Effect of Classification Procedure on the Performance of Numerically Defined Ecological Regions

Ecological regionalizations define geographic regions exhibiting relative homogeneity in ecological (i.e., environmental and biotic) characteristics. Multivariate clustering methods have been used to define ecological regions based on subjectively chosen environmental variables. We developed and tested three procedures for defining ecological regions based on spatial modeling of a multivariate target pattern that is represented by compositional dissimilarities between locations (e.g., taxonomic dissimilarities). The procedures use a “training dataset” representing the target pattern and models this as a function of environmental variables. The model is then extrapolated to the entire domain of interest. Environmental data for our analysis were drawn from a 400 m grid covering all of Switzerland and consisted of 12 variables describing climate, topography and lithology. Our target patterns comprised land cover composition of each grid cell that was derived from interpretation of aerial photographs. For Regionalization 1 we used conventional cluster analysis of the environmental variables to define 60 hierarchically organized levels comprising from 5 to 300 regions. Regionalization 1 provided a base-case for comparison with the model-based regionalizations. Regionalization 2, 3 and 4 also comprised 60 hierarchically organized levels and were derived by modeling land cover composition for 4000 randomly selected “training” cells. Regionalization 2 was based on cluster analysis of environmental variables that were transformed based on a Generalized Dissimilarity Model (GDM). Regionalization 3 and 4 were defined by clustering the training cells based on their land cover composition followed by predictive modeling of the distribution of the land cover clusters using Classification and Regression Tree (CART) and Random Forest (RF) models. Independent test data (i.e. not used to train the models) were used to test the discrimination of land cover composition at all hierarchical levels of the regionalizations using the classification strength (CS) statistic. CS for all the model-based regionalizations was significantly higher than for Regionalization 1. Regionalization 3 and 4 performed significantly better than Regionalization 2 at finer hierarchical levels (many regions) and Regionalization 4 performed significantly better than Regionalization 3 for coarse levels of detail (few regions). Compositional modeling can significantly increase the performance of numerically defined ecological regionalizations. CART and RF-based models appear to produce stronger regionalizations because discriminating variables are able to change at each hierarchic level.     

Microsoft Excel在环境监测数据处理方面的应用-Grubbs检验离群数据

利用Microsoft Excel创建Grubbs检验离群数据的电子表格，并介绍了该表格的使用方法。     

环境监测数值修约在Excel中的实现

本文简要介绍了环境监测技术规范中所规定的数值修约规则及相关规范要求的主要内容,并给出了相应的Excel修约公式和修约函数,可方便地用于对环境监测工作中实验测定和计算得出的各种数值进行修约。修约公式是一个利用Excel工作表函数构造的满足数值修约基本规则的工作表计算公式,在给定修约位数的前提下,可直接在工作表单元格中使用修约公式对数值进行修约,对于简单应用,具有方便、快捷、直观的特点。修约函数是一个利用Excel VBA编制的自定义函数,共有四个参数,其调用方法同工作表函数,具有针对性强、灵活、便捷的特点,可根据环境监测技术规范的特定要求,实现自动按有效位数或小数位数进行数值修约,并按相应的格式输出数据。     

农用地转用的景观生态补偿价格研究

从农用地价值的综合分析出发，提出了农用地转用的景观生态补偿价格结构。为实现农用地景观生态价值的货币化，建立了以条件价值法为核心的农用地转用的景观生态补偿价格评估模型，并以重庆市北碚区为例进行了实证研究。研究表明，开展农用地转用的环境影响评价是十分必要的，运用景观生态补偿价格评估模型估算农用地转用的景观生态补偿价格是可行的。     

Excel软件在环境监测质量控制中的应用

本文介绍了Excel软件在环境监测质量控制中的应用,结合实例详细阐述了利用Exeel软件制作Youden双样图的方法。     

Strong Influence of Variable Treatment on the Performance of Numerically Defined Ecological Regions

