A More Cost-Effective Emap Benthic Macrofaunal Sampling Protocol

Benthic macrofaunal sampling protocols in the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) are to collect 30 to 50 random benthic macrofauna [defined as animals retained on a 0.5 mm (East and Gulf Coasts, USA) or a 1.0 mm mesh sieve (West Coast, USA)] samples per reporting unit using a 0.044 m² (East and Gulf Coasts) or 0.1 m² (West Coast) grab. Benthic macrofaunal community conditions in the reporting unit are characterized by cumulative distribution functions (CDFs) on end points of interest, such as number of species (S), abundance (A), and Shannon--Wiener diversity (H′). An EMAP and a companion field study were conducted concurrently in Tillamook Bay (Oregon, USA) to compare the cost effectiveness of benthic macrofauna samples collected using the EMAP West Coast (0.1 m² × ≥7 cm deep, 1.0 mm mesh), a 0.01 m² × 5 cm deep, 1.0 mm mesh, and a 0.01 m² × 5 cm deep, 0.5 mm mesh sampling protocol. Cost was estimated in relative laboratory sample-processing time. Sampling protocols were judged equally effective for EMAP purposes if, after linear transformation to adjust for scale changes in end point distributions, their S, A, and H′ CDFs were not significantly different. The 0.01 m² × 5 cm deep, 1.0 mm mesh sampling protocol was the most cost effective.     

Factors influencing farmers' concerns regarding bovine tuberculosis in wildlife and livestock around Riding Mountain National Park

Despite intensive efforts over the last century to eradicate bovine tuberculosis (TB) in North America, several hotspots of infected wildlife and livestock remain, raising concerns that the disease will never be eradicated. The stress and frustration for a farmer caused by having a herd test positive for TB or living in an infected region can be substantial. The goal of this study was to investigate the concerns of farmers around Riding Mountain National Park (RMNP) regarding the presence of TB in wildlife and livestock and conduct an exploratory analysis of causal factors. Data were collected from 786 farmers within 50 km of RMNP using a mail-back questionnaire. Overall, farmers indicated a high level of concern toward diseases in both wildlife and cattle relative to other concerns. The spatial variables that had the greatest influence on TB concern were both the distance of farms to the RMNP boundary and distance of farms to previous cases of TB. The most important aspatial factor associated with high TB concern was the frequency with which farmers observed elk on their land. These results underscore the important differences between 'objective' measures of risk, such as epidemiological estimates of disease prevalence, and subjective measures of disease concern, such as risk perception and acceptability of management actions. Written responses suggest that concerns regarding disease may affect how farmers view wildlife on their land and their relationship with neighbouring protected areas. Management activities that reduce the frequency of elk interactions with farms, but also recognize the complex relationship that farmers have with wildlife and protected areas, will be most effective in mitigating farmer concern regarding this important problem.     

Local Responses to Inundation and De-Farming in the Reservoir Region of the Three Gorges Project (China)

Large-scale infrastructural developments in rural areas often impose significant direct and indirect impacts on environment and people. The Three Gorges Project to dam the Yangtze River in China will create a huge reservoir, inundate farmlands and villages, and incur large-scale resettlement. The concurrent de-farming program to reforest marginal farmlands on steep slopes imposes additional stresses on local people. This study evaluates the ecological and economic adjustments in rural areas affected by both projects, and explores villagers’ knowledge, attitudes, perceptions, and expectations vis-à-vis the drastic changes. Eleven villages in Yunyang County in Sichuan Province, stratified into three zones based on topography and agriculture, were assessed by field studies, questionnaire surveys, maps, satellite imagery, and census and government reports. Multiple regressions identified predictors for 17 dependent variables. Spatial variations in the difficult terrain imposed zone-differentiated agricultural constraints, ecological impacts, and human responses. The dominant farming population—mainly young adults working as migrant laborers in cities—has adopted some nonagricultural work to supplement incomes. Expected per-capita standardized farmland (SF) exceeded threshold SF, which surpasses existing SF. Motivations to reclaim more farmlands, de-farm marginal lands, and become migrant laborers were explained by different multiple-regression predictors. Reduction in farmland stock by inundation and de-farming, aggravated by unwillingness towards nonlocal resettlement, would impose ecological pressures and stimulate demands for nonfarming incomes. Common anticipation of better future income and occupation has been subdued by unfavorable feedbacks from early relocatees. Future environmental and landscape changes are hinged upon changing human responses. Government policies could be informed by research findings to match economic, ecological, and social realities.     

A Statistical Assessment of Changes in Precipitation Chemistry at CAPMoN Sites, Canada

The objective of this study is to decide if chemical concentrations measured during 1988-1997in precipitation by the Canadian Air and Precipitation Monitoring Network (CAPMoN) indicate changes in the annual patterns. The inference is based on SO₄, NO₃, Cl,NH₄, Na, Ca and K concentrations monitored daily with the rain water acidity pH. By pattern is understood the probability distribution of the annual sample at a particular location. Most of the annual data can be well described by means of a linear regression model with second order polynomial trend and autocorrelated noise. Statistical analysis based on the model shows luck of systematic significant year to year increases or declines of the concentrations.     

