Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

Watershed Regressions for Pesticides (warp) Models for Predicting Atrazine Concentrations in Corn Belt Streams1

Stone, Wesley W. and Robert J. Gilliom, 2012. Watershed Regressions for Pesticides (WARP) Models for Predicting Atrazine Concentrations in Corn Belt Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 970‐986. DOI: 10.1111/j.1752‐1688.2012.00661.x Abstract: Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region‐specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP‐CB) were developed for annual maximum moving‐average (14‐, 21‐, 30‐, 60‐, and 90‐day durations) and annual 95th‐percentile atrazine concentrations in streams of the Corn Belt region. The WARP‐CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model‐development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model‐development sites. The WARP‐CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine‐use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP‐CB models. The WARP‐CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine‐use intensities of 17 kg/km² of watershed area or greater.     

Water quality trends and changing agricultural practices in a midwest U.S. watershed, 1994-2006

Sediment and nutrient concentrations in surface water in agricultural regions are strongly influenced by agricultural activities. In the Corn Belt, recent changes in farm management practices are likely to affect water quality, yet there are few data on these linkages at the landscape scale. We report on trends in concentrations of N as ammonium (NH(4)) and nitrate (NO(3)), soluble reactive phosphorus (SRP), and suspended sediment (SS) in three Corn Belt streams with drainage areas of 12 to 129 km(2) for 1994 through 2006. During this period, there has been an increase in conservation tillage, a decline in fertilizer use, and consolidation of animal feeding operations in our study watersheds and throughout the Corn Belt. We use an autoregressive moving average model to include the effects of discharge and season on concentrations, LOWESS plots, and analyses of changes in the relation between discharge and concentration. We found significant declines in mean monthly concentrations of NH(4) at all three streams over the 13-yr period, declines in SRP and SS in two of the three streams, and a decline in NO(3) in one stream. When trend coefficients are converted to percent per year and weighted by drainage, area changes in concentration are -8.5% for NH(4), -5.9% for SRP, -6.8% for SS, and -0.8% for NO(3). Trends in total N and P are strongly tied to trends in NO(3), SRP, and SS and indicate that total P is declining, whereas total N is not.     

Landscape-level ecological regions: Linking state-level ecoregion frameworks with stream habitat classifications

Regionalization is a form of spatial classification, where boundaries are drawn around areas that are relatively homogeneous in landscape characteristics. The process of delineating ecological regions, or ecoregions, includes the analysis of ecosystem structure. To date, ecoregions have been developed at national and state scales for research and resource management. Stream classification is another method to order the variability of aquatic habitats that spans spatial scales from microhabitat to valley segment. In this study, landscape-level ecoregions are developed for the upper Grande Ronde River basin in northeastern Oregon, 3000 sq km in area. The ecoregion framework presented here is proposed to bridge the gap between stream habitat and state-level ecoregion classifications. Classification at this scale is meant to address issues of management at local scales: to aid in sampling design, in extrapolation of the results of site-specific studies, and in the development of best management practices that are more predictive of ecosystem response than current methods.     

Effective Transboundary Aquifer Areas: An Approach for Transboundary Groundwater Management

The natural complexity, heterogeneity, and extent of transboundary aquifers around the world, have led to controversy over which method or criteria should be used to identify and delineate their boundaries. Currently, there is no standard methodology that aquifer‐sharing countries can use to delineate the area of a transboundary aquifer. In the case of Mexico and Texas, Mexico uses administrative boundaries, whereas Texas uses geological boundaries. This paper proposes a method for delineation and prioritization of aquifers (or aquifer areas) called effective transboundary aquifer areas (ETAAs), which uses a combination of physical criteria (geological boundaries, topography, and hydrography) and the location and density of active water wells in the borderland between Mexico and Texas. This method identifies the area of priority (productivity area) in the aquifer using pumping patterns or hot spots regardless of the aquifer’s surficial geological limits, therefore offering a more effective, local and practical management option at the transboundary level. Different geological features or pumping patterns will have different sizes and locations of ETAAs within the same aquifer. In West Texas, which is dominated by bolsons, the method produces limited options for ETAAs, whereas in South Texas in the easternmost border the identified ETAAs are more significant.     

