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Ecologists are challenged by the need to bridge and synthesize different approaches and theories to obtain a coherent understanding of ecosystems in a changing world. Both food web theory and regime shift theory shine light on mechanisms that confer stability to ecosystems, but from different angles. Empirical food web models are developed to analyze how equilibria in real multi-trophic ecosystems are shaped by species interactions, and often include linear functional response terms for simple estimation of interaction strengths from observations. Models of regime shifts focus on qualitative changes of equilibrium points in a slowly changing environment, and typically include non-linear functional response terms. Currently, it is unclear how the stability of an empirical food web model, expressed as the rate of system recovery after a small perturbation, relates to the vulnerability of the ecosystem to collapse. Here, we conduct structural sensitivity analyses of classical consumer-resource models in equilibrium along an environmental gradient. Specifically, we change non-proportional interaction terms into proportional ones, while maintaining the equilibrium biomass densities and material flux rates, to analyze how alternative model formulations shape the stability properties of the equilibria. The results reveal no consistent relationship between the stability of the original models and the proportionalized versions, even though they describe the same biomass values and material flows. We use these findings to critically discuss whether stability analysis of observed equilibria by empirical food web models can provide insight into regime shift dynamics, and highlight the challenge of bridging alternative modelling approaches in ecology and beyond.

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.

This study investigates the effect of water temperature on the development rate of eggs and larvae, the duration of the endogenous feeding period and its consequences for recruitment of smelt (Osmerus eperlanus ) in Dutch lakes IJsselmeer and Markermeer. This study measured temperature‐dependent egg and larval development rates as well as mortality rates from fertilization till the moment of absorption of the yolk‐sac and from yolk‐sac depletion onwards in temperature‐controlled indoor experiments. Using multinomial modelling the authors found significant differences in development time of egg development stages under different temperature regimes. Based on historic water temperatures, the model predicted that the larval endogenous feeding period has advanced at a rate of about 2.9 days per decade in a more than 50 year period since 1961, yet there was no change in the duration of the endogenous feeding period. As zooplankton is more responsive to daylight than water temperature cues, a mismatch between the peak of the onset of exogenous feeding of smelt and the peak of zooplankton blooms could lead to high mortality and therefore low recruitment of smelt. Such a mismatch might contribute to a decline in the smelt population in Lake IJsselmeer and Lake Markermeer.

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.

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.

Achieving global sustainability goals requires most people and societies to fundamentally alter their relationship with nature. New approaches are called for to guide change processes towards sustainable futures that embrace the plurality of people’s perspectives on nature. This paper presents a novel approach to exploring desirable futures for nature and people that was developed through an application in National Park Hollandse Duinen in the Netherlands. This new national park is developed bottom-up by a diverse group of actors reshaping their interactions with each other and with nature. Our approach, co-designed with key stakeholders of the national park, engages with a new pluralistic framework for nature values presented by the IPBES task force on scenarios and models to catalyze the development of nature-centered scenarios. We integrated this Nature Futures Framework with the Three Horizons Framework in a participatory workshop process designed to bring people’s diverse relationships with nature to the fore, and jointly envision desirable futures and the pathways to get there. An analytical framework is used to analyze and compare the visions and assess their potential contribution to the SDGs. We summarize the results of the application in National Park Hollandse Duinen and reflect on lessons learned. We see much potential for this values-based futures approach to support change processes in various social-ecological contexts toward more sustainable futures for nature and people.

