Environmental Statistics with S-PLUS

Millard, Steven P.; Neerchal, Nagaraj K.

doi:10.1201/9781420037173

Cited by 75 publications

(74 citation statements)

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“…Pearson correlation (Millard and Neerchal, 2001) was used to characterize the relationships between response (cross-sectional area growth) and indicator variables. Multiple regression models (Millard and Neerchal, 2001) were developed using six indicator variables.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…Multiple regression models (Millard and Neerchal, 2001) were developed using six indicator variables. Although multiple linear regression models of aspen clone growth on O 3 were very highly statistically significant, polynomial cubic regression (Millard and Neerchal, 2001) was investigated in order to evaluate if assumption of non-linearity in tree growth response to O 3 exposure could be verified. To determine the most suitable regression models for assessment of O 3 and the other indicator variables on cross-sectional area growth, the Best Regression Algorithm (Millard and Neerchal, 2001) was systematically applied to each of the five aspen clones.…”

Section: Resultsmentioning

confidence: 99%

“…Using this outcome, the best multiple regression models were developed incorporating the three best indicators of aspen cross-sectional area growth. Confidence intervals for the cross-sectional area growth were computed using Monte Carlo techniques (Millard and Neerchal, 2001) to randomly generate thousands of scenarios for all relevant ranges of O 3 , GDD, and WS. Resulting confidence (95%) bands in 2-dimensional Euclidean spaces were represented by a graph in a plane for ease of visualization.…”

Section: Resultsmentioning

confidence: 99%

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New exposure-based metric approach for evaluating O3 risk to North American aspen forests

Percy

Nosal

Heilman³

et al. 2007

Environmental Pollution

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A new exposure-based metric approach to predict O 3 risk to North American aspen forests has been developed. AbstractThe United States and Canada currently use exposure-based metrics to protect vegetation from O 3 . Using 5 years (1999e2003) of comeasured O 3 , meteorology and growth response, we have developed exposure-based regression models that predict Populus tremuloides growth change within the North American ambient air quality context. The models comprised growing season fourth-highest daily maximum 8-h average O 3 concentration, growing degree days, and wind speed. They had high statistical significance, high goodness of fit, include 95% confidence intervals for tree growth change, and are simple to use. Averaged across a wide range of clonal sensitivity, historical 2001e2003 growth change over most of the 26 M ha P. tremuloides distribution was estimated to have ranged from no impact (0%) to strong negative impacts (e31%). With four aspen clones responding negatively (one responded positively) to O 3 , the growing season fourth-highest daily maximum 8-h average O 3 concentration performed much better than growing season SUM06, AOT40 or maximum 1 h average O 3 concentration metrics as a single indicator of aspen stem cross-sectional area growth.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

New exposure-based metric approach for evaluating O3 risk to North American aspen forests

Percy

Nosal

Heilman³

et al. 2007

Environmental Pollution

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“…The estimation formula as presented in Hyland et al [21] was used to construct the CDFs. The CDFs were tested for difference between systems using the Kolmogorov-Smirnov test [22]. There were no non-detects in the data sets used.…”

Section: Basic Statistical Analysismentioning

confidence: 99%

Characterization Methods for Small Estuarine Systems in the Mid-Atlantic Region of the United States

Paul¹

2010

TOHYDJ

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Various statistical methods were applied to spatially discrete data from 14 intensively sampled small estuarine systems in the mid-Atlantic U.S. The number of sites per system ranged from 6 to 37. The surface area of the systems ranged from 1.9 to 193.4 km 2 . Parameters examined were depth, bottom temperature, bottom salinity, surface chlorophyll a, bottom dissolved oxygen, lead concentration in sediments, silt-clay content of sediments, and number of infaunal benthic species. Statistical methods included means, standard deviations, coefficients of variation, empirical cumulative distribution functions, and contours determined by bivariate interpolation and interpolation by kriging. All of these methods were found to be appropriate depending upon the purpose of the characterization. Contouring was applied only to those systems with at least 23 discrete sample sites (7 systems). Cross-validation and randomization techniques were used to compare the two interpolation methods. Kriging was advantageous over bivariate interpolation when moderate to strong spatial correlation existed in the residuals (that is, after removal of the spatial trend with a nonparametric regression model). When kriging was conducted, the removal of the trend was necessary if the stationarity assumption was to be valid. The Delaware/Maryland coastal bays are shallow, well-mixed (horizontally and vertically) systems that exhibit little or no spatial correlation for the parameters examined. The South and Severn Rivers, subsystems of the Chesapeake Bay, exhibited moderate to strong spatial dependence for some parameters. Randomization techniques were used to evaluate the effect of decreasing the number of sites in kriged parameters. Based upon these randomizations, it was found that 23 discrete sites could be used for kriging in estuaries with characteristics similar to those in the mid-Atlantic and if the samples were collected with a comparable design.

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Data analysis of environmental air pollutant monitoring systems in Europe

Voigt

Welzl²,

Brüggemann

2004

Environmetrics

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Public access to information about the environment is being strengthened across Europe. The concept of public's right to information gives the basis for the access to environmental information. In this paper the quality of air pollutant monitoring systems in the 15 European member states is analyzed. For pragmatic reasons only the capitals are looked upon. Comprehensive data on environmental monitoring programs concerning air pollutants like ozone (O3), nitrogen dioxide (NO2), nitrogen oxide (NO), carbon dioxide (CO2) and carbon monoxide (CO), and sometimes suspended dust, benzene and other environmental chemicals are available on the free Internet. As different monitoring information systems exist in the European member states a comparison of these systems with their pros and cons is of great interest to the public. Environmental air pollutant monitoring systems in the capitals of the 15 EEC member countries (objects) are evaluated by applying 5 evaluation criteria for the differentiation of these systems. The scores run from 0 = insufficient, 1 = medium, to 2 = excellent.Different data‐analysis methods will be applied. As order theory is still not sufficiently presented in the scientific literature, a short overview about the so‐called Hasse diagram technique and POSAC method is outlined. In several steps the data‐matrix is analyzed coming to the conclusion that all methods (additionally PCA is used) identify one criterion as specifically important. Not unexpected, each method has its own advantage. The aim of this data‐analysis is the evaluation of the publicly available air quality monitoring systems in Europe with their pros and cons. This might help the interested public to find and understand the information given on the Internet. Furthermore our evaluation approach might give some recommendations for an improvement of the air quality monitoring systems. Copyright © 2004 John Wiley & Sons, Ltd.

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Environmental Statistics with S-PLUS

Cited by 75 publications

References 0 publications

New exposure-based metric approach for evaluating O3 risk to North American aspen forests

New exposure-based metric approach for evaluating O3 risk to North American aspen forests

Characterization Methods for Small Estuarine Systems in the Mid-Atlantic Region of the United States

Data analysis of environmental air pollutant monitoring systems in Europe

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