An isobole-based statistical model and test for synergism/antagonism in binary mixture toxicity experiments

Synergism and antagonism are often defined in relation to the model of Concentration Addition (CA). Hence, it is vital for the conclusion of mixture toxicity studies to be able to test whether an observed deviation from CA reflects a true deviation or whether it is simply due to random variation. In this paper we consider a non-linear regression model for the classical ray designs for binary mixture experiments. The model combines dose–response curves for each mixture in the experiment with an isobole model, describing possible deviations from CA. The method allows us to test whether the chosen isobole model is reasonable for the data and to test the hypothesis of CA. Furthermore, it provides us with a measure of the degree of synergism/antagonism. The method is flexible since both the dose–response relationships and the isobole model can be chosen arbitrarily. We demonstrate the use of the method on datasets where combinations of pesticides are tested on a floating plant, Lemna minor, and an algae, Pseudokirchneriella subcapitata. Furthermore, we conduct a simulation study in order to explore the power with which a specific deviation from CA can be distinguished in different test-systems.     

The dynamics of shifting cultivation captured in an extended Constrained Cellular Automata land use model

This paper presents an extension to the Constrained Cellular Automata (CCA) land use model of White et al. [White, R., Engelen, G., Uljee, I., 1997. The use of constrained cellular automata for high-resolution modelling of urban land-use dynamics. Environment and Planning B: Planning and Design 24(3), 323–343] to make it better suited for modelling the dynamics of shifting cultivation. In the extended model the time passed since the last land use transition of a location is a factor of its land use potential. The model can now account for the gradual decrease in soil fertility after an area of forest has been cleared for cultivation and also capture the process of regeneration once the plot is fallowed. The model is applied for the Ruhunupura area of Sri Lanka where chena, a particular practice of shifting cultivation, is a common land use that dominates the landscape dynamics. The model is calibrated for the period 1985–2001 and the results are assessed in terms of location to location overlap as well as structural similarity at multiple scales. These results give confidence in the representation of land use dynamics for the main land use classes. On the basis of a long term scenario run for the period 2001–2030, it is verified that the model captures stylized facts related to chena dynamics, in particular shortening fallow periods and increasingly long cultivation periods of chena, as a result of increasing land use pressure.     

Selecting parameters for calibration via sensitivity analysis: An individual-based model of mosquitofish population dynamics

A stochastic individual-based model (IBM) of mosquitofish population dynamics in experimental ponds was constructed in order to increase, virtually, the number of replicates of control populations in an ecotoxicology trial, and thus to increase the statistical power of the experiments. In this context, great importance had to be paid to model calibration as this conditions the use of the model as a reference for statistical comparisons. Accordingly, model calibration required that both mean behaviour and variability behaviour of the model were in accordance with real data. Currently, identifying parameter values from observed data is still an open issue for IBMs, especially when the parameter space is large. Our model included 41 parameters: 30 driving the model expectancy and 11 driving the model variability. Under these conditions, the use of “Latin hypercube” sampling would most probably have “missed” some important combinations of parameter values. Therefore, complete factorial design was preferred. Unfortunately, due to the constraints of the computational capacity, cost-acceptable “complete designs” were limited to no more than nine parameters, the calibration question becoming a parameter selection question. In this study, successive “complete designs” were conducted with different sets of parameters and different parameter values, in order to progressively narrow the parameter space. For each “complete design”, the selection of a maximum of nine parameters and their respective n values was carefully guided by sensitivity analysis. Sensitivity analysis was decisive in selecting parameters that were both influential and likely to have strong interactions. According to this strategy, the model of mosquitofish population dynamics was calibrated on real data from two different years of experiments, and validated on real data from another independent year. This model includes two categories of agents; fish and their living environment. Fish agents have four main processes: growth, survival, puberty and reproduction. The outputs of the model are the length frequency distribution of the population and the 16 scalar variables describing the fish populations. In this study, the length frequency distribution was parameterized by 10 scalars in order to be able to perform calibration. The recently suggested notion of “probabilistic distribution of the distributions” was also applied to our case study, and was shown to be very promising for comparing length frequency distributions (as such).     

