Variable importance for sustaining macrophyte presence via random forests : data imputation and model settings

Data 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

Functional response (FR) and relative growth rate (RGR) do not show the known invasiveness of Lemna minuta (Kunth)

Growing 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

Links and trade-offs between fisheries and environmental protection in relation to the sustainable development goals in Thailand

The fisheries sector significantly contributes to global food security, nutrition, and livelihood of people. Its importance for economic benefits, healthy diets, and nutrition, and achieving sustainable food systems is highlighted by several Sustainable Development Goals (SDGs), i.e., SDG 1 (No Poverty), SDG 2 (Zero Hunger), and SDG 14 (Life Below Water). However, due to unprecedented population levels, the contribution of the fisheries sector to fulfills these roles is challenging, particularly given additional concerns regarding environmental well-being and sustainability. From this perspective, this study aims to identify the links and trade-offs between the development of this sector and the environmental sustainability in Thailand via a critical analysis of their trends, current ecological impacts, and more importantly, their contributions to several individual SDGs. A time-series of Thailand's fisheries production from 1995 to 2015 indicates a recent reduction from around 3.0 million tons in 1995 to 1.5 million tons in 2015 of wild fish and shellfish from marine and freshwater habitats. The maximum sustainable yield of these species has been exceeded. Conversely, Thailand's aquaculture production has continued to grow over the last decade, resulting in a reduction of mangrove forest area, wild fish stocks, and water quality. While capture fisheries and aquaculture production significantly contribute to several SDG targets, there are potential trade-offs between their development and the achievement of SDGs within the planet dimension, i.e., SDG 6 (Clean Water and Sanitation), SDG 12 (Responsible Consumption and Production), SDG 13 (Climate Action), SDG 14, and SDG 15 (Life on Land). On the one hand, the mitigation of overfishing will be beneficial for the targets of SDG 14, leading to more sustainable resource management. On the other hand, it might cause a decrease in the volume of marine catches and economic and social profits. We conclude that the SDGs can serve as a framework for both policymakers and industrial workers to monitor and compromise on regulations that will optimize productivity in the context of sustainable development

A practical protocol for the experimental design of comparative studies on water treatment

The design and execution of effective and informative experiments in comparative studies on water treatment is challenging due to their complexity and multidisciplinarity. Often, environmental engineers and researchers carefully set up their experiments based on literature information, available equipment and time, analytical methods and experimental operations. However, because of time constraints but mainly missing insight, they overlook the value of preliminary experiments, as well as statistical and modeling techniques in experimental design. In this paper, the crucial roles of these overlooked techniques are highlighted in a practical protocol with a focus on comparative studies on water treatment optimization. By integrating a detailed experimental design, lab experiment execution, and advanced data analysis, more relevant conclusions and recommendations are likely to be delivered, hence, we can maximize the outputs of these precious and numerous experiments. The protocol underlines the crucial role of three key steps, including preliminary study, predictive modeling, and statistical analysis, which are strongly recommended to avoid suboptimal designs and even the failure of experiments, leading to wasted resources and disappointing results. The applicability and relevance of this protocol is demonstrated in a case study comparing the performance of conventional activated sludge and waste stabilization ponds in a shock load scenario. From that, it is advised that in the experimental design, the aim is to make best possible use of the statistical and modeling tools but not lose sight of a scientific understanding of the water treatment processes and practical feasibility

Statistically-Based Comparison of the Removal Efficiencies and Resilience Capacities between Conventional and Natural Wastewater Treatment Systems: A Peak Load Scenario

Emerging global threats, such as climate change, urbanization and water depletion, are driving forces for finding a feasible substitute for low cost-effective conventional activated sludge (AS) technology. On the other hand, given their low cost and easy operation, nature-based systems such as constructed wetlands (CWs) and waste stabilization ponds (WSPs) appear to be viable options. To examine these systems, a 210-day experiment with 31 days of peak load scenario was performed. Particularly, we conducted a deliberate strategy of experimentation, which includes applying a preliminary study, preliminary models, hypothetical tests and power analysis to compare their removal efficiencies and resilience capacities. In contrast to comparable high removal efficiencies of organic matter-around 90%-both natural systems showed moderate nutrient removal efficiencies, which inferred the necessity for further treatment to ensure their compliance with environmental standards. During the peak period, the pond treatment systems appeared to be the most robust as they indicated a higher strength to withstanding the organic matter and nitrogen shock load and were able to recover within a short period. However, high demand of land-2.5 times larger than that of AS-is a major concern of the applicability of WSPs despite their lower operation and maintenance (O&M) costs. It is also worth noting that initial efforts on systematic experimentation appeared to have an essential impact on ensuring statistically and practically meaningful results in this comparison study

Model-based analysis of increased loads on the performance of activated sludge and waste stabilization ponds

In a way to counter criticism on low cost-effective conventional activated sludge (AS) technology, waste stabilization ponds (WSPs) offer a valid alternative for wastewater treatment due to their simple and inexpensive operation. To evaluate this alternative with respect to its robustness and resilience capacity, we perform in silico experiments of different peak-load scenarios in two mathematical models representing the two systems. A systematic process of quality assurance for these virtual experiments is implemented, including sensitivity and identifiability analysis, with non-linear error propagation. Moreover, model calibration of a 210-day real experiment with 31 days of increased load was added to the evaluation. Generally speaking, increased-load scenarios run in silico showed that WSP systems are more resilient towards intermediate disturbances, hence, are suitable to treat not only municipal wastewater, but also industrial wastewater, such as poultry wastewater, and paperboard wastewater. However, when disturbances are extreme (over 7000 mg COD.L-1), the common design of the natural system fails to perform better than AS. Besides, the application of sensitivity analysis reveals the most influential parameters on the performance of the two systems. In the AS system, parameters related to autotrophic bacteria have the highest influence on the dynamics of particulate organic matter, while nitrogen removal is largely driven by nitrification and denitrification. Conversely, with an insignificant contribution of heterotrophs, the nutrient removal in the pond system is mostly done by algal assimilation. Furthermore, this systematic model-based analysis proved to be a suitable means for investigating the maximum load of wastewater treatment systems, and from that avoiding environmental problems and high economic costs for cleaning surface waters after severe overload events