•We developed species distribution models supporting river management in Flanders.•The models were based on landscape filter and ecological niche theories.•Models were scored on their accuracy and ...ecological soundness.•Stakeholder needs were considered throughout the model development process.•The approach resulted in an increased credibility and acceptability for model users.
Species distribution modelling has gained importance since the introduction of the Water Framework Directive. Several efforts have been made for the development of decision support tools to aid river basin managers. However, there is a mismatch between the available ecological models and stakeholder needs. For example, models can be so complex that they can only be applied on a limited set of species, or models can be so qualitative that they fail to deliver insight in the underlying processes behind changing ecological quality. Yet, much is known already about ecology and ecography, in general and for specific species. To valorize this available knowledge, we have developed species distribution models for macroinvertebrates in Flanders grounded in ecological theories. We introduce a conceptual approach based on niche and landscape filter theories. To apply the concept on many different macroinvertebrate species, the model development uses both data from Flanders, expert knowledge and data from other similar river systems. Implementing these niche and migration models results in a moderate predictive accuracy (average Kappa of 0.19). For sensitive species that are essential for an ecological quality status the approach results in a higher accuracy. Despite the moderate predictive accuracy, the resulting models have a good applicability. The models concur well with ecological knowledge on species preferences. Furthermore, throughout the model development process stakeholders and end users have been involved to discuss model structure and its related assumptions. This ensures that the developed model is credible and acceptable. This model approach has shown to be a way forward for ecological decision support in river management in Flanders, but inclusion of additional knowledge on migration behaviour and species interactions could help to improve the predictive accuracy the models in the future.
Current mitigation strategies to offset marine plastic pollution, a global concern, typically rely on preventing floating debris from reaching coastal ecosystems. Specifically, clean-up technologies ...are designed to collect plastics by removing debris from the aquatic environment such as rivers and estuaries. However, to date, there is little published data on their potential impact on riverine and estuarine organisms and ecosystems. Multiple parameters might play a role in the chances of biota and organic debris being unintentionally caught within a mechanical clean-up system, but their exact contribution to a potential impact is unknown. Here, we identified four clusters of parameters that can potentially determine the bycatch: (i) the environmental conditions in which the clean-up system is deployed, (ii) the traits of the biota the system interacts with, (iii) the traits of plastic items present in the system, and, (iv) the design and operation of the clean-up mechanism itself. To efficiently quantify and assess the influence of each of the clusters on bycatch, we suggest the use of transparent and objective tools. In particular, we discuss the use of Bayesian Belief Networks (BBNs) as a promising probabilistic modelling method for an evidence-based trade-off between removal efficiency and bycatch. We argue that BBN probabilistic models are a valuable tool to assist stakeholders, prior to the deployment of any clean-up technology, in selecting the best-suited mechanism to collect floating plastic debris while managing potential adverse effects on the ecosystem.
Display omitted
•Objective assessment of environmental impact of plastic clean-up technologies•Plastic clean-up technologies are fundamental to fight plastic pollution•Multiple parameters play a role in causing potential bycatch•Bayesian Belief Networks as trade-off tools between plastic removal and bycatch•BBN as a step towards a decision support framework for plastic clean-up technologies
The combination of rapid urbanization, industrialization, population growth, and low environmental awareness poses a major threat to worldwide valuable freshwater resources, which provide important ...ecosystem services to humans. There is an urgent need to monitor and assess these resources, as this information is indispensable for sustainable decision-making and management. In this context, we analyzed the chemical and ecological water quality of the riverine environment of a fast growing city in Southwest Ethiopia for which we proposed possible remediation options that were evaluated with an empirical model. The chemical and ecological water quality was assessed at 53 sampling locations using the oxygen Prati index and the ETHbios, which is a biotic index based on macroinvertebrates. In addition, a microbiological analysis was performed to estimate the degree of fecal contamination. Finally, we analyzed the relationship between the oxygen content and the organic pollution to simulate the effect of organics removal from waste streams on the chemical water quality. Our results showed that the average values for dissolved oxygen (4.2 mg DO*L-1) and nutrients (0.9 mg oPO43-*L-1 and 12.8 mg TAN*L-1) exceeded international standards. Moreover, high turbidity levels revealed that land erosion is a severe problem in the region. Along the rivers, a significant increase in oxygen consumption and in nutrient concentrations was observed, indicating organic pollution originating from different diffuse and point sources of pollution. The lack of proper sanitation also led to exceedingly high abundances of fecal coliforms in the surface water (>320 MPN*mL-1). However, fecal contamination was strongly reduced (>92%) after the polluted river water passed Boye wetland, indicating the purification potential of natural wetlands and the importance of conserving and protecting those ecosystems. The simulation results of the model showed that water quality could be substantially improved if municipal, industrial, and institutional wastewater was efficiently collected and transported to a treatment facility. Waste stabilization ponds and constructed wetlands are highly promising techniques, as they provide a cheap, effective, reliable, and sustainable way to purify wastewater. It is advised that the environmental awareness of the people via sensitization, education, and law enforcement is increased, as this is essential for sustainable development.