Simulating forest succession after blowdown events: The crucial role of space for a realistic management

Ecological patterns vary in space and time. Therefore, when using dynamic models in ecology, the spatial aspect should not be neglected prematurely since it could possibly change the model outcomes to a considerable extent. In view of this problem, we describe here a method how to construct a non-spatial version from a spatially explicit simulation model. The principle idea is to suppress the spatial correlations of cells in a grid in time by continuously re-assigning a random neighbourhood for each cell on the grid. Since this procedure actually eliminates the spatial dimensions, it allows to quantify the unadulterated impact of spatial processes on the model results. To illustrate an important application of this approach in the context of forest management we use a grid-based model that simulates succession of Norway spruce (Picea abies (L.) Karst.) at mountainous sites after blowdown events. The output of this model is compared with the results of the deduced non-spatial version of this model regarding the predicted amount of re-growing trees. The non-spatial version dramatically overestimates the number of spruce trees on different microsites. Thus, the uncritical use of the non-spatial model might give reason to wrong management decisions that are based on too optimistic predictions. In practice, this may lead to dangerous situations, especially in mountain forests serving as protection against avalanches and landslides. This example demonstrates the successful applicability of our approach. Our method can be interpreted as a contribution to an extended sensitivity analysis: it analyses the sensitivity of the results due to structural changes of the model. This sensitivity allows one to estimate the redundancy or the necessity of spatially explicit processes in a model with regard to the parsimony principle of modelling. Since our approach is not dependent on special features of the simulation model used here, it is assumed to be applicable for other spatial models, too, and can thus be considered of general interest for a diligent model analysis.     

Models of withdrawing renewable and non-renewable resources based on Odum's energy systems theory and Daly's quasi-sustainability principle

This paper presents a theoretical model of withdrawing resources based on Odum's energy systems diagrams. According to the theory of a general pulsing principle, withdrawing resources changes in time shifting from the initial phases of growth and maturity to the phases of descent and low energy restoration. A simulation was performed in order to hypothesize potential future trends of withdrawing renewable and non-renewable resources and to show some aspects of their sustainability–unsustainability, respectively. According to Odum's theory, after the rapid growth of the last century, our civilization is living in a climax transition phase and it is now approaching a descent phase. A “way down” will be necessary due to the exhaustion of non-renewable and to the limited use of renewable resources. An integrated “renew–non-renew” model was developed by Odum to show how a “business as usual” trend will bring us to a drastic transition to a world that uses scarce renewable resources. Nevertheless, a different choice is possible, based on Daly's concept of quasi-sustainability that can inspire a new model. The latter argued that the exploitation of a non-renewable resource must be paired with a compensating investment in a renewable substitute. Our model shows that we can use non-renewable resources better to considerably improve our capacity of capturing renewable resources in the future. We present this as a necessary condition to address a sustainable environmental policy.     

A CFD-based wind solver for an urban fast response transport and dispersion model

In many cities, ambient air quality is deteriorating leading to concerns about the health of city inhabitants. In urban areas with narrow streets surrounded by clusters of tall buildings, called street canyons, air pollution from traffic emissions and other sources may accumulate resulting in high pollutant concentrations. For various situations, including the evacuation of populated areas in the event of an accidental or deliberate release of chemical, biological and radiological agents, it is important that models should be developed that produce urban flow fields quickly. Various computational techniques have been used to calculate these flow fields, but these techniques are often computationally intensive. Most fast response models currently in use are at a disadvantage in these cases as they are unable to correlate highly heterogeneous urban structures with the diagnostic parameterizations on which they are based. In this paper, a novel variant of the popular projection method for solving the Navier–Stokes equations has been developed and applied to produce fast and reasonably accurate parallel computational fluid dynamics (CFD) solutions for flow in complex urban areas. This model, called QUIC-CFD represents an intermediate balance between fast (on the order of minutes for a several block problem) and reasonably accurate solutions. This paper details the solution procedure and validates this model for various simple and complex urban geometries.     

