Using Spatial Pattern to Quantify Relationship Between Samples, Surroundings, and Populations

The need for accurate carbon budgeting, climate change modelling, and sustainable resource management has lead to an increase in the number of large area forest monitoring programs. Large area forest monitoring programs often utilize field and remotely sensed data sources. Sampling, via field or photo plots, enables the collection of data with the desired level of categorical detail in a timely and efficient manner. When sampling, the aim is to collect representative detailed data enabling the statistical reporting upon the characteristics of larger areas. As a consequence, approaches for investigating how well sample data represent larger areas (i.e., the sample neighbourhood and the population) are desired. Presented in this communication is a quantitative approach for assessing the nature of sampled areas in relation to surrounding areas and the overall population of interest. Classified Landsat data is converted to forest/non-forest categories to provide a consistent and uniform data set over a 130,000 km² study region in central British Columbia, Canada. From this larger study area 322 2 × 2 km photo plots on a 20 × 20 km systematic grid are populated with composition and configuration information for comparison to non-sampled areas. Results indicate that typically, within the study area, the spatial pattern of forest within a photo plot is representative of the forest patterns found within primary and secondary neighbourhoods and over the entire population of the study. These methods have implications for understanding the nature of data used in monitoring programs worldwide. The ability to audit photo and field plot information promotes an increased understanding of the results developed from sampling and provides tools identifying locations of possible bias.     

A Quantitative Method for Delineating Regions: An Example for the Western Corn Belt Plains Ecoregion of the USA

/ A method was developed to systematically delineate boundaries forecological classification of regions. The process entailed the use ofsmall-scale digital data to quantify spatial concordance among environmentalattribute data sets. The data sets were grouped into spatially related themesusing cluster analysis and multidimensional scaling. Selected data sets werethen used either individually or collectively to divide the study area intosubregions that exhibited different environmental attributes. The method wasapplied to a previously defined ecological unit, the western Corn Belt of thecentral United States. The results showed that the portion of the study areawith intensive corn and soybean production was identifiable using each of thethree input data sets selected for partitioning (soil associations; AVHRRremote-sensing imagery; and a combined data set of landform, forest, andsoils data). The classification of other portions of the study area washighly dependent on the type and scale of the input data. The systematicmethodology used here offers advantages over other methods for identifyingecological regions in that the results from the systematic approach can bereproduced, the boundaries between ecological units can be revised based onnew or more accurate data, important ecological processes are explicitlychosen to delineate boundaries, and transition zones between regions can bequantified.KEY WORDS: Ecoregions; Spatial analysis; Corn Belt; Iowa; GIS;Regionalization     

Variations in the chemical properties of landfill leachate

Landfill leachates were collected and their chemical properties analyzed once every two months over a ten-month period from the Gin Drinkers' Bay (GDB) and Junk Bay (JB) landfills. The contents of solids, and inorganic and organic components fluctuated considerably with time. In general, the chemical properties of the two leachates correlated negatively (P<0.05) with the amounts of rainfall prior to the sampling periods. However, magnesium and pH of the leachates remained relatively constant with respect to sampling time. The JB leachate contained higher average contents of solids and inorganic and organic matter than those of GDB with the exception of trace metals. Trace metals were present in the two leachates in trace quantities (<1.0 mg/liter). The concentrations of average ammoniacal nitrogen were 1040 and 549 mg/liter, while chemical oxygen demand (COD) values were 767 and 695 mg/liter for JB and GDB leachates, respectively. These results suggest that the leachates need further treatment before they can be discharged to the coastal waters.     

Classification and spatial mapping of riparian habitat with applications toward management of streams impacted by nonpoint source pollution

Management of riparian habitats has been recognized for its importance in reducing instream effects of agricultural nonpoint source pollution. By serving as a buffer, well structured riparian habitats can reduce nonpoint source impacts by filtering surface runoff from field to stream. A system has been developed where key characteristics of riparian habitat, vegetation type, height, width, riparian and shoreline bank slope, and land use are classified as discrete categorical units. This classification system recognizes seven riparian vegetation types, which are determined by dominant plant type. Riparian and shoreline bank slope, in addition to riparian width and height, each consist of five categories. Classification by discrete units allows for ready digitizing of information for production of spatial maps using a geographic information system (GIS). The classification system was tested for field efficiency on Tom Beall Creek watershed, an agriculturally impacted third-order stream in the Clearwater River drainage, Nez Perce County, Idaho, USA. The classification system was simple to use during field applications and provided a good inventory of riparian habitat. After successful field tests, spatial maps were produced for each component using the Professional Map Analysis Package (pMAP), a GIS program. With pMAP, a map describing general riparian habitat condition was produced by combining the maps of components of riparian habitat, and the condition map was integrated with a map of soil erosion potential in order to determine areas along the stream that are susceptible to nonpoint source pollution inputs. Integration of spatial maps of riparian classification and watershed characteristics has great potential as a tool for aiding in making management decisions for mitigating off-site impacts of agricultural nonpoint source pollution.     

