A. H. El-Shaarawi

Measuring the potency of pulp mill effluents for induction of hepatic mixed-function oxygenase activity in fish

A bioassay protocol was optimized for measuring the potency of effluents or waterborne chemicals for inducing mixed-function oxygenase (MFO) activity of rainbow trout (Oncorhynchus mykiss). Measurements of ethoxyresorufin O-deethylase (EROD) can be made with an established endpoint assay using large volumes of reagents and tissue. However, a new kinetic microplate assay offers significant savings in time, reagents, and sample volumes. Data are distributed lognormally and must be log transformed before statistical analyses. EROD activity increases with exposure time to pulp mill effluent, and a 4-d exposure provides a near-maximal response. Optimum fish size conforms to standard practices in fish toxicology; loading rates should not exceed 1 g of fish per liter of test solution per day. Feed should be withheld from test fish 48 h before testing to reduce the variance of measured activity, and anaesthetizing fish with MS-222 does not affect their response to MFO inducers. Pulp mill effluents do not lose their potency during 2-3 wk of exposure at temperatures ranging from -20 to 13 degrees C, whether stored in plastic or glass. Steel containers were associated with slight losses in potency. Bioassays of MFO induction in fish exposed to liquid effluents are practical and conform to standard practice for testing the lethality of waterbone chemicals. The results are sufficiently precise that differences among means based on live fish per treatment can be discriminated statistically when activity changes by threefold or more.

Egg Thiamine Status of Lake Ontario Salmonines 1995–2004 with Emphasis on Lake Trout

ABSTRACT Alewives (Alosa pseudoharengus), the major prey fish for Lake Ontario, contain thiaminase. They are associated with development of a thiamine deficiency in salmonines which greatly increases the potential for developing an early mortality syndrome (EMS). To assess the possible effects of thiamine deficiency on salmonine reproduction we measured egg thiamine concentrations for five species of Lake Ontario salmonines. From this we estimated the proportion of families susceptible to EMS based on whether they were below the ED20, the egg thiamine concentration associated with 20% mortality due to EMS. The ED20s were 1.52, 2.63, and 2.99 nmol/g egg for Chinook salmon (Oncorhynchus tshawytscha), lake trout (Salvelinus namaycush), and coho salmon (Oncorhynchus kisutch), respectively. Based on the proportion of fish having egg thiamine concentrations falling below the ED20, the risk of developing EMS in Lake Ontario was highest for lake trout, followed by coho (O. kisutch), and Chinook salmon, with the least risk for rainbow trout (O. mykiss). For lake trout from western Lake Ontario, mean egg thiamine concentration showed significant annual variability during 1994 to 2003, when the proportion of lake trout at risk of developing EMS based on ED20 ranged between 77 and 100%. Variation in the annual mean egg thiamine concentration for western Lake Ontario lake trout was positively related (p < 0.001, r2 = 0.94) with indices of annual adult alewife biomass. While suggesting the possible involvement of density-dependent changes in alewives, the changes are small relative to egg thiamine concentrations when alewife are not part of the diet and are of insufficient magnitude to allow for natural reproduction by lake trout.

A Statistical Evaluation of Trends in the Water Quality of the Niagara River

Abstract Using water quality data collected at Niagara-on-the-Lake by the Water Quality Branch, Ontario Region, between 1975 and 1980, pH, alkalinity, total phosphorous, and nitrate concentrations are examined for changes over time. Moving averages, Spearmans rank correlation coefficient and regression methods, which model the seasonal cycle, are used. It appears that pH and alkalinity are decreasing, and nitrate increasing, but these changes do not occur for all months. Since river discharge did not change significantly in any month, the changes in pH, alkalinity, and nitrate are not due simply to changes in discharge. A change in total phosphorous concentrations over years was not detected.