Evaluation of Reynolds stress, k-ε and RNG k-ε turbulence models in street canyon flows using various experimental datasets

In this study the Reynolds-averaged Navier-Stokes computational fluid dynamics methodology is used, which has proved to be a powerful tool for the simulations of the airflow and pollutant dispersion in the atmospheric environment. The interest is focused on the urban areas and more specifically on the street canyons, several types of which are examined in order to evaluate the performance of various turbulence models, including a Reynolds-stress model and variations of the k-ε model. The results of the two-dimensional simulations are compared with measurements from a diversity of independent street canyon experimental datasets, covering a wide range of aspect ratios, free stream velocities and roughnesses. This way more general and reliable conclusions can be reached about the applicability, accuracy and ease of use of each turbulence model. In this work, the renormalization group k-ε presented better results in most cases examined, while the Reynolds-stress model did not stand up for the expectations and also exhibited convergence problems.     

Modeling seasonal course of carbon fluxes and evapotranspiration in response to low temperature and moisture in a boreal Scots pine ecosystem

Environmental conditions act above and below ground, and regulate carbon fluxes and evapotranspiration. The productivity of boreal forest ecosystems is strongly governed by low temperature and moisture conditions, but the understanding of various feedbacks between vegetation and environmental conditions is still unclear. In order to quantify the seasonal responses of vegetation to environmental factors, the seasonality of carbon and heat fluxes and the corresponding responses for temperature and moisture in air and soil were simulated by merging a process-based model (CoupModel) with detailed measurements representing various components of a forest ecosystem in Hyytiälä, southern Finland. The uncertainties in parameters, model assumptions, and measurements were identified by generalized likelihood uncertainty estimation (GLUE). Seasonal and diurnal courses of sensible and latent heat fluxes and net ecosystem exchange (NEE) of CO₂ were successfully simulated for two contrasting years. Moreover, systematic increases in efficiency of photosynthesis, water uptake, and decomposition occurred from spring to summer, demonstrating the strong coupling between processes. Evapotranspiration and NEE flux both showed a strong response to soil temperature conditions via different direct and indirect ecosystem mechanisms. The rate of photosynthesis was strongly correlated with the corresponding water uptake response and the light use efficiency. With the present data and model assumptions, it was not possible to precisely distinguish the various regulating ecosystem mechanisms. Our approach proved robust for modeling the seasonal course of carbon fluxes and evapotranspiration by combining different independent measurements. It will be highly interesting to continue using long-term series data and to make additional tests of optional stomatal conductance models in order to improve our understanding of the boreal forest ecosystem in response to climate variability and environmental conditions.     

Constrained ordination analysis with flexible response functions

Canonical correspondence analysis (CCA) is perhaps the most popular multivariate technique used by environmental ecologists for constrained ordination; it is an approximation to the maximum likelihood solution of the Gaussian response model. In this article, we look at the constrained ordination problem from a slightly different point of view and argue that it is this particular point of view that CCA implicitly adopts. This gives us additional insights into the nature of CCA. We then exploit the new perspective to generalize the Gaussian response model to incorporate more flexible response functions. A real example is presented to illustrate the use of the more flexible model.     

Dynamic environ analysis of compartmental systems: A computational approach

Ecosystems are often modeled as stocks of matter or energy connected by flows. Network environ analysis (NEA) is a set of mathematical methods for using powers of matrices to trace energy and material flows through such models. NEA has revealed several interesting properties of flow–storage networks, including dominance of indirect effects and the tendency for networks to create mutually positive interactions between species. However, the applicability of NEA is greatly limited by the fact that it can only be applied to models at constant steady states. In this paper, we present a new, computationally oriented approach to environ analysis called dynamic environ approximation (DEA). As a test of DEA, we use it to compute compartment throughflow in two implementations of a model of energy flow through an oyster reef ecosystem. We use a newly derived equation to compute model throughflow and compare its output to that of DEA. We find that DEA approximates the exact results given by this equation quite closely – in this particular case, with a mean Euclidean error ranging between 0.0008 and 0.21 – which gives a sense of how closely it reproduces other NEA-related quantities that cannot be exactly computed and discuss how to reduce this error. An application to calculating indirect flows in ecosystems is also discussed and dominance of indirect effects in a nonlinear model is demonstrated.     