基于改进SIFT算法的交通事故图像匹配

为解决无人机航拍交通事故现场图像特征点数量较少、匹配成功率较低、耗时过长的问题,提出1种改进的SIFT算法,使用Gabor滤波对图像进行特征提取,基于改进的高斯金字塔和多方向多尺度Gabor频谱特点提取出具有尺度、旋转不变性的特征点,结合LLE算法对特征描述符进行降维处理,通过DBSCAN算法对特征点进行密度聚类,计算...     

郑州市PM2.5浓度时空分布特征及预测模型研究

利用统计学原理和GIS技术,对郑州市2013年8月17—12月31日期间PM2.5浓度时空分布特征进行分析,同时结合气象资料与前一日污染数据,建立人工神经网络反向传播算法模型(BP-ANN)和多元线性回归模型用于该市细颗粒物污染的短期预测。结果表明,郑州市PM2.5浓度日变化呈单峰模式,随逆温现象的发生和交通的密集于上午11:00达到峰值,午后逐步下降。在工作日、周末与国庆节的对比中,国庆节期间颗粒物污染浓度高出平日32.8%,表明人为活动的加剧影响PM2.5的排放;周末与工作日期间无显著差异。在空间分布上,金水区、管城回族区污染最为严重,工业燃煤、地铁施工等源排放是造成污染的主要原因;位于远郊的岗里水库,受秸秆焚烧和市区污染输送等影响,PM2.5浓度亦维持较高水平。最后,研究将所构建的BP-ANN预测模型和多元线性回归模型对比,结果发现两模型在建模阶段预测值与真实值的拟合一致性指标分别为0.944、0.918,均方根误差分别为59.788、70.611;验证阶段拟合一致性指标分别为0.854、0.794,平均绝对误差分别为25.298、32.775,表明BP-ANN模型在预测郑州市PM2.5污染过程中更具优势。     

基于多元回归理论的太湖湖泛预警模型研究

在太湖宜兴段藻源性湖泛高发区设立4个监测点,以湖泛发生的物质基础"藻类生物量"为研究对象,运用数据分析软件SPSS对监测点的藻类生物量、水质、气温等数据进行相关分析,建立了以藻密度为因变量的多元逐步回归模型。结合往年太湖藻源性湖泛发生时的气象条件等历史资料以及相关藻密度阈值的报道,构建了太湖宜兴段藻源性湖泛高发区监测预警模型系统,该模型能够基于监测点的实时水质数据和气象预报数据,对监控区域湖水在未来某时间段内发生湖泛风险的可能性进行分级预警。     

响应面法优化铝灰中氮化铝脱除工艺

为了优化二次铝灰中AlN氧化焙烧脱除工艺,基于响应面法建立了焙烧温度、焙烧时间、铝灰粒径等工艺参数与AlN脱除率之间的数学模型,并进行了方差分析,对铝灰中AlN的脱除工艺参数进行了优化设计.结果表明,所建立的回归模型能够准确预测AlN脱除率,预测值与实验值误差为0.93％.经优化设计得到铝灰中AlN的最佳脱除工艺参数为...     

三峡水库上游河流入库面源污染负荷研究

借鉴水文分割法的原理,在基流分割的基础上,建立了面源污染负荷估算公式. 基于相关性分析、回归分析,提出了污染类型判定和数据补插原则. 以2004和2005年的水文水质数据为基础,将该方法应用于三峡库区上游河流入库面源污染负荷研究, 并采用相关系数法作为对比,对该方法在应用中可能导致的结构性偏差予以探讨. 结果表明,2004年嘉陵江、长江干流、乌江三江入库COD_Mn,总氮和总磷的污染负荷(以包含溶解态和颗粒态成分的总物质通量表示)分别为168.96×104,70.30×104和10.95×104 t;2005年分别为228.24×104,66.64×104和14.24×104 t;在总量组成中,面源是三江入库污染物的主要来源,占总入库负荷的60%～80%;在空间分布上,长江干流对入库面源污染负荷的贡献占绝对优势,嘉陵江、乌江的面源污染总贡献率仅占13.4%～39.4%;在营养物负荷组成方面,氮对水体的影响以溶解态氮作用为主,磷对水体的影响以颗粒态磷作用为主. 水文分割法的改进值得进一步关注,但在尚未出现十分科学、合理的改进算法时,该方法仍不失为面源负荷研究的有效方法.      

基于Landsat TM的澳门城市热场影响因素分析

利用2004年10月19日Landsat TM数据提取澳门城区城市用地类型信息,反演城市地表温度,在此基础上通过主成分回归方法分析澳门城市热场的影响因素.结果表明,澳门城市热场受到硬化地表指数的影响较大,其次为植被比例.地表温度与硬化地表指数、道路密度呈显著正相关(P＜0.05),与归一化植被指数、植被比例及水体比例呈显著负相关(P＜0.05).