Political agendas worldwide include increased production of biofuel, which multiplies the trade-offs among conflicting objectives, including food and fodder production, water quantity, water quality, ...biodiversity, and ecosystem services. Quantification of trade-offs among objectives in bioenergy crop production is most frequently accomplished by a comparison of a limited number of plausible scenarios. Here we analyze biophysical trade-offs among bioenergy crop production based on rape seed, food crop production, water quantity, and water quality in the Parthe catchment in Central Germany. Based on an integrated river basin model (SWAT) and a multi-objective genetic algorithm (NSGA-II), we estimated Pareto optimal frontiers among multiple objectives. Results indicate that the same level of bioenergy crop production can be achieved at different costs with respect to the other objectives. Intermediate rapeseed production does not lead to strong trade-offs with water quality and low flow if a reduction of food and fodder production can be accepted. Compared to solutions focused on maximizing food and fodder yield, solutions with intermediate rapeseed production even improve with respect to water quality and low flow. If rapeseed production is further increased, negative effects on low flow prevail. The major achievement of the optimization approach is the quantification of the functional trade-offs for the feasible range of all objectives. The application of the approach provides the results of what is in effect an infinite number of scenarios. We offer a general methodology that may be used to support recommendations for the best way to achieve certain goals, and to compare the optimal outcomes given different policy preferences. In addition, visualization options of the resulting non-dominated solutions are discussed.
•Quantification of functional trade-offs under increasing biodiesel crop production.•Integration of a watershed model and a multi-objective optimization algorithm.•Identification of an approximately Pareto optimal set of crop rotation schemes.
•The development of species distribution models relies on machine learning algorithms.•Evolutionary algorithms (EAs) bring new insights in ecological model development.•Feature selection and ...parameter-rich model calibration are key EA training subjects.•Many learning methods used in ecology can be combined with EAs.•Adaptable and flexible frameworks for machine learning in ecology are needed.
Scientists and decision-makers need tools that can assess which specific pressures lead to ecosystem deterioration, and which measures could reduce these pressures and/or limit their effects. In this context, species distribution models are tools that can be used to help asses these pressures. Evolutionary algorithms represent a collection of promising techniques, inspired by concepts observed in natural evolution, to support the development of species distribution models. They are suited to solve non-trivial tasks, such as the calibration of parameter-rich models, the reduction of model complexity by feature selection and/or the optimization of hyperparameters of other machine learning algorithms. Although widely used in other scientific domains, the full potential of evolutionary algorithms has yet to be explored for applied ecological research. In this synthesis, we study the role of evolutionary algorithms as a machine learning technique to develop the next generation of species distribution models. To do so, we review available methods for species distribution modelling and synthesize literature using evolutionary algorithms. In addition, we discuss specific advantages and weaknesses of evolutionary algorithms and present a guideline for their application. We find that evolutionary algorithms are increasingly used to solve specific and challenging problems. Their flexibility, adaptability and transferability in addition to their capacity to find adequate solutions to complex, non-linear problems are considered as main strengths, especially for species distribution models with a large degree of complexity. The need for programming and modelling skills can be considered as a drawback for novice modellers. In addition, setting values for hyperparameters is a challenge. Future ecological research should focus on exploring the potential of evolutionary algorithms that combine multiple tasks in one learning cycle. In addition, studies should focus on the use of novel machine learning schemes (e.g. automated hyperparameter optimization) to apply evolutionary algorithms, preferably in the context of open science. This way, ecologists and model developers can achieve an adaptable and flexible framework for developing tools useful for decision management.
The formation of singlet oxygen by irradiation of gold nanoparticles in their plasmon resonance band with continuous or pulsed laser light has been investigated. Citrate-stabilized nanoparticles were ...found to facilitate the photogeneration of singlet oxygen, albeit with low quantum yield. The reaction caused by pulsed laser irradiation makes use of the equilibrated hot electrons that can reach temperatures of several thousand degrees during the laser pulse. Although less efficient, continuous irradiation, which acts via the short-lived directly excited primary “hot” electrons only, can produce enough singlet oxygen for photodynamic cancer therapy and has significant advantages for practical applications. However, careful design of the nanoparticles is needed, since even a moderately thick capping layer can completely inhibit singlet oxygen formation. Moreover, the efficiency of the process also depends on the nanoparticle size.