Aquatic macroinvertebrates, 18 physical-chemical water characteristics and 30 hydromorphological variables were assessed at 85 locations on Leyte island, Philippines. Biological traits derived from ...literature were linked to the biological samples based on four different trait estimation methods. These data were used to determine the relation with river characteristics using negative binomial regression. At least five feeding habit modalities were associated with conductivity, velocity, pH, temperature, ammonium-N concentrations, and sediment. The various methods of estimating trait abundance differ in determined major patterns and ecological implications. Therefore, the estimation method used should be explicitly described in trait-related papers to avoid misinterpretation. Trait abundance-environment relationships can be linear or non-linear and therefore a careful selection of the functional relationship should be performed. The process of extracting knowledge from data is of paramount importance as relevant ecological insights were extracted providing insights on flow, wastewater and nutrient management in the rivers.
•Biological traits were modelled with environmental river characteristics on a tropical island (Philippines).•Four data processing methodologies resulted in very different estimates of trait abundance.•The different methods of estimating trait abundance vary in determined major patterns and ecological implications.•Trait-environment relationships can be linear or non-linear, thus, selection of functional relationship should be performed.•Trait abundances increased with increasing velocity, thus flow alterations may have serious ecological implications.
Species distribution models (SDMs) have received increasing attention in freshwater management to support decision making. Existing SDMs are mainly data-driven and often developed with statistical ...and machine learning methods but with little consideration of hypothetic ecological knowledge. Conceptual SDMs exist, but lack in performance, making them less interesting for decision management. Therefore, there is a need for model identification tools that search for alternative model formulations. This paper presents a methodology, illustrated with the example of river pollution in Ecuador, using a simple genetic algorithm (SGA) to identify well performing SDMs by means of an input variable selection (IVS). An analysis for 14 macroinvertebrate taxa shows that the SGA is able to identify well performing SDMs. It is observed that uncertainty on the model structure is relatively large. The developed tool can aid model developers and decision makers to obtain insights in driving factors shaping the species assemblage.
•An approach to improve conceptual species distribution models (SDMs) is presented.•Alternative SDM formulations are found with input variables selection (IVS).•The use of genetic algorithms as a tool for IVS improves SDM performance.•Uncertainties in the structure of the identified models are present.•The proposed approach increases insight in freshwater ecosystem functioning.
The art of applied modeling is determining an appropriate balance between integration of more processes and variables for the sake of increasing representativeness and reliability of the models, ...while also avoiding too long development and simulation times. The latter can be achieved via leanification, which can be based on reducing the number of variables and processes by focusing on key processes in the system and its management, but can be as well induced by using simplified methods for the description of relations among variables (such as regression and probabilistic methods) to, for instance, reduce the simulation time. In this way, integration and leanification can be combined and together contribute to models that are more relevant and convenient for use by water managers. In particular, it is crucial to find a good balance between the integration level of ecological processes answering environmental challenges in a relevant manner and costs for data collection and model development (and application).
Although 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.
Social-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.
Adequate environmental management in tropical aquatic ecosystems is imperative. Given the lack of knowledge about functional diversity and bioassessment programs, management is missing the needed ...evidence on pollution and its effect on biodiversity and functional ecology. Therefore, we investigated the composition and distribution of the macroinvertebrate community along two rivers. Specifically, 15 locations were sampled in the Coca and Aguarico Rivers (Ecuadorian Amazon) and the macroinvertebrates were used to indicate water quality (WQ), expressed as the Biological Monitoring Working Party Colombia (BMWP-Col) classes. Results indicate that elevation, pH, temperature, width, and water depth played an important role in the taxa and functional feeding groups (FFG) composition. The results show that diversity of taxa and FFG were generally scarce but were more abundant in good quality sites. Collector-gathers (CG) were, in general, dominant and were particularly abundant at low WQ and downstream sites. Scrapers (SC) were the second most abundant group, dominating mostly at good WQ and upstream sites. Predators (PR) were homogeneously distributed among the sites, without clear dominance, and their abundance was slightly higher in sites with medium-low WQ and downstream sites. Lastly, both shredders (SH) and collector-filterers (CF) were almost absent and were more abundant in good quality sites. The findings of this research can be used as baseline information in the studied region since a dam was constructed two years after the sampling campaign, which has been operating since. Furthermore, the results can be used to fill the knowledge gaps related to the bioassessments of other similar systems, particularly for a tropical rainforest.
Only 35% of the Ecuadorian population consumes drinking water of “assured quality”. One of the causes is related to the deficiencies in the technical ability of the operators due to their lack of ...education, technical training, and experience. Massive open online courses (MOOCs) responsive to characteristics and learning needs are an option to strengthen the skills of operators. The goal of the present study is therefore to describe a methodology that includes the application of a survey and the use of statistical methods such as categorical principal component analysis (CATPCA) and cluster analysis to identify and assess learning characteristics. The results present the most frequent variables in the personal, academic, emotional, social, and cognitive aspects. They also show the preferences and learning needs of the operators. Finally, it is concluded that this study identifies common learning characteristics, needs, and preferences that are relevant for the creation of a quality personalized instructional design in MOOCs.
PDF
