An integrated approach of multi-community monitoring and assessment of aquatic ecosystems to support sustainable development

Aquatic ecosystems are one of the most threatened ecosystems in the world resulting in the decline of aquatic biodiversity. Monitoring and the assessment of aquatic ecosystems are necessary to protect and conserve these ecosystems as monitoring provides insights into the changes in the aquatic ecosystem over a long period of time and assessment indicates the status of these ecosystems. This paper presents an overview of different methods for the hydromorphological, physical-chemical and the biological monitoring and assessment of surface waters. Furthermore, recently developed monitoring and assessment methods are discussed to support sustainable water management and contribute to the implementation of the Sustainable Development Goals 6 (SDG6 related to clean water and sanitation) and 15 (SDG15 related to terrestrial and freshwater systems) of the United Nations. However, many other SDGs are dependent on freshwater, such as food (e.g., SDG2) and climate-related SDGs. We presented an innovative concept for integrated monitoring and assessment. The main new elements are the monitoring of all communities and the use of integrated socio-environmental models to link these communities to ecosystem interactions and functions as a basis for determining their relation to the SDGs. Models can also allow to determine the effects of changes in SDGs on the different elements of the concept, and serve in this manner as tools for the selection of an optimal balance between the SDGs in the context of sustainable development

Advances in ecological water system modeling : integration and leanification as a basis for application in environmental management

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)

Evidence-based management of the Anzali wetland system (Northern Iran) based on innovative monitoring and modeling methods

As an “international aquatic ecosystem” in Northern Iran, the Anzali wetland is a nursery for fish and a breeding and wintering area for a wide variety of waterfowl. The wetland is threatened by human activities (deforestation, hunting, tourism, and urbanization), leading to habitat destruction, eutrophication, and sediment accumulation. To stop the degradation and to set up effective protection and restoration in line with the Sustainable Development Goals, scientific insights must be integrated into a practical framework for evidence-based support for policymakers and managers of the Anzali wetland. In this study, the Drivers–Pressure–State–Impact–Response (DPSIR) framework is used as a suitable tool to link human pressures and state changes to derive an overview of the potential impacts. Population growth, intensive agriculture, increased urbanization, and industrialization are the major driving forces that have led to a complex cascade of state changes. For instance, during recent years, water quality deterioration, habitat degradation, and the overgrowth of invasive species in the Anzali wetland watershed have caused negative socio-economic and human health impacts. Integrated and innovative monitoring programs combined with socio-environmental modeling techniques are needed for a more evidence-based management approach as part of a multiresponse strategy for the sustainable development of the wetland system. In this respect, there is a critical gap in useful information concerning biological composition and innovative monitoring methods. Moreover, the relation of biota with human activity and environmental conditions needs to be better quantified. Therefore, ecological modeling techniques based on machine learning and statistics were reviewed for their advantages and disadvantages. The overview of approaches presented here can serve as the basis for scientists, practitioners, and decision-makers to develop and implement evidence-based management programs for the Anzali wetland

Water research in support of the Sustainable Development Goal 6 : a case study in Belgium

Reaching the Sustainable Development Goal (SDG) 6 on water and sanitation is fundamentally important and conditional to the achievement of all the other SDGs. Nonetheless, achieving this goal by 2030 is challenging, especially in the Global South. Science lies at the root of sustainable development and is a key to new solutions for addressing SDG 6. However, SDG 6-related scientific outputs are often unknown, forming disconnections between academic world and practitioners implementing solutions. This study proposed a bibliometric and text mining method to qualitatively and quantitatively characterize the contribution of water research to the achievement of SDG 6. The method was applied for water research produced by Belgian-affiliated authors with a focus on the Global South collaboration. Despite accounting for less than one percent of the total global publications, Belgian water research has had a relatively high publication rate compared to its neighboring countries. We observed longstanding collaborations between Belgian and scientists from worldwide countries, and an increasing collaboration rate with countries from the Global South. The biggest share of publications focused on topics related to the targets 6.3, 6.4, 6.5, and 6.6, with the main hotspots for Belgian water research being water treatment, water stress, water pollution, climate change, and water modeling. The findings of the bibliometric search have been integrated into an online, user-friendly dashboard to facilitate the identification of research body and experts for practitioners and policy makers. The presented methodology is sufficiently generic and can be used to optimize other science programs in relation to the 2030 Agenda in other countries and regions. In this case study, the findings support shaping the Belgian cooperation and development policy in the water sector, and creating appropriate synergies between Belgian water researchers and their counterparts in the Global South

Development of a reef fish community evaluation system for the Galapagos islands

Reef fish in several islands of the Galapagos are affected via habitat deterioration, fisheries and water quality changes. Sound data acquisition and processing techniques to quantify the impact of anthropogenic pressures are therefore of paramount importance. In this study we developed an indicator system to assess the quality of fish communities. The evaluation is based on both taxonomic and trait-based approaches and allowed us to study ecosystem functioning and the role of certain species and groups in their habitats. The data were collected during a sampling campaign in 2017, during which reef fish were monitored via video recording of diver transects

BBN models as trade-off tools for ecosystem services

Human activities (e.g. agriculture and industry) have been increasing within the river basins. These agricultural and industrial impacts affect the water quality in the basin and the related ecosystem and ecosystem services. We aim to identify the link between water management options and ecosystem services, and how the ecosystem services change when certain management actions are applied. Thus, a case study in the Guayas River basin (Ecuador) is presented. A trade-off tool was developed to assess ecosystem services. A model was developed with both biophysical and management variables as input to calculate the effect on multiple ecosystem services (food production, fresh water availability and recreational value). With these three ecosystem services, a trade-off tool was constructed with the use of Bayesian Belief Networks (BBNs). Based on the model outcome, it can be stated that in general, the changes in management leading to an increase in food production, made the fresh water availability and recreational value go down. With further research on the influences of different variables on ecosystem functions and services, this BBN model can become a valuable trade-off tool to be implemented in both water and environmental management and decision making

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

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

Rwenzori Score (RS) : a benthic macroinvertebrate index for biomonitoring rivers and streams in the Rwenzori region, Uganda

The Rwenzori region in Uganda, a global biodiversity hotspot, is currently undergoing exponential economic and population growth, which puts continuous stress on its freshwater ecosystems. In Sub-Saharan Africa, biomonitoring campaigns using region-specific biotic indices is limited, particularly in Uganda. In this research, we present the Rwenzori Score (RS), a new macroinvertebrate-based biotic index developed to specifically assess the aquatic health of Rwenzori streams and rivers. We collected and measured both biological and physicochemical variables and identified 34,202 macroinvertebrates, belonging to 64 different taxa. The RS was developed in two steps. First, using canonical ordination, we identified chemical variables that correlated significantly with gradients in macroinvertebrate assemblage distribution and diversity. Second, based on selected variables and weighted averages, we determined specific family indicator values and assigned pollution tolerance values (varying from 1: tolerant; to 10: sensitive) to a family. Finally, we established four water quality classes: poor, fair, good, and excellent. The RS is highly correlated with the Average Score Per Taxon System (p < 0.05), a well-known and widely used biotic index. The RS has 5 unique taxa that are not included in other regional indices. In this regard, the development of the RS is a beneficial tool for tailor-made biomonitoring that can contribute to the sustainable development of the Rwenzori stream and river basins