26 research outputs found

    Optimization of habitat suitability models for freshwater species distribution using evolutionary algorithms

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    Assessing the suitable habitat for reintroduction of brown trout (Salmo trutta forma fario) in a lowland river : a modeling approach

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    Huge efforts have been made during the past decades to improve the water quality and to restore the physical habitat of rivers and streams in western Europe. This has led to an improvement in biological water quality and an increase in fish stocks in many countries. However, several rheophilic fish species such as brown trout are still categorized as vulnerable in lowland streams in Flanders (Belgium). In order to support cost-efficient restoration programs, habitat suitability modeling can be used. In this study, we developed an ensemble of habitat suitability models using metaheuristic algorithms to explore the importance of a large number of environmental variables, including chemical, physical, and hydromorphological characteristics to determine the suitable habitat for reintroduction of brown trout in the Zwalm River basin (Flanders, Belgium), which is included in the Habitats Directive. Mean stream velocity, water temperature, hiding opportunities, and presence of pools or riffles were identified as the most important variables determining the habitat suitability. Brown trout mainly preferred streams with a relatively high mean reach stream velocity (0.2-1m/s), a low water temperature (7-15 degrees C), and the presence of pools. The ensemble of models indicated that most of the tributaries and headwaters were suitable for the species. Synthesis and applications. Our results indicate that this modeling approach can be used to support river management, not only for brown trout but also for other species in similar geographical regions. Specifically for the Zwalm River basin, future restoration of the physical habitat, removal of the remaining migration barriers and the development of suitable spawning grounds could promote the successful restoration of brown trout

    Setting priorities in river management using habitat suitability models

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    Worldwide river systems are under pressure from human development. River managers need to identify the most important stressors in a stream basin, to propose effective management interventions for river restoration. In the European Union, the Water Framework Directive proposes the ecological status as the management endpoint for these interventions. Many decision support tools exist that use predictive water quality models to evaluate different river management scenarios, but only a few consider a river’s ecological status in this analysis explicitly. This paper presents a novel method, which combines abiotic monitoring data and biological monitoring data, to provide information and insight on why the ecological status does not reach the good status. We use habitat suitability models as a decision support tool, which can identify the most important stressors in river systems to define management scenarios. To this end, we disassemble the ecological status into its individual building blocks, i.e., the community composition, and we use habitat suitability models to perform an ecological gap analysis. In this paper, we present our method and its underlying ecological concepts, and we illustrate its benefits by applying the method on a regional level for Flanders using a biotic index, the Multimetric Macroinvertebrate Index Flanders (MMIF). To evaluate our method, we calculated the number of correctly classified instances (CCI = 47.7%) and the root-mean-square error (RMSE = 0.18) on the MMIF class and the MMIF value. Furthermore, there is a monotonic decreasing relationship between the results of the priority classification and the ecological status expressed by the MMIF, which is strengthened by the inclusion of ecological concepts in our method (Pearson’s R2 −0.92 vs. −0.87). In addition, the results of our method are complementary to information derived from the legal targets set for abiotic variables. Thus, our proposed method can further optimize the inclusion of monitoring data for the sake of sustainable decisions in river management

    Assessing the integration of wetlands along small European waterways to address diffuse nitrate pollution

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    Nitrate concentrations in numerous European fresh watercourses have decreased due to end-of-pipe measures towards manure and fertilization management, but fail to meet the environmental objectives. The implementation of complementary measures to attenuate diffuse nitrate pollution in densely populated regions characterised by limited available area has been barely studied. To tackle this issue, this study evaluates the feasibility of integrating Constructed Wetlands (CWs) along waterways as a promising tool to facilitate compliance with the nitrate regulations. The aim is to calculate the required area of land alongside a specific watercourse to integrate CWs to reduce nitrate concentrations consistently below the 11.3 and 5.65 mgNO(3)-N/L levels, according to the Nitrates Directive and the Flemish Environmental Regulations. Nitrate-nitrogen removal efficiencies achieved at case study CWs were compared and validated with reported values to estimate the needed wetland areas. In addition, the removal efficiencies and areas needed to meet the standards were calculated via the kinetic model by Kadlec and Knight. The predicted areas by both methods indicated that CWs of 1.4-3.4 ha could be implemented in certain regions, such as Flanders (Belgium), with restricted available land. To conclude, three designs for ICWs (Integrated Constructed Wetlands) are proposed and evaluated, assessing the feasibility of their implementation

    Assessing the ecological relevance of organic discharge limits for constructed wetlands by means of a model-based analysis