Numerical clustering has frequently been used to define hierarchically organized ecological regionalizations, but there has been little robust evaluation of their performance (i.e., the degree to which regions discriminate areas with similar ecological character). In this study we investigated the effect of the weighting and treatment of input variables on the performance of regionalizations defined by agglomerative clustering across a range of hierarchical levels. For this purpose, we developed three ecological regionalizations of Switzerland of increasing complexity using agglomerative clustering. Environmental data for our analysis were drawn from a 400 m grid and consisted of estimates of 11 environmental variables for each grid cell describing climate, topography and lithology. Regionalization 1 was defined from the environmental variables which were given equal weights. We used the same variables in Regionalization 2 but weighted and transformed them on the basis of a dissimilarity model that was fitted to land cover composition data derived for a random sample of cells from interpretation of aerial photographs. Regionalization 3 was a further two-stage development of Regionalization 2 where specific classifications, also weighted and transformed using dissimilarity models, were applied to 25 small scale “sub-domains” defined by Regionalization 2. Performance was assessed in terms of the discrimination of land cover composition for an independent set of sites using classification strength (CS), which measured the similarity of land cover composition within classes and the dissimilarity between classes. Regionalization 2 performed significantly better than Regionalization 1, but the largest gains in performance, compared to Regionalization 1, occurred at coarse hierarchical levels (i.e., CS did not increase significantly beyond the 25-region level). Regionalization 3 performed better than Regionalization 2 beyond the 25-region level and CS values continued to increase to the 95-region level. The results show that the performance of regionalizations defined by agglomerative clustering are sensitive to variable weighting and transformation. We conclude that large gains in performance can be achieved by training classifications using dissimilarity models. However, these gains are restricted to a narrow range of hierarchical levels because agglomerative clustering is unable to represent the variation in importance of variables at different spatial scales. We suggest that further advances in the numerical definition of hierarchically organized ecological regionalizations will be possible with techniques developed in the field of statistical modeling of the distribution of community composition.     

Anisotropy of environmental perception caused by spatial changes during locomotion

Daily perception entails an immediate awareness of the environment surrounding the body. To explore its dynamic nature during locomotion, this study tests the hypothesis that significant changes in spatial volume induce the directional focusing (i.e., anisotropy) of environmental perception. To capture perceptual activity in its natural state, we have attempted an approach using the feeling of visual pressure (i.e., felt presence) caused by the surrounding environment. In the present experiment that uses a virtual reality setup, participants were required to continuously rate their feelings while moving along a virtual outdoor route. Their ratings were analyzed in relation to environmental measurements along the route, such as the visible area of buildings and the horizontal extent of surrounding space. The relationship between the ratings and measurements was explored by using two prediction models: with and without consideration of perceptual anisotropy. The results suggested that a consideration of anisotropy improved the prediction accuracy, thereby supporting our hypothesis.     

Taking Environmental Action: The Role of Local Composition, Context, and Collective

This article explores individual and community action taken in response to perceived environmental risks by investigating the determinants of environmental action across a range of action types. A conceptual framework is first presented, which provides a foundation for investigating the role of local compositional (i.e., individual characteristics), contextual (i.e., neighborhood environment), and collective (i.e., social networks) factors in environmental action. To test the utility of the conceptual framework, a quantitative survey was administered to a random sample of households (n = 512) in Hamilton, Canada. The results suggest that the predictors of environmental action vary by action type (i.e., personal change, individual civic action, and cooperative civic action), and that factors related to perceived environmental exposure and social capital generally play a stronger, more consistent role in civic environmental action than sociodemographic or neighborhood factors. The results underscore the role of social connection in responses to perceived environmental risks.     

The effects of environmental change on individuals and groups: Some neglected issues in stress research

Homeostatic models of the effects of environmental change often entail certain assumptions that may not be warranted. It is widely assumed that the effects of negative environmental change or stress are necessarily adverse and have relatively short-term effects. It is further assumed that these effects are linear, that is, the greater the stress, the more negative the outcome. In contrast, from an ecological and developmental perspective, environmental change is seen as having possible paradoxical (i.e., positive) outcomes as well, depending upon the type and timing of the outcome assessed, and situational and individual factors. Non-linear models are reviewed for their applicability to a broader conceptualization of environmental change. This approach includes both multiple determinants and outcomes of stress, and is sensitive to ecological and developmental concerns, such as the timing and context of the stressor and possible long-term outcomes.     