Correspondence between spatial patterns in fish assemblages in ohio streams and aquatic ecoregions

Land classification systems can be useful for assessing aquatic ecosystems if relationships among them exist. Because the character of an aquatic ecosystem depends to a large extent upon the character of the landscape it drains, spatial patterns in aquatic ecosystems should correspond to patterns in the landscape. To test this hypothesis, the US state of Ohio was divided into four aquatic ecoregions based on an analysis of spatial patterns in the combination of land-surface form, land use, potential natural vegetation, and soil parent material. During the period July–October 1983, fish assemblages were sampled in 46 streams that were representative of the ecoregions, and that had watersheds relatively undisturbed by human activities. Spatial patterns of the fish assemblages were examined relative to the ecoregions; distinct regional differences were identified. The assemblages differed most between the Huron/Erie Lake Plain region and the Western Allegheny Plateau region; assemblages in the Eastern Corn Belt Plains and the Erie/Ontario Lake Plain-Interior Plateau regions were intermediate. This pattern also reflects the gradient in landscape character as one moves from the northwest to the southeast of Ohio.     

A Regional Classification Scheme for Estimating Reference Water Quality in Streams Using Land-Use-Adjusted Spatial Regression-Tree Analysis

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States.     

Comparing the Use of Indigenous Knowledge with Classification and Ordination Techniques for Assessing the Species Composition and Structure of Vegetation in a Tropical Forest

dentification of groups that are similar in their floristic composition and structure (habitat types) is essential for conservation and forest managers to allocate high priority areas and to designate areas for reserves, refuges, and other protected areas. In this study, the use of indigenous knowledge for the identification of habitat types in the field was compared against an ecological characterization of habitat types, including their species composition obtained by using classification and ordination techniques for a tropical landscape mosaic in a rural Mayan area of Quintana Roo, Mexico. Plant diversity data calculated from 141 sampled sites chosen randomly on a vegetation class’s thematic map obtained by multispectral satellite image classification were used for this propose. Results indicated high similarity in the categorization of vegetation types between the Mayan classification and those obtained by cluster and detrended correspondence analysis. This suggests that indigenous knowledge has a practical use and can be comparable to that obtained by using science-based methods. Finally, identification and mapping of vegetation classes (habitat types) using satellite image classification allowed us to discriminate significantly different species compositions, in such a way that they can provide a useful mechanism for interpolating diversity values over the entire landscape.     

Multivariate Analysis of the Ecoregion Delineation for Aquatic Systems

The ecoregion concept is a popular method of understanding the spatial distribution of the environment', however, it has yet to be adequately demonstrated that the environment is distributed in accordance with these bounded units. In this paper, we generated a testable hypothesis based on the current usage of ecoregions: the ecoregion classification will allow for discrimination between lakes of different water quality. The ecoregion classification should also be more effective better than a comparably scaled classification based on political boundaries, land-use class, or random grouping. To test this hypothesis we used the Environmental Monitoring and Assessment Program (EMAP) lake water chemistry data from the northeast United States. The water chemistry data were reduced to four components using principal component analysis. For comparison to an optimal grouping of these data we used K-means cluster analysis to define the extent at which these lakes could be segregated into distinct classes. Jackknifed discriminant analysis was used to determine the classification rate of ecoregions, the three alternative spatial classification methods, and the clustering algorithm. The classification based on ecoregions was successful for 35% of the lakes included in this study, in comparison to the clustered groups accuracy of 98%. These results suggest that the large scale spatial distribution of ecosystem types is more complicated than that suggested by the present ecoregion boundaries. Further tests of ecoregion delineations are needed and alternative large-scale management strategies should be investigated.     

