Accuracy of plant assemblage predictions from species distribution models varies along environmental gradients

Aim: Climatic niche modelling of species and community distributions implicitly assumes strong and constant climatic determinism across geographic space. This assumption had however never been tested so far. We tested it by assessing how stacked-species distribution models (S-SDMs) perform for predicting plant species assemblages along elevation. Location: Western Swiss Alps. Methods: Using robust presence-absence data, we first assessed the ability of topo-climatic S-SDMs to predict plant assemblages in a study area encompassing a 2800 m wide elevation gradient. We then assessed the relationships among several evaluation metrics and trait-based tests of community assembly rules. Results: The standard errors of individual SDMs decreased significantly towards higher elevations. Overall, the S-SDM overpredicted far more than they underpredicted richness and could not reproduce the humpback curve along elevation. Overprediction was greater at low and mid-range elevations in absolute values but greater at high elevations when standardised by the actual richness. Looking at species composition, the evaluation metrics accounting for both the presence and absence of species (overall prediction success and kappa) or focusing on correctly predicted absences (specificity) increased with increasing elevation, while the metrics focusing on correctly predicted presences (Jaccard index and sensitivity) decreased. The best overall evaluation - as driven by specificity - occurred at high elevation where species assemblages were shown to be under significant environmental filtering of small plants. In contrast, the decreased overall accuracy in the lowlands was associated with functional patterns representing any type of assembly rule (environmental filtering, limiting similarity or null assembly). Main Conclusions: Our study reveals interesting patterns of change in S-SDM errors with changes in assembly rules along elevation. Yet, significant levels of assemblage prediction errors occurred throughout the gradient, calling for further improvement of SDMs, e.g., by adding key environmental filters that act at fine scales and developing approaches to account for variations in the influence of predictors along environmental gradients.

06014-007 Lower Coldwater-Palmer Creek Watershed Final Report

Lower Coldwater and Palmer Creeks in Butler and Floyd counties are subwatersheds of the Cedar River, which provides drinking water to Cedar Rapids, IA. The increasing concentration of nitrate+nitrate in the river is of concern to the Cedar Rapids water utility, and IDNR snapshot monitoring shows Coldwater and Palmer to be significant potential sources (above the 90th percentile for subwatersheds monitored). Both creeks are also on the Iowa Section 303(d) list of impaired waters (aquatic life). Citizens of these predominantly agricultural watersheds organized the Coldwater-Palmer Watershed Improvement Association to deal proactively with nonpoint source pollutants from crop and livestock operations through a performance-based environmental management program. The locally-adapted program implemented by the Coldwater-Palmer watershed council rewards participants for environmental accomplishments - soil quality improvement and nutrient source reduction as measured by accepted, scientifically-based tests and models. Most of the locally­appropriate BMPs used to improve performance are undertaken voluntarily at participants' initiative. WIRB funds will be combined with funding from the Iowa Com Growers Association and significant in-kind support from the Cedar River Watershed Monitoring Coalition, Iowa State University Extension and other partners. The project will result in sustainable reduction in nutrient loading achieved with voluntary participation of a majority of watershed farm operators.

Diagnostic and prognostic value of antibodies against chimeric fibrin/filaggrin citrullinated synthetic peptides in rheumatoid arthritis

Introduction: Evidence suggests that citrullinated fibrin(ogen) may be a potential in vivo target of anticitrullinated protein/peptide antibodies (ACPA) in rheumatoid arthritis (RA). We compared the diagnostic yield of three enzyme-linked immunosorbent assay (ELISA) tests by using chimeric fibrin/filaggrin citrullinated synthetic peptides (CFFCP1, CFFCP2, CFFCP3) with a commercial CCP2-based test in RA and analyzed their prognostic values in early RA. Methods: Samples from 307 blood donors and patients with RA (322), psoriatic arthritis (133), systemic lupus erythematosus (119), and hepatitis C infection (84) were assayed by using CFFCP- and CCP2-based tests. Autoantibodies also were analyzed at baseline and during a 2-year follow-up in 98 early RA patients to determine their prognostic value. Results: With cutoffs giving 98% specificity for RA versus blood donors, the sensitivity was 72.1% for CFFCP1, 78.0% for CFFCP2, 71.4% for CFFCP3, and 73.9% for CCP2, with positive predictive values greater than 97% in all cases. CFFCP sensitivity in RA increased to 80.4% without losing specificity when positivity was considered as any positive anti-CFFCP status. Specificity of the three CFFCP tests versus other rheumatic populations was high (> 90%) and similar to those for the CCP2. In early RA, CFFCP1 best identified patients with a poor radiographic outcome. Radiographic progression was faster in the small subgroup of CCP2-negative and CFFCP1-positive patients than in those negative for both autoantibodies. CFFCP antibodies decreased after 1 year, but without any correlation with changes in disease activity. Conclusions: CFFCP-based assays are highly sensitive and specific for RA. Early RA patients with anti-CFFCP1 antibodies, including CCP2-negative patients, show greater radiographic progression.