Curriculum Development in Environmental Science: A Case Study on Paradigm and Institutions

/ The case of "Environment and Development" at Leiden University, the Netherlands, offers an example of developing a new environmental science curriculum in a conservative, disciplines-oriented university context. The core of this history is the long-term struggle of environmental science to evolve from the level of doing applied interdisciplinary studies and establish itself as a distinct body of knowledge with its own theory level, i.e., a discipline of its own. The struggle itself as well as its final outcome, a "bidisciplinary" curriculum in which both environmental science and one social science are expressed as disciplines (hence not environmental science as a mere "field of application") may be of value in other "classical" universities, too. KEY WORDS: Environmental science; Curriculum; Interdisciplinarity; Universities     

Physical and ecological thresholds for deposited sediments in streams in agricultural landscapes

Excessive sedimentation in streams and rivers remains a pervasive problem for the protection of aquatic habitat and the sustainability of aquatic communities. Whereas water quality criteria have been determined for suspended sediments in many jurisdictions across North America, comparably little has been done for deposited (also known as bedded) sediments. Through Canada's National Agri-Environmental Standards Initiative, assessment techniques and analytical tools were developed for estimating environmental thresholds for deposited sediments in agricultural watersheds in New Brunswick (NB) and Prince Edward Island (PEI) in the Atlantic Maritimes of Canada. Physical thresholds were developed through assessment of geomorphic metrics, which were then analyzed using y-intercept and 25th percentile approaches. For NB, there was strong agreement in physical thresholds for both analytical approaches (e.g., percent fines <2 mm were 7.5 for y-intercept and 6.9 for 25th percentile approaches). In contrast, physical thresholds for PEI differed considerably between approaches (e.g., percent fines <2 mm were 6.1 for y-intercept and 19.6 for 25th percentile approaches), likely due to a narrower range in agricultural land cover. Cross-calibration of our provisional physical thresholds for NB with ecological (i.e., benthic macroinvertebrate) assessments show that ecological thresholds, calculated as change-points in relationships between Ephemeroptera-Plecoptera-Trichoptera relative abundance or Modified Family Biotic Index and geomorphic criteria, were more liberal than physical thresholds. These results suggest that provisional thresholds developed using geomorphic criteria should demarcate change from the least disturbed condition and reduce the risk of sedimentation degrading benthic ecosystems.     

EFFECTIVENESS OF BIOPHYSICAL CRITERIA IN THE HIERARCHICAL CLASSIFICATION OF DRMNAGE BASINS1

ABSTRACT: A subwatershed base map of 84 hydrologic subregions within the Columbia River Basin (approximately 58,361,000 ha) was developed following hierarchical principles of ecological unit mapping. Our primary objectives were to inspect the relations between direct and indirect biophysical variables in the prediction of valley bottom and stream type patterns, and to identify hydrologic subregions (based on these results) that had similar aquatic patterns for which consistent management practices could be applied. Realization of these objectives required: (1) stratified subsampling of valley bottom and stream type composition within selected sub‐watersheds, (2) identification of direct and indirect biophysical variables that were mappable across the basin and that exerted primary control on the distribution of sampled aquatic patterns, and (3) development of hydrologic subregion maps based on the primary biophysical variables identified. Canonical correspondence analysis indicated that a core set of 15 direct variables (e.g., average watershed slope, drainage density, ten‐year peak flow) and 19 indirect variables (i.e., nine subsection groups, four lithology groups, and six potential vegetation settings) accounted for 31 and 30 percent (respectively) of valley bottom/stream type composition variability and 84 and 80 percent (respectively) of valley bottom/stream type environmental variability within subsamples. The 19 indirect biophysical variables identified were used to produce an ecological unit classification of 7,462 subwatersheds within the basin by a hierarchical agglomerative clustering technique (i.e., hydrologic subregions were identified). Discriminant analysis indicated that 13 direct biophysical variables could correctly assign 80 percent of the subwatersheds to their indirect biophysical classification, thus demonstrating the strong relation that exists between indirect biophysical based classifications (ecological units) and the direct biophysical variables that determine finer‐level aquatic patterns. Our hydrologic subregion classifications were also effective in explaining observed differences in management hazard ratings across all subwatersheds of the basin. Results of this research indicate that ecological units can be effectively used to produce watershed classifications that integrate the effects of direct biophysical variables on finer‐level aquatic patterns, and predict opportunities and limitations for management.     

