Environmental Data (environmental + data)

Distribution by Scientific Domains
Distribution within Life Sciences

Selected Abstracts

Effects of species and habitat positional errors on the performance and interpretation of species distribution models

Patrick E. Osborne
Abstract Aim, A key assumption in species distribution modelling is that both species and environmental data layers contain no positional errors, yet this will rarely be true. This study assesses the effect of introduced positional errors on the performance and interpretation of species distribution models. Location, Baixo Alentejo region of Portugal. Methods, Data on steppe bird occurrence were collected using a random stratified sampling design on a 1-km2 pixel grid. Environmental data were sourced from satellite imagery and digital maps. Error was deliberately introduced into the species data as shifts in a random direction of 0,1, 2,3, 4,5 and 0,5 pixels. Whole habitat layers were shifted by 1 pixel to cause mis-registration, and the cumulative effect of one to three shifted layers investigated. Distribution models were built for three species using three algorithms with three replicates. Test models were compared with controls without errors. Results, Positional errors in the species data led to a drop in model performance (larger errors having larger effects , typically up to 10% drop in area under the curve on average), although not enough for models to be rejected. Model interpretation was more severely affected with inconsistencies in the contributing variables. Errors in the habitat layers had similar although lesser effects. Main conclusions, Models with species positional errors are hard to detect, often statistically good, ecologically plausible and useful for prediction, but interpreting them is dangerous. Mis-registered habitat layers produce smaller effects probably because shifting entire layers does not break down the correlation structure to the same extent as random shifts in individual species observations. Spatial autocorrelation in the habitat layers may protect against species positional errors to some extent but the relationship is complex and requires further work. The key recommendation must be that positional errors should be minimised through careful field design and data processing. [source]

A missing values imputation method for time series data: an efficient method to investigate the health effects of sulphur dioxide levels

Swarna Weerasinghe
Abstract Environmental data contains lengthy records of sequential missing values. Practical problem arose in the analysis of adverse health effects of sulphur dioxide (SO2) levels and asthma hospital admissions for Sydney, Nova Scotia, Canada. Reliable missing values imputation techniques are required to obtain valid estimates of the associations with sparse health outcomes such as asthma hospital admissions. In this paper, a new method that incorporates prediction errors to impute missing values is described using mean daily average sulphur dioxide levels following a stationary time series with a random error. Existing imputation methods failed to incorporate the prediction errors. An optimal method is developed by extending a between forecast method to include prediction errors. Validity and efficacy are demonstrated comparing the performances with the values that do not include prediction errors. The performances of the optimal method are demonstrated by increased validity and accuracy of the , coefficient of the Poisson regression model for the association with asthma hospital admissions. Visual inspection of the imputed values of sulphur dioxide levels with prediction errors demonstrated that the variation is better captured. The method is computationally simple and can be incorporated into the existing statistical software. Copyright © 2009 John Wiley & Sons, Ltd. [source]

Space,time zero-inflated count models of Harbor seals,

Jay M. Ver Hoef
Abstract Environmental data are spatial, temporal, and often come with many zeros. In this paper, we included space-time random effects in zero-inflated Poisson (ZIP) and ,hurdle' models to investigate haulout patterns of harbor seals on glacial ice. The data consisted of counts, for 18 dates on a lattice grid of samples, of harbor seals hauled out on glacial ice in Disenchantment Bay, near Yakutat, Alaska. A hurdle model is similar to a ZIP model except it does not mix zeros from the binary and count processes. Both models can be used for zero-inflated data, and we compared space-time ZIP and hurdle models in a Bayesian hierarchical model. Space-time ZIP and hurdle models were constructed by using spatial conditional autoregressive (CAR) models and temporal first-order autoregressive (AR(1)) models as random effects in ZIP and hurdle regression models. We created maps of smoothed predictions for harbor seal counts based on ice density, other covariates, and spatio-temporal random effects. For both models predictions around the edges appeared to be positively biased. The linex loss function is an asymmetric loss function that penalizes overprediction more than underprediction, and we used it to correct for prediction bias to get the best map for space-time ZIP and hurdle models. Published in 2007 by John Wiley & Sons, Ltd. [source]

A spatial model of population dynamics of the early life stages of Japanese sardine, Sardinops melanostictus, off the Pacific coast of Japan

Maki Suda
Abstract We constructed a numerical model reproducing the transport, survival and individual growth of the early life stages of Japanese sardine, Sardinops melanostictus, off the Pacific coast of Japan during 1978,93. The causes of early life stage mortality, including the influence of the effects of the spatial relationship between the spawning grounds and the Kuroshio on the mortality rate, were investigated. Survival and transport from egg stage to 60 days after spawning were modelled daily in a 1 × 1 degree mesh cell and individual growth in the period was modelled in each region (Kuroshio, Inshore, Offshore and Transition regions). Individual growth and survival from 60 to 180 days after spawning were modelled daily in the Transition region. Environmental data were taken from outside the model system. Our simulation indicates that survival variability in the larval stage (5,25 mm in standard length) is the key factor in determining the year-class strength. The simulation revealed that strong year classes occurred with good survival in the spawning ground and whilst entrained in the Kuroshio current being transported to the main feeding grounds in the Transition region. The simulation also indicated that survival rates in 1988,93 were low in the Inshore, Kuroshio and Offshore regions, which depressed the year-class strength during that period. [source]

The influence of stream invertebrate composition at neighbouring sites on local assemblage composition

