A statistical evaluation of non-ergodic variogram estimators

Geostatistics is a set of statistical techniques that is increasingly used to characterize spatial dependence in spatially referenced ecological data. A common feature of geostatistics is predicting values at unsampled locations from nearby samples using the kriging algorithm. Modeling spatial dependence in sampled data is necessary before kriging and is usually accomplished with the variogram and its traditional estimator. Other types of estimators, known as non-ergodic estimators, have been used in ecological applications. Non-ergodic estimators were originally suggested as a method of choice when sampled data are preferentially located and exhibit a skewed frequency distribution. Preferentially located samples can occur, for example, when areas with high values are sampled more intensely than other areas. In earlier studies the visual appearance of variograms from traditional and non-ergodic estimators were compared. Here we evaluate the estimators' relative performance in prediction. We also show algebraically that a non-ergodic version of the variogram is equivalent to the traditional variogram estimator. Simulations, designed to investigate the effects of data skewness and preferential sampling on variogram estimation and kriging, showed the traditional variogram estimator outperforms the non-ergodic estimators under these conditions. We also analyzed data on carabid beetle abundance, which exhibited large-scale spatial variability (trend) and a skewed frequency distribution. Detrending data followed by robust estimation of the residual variogram is demonstrated to be a successful alternative to the non-ergodic approach.     

Model-based combination of spatial information for stream networks

Evolutionary improvements in Geographic Information Systems (GIS) now routinely allow the management and mapping of spatial-temporal information. In response, the development of statistical models to combine information of different types and spatial support is of vital importance to environmental science. In this paper we develop a hierarchical spatial statistical model for environmental indicators of stream and river systems in the United States Mid-Atlantic Region by combining information from separate monitoring surveys, available contextual information on hydrologic units and remote sensing information. These models are used to estimate the indicators throughout the riverine system based on information from multiple sources and aggregate scales. The analysis is based on information underlying the Landscape Atlas of the mid-Atlantic region produced by the US Environmental Monitoring and Assessment Program (EMAP). We also combine information from two overlapping separate monitoring surveys, the EMAP Stream and River Survey and the Maryland Biological Streams Survey. We present a general framework for comparative distributional analysis based on the concept of a relative spatial distribution. As an application, the spatial model is used to predict spatial distributions and relative spatial distributions for a watershed.     

Active Adaptive Management for Conservation

Abstract:  Active adaptive management balances the requirements of management with the need to learn about the system being managed, which leads to better decisions. It is difficult to judge the benefit of management actions that accelerate information gain, relative to the benefit of making the best management decision given what is known at the time. We present a first step in developing methods to optimize management decisions that incorporate both uncertainty and learning via adaptive management. We assumed a manager can allocate effort to discrete units (e.g., areas for revegetation or animals for reintroduction), the outcome can be measured as success or failure (e.g., the revegetation in an area is successful or the animal survives and breeds), and the manager has two possible management options from which to choose. We further assumed that there is an annual budget that may be allocated to one or both of the two options and that the manager must decide on the allocation. We used Bayesian updating of the probability of success of the two options and stochastic dynamic programming to determine the optimal strategy over a specified number of years. The costs, level of certainty about the success of the two options, and the timeframe of management all influenced the optimal allocation of the annual budget. In addition, the choice of management objective had a large influence on the optimal decision. In a case study of Merri Creek, Melbourne, Australia, we applied the approach to determining revegetation strategies. Our approach can be used to determine how best to manage ecological systems in the face of uncertainty.     

ECONOMIC AND WATER QUALITY EFFECTS OF VARIABLE AND UNIFORM APPLICATION OF NITROGEN1

ABSTRACT: Nitrogen (N) fertilizer rates for achieving optimum crop yields often vary within a field due to spatial variability in soil moisture and nitrogen content and other crop growth factors. When there is substantial within-field variability in these factors, uniform application of N (UAN) may not be economically efficient in terms of maximizing net return because N is likely to be over-applied in some areas and under-applied in other areas of the field. In addition, over-application can adversely affect water quality. A sample of fields in a Midwestern agricultural watershed is used to test for statistically significant differences in N application rates, crop yields, surface and ground water quality and net returns between UAN and variable application of N (VAN) for four cropping systems. Profitability and water quality benefits of VAN are sensitive to the distribution of soil types within a field. Water quality effects and profitability of UAN and VAN vary with cropping systems. VAN is not uniformly superior to UAN in terms of increasing net returns and improving water quality for the farming systems and watershed evaluated in this study.     

