gallego for helping out with the Swiss survey. We thank Wendy Beekman and Els J. Faassen for the nutrient and toxin analysis.

Under ongoing climate change and increasing anthropogenic activity, which continuously challenge ecosystem resilience, an in-depth understanding of ecological processes is urgently needed. Lakes, as providers of numerous ecosystem services, face multiple stressors that threaten their functioning. Harmful cyanobacterial blooms are a persistent problem resulting from nutrient pollution and climate-change induced stressors, like poor transparency, increased water temperature and enhanced stratification. Consistency in data collection and analysis methods is necessary to achieve fully comparable datasets and for statistical validity, avoiding issues linked to disparate data sources. The European Multi Lake Survey (EMLS) in summer 2015 was an initiative among scientists from 27 countries to collect and analyse lake physical, chemical and biological variables in a fully standardized manner. This database includes in-situ lake variables along with nutrient, pigment and cyanotoxin data of 369 lakes in Europe, which were centrally analysed in dedicated laboratories. Publishing the EMLS methods and dataset might inspire similar initiatives to study across large geographic areas that will contribute to better understanding lake responses in a changing environment., The authors acknowledge COST Action ES 1105 “CYANOCOST – Cyanobacterial blooms and toxins in water resources: Occurrence impacts and management” and COST Action ES 1201 “NETLAKE – Networking Lake Observatories in Europe” for contributing to this study through networking and knowledge sharing with European experts in the field. Evanthia Mantzouki was supported by a grant from the Swiss State Secretariat for Education, Research and Innovation (SERI) to Bas Ibelings and by supplementary funding from University of Geneva. We thank Wendy Beekman for the nutrient analysis and the University of Wageningen for covering the costs of this analysis from the personal funding of dr. Miquel Lürling. We thank Pieter Slot for assisting with the pigment analysis and the University of Amsterdam for covering the costs of the analysis through funding from the group of Prof. Jef Huisman and dr. Petra Visser (IBED). We would like to thank the Environmental Data Initiative for covering the cost of archiving the EMLS dataset. We would like to thank the Leibniz Institute of Freshwater Ecology and Inland Fisheries, Dept. of Experimental Limnology and the Aquatic Microbial Ecology Group for logistic and technical support of J. Fonvielle and H.-P. Grossart; and the Leibniz Association for financial support. The collection of data for Lough Erne and Lough Neagh were funded by the Department of Agriculture, Environment and Rural Affairs, Northern Ireland.

Soil-borne pathogens cause great crop losses in agriculture. Because of their resilience in the soil, these pathogens persist in a population reservoir, causing future outbreaks of crop diseases. Management focus is usually on the most common pathogens occurring, but it is likely that a mixed population of pathogens together affect crops. Next generation sequencing of DNA from environmental samples can provide information on the presence of potential pathogens. The aim of this study was to obtain insight into the factors that drive the composition of potential plant pathogen populations in agricultural soils. To this end, the alpha and beta diversity of fungal OTUs that were assigned as potential plant pathogens for 42 agricultural soils were assessed. The presented study is the first inventory of the pool of pathogens and its correlating factors. The results of this inventory indicate that the composition of pathogens in soil is driven by pH, soil type, crop history, litter saprotrophic fungi and spatial patterns. The major driving factors differed between potential root- and shoot-infecting fungi, suggesting interactions among environmental factors and pathogen traits like reproduction, survival and dispersal. This information is important to understand risks for disease outbreaks and to recommend management strategies to prevent such outbreaks.