Summary 1. The composition of freshwater invertebrate assemblages at a location is determined by a range of physico-chemical and biotic factors in the local environment, as well as larger-scale spatial factors such as sources of recruits. We assessed the relative importance of the species composition of local neighbourhoods and proximal environmental factors on the composition of invertebrate assemblages. 2. Macroinvertebrate assemblages were sampled at 188 running-water sites in the catchment of the River Rede, north-east England. A total of 176 species were recorded. 3. Environmental data, in the form of 13 biotic and abiotic measurements that described stream physical structure, aquatic vegetation and water characteristics, were recorded for each site. Detrended correspondence analysis was then used to simplify nine of these stream environmental variables to create an index of stream structure. 4. The species composition of the invertebrate assemblages was related to the environmental variables, using an information theoretic approach. The impact of the species composition of neighbouring sites on each site was determined using Moran's I and autoregressive modelling techniques. 5. Species composition was primarily associated with water pH and stream structure. The importance of the species composition of neighbouring sites in determining local species assemblages differed markedly between taxa. The autoregressive component was low for Coleoptera, intermediate for Trichoptera and Plecoptera, and high for Ephemeroptera. 6. We hypothesise that the observed differences in the autoregressive component amongst these orders reflects variation in their dispersal abilities from neighbouring sites. [source]

Epidemiologic Analysis of Factors Associated with Local Disappearances of Native Ranid Frogs in Arizona

análisis de factores de riesgo; declinación de anfibios; declinación de ranas; epidemiología de vida silvestre; métodos de control de casos Abstract:,We examined factors that may independently or synergistically contribute to amphibian population declines. We used epidemiologic case,control methodology to sample and analyze a large database developed and maintained by the Arizona Game and Fish Department that describes historical and currently known ranid frog localities in Arizona, U.S.A. Sites with historical documentation of target ranid species (n= 324) were evaluated to identify locations where frogs had disappeared during the study period (case sites) and locations where frog populations persisted (control sites). Between 1986 and 2003, 117 (36%) of the 324 sites became case sites, of which 105 were used in the analyses. An equal number of control sites were sampled to control for the effects of time. Risk factors, or predictor variables, were defined from environmental data summarized during site surveys and geographic information system data layers. We evaluated risk factors with univariate and multifactorial logistic-regression analyses to derive odds ratios (OR). Odds for local population disappearance were significantly related to 4 factors in the multifactorial model. Disappearance of frog populations increased with increasing elevation (OR = 2.7 for every 500 m, p < 0.01). Sites where disappearances occurred were 4.3 times more likely to have other nearby sites that also experienced disappearances (OR = 4.3, p < 0.01), whereas the odds of disappearance were 6.7 times less (OR = 0.15, p < 0.01) when there was a source population nearby. Sites with disappearances were 2.6 times more likely to have introduced crayfish than were control sites (OR = 2.6, p= 0.04). The identification of factors associated with frog disappearances increases understanding of declines occurring in natural populations and aids in conservation efforts to reestablish and protect native ranids by identifying and prioritizing implicated threats. Resumen:,Examinamos los factores que pueden contribuir independiente o sinérgicamente a la declinación de poblaciones de anfibios. Utilizamos una metodología epidemiológica de control de casos para muestrear y analizar una base de datos desarrollada y mantenida por el Departamento de Caza y Pesca de Arizona que describe las localidades históricas y actuales de ranas en Arizona, E. U. A. Los sitios con documentación histórica de las especies de ránidos (n= 324) fueron evaluados para identificar localidades donde las ranas desaparecieron durante el período de estudio (sitios caso) y localidades donde las poblaciones de ranas persistieron (sitios control). Entre 1986 y 2003, 36% (117) de los 324 sitios se volvieron sitios caso, de los cuales 105 fueron utilizados en los análisis. El mismo número de sitios control fueron muestreados para controlar los efectos del tiempo. Los factores de riesgo, o variables predictivas, fueron definidos a partir de datos ambientales obtenidos de los muestreos en los sitios y de capas de datos de un sistema información geográfica. Evaluamos los factores de riesgo con análisis de regresión logística univariada y multivariada para derivar proporciones de probabilidades (PP). Las probabilidad para la desaparición de una población local estuvo relacionada significativamente con 4 factores en el modelo multifactorial. La desaparición de poblaciones de ranas incrementó con la elevación (PP = 2.7 por cada 500 m, p < 0.01). Los sitios donde ocurrieron las desapariciones fueron 4.3 veces más propensos a estar cerca de otros sitios donde ocurrieron desapariciones (PP = 4.3, p < 0.01), mientras que la probabilidad de desaparición fue 6.7 veces menos (PP = 0.15, p < 0.01) cuando había una población fuente cercana. Los sitios con desapariciones fueron 2.6 veces más propensos a tener langostinos introducidos que los sitios control (PP = 2.6, p= 0.04). La identificación de factores asociados con la desaparición de ranas incrementa el conocimiento de las declinaciones de poblaciones naturales y ayuda a los esfuerzos de conservación para el reestablecimiento y la protección de ránidos nativos mediante la identificación y priorización de las amenazas implicadas. [source]

Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment

Simon Ferrier
ABSTRACT Generalized dissimilarity modelling (GDM) is a statistical technique for analysing and predicting spatial patterns of turnover in community composition (beta diversity) across large regions. The approach is an extension of matrix regression, designed specifically to accommodate two types of nonlinearity commonly encountered in large-scaled ecological data sets: (1) the curvilinear relationship between increasing ecological distance, and observed compositional dissimilarity, between sites; and (2) the variation in the rate of compositional turnover at different positions along environmental gradients. GDM can be further adapted to accommodate special types of biological and environmental data including, for example, information on phylogenetic relationships between species and information on barriers to dispersal between geographical locations. The approach can be applied to a wide range of assessment activities including visualization of spatial patterns in community composition, constrained environmental classification, distributional modelling of species or community types, survey gap analysis, conservation assessment, and climate-change impact assessment. [source]

Plant species richness and environmental heterogeneity in a mountain landscape: effects of variability and spatial configuration