Analysing the effects of soil properties changes associated with land use changes on the simulated water balance: A comparison of three hydrological catchment models for scenario analysis

This paper presents results of a model comparison study within the LUCHEM framework (‘assessing the impact of Land Use Change on Hydrology by Ensemble Modelling’) where the effects of land use change on catchment water balances were assessed with various hydrological catchment models. The motivation for this part of LUCHEM is that it is well known that land use changes may induce changes in soil chemical and soil physical properties (e.g. bulk density). Unfortunately the effects of land use change on soil hydraulic properties are seldom investigated directly, but some information on changes in bulk density is available. Changes in bulk density can be used as input for pedotransfer functions to derive changes in soil hydraulic model parameters. In this study, three different catchment models (SWAT, TOPLATS, WASIM) are compared with respect to their sensitivity to land use change with and without consideration of associated changes in soil parameterisation. The results reveal that different models show a different sensitivity to the change in soil parameterisation while the magnitude of absolute changes in simulated evapotranspiration and discharge is similar. SWAT calculates largest changes in the water balance in a German mesoscale catchment. TOPLATS also shows significant changes in the calculated catchment water balances as well as in the runoff generation while WASIM reacts least sensitive. While TOPLATS and WASIM show similar patterns with respect to changes in the water flows for all subcatchments and land use scenarios, SWAT results are similar for the different catchments, but show scenario specific patterns. In relation to the magnitude of the effects on simulated water flows induced by land use change, the significance of considering soil change effects depends on both, the scenario definition and on the model sensitivity to soil parameterisation. For two of the three land use scenarios representing an intensified land use, SWAT and TOPLATS simulate water balance changes in the same order of magnitude due to both, land use and soil property changes. Therefore, a consideration of changes in soil properties as part of land use change scenario analysis is recommended. Future field work needs to aim at the validation of the assumed dependency of soil hydrologic properties on land use change.     

Enhancing submerged coastal constructions by incorporating multifunctional purposes

Surfing has becoming more and more attractive in the past few decades, constituting nowadays an important source of revenue for many countries with extensive coastlines. For this purpose and also for environmental reasons, the conventional ways of protecting a coastline appear to entail some disadvantages. An innovative and interesting way of improving surfing capacities and contributing to protect a local coastal zone is by means of multifunctional artificial reefs. A multifunctional artificial reef (MFAR) is a submerged structure that serves several purposes; in particular, it may enhance the surfing possibilities and the environmental value of the local area. This structure has some promising new aspects, too: first, it provides an unimpaired visual amenity; second, it offers tourist and economic benefits by improving the surfing conditions; third, it can enhance the environmental value of the area where it is built, and fourth, if designed properly, the down drift erosion can be minimal. An appropriate reef design in terms of ‘surfability’, i.e. the possibility to surf a wave, for the Leirosa beach, located to the south of Figueira da Foz, midway along Portugal’s West Atlantic coast, has been investigated. In order to achieve the best design several steps were conducted. First, the performance of the Boussinesq-type COULWAVE model is tested with experimental data. Next, this numerical model is used to define the best values for three design parameters: reef angle; geometry of the reef (without or with a platform), and horizontal dimensions for the appropriate geometry. A preliminary design was achieved step by step, making use of the theory and of the state of the art of multifunctional reefs. This reef geometry is used in the numerical study. In terms of ‘surfability’ and for the conditions of the local coastline of Leirosa, the following values were found for the main parameters: a reef angle of 66°; a structure height of 3.20 m; a reef geometry composed of a delta without a platform; a reef submergence of 1.50 m, and a structure seaward slope of 1:10.     

