Independent and combined associations of risky single-occasion drinking and drinking volume with alcohol use disorder: Evidence from a sample of young Swiss men.

BACKGROUND: Risky single-occasion drinking (RSOD) is a prevalent and potentially harmful alcohol use pattern associated with increased alcohol use disorder (AUD). However, RSOD is commonly associated with a higher level of alcohol intake, and most studies have not controlled for drinking volume (DV). Thus, it is unclear whether the findings provide information about RSOD or DV. This study sought to investigate the independent and combined effects of RSOD and DV on AUD. METHODS: Data were collected in the longitudinal Cohort Study on Substance Use Risk Factors (C-SURF) among 5598 young Swiss male alcohol users in their early twenties. Assessment included DV, RSOD, and AUD at two time points. Generalized linear models for binomial distributions provided evidence regarding associations of DV, RSOD, and their interaction. RESULTS: DV, RSOD, and their interaction were significantly related to the number of AUD criteria. The slope of the interaction was steeper for non/rare RSOD than for frequent RSOD. CONCLUSIONS: RSOD appears to be a harmful pattern of drinking, associated with increased AUD and it moderated the relationship between DV and AUD. This study highlighted the importance of taking drinking patterns into account, for both research and public health planning, since RSO drinkers constitute a vulnerable subgroup for AUD.

What do we gain from simplicity versus complexity in species distribution models?

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models.

BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.

Do habitat suitability models reliably predict the recovery areas of threatened species?

1. Identifying those areas suitable for recolonization by threatened species is essential to support efficient conservation policies. Habitat suitability models (HSM) predict species' potential distributions, but the quality of their predictions should be carefully assessed when the species-environment equilibrium assumption is violated.2. We studied the Eurasian otter Lutra lutra, whose numbers are recovering in southern Italy. To produce widely applicable results, we chose standard HSM procedures and looked for the models' capacities in predicting the suitability of a recolonization area. We used two fieldwork datasets: presence-only data, used in the Ecological Niche Factor Analyses (ENFA), and presence-absence data, used in a Generalized Linear Model (GLM). In addition to cross-validation, we independently evaluated the models with data from a recolonization event, providing presences on a previously unoccupied river.3. Three of the models successfully predicted the suitability of the recolonization area, but the GLM built with data before the recolonization disagreed with these predictions, missing the recolonized river's suitability and badly describing the otter's niche. Our results highlighted three points of relevance to modelling practices: (1) absences may prevent the models from correctly identifying areas suitable for a species spread; (2) the selection of variables may lead to randomness in the predictions; and (3) the Area Under Curve (AUC), a commonly used validation index, was not well suited to the evaluation of model quality, whereas the Boyce Index (CBI), based on presence data only, better highlighted the models' fit to the recolonization observations.4. For species with unstable spatial distributions, presence-only models may work better than presence-absence methods in making reliable predictions of suitable areas for expansion. An iterative modelling process, using new occurrences from each step of the species spread, may also help in progressively reducing errors.5. Synthesis and applications. Conservation plans depend on reliable models of the species' suitable habitats. In non-equilibrium situations, such as the case for threatened or invasive species, models could be affected negatively by the inclusion of absence data when predicting the areas of potential expansion. Presence-only methods will here provide a better basis for productive conservation management practices.

Evaluating the ability of habitat suitability models to predict species presences.

Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presenceonly evaluators to usual presence/absence measures. We use a reliable, diverse, presence/absence dataset of 114 plant species to test how common presence/absence indices (Kappa, MaxKappa, AUC, adjusted D-2) compare to presenceonly measures (AVI, CVI, Boyce index) for evaluating generalised linear models (GLM). Moreover we propose a new, threshold-independent evaluator, which we call "continuous Boyce index". All indices were implemented in the B10MAPPER software. We show that the presence-only evaluators are fairly correlated (p > 0.7) to the presence/absence ones. The Boyce indices are closer to AUC than to MaxKappa and are fairly insensitive to species prevalence. In addition, the Boyce indices provide predicted-toexpected ratio curves that offer further insights into the model quality: robustness, habitat suitability resolution and deviation from randomness. This information helps reclassifying predicted maps into meaningful habitat suitability classes. The continuous Boyce index is thus both a complement to usual evaluation of presence/absence models and a reliable measure of presence-only based predictions.