ECOGRAPHY, Issue 4 2006
Alexia Dufour
The loss of biodiversity has become a matter of urgent concern and a better understanding of local drivers is crucial for conservation. Although environmental heterogeneity is recognized as an important determinant of biodiversity, this has rarely been tested using field data at management scale. We propose and provide evidence for the simple hypothesis that local species diversity is related to spatial environmental heterogeneity. Species partition the environment into habitats. Biodiversity is therefore expected to be influenced by two aspects of spatial heterogeneity: 1) the variability of environmental conditions, which will affect the number of types of habitat, and 2) the spatial configuration of habitats, which will affect the rates of ecological processes, such as dispersal or competition. Earlier, simulation experiments predicted that both aspects of heterogeneity will influence plant species richness at a particular site. For the first time, these predictions were tested for plant communities using field data, which we collected in a wooded pasture in the Swiss Jura mountains using a four-level hierarchical sampling design. Richness generally increased with increasing environmental variability and "roughness" (i.e. decreasing spatial aggregation). Effects occurred at all scales, but the nature of the effect changed with scale, suggesting a change in the underlying mechanisms, which will need to be taken into account if scaling up to larger landscapes. Although we found significant effects of environmental heterogeneity, other factors such as history could also be important determinants. If a relationship between environmental heterogeneity and species richness can be shown to be general, recently available high-resolution environmental data can be used to complement the assessment of patterns of local richness and improve the prediction of the effects of land use change based on mean site conditions or land use history. [source]

Patterns and causes of species richness: a general simulation model for macroecology

Nicholas J. Gotelli
Abstract Understanding the causes of spatial variation in species richness is a major research focus of biogeography and macroecology. Gridded environmental data and species richness maps have been used in increasingly sophisticated curve-fitting analyses, but these methods have not brought us much closer to a mechanistic understanding of the patterns. During the past two decades, macroecologists have successfully addressed technical problems posed by spatial autocorrelation, intercorrelation of predictor variables and non-linearity. However, curve-fitting approaches are problematic because most theoretical models in macroecology do not make quantitative predictions, and they do not incorporate interactions among multiple forces. As an alternative, we propose a mechanistic modelling approach. We describe computer simulation models of the stochastic origin, spread, and extinction of species' geographical ranges in an environmentally heterogeneous, gridded domain and describe progress to date regarding their implementation. The output from such a general simulation model (GSM) would, at a minimum, consist of the simulated distribution of species ranges on a map, yielding the predicted number of species in each grid cell of the domain. In contrast to curve-fitting analysis, simulation modelling explicitly incorporates the processes believed to be affecting the geographical ranges of species and generates a number of quantitative predictions that can be compared to empirical patterns. We describe three of the ,control knobs' for a GSM that specify simple rules for dispersal, evolutionary origins and environmental gradients. Binary combinations of different knob settings correspond to eight distinct simulation models, five of which are already represented in the literature of macroecology. The output from such a GSM will include the predicted species richness per grid cell, the range size frequency distribution, the simulated phylogeny and simulated geographical ranges of the component species, all of which can be compared to empirical patterns. Challenges to the development of the GSM include the measurement of goodness of fit (GOF) between observed data and model predictions, as well as the estimation, optimization and interpretation of the model parameters. The simulation approach offers new insights into the origin and maintenance of species richness patterns, and may provide a common framework for investigating the effects of contemporary climate, evolutionary history and geometric constraints on global biodiversity gradients. With further development, the GSM has the potential to provide a conceptual bridge between macroecology and historical biogeography. [source]

Seasonal and spatial variation in a prairie stream-fish assemblage

K. G. Ostrand
Abstract,,,Stream-fish assemblage and environmental data for 13 sites in the upper Brazos River, Texas, USA during 1997 and 1998 were used to assess the relationship between environmental conditions, and seasonal and spatial variation in fish species abundance and distribution patterns. There was considerable spatial variation in environmental conditions among sites. Spatial variation in species diversity and species composition was related to variation in conductance (salinity), depth and current velocity among sites and streams. Species diversity increased downstream and species composition shifted from primarily cyprinodontids upstream to cyprinids downstream. Among all dominant species, spatial components of variation in fish abundance were greater than seasonal components, suggesting that assemblage structure is determined more by average or persistent differences in environmental conditions among sites than by seasonal variation in environmental conditions. [source]

The role of indicators in improving timeliness of international environmental reports

Ulla Rosenström
Abstract Environmental indicators were developed mainly to improve information flows from scientists to policy-makers. This article discusses the importance of timely environmental data and investigates the influence of indicator-based reporting on the data timeliness of environmental reports by international organizations. Timeliness of information contributes to the quality and appeal of the reports, and to their role as early warning tools, and increases their usability by decision-makers in short-term decision cycles. The results of an analysis of 11 international reports by the European Environmental Agency (EEA) and the Organization for Economic Co-Operation and Development (OECD) show a considerable time lag of three years on average, with only minor development towards more timely reporting. The results suggest that the introduction of environmental indicators has not improved the timeliness of reporting. In order to overcome these problems, the article recommends some methods for improving timeliness. These include better choice of indicators in smaller sets, use of preliminary data and outlooks, development of new indicators, publishing on the internet and more effective use of internet databases to avoid intermediate levels in data collection. Copyright © 2006 John Wiley & Sons, Ltd and ERP Environment. [source]

Pharmaceutical metabolites in the environment: Analytical challenges and ecological risks,