Ein Indikator für den Einsatz gefährlicher Stoffe in Produkten und Prozessen: Monoethylenglykol-Äquivalente

In order to quantify hazardous substance use in production processes, a special methodology has been designed within the context of the EcoGrade integrated environmental assessment method developed by the Öko-Institut, Institute for Applied Ecology. This methodology uses monoethylene glycol (MEG) equivalents as an indicator value for hazardous substance use. MEG equivalents permit direct, noxious-substance-focussed comparison of processes and products (Bunke 2001). The assessment is based upon the standardized risk phrases assigned to the component substances. The MEG equivalent methodology is a refinement and application of the potency factor model (Wirkfaktorenmodell) of the German Technical Rule for Hazardous Substances (Technische Regel für Gefahrstoffe, TRGS) 440 (AGS 2001). The data required for the assessment procedure are available within companies (safety data sheets) or are readily accessible publicly (hazardous substance databanks). A further benefit is that inventory analysis of hazardous substances using the method presented here makes it possible to take hazardous substance use into account in a systematic manner within life-cycle assessment (LCA) studies. The methodology has been tested for the example of residential buildings. Note: The terms ‘hazardous substance’, ‘noxious substance’ and ‘hazardous constituent’ are used in this paper in the sense of substances that have one of the hazard attributes set out in Article 3 of the German Chemicals Act (Chemikaliengesetz).     

Non-homogeneous Poisson models with a change-point: an application to ozone peaks in Mexico city

In this paper, we use some non-homogeneous Poisson models in order to study the behavior of ozone measurements in Mexico City. We assume that the number of ozone peaks follows a non-homogeneous Poisson process. We consider four types of rate function for the Poisson process: power law, Musa–Okumoto, Goel–Okumoto, and a generalized Goel–Okumoto rate function. We also assume that a change-point may or may not be present. The analysis of the problem is performed by using a Bayesian approach via Markov chain Monte Carlo methods. The best model is chosen using the DIC criterion as well as graphical approach.     

Null models reveal preferential sampling, spatial autocorrelation and overfitting in habitat suitability modelling

Nowadays, species are driven to extinction at a high rate. To reduce this rate it is important to delineate suitable habitats for these species in such a way that these areas can be suggested as conservation areas. The use of habitat suitability models (HSMs) can be of great importance for the delineation of such areas. In this study MaxEnt, a presence-only modelling technique, is used to develop HSMs for 223 nematode species of the Southern Bight of the North Sea. However, it is essential that these models are beyond discussion and they should be checked for potential errors. In this study we focused on two categories (1) errors which can be attributed to the database such as preferential sampling and spatial autocorrelation and (2) errors induced by the modelling technique such as overfitting, In order to quantify these adverse effects thousands of nulls models were created. The effect of preferential sampling (i.e. some areas where visited more frequenty than others) was investigated by comparing model outcomes based from null models sampling the actual sampling stations and null models sampling the entire mapping area (Raes and ter Steege, 2007). Overfitting is exposed by a fivefold cross-validation and the influence of spatial autocorrelation is assessed by separating test and training sets in space. Our results clearly show that all these effects are present: preferential sampling has a strong effect on the selection of non-random species models. Crossvalidation seems to have less influence on the model selection and spatial autocorrelation is also strongly present. It is clear from this study that predefined thresholds are not readily applicable to all datasets and additional tests are needed in model selection.     

Verification of fractal growth models of the sponge Haliclona oculata (Porifera) with transplantation experiments

The growth form of the sponge Haliclona oculata is to a significant extent determined by the environmental conditions in which the form emerges. One of the main environmental parameters affecting the growth form is exposure to water movement. In this study, a morphological growth model is used to simulate the effect on the growth process of a change in exposure to water movement. Predictions based on the model are verified by experiments in which sponges from a sheltered growth site are transplanted to an exposed site, and vice versa. The effect of the transplantation on growth forms is determined by morphological comparisons. By combining the morphological simulation model with interpretation of growth forms, it becomes possible to use the growth form of H. oculata for bio-monitoring purposes. This form reflects the environmental conditions governing the growth process.     

