Mass Coral Reef Bleaching: A Recent Outcome of Increased El Niño Activity?

Coral reefs are generally considered to be the most biologically productive of all marine ecosystems, but in recent times these vulnerable aquatic resources have been subject to unusual degradation. The general decline in reefs has been greatly accelerated by mass bleaching in which corals whiten en masse and often fail to recover. Empirical evidence indicates a coral reef bleaching cycle in which major bleaching episodes are synchronized with El Niño events that occur every 3–4 years on average. By heating vast areas of the Pacific Ocean, and affecting the Indian and Atlantic Oceans as well, El Niño causes widespread damage to reefs largely because corals are very sensitive to temperature changes. However, mass bleaching events were rarely observed before the 1970s and their abrupt appearance two decades ago remains an enigma. Here we propose a new explanation for the sudden occurrence of mass bleaching and show that it may be a response to the relative increase in El Niño experienced over the last two decades.     

Assessment of Optimal Selected Prognostic Factors

The identification and assessment of prognostic factors is one of the major tasks in clinical research. The assessment of one single prognostic factor can be done by recently established methods for using optimal cutpoints. Here, we suggest a method to consider an optimal selected prognostic factor from a set of prognostic factors of interest. This can be viewed as a variable selection method and is the underlying decision problem at each node of various tree building algorithms. We propose to use maximally selected statistics where the selection is defined over the set of prognostic factors and over all cutpoints in each prognostic factor. We demonstrate that it is feasible to compute the approximate null distribution. We illustrate the new variable selection test with data of the German Breast Cancer Study Group and of a small study on patients with diffuse large B‐cell lymphoma. Using the null distribution for a p‐value adjusted regression trees algorithm, we adjust for the number of variables analysed at each node as well. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Conditional and Unconditional Simulation of Healthy Patients' Visual Fields

This paper describes a simulation problem, motivated by the study of glaucoma, a very serious and widespread ocular illness. To ascertain whether a patient suffers from glaucoma, a perimetric test is done, but the evolution of the disease is very slow, and large longitudinal sets of tests taken on the same patient are needed to study its evolution, to analyze the efficiency of existing methods to detect the progression of glaucoma and to develop new ones. Simulation can be a very useful procedure to get appropriate data sets to work with. Our aim in this work is to simulate several VFs in a healthy patient to reflect his evolution in time. We use a spatio‐temporal model to simulate from, taking into account the correlation existing between the observed (or simulated) values in space and time. Two different simulation procedures (unconditional and conditional) are studied, and applied to obtain the simulations we are interested in. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Reaction mechanism of surfactant‐sensitized chemiluminescence of bis(2,4,6‐trichlorophyenyl) oxalate and hydrogen peroxide induced by gold nanoparticles

The chemiluminescence (CL) of bis(2,4,6‐trichlorophyenyl) oxalate with hydrogen peroxide in the present of cationic surfactant and gold nanoparticles was studied. The CL emission was obviously enhanced in the presence of surfactant at a suitable concentration, with a synergetic catalysis effect exhibited. Different sizes of gold nanoparticles (15 and 50 nm) showed different effects on CL intensity. Mechanisms of the CL reaction and sensitization effect are discussed. Copyright © 2008 John Wiley & Sons, Ltd.     

Describing Ordinal Odds Ratios for Stratified r × c Tables

For an r × ctable with ordinal responses, odds ratios are commonly used to describe the relationship between the row and column variables. This article shows two types of ordinal odds ratios where local‐global odds ratios are used to compare several groups on a c‐category ordinal response and a global odds ratio is used to measure the global association between a pair of ordinal responses. When there is a stratification factor, we consider Mantel‐Haenszel (MH) type estimators of these odds ratios to summarize the association from several strata. Like the ordinary MH estimator of the common odds ratio for several 2 × 2 contingency tables, the estimators are used when the association is not expected to vary drastically among the strata. Also, the estimators are consistent under the ordinary asymptotic framework in which the number of strata is fixed and also under sparse asymptotics in which the number of strata grows with the sample size. Compared to the maximum likelihood estimators, simulations find that the MH type estimators perform better especially when each stratum has few observations. This article provides variances and covariances formulae for the local‐global odds ratios estimators and applies the bootstrap method to obtain a standard error for the global odds ratio estimator. At the end, we discuss possible ways of testing the homogeneity assumption.     

Coexistence of natural enemies in a multitrophic host–parasitoid system

Abstract.  1. This study explored the temporal and spatial aspects of coexistence over many generations in a multispecies host–parasitoid assemblage.
2. The long-term interaction between the cabbage root fly, Delia radicum (Diptera: Anthomyiidae), and two of its natural enemies, Trybliographa rapae (Hymenoptera: Fitigidae) and Aleochara bilineata (Coleoptera: Staphylinidae), in a cultivated field at Silwood Park over 19 years was explored.
3. Although time series showed that the populations were regulated, the impact of the natural enemies was highly variable. Within-year determinants showed that the spatial response of the specialist parasitoid, T. rapae , was predominantly independent of host density while A. bilineata acted simply as a randomly foraging generalist parasitoid.
4. These findings are compared and contrasted with an earlier investigation of the same system when only the first 9 years of the time series were available. This study demonstrated the potential of long-term field studies for exploring hypotheses on population regulation, persistence, and coexistence.     

Estimating woody and herbaceous vegetation cover from time series satellite observations

In this paper we test a method to estimate the tree and grass vegetation cover over Australia from satellite-derived normalized difference vegetation index (NDVI) time series (monthly 1981–91, ≈5 km pixels) observations. The evergreen cover is assumed to track along the base of the NDVI time series, which is assumed to be equivalent to the woody vegetation cover. The base of the NDVI time series is estimated using modifications to a classical econometric model (i.e. time series is the sum of trend, seasonal and random components). Estimates of the average evergreen component during 1982–85 and 1986–89 were generally consistent with known vegetation distributions. Changes in evergreen cover were largely restricted to the south-west and south-east of Australia. Those changes were largely the result of differences in rainfall between the two periods. The proposed method for estimating woody vegetation cover is found to be generally robust. However, there are some regions where the grass (or pasture) is mostly evergreen. Some possible refinements are proposed to handle such cases.