185 research outputs found
Determining Tipping Points and Responses of Macroinvertebrate Traits to Abiotic Factors in Support of River Management
No full textAlthough the trait concept is increasingly used in research, quantitative relations that can support in determining ecological tipping points and serve as a basis for environmental standards are lacking. This study determines changes in trait abundance along a gradient of flow velocity, turbidity and elevation, and develops trait–response curves, which facilitate the identification of ecological tipping points. Aquatic macroinvertebrates and abiotic conditions were determined at 88 different locations in the streams of the Guayas basin. After trait information collection, a set of trait diversity metrics were calculated. Negative binomial regression and linear regression were applied to relate the abundance of each trait and trait diversity metrics, respectively, to flow velocity, turbidity and elevation. Tipping points for each environmental variable in relation to traits were identified using the segmented regression method. The abundance of most traits increased with increasing velocity, while they decreased with increasing turbidity. The negative binomial regression models revealed that from a flow velocity higher than 0.5 m/s, a substantial increase in abundance occurs for several traits, and this is even more substantially noticed at values higher than 1 m/s. Furthermore, significant tipping points were also identified for elevation, wherein an abrupt decline in trait richness was observed below 22 m a.s.l., implying the need to focus water management in these altitudinal regions. Turbidity is potentially caused by erosion; thus, measures that can reduce or limit erosion within the basin should be implemented. Our findings suggest that measures mitigating the issues related to turbidity and flow velocity may lead to better aquatic ecosystem functioning. This quantitative information related to flow velocity might serve as a good basis to determine ecological flow requirements and illustrates the major impacts that hydropower dams can have in fast-running river systems. These quantitative relations between invertebrate traits and environmental conditions, as well as related tipping points, provide a basis to determine critical targets for aquatic ecosystem management, achieve improved ecosystem functioning and warrant trait diversity
Correction: Ho, L.T.; Goethals, P.L.M. Opportunities and Challenges for the Sustainability of Lakes and Reservoirs in Relation to the Sustainable Development Goals (SDGs). Water 2019, 11, 1462
No full textIn the original article [...
Modelling the ecological impact of discharged urban waters upon receiving aquatic ecosystems. A tropical lowland river case study: city Cali and the Cauca river in Colombia
No full textThe Cauca river is one of most severe cases of pollution for domestic and industrial wastewater discharges in Colombia, principally when it crosses the industrial cities of Cali and Yumbo. The rapid urbanization and major economic development in the Cauca river´s geographical valley has led to dramatic degradation of the environment and increased health risks due to inefficient processing of the increased pollutant load effluents and solid wastes. The city of Cali which is the main urbanization center, with more than two million inhabitants and limitations of the treatment of its wastewaters, discharged in the year 2005, 75 tons of BOD5 per day. These discharges of wastewater are producing an increasing deterioration of the water quality of the Cauca river. This pollution problem is critical after the river crosses the city of Cali, especially during dry season (low flows), when pollution can reach values of 7.5 mg/l of BOD5 and concentrations of Dissolved Oxygen (DO) near to zero (0) mg/l. Low DO levels affect the ecosystem equilibrium and the functioning and survival of biological communities. For this reason, the main objective of this research was to contribute to the integrated water quality management of the Cauca river, developing a mathematical model to investigate the ecological quality of this river under actual conditions as well as after different restoration actions. The approach followed was to build habitat suitability models (statistical models) that allow predicting the presence and the abundance of macroinvertebrates in this river under different conditions. An integration of these ecological models with the hydrodynamic and physical-chemical water quality model MIKE11 was performed. The integrated ecological model allows to model and assess the ecological impact of wastewater discharges into the Cauca river and to calculate the needed reductions in discharges of organic matter to meet biological quality criteria in this river
Modelling the ecological impact of discharged urban waters upon receiving aquatic ecosystems. A tropical lowland river case study: city Cali and the Cauca river in Colombia