中国区域能源效率对霾污染的空间效应——基于空间杜宾模型的实证分析

以中国29个省市自治区为研究对象，并以2001~2015年PM_2.5年度均值作为衡量霾污染的指标，构建了全要素能源效率对中国霾污染影响的空间杜宾模型.研究表明：中国绝大部分省市的霾污染演变趋势具有倒"U"的特点，这说明中国的霾污染在2001~2015年间经历了先上升后下降的总体变化趋势；无论是采用地理相邻权重还是经济权重，中国省际间的霾污染均存在显著空间集聚效应，这揭示霾污染的治理与控制需要地区间建立恰当的合作机制，避免出现"损人利己"现象；在对一系列经济社会因素控制的基础上，全要素能源效率对霾污染存在显著的负向影响并且具有显著的空间溢出效应，这表明全要素能源效率的提高不仅会显著降低本地区的霾污染水平，还将对周边地区的霾污染产生显著的负向影响；分解方程结果显示，技术进步和技术效率对霾污染的负向效应显著，并且技术进步的直接效应大于技术效率，但两者的间接效应均显著大于直接效应，这揭示了技术扩散对霾污染具有重要的潜在促降效应.因此，在治理霾污染的过程中，要通过不断优化能源结构和开发新能源技术以发挥全要素能源效率的减霾效果，以及通过地区间的交流与合作发挥技术扩散效应在霾污染治理中的作用.     

Community richness and stability in agricultural landscapes: The importance of surrounding habitats

In this paper, the role played by habitat diversity in the landscape on species richness and on the stability of farmland bird communities was investigated. Species richness was estimated on 374 samples monitored in farmland by the French breeding bird survey during the 2001–2005 period. A capture–recapture approach was used to estimate species richness accounting for the variation in detection probability among species of the 100 most common species detected in farmland. Landscape structure and composition were measured both in farmland and in adjacent habitats. The independent effect of each variable on community richness and stability was further assessed using hierarchical variance partitioning and taking spatial autocorrelation into account. A strong matrix effect was detected: non-cropped land deeply influenced richness and stability of bird assemblages.     

Soil seed bank and seedling populations of Hordeum murinum and Cardaria draba in saffron fields

Geostatistical techniques were used to characterize the spatial relationship between Hordeum murinum and Cardaria draba seedling and soil seed bank over the entire growing season of 2004–2005 in three saffron (Crocus sativus) fields, located in Southern Khorasan (33°N latitude, 57°E longitude), Iran. The maps of H. murinum seed bank density corresponded moderately to those seedling density in a and strongly to those in b and c fields. The emergence percentage of C. draba was higher than for H. murinum in all fields. Semivariograms showed spatial autocorrelation in seed bank and seedling populations of H. murinum and C. draba in all fields. Grey-scale field maps of C. draba seed banks corresponded visually to maps of seedling populations and could have been used to target control efforts, but visual correspondence between H. murinum seed bank and seedling maps was poor.     

南方红豆杉天然群落种群空间分布规律的研究

采用罗盘仪定位测定的方法，对井冈山较大的南方红豆杉天然群落的空间分布规律进行研究，结果表明：群落的南方红豆杉种群累积曲线呈Ｓ型，具有Ｓ型曲线的特性，群落内部南方红豆杉的个体分布格局表现出空间和时间上的规律。     

Spatial heterogeneity of vegetation under different grazing intensities in the Northwest Heilongjiang Steppe of China

In northern China, recent degradation of semi-arid grasslands caused by overgrazing is serious. At Green Grassland Village, west of Daqing City in Heilongjiang Province, three grasslands with different degrees of degradation were surveyed. In the survey, a new method of vegetation analysis based on the beta-binomial distribution, was adopted to describe the frequency of occurrence and spatial heterogeneity for each plant species.Chenopodium centrorubrum, Cleistogenes squarrosa and a Carex species were commonly found in the three grasslands. Non-degraded grassland with light grazing was dominated by Arundinella hirta, Filifolium sibiricium, Lespedeza hedysaroides, Potentilla verticillaris, Stipa baicalensis and Thymus serpyllum. These species belong to the erect-type or do not develop large clones under light grazing. These species can be used as indicators of a well-managed grassland in this area. On the other hand, the degraded grassland with heavy grazing was dominated by Artemisia spp. and Euphorbia humifusa var. pilosa. Artemisia spp., E. humifusa var. pilosa, Eragrostis pilosa and Setaria viridis belong to the creeping-type or develop rather large stocks or stolons under heavy utilization. These species increased the spatial heterogeneity in the degraded grassland with heavy grazing.Under degraded conditions, species diversity decreased and spatial heterogeneity of the communities tended to increase.     

应用GIS模拟城市大气污染物浓度分布

从点源大气污染扩散模型出发,借助GIS的栅格与数据库运算功能,结合自已设计的推算流程,对兰州市大气污染物SO2的空间分布情况进行了模拟。经检验,该方法能够较准确的反映出兰州大气污染物的空间分布特征,较应用实测值进行插值的方法简便,具有较好的应用前景。