The main objective of the European Water Framework Directive (WFD) is the achievement of a good ecological and chemical status of the water environment (water bodies). This status corresponds to the ...limit value of Germany's Working Group of the Federal States on Water Problems Issues (LAWA) for water quality class II (3 mg/l total nitrogen). The rivers in the intensively cropped Upper Ems River basin (northwestern Germany) show total nitrogen concentrations in excess of 5-10 mg/l. Hence, the objective of our study was to find a land use and land management scenario that would reduce the total nitrogen concentration to meet the WFD requirements for good ecological and chemical status. We developed consecutive land use and management scenarios on the basis of policy instruments such as the support of agro-environmental measures by Common Agricultural Policy and regional landscape development programs. The model simulations were done by using the Soil and Water Assessment Tool (SWAT). Results of SWAT scenario calculations showed that drastic measures, which are unrealistic from a socio-economic point of view, would be needed to achieve the water quality target in the basin (reduction of arable land from 77.2% to 46% 13% organic farming, increase of pasture from 4% to 15%, afforestation from 10% to 21%, increase of protected wetlands from 0% to 9%, etc.). The example shows additionally that the achievement of the WFD targets is only possible with a consideration of regional landscape and land use distinctions. A related problem yet to be addressed is the general lack of measured water quality data with which to calibrate and validate water quality models such as SWAT. This adds considerable uncertainty to already complicated and uncertainty situations. Thus, improved strategies for water quality monitoring, and data accessibility must be established.
Historically, 131II has been a common isotope in radionuclide therapy, with 177LuLu-labelled radiopharmaceuticals now seeing a surge in use. These can include no-carrier-added or carrier-added ...177LuLu with slight impurities of 177mLuLu with a significantly longer half-life than 131II. Wastewater from therapy wards can contain a mixture of these radioisotopes. In some countries, national regulations require wastewater to be stored in dedicated systems before it is discharged into the public sewage system. To fulfill legal requirements, the nuclide specific activity concentration must be verified.BACKGROUNDHistorically, 131II has been a common isotope in radionuclide therapy, with 177LuLu-labelled radiopharmaceuticals now seeing a surge in use. These can include no-carrier-added or carrier-added 177LuLu with slight impurities of 177mLuLu with a significantly longer half-life than 131II. Wastewater from therapy wards can contain a mixture of these radioisotopes. In some countries, national regulations require wastewater to be stored in dedicated systems before it is discharged into the public sewage system. To fulfill legal requirements, the nuclide specific activity concentration must be verified.We evaluate a method for determining the activity concentration of 177mLuLu /177LuLu at equilibrium and 131II in pure and mixed samples in order to prove that the determined values are reliably below the limits for release.PURPOSEWe evaluate a method for determining the activity concentration of 177mLuLu /177LuLu at equilibrium and 131II in pure and mixed samples in order to prove that the determined values are reliably below the limits for release.We analysed the emitted energy spectrum of 1 L samples with a wastewater counter using an energy window-based approach by evaluating measurements from two different time points. Based on the law of decay and the time and energy-dependent measured values, equation systems were set up to calculate the count rates for 131II and 177mLuLu, which were converted into activity concentration using calibration factors.METHODSWe analysed the emitted energy spectrum of 1 L samples with a wastewater counter using an energy window-based approach by evaluating measurements from two different time points. Based on the law of decay and the time and energy-dependent measured values, equation systems were set up to calculate the count rates for 131II and 177mLuLu, which were converted into activity concentration using calibration factors.There is strong linear correlation between the nominal and determined activity concentrations (correlation coefficients R = 0.99; coefficient of determinations R2 = 0.99). We underestimate the actual activity concentration by a median of -1.4% for 177mLuLu and overestimate the activity concentration for 131II by a median of 7.1%.RESULTSThere is strong linear correlation between the nominal and determined activity concentrations (correlation coefficients R = 0.99; coefficient of determinations R2 = 0.99). We underestimate the actual activity concentration by a median of -1.4% for 177mLuLu and overestimate the activity concentration for 131II by a median of 7.1%.We show that an undercut of the clearance levels for material release is measurable. We analyse and determine activity concentrations of mixed samples consisting of 131II and 177mLuLu/177LuLu in equilibrium. The method is simple to implement using a conventional wastewater counter, however with a slightly increased effort, as two samples and measurements are required. The methodology can be adapted for the analysis of other nuclide mixtures.CONCLUSIONWe show that an undercut of the clearance levels for material release is measurable. We analyse and determine activity concentrations of mixed samples consisting of 131II and 177mLuLu/177LuLu in equilibrium. The method is simple to implement using a conventional wastewater counter, however with a slightly increased effort, as two samples and measurements are required. The methodology can be adapted for the analysis of other nuclide mixtures.
► Ensemble of precipitation data as input for hydrological modeling. ► Model parameter uncertainty due to considering different rain inputs. ► Ensemble combination of model outputs leads to better ...deterministic predictions. ► Bayesian Model Averaging (BMA) results in concise prediction uncertainty intervals. ► Overdispersion in BMA uncertainty for low-flow conditions (dry season).
