Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Bioclimatic constraints to Andean cat distribution: a modelling application for rare species

AimTo identify the bioclimatic niche of the endangered Andean cat (Leopardus jacobita), one of the rarest and least known felids in the world, by developing a species distribution model.LocationSouth America, High Andes and Patagonian steppe. Peru, Bolivia, Chile, Argentina.MethodsWe used 108 Andean cat records to build the models, and 27 to test them, applying the Maxent algorithm to sets of uncorrelated bioclimatic variables from global databases, including elevation. We based our biogeographical interpretations on the examination of the predicted geographic range, the modelled response curves and latitudinal variations in climatic variables associated with the locality data.ResultsSimple bioclimatic models for Andean cats were highly predictive with only 3-4 explanatory variables. The climatic niche of the species was defined by extreme diurnal variations in temperature, cold minimum and moderate maximum temperatures, and aridity, characteristic not only of the Andean highlands but also of the Patagonian steppe. Argentina had the highest representation of suitable climates, and Chile the lowest. The most favourable conditions were centrally located and spanned across international boundaries. Discontinuities in suitable climatic conditions coincided with three biogeographical barriers associated with climatic or topographic transitions.Main conclusionsSimple bioclimatic models can produce useful predictions of suitable climatic conditions for rare species, including major biogeographical constraints. In our study case, these constraints are also known to affect the distribution of other Andean species and the genetic structure of Andean cat populations. We recommend surveys of areas with suitable climates and no Andean cat records, including the corridor connecting two core populations. The inclusion of landscape variables at finer scales, crucially the distribution of Andean cat prey, would contribute to refine our predictions for conservation applications.

Modelling the effect of minor orthopaedic day surgery on patient mood at the early post-operative period: a prospective population-based cohort study.

OBJECTIVE: The effect of minor orthopaedic day surgery (MiODS) on patient's mood. METHODS: A prospective population-based cohort study of 148 consecutive patients with age above 18 and less than 65, an American Society of Anaesthesiology (ASA) score of 1, and the requirement of general anaesthesia (GA) were included. The Medical Outcomes Study - Short Form 36 (SF-36), Beck Anxiety Inventory (BAI) and Beck Depression Inventory (BDI) were used pre- and post-operatively. RESULTS: The mean physical component score of SF-36 before surgery was 45.3 (SD=+/-10.1) and 8 weeks following surgery was 44.9 (SD=+/-11.04) [n=148, p=0.51, 95% CI=(-1.03 to 1.52)]. For the measurement of the changes in mood using BDI, BAI and SF-36, latent construct modelling was employed to increase validity. The covariance between mood pre- and post-operatively (cov=69.44) corresponded to a correlation coefficient, r=0.88 indicating that patients suffering a greater number of mood symptoms before surgery continue to have a greater number of symptoms following surgery. When the latent mood constructs were permitted to have different means the model fitted well with chi(2) (df=1)=0.86 for which p=0.77, thus the null hypothesis that MiODS has no effect on patient mood was rejected. CONCLUSIONS: MiODS affects patient mood which deteriorates at 8 weeks post-operatively regardless of the pre-operative patient mood state. More importantly patients suffering a greater number of mood symptoms before MiODS continue to have a greater number of symptoms following surgery.

Multiscale phylogeography: glacial history and autopolyploidy of Biscutella laevigata L. (Brassicaceae) in the Western Alps