高速公路生态型声屏障评价指标体系研究

以交通部＂西部高速公路生态型声屏障技术应用研究＂课题为依托,开展高速公路生态型声屏障评价指标体系研究。基于AHP层次分析法,提出了由功能性、环保性、景观性以及经济性4个准则层指标和23个具体评价指标构成的一套高速公路生态型声屏障评价指标体系。工程应用结果表明,该体系能客观地反映高速公路生态型声屏障特征,评价结果更趋合理...     

Vulnerability of Rehabilitated Agricultural Production Systems to Invasion by Nontarget Plant Species

Vast areas of arable land have been retired from crop production and “rehabilitated” to improved system states through landowner incentive programs in the United States (e.g., Conservation and Wetland Reserve Programs), as well as Europe (i.e., Agri-Environment Schemes). Our review of studies conducted on invasion of rehabilitated agricultural production systems by nontarget species elucidates several factors that may increase the vulnerability of these systems to invasion. These systems often exist in highly fragmented and agriculturally dominated landscapes, where propagule sources of target species for colonization may be limited, and are established under conditions where legacies of past disturbance persist and prevent target species from persisting. Furthermore, rehabilitation approaches often do not include or successfully attain all target species or historical ecological processes (e.g., hydrology, grazing, and/or fire cycles) key to resisting invasion. Uncertainty surrounds ways in which nontarget species may compromise long term goals of improving biodiversity and ecosystem services through rehabilitation efforts on former agricultural production lands. This review demonstrates that more studies are needed on the extent and ecological impacts of nontarget species as related to the goals of rehabilitation efforts to secure current and future environmental benefits arising from this widespread conservation practice.     

Geostatistical analysis and risk assessment on soil total nitrogen and total soil phosphorus in the Dongting Lake plain area, China

Nonpoint-source pollution and water body eutrophication have become increasing concerns for scientists and policymakers. Nitrogen and phosphorus affect environmental pollution, especially lake eutrophication. To assess the environmental risk of soil total nitrogen (TN) and total phosphorus (TP) pollution, a typical ecological unit of Dongting Lake plain was selected as the experimental site. To verify the stationary of the data, a moving windows technique was adopted. Our results showed that Box-Cox transformation achieved normality in the data set and dampened the effect of outliers. The best theoretical model for semivariogram of TN and TP was a spherical model. The ordinary kriging estimates of TN and TP concentrations were mapped. The integrative comparisons of semivariogram parameters with different trends to the kriging prediction errors of TN and TP indicated that the two-order trend is preferable. Kriging SDs provided valuable information that will increase the accuracy of TN and TP mapping. The probability kriging method is useful to assess the risk of N and P pollution by providing the conditional probability of N and P concentrations exceeding the threshold concentrations of 3.2 and 1.05 g/kg, respectively. The probability distribution of TN and TP at different levels will be helpful to conduct risk assessment, optimize fertilization, and control the pollution of N and P.     

Using penalty functions to evaluate aggregation models for environmental indices

The purpose of indices is to summarize a large volume of information into a single number that is easy to understand and interpret. Environmental indices provide a composite picture of an environmental condition derived from a series of observed measurements and parameters. They are used as communication tools by regulatory agencies to characterize the state of a specific environmental system (air, water, and sediments) and to study the impact of regulatory policies on various environmental management practices. In the development of environmental indices, a few issues and problems have been encountered arising as a result of the abstraction of information and data. These problems are referred to as characteristic properties that include ambiguity, eclipsing, compensation and rigidity. These characteristic properties have long been identified and interpreted in Boolean (e.g., Yes/No) or qualitative (e.g., low, medium, high) terms. In this paper, we propose a new approach to describe the above stated characteristic properties on a continuous scale to evaluate and compare the behavior of various aggregation models. Our approach is based on developing penalty functions for each characteristic property. A water quality index example by Swamee and Tyagi (2000) is used to explain our approach. A detailed case study for a developing microbial risk index is also provided to show how the proposed approach can be extended to complex hierarchical systems. Results show that it is possible to improve aggregation models for index development. Future research directions to improve index development are also discussed.     

