Uncertainty propagation in vegetation distribution models based on ensemble classifiers

Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the uncertainty on spatial interpolation of environmental variables and the uncertainty on species clustering into vegetation types, is quantified based on sequential Gaussian simulation and pseudo-randomization tests, respectively. An empirical assessment of the uncertainty propagation to the distribution modelling results indicated a gradual decrease in performance with increasing input uncertainty. The test set error ranged from 30.83% to 52.63% and from 30.83% to 83.62%, when the uncertainty ranges on spatial interpolation and on vegetation clustering, respectively, were fully covered. Shannon’s entropy, which is proposed as a measure for uncertainty of ensemble predictions, revealed a similar increasing trend in prediction uncertainty. The implications of these results in an empirical distribution modelling framework are further discussed with respect to monitoring setup, spatial interpolation and species clustering.     

A case study of GM maize gene flow in South Africa

In order to thank Prof. Dr. Hans-Toni Ratte on the occasion of his retirement for his outstanding experimental and modelling merits in the field of ecotoxicology and ecology and his personal 65th anniversary on November 25th this article will present a laudation.     

基于斑马鱼的水生生态毒理学实验教学体系的构建

在我国现有的生态毒理学教学体系中,相对于理论教学,其实验教学体系的构建和实践相对滞后,阻碍了相关领域的人才培养。斑马鱼是国际上广受瞩目的小型模式鱼,本文在目前已成功开发并应用于科研的一系列斑马鱼毒性测试策略和方法的基础上,初步构建较为完整的水生生态毒理学实验内容和案例。虽然仅基于斑马鱼这一实验物种,但包括了致死效应、致畸效应、神经毒性、内分泌干扰效应、免疫毒性、遗传毒性等,涵盖不同生物学层面的多个毒理学终点,有助于充分训练学生的实验技能,巩固所学的理论知识。此外,在学生初步掌握上述实验手段的基础上,设置综合性或者设计性实验,可进一步培养学生的创造性思维和科研能力。本文对于现有的生态毒理学实验教学有一定的参考和借鉴意义。     

Optimal resource management control for CO2 emission and reduction of the greenhouse effect

In recent years, the world has witnessed an ever-growing concern towards global warming caused by greenhouse gases, such as carbon dioxide (CO₂). In order to reduce the emissions of CO₂ without limiting economic growth, substantial investments should target the development of clean technology and the expansion of forested areas. Considering the limited availability of resources, investments must be used in the most effective way. The present work proposes a method to efficiently manage these resources by applying the optimal control theory to a new mathematical model that describes the dynamics of the atmospheric CO₂. The contributions of this work are twofold: (1) present a model that describes the dynamic relation of CO₂ emission with investment in reforestation and clean technology and (2) present a method to efficiently manage the available resources by casting an optimal control problem. The mathematical model uses ordinary differential equations to relate the production of CO₂ with forest area and Gross Domestic Product (GDP). The model parameters are adjusted to fit the actual published data. Given an appropriate performance index, the optimal solution is found by numerically solving the Two-Point Boundary Value Problem (TPBVP) that arises from the application of Pontriagyn's Maximum Principle. The sensitivity of the obtained numerical solution is evaluated with respect to the uncertainties in the model parameters. The main objective of this work is to provide a quantitative tool for the efficient allocation of resources to reduce the greenhouse effect caused CO₂ emissions.     

Statistical evaluation of the attainment of interim cleanup standards at hazardous waste sites

Cleanup standards at hazardous waste sites include (i) numeric standards (often risk-based), (ii) background standards in which the remediated site is compared with data from a supposedly clean region, and (iii) interim standards in which the remediated site is compared with preremediation data from the same site. The latter are especially appropriate for verifying progress when an innovative, but unproven, technology is used for remediation. Standards of type (i) require one-sample statistical tests, while those of type (ii) and type (iii) call for two-sample tests. This paper considers two-sample tests with an emphasis upon the type (iii) scenario. Both parametric (likelihood ratio) and nonparametric (linear rank) protocols are examined. The methods are illustrated with preremediation data from a site on the National Priorities List. The results indicate that nonparametric procedures can be quite competitive (in terms of power) with distributional modelling provided a near optimal rank test is selected. Suggestions are given for identifying such rank tests. The results also confirm the importance of sound baseline sampling; no amount of post-remediation sampling can overcome baseline deficiencies.This paper has been prepared with partial support from the United States Environmental Protection Agency under a Cooperative Agreement Number CR-815273. The contents have not been subject to Agency review and therefore do not necessarily reflect the views or policies of the Agency and no official endorsement should be inferred.     