Mary D. Celiz
Abstract The occurrence of human and veterinary pharmaceuticals in the environment has been a subject of concern for the past decade because many of these emerging contaminants have been shown to persist in soil and water. Although recent studies indicate that pharmaceutical contaminants can pose long-term ecological risks, many of the investigations regarding risk assessment have only considered the ecotoxicity of the parent drug, with very little attention given to the potential contributions that metabolites may have. The scarcity of available environmental data on the human metabolites excreted into the environment or the microbial metabolites formed during environmental biodegradation of pharmaceutical residues can be attributed to the difficulty in analyzing trace amounts of previously unknown compounds in complex sample matrices. However, with the advent of highly sensitive and powerful analytical instrumentations that have become available commercially, it is likely that an increased number of pharmaceutical metabolites will be identified and included in environmental risk assessment. The present study will present a critical review of available literature on pharmaceutical metabolites, primarily focusing on their analysis and toxicological significance. It is also intended to provide an overview on the recent advances in analytical tools and strategies to facilitate metabolite identification in environmental samples. This review aims to provide insight on what future directions might be taken to help scientists in this challenging task of enhancing the available data on the fate, behavior, and ecotoxicity of pharmaceutical metabolites in the environment. [source]

Evaluation of statistical methods for left-censored environmental data with nonuniform detection limits

Parikhit Sinha
Abstract Monte Carlo simulations were used to evaluate statistical methods for estimating 95% upper confidence limits of mean constituent concentrations for left-censored data with nonuniform detection limits. Two primary scenarios were evaluated: data sets with 15 to 50% nondetected samples and data sets with 51 to 80% nondetected samples. Sample size and the percentage of nondetected samples were allowed to vary randomly to generate a variety of left-censored data sets. All statistical methods were evaluated for efficacy by comparing the 95% upper confidence limits for the left-censored data with the 95% upper confidence limits for the noncensored data and by determining percent coverage of the true mean (,). For data sets with 15 to 50% nondetected samples, the trimmed mean, Winsorization, Aitchison's, and log-probit regression methods were evaluated. The log-probit regression was the only method that yielded sufficient coverage (99,100%) of ,, as well as a high correlation coefficient (r2 = 0.99) and small average percent residuals (, 0.1%) between upper confidence limits for censored versus noncensored data sets. For data sets with 51 to 80% nondetected samples, a bounding method was effective (r2 = 0.96,0.99, average residual = ,5% to ,7%, 95-98% coverage of ,), except when applied to distributions with low coefficients of variation (standard deviation/, < 0.5). Thus, the following recommendations are supported by this research: data sets with 15 to 50% nondetected samples,log-probit regression method and use of Chebyshev theorem to estimate 95% upper confidence limits; data sets with 51 to 80% nondetected samples, bounding method and use of Chebyshev theorem to estimate 95% upper confidence limits. [source]

Maximum likelihood estimators of population parameters from doubly left-censored samples

Abou El-Makarim A. Aboueissa
Abstract Left-censored data often arise in environmental contexts with one or more detection limits, DLs. Estimators of the parameters are derived for left-censored data having two detection limits: DL1 and DL2 assuming an underlying normal distribution. Two different approaches for calculating the maximum likelihood estimates (MLE) are given and examined. These methods also apply to lognormally distributed environmental data with two distinct detection limits. The performance of the new estimators is compared utilizing many simulated data sets. Examples are given illustrating the use of these methods utilizing a computer program given in the Appendix. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Site scores and conditional biplots in canonical correspondence analysis

Jan Graffelman
Abstract Canonical correspondence analysis is an important multivariate technique in community ecology. It produces an interesting biplot that summarizes the data matrices involved in the analysis. The method produces two sets of site scores that can be used in a biplot. One set concerns site scores that are weighted averages of the species scores (WA scores), and the other set represents site scores that are linear combinations of the environmental variables (LC scores). We show that the use of both sets of scores in a CCA biplot can be justified. The use of the WA scores leads to the best possible representation of the species data conditional on the representation of the weighted averages. Likewise, the LC scores lead to the best possible representation of the environmental variables, also conditional on the representation of the weighted averages and on the use of a Mahalanobis metric. The eigenvalues obtained in CCA indicate how well the species data are represented when LC scores are used. The quality of representation of the species data when WA scores are used can be computed from the CCA eigenvalues and the variances of the WA scores. Scalar products between WA scores and environmental variable vectors do not form a biplot of the environmental data. Theoretical results are illustrated with Australian data from freshwater ecology. Copyright © 2003 John Wiley & Sons, Ltd. [source]

Multi-step forecasting for nonlinear models of high frequency ground ozone data: a Monte Carlo approach

Alessandro Fassò
Abstract Multi-step prediction using high frequency environmental data is considered. The complex dynamics of ground ozone often requires models involving covariates, multiple frequency periodicities, long memory, nonlinearity and heteroscedasticity. For these reasons parametric models, which include seasonal fractionally integrated components, self-exciting threshold autoregressive components, covariates and autoregressive conditionally heteroscedastic errors with heavy tails, have been recently introduced. Here, to obtain an h step ahead forecast for these models we use a Monte Carlo approach. The performance of the forecast is evaluated on different nonlinear models comparing some statistical indices with respect to the prediction horizon. As an application of this method, the forecast precision of a 2 year hourly ozone data set coming from an air traffic pollution station located in Bergamo, Italy, is analyzed. Copyright © 2002 John Wiley & Sons, Ltd. [source]

Environmental effects on recruitment and productivity of Japanese sardine Sardinops melanostictus and chub mackerel Scomber japonicus with recommendations for management