基于全产业链视角实施生态资产管理

生态资产是人类赖以生存的基本条件,当前研究尚未充分关注人类活动对生态资产的影响。本文从社会经济系统的全产业链视角出发,探讨产业链不同环节的生产消费活动对生态资产的影响以及所对应的不同政策内涵。分析结果表明,产业链的不同环节对应不同政策内涵,识别不同环节上的关键区域/行业能够为不同类型的政策决策指出着力点。初始投入环节的核算服务于人力资本投入行为的调控;初始生产环节的核算服务于末端控制手段,包括资源节约与污染物减排;中间生产环节和末端生产环节的核算服务于提升生产效率的政策手段;最终消费环节的核算服务于消费行为优化。最终得出应该从全产业链视角实施多环节生态资产管理的结论,并提出,为了从全产业链视角实施生态资产管理,应考虑建立一套标准化、全产业链视角的生态资产需求核算框架,建设支持全产业链视角核算生态资产需求的基础数据库,将全产业链视角管理生态资产的思维融入政策决策等建议。     

基于模糊聚类的生态功能区若干指标定量划分的研究

以江苏省沿东陇海线地区为研究区域,利用遥感与G IS工具,研究基于模糊聚类与若干定量指标的生态功能区划方法。该方法选取了5个指标用于区划过程,首先将研究区域分成5×5km大小的空间单元,并提取各单元属性数据生成属性矩阵,利用M atlab模糊逻辑工具箱对单元进行模糊聚类。参照聚类结果与其他资料进行了生态功能区划,并根据区划结果对各分区的产业发展与生态保护提出了建议。     

鄂尔多斯某区域石油开发生态环境变化分析

通过回顾鄂尔多斯盆地某地区石油开发以来区域生态环境变化,分析研究区目前的生态环境质量现状及石油开发等经济活动对区域生态环境的影响。利用GIS(地理信息系统)软件的最大值合成法(MVC)对研究区1989—2010年植被覆盖度遥感MODIS(中分辨率成像光谱仪)数据进行解译。研究结果表明:研究区石油开发以来,生态环境的变化特征能够反映出该地区社会经济发展客观规律以及随之带来的环境问题,对研究区制定环境保护与资源开发政策具有一定参考意义。     

A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE

A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.     

Factors influencing transboundary wildlife management in the North American ‘Crown of the Continent’

Jurisdictional boundaries and borders are rarely coincident with ecological systems. The long-term persistence of viable wildlife populations and habitats, especially for highly mobile and migratory species, is contingent upon effective management that transcends administrative boundaries. Although transboundary natural resource management has emerged as a topic of academic and professional discourse, implementation has been hampered by a host of barriers that include institutional, administrative, financial and contextual factors. The Crown Managers Partnership, a collaborative initiative of public land managers in the transboundary Rocky Mountains of Canada and the United States, is exploring the approaches to overcome these barriers. This paper reports on the results of interviews to identify the factors that influence the management of transboundary wildlife and provides a series of recommendations that are specific to the study area context, but are also transferable to other regions. Formalizing the existing partnership, exploring options for expanding participation in the partnership to include non-government interests, engaging third party facilitation, using non-traditional data sources, applying metapopulation ecology theory, and interdisciplinary problem solving are all elements recommended for improved transboundary management and of wildlife in the Crown of the Continent Ecosystem.     

“一带一路”绿色发展的战略实施框架

本研究认为推进实施绿色化"一带一路"战略是我国与沿线各国深化经济合作,展示负责任大国形象,规避环境风险,促进顺利实现"五通"的根本要求。同时,我国实施绿色化"一带一路"战略还面临着对外投资的环境管控制度不健全,"一带一路"沿线不少国家和地区生态环境脆弱,环境管理基础弱,以及沿线各国和地区发展阶段及环保诉求不同,区域合作平台与机制不完善等内外因素带来的挑战。本文结合我国实施"一带一路"战略的国际、国内形势研判,提出了推进"一带一路"绿色发展的战略框架,建议加快推进四项重点工作,包括强化绿色发展规划顶层设计,健全风险规制机制,构建对外投资行为调控机制,形成有效的"共通"保障机制。     

