Aquatic Ecosystem Model Research Articles

Development of water quality and aquatic ecosystem model for Andong lake using SWAT-WET

Development of water quality and aquatic ecosystem model for Andong lake using SWAT-WET

A Predictive Model of Chlorophyll a in Western Lake Erie Based on Artificial Neural Network

The reoccurrence of algal blooms in western Lake Erie (WLE) since the mid-1990s, under increased system stress from climate change and excessive nutrients, has shown the need for developing management tools to predict water quality. In this study, process-based model GLM-AED (General Lake Model-Aquatic Ecosystem Dynamics) and statistical model ANN (artificial neural network) were developed with meteorological forcing derived from surface buoys, airports, and land-based stations and historical monitoring nutrients, to predict water quality in WLE from 2002 to 2015. GLM-AED was calibrated with observed water temperature and chlorophyll a (Chl-a) from 2002 to 2015. For ANN, during the training period (2002–2010), the inputs included meteorological forcing and nutrient concentrations, and the target was Chl-a simulated by calibrated GLM-AED due to the lack of continuously daily measured Chl-a concentrations. During the testing period (2011–2015), the predicted Chl-a concentrations were compared with the observations. The results showed that the ANN model has higher accuracy with lower Chl-a RMSE and MAE values than GLM-AED during 2011 and 2015. Lastly, we applied the established ANN model to predict the future 10-year water quality of WLE, which showed that the probability of adverse health effects would be moderate, so more intense water resources management should be implemented.

A potential tipping point in the thermal regime of a warm monomictic reservoir under climate change using three-dimensional hydrodynamic modeling

ABSTRACT The response of the Maroon reservoir in southwest Iran is modeled to evaluate possible impacts of 21st century climate change. Projections of 3 CMIP5 General Circulation Models (GCMs) were investigated using 2 Representative Concentration Pathways (RCP4.5 and RCP8.5), which respectively represent low/medium and high greenhouse gas emission scenarios. The raw GCM projections are statistically bias-corrected to provide boundary conditions for the 3-dimensional Aquatic Ecosystem Model (AEM3D). A new overturn bias analysis method was developed to evaluate possible bias in the GCM predictors during the observational (historic) period and determined it to be negligible. The modeling results, quantified by the analysis of various limnological parameters (onset and length of mixing and stratification periods, hypolimnion and epilimnion thickness and temperature, Brunt-Väisälä frequency, and Schmidt stability) indicate for RCP4.5 a continuous reduction in winter mixing and complete suppression of mixing by the end of the 21st century, implying a switch from monomictic to weakly oligomictic behavior. Under RCP8.5, the behavior transition occurs abruptly in the late 2050s in the form of a tipping point, followed by intermittent oligomictic behavior and transition to permanent stratification (thermal meromixis) within a decade. The change in behavior occurs because the surface and mixing temperatures significantly increase due to climate warming, whereas the hypolimnion is less affected, partly because of milder warming of cold winter river inflows (underflow) and strengthening stratification. The climate change-induced tipping point for the thermal regime of Maroon reservoir might serve as an indicator of changes in other warm monomictic systems.

Short review: Which aquatic ecosystem model should Indonesian lake managers opt for?

One of the key requirements of successful water quality management in lakes and reservoirs is a good understanding of the underlying processes within the system. Lake managers, however, need a very simple practical tool to support quality regulation and policy implementation in terms of protecting and restoring these ecosystems. Here, we communicate a starting point from which lake managers, particularly in Indonesia, can gain a better understanding of aquatic ecosystem processes through the integrated application of different models. Until now, numerical aquatic ecosystem models have been used rarely in designing lake and reservoir restoration programs in Indonesia. We highlight the importance of model applications, while noting the difficulties of advancing management plans for Indonesian lakes and reservoirs.