Precipitation patterns in the tropics are characterized by extremely high spatial and temporal variability that are difficult to adequately represent with rain gauge networks. Since precipitation is commonly the most important input data in hydrological models, model performance and uncertainty will be negatively impacted in areas with sparse rain gauge networks. To investigate the influence of precipitation uncertainty on both model parameters and predictive uncertainty in a data sparse region, the integrated river basin model SWAT was calibrated against measured streamflow of the Pipiripau River in Central Brazil. Calibration was conducted using an ensemble of different precipitation data sources, including: (1) point data from the only available rain gauge within the watershed, (2) a smoothed version of the gauge data derived using a moving average, (3) spatially distributed data using Thiessen polygons (which includes rain gauges from outside the watershed), and (4) Tropical Rainfall Measuring Mission radar data. For each precipitation input model, the best performing parameter set and their associated uncertainty ranges were determined using the Sequential Uncertainty Fitting Procedure. Although satisfactory streamflow simulations were generated with each precipitation input model, the results of our study indicate that parameter uncertainty varied significantly depending upon the method used for precipitation data-set generation. Additionally, improved deterministic streamflow predictions and more reliable probabilistic forecasts were generated using different ensemble-based methods, such as the arithmetic ensemble mean, and more advanced Bayesian Model Averaging schemes. This study shows that ensemble modeling with multiple precipitation inputs can considerably increase the level of confidence in simulation results, particularly in data-poor regions.
This study demonstrates the importance of considering potential land use and management changes in climate impact research. By taking into account possible trends of economic development and ...environmental awareness, we assess effects of global warming on water availability and quality in the catchments of four European lagoons:
Ria de Aveiro
(Portugal),
Mar Menor
(Spain),
Vistula Lagoon
(Poland and Russia), and
Tyligulskyi Liman
(Ukraine). Different setups of the process-based soil and water integrated model (SWIM), representing one reference and four socio-economic scenarios for each study area: the “business as usual”, “crisis”, “managed horizons”, and “set-aside” scenarios are driven by sets of 15 climate scenarios for a reference (1971–2000) and near future (2011–2040) scenario period. Modeling results suggest a large spatial variability of potential impacts across the study areas, due to differences in the projected precipitation trends and the current environmental and socio-economic conditions. While climate change may reduce water and nutrients input to the
Ria de Aveiro
and
Tyligulsyi Liman
and increase water inflow to the
Vistula Lagoon
the socio-economic scenarios and their implications may balance out or reverse these trends. In the intensely managed
Mar Menor
catchment, climate change has no notable direct impact on water resources, but changes in land use and water management may certainly aggravate the current environmental problems. The great heterogeneity among results does not allow formulating adaptation or mitigation measures at pan-European level, as initially intended by this study. It rather implies the need of a regional approach in coastal zone management.
The Volta clam, Galatea paradoxa, is a freshwater macrobenthic bivalve which is endemic to the Lower Volta River in Ghana. The range of occurrence of the clam has been influenced by the flow regime ...in the Lower Volta which is in turn controlled by operation of two dams located upstream. Previous research has documented the changes to the Lower Volta due to the dams and attempts have been made to design environmental flows (e-flows), freshwater flows to sustain ecosystems, to inform the re-operation of the dams. The past attempts were based on the pre-dam, natural flow regime of the Lower Volta. In this study, a designer e-flow approach is explored using the Volta clam as an indicator species. Using knowledge garnered from various sources on the lifecycle, habitat and the local conditions corresponding to historical and current states of the Volta clams, the factors influencing its extent are visualized and quantified in a Bayesian belief network (BBN). Based on this BBN, an e-flow recommendation for the Lower Volta is for low flows, between 50 m3/s and 330 m3/s, for four months during the Volta clam veliger larva and recruitment life stages which occur in November to March. In addition, it is recommended that full breaching of the sandbar which regularly builds up at the Volta Estuary is done annually and that sand winning on the river bed is prohibited. These e-flow and management recommendations will have consequences for other water users and these have to be investigated, for instance by flow experiments and trade-off analysis. The results show that a BBN is potentially suitable for modelling the linkages between flows, management practices and the status of ecological indicators for the development of e-flows for highly modified rivers in data scarce regions.
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•Dam operations have altered and now control the range of the Lower Volta clam.•Bayesian belief networks can model flow, management and ecosystem linkages.•Management and flow recommendations should target most sensitive nodes in model.•Low flow dam releases from November to March will enhance Volta clam range.
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