Résumé Les changements climatiques du Quaternaire ont eu une influence majeure sur la distribution et l'évolution des biota septentrionaux. Les Alpes offrent un cadre spatio-temporel bien étudié pour comprendre la réactivité de la flore et le potentiel d'adaptation d'une espèce végétale face aux changements climatiques. Certaines hypothèses postulent une diversification des espèces en raison de la disparition complète de la flore des Alpes et d'un isolement important des espèces dans des refuges méridionaux durant les dernières glaciations (Tabula Rasa). Une autre hypothèse stipule le maintien de poches de résistance pour la végétation au coeur des Alpes (Nunataks). Comme de nombreuses espèces végétales présentant un grand succès écologique semblent avoir réagi aux glaciations par la multiplication de leur génome (autopolyploïdie), leur étude en milieu naturel devrait permettre de comprendre les avantages inhérents à la polyploïdie. Biscutella laevigata est un modèle emblématique de biogéographie historique, diverses études ayant montré que des populations diploïdes sont actuellement isolées dans les zones restées déglacées durant le dernier maximum glaciaire, alors que des tétraploïdes ont recolonisé l'ensemble des zones alpines mises à nu par le retrait des glaciers. Si le contexte périglaciaire semble avoir favorisé ce jeune complexe autopolyploïde, les circonstances et les avantages de cette mutation génomique ne sont pas encore clairs. Y a-t-il eu de multiples événements de polyploïdisation ? Dans quelle mesure affecte(nt)il(s) la diversité génétique et le potentiel évolutif des polyploïdes ? Les polyploïdes ont-ils une grande flexibilité génomique, favorisant une radiation adaptative, ou doivent-ils leur succès à une grande plasticité écologique ? Cette étude aborde ces questions à différentes échelles spatiales et temporelles. L'échelle régionale des Alpes occidentales permet d'aborder les facteurs distaux (aspects historiques), alors que l'échelle locale cherche à appréhender les facteurs proximaux (mécanismes évolutifs). Dans les Alpes occidentales, des populations ont été densément échantillonnées et étudiées grâce à (1) leur cytotype, (2) leur appartenance taxonomique, (3) leur habitat et (4) des marqueurs moléculaires de l'ADN chloroplastique, en vue d'établir leurs affinités évolutives. Á l'échelle locale, deux systèmes de population ont été étudiés : l'un où les populations persistent en périphérie de l'aire de distribution et l'autre au niveau du front actif de colonisation, en marge altitudinale. Les résultats à l'échelle des Alpes occidentales révèlent les sites d'intérêt (refuges glaciaires, principales barrières et voies de recolonisation) pour une espèce représentative des pelouses alpines, ainsi que pour la biodiversité régionale. Les Préalpes ont joué un rôle important dans le maintien de populations à proximité immédiate des Alpes centrales et dans l'évolution du taxon, voire de la végétation. Il est aussi démontré que l'époque glaciaire a favorisé l'autopolyploïdie polytopique et la recolonisation des Alpes occidentales par des lignées distinctes qui s'hybrident au centre des Alpes, influençant fortement leur diversité génétique et leur potentiel évolutif. L'analyse de populations locales en situations contrastées à l'aide de marqueurs AFLP montre qu'au sein d'une lignée présentant une grande expansion, la diversité génétique est façonnée par des forces évolutives différentes selon le contexte écologique et historique. Les populations persistant présentent une dispersion des gènes restreinte, engendrant une diversité génétique assez faible, mais semblent adaptées aux conditions locales de l'environnement. À l'inverse, les populations colonisant la marge altitudinale sont influencées par les effets de fondation conjugués à une importante dispersion des gènes et, si ces processus impliquent une grande diversité génétique, ils engendrent une répartition aléatoire des génotypes dans l'environnement. Les autopolyploïdes apparaissent ainsi comme capables de persister face aux changements climatiques grâce à certaines facultés d'adaptation locale et de grandes capacités à maintenir une importante diversité génétique lors de la recolonisation post-glaciaire. Summary The extreme climate changes of the Quaternary have had a major influence on species distribution and evolution. The European Alps offer a great framework to investigate flora reactivity and the adaptive potential of species under changing climate. Some hypotheses postulate diversification due to vegetation removal and important isolation in southern refugia (Tabula Rasa), while others explain phylogeographic patterns by the survival of species in favourable Nunataks within the Alps. Since numerous species have successfully reacted to past climate changes by genome multiplication (autopolyploidy), studies of such taxa in natural conditions is likely to explain the ecological success and the advantages of autopolyploidy. Early cytogeographical surveys of Biscutella laevigata have shed light on the links between autopolyploidy and glaciations by indicating that diploids are now spatially isolated in never-glaciated areas, while autotetraploids have recolonised the zones covered by glaciers- during the last glacial maximum. A periglacial context apparently favoured this young autopolyploid complex but the circumstances and the advantages of this genomic mutation remain unclear. What is the glacial history of the B. laevigata autopolyploid complex? Are there multiple events of polyploidisation? To what extent do they affect the genetic diversity and the evolutionary potential of polyploids? Is recolonisation associated with adaptive processes? How does long-term persistence affect genetic diversity? The present study addresses these questions at different spatiotemporal scales. A regional survey at the Western Alps-scale tackles distal factors (evolutionary history), while local-scale studies explore proximal factors (evolutionary mechanisms). In the Western Alps, populations have been densely sampled and studied from the (1) cytotypic, (2) morphotaxonomic, (3) habitat point of views, as well as (4) plastid DNA molecular markers, in order to infer their relationships and establish the maternal lineages phylogeography. At the local scale, populations persisting at the rear edge and populations recolonising the attitudinal margin at the leading edge have been studied by AFLPs to show how genetic diversity is shaped by different evolutionary forces across the species range. The results at the regional scale document the glacial history of a widespread species, representative of alpine meadows, in a regional area of main interest (glacial refugia, main barriers and recolonisation routes) and points out to sites of interest for regional biodiversity. The external Alps have played a major role in the maintenance of populations near the central Alps during the Last Glacial Maximum and influenced the evolution of the species, and of vegetation. Polytopic autopolyploidy in different biogeographic districts is also demonstrated. The species has had an important and rapid radiation because recolonisation took place from different refugia. The subsequent recolonisation of the Western Alps was achieved by independent lineages that are presently admixing in the central Alps. The role of the Pennic summit line is underlined as a great barrier that was permeable only through certain favourable high-altitude passes. The central Alps are thus viewed as an important crossroad where genomes with different evolutionary histories are meeting and admixing. The AFLP analysis and comparison of local populations growing in contrasted ecological and historical situations indicate that populations persisting in the external Alps present restricted gene dispersal and low genetic diversity but seem in equilibrium with their environment. On the contrary, populations colonising the attitudinal margin are mainly influenced by founder effects together with great gene dispersal and genotypes have a nearly random distribution, suggesting that recolonisation is not associated with adaptive processes. Autopolyploids that locally persist against climate changes thus seem to present adaptive ability, while those that actively recolonise the Alps are successful because of their great capacity to maintain a high genetic diversity against founder effects during recolonisation.