Ecologists are challenged by the need to bridge and synthesize different approaches and theories to obtain a coherent understanding of ecosystems in a changing world. Both food web theory and regime shift theory shine light on mechanisms that confer stability to ecosystems, but from different angles. Empirical food web models are developed to analyze how equilibria in real multi-trophic ecosystems are shaped by species interactions, and often include linear functional response terms for simple estimation of interaction strengths from observations. Models of regime shifts focus on qualitative changes of equilibrium points in a slowly changing environment, and typically include non-linear functional response terms. Currently, it is unclear how the stability of an empirical food web model, expressed as the rate of system recovery after a small perturbation, relates to the vulnerability of the ecosystem to collapse. Here, we conduct structural sensitivity analyses of classical consumer-resource models in equilibrium along an environmental gradient. Specifically, we change non-proportional interaction terms into proportional ones, while maintaining the equilibrium biomass densities and material flux rates, to analyze how alternative model formulations shape the stability properties of the equilibria. The results reveal no consistent relationship between the stability of the original models and the proportionalized versions, even though they describe the same biomass values and material flows. We use these findings to critically discuss whether stability analysis of observed equilibria by empirical food web models can provide insight into regime shift dynamics, and highlight the challenge of bridging alternative modelling approaches in ecology and beyond.

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.

The current anthropogenic impacts on nature necessitate more research for nature conservation and restoration purposes. To answer ecological and conservation questions concerning endangered species, individual-based modelling is an obvious choice. Individual-based models can provide reliable results that may be used to predict the effects of different future conservation strategies, once calibrated correctly. Here, we calibrate an individual-based model of Maui dolphin movement, which generates Maui dolphin probability distribution maps. We used sighting data for calibration of the chosen parameter combinations; for each simulation run, collected simulated data was compared to the empirical survey data, resulting in cost (Badness-of-Fit) estimates. Using costs of four different aspects of dolphin behaviour, we estimated the most likely parameter combinations. With optimized parameter values, Maui dolphin probability distribution maps were created, resulting in distributions that fall well outside of the current protection zones where either gillnets or trawling or both are prohibited. With these results, protected areas can be properly adjusted to the estimated distribution of this critically endangered species and so aid in their conservation.

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.

Addressing challenges of water, energy and food security, nexus approaches towards resources management are being developed and starting to be implemented. However, the ecosystem perspective, essential for sustainable resources management, has been identified as a missing element within earlier nexus assessments. With regard to water they have mainly focused on the allocation to different sectors and users, while ecosystem services were rarely explicitly addressed. Existing aquatic ecosystem models are capable of quantifying a wide range of ecosystem services, but have thus far not been comprehensively used in a nexus context. Recent developments in aquatic ecosystem modelling approaches provide opportunities to achieve the sought integration of ecosystem services in the nexus approach. Therefore, we argue for a stronger role of aquatic ecosystem models in nexus assessments.

A long-standing debate in ecology deals with the role of nitrogen and phosphorus in management and restoration of aquatic ecosystems. It has been argued that nutrient reduction strategies to combat blooms of phytoplankton or floating plants should solely focus on phosphorus (P). The underlying argument is that reducing nitrogen (N) inputs is ineffective because N2-fixing species will compensate for N deficits, thus perpetuating P limitation of primary production. A mechanistic understanding of this principle is, however, incomplete. Here, we use resource competition theory, a complex dynamic ecosystem model and a 32-year field data set on eutrophic, floating-plant dominated ecosystems to show that the growth of non-N2-fixing species can become N limited under high P and low N inputs, even in the presence of N2 fixing species. N2-fixers typically require higher P concentrations than non-N2-fixers to persist. Hence, the N2 fixers cannot deplete the P concentration enough for the non-N2-fixing community to become P limited because they would be outcompeted. These findings provide a testable mechanistic basis for the need to consider the reduction of both N and P inputs to most effectively restore nutrient over-enriched aquatic ecosystems. This article is protected by copyright. All rights reserved.