农药和化肥对无尾两栖类蝌蚪的毒性效应研究进展

以两栖动物研究环境污染物的毒性效应进而监测环境的变化,已成为国内外的研究热点.两栖类的胚胎发育和变态过程对水的依赖性极强,而且鳃和皮肤有很强的渗透性,当其受到污染胁迫时,在细胞、组织及生理生化水平上都会发生显著变化,进而会影响其存活和生长发育.在总结国内外相关研究基础上,综述和分析了农药、化肥(氮肥)对无尾两栖类蝌蚪的行为表现、生长发育、组织结构和生理生化变化等方面的毒性效应,以期为农药、化肥的水环境监测及合理使用提供全面的科学依据.     

Uncertainty analysis of a pharmacokinetic modeling for inorganic arsenic

This paper presents an uncertainty and sensitivity analysis of a pharmacokinetic modeling of inorganic arsenic deposition in rodents for a short‐term exposure. Efforts to develop the pharmacokinetic model are directed towards predicting the kinetic behavior of inorganic arsenic in the body, including tissue and blood concentrations, and especially, the urinary excretion of arsenic and its methylated metabolites. However, the use of the model raises an important question when fixed values of model parameters are used: how is the uncertainty in the model prediction based on the collective uncertainties in the model inputs? This study focuses on an “epistemic”; uncertainty in order to handle this problem. In this case, the uncertainty refers to an input that has a single value which cannot be known with precision due to a lack of knowledge about items or its measurement. The combination of the pharmacokinetic model and the uncertainty analysis would help understand the uncertainties in risk assessment associated with inorganic arsenic.     

Fuzzy modelling of chlorophyll production in a Brazilian upwelling system

In the context of coastal management the aim of this paper is to present the development of a fuzzy model through the application of a Genetic algorithm in order to select the most appropriate set of variables and improve our understanding with a set of rules. The case studied is the chlorophyll response as bioindicator of ecological status in the Northeast coastal upwelling system of Rio de Janeiro state, Southeastern of Brazil. The prediction of the fuzzy model has shown an improved performance when compared to the traditional approaches as Multiple Regression modelling. The results show that the set of inferred rules can assess three different water masses. Despite the increased occurrence of upwelling is observed in spring–summer period and some instability of the model, it is able to forecast some chlorophyll peaks. We conclude that the sampling frequency is crucial to reach a better performance.     

基于修正遗传算法的夏玉米作物系数及蒸散发估算

农田蒸散量是作物蒸腾量和土壤蒸发量的总和,准确估算农田蒸散量对制定合理的灌溉计划至关重要,进而对农作物的增产保收具有重要的意义。研究作物系数及蒸散量估算模型已成为一个热点科学问题。淮河流域是中国主要的农业生产基地,而夏玉米是淮河流域最主要的粮食作物之一。为研究夏玉米全生育期蒸散估算模型,反映夏玉米逐日作物系数及蒸散量的变化,为当地的农业生产活动提供指导,采用五道沟水文实验站称重式蒸渗仪及气象要素实测数据,应用遗传算法,构建夏玉米全生育期单作物系数蒸散模型,得到其4个生长阶段的作物系数估算值。其中,参考作物蒸散量采用FAO PenmanMonteith公式计算;对估算误差较大的发育期,利用叶面积指数和发育期天数构建调整模型,对发育期作物系数进行数值修正,取得了较好的效果,并进一步估算蒸散量,最终得到遗传算法与多项式回归相结合的夏玉米蒸散估算模型。结果表明:全生育期内,修正后作物系数计算值与实际值的平均绝对误差为0.09,均方根误差为0.12,准确率(绝对误差<0.3)为96.2%;蒸散量计算值与实际值的平均绝对误差为0.89 mm·d^-1,均方根误差为1.28 mm·d^-1,准确率(绝对误差<4 mm·d^-1)为100%;相比FAO推荐的作物系数模型,修正遗传算法模型作物系数和蒸散量的拟合准确率均明显提高,达到精度要求,该文修正遗传算法模型可用于夏玉米的蒸散估算。