A sampling device to quantify offspring release of sessile marine invertebrates

Quantifying the rate of propagule release is of most importance to estimate reproductive output of natural populations, but simple methods to obtain such data are seldom reported. We designed and tested an inexpensive apparatus capable of reliably measure the release of gametes, eggs or larvae of sessile marine invertebrates in vertical walls. A population of the acom barnacle Chthamalus bisinuatus was sampled with this trap over 68d to obtain a time series of naupliar release. An apparent semilunar trend is shown, indicating the effectiveness of this sampling method.

Sampling study in milk storage tanks by INAA

This study investigated the representativeness of samples for assessing chemical elements in milk bulk tanks. Milk samples were collected from a closed tank in a dairy plant and from an open top tank in a dairy farm. Samples were analyzed for chemical elements by instrumental neutron activation analysis (INAA). For both experiments, Br, Ca, Cs, K, Na, Rb and Zn did not present significant differences between samples thereby indicating the appropriateness of the sampling procedure adopted to evaluate the analytes of interest.

Feasibility of using solid sampling graphite furnace atomic absorption spectrometry for preparation of spiked filter papers with Cu and Zn as standards for direct solid analysis

An approach was developed for the preparation of cryogenic ground spiked filter papers with Cu and Zn for use as synthetic calibrating standards for direct solid microanalysis. Solid sampling graphite furnace atomic absorption spectrometry was used to evaluate the microhomogeneity and to check the applicability of the synthetic calibrating standards for the direct determination of Cu and Zn in vegetable certified reference materials. The found concentrations presented no statistical differences at the 95% confidence level. The homogeneity factors ranged from 2.7 to 4.2 for Cu and from 6.4 to 11.5 for Zn.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

Sampling phylogenetic tree space with the generalized Gibbs sampler

The generalized Gibbs sampler (GGS) is a recently developed Markov chain Monte Carlo (MCMC) technique that enables Gibbs-like sampling of state spaces that lack a convenient representation in terms of a fixed coordinate system. This paper describes a new sampler, called the tree sampler, which uses the GGS to sample from a state space consisting of phylogenetic trees. The tree sampler is useful for a wide range of phylogenetic applications, including Bayesian, maximum likelihood, and maximum parsimony methods. A fast new algorithm to search for a maximum parsimony phylogeny is presented, using the tree sampler in the context of simulated annealing. The mathematics underlying the algorithm is explained and its time complexity is analyzed. The method is tested on two large data sets consisting of 123 sequences and 500 sequences, respectively. The new algorithm is shown to compare very favorably in terms of speed and accuracy to the program DNAPARS from the PHYLIP package.

Isotopes, wool, and rangeland monitoring: Let the sheep do the sampling

Stable carbon isotope analyses of wool staples provided insight into the vegetation consumed by sheep at a temporal resolution not previously studied. Contemporary Australian and historic South African samples dating back to 1916 were analyzed for their stable carbon isotope ratio, a proxy for the proportion of C-3 and C-4 plant species consumed by animals. Sheep sample vegetation continuously throughout a year, and as their wool grows it integrates and stores information about their diet. In subtropical and tropical rangelands the majority of grass species are C-4. Since sheep prefer to graze, and their wool is an isotopic record of their diet, we now have the potential to develop a high resolution index to the availability of grass from a sheep's perspective. Isotopic analyses of wool suggest a new direction for monitoring grazing and for the reconstruction of past vegetation changes, which will make a significant contribution to traditional rangeland ecology and management. It is recommended that isotopic and other analyses of wool be further developed for use in rangeland monitoring programs to provide valuable feedback for land managers.

Protein fold recognition without Boltzmann statistics or explicit physical basis

We present a fast method for finding optimal parameters for a low-resolution (threading) force field intended to distinguish correct from incorrect folds for a given protein sequence. In contrast to other methods, the parameterization uses information from >10(7) misfolded structures as well as a set of native sequence-structure pairs. In addition to testing the resulting force field's performance on the protein sequence threading problem, results are shown that characterize the number of parameters necessary for effective structure recognition.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

Bacteria in shrimp pond sediments: their role in mineralizing nutrients and some suggested sampling strategies

Strategies for sampling sediment bacteria were examined in intensive shrimp, Penaeus monodon (Fabricius), ponds in tropical Australia. Stratified sampling of bacteria at the end of the production season showed that the pond centre, containing flocculated sludge, had significantly higher bacterial counts (15.5 X 10(9) g(-1) dw) than the pond periphery (8.1 X 10(9) g(-1) dw), where the action of aerators had swept the pond floor. The variation in bacterial counts between these two zones within a pond was higher than that between sites within each zone or between ponds. Therefore, sampling effort should be focused within these zones: for example, sampling two ponds at six locations within each of the two zones resulted in a coefficient of variation of approximate to 5%. Bacterial numbers in the sediment were highly correlated with sediment grain size, probably because eroded soil particles and organic waste both accumulated in the centre of the pond. Despite high inputs of organic matter added to the ponds, principally as pelleted feeds, the mean bacterial numbers and nutrient concentrations (i.e. organic carbon, nitrogen and phosphorus) in the sediment were similar to those found in mangrove sediments. This suggests that bacteria are rapidly remineralizing particulates into soluble compounds. Bacterial numbers were highly correlated with organic carbon and total kjeldahl nitrogen in the sediment, suggesting that these were limiting factors to bacterial growth.

Critical values for unit root and cointegration test statistics - the use of response surface equations

This note considers the value of surface response equations which can be used to calculate critical values for a range of unit root and cointegration tests popular in applied economic research.

Accelerating seismic energy release and evolution of event time and size statistics: Results from two heterogeneous cellular automaton models

The evolution of event time and size statistics in two heterogeneous cellular automaton models of earthquake behavior are studied and compared to the evolution of these quantities during observed periods of accelerating seismic energy release Drier to large earthquakes. The two automata have different nearest neighbor laws, one of which produces self-organized critical (SOC) behavior (PSD model) and the other which produces quasi-periodic large events (crack model). In the PSD model periods of accelerating energy release before large events are rare. In the crack model, many large events are preceded by periods of accelerating energy release. When compared to randomized event catalogs, accelerating energy release before large events occurs more often than random in the crack model but less often than random in the PSD model; it is easier to tell the crack and PSD model results apart from each other than to tell either model apart from a random catalog. The evolution of event sizes during the accelerating energy release sequences in all models is compared to that of observed sequences. The accelerating energy release sequences in the crack model consist of an increase in the rate of events of all sizes, consistent with observations from a small number of natural cases, however inconsistent with a larger number of cases in which there is an increase in the rate of only moderate-sized events. On average, no increase in the rate of events of any size is seen before large events in the PSD model.

Semiochemicals and social signaling in the wild European rabbit in Australia: II. Variations in chemical composition of chin gland secretion across sampling sites

The volatile components of the chin gland secretion of the wild European rabbit, Oryctolagus cuniculus (L.), were investigated with the use of gas chromatography. Studies of the chemical nature of this secretion by previous workers demonstrated that it was important in the maintenance of social structure in this species. This study identified 34 different volatile components that consist primarily of aromatic and aliphatic hydrocarbons. Especially common are a series of alkyl-substituted benzene derivatives that provide most of the compound diversity in the secretion. Samples of chin gland secretion collected from animals at three different geographical locations, separated by more than 100 km, showed significant differences in composition. This work suggests that variation among populations needs to be considered when undertaking semiochemical research. Alternate nonparametric methods are also used for the analysis of chromatographic data.

Estimating correlations from epidemiological data in the presence of measurement error

Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.