bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying spatial and temporal patterns in the hydrological character of the Condamine–Balonne river, Australia, using multivariate statistics
Authors: Thoms Martin C. , Parsons Melissa 
Published: September 2003

AbstractMany environmental flow approaches calculate hydrological indicators on an annual or daily basis and do not consider the multiple scales of a rivers' hydrological character. However, hydrologic processes operate within a temporal and spatial dimension, in accordance with multidimensional and hierarchical views of river systems. This study investigates spatial and temporal patterns of the hydrological character of a large river system, and examines the impact of water‐resource development on these patterns. Over 300 regime, history and pulse‐scale flow variables have been calculated from simulated discharge data representing ‘reference’ and ‘current’ water‐resource development scenarios. Multivariate statistical analyses are used to identify measurement nodes with similar hydrological character and to determine the association between different temporal scale flow variables and groups of nodes. Six spatial hydrological zones are identified in the Condamine–Balonne River, Australia. These hydrological zones are found to have become homogenized with water‐resource development. Different temporal scales of flow variables are related to the different hydrological zones, and to water‐resource development scenarios. Thus, the temporal dimension of hydrological character is embedded within a spatial dimension of river zonation. Both dimensions should be considered in a hierarchical context, and environmental flow restoration targets may need to be set for each dimension of a river system. Copyright © 2003 John Wiley & Sons, Ltd.
Classifying the hydraulic performance of riffle–pool bedforms for habitat assessment and river rehabilitation design
Authors: Emery Joanne C. , Gurnell Angela M. , Clifford Nicholas J. , Petts Geoffrey E. , Morrissey Ian P. , Soar Philip J. 
Published: September 2003

AbstractRiffle–pool sequences are the dominant bedforms in gravel and mixed bedded channels of intermediate slope. Their fundamental importance in determining the mesoscale habitat environment is demonstrated in their widespread recreation in channel restoration and rehabilitation schemes. This paper explores the hydraulic functioning of riffle–pool bedforms, particularly the variations in the hydraulic performance of different bed oscillation morphologies. It addresses the need for a quantitative means of classifying flow behaviour that can be applied in functional ecohydraulic river rehabilitation designs.Information from reaches on two physically contrasting UK rivers with well marked riffle–pool topography are used to illustrate the approach. The reaches are mapped to obtain a detailed channel morphology. Surveys describing the streamwise depth‐averaged velocities at three flow stages are interpolated to a common regular grid, grouped using cluster analysis, and then the validity of each cluster as a distinct hydraulic patch class is assessed statistically using analysis of variance. The spatial pattern of the hydraulic patch classes is then overlain on the bed topography to link the patches to the bed morphology. The procedure groups locations along the channel which display similar suites of velocity values at different flow stages and thus differentiates between areas in the channel within which the hydraulic habitat is spatially relatively invariant from those where abrupt changes occur. It also allows the quantitative description of different hydraulic patch classes. Overlay of the hydraulic patch class boundaries on channel reach topography provides a simple but innovative method of exploring and defining the spatial hydraulic habitat implications of riffle–pools of different topographic forms. Copyright © 2003 John Wiley & Sons, Ltd.
Flow restoration and protection in Australian rivers
Authors: Arthington Angela H. , Pusey Bradley J. 
Published: September 2003

AbstractSince 1857 new Australians have constructed many thousands of weirs (3600 in the Murray–Darling Basin alone) and floodplain levee banks, 446 large dams (>10 m crest height) and over 50 intra‐ and inter‐basin water transfer schemes to secure water supplies for human use. Flow regulation has changed the hydrology of major rivers on three temporal sales–the flood pulse (days to weeks), flow history (weeks to years) and the long‐term statistical pattern of flows, or flow regime (decades or longer). The regulation of river flows is widely acknowledged as a major cause of deteriorating conditions in many Australian river and floodplain ecosystems. In response to mounting environmental concerns, all states, territories and the Commonwealth Government have committed the nation to the principles of ecologically sustainable development and a process of national water reform. Rivers and wetlands are now recognized as legitimate ‘users’ of water, and jurisdictions must provide water allocations to sustain and where necessary restore ecological processes and the biodiversity of water‐dependent ecosystems. Progress in the protection and restoration of river and wetland water regimes has been significant, with over half of mainland aquatic systems designated to receive water allocations of some sort. However, exactly how much water they will receive or retain is unclear from the data available. Moreover, the ecological outcomes and benefits of water allocations are not yet apparent in most aquatic ecosystems, with the exception of certain waterbird breeding events, the disruption of algal blooms in weirs and improved fish passage. After reviewing these issues, this paper addresses two vital questions: How much water does a river need? and How can this water be clawed back from other users? Studies conducted to date in Queensland rivers suggest that around 80–92% of natural mean annual flow (and other ecologically relevant hydrological indicators) may be needed to maintain a low risk of environmental degradation. In the Top End of the Northern Territory, some rivers are maintained at 80% of their natural flow, whereas two‐thirds of various flow indicators has been proposed as the restoration target for the River Murray, and 28% of natural mean annual flow has been negotiated for the Snowy River in Victoria. To validate these estimates, ecologists are seeking opportunities to turn river restoration projects into long‐term hypothesis‐driven experiments in ecological restoration, and the funding, time and institutional support to do so. The paper ends with some suggestions to advance the water reforms and achieve higher levels of water allocation for the environment. Copyright © 2003 John Wiley & Sons, Ltd.
Links between ecotoxicology, biomonitoring and water chemistry in the integration of water quality into environmental flow assessments
Authors: Scherman P.‐A. , Muller W. J. , Palmer C. G. 
Published: September 2003