Divergent and narrower climatic niches characterize polyploid species of European primroses in Primula sect. Aleuritia

Aim It is hypothesized that the ecological niches of polyploids should be both distinct and broader than those of diploids - characteristics that might have allowed the successful colonization of open habitats by polyploids during the Pleistocene glacial cycles. Here, we test these hypotheses by quantifying and comparing the ecological niches and niche breadths of a group of European primroses. Location Europe. Methods We gathered georeferenced data of four related species in Primula sect. Aleuritia at different ploidy levels (diploid, tetraploid, hexaploid and octoploid) and used seven bioclimatic variables to quantify niche overlap between species by applying a series of univariate and multivariate analyses combined with modelling techniques. We also employed permutation-based tests to evaluate niche similarity between the four species. Niche breadth for each species was evaluated both in the multivariate environmental space and in geographical space. Results The four species differed significantly from each other in mono-dimensional comparisons of climatological variables and occupied distinct habitats in the multi-dimensional environmental space. The majority of the permutation-based tests either indicated that the four species differed significantly in their habitat preferences and ecological niches or did not support significant niche similarity. Furthermore, our results revealed narrower niche breadths and geographical ranges in species of P. sect. Aleuritia at higher ploidy levels. Main conclusions The detected ecological differentiation between the four species of P. sect. Aleuritia at different ploidy levels is consistent with the hypothesis that polyploids occupy distinct ecological niches that differ from those of their diploid relative. Contrary to expectations, we find that polyploid species of P. sect. Aleuritia occupy narrower environmental and geographical spaces than their diploid relative. These results on the ecological niches of closely related polyploid and diploid species highlight factors that potentially contribute to the evolution and distribution of polyploid species.

A multi-contrast MRI study of microstructural brain damage in patients with mild cognitive impairment.

OBJECTIVES: The aim of this study was to investigate pathological mechanisms underlying brain tissue alterations in mild cognitive impairment (MCI) using multi-contrast 3 T magnetic resonance imaging (MRI). METHODS: Forty-two MCI patients and 77 healthy controls (HC) underwent T1/T2* relaxometry as well as Magnetization Transfer (MT) MRI. Between-groups comparisons in MRI metrics were performed using permutation-based tests. Using MRI data, a generalized linear model (GLM) was computed to predict clinical performance and a support-vector machine (SVM) classification was used to classify MCI and HC subjects. RESULTS: Multi-parametric MRI data showed microstructural brain alterations in MCI patients vs HC that might be interpreted as: (i) a broad loss of myelin/cellular proteins and tissue microstructure in the hippocampus (p ≤ 0.01) and global white matter (p < 0.05); and (ii) iron accumulation in the pallidus nucleus (p ≤ 0.05). MRI metrics accurately predicted memory and executive performances in patients (p ≤ 0.005). SVM classification reached an accuracy of 75% to separate MCI and HC, and performed best using both volumes and T1/T2*/MT metrics. CONCLUSION: Multi-contrast MRI appears to be a promising approach to infer pathophysiological mechanisms leading to brain tissue alterations in MCI. Likewise, parametric MRI data provide powerful correlates of cognitive deficits and improve automatic disease classification based on morphometric features.

