Assessment of non-point source pollution using a spatial multicriteria analysis approach

Eutrophication caused by the enrichment of nutrients from diffusing sources is degrading surface water quality throughout the world. Assessing the potential contributions of different land areas in diffuse nutrient export has become an important task in non-point source (NPS) pollution control. Existing methods were often limited by the availability of local data and the complexity of model formulation. This study developed a spatial multicriteria method to evaluate the nitrogen loss potential at the basin level. Four criteria were formulated to characterize the source capacity of nitrogen export, the flow path to water body, the efficiency of runoff generation and the climatic driving force. The proposed method is a low-effort approach since the required data is either already available in a global context or easily produced with limited inputs. Being implemented in GIS environment, this method generates maps that can be easily interpreted to provide decision support. The method was applied to the Huai River Basin, China. The results were validated based on the correlation between the nitrogen loss potential of sub-basin and the water quality class of river. The maps of nitrogen loss potential were helpful for examining the regional pattern of diffuse nitrogen loss, and could facilitate the decisions of NPS pollution management at the provincial or basin level.     

Identifying habitat patches and potential ecological corridors for remnant Asiatic black bear (Ursus thibetanus japonicus) populations in Japan

The Japanese National Biodiversity Strategy 2010 calls for the creation of ecological networks as a biodiversity conservation policy. However, there is an obvious lack of information on the spatial distribution of many species and a lack of scientific methods for examining habitat requirements to establish the need for constructing these networks for target species. This study presents a quantitative method for assessing the need for ecological networks through modeling the potential geographic distributions of species based on a case study of local populations of Asiatic black bear (Ursus thibetanus japonicus) in Fuji and Tanzawa, Japan. A total of 1541 point records of occurrences of Asiatic black bears and 11 potential predictors were analyzed in a GIS environment. After a predictive distributional map was obtained using the Maximum Entropy (MaxEnt) algorithm, a gap analysis was carried out and population size was estimated. Approximately 24% of the bear's predicted habitat area fell within a wildlife protection area, 2% within a nature reserve, and 37% within natural parks. Conservation forest comprised 54% of the total area of predicted habitat; of this, national forest comprised 2%, and private and communal forest comprised 37%. The total estimated Asiatic black bear population in this region was 242, with 179 individuals in the Fuji local population, 26 in the Tanzawa local population, and 37 in the corridor patch between the two local populations. Our study also found a potential corridor connecting the Fuji and Tanzawa local populations, as well as potential habitat corridors in the Fuji region containing subpopulations on Mt. Fuji (119 individuals) and Mt. Kenashi (53 individuals). An additional subpopulation on Mt. Ashitaka (7 individuals) is isolated and not fully protected by a zoning plan. Mt. Furo's subpopulation is considered to be almost extinct, although black bears were observed here until 2002 based on the report by Mochizuki et al. (2005). The total black bear population of the Fuji-Tanzawa region is considered to be “endangered”; thus, an adequate population size might be difficult to maintain even if this region were to be internally connected by means of an ecological network.     

The crucial role of the accessible area in ecological niche modeling and species distribution modeling

Using known occurrences of species and correlational modeling approaches has become a common paradigm in broad-scale ecology and biogeography, yet important aspects of the methodology remain little-explored in terms of conceptual basis. Here, we explore the conceptual and empirical reasons behind choice of extent of study area in such analyses, and offer practical, but conceptually justified, reasoning for such decisions. We assert that the area that has been accessible to the species of interest over relevant time periods represents the ideal area for model development, testing, and comparison.     

Predictors of occupancy trend across spatial scale

Many explorations of extinction probability have had a global focus, yet it is unclear whether variables that explain the probability of extinction at large spatial extents are the same as those at small spatial extents. Thus, we used nearly annual presence-absence records for the most recent 40 years of a 110-year data set from Palenque, Mexico, an area with ongoing deforestation, to explore which of >200 species of birds have probabilities of extirpation that are likely to increase. We assessed associations between long-term trends in species presence (i.e., detection in a given year) and body size, geographic range size, diet, dependence on forest cover, taxonomy, and ecological specialization. Our response variable was the estimated slope of a weighted logistic regression for each species. We assessed the relative strength of each predictor by means of a model ranking scheme. Several variables associated with high extinction probability at global extents, such as large body size or small geographic range size, were not associated with occurrence of birds over time at our site. Body size was associated with species loss at Palenque, but occurrence trends of both very large and very small species, particularly the latter, have declined, or the species have been extirpated. We found no association between declining occurrence trend and geographic range size, yet decline correlated with whether a species depends on forest (mean occupancy trend =-0.0380, 0.0263, and 0.0186 for, respectively, species with high, intermediate, or low dependence on forest) and with complex combinations of diet and foraging strata (e.g., occurrence of canopy insectivores and terrestrial omnivores has increased, whereas occurrence of mid-level frugivores and terrestrial granivores has decreased). Our findings emphasize that analyses of local areas are necessary to explicate extirpation risk at various spatial extents.     

