Can we gain precision by sampling with probabilities proportional to size in surveying recent landscape changes in the Netherlands?

Seventy-two squares of 100 ha were selected by stratified random sampling with probabilities proportional to size (pps) to survey landscape changes in the period 1996–2003. The area of the plots times the urbanization pressure was used as a size measure. The central question of this study is whether the sampling with probabilities proportional to size leads to gain in precision compared to equal probability sampling. On average 1.03 isolated buildings per 100 ha have been built, while 0.90 buildings per 100 ha have been removed, leading to a net change of 0.13 building per 100 ha. The area with unspoiled natural relief has been reduced by 2.3 ha per 100 ha, and the length of linear relicts by 137 m per 100 ha. On average 74 m of linear green elements have been planted per 100 ha, while 106 m have been removed, leading to a net change of −31 m per 100 ha. For the state variables ‘unspoiled natural relief', ‘ linear relicts', ‘removed linear green elements', and ‘new – removed linear green elements' there is a gain in precision due to the pps-sampling. For the remaining state variables there is no gain or even a loss of precision (`new buildings', ‘removed buildings', ‘new – removed buildings', ‘new linear green elements'). Therefore, if many state variables must be monitored or when interest is not only in the change but also in the current totals, we recommend to keep things simple, and to select plots with equal probability.     

Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods

Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions, kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional role was found very useful in aiding decisions in conservation planning.     

Using Ion-Exchange Resins to Study Soil Response to Experimental Watershed Acidification

Ion-exchange resins (IER) offer alternative approaches to measuring ionic movement in soils that may have advantages over traditional approaches in some settings, but more information is needed to understand how IER compare with traditional methods of measurement in forested ecosystems. At the Bear Brook Watershed in Maine (BBWM), one of two paired, forested watersheds is treated bi-monthly with S and N (28.8 and 25.2kgha⁻¹yr⁻¹ of S and N, respectively). Both IER and ceramic cup tension lysimeters were used to study soil solution responses after ∼11 years of treatment. Results from both methods showed treatments resulted in the mobilization of base cations and Al, and higher SO₄—S and inorganic N in the treated watershed. Both methods indicated similar differences in results associated with forest type (hardwoods versus softwoods), a result of differences in litter quality and atmospheric aerosol interception capacity. The correlation between lysimeter and IER data for individual analytes varied greatly. Significant correlations were evident for Na (r=0.75), Al (r=0.65), Mn (r=0.61), Fe (r=0.57), Ca (r=0.49), K (r=0.41) and NO₃—N (r=0.59). No correlation was evident between IER and soil solution data for NH₄—N and Pb. Both IER and soil solution techniques suggested similar interpretations of biogeochemical behavior in the watershed.     

A Rapid Method for Assessing the Environmental Performance of Commercial Farms in the Pampas of Argentina

The generation of reliable updated information is critical to support the harmonization of socio-economic and environmental issues in a context of sustainable development. The agro-environmental assessment and management of agricultural systems often relies on indicators that are necessary to make sound decisions. This work aims to provide an approach to (a) assess the environmental performance of commercial farms in the Pampas of Argentina, and (b) propose a methodological framework to calculate environmental indicators that can rapidly be applied to practical farming. 120 commercial farms scattered across the Pampas were analyzed in this study during 2002 and 2003. Eleven basic indicators were identified and calculation methods described. Such indicators were fossil energy (FE) use, FE use efficiency, nitrogen (N) balance, phosphorus (P) balance, N contamination risk, P contamination risk, pesticide contamination risk, soil erosion risk, habitat intervention, changes in soil carbon stock, and balance of greenhouse gases. A model named Agro-Eco-Index was developed on a Microsoft-Excel support to incorporate on-farm collected data and facilitate the calculation of indicators by users. Different procedures were applied to validate the model and present the results to the users. Regression models (based on linear and non-linear models) were used to validate the comparative performance of the study farms across the Pampas. An environmental dashboard was provided to represent in a graphical way the behavior of farms. The method provides a tool to discriminate environmentally friendly farms from those that do not pay enough attention to environmental issues. Our procedure might be useful for implementing an ecological certification system to reward a good environmental behavior in society (e.g., through tax benefits) and generate a commercial advantage (e.g., through the allocation of green labels) for committed farmers.     

Assessing Spatial, Temporal, and Analytical Variation of Groundwater Chemistry in a Large Nuclear Complex, USA

Statistical analyses were applied at the Hanford Site, USA, to assess groundwater contamination problems that included (1) determining local backgrounds to ascertain whether a facility is affecting the groundwater quality and (2) determining a ‘pre-Hanford' groundwater background to allow formulation of background-based cleanup standards. The primary purpose of this paper is to extend the random effects models for (1) assessing the spatial, temporal, and analytical variability of groundwater background measurements; (2) demonstrating that the usual variance estimate s ², which ignores the variance components, is a biased estimator; (3) providing formulas for calculating the amount of bias; and (4) recommending monitoring strategies to reduce the uncertainty in estimating the average background concentrations. A case study is provided. Results indicate that (1) without considering spatial and temporal variability, there is a high probability of false positives, resulting in unnecessary remediation and/or monitoring expenses; (2) the most effective way to reduce the uncertainty in estimating the average background, and enhance the power of the statistical tests in general, is to increase the number of background wells; and (3) background for a specific constituent should be considered as a statistical distribution, not as a single value or threshold. The methods and the related analysis of variance tables discussed in this paper can be used as diagnostic tools in documenting the extent of inherent spatial and/or temporal variation and to help select an appropriate statistical method for testing purposes.     