Abstract We compared a wide range of environmental data with measures of recruitment and stock production for Japanese sardine Sardinops melanostictus and chub mackerel Scomber japonicus to examine factors potentially responsible for fishery regimes (periods of high or low recruitment and productivity). Environmental factors fall into two groups based on principal component analyses. The first principal component group was determined by the Pacific Decadal Oscillation Index and was dominated by variables associated with the Southern Oscillation Index and Kuroshio Sverdrup transport. The second was led by the Arctic Oscillation and dominated by variables associated with Kuroshio geostrophic transport. Instantaneous surplus production rates (ISPR) and log recruitment residuals (LNRR) changed within several years of environmental regime shifts and then stabilized due, we hypothesize, to rapid changes in carrying capacity and relaxation of density dependent effects. Like ISPR, LNRR appears more useful than fluctuation in commercial catch data for identifying the onset of fishery regime shifts. The extended Ricker models indicate spawning stock biomass and sea surface temperatures (SST) affect recruitment of sardine while spawning stock biomass, SST and sardine biomass affect recruitment of chub mackerel. Environmental conditions were favorable for sardine during 1969,87 and unfavorable during 1951,67 and after 1988. There were apparent shifts from favorable to unfavorable conditions for chub mackerel during 1976,77 and 1985,88, and from unfavorable to favorable during 1969,70 and 1988,92. Environmental effects on recruitment and surplus production are important but fishing effects are also influential. For example, chub mackerel may have shifted into a new favorable fishery regime in 1992 if fishing mortality had been lower. We suggest that managers consider to shift fishing effort in response to the changing stock productivity, and protect strong year classes by which we may detect new favorable regimes. [source]

Local and ecoregion effects on fish assemblage structure in tributaries of the Rio Paraíba do Sul, Brazil

Summary 1.,We examined the effects of physical and chemical habitat variables and ecoregions on species occurrence and fish assemblage structure in streams of the Paraíba do Sul basin, in southeast Brazil. 2.,Fish and environmental data were collected from 42 sites on 26 first to fourth order streams (1 : 50 000 map scale) in three ecoregions. The sites occurred in one valley and two plateau ecoregions at altitudes of 40,1080 m and distances of 0.1,188 km from the main channel of the Rio Paraíba do Sul. Physical habitat (substratum, riparian cover, habitat types) and water quality (dissolved oxygen, pH, temperature and conductivity) variables were measured at each sampling site. 3.,A total of 2684 individuals in 16 families and 59 species were recorded. 4.,Ecoregion was a better predictor of the fish assemblage than the other environmental variables, according to the differences between the mean within-class and mean between-class similarities in assemblage data. 5.,Differing landscape characteristics were associated with differing local variables and thereby with differing fish assemblage structures. Riffles, shrub, grass, dissolved oxygen, conductivity and temperature were closely related to fish assemblage structure. 6.,Fish assemblages in sites far from the main river and at higher altitudes also differed from those near the Paraíba do Sul main channel, presumably as a result of differences in connectivity, covarying environmental factors and anthropogenic influence. 7.,These results reinforce the importance of understanding how stream communities are influenced by processes and patterns operating at local and regional scales, which will aid water resource managers to target those factors in their management and rehabilitation efforts. [source]

Ecological relationships between stream communities and spatial scale: implications for designing catchment-level monitoring programmes

Summary 1. Stream communities are structured by factors acting over multiple spatial and temporal scales. Identifying what factors are driving spatial patterns in stream communities is a central aim of ecology. 2. Here we used two large European data sets of fish, invertebrates, macrophytes, benthic diatoms and environmental data in two stream groups (lowland and mountain) to determine the importance of variables at different spatial scales (geographical, regional, local) on community structure. 3. Both geographical position and ecoregion were selected first in canonical correspondence analysis (CCA), clearly showing the broad spatial gradients covered in the data set. Secondary predictors (after accounting for spatial and/or ecoregion effects) were similar between stream groups and among the four organism groups. In particular, conductivity and N concentration were strong predictors reflecting catchment land use. 4. Using partial CCA, we assessed the individual importance of the three spatial scales on the community structure of the four organism groups in the two stream groups. The majority of among-site variability (22,29%) was accounted for by local scale variables (e.g. water chemistry and substratum type), with regional and spatial variables accounting 11,13% and 5,6%, respectively. Our findings indicate that the four organism groups are responding similarly to the different levels of spatial scale, implying much redundancy which should be consider when implementing studies of bioassessment. [source]

Selecting discriminant function models for predicting the expected richness of aquatic macroinvertebrates

Summary 1. The predictive modelling approach to bioassessment estimates the macroinvertebrate assemblage expected at a stream site if it were in a minimally disturbed reference condition. The difference between expected and observed assemblages then measures the departure of the site from reference condition. 2. Most predictive models employ site classification, followed by discriminant function (DF) modelling, to predict the expected assemblage from a suite of environmental variables. Stepwise DF analysis is normally used to choose a single subset of DF predictor variables with a high accuracy for classifying sites. An alternative is to screen all possible combinations of predictor variables, in order to identify several ,best' subsets that yield good overall performance of the predictive model. 3. We applied best-subsets DF analysis to assemblage and environmental data from 199 reference sites in Oregon, U.S.A. Two sets of 66 best DF models containing between one and 14 predictor variables (that is, having model orders from one to 14) were developed, for five-group and 11-group site classifications. 4. Resubstitution classification accuracy of the DF models increased consistently with model order, but cross-validated classification accuracy did not improve beyond seventh or eighth-order models, suggesting that the larger models were overfitted. 5. Overall predictive model performance at model training sites, measured by the root-mean-squared error of the observed/expected species richness ratio, also improved steadily with DF model order. But high-order DF models usually performed poorly at an independent set of validation sites, another sign of model overfitting. 6. Models selected by stepwise DF analysis showed evidence of overfitting and were outperformed by several of the best-subsets models. 7. The group separation strength of a DF model, as measured by Wilks',, was more strongly correlated with overall predictive model performance at training sites than was DF classification accuracy. 8. Our results suggest improved strategies for developing reliable, parsimonious predictive models. We emphasise the value of independent validation data for obtaining a realistic picture of model performance. We also recommend assessing not just one or two, but several, candidate models based on their overall performance as well as the performance of their DF component. 9. We provide links to our free software for stepwise and best-subsets DF analysis. [source]