Photoactive titanium dioxide nanoparticles modify heterotrophic microbial functioning

Nanoparticulate titanium dioxide (nTiO2) is frequently applied, raising concerns about potential side effects on the environment. While various studies have assessed structural effects in aquatic model ecosystems, its impact on ecosystem functions provided by microbial communities (biofilms) is not well understood. This is all the more the case when considering additional stressors, such as UV irradiation — a factor known to amplify nTiO2-induced toxicity. Using pairwise comparisons, we assessed the impact of UV (UV-A = 1.6 W/m2; UV-B = 0.7 W/m2) at 0, 20 or 2000 μg nTiO2/L on two ecosystem functions provided by leaf-associated biofilms: while leaf litter conditioning, important for detritivorous invertebrate nutrition, seems unaffected, microbial leaf decomposition was stimulated (up to 25%) by UV, with effect sizes being higher in the presence of nTiO2. Although stoichiometric and microbial analyses did not allow for uncovering the underlying mechanism, it seems plausible that the combination of a shift in biofilm community composition and activity together with photodegradation as well as the formation of reactive oxygen species triggered changes in leaf litter decomposition. The present study implies that the multiple functions a microbial community performs are not equally sensitive. Consequently, relying on one of the many functions realized by the same microbial community may be misleading for environmental management.

Genomic evidence for sulfur intermediates as new biogeochemical hubs in a model aquatic microbial ecosystem

BackgroundThe sulfur cycle encompasses a series of complex aerobic and anaerobic transformations of S-containing molecules and plays a fundamental role in cellular and ecosystem-level processes, influencing biological carbon transfers and other biogeochemical cycles. Despite their importance, the microbial communities and metabolic pathways involved in these transformations remain poorly understood, especially for inorganic sulfur compounds of intermediate oxidation states (thiosulfate, tetrathionate, sulfite, polysulfides). Isolated and highly stratified, the extreme geochemical and environmental features of meromictic ice-capped Lake A, in the Canadian High Arctic, provided an ideal model ecosystem to resolve the distribution and metabolism of aquatic sulfur cycling microorganisms along redox and salinity gradients.ResultsApplying complementary molecular approaches, we identified sharply contrasting microbial communities and metabolic potentials among the markedly distinct water layers of Lake A, with similarities to diverse fresh, brackish and saline water microbiomes. Sulfur cycling genes were abundant at all depths and covaried with bacterial abundance. Genes for oxidative processes occurred in samples from the oxic freshwater layers, reductive reactions in the anoxic and sulfidic bottom waters and genes for both transformations at the chemocline. Up to 154 different genomic bins with potential for sulfur transformation were recovered, revealing a panoply of taxonomically diverse microorganisms with complex metabolic pathways for biogeochemical sulfur reactions. Genes for the utilization of sulfur cycle intermediates were widespread throughout the water column, co-occurring with sulfate reduction or sulfide oxidation pathways. The genomic bin composition suggested that in addition to chemical oxidation, these intermediate sulfur compounds were likely produced by the predominant sulfur chemo- and photo-oxidisers at the chemocline and by diverse microbial degraders of organic sulfur molecules.ConclusionsThe Lake A microbial ecosystem provided an ideal opportunity to identify new features of the biogeochemical sulfur cycle. Our detailed metagenomic analyses across the broad physico-chemical gradients of this permanently stratified lake extend the known diversity of microorganisms involved in sulfur transformations over a wide range of environmental conditions. The results indicate that sulfur cycle intermediates and organic sulfur molecules are major sources of electron donors and acceptors for aquatic and sedimentary microbial communities in association with the classical sulfur cycle.-hYdWkMRSgNRZXNRu4CdmLVideo abstract

Predicting the effects of climate change on freshwater cyanobacterial blooms requires consideration of the complete cyanobacterial life cycle

Abstract To date, most research on cyanobacterial blooms in freshwater lakes has focused on the pelagic life stage. However, examining the complete cyanobacterial life cycle—including benthic life stages—may be needed to accurately predict future bloom dynamics. The current expectation, derived from the pelagic life stage, is that blooms will continue to increase due to the warmer temperatures and stronger stratification associated with climate change. However, stratification and mixing have contrasting effects on different life stages: while pelagic cyanobacteria benefit from strong stratification and are adversely affected by mixing, benthic stages can benefit from increased mixing. The net effects of these potentially counteracting processes are not yet known, since most aquatic ecosystem models do not incorporate benthic stages and few empirical studies have tracked the complete life cycle over multiple years. Moreover, for many regions, climate models project both stronger stratification and increased storm-induced mixing in the coming decades; the net effects of those physical processes, even on the pelagic life stage, are not yet understood. We therefore recommend an integrated research agenda to study the dual effects of stratification and mixing on the complete cyanobacterial life cycle—both benthic and pelagic stages—using models, field observations and experiments.