Organochlorine Pesticide Residues in Milk and Blood of Women from Anupgarh, Rajasthan, India

Anupgarh is the most fertile area of Rajasthan state where a variety of seasonal crops are grown. The availability of three manmade canals has enhanced the agricultural activities in this area. The farmers use huge amounts of pesticides to increase the crop productivity. Exposure of humans to these hazardous chemicals occurs directly in the fields and indirectly due to consumption of contaminated diet, or by inhalation or by dermal contact. The organochlorine pesticides are reported to be lipophilic and their presence in human milk and blood has been documented in different parts of the world. Blood and milk samples were collected from lactating women who were divided into four groups on the basis of different living standards viz residence area, dietary habits, working conditions and addiction to tobacco. The level of total organochlorine pesticides in blood ranged from 3.319mg/L—6.253mg/L while in milk samples it ranged from 3.209Mdash;4.608 mg/L. The results are in concurrence with the reports from other countries.     

Study of Meteorological Aspects and Urban Concentration of SO2 in Atmospheric Environment of La Plata, Argentina

This article presents and discusses SO₂ (ppbv) concentration measurements combined with meteorological data (mainly wind speed and direction) for a five-year campaign (1996 to 2000), in a site near an oil refinery plant close to the city of La Plata and surroundings (aprox. 740.000 inh.), considered one of the six most affected cities by air pollution in the country. Since there is no monitoring network in the area, the obtained results should be considered as medium term accumulated data that enables to determine trends by analyzing together gas concentrations and meteorological parameters. Preliminary characterization of the behaviour of the predominant winds of the region in relation with potential atmospheric gas pollutants from seasonal wind roses is possible to carry out from the data. These results are complemented with monthly averaged SO₂ measurements. In particular, for year 2000, pollutant roses were determined which enable predictions about contamination emission sources. As a general result we can state that there is a clear increase in annual SO₂ concentration and that the selected site should be considered as a key site for future survey monitoring network deployment. Annual SO₂ average concentration and prevailing seasonal winds determined in this work, together with the potential health impact of SO₂ reveals the need for a comprehensive and systematic study involving particulate matter an other basic pollutant gases.     

A new approach to Assess Atmospheric Nitrogen Deposition by Way of Standardized Exposition of mosses

A standardized method of moss exposition for assessing variations in nitrogen deposition was tested in the western part of Germany. Six pleurocarpous moss species were transplanted to two sites differing in their deposition rates but being comparable as to their climatic conditions. The mosses were exposed in standardized containers over a period of 12 months; the focus of interest was the effect of N deposition on nitrogen content and on ¹⁵N natural abundance (δ¹⁵N-values). Within the first nine months only trends could be observed. However, after one year all species tested showed significantly higher N concentrations at the highly polluted site. Besides, more negative δ¹⁵N-values possibly reflecting the higher ammonium input were detected at this site. Surprisingly, most of the plants though being kept in plastic containers without a favourable substratum did not show any conspicuous deficiency symptoms. The potential advantages of a standardized moss exposition for N monitoring purposes are discussed. It is concluded that the method presented here can yield significant results in particular if the number of testing sites is increased.     

Monitoring Biofilm Thickness Using A Non-Destructive, On-Line, Electrical Capacitance Technique

Abstact The present study was designed to evaluate indirect, non-invasive, on-line measurement of biofilm thickness using an electrical capacitance technique. Several assays were carried out and the results showed that, at a frequency of 1 kHz, electrical capacitance could be used to measure biofilm thickness indirectly (with a correlation coefficient of 0.9495). The reproducibility revealed by the assays was also highly satisfactory.However, in contrast to what was expected, there was an inverse relationship between electrical capacitance and biofilm thickness, i.e. electrical capacitance diminished with the increase in the biofilm thickness.The tests were also carried out at different frequencies (1 kHz, 10 kHz and 100 kHz)     

Comparison of Nitrate Levels in Raw Water and Finished Water from Historical Monitoring Data on Iowa Municipal Drinking Water Supplies

Nitrate contamination of water sources is a concern where large amounts of nitrogen fertilizers are regularly applied to soils. Ingested nitrate from dietary sources and drinking water can be converted to nitrite and ultimately to N-nitroso compounds, many of which are known carcinogens. Epidemiologic studies of drinking water nitrate and cancer report mixed findings; a criticism is the use of nitrate concentrations from retrospective drinking water data to assign exposure levels. Residential point-of-use nitrate data are scarce; gaps in historical data for municipal supply finished water hamper exposure classification efforts. We used generalized linear regression models to estimate and compare historical raw water and finished water nitrate levels (1960s--1990s) in single source Iowa municipal supplies to determine whether raw water monitoring data could supplement finished water data to improve exposure assessment. Comparison of raw water and finished water samples (same sampling date) showed a significant difference in nitrate levels in municipalities using rivers; municipalities using other surface water or alluvial groundwater had no difference in nitrate levels. A regional aggregation of alluvial groundwater municipalities was constructed based on results from a previous study showing regional differences in nitrate contamination of private wells; results from this analysis were mixed, dependent upon region and decade. These analyses demonstrate using historical raw water nitrate monitoring data to supplement finished water data for exposure assessment is appropriate for individual Iowa municipal supplies using alluvial groundwater, lakes or reservoirs. Using alluvial raw water data on a regional basis is dependent on region and decade.