Wild vertebrate populations all over the globe are in decline, with poaching being the second-most-important cause. The high poaching rate of rhinoceros may drive these species into extinction within the coming decades. Some stakeholders argue to lift the ban on international rhino horn trade to potentially benefit rhino conservation, as current interventions appear to be insufficient. We reviewed scientific and grey literature to scrutinize the validity of reasoning behind the potential benefit of legal horn trade for wild rhino populations. We identified four mechanisms through which legal trade would impact wild rhino populations, of which only the increased revenue for rhino farmers could potentially benefit rhino conservation. Conversely, the global demand for rhino horn is likely to increase to a level that cannot be met solely by legal supply. Moreover, corruption is omnipresent in countries along the trade routes, which has the potential to negatively affect rhino conservation. Finally, programmes aimed at reducing rhino horn demand will be counteracted through trade legalization by removing the stigma on consuming rhino horn. Combining these insights and comparing them with criteria for sustainable wildlife farming, we conclude that legalizing rhino horn trade will likely negatively impact the remaining wild rhino populations. To preserve rhino species, we suggest to prioritize reducing corruption within rhino horn trade, increasing the rhino population within well-protected 'safe havens' and implementing educational programmes and law enforcement targeted at rhino horn consumers. peerReviewed

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.

Submerged macrophytes play an important role in maintaining good water quality in shallow lakes. Yet extensive stands easily interfere with various services provided by these lakes, and harvesting is increasingly applied as a management measure. Because shallow lakes may possess alternative stable states over a wide range of environmental conditions, designing a successful mowing strategy is challenging, given the important role of macrophytes in stabilizing the clear water state. In this study, the integrated ecosystem model PCLake is used to explore the consequences of mowing, in terms of reducing nuisance and ecosystem stability, for a wide range of external nutrient loadings, mowing intensities and timings. Elodea is used as a model species. Additionally, we use PCLake to estimate how much phosphorus is removed with the harvested biomass, and evaluate the long-term effect of harvesting. Our model indicates that mowing can temporarily reduce nuisance caused by submerged plants in the first weeks after cutting, particularly when external nutrient loading is fairly low. The risk of instigating a regime shift can be tempered by mowing halfway the growing season when the resilience of the system is highest, as our model showed. Up to half of the phosphorus entering the system can potentially be removed along with the harvested biomass. As a result, prolonged mowing can prevent an oligo—to mesotrophic lake from becoming eutrophic to a certain extent, as our model shows that the critical nutrient loading, where the lake shifts to the turbid phytoplankton-dominated state, can be slightly increased.

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.

Many aquatic ecosystems have deteriorated due to human activities and their restoration is often troublesome. It is proposed here that the restoration success of deteriorated lakes critically depends on hitherto largely neglected spatial heterogeneity in nutrient loading and hydrology. A modelling approach is used to study this hypothesis by considering four lake types with contrasting nutrient loading (point versus diffuse) and hydrology (seepage versus drainage). By comparing the longterm effect of common restoration measures (nutrient load reduction, lake flushing or biomanipulation) in these four lake types, we found that restoration through reduction of nutrient loading is effective in all cases. In contrast, biomanipulation only works in seepage lakes with diffuse nutrient inputs, while lake flushing will even be counterproductive in lakes with nutrient point sources. The main conclusion of the presented analysis is that a priori assessment of spatial heterogeneity caused by nutrient loading and hydrology is essential for successful restoration of lake ecosystems.

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.

Quantitative evidence of sudden shifts in ecological structure and function in large shallow lakes is rare, even though they provide essential benefits to society. Such ‘regime shifts’ can be driven by human activities which degrade ecological stability including water level control (WLC) and nutrient loading. Interactions between WLC and nutrient loading on the long-term dynamics of shallow lake ecosystems are, however, often overlooked and largely underestimated, which has hampered the effectiveness of lake management. Here, we focus on a large shallow lake (Lake Chaohu) located in one of the most densely populated areas in China, the lower Yangtze River floodplain, which has undergone both WLC and increasing nutrient loading over the last several decades. We applied a novel methodology that combines consistent evidence from both paleolimnological records and ecosystem modeling to overcome the hurdle of data insufficiency and to unravel the drivers and underlying mechanisms in ecosystem dynamics. We identified the occurrence of two regime shifts: one in 1963, characterized by the abrupt disappearance of submerged vegetation, and another around 1980, with strong algal blooms being observed thereafter. Using model scenarios, we further disentangled the roles of WLC and nutrient loading, showing that the 1963 shift was predominantly triggered by WLC, whereas the shift ca. 1980 was attributed to aggravated nutrient loading. Our analysis also shows interactions between these two stressors. Compared to the dynamics driven by nutrient loading alone, WLC reduced the critical P loading and resulted in earlier disappearance of submerged vegetation and emergence of algal blooms by approximately 26 years and 10 years, respectively. Overall, our study reveals the significant role of hydrological regulation in driving shallow lake ecosystem dynamics, and it highlights the urgency of using multi-objective management criteria that includes ecological sustainability perspectives when implementing hydrological regulation for aquatic ecosystems around the globe.