Effect of including environmental data in investigations of gene-disease associations in the presence of qualitative interactions

Elizabeth Williamson
Abstract Complex diseases are likely to be caused by the interplay of genetic and environmental factors. Despite this, gene-disease associations are frequently investigated using models that focus solely on a marginal gene effect, ignoring environmental factors entirely. Failing to take into account a gene-environment interaction can weaken the apparent gene-disease association, leading to loss in statistical power and, potentially, inability to identify genuine risk factors. If a gene-environment interaction exists, therefore, a joint analysis allowing the effect of the gene to differ between groups defined by the environmental exposure can have greater statistical power than a marginal gene-disease model. However, environmental data are subject to measurement error. Substantial losses in statistical power for detecting gene-environment interactions can arise from measurement error in the environmental exposure. It is unclear, however, what effect measurement error may have on the power of the joint analysis. We consider the potential benefits, in terms of statistical power, of collecting concurrent environmental data within large cohorts in order to enhance gene detection. We further consider whether these benefits remain in the presence of misclassification in both the gene and the environmental exposure. We find that when an effect of the gene is apparent only in the presence of the environmental exposure, the joint analysis has greater power than a marginal gene-disease analysis. This comparative increase in power remains in the presence of likely levels of misclassification of either the gene or environmental exposure. Genet. Epidemiol. 34:552,560, 2010. © 2010 Wiley-Liss, Inc. [source]

Carbon dioxide balance of a fen ecosystem in northern Finland under elevated UV-B radiation

Abstract The effect of elevated UV-B radiation on CO2 exchange of a natural flark fen was studied in open-field conditions during 2003,2005. The experimental site was located in Sodankylä in northern Finland (67°22,N, 26°38,E, 179 m a.s.l.). Altogether 30 study plots, each 120 cm × 120 cm in size, were randomly distributed between three treatments (n=10): ambient control, UV-A control and UV-B treatment. The UV-B-treated plots were exposed to elevated UV-B radiation level for three growing seasons. The instantaneous net ecosystem CO2 exchange (NEE) and dark respiration (RTOT) were measured during the growing season using a closed chamber method. The wintertime CO2 emissions were estimated using a gradient technique by analyzing the CO2 concentration in the snow pack. In addition to the instantaneous CO2 exchange, the seasonal CO2 balances during the growing seasons were modeled using environmental data measured at the site. In general, the instantaneous NEE at light saturation was slightly higher in the UV-B treatment compared with the ambient control, but the gross photosynthesis was unaffected by the exposure. The RTOT was significantly lower under elevated UV-B in the third study year. The modeled seasonal (June,September) CO2 balance varied between the years depending on the ground water level and temperature conditions. During the driest year, the seasonal CO2 balance was negative (net release of CO2) in the ambient control and the UV-B treatment was CO2 neutral. During the third year, the seasonal CO2 uptake was 43±36 g CO2 -C m,2 in the ambient control and 79±45 g CO2 -C m,2 in the UV-B treatment. The results suggest that the long-term exposure to high UV-B radiation levels may slightly increase the CO2 accumulation to fens resulting from a decrease in microbial activity in peat. However, it is unlikely that the predicted development of the level of UV-B radiation would significantly affect the CO2 balance of fen ecosystems in future. [source]

Environmental change and the phenology of European aphids

Abstract Aphids, because of their short generation time and low developmental threshold temperatures, are an insect group expected to respond particularly strongly to environmental changes. Forty years of standardized, daily data on the abundance of flying aphids have been brought together from countries throughout Europe, through the EU Thematic Network ,EXAMINE'. Relationships between phenology, represented by date of first appearance in a year in a suction trap, of 29 aphid species and environmental data have been quantified using the residual maximum likelihood (REML) methodology. These relationships have been used with climate change scenario data to suggest plausible changes in aphid phenology. In general, the date of first record of aphid species in suction traps is expected to advance, the rate of advance varying with location and species, but averaging 8 days over the next 50 years. Strong relationships between aphid phenology and environmental variables have been found for many species, but they are notably weaker in species living all year on trees. Canonical variate analysis and principal coordinate analysis were used to determine ordinations of the 29 species on the basis of the presence/absence of explanatory variables in the REML models. There was strong discrimination between species with different life cycle strategies and between species feeding on herbs and trees, suggesting the possible value of trait-based groupings in predicting responses to environmental changes. [source]

Mental health in infants with esophageal atresia,

Anne Faugli
Chronic somatic illness in infancy may challenge the development of mental health and impinge the infant's capability to form close interpersonal relationships. Esophageal atresia (EA) is a congenital anomaly requiring neonatal surgery, medical aftertreatment, and extended hospitalization. The aim of the study was to assess mental health and to find prognostic factors for mental health among infants with EA. Thirty-nine infants treated consecutively during 2000 to 2003 and their mothers were included. Infant mental health was assessed by Diagnostic Classification: 0,3 (Zero to Three, 1994). Medical and environmental data were collected from medical records and semistructured interview with the mothers. Child development was assessed with the Bayley scales, second edition (N. Bayley, 1993). Maternal psychological distress, anxiety, and child temperament were assessed by self-report questionnaires: the General Health Questionnaire, 30-item version (D. Goldberg & P. Williams, 1988); the State Trait Anxiety Inventory (C.D. Spielberger, R. Gorsuch, & R. Lushene, 1970); and the Infant Behaviour Questionnaire (M.K. Rothbart, 1981). Thirty-one percent of the infants with EA showed mental health disorders by 1 year of age. Prognostic factors predicting mental health were posttraumatic symptoms reported by mother, more than one operation, mechanical ventilation beyond 1 day, and moderate/severe chronic family strain. Relational trauma, vulnerable attachment, and impaired self-development are highlighted as possible pathways for psychopathology. Children with EA are vulnerable to mental health disorders, and this study may help clinicians to identify children at risk. [source]