River environmental decision support system development for Suzhou Creek in Shanghai

The Suzhou Creek Rehabilitation Project (SCRP) is one of the largest water-related environmental rehabilitation schemes ever undertaken in the vicinity of Shanghai, China. This paper details the development and application of a River Environmental Decision Support System (REDSS) for scientific planning and decision-making on the Suzhou Creek project, and illustrates the flexibility of the REDSS framework. We developed the following components: (1) a GIS-based analysis employing Component technology; (2) a "data mart" for multi-dimensional, multi-level, integrated, dynamic, and flexible data querying; and (3) a set of hydrodynamic and water quality models which can simulate complex tidal river networks. In addition, we detail how a water quality assessment model is embedded into the REDSS by employing an Identification Index Method. With the REDSS, all GIS and non-GIS components are integrated seamlessly and data from different sources can be queried simultaneously. This allows for various scenarios to be simulated and analyzed in advance to predict and assess the effects of proposed engineering and management measures. Generated information can thus support effective decisions. All operations of the REDSS can be implemented conveniently through user-friendly interfaces. The function of the REDSS framework is demonstrated through an application to Suzhou Creek. Because the REDSS characteristics are quite general, it may be applied in different geographic regions.     

基于GIS的交通事故信息空间数据库研究

笔者分析了建立基于GIS的交通事故信息空间数据库的紧迫性;探讨了完备的交通事故信息数据库的内容构成,认为应包括空间数据库、影响因素数据库以及元数据和数据字典库三大部分;研讨了交通事故空间数据库的重要应用价值,进而采用GIS的分层组织思想对交通事故信息空间数据库中的数据进行组织;详细设计了各个数据表以及数据表间的关系,建立了包含交通事故对象、人、车、路以及环境等要素的交通事故空间数据库,为交通事故研究提供完备的数据支持。     

Quantitative Pollution Spill Risk Assessment: Using A Gis-Based System

Federal and State agencies have recently advocated risk-based analysis as a mechanism for advancing regulatory reform and safety determination in marine systems. the present investigation promotes this objective through the development of risk-based environmental planning strategies for oil spill contingency plans. This alternative approach to contingency planning departs from conventional methodology by employing quantitative risk assessment methods to identify hazardous oil spill zones and sensitive environmental areas, R_o and R_e respectively. the product of this conversion is referenced on a single “Risk” layer within a Geographic Information System (GIS) framework allowing coastal managers to evaluate natural resource data with associated elements of oil spill risk. As a new tool for coastal pollution management, risk-based environmental planning strategies have shown potential for evolving more efficient oil spill contingency plans.     

North East Scotland River Catchment Nitrate Loading in Relation to Agricultural Intensity

Modern agricultural practices have been strongly linked with increased NO₃-N loadings in surface waters. Nitrate leaching increases as land use progresses from forest and moorland through grassland, to arable agriculture. There are, within the UK, few studies on a regional scale capable of displaying a relationship between land cover (agricultural intensity) and water quality. This relationship can be investigated using computer manipulation of spatial geographic information together with conventional river and agricultural census data.

Simple regression analysis against primary land cover suggests that agriculture is reponsible for annual losses of nitrate in North East Scotland river catchments. Further multi-linear regression analysis, using the GIS data and agricultural census returns indicate that most of the outstanding variation can be accounted for if the agricultural variable is related to agricultural practice, such as spring, winter and grass cropping.     

Integrated resource management systems: Coupling expert systems with data-base management and geographic information systems

Decision making in natural resource management is becoming increasingly information-intensive because of the rising public concerns about resource conservation and environmental quality. The volume of information that must be analyzed and the complexity of the decision-making process demands that computerized systems be developed to provide decision support services. An integrated systems approach that couples data-base management, geographic information systems, and expert systems is needed. We refer to such an approach as integrated resource management automation (IRMA) and describe a prototype system that is currently being tested in the Nicolet National Forest. This type of information system is likely to play an increasingly important role in the management of natural resources in the future.