Importance of benthic-pelagic coupling in food-web interactions of Kakinada Bay, India

Benthic components occupy the sediment layer of aquatic ecosystems and play a definitive role in overall system functioning and maintenance. The exchange of inorganic and organic materials between the sediment and water column through benthic-pelagic coupling plays a very important role especially in shallow water ecosystems. It is facilitated mainly by trophic interactions between the benthic and pelagic food webs, or specifically, between the coupling links i.e. the nodes that participate in coupling. Aquatic ecosystem models incorporating benthic food web in details have been few. In the present study, a food web model incorporating both benthic and pelagic food webs has been developed using EcoPath with EcoSim software, for Kakinada Bay ecosystem of Coastal Andhra Pradesh, India and has been analysed to get an idea about this system's functioning and integrity. Hypothetical perturbation scenarios (perturbation of biomass of two important benthic components – microphytobenthos and suspension feeding invertebrates) were applied to the model to study the effects of these two components on overall system robustness and integrity. The analysis of the base model revealed that while the bay system has not yet attained maturity, it also does not face much stress. While the system saw a decline in maturity with increase in microphytobenthos (MPB) biomass, increase in biomass of suspension feeding invertebrate (SFI) resulted in the exact opposite. Study of SFI biomass perturbation scenario also highlighted its role in coupling. Modelling studies incorporating benthic components as separate groups have been few. This work aims to provide a better insight into how benthic components may affect the whole system. Information regarding system health and resilience provided by such models can also be used as guidelines for fishery management and policy making.

Introducing QWET – A QGIS-plugin for application, evaluation and experimentation with the WET model: Environmental Modelling and Software

We wish to introduce QWET, a new version of the free and open-source QGIS plugin for the aquatic ecosystem model WET. QWET is as a graphical user interface for the application, evaluation and experimentation of WET. Several new features have been incorporated since its predecessor and, here, we demonstrate elements of the new plugin by applying it to Danish Lake Ravn. Among others, we compare model simulations against observations and describe how the scenario platform now supports scheduling of state-variable manipulation, which allows users to explore lake or reservoir restoration interventions such as biomanipulation and oxygenation. With QWET, we seek to aid practitioners who do not possess the sufficient technical expertise to operate a state-of-the art complex model system, such as WET, and thereby hope to facilitate a wider use and adaptation of aquatic ecosystem models.

PyAEM: A Python toolkit for aquatic ecosystem modelling

Aquatic ecosystem modelling has been a challenging task for scientists partly due to limited tools/software to support. This study attempted to develop a Python toolkit (PyAEM) that was able to support multiple procedures in aquatic ecosystem modelling. PyAEM included improved algorithms for sensitivity analysis, parameter optimization, data assimilation and model visualization. In PyAEM, one-at-a-time and variance-based methods were implemented to identify sensitive parameters in target models. Genetic algorithm was improved for global optimization of model parameters. Ensemble Kalman Filter was implemented for assimilating multi-source measured data to improve model performance. An aquatic ecosystem model viewer was specifically developed for model visualization with the advantages of multi-scenario comparison, model fit evaluation, multi-mesh support and time series data extraction. An application overview of PyAEM in watershed and lake modelling is given, and revealed that PyAEM can be easily adapted to support the implementation of a case for aquatic ecosystem modelling.

Predicting ecosystem state changes in shallow lakes using an aquatic ecosystem model: Lake Hinge, Denmark, an example.