Surveys of rodent-borne disease in Thailand with a focus on scrub typhus assessment

Kriangkrai Lerdthusnee
Abstract The epidemiology of many rodent-borne diseases in South-East Asia remains ill-defined. Scrub typhus and lep-tospirosis are common and medically significant, while other zoonotic diseases, such as spotted fever group Rickettsiae have been identified, but their overall medical significance is unknown. Rodent surveillance was conducted from June 2002 to July 2004 in 18 provinces from Thailand. Traps were set up for one to three nights. Blood and serum samples and animal tissue samples (liver, spleen, kidney and urinary bladder) were collected. Chiggermites, ticks and fleas were removed from captured rodents. A total of 4536 wild-caught rodents from 27 species were captured over two years of animal trapping. Rattus rattus was the dominant species, followed by Rattus exulans and Bandicota indica. Almost 43 000 ectoparasites were removed from the captured animals. Approximately 98% of the ectoparasites were chigger-mites, of which 46% belonged to the genus Leptotrombidium (scrub typhus vector). Other genera included Schoengastia and Blankaartia. Tick and flea specimens together comprised less than 1% of the sample. Among the five species of ticks collected, Haemaphysalis bandicota was the predominant species caught, followed by Ixodes granulatus other Haemaphysalis spp., Rhipicephalus spp. and Dermacentor spp. Only two species of fleas were collected and Xenopsylla cheopis (rat flea) was the predominant species. Using both commercial diagnostic kits and in-house molecular assays, animal tissue samples were examined and screened for zoonotic diseases. Seven zoonotic diseases were detected: scrub typhus, leptospirosis, murine typhus, tick typhus, bartonella, babesiosis and trypanosomiasis. Most samples were positive for scrub typhus. Other zoonotic diseases still under investigation include borrelosis, ehrlichiosis, the plague, and other rickettsial diseases. Using geographic information systems, global positioning systems and remote sensing technology, epidemiological and environmental data were combined to assess the relative risk in different biotopes within highly endemic areas of scrub typhus in Thailand. [source]

The ED strategy: how species-level surrogates indicate general biodiversity patterns through an ,environmental diversity' perspective

D. P. Faith
Abstract Biodiversity assessment requires that we use surrogate information in practice to indicate more general biodiversity patterns. ,ED' refers to a surrogates framework that can link species data and environmental information based on a robust relationship of compositional dissimilarities to ordinations that indicate underlying environmental variation. In an example analysis of species and environmental data from Panama, the environmental and spatial variables that correlate with an hybrid multi-dimensional scaling ordination were able to explain 83% of the variation in the corresponding Bray Curtis dissimilarities. The assumptions of ED also provide the rationale for its use of p-median optimization criteria to measure biodiversity patterns among sites in a region. M.B. Araújo, P.J. Densham & P.H. Williams (2004, Journal of Biogeography31, 1) have re-named ED as ,AD' in their evaluation of the surrogacy value of ED based on European species data. Because lessons from previous work on ED options consequently may have been neglected, we use a corroboration framework to investigate the evidence and ,background knowledge' presented in their evaluations of ED. Investigations focus on the possibility that their weak corroboration of ED surrogacy (non-significance of target species recovery relative to a null model) may be a consequence of Araújo et al.'s use of particular evidence and randomizations. We illustrate how their use of discrete ED, and not the recommended continuous ED, may have produced unnecessarily poor species recovery values. Further, possible poor optimization of their MDS ordinations, due to small numbers of simulations and/or low resolution of stress values appears to have provided a possible poor basis for ED application and, consequently, may have unnecessarily favoured non-corroboration results. Consideration of Araújo et al.'s randomizations suggests that acknowledged sampling biases in the European data have not only artefactually promoted the non-significance of ED recovery values, but also artefactually elevated the significance of competing species surrogates recovery values. We conclude that little credence should be given to the comparisons of ED and species-based complementarity sets presented in M.B. Araújo, P.J. Densham & P.H. Williams (2004, Journal of Biogeography31, 1), unless the factors outlined here can be analysed for their effects on results. We discuss the lessons concerning surrogates evaluation emerging from our investigations, calling for better provision in such studies of the background information that can allow (i) critical examination of evidence (both at the initial corroboration and re-evaluation stages), and (ii) greater synthesis of lessons about the pitfalls of different forms of evidence in different contexts. [source]

Explaining bird species composition and richness in eucalypt-dominated remnants in subhumid Tasmania

Michael A. MacDonald
Abstract Aim To determine the factors influencing the distribution of birds in remnants in a fragmented agricultural landscape. Location Forty-seven eucalypt remnants and six sites in continuous forest in the subhumid Midlands region of Tasmania, Australia. Methods Sites were censused over a two-year period, and environmental data were collected for remnants. The avifauna of the sites was classified and ordinated. The abundances of bird species, and bird species composition, richness, abundance and diversity were related to environmental variables, using simple correlation and modelling. Results There were two distinct groups of sample sites, which sharply differed in species composition, richness, diversity and bird abundance, separated on the presence/absence of noisy miner (Manorina melanocephala Latham) colonies, remnant size, vegetation structural attributes and variables that reflected disturbance history. The approximate remnant size threshold for the change from one group to another was 20,30 ha. Remnant species richness and diversity were most strongly explained by remnant area and noisy miner abundance, with contributions from structural and isolation attributes in the second case. Segment richness was explained by precipitation, logging history and noisy miner abundance. Bird abundance was positively related to precipitation and negatively related to tree dieback. The 28 individual bird species models were highly individualistic, with vegetation structural variables, noisy miner abundance, climatic variables, variables related to isolation, area, variables related to floristics, disturbance variables, the nature of the matrix and remnant shape all being components in declining order of incidence. Age of the remnant did not relate to any of the dependent variables. Main conclusions Degraded and small remnants may have become more distinct in their avifaunal characteristics than might otherwise be the case, as a result of the establishment of colonies of an aggressive native bird, the noisy miner. The area, isolation and shape of remnants directly relate to the abundance of relatively few species, compared to vegetation attributes, climate and the abundance of the noisy miner. The nature of the matrix is important in the response of some species to fragmentation. [source]