COMPARING SAMPLING SCHEMES FOR MONITORING POLLUTANT EXPORT FROM A DAIRY PASTURE1

ABSTRACT: Dairy cow pastures and feeding areas around barns can be a significant source of nonpoint source pollutants to nearby streams. To help document the significance of these sources, nutrient export in streamfiow from a 56.7-ha, mostly agricultural, watershed located in southwestern North Carolina was monitored from August 1994 to January 1996. Total nitrogen and phosphorus export rates from the upper, predominantly pasture, part of the watershed were 18.0 and 1.4 kg/ha/yr, respectively, as measured by weekly grab sampling and 18.7 and 4.9 kg/halyr, respectively, as measured from storm event monitoring. Nitrogen and phosphorus export rates for the area between the monitoring sites, which included overgrazed cow holding and feeding areas and farm buildings, were 376 and 86 kgfhalyr, respectively, for grab sampling and 351 and 160 kg/ha/yr, respectively, for storm event monitoring. To estimate the amount of reduction from nonpoint source controls necessary to effect a significant reduction in pollutant loading, statistical analyses of the load data were conducted. The analyses for the five pollutants monitored showed that total suspended solids would require the greatest reduction (34.6 percent for weekly grab and 33.6 percent for storm) in loading after the implementation of controls for statistical significance. Nitrate plus nitrite was found to require the least reduction (12.6 percent for weekly grab). Pollutant export rates computed from weekly grab samples and storm event samples used separately were compared to corresponding export rates computed from combining grab and storm event samples to assess the differences in monitoring schemes.     

NONLINEAR MODELING AND PREDICTION OF A RIVER FLOW SYSTEM1

ABSTRACT: Model estimation and prediction of a river flow system are investigated using nonlinear system identification techniques. We demonstrate how the dynamics of the system, rainfall, and river flow can be modeled using NARMAX (Nonlinear Autoregressive Moving Average with eXogenuous input) models. The parameters of the model are estimated using an orthogonal least squares algorithm with intelligent structure detection. The identification of the nonlinear model is described to represent the relationship between local rainfall and river flow at Enoree station (inputs) and river flow at Whitmire (output) for a river flow system in South Carolina.     

中国环境科学专题文献研究

本文运用文献计量学方法,对我国环境科学10种主要期刊(1989～1991)年间总计刊载的2584篇文献所著录的全部引文及文献著者进行一次统计调查与分析研究,从中寻找出我国环境科学研究文献引文的一般规律和我国环境科学科研作者队伍的构成及分布现状。     

2017年5-6月国内环境事件

简要统计了2017年5-6月国内发生的各种环境事件142起,包括沙尘天气12起,污染事件16起,地震44起,山体滑坡和泥石流16起,以及其他自然灾害54起.     

江河水质监测断面优化布设方法

江河水质监测断面应掌控水质的时空变化规律.数理统计分析方法可以发现一条河流上现有水质监测断面是否存在功能相似的邻近断面,水环境数值模拟方法可以近似地展现一条河流任意位置的水质情况,二者结合即可解决缺乏实测数据的河流水质监测断面优化布设问题.以我国某条大河为研究实例,运用物元分析法、模糊聚类分析法以及一维水环境数值模型结合物元分析法研究其水质断面优化问题.研究发现该河现有15个监测断面需要去除2个,同时需要增设2个新的水质监测断面.通过实地调查,该优化方法很好地解决了河流水质监测断面的合理布设问题.     

2016年7-8月国内环境事件

简要统计了2016年7-8月国内发生的各种环境事件147起,包括沙尘天气2起,污染事件24起,地震41起,山体滑坡和泥石流32起,旱灾3起以及其他自然灾害45起.