This study presents FABM-PCLake, a redesigned structure of the PCLake aquatic ecosystem model, which we implemented in the Framework for Aquatic Biogeochemical Models (FABM). In contrast to the original model, which was designed for temperate, fully mixed freshwater lakes, the new FABM-PCLake represents an integrated aquatic ecosystem model that can be linked with different hydrodynamic models and allows simulations of hydrodynamic and biogeochemical processes for zero-dimensional, one-dimensional as well as three-dimensional environments. FABM-PCLake describes interactions between multiple trophic levels, including piscivorous, zooplanktivorous and benthivorous fish, zooplankton, zoobenthos, three groups of phytoplankton and rooted macrophytes. The model also accounts for oxygen dynamics and nutrient cycling for nitrogen, phosphorus and silicon, both within the pelagic and benthic domains. FABM-PCLake includes a two-way communication between the biogeochemical processes and the physics, where some biogeochemical state variables (e.g., phytoplankton) influence light attenuation and thereby the spatial and temporal distributions of light and heat. At the same time, the physical environment, including water currents, light and temperature influence a wide range of biogeochemical processes. The model enables studies on ecosystem dynamics in physically heterogeneous environments (e.g., stratifying water bodies, and water bodies with horizontal gradients in physical and biogeochemical properties), and through FABM also enables data assimilation and multi-model ensemble simulations. Examples of potential new model applications include climate change impact studies and environmental impact assessment scenarios for temperate, sub-tropical and tropical lakes and reservoirs. © Author(s) 2016. This study presents FABM-PCLake, a redesigned structure of the PCLake aquatic ecosystem model, which we implemented in the Framework for Aquatic Biogeochemical Models (FABM). In contrast to the original model, which was designed for temperate, fully mixed freshwater lakes, the new FABM-PCLake represents an integrated aquatic ecosystem model that can be linked with different hydrodynamic models and allows simulations of hydrodynamic and biogeochemical processes for zero-dimensional, one-dimensional as well as three-dimensional environments. FABM-PCLake describes interactions between multiple trophic levels, including piscivorous, zooplanktivorous and benthivorous fish, zooplankton, zoobenthos, three groups of phytoplankton and rooted macrophytes. The model also accounts for oxygen dynamics and nutrient cycling for nitrogen, phosphorus and silicon, both within the pelagic and benthic domains. FABM-PCLake includes a two-way communication between the biogeochemical processes and the physics, where some biogeochemical state variables (e.g., phytoplankton) influence light attenuation and thereby the spatial and temporal distributions of light and heat. At the same time, the physical environment, including water currents, light and temperature influence a wide range of biogeochemical processes. The model enables studies on ecosystem dynamics in physically heterogeneous environments (e.g., stratifying water bodies, and water bodies with horizontal gradients in physical and biogeochemical properties), and through FABM also enables data assimilation and multi-model ensemble simulations. Examples of potential new model applications include climate change impact studies and environmental impact assessment scenarios for temperate, sub-tropical and tropical lakes and reservoirs.