Motility of cryopreserved spermatozoa for the ecotoxicological evaluation of aquatic environments

A new approach to environmental studies was investigated by the authors, who propose the use of cryopreserved biological systems in ecotoxicological bioassays. The feasibility of spermiotoxicity tests using cryopreserved semen of the sea bream Sparus aurata, with sperm motility parameters as the endpoint, was evaluated. Thawed sperm was incubated in environmental samples (sediment elutriate and dumpsite leachate) and in a reference toxicant (cadmium) at scaled concentrations. Motility was then evaluated by video-microscopy using both visual and computer-assisted analyses. Activation time, sperm motility and velocity and motility duration were assessed on thawing and at the end of the incubation time, and the difference with respect to the control was statistically evaluated. All the endpoints of the bioassay proved to have good sensitivity even at the highest dilutions of the tested matrices. Observed differences in the sensitivity thresholds of the endpoints were considered to be representative of different aspects of sperm physiology. Therefore the proposed bioassay is a promising starting point for the development of toxicity tests that are increasingly tailored to the needs of ecotoxicology and environmental quality evaluation strategies for aquatic environments.     

水质转化的现代科学与技术：兼谈环境水化学实验室的科研方向

本文综述了当前环境水化学的发展趋势及其中苦干部分的研究动态与方向，例如：化学形态分布、酸化与风化、表面络合、沉积物质量评价、生态毒理、水陆交错带、水处理中的絮凝、膜分离、化学氧化、生物氧化和水质模式。离作者的若干观点及对环境水化学实验室近期研究方向的一些看法。     

Are ecological groups of species optimal for forest dynamics modelling?

The huge diversity of tree species in tropical rain-forests makes the modelling of its dynamics a difficult task. One-way to deal with it is to define species groups. A classical approach for building species groups consists in grouping species with nearby characteristics, using cluster analysis. A group of species is then characterized by the same list of attributes as a single species, and it is incorporated in the model of forest dynamics in the same way as a single species. In this paper, a new approach for building species group is proposed. It relies on the discrepancy between model predictions when all species are considered separately, and model predictions when species groups are used. An aggregation error that quantifies the bias in model predictions that results from species grouping is thus defined. We then define the optimal species grouping as the one that minimizes the aggregation error. Using data from a tropical rain-forest in French Guiana and a toy model of forest dynamics, this new method for species grouping is confronted to the classical method based on cluster analysis of the species characteristics, and to a combined method based on a cluster analysis that uses the aggregation error as a dissimilarity between species. The optimal species grouping is quite different from the classical species grouping. The ecological interpretation of the optimal groups is difficult, as there is no direct linkage between the species characteristics and the way that they are grouped. The combined approach yields species groups that are closed to the optimal ones, with much less computations. The optimal species groups are thus specific to the model of forest dynamics and lack the generality of those of the classical method, that in turn are not optimal.     

人工纳米材料对斑马鱼生态毒理效应研究进展

随着纳米技术的快速发展,人工纳米材料在光电、生物医药、化妆品等诸多领域得到了广泛应用。人工纳米材料在生产、使用和废弃处理等过程中,不可避免地通过水体、土壤、大气等进入环境,其对环境产生的生态效应逐渐引起国内外的广泛关注。斑马鱼(Danio rerio)作为一种重要的脊椎模式生物,在环境毒理学研究中应用广泛,可以作为检测人工纳米材料生态毒理效应的一种重要工具。本文介绍了人工纳米材料对水生态环境的影响及斑马鱼在生态毒理学研究中的优势,总结了其对斑马鱼的毒性效应,主要包括急性毒性和对个体发育的影响、对组织细胞及基因表达的影响,分析了人工纳米材料对斑马鱼的毒性机制,以期为人工纳米材料毒理学研究提供基础信息。     

Multi-model approach and evaluation of the uncertainty of model results. Rationale and applications to predict the behaviour of contaminants in the abiotic components of the fresh water environment

This work aims at discussing some concepts pertaining to the theory and practice of environmental modelling in view of the results of several model validation exercises performed by the group “Model validation for radionuclide transport in the system watershed-river and in estuaries” of project EMRAS (Environmental Modelling for Radiation Safety) supported by the IAEA (International Atomic Energy Agency). The analyses here performed concern models applied to real scenarios of environmental contamination. In particular, the reasons for the uncertainty of the models and the EBUA (empirically based uncertainty analysis) methodology are discussed. The foundations of multi-model approach in environmental modelling are presented and motivated. An application of EBUA to the results of a multi-model exercise concerning three models aimed at predicting the wash-off of radionuclide deposits from the Pripyat floodplain (Ukraine) was described. Multi-model approach is, definitely, a tool for uncertainty analysis. EBUA offers the opportunity of an evaluation of the uncertainty levels of predictions in multi-model applications.     