AbstractAquatic organisms have physico‐chemical as well as flow habitat requirements. There are three main kinds of data which are useful in quantifying these requirements: chemical data which describe in‐stream chemical conditions; ecotoxicity data which describe the tolerances of organisms and their in‐stream responses to changing chemical concentrations; and biomonitoring data which describe the distribution and composition of communities. However, it is only by linking these data that organism requirements can be adequately elucidated and translated into resource quality objectives. This paper describes the methods for linking these data and their application in the integration of water quality into environmental flow assessments and the assessment of the water quality Reserve. A case study is presented to demonstrate the methodology. Copyright © 2003 John Wiley & Sons, Ltd.
Factors influencing stranding of wild juvenile brown trout (Salmo trutta) during rapid and frequent flow decreases in an artificial stream
Authors: Halleraker J. H. , Saltveit S. J. , Harby A. , Arnekleiv J. V. , Fjeldstad H.‐P. , Kohler B. 
Published: September 2003

AbstractTo provide environmental guidelines for operation of peaking hydropower plants, stranding experiments with juvenile brown trout (Salmo trutta) were conducted in a 3.8 m wide and 19.2 m long artificial stream. We found a significant decrease in stranding of trout fry by reducing the dewatering speed from >60 cm h−1 to <10 cm h−1. At water temperatures around 11°C we found that less than 8% of the trout stranded during night experiments (on average for all subsets at dewatering rate >60 cm h−1). However, the highest stranding rate occurred at water temperatures around 7°C during rapid dewatering at night (mean=22% stranding). Significantly more fry were stranded in the first versus the second to fifth dewatering episode (mean=22% versus 10% stranding) at rapid daytime dewatering in 11°C water. Stranding of larger fry (>0+) was negligible at water temperatures around 11°C, except at rapid dewatering during daylight. Further, twice as many 0+trout as larger fry (>70 mm in June, >60 mm in late summer) stranded during rapid dewatering during daytime, and almost three times as many 0+stranded during rapid dewatering when they were mixed with trout parr compared to homogeneous 0+experiments. Our study showed a tendency towards an increased stranding of fry with long habituation time (<30 hours versus >30 hours with stable flow). We recommend dewatering in darkness at all times of year to reduce stranding of salmonids, and to use slow ramping rates <10 cm h−1. After longer periods with stable flows, a gentle drop in discharge is recommended, which might also reduce stress and possible sub‐lethal effects. Copyright © 2003 John Wiley & Sons, Ltd.
Evolving policy reforms and experiences for addressing downstream impacts in World Bank water resources projects
Authors: Hirji Rafik , Panella Thomas 
Published: September 2003

AbstractThe systematic integration of environmental flow requirements (EFR) in water resources management decision‐making and policy reforms is a complex task and still a developing field, on which agreement does not yet exist, even in industrialized countries. The complexity is compounded by lack of data and weak institutional capacity. In addition, environmental flow assessments, i.e. the process of determining EFR, can be costly and may yield uncertain results with limited utility to decision‐makers.This paper focuses on the evolving policy reforms and operational experiences within the World Bank to mainstream EFR into water resources management. It includes a brief discussion of the context of environmental flows in the World Bank's work, and looks at the evolution of the World Bank's policies related to the integration of environmental flow considerations in its activities. Five case studies illustrate the World Bank's varied involvement in environmental flow issues. The paper concludes with recommendations for improving the integration of environmental flow considerations into water resource development and management. Copyright © 2003 John Wiley & Sons, Ltd.
A score test for binary data with patient non‐compliance
Authors: Branson Michael , Whitehead John 
Published: September 2003