Diagnostic and prognostic value of antibodies against chimeric fibrin/filaggrin citrullinated synthetic peptides in rheumatoid arthritis

Introduction: Evidence suggests that citrullinated fibrin(ogen) may be a potential in vivo target of anticitrullinated protein/peptide antibodies (ACPA) in rheumatoid arthritis (RA). We compared the diagnostic yield of three enzyme-linked immunosorbent assay (ELISA) tests by using chimeric fibrin/filaggrin citrullinated synthetic peptides (CFFCP1, CFFCP2, CFFCP3) with a commercial CCP2-based test in RA and analyzed their prognostic values in early RA. Methods: Samples from 307 blood donors and patients with RA (322), psoriatic arthritis (133), systemic lupus erythematosus (119), and hepatitis C infection (84) were assayed by using CFFCP- and CCP2-based tests. Autoantibodies also were analyzed at baseline and during a 2-year follow-up in 98 early RA patients to determine their prognostic value. Results: With cutoffs giving 98% specificity for RA versus blood donors, the sensitivity was 72.1% for CFFCP1, 78.0% for CFFCP2, 71.4% for CFFCP3, and 73.9% for CCP2, with positive predictive values greater than 97% in all cases. CFFCP sensitivity in RA increased to 80.4% without losing specificity when positivity was considered as any positive anti-CFFCP status. Specificity of the three CFFCP tests versus other rheumatic populations was high (> 90%) and similar to those for the CCP2. In early RA, CFFCP1 best identified patients with a poor radiographic outcome. Radiographic progression was faster in the small subgroup of CCP2-negative and CFFCP1-positive patients than in those negative for both autoantibodies. CFFCP antibodies decreased after 1 year, but without any correlation with changes in disease activity. Conclusions: CFFCP-based assays are highly sensitive and specific for RA. Early RA patients with anti-CFFCP1 antibodies, including CCP2-negative patients, show greater radiographic progression.

N-terminal amino acids of bovine alpha interferons are relevant for the neutralization of their antiviral activity

The structure-function relationship of interferons (IFNs) has been studied by epitope mapping. Epitopes of bovine IFNs, however, are practically unknown, despite their importance in virus infections and in the maternal recognition of pregnancy. It has been shown that recombinant bovine (rBo)IFN-alphaC and rBoIFN-alpha1 differ only in 12 amino acids and that the F12 monoclonal antibody (mAb) binds to a linear sequence of residues 10 to 34. We show here that the antiviral activities of these two IFNs were neutralized by the F12 mAb to different extents using two tests. In residual activity tests the antiviral activity dropped by more than 99% with rBoIFN-alphaC and by 84% with rBoIFN-alpha1. In checkerboard antibody titrations, the F12 mAb titer was 12,000 with rBoIFN-alphaC and only 600 with rBoIFN-alpha1. Since these IFNs differ in their amino acid sequence at positions 11, 16 and 19 of the amino terminus, only these amino acids could account for the different neutralization titers, and they should participate in antibody binding. According to the three-dimensional structure described for human and murine IFNs, these amino acids are located in the alpha helix A; amino acids 16 and 19 of the bovine IFNs would be expected to be exposed and could bind to the antibody directly. The amino acid at position 11 forms a hydrogen bond in human IFNs-alpha and it is possible that, in bovine IFNs-alpha, the F12 mAb, binding near position 11, would disturb this hydrogen bond, resulting in the difference in the extent of neutralization observed.

Potential Urinary miRNA Biomarker Candidates for the Accurate Detection of Prostate Cancer among Benign Prostatic Hyperplasia Patients

MicroRNAs (miRNAs) are a class of short (similar to 22nt), single stranded RNA molecules that function as post-transcriptional regulators of gene expression. MiRNAs can regulate a variety of important biological pathways, including: cellular proliferation, differentiation and apoptosis. Profiling of miRNA expression patterns was shown to be more useful than the equivalent mRNA profiles for characterizing poorly differentiated tumours. As such, miRNA expression "signatures" are expected to offer serious potential for diagnosing and prognosing cancers of any provenance. The aim of this study was to investigate the potential of using deregulation of urinary miRNAs in order to detect Prostate Cancer (PCa) among Benign Prostatic Hyperplasia (BPH). To identify the miRNA signatures specific for PCa, miRNA expression profiling of 8 PCa patients, 12 BPH patients and 10 healthy males was carried out using whole genome expression profiling. Differential expression of two individual miRNAs between healthy males and BPH patients was detected and found to possibly target genes related to PCa development and progression. The sensitivity and specificity of miR-1825 for detecting PCa among BPH individuals was found to be 60% and 69%, respectively. Whereas, the sensitivity and specificity of miR-484 were 80% and 19%, respectively. Additionally, the sensitivity and specificity for miR-1825/484 in tandem were 45% and 75%, respectively. The proposed PCa miRNA signatures may therefore be of great value for the accurate diagnosis of PCa and BPH. This exploratory study has identified several possible targets that merit further investigation towards the development and validation of diagnostically useful, non-invasive, urine-based tests that might not only help diagnose PCa but also possibly help differentiate it from BPH.