Water Quality Changes in Lake Erie, 1968–1980☆

Abstract Data on chlorophyll a, total phosphorus, and hypolimnetic dissolved oxygen concentration, which were collected by Canada Centre for Inland Waters during the period 1968 to 1980, are statistically analyzed to evaluate the changes in the water quality of Lake Erie. There are strong evidences of a decreasing trend in the value of chlorophyll a and total phosphorus in the western, central, and eastern basins of the lake between 1970 and 1980. Furthermore, a statistical model is developed for the hypolimnetic dissolved oxygen concentration in the central basin. The model shows that the increase in depletion is related to the increase in the level of total phosphorus. Hence, it is possible to improve the anoxic conditions in the lake by controlling total phosphorus loadings.

Inference about the mean in log-regression with environmental applications

A standard practice in the analysis of contaminant concentrations is to conduct the statistical analyses in the logarithmic scale. This practice finds support in the empirical fact that many contaminant concentration data appear to be lognormally distributed. However, regulatory rules such as those followed by the US Environmental Protection Agency require that risks should be characterized in terms of the mean contaminant concentration. Furthermore, recent studies suggest that the lognormal distribution may exhibit heavier tails than required in practice for adequate description of contaminant concentrations. Most of the studies on contaminant concentration data deal with one-sample or several sample problems. In this article, we examine the above issues in situations where the contaminant concentration data are supplemented with measurements on concomitant variables such as environmental factors. We use log-regression with arbitrary error distributions as the underlying models and develop estimation and inferential methods for the moments of the contaminant concentration at a new set of experimental conditions. We focus on maximum likelihood, bias correction, minimum variance unbiased estimation, nonparametric estimation and confidence intervals. To illustrate the methods we provide a detailed analysis of data on calcium and magnesium concentrations in samples of water from the Fraser River, British Columbia, Canada, as well as some comparisons using a small sample of the year production and price of ground nuts and cotton in Israel.

Change‐point methods and their applications: contributions of Ian MacNeill

The present paper reviews the important contributions of Ian MacNeill to the theory and methodology of change-point analysis and environmental statistics. The review concentrates on four areas of change-point analysis: sequences of independent random variables; linear regression models with independent as well as serially correlated random errors; regression models with continuity constraints and spatial models of change-points.

Statistical Inference from Multiply Censored Environmental Data

Maximum likelihood estimation for multiply censored samples are discussed. Approximate confidence intervals for the lognormal mean are obtained using both Taylor expansion method and direct method. It is shown that the direct method performs noticeably better than the Taylor expansion method. Simulation results and applications are provided.

Predicting benthic counts in Lake Huron using spatial statistics and quasi-likelihood

Spatial statistics have been applied to many types of problems in the environmental sciences, mostly dealing with continuously distributed data from Gaussian or near-Gaussian processes. There is a need for methods capable of handling discrete, non-Gaussian data, such as species counts from biological processes. This paper applies the method of quasi-likelihood from general linear models to the problem of spatial prediction of benthic invertebrate counts. Variogram models are fitted to quasi-likelihood residuals with two alternative distance metrics. The models are compared using cross-validation and predictions are made using the classical estimator of the variogram and distance determined from a Geographic Information System (GIS). A brief simulation study is included that verifies the applicability of asymptotic results to the estimation of model parameters. Copyright

Maximum microbiological contaminant levels

Microbiological monitoring of drinking water for fecal contamination is a legal requirement in most countries. The objective is to protect the users from water borne disease. We expressed The United States Drinking Water Regulations (DWR) in statistical terms and examined their probabilistic characteristics both analytically and by simulations. The DWR set upper limits on the mean coliform count and on the individual counts of all samples examined per month. Our results show that only an upper limit on the mean coliform count is basically sufficient for DWR. Copyright

On the efficiency of regression analysis with AR(p) errors

In this paper we will consider a linear regression model with the sequence of error terms following an autoregressive stationary process. The statistical properties of the maximum likelihood and least squares estimators of the regression parameters will be summarized. Then, it will be proved that, for some typical cases of the design matrix, both methods produce asymptotically equivalent estimators. These estimators are also asymptotically efficient. Such cases include the most commonly used models to describe trend and seasonality like polynomial trends, dummy variables and trigonometric polynomials. Further, a very convenient asymptotic formula for the covariance matrix will be derived. It will be illustrated through a brief simulation study that, for the simple linear trend model, the result applies even for sample sizes as small as 20.