AbstractA score test is developed for binary clinical trial data, which incorporates patient non‐compliance while respecting randomization. It is assumed in this paper that compliance is ‘all‐or‐nothing’, in the sense that a patient either accepts all of the treatment assigned as specified in the protocol, or none of it. Direct analytic comparisons of the adjusted test statistic for both the score test and the likelihood ratio test are made with the corresponding test statistics that adhere to the intention‐to‐treat principle. It is shown that no gain in power is possible over the intention‐to‐treat analysis, by adjusting for patient non‐compliance. Sample size formulae are derived and simulation studies are used to demonstrate that the sample size approximation holds. Copyright © 2003 John Wiley & Sons, Ltd.
Full‐likelihood approaches to misclassification of a binary exposure in matched case‐control studies
Authors: Rice Kenneth 
Published: September 2003

AbstractWe consider analysis of matched case‐control studies where a binary exposure is potentially misclassified, and there may be a variety of matching ratios. The parameter of interest is the ratio of odds of case exposure to control exposure. By extending the conditional model for perfectly classified data via a random effects or Bayesian formulation, we obtain estimates and confidence intervals for the misclassified case which reduce back to standard analytic forms as the error probabilities reduce to zero. Several examples are given, highlighting different analytic phenomena. In a simulation study, using mixed matching ratios, the coverage of the intervals are found to be good, although point estimates are slightly biased on the log scale. Extensions of the basic model are given allowing for uncertainty in the knowledge of misclassification rates, and the inclusion of prior information about the parameter of interest. Copyright © 2003 John Wiley & Sons, Ltd.
A comparison of two methods for the estimation of precision with incomplete longitudinal data, jointly modelled with a time‐to‐event outcome
Authors: Touloumi G. , Babiker A. G. , Kenward M. G. , Pocock S. J. , Darbyshire J. H. 
Published: September 2003

AbstractSeveral methods for the estimation and comparison of rates of change in longitudinal studies with staggered entry and informative drop‐outs have been recently proposed. For multivariate normal linear models, REML estimation is used. There are various approaches to maximizing the corresponding log‐likelihood; in this paper we use a restricted iterative generalized least squares method (RIGLS) combined with a nested EM algorithm. An important statistical problem in such approaches is the estimation of the standard errors adjusted for the missing data (observed data information matrix). Louis has provided a general technique for computing the observed data information in terms of completed data quantities within the EM framework. The multiple imputation (MI) method for obtaining variances can be regarded as an alternative to this. The aim of this paper is to develop, apply and compare the Louis and a modified MI method in the setting of longitudinal studies where the source of missing data is either death or disease progression (informative) or end of the study (assumed non‐informative). Longitudinal data are simultaneously modelled with the missingness process. The methods are illustrated by modelling CD4 count data from an HIV‐1 clinical trial and evaluated through simulation studies. Both methods, Louis and MI, are used with Monte Carlo simulations of the missing data using the appropriate conditional distributions, the former with 100 simulations, the latter with 5 and 10. It is seen that naive SEs based on the completed data likelihood can be seriously biased. This bias was largely corrected by Louis and modified MI methods, which gave broadly similar estimates. Given the relative simplicity of the modified MI method, it may be preferable. Copyright © 2003 John Wiley & Sons, Ltd.
Efficacy endpoint selection and multiplicity adjustment methods in clinical trials with inherent multiple endpoint issues
Authors: Sankoh Abdul J. , D'Agostino Ralph B. , Huque Mohammad F. 
Published: September 2003

AbstractThe ideal approach for the design and analysis of clinical trials is to select a single primary endpoint that provides a complete characterization of the disease under study and permits an efficient evaluation of the effect of a test drug. However, this is often not possible for a number of diseases or clinical trials. This paper examines some practical clinical decision‐making scenarios for the selection and analysis of efficacy outcome measures in clinical trials with inherent multiplicity components. Copyright © 2003 John Wiley & Sons, Ltd.
Robust asymptotic sampling theory for correlations in pedigrees
Authors: Keen K. J. , Elston Robert C. 
Published: September 2003

AbstractMethods to unravel the genetic determinants of non‐Mendelian diseases lie at the next frontier of statistical approaches for human genetics. It is generally agreed that, before proceeding with segregation or linkage analysis, the trait under study ought to be shown to exhibit familial correlation. By coding dichotomous traits as binary variables, a single robust approach in the estimation of pedigree correlations, rather than two distinct approaches, can be used to assess the potential heritability of a trait, and, latterly, to examine the mode of inheritance. The asymptotic theory to conduct hypothesis tests and confidence intervals for correlations among different members of nuclear families is well established but is applicable only if the nuclear families are independent. As a further contribution to the literature, we derive the asymptotic sampling distribution of correlations between random variables among arbitrary pairs of members in extended families for the Pearson product‐moment estimator with generalized weights. This derivation is done without assuming normality of the traits. The sampling distribution is shown to be asymptotically normal to first order, and hence large‐sample hypothesis tests and confidence intervals with estimates of the variances and correlation coefficients are proposed. Discussion concludes with an example and a suggestion for future research. Copyright © 2003 John Wiley & Sons, Ltd.
Comparing linear and nonlinear mixed model approaches to cosinor analysis
Authors: Mikulich Susan K. , Zerbe Gary O. , Jones Richard H. , Crowley Thomas J. 
Published: September 2003