No full textThe Cauca river is one of most severe cases of pollution for domestic and industrial wastewater discharges in Colombia, principally when it crosses the industrial cities of Cali and Yumbo. The rapid urbanization and major economic development in the Cauca river´s geographical valley has led to dramatic degradation of the environment and increased health risks due to inefficient processing of the increased pollutant load effluents and solid wastes. The city of Cali which is the main urbanization center, with more than two million inhabitants and limitations of the treatment of its wastewaters, discharged in the year 2005, 75 tons of BOD5 per day. These discharges of wastewater are producing an increasing deterioration of the water quality of the Cauca river. This pollution problem is critical after the river crosses the city of Cali, especially during dry season (low flows), when pollution can reach values of 7.5 mg/l of BOD5 and concentrations of Dissolved Oxygen (DO) near to zero (0) mg/l. Low DO levels affect the ecosystem equilibrium and the functioning and survival of biological communities. For this reason, the main objective of this research was to contribute to the integrated water quality management of the Cauca river, developing a mathematical model to investigate the ecological quality of this river under actual conditions as well as after different restoration actions. The approach followed was to build habitat suitability models (statistical models) that allow predicting the presence and the abundance of macroinvertebrates in this river under different conditions. An integration of these ecological models with the hydrodynamic and physical-chemical water quality model MIKE11 was performed. The integrated ecological model allows to model and assess the ecological impact of wastewater discharges into the Cauca river and to calculate the needed reductions in discharges of organic matter to meet biological quality criteria in this river
Ecological informatics applied to decision support in river management : case studies for education purposes
No full textDecision Support Framework for Optimal Reservoir Operation to Mitigate Cyanobacterial Blooms in Rivers
No full textFlow control flushing water from reservoirs has been imposed in South Korea for mitigating harmful cyanobacterial blooms (CyanoHABs) in rivers. This measure, however, can cause water shortage in reservoirs, as the measure adopting this flow control may require an additional amount of water which exceeds the water demand allocated to the reservoirs. In terms of sustainability, a trade-off between improving water quality and alleviating water shortage needs to be considered. This study aimed at establishing a practical framework for a decision support system for optimal joint operation of the upstream reservoirs (Andong and Imha) to reduce the frequency of CyanoHABs in the Nakdong River, South Korea. Methodologically, three models were introduced: (1) a machine learning model (accuracy 88%) based on the k-NN (k-Nearest Neighbor) algorithm to predict the occurrence of CyanoHABs at a selected downstream location (the Chilgok Weir located approximately 140 km downstream from the Andong Dam), (2) a multiobjective optimization model employing NSGA-II (Nondominated Sorting Genetic Algorithm II) to determine both the quantity and quality of water released from the reservoirs, and (3) a river water quality model (R2 0.79) using HEC-RAS to simulate the water quality parameter at Chilgok Weir according to given upstream boundary conditions. The applicability of the framework was demonstrated by simulation results using observational data from 2015 to 2019. The simulation results based on the framework confirmed that the frequency of CyanoHABs would be decreased compared with the number of days when CyanoHABs were observed at Chilgok Weir. This framework, with a combination of several models, is a novelty in terms of efficiency, and it can be a part of a solution to the problem of CyanoHABs without using an additional amount of water from a reservoir.Water Resource
Structural and contentual complexity in water governance
No full textSocial-ecological systems and governance are complex systems and crises that affect those systems are likely to be complex as well. Environmental topics are multi-faceted with respect to both structure and content. Structural complexity is about societal and institutional organization and management, whereas contentual complexity deals with environmental (or societal) analyses, knowledge, and problem-solving. Interactions between both are manifold, and it is essential they are included in decision-making. Describing these interactions results in a series of nineteen units, arranged in a matrix according to their prevailing mutual dependencies. These units show dominant processes and concepts, representative of environmental analysis. This approach, called ACCU (aggregation of concepts and complex adapted systems units), is provided with evidence through practices of, in particular, water governance
A variable length chromosome genetic algorithm approach to identify species distribution models useful for freshwater ecosystem management