Freshwater shallow lake ecosystems provide valuable ecological services to human beings. However, these systems are subject to severe contamination from anthropogenic sources. Per- and polyfluoroalkyl substances (PFASs), including perfluorooctanoic acid (PFOA) and perfluorooctane sulphonate (PFOS), are among the contaminants that have received substantial attention, primarily due to abundant applications, environment persistence, and potential threats to ecological and human health. Understanding the environmental behavior of these contaminants in shallow freshwater lake environments using a modeling approach is therefore critical. Here, we characterize the fate, transport and transformation of both PFOA and PFOS in the fifth largest freshwater lake in China (Chaohu) during a two-year period (2013–2015) using a fugacity-based multimedia fate model. A reasonable agreement between the measured and modeled concentrations in various compartments confirms the model's reliability. The model successfully quantifies the environmental processes and identifies the major sources and input pathways of PFOA and PFOS to the Chaohu water body. Sensitivity analysis reveals the critical role of nonlinear Freundlich sorption, which contributes to a variable fraction of the model true uncertainty in different compartments (8.1%–93.6%). Through additional model scenario analyses, we further elucidate the importance of nonlinear Freundlich sorption that is essential for the reliable model performance. We also reveal the distinct composition of emission sources for the two contaminants, as the major sources are indirect soil volatilization and direct release from human activities for PFOA and PFOS, respectively. The present study is expected to provide implications for local management of PFASs pollution in Lake Chaohu and to contribute to developing a general model framework for the evaluation of PFASs in shallow lakes.

Introduction Although the ubiquitous biodiversity-related flexibility of ecological systems is qualitatively well established, most empirical and theoretical studies regard ecological systems so far as units with rigid, predefined properties. The reason for this static approach is that incorporating the tremendous diversity and flexibility of natural systems into empirical and theoretical studies has been extremely challenging in terms of developing consistent mathematical frameworks and designing appropriate experiments. This approach has also been necessary owing to the lack of empirical data on the ability of species to change properties over time. A recent approach to solve this problem is to move from a species- to a trait-based perspective. This is not just a change in terminology but in concept, providing a mechanistic basis for biodiversity–ecosystem function relationships and improving our potential to identify general rules in community ecology (McGill et al., 2006; Savage et al., 2007; Hillebrand and Matthiessen, 2009). Functional traits are used to link species to their function in the ecosystem. They are well defined, measurable properties of individuals (e.g., edibility or diet selectivity) affecting their performance and responses to environmental changes and hence population and community dynamics as well as trophic interactions. The frequency distribution of functional traits (Figure 10.1a) enables a quantification of functional diversity. Large variation in trait values (e.g., a full range from highly edible, fast growing to almost inedible, slow growing species) implies a high functional diversity and vice versa. This trait distribution may be described by its shape and central tendency (Figure 10.1b) and may change in response to altered abiotic (e.g., temperature) and biotic conditions (e.g., predator density) and thus characterize the milieu with which individual organisms interact (McGill et al., 2006) (Figure 10.1c). Scientific Background Maintaining the different kinds of ecosystem services in a way that optimizes human well-being and economy is one of the most urgent tasks of our century, which challenges policy-makers as well as scientists. The frequency and intensity of land use, climate change, and other anthropogenically induced environmental disturbances are accelerating biodiversity declines worldwide. The negative impact of these processes on ecological systems (e.g., individuals, populations, communities, and food webs) may amplify each other: environmental changes can accelerate biodiversity loss and a reduced biodiversity may increase the sensitivity of ecological systems to environmental changes. © Cambridge University Press 2018.