AbstractThe cosinor model, used for variables governed by circadian and other biological rhythms, is a nonlinear model in the amplitude and acrophase parameters that has a linear representation upon transformation. With linear cosinor analysis, amplitude and acrophase for each harmonic can be computed as nonlinear functions of the estimated linear regression coefficients. Here a flexible mixed model approach to cosinor analysis is considered, where the fixed effect parameters may enter nonlinearly as acrophase and amplitude for each harmonic or linearly after transformation to regression coefficients. In addition, the random effects may enter nonlinearly as subject‐specific deviations from the acrophases and amplitudes or linearly as subject‐specific deviations from the regression coefficients. It is also possible for the fixed effects to enter nonlinearly while the random effects enter linearly. Additionally, we evaluate whether including higher order linear harmonic terms as random effects, that is, Rao–Khatri ‘covariance adjustment’, improves precision. Applying the delta method to nonlinear functions of the parameters from linear mixed cosinor models to obtain approximate variances produces results that are often identical to results from nonlinear mixed models. Consequently, traditional linear cosinor analysis can often be used to estimate and compare the nonlinear parameters of interest, that is, amplitudes and acrophases, via the delta method. This is advantageous since the nonlinear mixed model may have convergence difficulties for more complex models. However, for some multiple‐group analyses, the linear cosinor transformation should not be used and we clarify when the two methods are equivalent and when they differ. Copyright © 2003 John Wiley & Sons, Ltd.
Modelling the relationship between continuous covariates and clinical events using isotonic regression
Authors: Ancukiewicz Marek , Finkelstein Dianne M. , Schoenfeld David A. 
Published: September 2003

AbstractIn a medical study we are often interested in graphically displaying the relationship between continuous variables and clinical events indicating disease progression. Often, it is reasonable to make the minimal assumption that the risk of progression is an arbitrary monotone function of the continuous variable. Sometimes the continuous variable is a disease marker which is recorded longitudinally, and so the goal is to provide a graphical display of the relationship between the hazard for progression and the most recent measurement of the longitudinal marker. For example, we know that for a patient with HIV infection, declining CD4 count is associated with an increased risk of opportunistic infection. The goal of this paper is to extend isotonic regression techniques to failure time data with a continuous covariate, to obtain a non‐parametric estimate for the hazard of disease progression as a monotonic function of the continuous variable. We propose two methods for modelling the relationship of the hazard and covariate: the first assumes that the hazard is constant over time, and the second allows the hazard to be an arbitrary function of time. These methods will be applied to graphically display the risk for an AIDS patient of an opportunistic infection as a function of CD4 count. Copyright © 2003 John Wiley & Sons, Ltd.
The analysis of survival data with a non‐susceptible fraction and dual censoring mechanisms
Authors: Gagnon David R. , Glickman Mark E. , Myers Richard H. , Cupples L. Adrienne 
Published: September 2003

AbstractIt is known that the ages of onset of many diseases are determined by both a genetic predisposition to disease as well as environmental risk factors that are capable of either triggering or hastening the onset of disease. Difficulties in modelling onset ages arise when a large fraction fail to inherit the disease‐causing gene, and multiple reasons for censoring result in unobserved onset ages. We present a parametric Bayesian model that includes subjects with missing age information, non‐susceptible subjects and allows for regression on risk factor information. The model is fit using Markov chain Monte Carlo simulation from the posterior distribution, and allows the simultaneous estimation of the proportion of the population at risk of disease, the mean onset age of disease, survival after disease onset, and the association of risk factors with susceptibility, onset age and survival after onset. An example employing Huntington's disease data is presented. Copyright © 2003 John Wiley & Sons, Ltd.
A hierarchical model for spatially clustered disease rates
Authors: Gangnon Ronald E. , Clayton Murray K. 
Published: September 2003

AbstractMaps of regional disease rates are potentially useful tools in examining spatial patterns of disease and for identifying clusters. Bayes and empirical Bayes approaches to this problem have proven useful in smoothing crude maps of disease rates. In recent years, models including both spatially correlated random effects and spatially unstructured random effects have been very popular. The spatially correlated random effects have been proposed in an attempt to capture a general clustering in the data. As an alternative, we propose replacing the spatially structured random effect with fixed clustering effects associated with particular areas. A reversible jump Markov chain Monte Carlo (RJMCMC) algorithm for posterior inference is described. We illustrate the model using the well‐known New York leukaemia data. Copyright © 2003 John Wiley & Sons, Ltd.