Moist lower montane rainforest classification: a case study from Bwindi Impenetrable National Park, Uganda

Tomas Chaigneau
Abstract Moist lower montane vegetation has rarely been classified beyond broad zonational belts over large altitudinal ranges due to highly diverse species composition and structure. This study shows it is possible to further classify such forest types within Bwindi-Impenetrable National Park (BINP), and that these assemblages can be explained by a combination of environmental conditions and past management. Botanical and environmental data were collected along some 4000 m of linear transects from the area surrounding Mubwindi Swamp, BINP. Ordination using Nonmetric Multidimensional Scaling (NMDS) and classification using Two-way Indicator Species Analysis (TWINSPAN) successfully identified four different species assemblages. These forest types were then named on the basis of the ecological characteristics of the species within the group, and the environmental conditions influencing the distribution and past disturbance of the forest. The techniques used were in agreement for three out of the four forest types identified. Analysis using an environmental overlay showed a significant association between forest type and altitude. The results of this study indicate that a regional classification of forest types within moist lower montane forest belt using only tree species is possible, and that the forest types identified can be explained by environmental conditions and past management. Résumé La végétation humide de basse montagne a rarement été classée au-delà de larges ceintures de zonage portant sur des étendues de grandes amplitudes altitudinales, en raison de compositions et de structures d'espèces extrêmement diverses. Cette étude montre qu'il est possible de classer plus précisément de tels types forestiers dans le Parc National de la Forêt Impénétrable de Bwindi (BINP), et que l'on peut expliquer ces assemblages par une combinaison de conditions environnementales et de gestion passée. Des données botaniques et environnementales ont été collectées le long de quelque 4,000 m de transects linéaires à partir de la zone entourant le Marais de Mubwindi, au BINP. L'ordination par la Gradation non métrique multidimensionnelle et la classification utilisant l'Analyse TWINSPAN (Two-way Indicator Species Analysis) ont réussi à identifier quatre assemblages d'espèces différents. Ces types forestiers furent alors nommés en se basant sur les caractéristiques écologiques des espèces au sein du groupe ainsi que sur les conditions environnementales qui influencent la distribution et des perturbations anciennes des forêts. Les techniques utilisées se sont montrées cohérentes pour trois des quatre types de forêt identifiés. L'analyse utilisant une superposition environnementale a révélé une association significative entre type forestier et altitude. Les résultats de cette étude indiquent qu'une classification régionale des types forestiers dans la ceinture forestière humide qui entoure la basse montagne est possible en n'utilisant que trois espèces d'arbres, et que les types forestiers identifiés peuvent s'expliquer par les conditions environnementales et par la gestion antérieure. [source]

Bayesian approaches in evolutionary quantitative genetics

Abstract The study of evolutionary quantitative genetics has been advanced by the use of methods developed in animal and plant breeding. These methods have proved to be very useful, but they have some shortcomings when used in the study of wild populations and evolutionary questions. Problems arise from the small size of data sets typical of evolutionary studies, and the additional complexity of the questions asked by evolutionary biologists. Here, we advocate the use of Bayesian methods to overcome these and related problems. Bayesian methods naturally allow errors in parameter estimates to propagate through a model and can also be written as a graphical model, giving them an inherent flexibility. As packages for fitting Bayesian animal models are developed, we expect the application of Bayesian methods to evolutionary quantitative genetics to grow, particularly as genomic information becomes more and more associated with environmental data. [source]

Effects of a tropical cyclone on the distribution of hatchery-reared black-spot tuskfish Choerodon schoenleinii determined by acoustic telemetry

Y. Kawabata
The effects of a tropical cyclone on the distribution of hatchery-reared black-spot tuskfish Choerodon schoenleinii were examined using acoustic telemetry. Nine fish were released in Urasoko Bay, Ishigaki Island, Japan, in September 2006, and another nine were released in June to July 2007, before a cyclone's passing through the area in September 2007. Data for the fish released in 2006 were used as the cyclone-inexperienced group to compare their distribution pattern to that of the 2007 cyclone-experienced group. Both groups of fish were monitored for up to 150 days. Of the nine fish in each group, four (44%) and two (22%) were monitored for over 150 days in the cyclone-inexperienced and the cyclone-experienced groups, respectively. Three of the five fish that had settled in the monitoring area left the area within a few days of the cyclone event. To estimate the time of disappearance of the fish, maximum wind speed during a period of 7 days (indicating the occurrence and intensity of the tropical cyclone), fish size and release year were evaluated as explanatory variables using a Cox proportional hazards model with Akaike's information criterion. The best predictive model included the effect of maximum wind speed. One fish that left the monitoring area displayed movement patterns related to strong winds, suggesting that wind-associated strong currents swept the fish away. No relationships were found between the movement patterns of the other two fish and any physical environmental data. The daily detection periods of one of the two fish gradually decreased after the cyclone hit, and this fish eventually left the monitoring area within 3 days, suggesting that it shifted to a habitat outside the monitoring area. These results indicate that tropical cyclones have both direct and indirect effects on the distribution of hatchery-reared C. schoenleinii. [source]