Resurgence of HIV infection among men who have sex with men in Switzerland: mathematical modelling study.

BACKGROUND: New HIV infections in men who have sex with men (MSM) have increased in Switzerland since 2000 despite combination antiretroviral therapy (cART). The objectives of this mathematical modelling study were: to describe the dynamics of the HIV epidemic in MSM in Switzerland using national data; to explore the effects of hypothetical prevention scenarios; and to conduct a multivariate sensitivity analysis. METHODOLOGY/PRINCIPAL FINDINGS: The model describes HIV transmission, progression and the effects of cART using differential equations. The model was fitted to Swiss HIV and AIDS surveillance data and twelve unknown parameters were estimated. Predicted numbers of diagnosed HIV infections and AIDS cases fitted the observed data well. By the end of 2010, an estimated 13.5% (95% CI 12.5, 14.6%) of all HIV-infected MSM were undiagnosed and accounted for 81.8% (95% CI 81.1, 82.4%) of new HIV infections. The transmission rate was at its lowest from 1995-1999, with a nadir of 46 incident HIV infections in 1999, but increased from 2000. The estimated number of new infections continued to increase to more than 250 in 2010, although the reproduction number was still below the epidemic threshold. Prevention scenarios included temporary reductions in risk behaviour, annual test and treat, and reduction in risk behaviour to levels observed earlier in the epidemic. These led to predicted reductions in new infections from 2 to 26% by 2020. Parameters related to disease progression and relative infectiousness at different HIV stages had the greatest influence on estimates of the net transmission rate. CONCLUSIONS/SIGNIFICANCE: The model outputs suggest that the increase in HIV transmission amongst MSM in Switzerland is the result of continuing risky sexual behaviour, particularly by those unaware of their infection status. Long term reductions in the incidence of HIV infection in MSM in Switzerland will require increased and sustained uptake of effective interventions.

How quickly should we titrate antihypertensive medication? Systematic review modelling blood pressure response from trial data.

Context There are no evidence syntheses available to guide clinicians on when to titrate antihypertensive medication after initiation. Objective To model the blood pressure (BP) response after initiating antihypertensive medication. Data sources electronic databases including Medline, Embase, Cochrane Register and reference lists up to December 2009. Study selection Trials that initiated antihypertensive medication as single therapy in hypertensive patients who were either drug naive or had a placebo washout from previous drugs. Data extraction Office BP measurements at a minimum of two weekly intervals for a minimum of 4 weeks. An asymptotic approach model of BP response was assumed and non-linear mixed effects modelling used to calculate model parameters. Results and conclusions Eighteen trials that recruited 4168 patients met inclusion criteria. The time to reach 50% of the maximum estimated BP lowering effect was 1 week (systolic 0.91 weeks, 95% CI 0.74 to 1.10; diastolic 0.95, 0.75 to 1.15). Models incorporating drug class as a source of variability did not improve fit of the data. Incorporating the presence of a titration schedule improved model fit for both systolic and diastolic pressure. Titration increased both the predicted maximum effect and the time taken to reach 50% of the maximum (systolic 1.2 vs 0.7 weeks; diastolic 1.4 vs 0.7 weeks). Conclusions Estimates of the maximum efficacy of antihypertensive agents can be made early after starting therapy. This knowledge will guide clinicians in deciding when a newly started antihypertensive agent is likely to be effective or not at controlling BP.