Bootstrapping Autoregressions with Conditional Heteroskedasticity of Unknown Form

Conditional heteroskedasticity is an important feature of many macroeconomic and financial time series. Standard residual-based bootstrap procedures for dynamic regression models treat the regression error as i.i.d. These procedures are invalid in the presence of conditional heteroskedasticity. We establish the asymptotic validity of three easy-to-implement alternative bootstrap proposals for stationary autoregressive processes with m.d.s. errors subject to possible conditional heteroskedasticity of unknown form. These proposals are the fixed-design wild bootstrap, the recursive-design wild bootstrap and the pairwise bootstrap. In a simulation study all three procedures tend to be more accurate in small samples than the conventional large-sample approximation based on robust standard errors. In contrast, standard residual-based bootstrap methods for models with i.i.d. errors may be very inaccurate if the i.i.d. assumption is violated. We conclude that in many empirical applications the proposed robust bootstrap procedures should routinely replace conventional bootstrap procedures for autoregressions based on the i.i.d. error assumption.

Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models

In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR) with applications to asset pricing models. We focus on departures from the assumption of i.i.d. errors assumption, at univariate and multivariate levels, with Gaussian and non-Gaussian (including Student t) errors. The univariate tests studied extend existing exact procedures by allowing for unspecified parameters in the error distributions (e.g., the degrees of freedom in the case of the Student t distribution). The multivariate tests are based on properly standardized multivariate residuals to ensure invariance to MLR coefficients and error covariances. We consider tests for serial correlation, tests for multivariate GARCH and sign-type tests against general dependencies and asymmetries. The procedures proposed provide exact versions of those applied in Shanken (1990) which consist in combining univariate specification tests. Specifically, we combine tests across equations using the MC test procedure to avoid Bonferroni-type bounds. Since non-Gaussian based tests are not pivotal, we apply the “maximized MC” (MMC) test method [Dufour (2002)], where the MC p-value for the tested hypothesis (which depends on nuisance parameters) is maximized (with respect to these nuisance parameters) to control the test’s significance level. The tests proposed are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995. Our empirical results reveal the following. Whereas univariate exact tests indicate significant serial correlation, asymmetries and GARCH in some equations, such effects are much less prevalent once error cross-equation covariances are accounted for. In addition, significant departures from the i.i.d. hypothesis are less evident once we allow for non-Gaussian errors.

News from compositions, the R package

The R-package “compositions”is a tool for advanced compositional analysis. Its basic functionality has seen some conceptual improvement, containing now some facilities to work with and represent ilr bases built from balances, and an elaborated subsys- tem for dealing with several kinds of irregular data: (rounded or structural) zeroes, incomplete observations and outliers. The general approach to these irregularities is based on subcompositions: for an irregular datum, one can distinguish a “regular” sub- composition (where all parts are actually observed and the datum behaves typically) and a “problematic” subcomposition (with those unobserved, zero or rounded parts, or else where the datum shows an erratic or atypical behaviour). Systematic classification schemes are proposed for both outliers and missing values (including zeros) focusing on the nature of irregularities in the datum subcomposition(s). To compute statistics with values missing at random and structural zeros, a projection approach is implemented: a given datum contributes to the estimation of the desired parameters only on the subcompositon where it was observed. For data sets with values below the detection limit, two different approaches are provided: the well-known imputation technique, and also the projection approach. To compute statistics in the presence of outliers, robust statistics are adapted to the characteristics of compositional data, based on the minimum covariance determinant approach. The outlier classification is based on four different models of outlier occur- rence and Monte-Carlo-based tests for their characterization. Furthermore the package provides special plots helping to understand the nature of outliers in the dataset. Keywords: coda-dendrogram, lost values, MAR, missing data, MCD estimator, robustness, rounded zeros

Valor en riesgo del portafolio de TES de los bancos colombianos

En este trabajo se realiza la medición del riesgo de mercado para el portafolio de TES de un banco colombiano determinado, abordando el pronóstico de valor en riesgo (VaR) mediante diferentes modelos multivariados de volatilidad: EWMA, GARCH ortogonal, GARCH robusto, así como distintos modelos de VaR con distribución normal y distribución t-student, evaluando su eficiencia con las metodologías de backtesting propuestas por Candelon et al. (2011) con base en el método generalizado de momentos, junto con los test de independencia y de cobertura condicional planteados por Christoffersen y Pelletier (2004) y por Berkowitz, Christoffersen y Pelletier (2010). Los resultados obtenidos demuestran que la mejor especificación del VaR para la medición del riesgo de mercado del portafolio de TES de los bancos colombianos, es el construido a partir de volatilidades EWMA y basado en la distribución normal, ya que satisface las hipótesis de cobertura no condicional, independencia y cobertura condicional, al igual que los requerimientos estipulados en Basilea II y en la normativa vigente en Colombia.