In recent years, considerable efforts have been made to restore turbid, phytoplankton‐dominated shallow lakes to a clear‐water state with high coverage of submerged macrophytes. Various dynamic lake models with simplified physical representations of vertical gradients, such as PCLake, have been used to predict external nutrient load thresholds for such nonlinear regime shifts. However, recent observational studies have questioned the concept of regime shifts by emphasizing that gradual changes are more common than sudden shifts. We investigated if regime shifts would be more gradual if the models account for depth‐dependent heterogeneity of the system by including the possibility of vertical gradients in the water column and sediment layers for the entire depth. Hence, bifurcation analysis was undertaken using the 1D hydrodynamic model GOTM, accounting for vertical gradients, coupled to the aquatic ecosystem model PCLake, which is implemented in the framework for aquatic biogeochemical modeling (FABM). First, the model was calibrated and validated against a comprehensive data set covering two consecutive 7‐yr periods from Lake Hinge, a shallow, eutrophic Danish lake. The autocalibration program Auto‐Calibration Python (ACPy) was applied to achieve a more comprehensive adjustment of model parameters. The model simulations showed excellent agreement with observed data for water temperature, total nitrogen, and nitrate and good agreement for ammonium, total phosphorus, phosphate, and chlorophyll a concentrations. Zooplankton and macrophyte coverage were adequately simulated for the purpose of this study, and in general the GOTM‐FABM‐PCLake model simulations performed well compared with other model studies. In contrast to previous model studies ignoring depth heterogeneity, our bifurcation analysis revealed that the spatial extent and depth limitation of macrophytes as well as phytoplankton chlorophyll‐a responded more gradually over time to a reduction in the external phosphorus load, albeit some hysteresis effects still appeared. In a management perspective, our study emphasizes the need to include depth heterogeneity in the model structure to more correctly determine at which external nutrient load a given lake changes ecosystem state to a clear‐water condition.

A system of metrics for the assessment and improvement of aquatic ecosystem models

In this paper, we introduce the CSPS framework for the hierarchical assessment of aquatic ecosystem models built on a range of metrics and characteristic signatures relevant to aquatic ecosystem condition. The framework is comprised of four levels: 0) conceptual validation; 1) comparison of simulated state variables with observations (‘state validation’); 2) comparison of fluxes with measured process rates (‘process validation’); and 3) assessment of system-level emergent properties, patterns and relationships (‘system validation’). Of these, only levels 0 and 1 are routinely undertaken at present. To highlight a diverse range of contexts relevant to the aquatic ecosystem modelling community, we present several case studies of improved validation approaches using the level 0–3 assessment hierarchy. We envision that the community–driven adoption of these metrics will lead to more rigorously assessed models, ultimately accelerating advances in model structure and function, and improved confidence in model predictions.

Characterizing Density Flow Regimes of Three Rivers with Different Physicochemical Properties in a Run-Of-The-River Reservoir

Inflow mixing affects the spatiotemporal heterogeneity of water quality in reservoirs. Reservoir water quality management requires accurate prediction of density flow regimes to understand the spatiotemporal distribution of dissolved and particulate nutrients and organics. This study aims to characterize the mixing and circulation of three rivers with different physicochemical properties in a run-of-the-river (ROR) reservoir, using high-frequency monitoring and three-dimensional (3D) hydrodynamic modeling. The Aquatic Ecosystem Model (AEM3D) was constructed for the reservoir and calibrated with high-frequency data obtained from May–June 2016, accurately reproducing the observed spatiotemporal variations of flow velocity, water temperature, and electrical conductivity (EC) in the reservoir. High-frequency data and 3D model results showed that mixing of the rivers in the ROR reservoir is governed by density flow regimes formed by influent water temperature differences. At the confluence, colder and warmer river influents formed underflows and surface buoyant overflows, respectively. The spatial arrangement of flow direction, water residence time, and EC concentration were largely controlled by the buoyancy-driven flow. Stagnant areas with long residence times corresponded with areas of observed algal blooms and hypoxia. High-frequency sensor technology, combined with 3D hydrodynamic modeling, is effective for understanding the complex flow regimes and associated water quality characteristics in ROR-type reservoirs.