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    Polder watercourses within agricultural areas are affected by high chemical oxygen demand (COD) and biological oxygen demand (BOD5) concentrations, due to intensive farming activities and runoff. Practical cases have shown that constructed wetlands (CWs) are eco-friendly and cost-effective treatment systems which can reduce high levels of organic and nutrient pollution from agricultural discharges. However, accumulated recalcitrant organic matter, originated by in-situ sources or elements of CWs (i.e., plants or microbial detritus), limits the fulfilment of current COD discharge threshold. Thus, to evaluate its relevance regarding rivers ecosystem health preservation, we analysed the response of bio-indicators, the Multimetric Macroinvertebrate Index Flanders (MMIF) and the occurrence of organic pollution sensitive taxa towards organic pollutants. For this purpose, statistical models were developed based on collected data in polder watercourses and CWs located in Flanders (Belgium). Results showed that, given the correlation between COD and BOD5, both parameters can be used to indicate the ecological and water quality conditions. However, the variability of the MMIF and the occurrence of sensitive species are explained better by BOD5, which captures a major part of their common effect. Whereas, recalcitrant COD and the interaction among other physico-chemical variables indicate a minor variability on the bio-indicators. Based on these outcomes we suggest a critical re-evaluation of current COD thresholds and moreover, consider other emerging technologies determining organic pollution levels, since this could support the feasibility of the implementation of CWs to tackle agricultural pollution

    Using the soil and water assessment tool to simulate the pesticide dynamics in the data scarce Guayas River Basin, Ecuador

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    Agricultural intensification has stimulated the economy in the Guayas River basin in Ecuador, but also affected several ecosystems. The increased use of pesticides poses a serious threat to the freshwater ecosystem, which urgently calls for an improved knowledge about the impact of pesticide practices in this study area. Several studies have shown that models can be appropriate tools to simulate pesticide dynamics in order to obtain this knowledge. This study tested the suitability of the Soil and Water Assessment Tool (SWAT) to simulate the dynamics of two different pesticides in the data scarce Guayas River basin. First, we set up, calibrated and validated the model using the streamflow data. Subsequently, we set up the model for the simulation of the selected pesticides (i.e., pendimethalin and fenpropimorph). While the hydrology was represented soundly by the model considering the data scare conditions, the simulation of the pesticides should be taken with care due to uncertainties behind essential drivers, e.g., application rates. Among the insights obtained from the pesticide simulations are the identification of critical zones for prioritisation, the dominant areas of pesticide sources and the impact of the different land uses. SWAT has been evaluated to be a suitable tool to investigate the impact of pesticide use under data scarcity in the Guayas River basin. The strengths of SWAT are its semi-distributed structure, availability of extensive online documentation, internal pesticide databases and user support while the limitations are high data requirements, time-intensive model development and challenging streamflow calibration. The results can also be helpful to design future water quality monitoring strategies. However, for future studies, we highly recommend extended monitoring of pesticide concentrations and sediment loads. Moreover, to substantially improve the model performance, the availability of better input data is needed such as higher resolution soil maps, more accurate pesticide application rate and actual land management programs. Provided that key suggestions for further improvement are considered, the model is valuable for applications in river ecosystem management of the Guayas River basin

    Development and assessment of an integrated ecological modelling framework to assess the effect of investments in wastewater treatment on water quality

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    xxxxxWorldwide, large investments in wastewater treatment are made to improve water quality. However, the impacts of these investments on river water quality are often not quantified. To assess water quality, the European Water Framework Directive (WFD) requires an integrated approach. The aim of this study was to develop an integrated ecological modelling framework for the River Drava (Croatia) that includes physical-chemical and hydromorphological characteristics as well as the ecological river water quality status. The developed submodels and the integrated model showed accurate predictions when comparing the modelled results to the observations. Dissolved oxygen and nitrogen concentrations (ammonium and organic nitrogen) were the most important variables in determining the ecological water quality (EWQ). The result of three potential investment scenarios of the wastewater treatment infrastructure in the city of Varaždin on the EWQ of the River Drava was assessed. From this scenario-based analysis, it was concluded that upgrading the existing wastewater treatment plant with nitrogen and phosphorus removal will be insufficient to reach a good EWQ. Therefore, other point and diffuse pollution sources in the area should also be monitored and remediated to meet the European WFD standar

    Evaluation of Deep Species Distribution Models using Environment and Co-occurrences

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    International audienceThis paper presents an evaluation of several approaches of plantsspecies distribution modeling based on spatial, environmental and co-occurrences data using machine learning methods. In particular, we re-evaluate the environmental convolutional neural network model that ob-tained the best performance of the GeoLifeCLEF 2018 challenge but on arevised dataset that fixes some of the issues of the previous one. We alsogo deeper in the analysis of co-occurrences information by evaluating anew model that jointly takes environmental variables and co-occurrencesas inputs of an end-to-end network. Results show that the environmentalmodels are the best performing methods and that there is a significantamount of complementary information between co-occurrences and envi-ronment. Indeed, the model learned on both inputs allows a significant performance gain compared to the environmental model alone
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