In this study, we apply an integrated empirical and mechanism approach to estimate a comprehensive long-term (1953–2012) total nitrogen (TN) and total phosphorus (TP) loading budget for the eutrophic Lake Chaohu in China. This budget is subsequently validated, firstly, by comparing with the available measured data in several years, and secondly, by model simulations for long-term nutrient dynamics using both Vollenweider (VW) model and dynamic nonlinear (DyN) model. Results show that the estimated nutrient budget is applicable for further evaluations. Surprisingly, nutrient loading from non-point sources (85% for TN and 77% for TP on average) is higher than expectation, suggesting the importance of nutrient flux from the soil in the basin. In addition, DyN model performs relatively better than VW model, which is attributed to both the additional sediment recycling process and the parameters adjusted by the Bayesian-based Markov Chain Monte Carlo (MCMC) method. DyN model further shows that the TP loading thresholds from the clear to turbid state (631.8 ± 290.16 t y−1) and from the turbid to clear state (546.0 ± 319.80 t y−1) are significantly different (p < 0.01). Nevertheless, the uncertainty ranges of the thresholds are largely overlapped, which is consistent with the results that the eutrophication of Lake Chaohu is more likely to be reversible (74.12%) than hysteretic (25.53%). The ecosystem of Lake Chaohu shifted from the clear to turbid state during late 1970s. For managers, approximately two-thirds of the current TP loading must be reduced for a shift back with substantial improvement in water quality. Because in practice the reduction of loading from a non-point source is very difficult and costly, additional methods beyond nutrient reduction, such as water level regulation, should be considered for the lake restoration.

Despite the importance of coral reef ecosystems to the social and economic welfare of coastal communities, the condition of these marine ecosystems have generally degraded over the past decades. With an increased knowledge of coral reef ecosystem processes and a rise in computer power, dynamic models are useful tools in assessing the synergistic effects of local and global stressors on ecosystem functions. We review representative approaches for dynamically modelling coral reef ecosystems and categorize them as minimal, intermediate and complex models. The categorization was based on the leading principle for model development and their level of realism and process detail. This review aims to improve the knowledge of concurrent approaches in coral reef ecosystem modeling and highlights the importance of choosing an appropriate approach based on the type of question(s) to be answered. We contend that minimal and intermediate models are generally valuable tools to assess the response of key states to main stressors and, hence, contribute to understanding ecological surprises. As has been shown in freshwater resources management, insight into these conceptual relations profoundly influences how natural resource managers perceive their systems and how they manage ecosystem recovery. We argue that adaptive resource management requires integrated thinking and decision support, which demands a diversity of modeling approaches. Integration can be achieved through complimentary use of models or through integrated models that systemically combine all relevant aspects in one model. Such whole-of-system models can be useful tools for quantitatively evaluating scenarios. These models allow an assessment of the interactive effects of multiple stressors on various, potentially conflicting, management objectives. All models simplify reality and, as such, have their weaknesses. While minimal models lack multidimensionality, system models are likely difficult to interpret as they require many efforts to decipher the numerous interactions and feedback loops. Given the breadth of questions to be tackled when dealing with coral reefs, the best practice approach uses multiple model types and thus benefits from the strength of different models types.

Shallow lakes can switch suddenly from a turbid situation with high concentrations of phytoplankton and other suspended solids to a vegetated state with clear water, and vice versa. These alternative stable states may have a substantial impact on the fate of hydrophobic organic compounds (HOCs). Models that are fit to simulate impacts from these complex interactions are scarce. We developed a contaminant fate model which is linked to an ecosystem model (PCLake) for shallow lakes. This integrated model was successful in simulating long-term dynamics (1953-2012) of representative polycyclic aromatic hydrocarbons (PAHs) in the main biotic and abiotic components in a large shallow lake (Chaohu in China), which has undergone regime shifts in this period. Historical records from sediment cores were used to evaluate the model. The model revealed that regime shifts in shallow lakes had a strong impact on the fate of less hydrophobic compounds due to the large storage capacity of macrophytes, which accumulated up to 55.6% of phenanthrene in the clear state. The abrupt disappearance of macrophytes after the regime shift resulted in a sudden change in phenanthrene distribution, as the sediment became the major sink. For more hydrophobic compounds such as benzo(a)pyrene, the modeled impact of the regime shift was negligible for the whole environment, yet large for biotic compartments. This study is the first to provide a full mechanistic analysis of the impact of regime shifts on the fate of PAHs in a real lake ecosystem.