No full textPart 4: Health and BiosphereInternational audienceIncreasing pressure on freshwater ecosystems requires river managers and policy makers to take actions to protect ecosystem health. Species distribution models (SDMs) are identified as appropriate tools to assess the effect of pressures on ecosystems. A number of methods are available to model species distributions, however, it remains a challenge to identify well-performing models from a large set of candidate models. Metaheuristic search algorithms can aid to identify appropriate models by scanning possible combinations of explanatory model variables, model parameters and interaction functions. This large search space can be efficiently scanned with simple genetic algorithms (SGAs). In this paper, we test the potential of a variable length chromosome SGA to perform parameter estimation (PE) and input variable selection (IVS) for a macroinvertebrate SDM. We show that the SGA is an appropriate tool to identify fair to satisfying performing SDMs. In addition, we show that SGA performance and the uncertainty varies as a function of the chosen hyper parameters. The results can aid to further optimise the algorithm so models explaining species distributions can be identified and used for analysis in river management
Functional response (FR) and relative growth rate (RGR) do not show the known invasiveness of Lemna minuta (Kunth)
No full textGrowing travel and trade threatens biodiversity as it increases the rate of biological invasions globally, either by accidental or intentional introduction. Therefore, avoiding these impacts by forecasting invasions and impeding further spread is of utmost importance. In this study, three forecasting approaches were tested and combined to predict the invasive behaviour of the alien macrophyte Lemna minuta in comparison with the native Lemna minor: the functional response (FR) and relative growth rate (RGR), supplemented with a combined biomass-based nutrient removal (BBNR). Based on the idea that widespread invasive species are more successful competitors than local, native species, a higher FR and RGR were expected for the invasive compared to the native species. Five different nutrient concentrations were tested, ranging from low (4 mgN.L-1 and 1 mgP.L-1) to high (70 mgN.L-1 and 21 mgP.L-1). After four days, a significant amount of nutrients was removed by both Lemna spp., though significant differences among L. minor and L. minuta were only observed at lower nutrient concentrations (lower than 17 mgN.L-1 and 6 mgP.L-1) with higher nutrient removal exerted by L. minor. The derived FR did not show a clear dominance of the invasive L. minuta, contradicting field observations. Similarly, the RGR ranged from 0.4 to 0.6 d-1, but did not show a biomass-based dominance of L. minuta (0.5 ± 0.1 d-1 versus 0.63 ± 0.09 d-1 for L. minor). BBNR showed similar results as the FR. Contrary to our expectations, all three approaches resulted in higher values for L. minor. Consequently, based on our results FR is sensitive to differences, though contradicted the expectations, while RGR and BBNR do not provide sufficient power to differentiate between a native and an invasive alien macrophyte and should be supplemented with additional ecosystem-based experiments to determine the invasion impact
Variable importance for sustaining macrophyte presence via random forests : data imputation and model settings
No full textData sets plagued with missing data and performance-affecting model parameters represent recurrent issues within the field of data mining. Via random forests, the influence of data reduction, outlier and correlated variable removal and missing data imputation technique on the performance of habitat suitability models for three macrophytes (Lemna minor, Spirodela polyrhiza and Nuphar lutea) was assessed. Higher performances (Cohen’s kappa values around 0.2–0.3) were obtained for a high degree of data reduction, without outlier or correlated variable removal and with imputation of the median value. Moreover, the influence of model parameter settings on the performance of random forest trained on this data set was investigated along a range of individual trees (ntree), while the number of variables to be considered (mtry), was fixed at two. Altering the number of individual trees did not have a uniform effect on model performance, but clearly changed the required computation time. Combining both criteria provided an ntree value of 100, with the overall effect of ntree on performance being relatively limited. Temperature, pH and conductivity remained as variables and showed to affect the likelihood of L. minor, S. polyrhiza and N. lutea being present. Generally, high likelihood values were obtained when temperature is high (>20 °C), conductivity is intermediately low (50–200 mS m−1) or pH is intermediate (6.9–8), thereby also highlighting that a multivariate management approach for supporting macrophyte presence remains recommended. Yet, as our conclusions are only based on a single freshwater data set, they should be further tested for other data sets
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