Ecological Impact Assessment in Data-Poor Systems: A Case Study on Metapopulation Persistence

Legislation on the protection of biodiversity (e.g., European Union Habitat and Bird Directives) increasingly requires ecological impact assessment of human activities. However, knowledge and understanding of relevant ecological processes and species responses to different types of impact are often incomplete. In this paper we demonstrate with a case study how impact assessment can be carried out for situations where data are scarce but some expert knowledge is available. The case study involves two amphibian species, the great crested newt (Triturus cristatus) and the natterjack toad (Bufo calamita) in the nature reserve the Meinweg in the Netherlands, for which plans are being developed to reopen an old railway track called the Iron Rhine. We assess the effects of this railway track and its proposed alternatives (scenarios) on the metapopulation extinction time and the occupancy times of the patches for both species using a discrete-time stochastic metapopulation model. We quantify the model parameters using expert knowledge and extrapolated data. Because of our uncertainty about these parameter values, we perform a Monte Carlo uncertainty analysis. This yields an estimate of the probability distribution of the model predictions and insight into the contribution of each distinguished source of uncertainty to this probability distribution. We show that with a simple metapopulation model and an extensive uncertainty analysis it is possible to detect the least harmful scenario. The ranking of the different scenarios is consistent. Thus, uncertainty analysis can enhance the role of ecological impact assessment in decision making by making explicit to what extent incomplete knowledge affects predictions.     

年度城市环境事件评选:方法、评析及启示

政府和民众对于城市环境事件的关注越来越高,树立典型是激励良性发展的有效手段。为了提高年度城市环境事件评选的科学性和合理性,本文提出定量和定性相结合的评选方法,包含事件收集、事件筛选、事件评定三个阶段。在此基础上,对2016年度中国城市环境保护十大事件进行了评选,无锡、贵溪、三亚、珠海的案例分别代表了水、土、气、生4个专项领域环境治理和保护的先进典型;杭州、深圳、三沙的案例分别体现了以大型赛事活动为契机开展城市综合环境整治的先进经验,以及市场化的治理手段和生态技术对于城市综合治理的重要性;上海(崇明)、重庆、鄂尔多斯(库布齐地区)代表了因地制宜的区域生态文明发展模式。通过案例分析,得出如下启示:提升环境治理成效应该兼顾责任制、市场化、民主化的管理模式创新和各种技术创新;生态环境要素应该被视为城市发展的新兴增长点;城市环境保护行为具有发展和再分配双重属性,环保行为的发展属性仍有待于继续普及,而先行城市应该借鉴典型经验,积极探索通过环境保护实现经济发展的新模式。     

Using Relative Risk to Compare the Effects of Aquatic Stressors at a Regional Scale

The regional-scale importance of an aquatic stressor depends both on its regional extent (i.e., how widespread it is) and on the severity of its effects in ecosystems where it is found. Sample surveys, such as those developed by the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program (EMAP), are designed to estimate and compare the extents, throughout a large region, of elevated conditions for various aquatic stressors. In this article, we propose relative risk as a complementary measure of the severity of each stressor’s effect on a response variable that characterizes aquatic ecological condition. Specifically, relative risk measures the strength of association between stressor and response variables that can be classified as either “good” (i.e., reference) or “poor” (i.e., different from reference). We present formulae for estimating relative risk and its confidence interval, adapted for the unequal sample inclusion probabilities employed in EMAP surveys. For a recent EMAP survey of streams in five Mid-Atlantic states, we estimated the relative extents of eight stressors as well as their relative risks to aquatic macroinvertebrate assemblages, with assemblage condition measured by an index of biotic integrity (IBI). For example, a measure of excess sedimentation had a relative risk of 1.60 for macroinvertebrate IBI, with the meaning that poor IBI conditions were 1.6 times more likely to be found in streams having poor conditions of sedimentation than in streams having good sedimentation conditions. We show how stressor extent and relative risk estimates, viewed together, offer a compact and comprehensive assessment of the relative importances of multiple stressors.