Many of the world's wetlands may be profoundly affected by climate change over the coming decades. Although wetland managers may have little control over the causes of climate change, they can help to counteract its effects through local measures. This is because direct anthropogenic impacts, such as water extraction and nutrient loading, work in concert with climate change to damage wetlands. Control of these local stressors may therefore ameliorate undesired effects of climate change, such as a shift towards dominance by invasive floating plants, increasingly frequent cyanobacteria blooms, or extinction of key species. Using the iconic Doñana wetlands in Spain as a case study, we illustrate how the concept of creating a “safe operating space” may be implemented to better ensure that ecosystems do not surpass thresholds for collapse during an era of global change., AJG was supported by a WIMEK grant for a research stay at WUR. EPM was supported by a JAE DOCTORES 2010 contract funded by the European Union (European Social Fund, ESF2007-­2013) and the Spanish Ministry for Economy and Competitiveness, as well as the EU FP7 project FAST (grant 607131). Funding was also provided by the European Union’s Horizon 2020 research and innovation program under grant agreement number 641762 to the ECOPOTENTIAL project. C Perennou provided helpful comments on earlier versions of the manuscript. Maps were made using data from CHG­ uadalquivir (www.chguadalquivir.es/ide) with QGIS (www.qgis.org) and the Google Maps API., PDF 9 pages

The amount of terrestrial particulate organic matter (t-POM) entering lakes is predicted to increase as a result of climate change. This may especially alter the structure and functioning of ecosystems in small, shallow lakes which can rapidly shift from a clear-water, macrophyte-dominated into a turbid, phytoplankton-dominated state. We used the integrative ecosystem model PCLake to predict how rising t-POM inputs affect the resilience of the clear-water state. PCLake links a pelagic and benthic food chain with abiotic components by a number of direct and indirect effects. We focused on three pathways (zoobenthos, zooplankton, light availability) by which elevated t-POM inputs (with and without additional nutrients) may modify the critical nutrient loading thresholds at which a clear-water lake becomes turbid and vice versa. Our model results show that (1) increased zoobenthos biomass due to the enhanced food availability results in more benthivorous fish which reduce light availability due to bioturbation, (2) zooplankton biomass does not change, but suspended t-POM reduces the consumption of autochthonous particulate organic matter which increases the turbidity, and (3) the suspended t-POM reduces the light availability for submerged macrophytes. Therefore, light availability is the key process that is indirectly or directly changed by t-POM input. This strikingly resembles the deteriorating effect of terrestrial dissolved organic matter on the light climate of lakes. In all scenarios, the resilience of the clear-water state is reduced thus making the turbid state more likely at a given nutrient loading. Therefore, our study suggests that rising t-POM input can add to the effects of climate warming making reductions in nutrient loadings even more urgent.

Algal blooms have caused severe problems in Lake Taihu, China. Early warning of phytoplankton accumulation can support decision-making against harmful algal bloom events. To investigate the performance of different models in forecasting high phytoplankton biomass, we developed a mechanistic, a regression and three artificial neural network (ANN) models to predict short-term (3 days) changes of phytoplankton biomass (expressed as chlorophyll-a concentration) in Gonghu Bay of Lake Taihu. We determined the input variables of the ANN models with a sensitivity analysis, and optimized their parameters with a trial-and-error approach. The sensitivity analysis revealed the effects of the input variables on phytoplankton biomass. To calibrate and validate the models, we collected two data sets of Lake Taihu in 2009: hourly-averaged data collected by an automatic monitoring system and field data with a sampling interval of twice a week. Although the sensitivity analysis results vary among the five models, there is a general consensus that phytoplankton changes are significantly affected by water temperature in Gonghu Bay. The ANN models obtained good model fit indicating their practical values in predicting non-linear phytoplankton dynamics for water management purpose. The mechanistic model predicted the phytoplanIcton distribution dynamically and described the variable interactions explicitly. The regression model is characterized by its easy development. This comparison study assists the modelers in selecting an approximate model for their specific purposes.