Contaminant transport in an unsaturated soil: laboratory tests and numerical simulation model as procedure for parameters evaluation

In this paper, lab tests coupled to a semi-pilot test section are used to derive data for the calibration of a numerical model. The paper is aimed at proposing a set of experiments, which can be used to calibrate a numerical model before using it on defined soils. The complexity of the phenomenon of transport of reactive pollutants in soil has to be faced in the most complete way. The different behaviour of soil after wet/dry cycles with respect to the fluidodynamic characteristics and the importance to consider the local biomass behaviour in case of organic contaminant has been underlined. An optimal approach has to take into account all the different components and here a simple series of experimental procedure is presented. The sensitivity analysis of the numerical model has shown that its results are not so much dependent on the classical numerical aspects (time or space increments) but mainly on a set of parameters related to soil structure which must then be derived through a good calibration.     

Beyond the cage: Ecosystem modelling for impact evaluation in aquaculture

An ecosystem modelling approach was used in two areas of the Eastern Mediterranean in order to examine the effects of aquaculture on the ecology of the water column. Aquaculture expansion to meet demands of a growing population is followed by concerns about keeping impacts within socially acceptable limits. Primarily the study aimed at investigating the fate of nutrients from finfish culture and evaluating changes in chemical and biological characteristics of the water body. The model used, Aquaculture Integrated Model (AIM), is based on a complex generic biogeochemical model coupled to a 3D hydrodynamic model. Selected areas included a finfish farm in the Northern Aegean, Greece and an aquaculture development area in Vassiliko, Cyprus. Ecosystem effects were evaluated on the basis of scale and importance. Scenarios under different production levels and hydrodynamic conditions were explored at the sites. Model results showed that farm discharges are rapidly dispersed from their point source in addition to a tendency for effluents to accumulate at distances not normally associated directly with farming activity. The wide range of parameters available in the model helped identify parameters more likely to be affected by the farming activities. There was a satisfactory correlation between observed and predicted model outputs. This study demonstrates the importance of approaching aquaculture impacts at an ecosystem level and the utility of a modelling tool to this end.     

Design of a Domain Specific Language for modelling processes in landscapes

The modelling of processes that occur in landscapes is often confronted to issues related to the representation of space and the difficulty of properly handling time and multiple scales. In order to investigate these issues, a flexible modelling environment is required. We propose to develop such a tool based on a Domain Specific Language (DSL) that capitalises on the service-oriented architecture (SOA) paradigm. The modelling framework around the DSL is composed of a model building environment, a code generator and compiler, and a program execution platform. The DSL introduces five language elements (entity, service, relation, scenario and datafacer) that can be combined to offer a wide range of possibilities for modelling in space and time at different scales. When developing a model, model parts are either built using the DSL or taken from libraries of previously built ones, and adapted to the specific model. The practical usage of the DSL is illustrated first with the Lotka–Volterra model, and then with a landscape modelling experiment on the spread of a mosquito-borne disease in the Sahelian region of West Africa. An interesting characteristic of this approach is the possibility of adding new elements into an existing model, and replacing others with more appropriate ones, thus allowing potentially complex models to be built from simpler parts.     

Assessing area-specific relative risks from large forest fire size in Canada

The evaluation of area-specific risks for large fires is of great policy relevance to fire management and prevention. When analyzing data for the burned areas of large fires in Canada, we found that there are dramatic patterns that cannot be adequately modelled by traditional hierarchical modelling assuming spatial autocorrelation. In this paper, we use the robust locally weighted scatterplot smoothing (LOESS) technique to remove spatial and temporal trends; and we account for periodical cycles by employing the relevant periodic functions as covariates in a hierarchical Gamma mixed effects model. Based on the results of this generalized multilevel analysis of large fire size, we provide an area-specific relative risks ranking system for Canada and confirm that lightning tends to cause more severe damage in terms of fire size than human factor. A diagnostic check on the modelling shows that large fires data are reasonably modelled using this combination of semiparametric and mixed effects modelling approaches.     

On the role of physical modelling in atmospheric and oceanic forecast

We discuss how physical modelling can be used to reproduce atmospheric or oceanic flows in the laboratory. The similarity conditions for the effects of density stratification and Earth rotation are first presented. Then examples of results obtained on the large ‘Coriolis’ platform in Grenoble are described. These include topographic wakes in a stratified fluid and gravity currents. Physical modelling is not used to get direct results of practical relevance, but rather to test numerical models on specific processes of environmental flows. Therefore it must be performed in close relationship with theory and numerical modelling, using advanced measurement and data assimilation techniques.