Which is the optimal sampling strategy for habitat suitability modelling

Designing an efficient sampling strategy is of crucial importance for habitat suitability modelling. This paper compares four such strategies, namely, 'random', 'regular', 'proportional-stratified' and 'equal -stratified'- to investigate (1) how they affect prediction accuracy and (2) how sensitive they are to sample size. In order to compare them, a virtual species approach (Ecol. Model. 145 (2001) 111) in a real landscape, based on reliable data, was chosen. The distribution of the virtual species was sampled 300 times using each of the four strategies in four sample sizes. The sampled data were then fed into a GLM to make two types of prediction: (1) habitat suitability and (2) presence/ absence. Comparing the predictions to the known distribution of the virtual species allows model accuracy to be assessed. Habitat suitability predictions were assessed by Pearson's correlation coefficient and presence/absence predictions by Cohen's K agreement coefficient. The results show the 'regular' and 'equal-stratified' sampling strategies to be the most accurate and most robust. We propose the following characteristics to improve sample design: (1) increase sample size, (2) prefer systematic to random sampling and (3) include environmental information in the design'

Multiscale determinants of tree frog (Hyla arborea L.) calling ponds in western Switzerland

A tree frog (Hyla arborea L., 1758) metapopulation in western Switzerland was studied during spring 2001. All potential calling ponds in an area of 350 km(2) were searched for tree frog calling males. Twenty-nine out of 111 ponds sheltered between 1 and 250 callers. Most ponds were occupied by less than 12 males. Pond parameters were measured at three different levels using field analysis and a Geographical Information System (GIS). The first level was water chemistry and pond-associated measures. The second level was the surrounding land use in a 30 m buffer around the pond. The third level consisted of landscape indices on a broader scale (up to 2 km). Logistic regression was applied to identify parameters that can predict the presence of calling males in a pond. Response variable was the presence or absence of callers. Four significant parameters allowed us to explain about 40% of the total deviance of the observed occupational pattern. Urbanization around the pond had a highly negative impact on the probability of presence of calling males. Hours of direct sunlight on the pond was positively correlated with callers. Higher water conductivity was associated with a lesser probability of species presence. Finally, the further the closest two-lane road, the higher the probability of callers presence. Our results show that presence or absence of callers is influenced by factors acting at various geographical scales.

Integrating detection probabilities in species distribution models of amphibians breeding in Mediterranean temporary ponds

Aim  The imperfect detection of species may lead to erroneous conclusions about species-environment relationships. Accuracy in species detection usually requires temporal replication at sampling sites, a time-consuming and costly monitoring scheme. Here, we applied a lower-cost alternative based on a double-sampling approach to incorporate the reliability of species detection into regression-based species distribution modelling.Location  Doñana National Park (south-western Spain).Methods  Using species-specific monthly detection probabilities, we estimated the detection reliability as the probability of having detected the species given the species-specific survey time. Such reliability estimates were used to account explicitly for data uncertainty by weighting each absence. We illustrated how this novel framework can be used to evaluate four competing hypotheses as to what constitutes primary environmental control of amphibian distribution: breeding habitat, aestivating habitat, spatial distribution of surrounding habitats and/or major ecosystems zonation. The study was conducted on six pond-breeding amphibian species during a 4-year period.Results  Non-detections should not be considered equivalent to real absences, as their reliability varied considerably. The occurrence of Hyla meridionalis and Triturus pygmaeus was related to a particular major ecosystem of the study area, where suitable habitat for these species seemed to be widely available. Characteristics of the breeding habitat (area and hydroperiod) were of high importance for the occurrence of Pelobates cultripes and Pleurodeles waltl. Terrestrial characteristics were the most important predictors of the occurrence of Discoglossus galganoi and Lissotriton boscai, along with spatial distribution of breeding habitats for the last species.Main conclusions  We did not find a single best supported hypothesis valid for all species, which stresses the importance of multiscale and multifactor approaches. More importantly, this study shows that estimating the reliability of non-detection records, an exercise that had been previously seen as a naïve goal in species distribution modelling, is feasible and could be promoted in future studies, at least in comparable systems.

Uncertainty Quantification with Support Vector Regression Prediction Models

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. The paper considers a data driven approach in modelling uncertainty in spatial predictions. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic features and describe stochastic variability and non-uniqueness of spatial properties. It is able to capture and preserve key spatial dependencies such as connectivity, which is often difficult to achieve with two-point geostatistical models. Semi-supervised SVR is designed to integrate various kinds of conditioning data and learn dependences from them. A stochastic semi-supervised SVR model is integrated into a Bayesian framework to quantify uncertainty with multiple models fitted to dynamic observations. The developed approach is illustrated with a reservoir case study. The resulting probabilistic production forecasts are described by uncertainty envelopes.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.