Complex ecological models are used to predict the consequences of anticipated future changes in climate and nutrient loading for lake water quality. These models may, however, suffer from nonuniqueness in that various sets of model parameter values may yield equally satisfactory representations of the system being modeled, but when applied in future scenarios these sets of values may divert considerably in their simulated outcomes. Compilation of an ensemble of model runs allows us to account for simulation variability arising from model parameter estimates. Thus, we propose a new approach for aquatic ecological models creating a more robust prediction of future water quality. We used our ensemble approach in an application of the widely used PCLake model for Danish shallow Lake Arreskov, which during the past two decades has demonstrated frequent shifts between turbid and clear water states. Despite marked variability, the span of our ensemble runs encapsulated 70-90% of the observed variation in lake water quality. The model exercise demonstrates that future warming and increased nutrient loading lead to lower probability of a clear water, vegetation-rich state and greater likelihood of cyanobacteria dominance. In a 6.0 degrees C warming scenario, for instance, the current nutrient loading of nitrogen and phosphorus must be reduced by about 75% to maintain the present ecological state of Lake Arreskov, but even in a near-future 2.0 degrees C warming scenario, a higher probability of a turbid, cyanobacteria-dominated state is predicted. As managers may wish to determine the probability of achieving a certain ecological state, our proposed ensemble approach facilitates new ways of communicating future stressor impacts.

Ongoing eutrophication frequently causes toxic phytoplankton blooms. This induces huge worldwide challenges for drinking water quality, food security and public health. Of crucial importance in avoiding and reducing blooms is to determine the maximum nutrient load ecosystems can absorb, while remaining in a good ecological state. These so called critical nutrient loads for lakes depend on the shape of the load-response curve. Due to spatial variation within lakes, load-response curves and therefore critical nutrient loads could vary throughout the lake. In this study we determine spatial patterns in critical nutrient loads for Lake Taihu (China) with a novel modelling approach called Spatial Ecosystem Bifurcation Analysis (SEBA). SEBA evaluates the impact of the lake's total external nutrient load on the local lake dynamics, resulting in a map of critical nutrient loads for different locations throughout the lake. Our analysis shows that the largest part of Lake Taihu follows a nonlinear load-response curve without hysteresis. The corresponding critical nutrient loads vary within the lake and depend on management goals, i.e. the maximum allowable chlorophyll concentration. According to our model, total nutrient loads need to be more than halved to reach chlorophyll-a concentrations of 30–40 μg L−1 in most sections of the lake. To prevent phytoplankton blooms with 20 μg L−1 chlorophyll-a throughout Lake Taihu, both phosphorus and nitrogen loads need a nearly 90% reduction. We conclude that our approach is of great value to determine critical nutrient loads of lake ecosystems such as Taihu and likely of spatially heterogeneous ecosystems in general.

1. A collapse of Nile perch stocks of Lake Victoria could affect up to 30million people. Furthermore, changes in Nile perch population size-structure and stocks make the threat of collapse imminent ...

UV/H2O2 treatment can be part of the process converting surface water to drinking water, but would pose a potential problem when resulting in genotoxicity. This study investigates the genotoxicity of samples collected from the water treatment plant Andijk, applying UV/H2O2 treatment with an electrical energy dose of 0.54 kWh/m(3) and a H2O2 dose of 6 mg/l. Genotoxicity was tested in vitro using the Ames and Comet assay. All samples showed negative results. Samples were also tested in in vivo genotoxicity tests in Eastern mudminnow fish (Umbra pygmaea) by a sister chromatid exchange (SCE) and a Comet assay. No significant increases in SCEs were observed, but gill cells isolated from fish exposed to water obtained immediately after UV/H2O2 treatment and to Lake IJsselmeer water showed significantly increased DNA damage in the Comet assay. All other samples tested negative in this Comet assay. This indicates that DNA damaging compounds may result from the UV/H2O2 treatment, but also that these can be efficiently eliminated upon granular activated carbon (GAC) treatment of the water. It is concluded that when combined with this subsequent GAC treatment, UV/H2O2 treatment for the production of drinking water from surface water is not of concern with respect to genotoxicity.