我国低碳转型进程中碳强度与电气化环境库兹涅茨倒U形关联的检验与政策启示

中国正在积极地谋求低碳化转型,政府承诺落实2030年前碳达峰的目标并努力争取2060年实现碳中和。碳强度控制是实现CO_2减排的关键制度,而电气化又与碳排放和经济增长都具有紧密的联系。因此,研究电气化与碳强度的关系对政策设计和制定碳强度控制政策具有重要意义。基于电气化与碳强度关系的现有研究,本文提出了碳排放强度随着电气化水平提高先上升后下降的环境库兹涅茨曲线(EKC)关系假设。本文以中国1997—2016年30个省份的面板数据为对象进行假设检验,并使用空间杜宾模型验证空间效应对结果的影响。结果显示,我国电气化与碳强度之间确实存在显著的倒U形的EKC关系,并且这一结论在考虑空间因素后仍然稳健。EKC曲线的拐点在不考虑空间因素的情况下位于电气化水平为10.52%的位置,在考虑了空间因素后略微后移到10.81%。截至2016年,所有省份的电气化水平均处于EKC拐点的右侧,即电气化水平的提高将对碳强度下降起到显著的促进作用。最后,针对电气化与碳强度关系的一般与空间特征,本文对电气化发展提出了政策建议。     

丝绸之路经济带资源环境成本及生态负荷强度的时空演变分析

为了科学地评价丝绸之路经济带生态系统对经济与社会发展的服务支撑能力,本研究引入生态系统服务理论,构建资源环境成本及绿色GDP核算、生态负荷强度模型,计算出丝绸之路经济带辐射国家2005—2012年的资源环境成本、生态负荷强度,并在此基础上利用探索性空间数据分析方法,对2005年以来丝绸之路经济带的生态负荷强度随时间演变的趋势及其空间分布特征进行分析和探讨(数据获取难易程度,仅分析了部分带内国家)。结果表明:在研究时段内,带内国家或地区的资源环境成本由2005年的675.02×108元攀升至1 178.51×108元(2005年可比价),生态负荷强度由0.3369下降到0.2307;丝绸之路经济带生态负荷强度呈现出由欧洲经济圈向中国西北地区集聚的空间分布特征,其中中亚及中国西北地区为高-高集聚区、欧洲经济圈为低-低集聚区;这种西、东集聚现象的显著性在研究时段内逐渐减弱,且区域生态效益或经济效益持续向周边溢出。     

基于CBW方法的美丽中国建设学习路径选择研究

坚持因地制宜、分区分类探索并打造各美其美的美丽中国建设样本是美丽中国建设实践的内涵。目前各地在美丽中国先行区等试点建设活动中已进行了大量评价,在筛选典范、分区分类等方面做了充分探索。虽然评价体系日趋成熟,但仍存在榜样的学习路径不够明确,表彰充分但分类指导力度不足等问题。为了解决此类问题,本文充分融合大数据技术与生态文明建设实践,提出基于大数据的CBW(Category-Better-Way)方法体系,依据标杆管理“分类、标杆、学习路径”三要素建立了具有通用性的美丽中国建设辅助绩效评价体系和学习路径选择机制,不仅可以帮助辅助评比的机构确定生态案例分类类别、树立分类标杆、提取标杆的学习路径,还可帮助各地区定位美丽中国建设新案例的学习标杆并找到学习路径。该方法具有通用性,适用于各地实践美丽中国建设。     

Water Quality Assessment of Large‐scale Bioenergy Cropping Scenarios for the Upper Mississippi and Ohio‐Tennessee River Basins

The Upper Mississippi River Basin and Ohio‐Tennessee River Basin comprise the majority of the United States Corn Belt region, resulting in degraded Mississippi River and Gulf of Mexico water quality. To address the water quality implications of increased biofuel production, biofuel scenarios were tested with a Soil and Water Assessment Tool (SWAT) model revision featuring improved biofuel crop representation. Scenarios included corn stover removal and the inclusion of two perennial bioenergy crops, switchgrass and Miscanthus, grown on marginal lands (slopes >2% and erosion rates >2 t/ha) and nonmarginal lands. The SWAT model estimates show water quality is not very sensitive to stover removal. The perennial bioenergy crops reduce simulated sediment, nitrogen (N), and phosphorus (P) yields by up to 60%. Simulated sediment and P reductions in marginal lands were generally twice that occurring in the nonmarginal lands. The highest unit area reductions of N occurred in the less sloping tile‐drained lands. Productivity showed corn grain yield was independent from stover removal, while yields of the two perennial bioenergy crops were similar in the marginal and nonmarginal lands. The results suggest planning for biofuel production in the Corn Belt could include the removal of stover in productive corn areas, and the planting of perennial bioenergy crops in marginal land and in low‐sloped tile‐drained areas characterized by high N pollution. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.