The role of biotic and abiotic factors in evolution of ant dispersal in the milkwort family (Polygalaceae)

A phylogenetic approach was taken to investigate the evolutionary history of seed appendages in the plant family Polygalaceae (Fabales) and determine which factors might be associated with evolution of elaiosomes through comparisons to abiotic (climate) and biotic (ant species number and abundance) timelines. Molecular datasets from three plastid regions representing 160 species were used to reconstruct a phylogenetic tree of the order Fabales, focusing on Polygalaceae. Bayesian dating methods were used to estimate the age of the appearance of ant-dispersed elaiosomes in Polygalaceae, shown by likelihood optimizations to have a single origin in the family. Topology-based tests indicated a diversification rate shift associated with appearance of caruncular elaiosomes. We show that evolution of the caruncular elaiosome type currently associated with ant dispersal occurred 54.0-50.5 million year ago. This is long after an estimated increase in ant lineages in the Late Cretaceous based on molecular studies, but broadly concomitant with increasing global temperatures culminating in the Late Paleocene-Early Eocene thermal maxima. These results suggest that although most major ant clades were present when elaiosomes appeared, the environmental significance of elaiosomes may have been an important factor in success of elaiosome-bearing lineages. Ecological abundance of ants is perhaps more important than lineage numbers in determining significance of ant dispersal. Thus, our observation that elaiosomes predate increased ecological abundance of ants inferred from amber deposits could be indicative of an initial abiotic environmental function.

Ventilation rates in schools

Research shows that poor indoor air quality in school buildings can cause a reduction in the students' performance assessed by short term computer based tests; whereas good air quality in classrooms can enhance children's concentration and also teachers' productivity. Investigation of air quality in classrooms helps us to characterise pollutant levels and implement corrective measures. Outdoor pollution, ventilation equipment, furnishings, and human activities affect indoor air quality. In school classrooms the occupancy density is high (1.8 to 2.4 m(2)/person) compared to offices (10 m(2) /person). Ventilation systems expend energy and there is a trend to save energy by reducing ventilation rates. We need to establish the minimum acceptable level of fresh air required for the health of the occupants. This paper describes a project which will aim to investigate the effect of indoor air quality and ventilation rates on pupils' performance and health using psychological tests. The aim is to recommend suitable ventilation rates for classrooms and examine the suitability of the air quality guidelines for classrooms.

Ventilation rates in schools

Research shows that poor indoor air quality (IAQ) in school buildings can cause a reduction in the students' performance assessed by short-term computer-based tests: whereas good air quality in classrooms can enhance children's concentration and also teachers' productivity. Investigation of air quality in classrooms helps us to characterise pollutant levels and implement corrective measures. Outdoor pollution, ventilation equipment, furnishings, and human activities affect IAQ. In school classrooms, the occupancy density is high (1.8-2.4m(2)/person) compared to offices (10 m(2)/person). Ventilation systems expend energy and there is a trend to save energy by reducing ventilation rates. We need to establish the minimum acceptable level of fresh air required for the health of the occupants. This paper describes a project, which will aim to investigate the effect of IAQ and ventilation rates on pupils' performance and health using psychological tests. The aim is to recommend suitable ventilation rates for classrooms and examine the suitability of the air quality guidelines for classrooms. The air quality, ventilation rates and pupils' performance in classrooms will be evaluated in parallel measurements. In addition, Visual Analogue Scales will be used to assess subjective perception of the classroom environment and SBS symptoms. Pupil performance will be measured with Computerised Assessment Tests (CAT), and Pen and Paper Performance Tasks while physical parameters of the classroom environment will be recorded using an advanced data logging system. A total number of 20 primary schools in the Reading area are expected to participate in the present investigation, and the pupils participating in this study will be within the age group of 9-11 years. On completion of the project, based oil the overall data recommendations for suitable ventilation rates for schools will be formulated. (C) 2006 Elsevier Ltd. All rights reserved.