Modelling inter‐annual and spatial variability of ice cover in a temperate lake with complex morphology

AbstractThe formation of ice cover on lakes alters heat and energy transfer with the water column. The fraction of surface area covered by ice and the timing of ice‐on and ice‐off therefore affects hydrodynamics and the seasonal development of stratification and related ecosystem processes. Multi‐year model simulations of temperate lake ecosystems that freeze partially or completely therefore require simulation of the formation and duration of ice cover. Here we present a multi‐year hydrodynamic simulation of an alpine lake with complex morphology (Lower Lake Constance, LLC) using the three‐dimensional (3D) model Aquatic Ecosystem Model (AEM3D) over a period of 9 years. LLC is subdivided into three basins (Gnadensee, Zeller See and Rheinsee) which differ in depth, morphological features, hydrodynamic conditions and ice cover phenology and thickness. Model results were validated with field observations and additional information on ice cover derived from a citizen science approach using information from social media. The model reproduced the occurrence of thin ice as well as its inter‐annual variability and differentiated the frequency and extent of ice cover between the three sub‐basins. It captured that full ice cover occurs almost each winter in Gnadensee, but only rarely in Zeller See and Rheinsee. The results indicate that the 3D model AEM3D is suitable for simulating long‐term dynamics of thin ice cover in lakes with complex morphology and inter‐annual changes in spatially heterogeneous ice cover.

Nature favours “one” as the leading digit in phytoplankton abundance data

Benford’s Law predicts the probability of the occurrence of leading digits and shows the first significant digit of many number series is more often 1 than any other of the digits between 1 and 9. Patterns of leading digits in multispecies phytoplankton communities utilising long-term records of phytoplankton abundance values in five lakes was studied. Phytoplankton abundance conformed to the law in individual lakes and when all datasets were combined. Opportunities for exploiting this finding include its use as a data quality control tool in large ecological data repositories, testing realism of ecological experiments and evaluating reasonableness of mathematical aquatic ecosystem models.

Environmental seasonality on predator–prey systems under nutrient and toxicant constraints

Bioaccumulation of toxicants in aquatic food webs can pose risks to ecosystem function and human health. Toxicant models of aquatic ecosystems can be improved by incorporating realistic environmental impacts such as nutrient availability and seasonality. It is well known that the carrying capacity of predator–prey systems can vary seasonally due to environmental cycles resulting from natural and human activities. As such, incorporating seasonal variation in the carrying capacity of a predator–prey system provides a better understanding of the underlying population dynamics bioaccumulation of toxicants. Here, we develop a seasonally varied predator–prey model subject to concurrent nutrient and toxicant stressors. We investigate the effects of seasonality on population dynamics to increase understanding of the complex governing processes of the trophic transfer of nutrients, energy, and toxicants. We observe that the strength of seasonality can shift solutions from periodic to quasi-periodic and models that neglect environmental seasonality may be under-predicting adverse effects of toxicity.

Predicting impacts of chemicals from organisms to ecosystem service delivery: A case study of insecticide impacts on a freshwater lake

Assessing and managing risks of anthropogenic activities to ecological systems is necessary to ensure sustained delivery of ecosystem services for future generations. Ecological models provide a means of quantitatively linking measured risk assessment endpoints with protection goals, by integrating potential chemical effects with species life history, ecological interactions, environmental drivers and other potential stressors. Here we demonstrate how an ecosystem modeling approach can be used to quantify insecticide-induced impacts on ecosystem services provided by a lake from toxicity data for organism-level endpoints. We used a publicly available aquatic ecosystem model AQUATOX that integrates environmental fate of chemicals and their impacts on food webs in aquatic environments. By simulating a range of exposure patterns, we illustrated how exposure to a hypothetical insecticide could affect aquatic species populations (e.g., recreational fish abundance) and environmental properties (e.g., water clarity) that would in turn affect delivery of ecosystem services. Different results were observed for different species of fish, thus the decision to manage the use of the insecticide for ecosystem services derived by anglers depends upon the favored species of fish. In our hypothetical shallow reservoir, water clarity was mostly driven by changes in food web dynamics, specifically the presence of zooplankton. In contrast to the complex response by fishing value, water clarity increased with reduced insecticide use, which produced a monotonic increase in value by waders and swimmers. Our study clearly showed the importance of considering nonlinear ecosystem feedbacks where the presence of insecticide changed the modeled food-web dynamics in unexpected ways. Our study highlights one of the main advantages of using ecological models for risk assessment, namely the ability to generalize to meaningful levels of organization and to facilitate quantitative comparisons among alternative scenarios and associated trade-offs among them while explicitly accounting for different groups of beneficiaries.