Water quality modelling deals with multidisciplinary questions ranging from fundamental to applied. Addressing this broad range of questions requires multiple analysis techniques and therefore multiple frameworks. Through the recently developed database approach to modelling (DATM), it has become possible to run a model in multiple software frameworks without much overhead. Here we apply DATM to the ecosystem model for ditches. PCDitch and its twin model for shallow lakes PCLake. Using DATM, we run these models in six frameworks (ACSL, DELWAQ, DUFLOW, GRIND for MATLAB, OSIRIS and R), and report on the possible model analyses with tools provided by each framework. We conclude that the dynamic link between frameworks and models resulting from DATM has the following main advantages: it allows one to use the framework one is familiar with for most model analyses and eases switching between frameworks for complementary model analyses, including the switch between a 0-D and 1-D to 3-D setting. Moreover, the strength of each framework – including runtime performance – can now be easily exploited. We envision that a community-based further development of the concept can contribute to the future development of water quality modelling, not only by addressing multidisciplinary questions but also by facilitating the exchange of models and process formulations within the community of water quality modellers.

Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5-10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary.

Alteration of natural flow regime is considered a major threat to biodiversity in river floodplain ecosystems. Measurements of quantitative relationships between flow regime change and biodiversity are, however, incomplete and inconclusive. This hampers the assessment of human impact on riverine floodplain wetlands in global biodiversity evaluations. We systematically reviewed the scientific literature and extracted information from existing data sets for a meta-analysis to unravel a general quantitative understanding of the ecological consequences of altered flow regimes. From 28 studies we retrieved both ecological and hydrological data. Relative mean abundance of original species (mean species abundance, MSA) and relative species richness were used as effect size measures of biodiversity intactness. The meta-analysis showed that alteration of a natural flow regime reduces the MSA by more than 50 % on average, and species richness by more than 25 %. Impact on species richness and abundance tends to be related to the degree of hydrological alteration. These results can be used in strategic quantitative assessments by incorporating the relationships into global models on environmental change and biodiversity such as GLOBIO-aquatic.

Many lakes worldwide are experiencing great change due to eutrophication. Consequently, species composition changes, toxic algal blooms proliferate, and drinking water supplies dwindle. The transition to the deteriorated state can be catastrophic with an abrupt change from macrophyte to phytoplankton domination. This has been shown repeatedly in small lakes. Whether such alternative stable states also exist in large shallow lakes is less clear, however. Here we discuss the characteristics that give rise to alternative stable states in large shallow lakes either in the lake as whole or restricted to specific regions of the lake. We include the effect of lake size, spatial heterogeneity and internal connectivity on a lake's response along the eutrophication axis. As a case study, we outline the eutrophication history of Lake Taihu (China) and illustrate how lake size, spatial heterogeneity and internal connectivity can explain the observed spatial presence of different states. We discuss whether these states can be alternatively stable by comparing the data with model output (PCLake). These findings are generalised for other large, shallow lakes. We conclude that locations with prevailing size effects generally lack macrophytes; and, therefore, alternative stable states are unlikely to occur there. However, most large shallow lakes have macrophytes whose presence remains unexplained when only size effect is taken into account. By including spatial heterogeneity in the analysis, the presence of macrophytes and alternative stable states in large shallow lakes is better understood. Finally, internal connectivity is important because a high internal connectivity reduces the stability of alternative states.

Simulation modelling in ecology is a field that is becoming increasingly compartmentalized. Here we propose a Database Approach To Modelling (DATM) to create unity in dynamical ecosystem modelling with differential equations. In this approach the storage of ecological knowledge is independent of the language and platform in which the model will be run. To create an instance of the model, the information in the database is translated and augmented with the language and platform specifics. This process is automated so that a new instance can be created each time the database is updated. We describe the approach using the simple Lotka-Volterra model and the complex ecosystem model for shallow lakes PCLake, which we automatically implement in the frameworks OSIRIS, GRIND for MATLAB, ACSL, R, DUFLOW and DELWAQ. A clear advantage of working in a database is the overview it provides. The simplicity of the approach only adds to its elegance. Scientific and educational experience with the proposed Database Approach To Modelling (DATM) shows the following:It facilitated overview of and insight in the model by developers and users.Allowed for a much more dynamic scientific development of the model.Allowed for a direct implementation of these developments in multiple platforms.