C:N:P stoichiometry of particulate and dissolved organic matter in river waters and changes during decomposition

BackgroundStoichiometry plays an important role in understanding nutrient composition and cycling processes in aquatic ecosystems. Previous studies have considered C:N:P ratios constant for both DOM (dissolved organic matter) and POM (particulate organic matter). In this study, water samples were collected in the six major rivers in Korea and were incubated for 20 days. C:N:P ratios were determined during the time course of the incubations. This allowed us to examine the changes in N and P contents of organic matter during decomposition.ResultsPOM and DOM showed significant differences in N and P content and the elemental ratios changed during the course of decomposition; DOM showed higher C:N and C:P ratios than POM, and the C:N and C:P ratios increased during decomposition, indicating the preferential mineralization of P over N and N over C.ConclusionsThe N and P contents of organic matter in aquatic ecosystem are far from constant and vary significantly during decomposition. More detailed information on the changes in C:N:P ratios will provide improved understanding of decomposition processes and improved modeling of aquatic ecosystems.

Food web and ecological models used to assess aquatic ecosystems submitted to aquaculture activities

ABSTRACT: Continental aquatic ecosystems play a fundamental role in economic and social development; however, they are vulnerable to environmental degradation due to the various stresses to which they are submitted. Aquaculture is among the main anthropic activities that influence these environments. Mathematical modelling of aquatic ecosystems performed using a set of computational tools allows simplified representation of environment regarding its biotic and abiotic components. Some of the most used techniques are: hydrodynamic modelling, focusing on the dispersion of nutrients; nutrient-mass balance modelling, especially phosphorus; bioenergetic modelling in animal production systems, with an estimate of the generation of residues in the environment by farmed animals; and trophic and ecological modelling, focusing on aquatic communities and their interactions. These techniques help understand changes caused by aquaculture systems in aquatic environments. In this way, it is possible to estimate the magnitude and extent of the impacts of these activities by simulating the possible environmental changes over time. It can be concluded that techniques involving mathematical modelling can provide relevant information for future impacts prediction on aquatic environments, promoting the management of water resources and their multiple uses.

Simulating eutrophication in a metacommunity landscape: an aquatic model ecosystem

Aquatic habitats are often characterized by both high diversity and the threat of multiple anthropogenic stressors. Our research deals with temporal and spatial aspects of two of the main threats for biodiversity, namely eutrophication and fragmentation. It is known that pulsed nutrient addition creates temporal differences in environmental conditions, promoting higher diversity by preventing the best competitor from dominating. Furthermore, a metacommunity landscape with intermediate connectivity increases autotrophs’ diversity and stability. However, it is yet unclear if these two factors are additive in increasing diversity and if the effects extend to the consumer level. With the goal of understanding how eutrophication impacts biodiversity in a metacommunity landscape, we hypothesized that pulsed nutrient addition will increase diversity among both autotrophs and heterotrophs, and this effect will be even greater in a metacommunity landscape. We simulated eutrophication and fragmentation in a microcosm experiment using phytoplankton as primary producers and microzooplankton as grazers. Four treatment combinations were tested including two different landscapes (metacommunity and isolated community) and two forms of nutrient supply (pulsed and continuous): metacommunity/continuous nutrient addition (MC); metacommunity/pulsed nutrient addition (MP); isolated community/continuous nutrient addition (IC); isolated community/pulsed nutrient addition (IP). As expected, pulsed nutrient addition had a persistent positive effect on phytoplankton diversity, with a weaker influence of landscape type. In contrast, the grazer community strongly benefited from a metacommunity landscape, with less significance of pulsed or continuous nutrient addition. Overall, the metacommunity landscape with pulsed nutrient supply supported higher diversity of primary producers and grazers.