Neocortical maturation during adolescence: change in neuronal soma dimension.

During adolescence, cognitive abilities increase robustly. To search for possible related structural alterations of the cerebral cortex, we measured neuronal soma dimension (NSD = width times height), cortical thickness and neuronal densities in different types of neocortex in post-mortem brains of five 12-16 and five 17-24 year-olds (each 2F, 3M). Using a generalized mixed model analysis, mean normalized NSD comparing the age groups shows layer-specific change for layer 2 (p < .0001) and age-related differences between categorized type of cortex: primary/primary association cortex (BA 1, 3, 4, and 44) shows a generalized increase; higher-order regions (BA 9, 21, 39, and 45) also show increase in layers 2 and 5 but decrease in layers 3, 4, and 6 while limbic/orbital cortex (BA 23, 24, and 47) undergoes minor decrease (BA 1, 3, 4, and 44 vs. BA 9, 21, 39, and 45: p = .036 and BA 1, 3, 4, and 44 vs. BA 23, 24, and 47: p = .004). These data imply the operation of cortical layer- and type-specific processes of growth and regression adding new evidence that the human brain matures during adolescence not only functionally but also structurally.

Improving generalized regression analysis for the spatial prediction of forest communities

Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

Genetic differentiation for size at first reproduction through male versus female functions in the widespread Mediterranean tree Pinus pinaster.

BACKGROUND AND AIMS: The study of local adaptation in plant reproductive traits has received substantial attention in short-lived species, but studies conducted on forest trees are scarce. This lack of research on long-lived species represents an important gap in our knowledge, because inferences about selection on the reproduction and life history of short-lived species cannot necessarily be extrapolated to trees. This study considers whether the size for first reproduction is locally adapted across a broad geographical range of the Mediterranean conifer species Pinus pinaster. In particular, the study investigates whether this monoecious species varies genetically among populations in terms of whether individuals start to reproduce through their male function, their female function or both sexual functions simultaneously. Whether differences among populations could be attributed to local adaptation across a climatic gradient is then considered. METHODS: Male and female reproduction and growth were measured during early stages of sexual maturity of a P. pinaster common garden comprising 23 populations sampled across the species range. Generalized linear mixed models were used to assess genetic variability of early reproductive life-history traits. Environmental correlations with reproductive life-history traits were tested after controlling for neutral genetic structure provided by 12 nuclear simple sequence repeat markers. KEY RESULTS: Trees tended to reproduce first through their male function, at a size (height) that varied little among source populations. The transition to female reproduction was slower, showed higher levels of variability and was negatively correlated with vegetative growth traits. Several female reproductive traits were correlated with a gradient of growth conditions, even after accounting for neutral genetic structure, with populations from more unfavourable sites tending to commence female reproduction at a lower individual size. CONCLUSIONS: The study represents the first report of genetic variability among populations for differences in the threshold size for first reproduction between male and female sexual functions in a tree species. The relatively uniform size at which individuals begin reproducing through their male function probably represents the fact that pollen dispersal is also relatively invariant among sites. However, the genetic variability in the timing of female reproduction probably reflects environment-dependent costs of cone production. The results also suggest that early sex allocation in this species might evolve under constraints that do not apply to other conifers.

Modelling the influence of change in fire regime on the local distribution of a Mediterranean pyrophytic plant species (Cistus salviifolius) at its northern range limit

Aims: To assess the potential distribution of an obligate seeder and active pyrophyte, Cistus salviifolius, a vulnerable species in the Swiss Red List; to derive scenarios by changing the fire return interval; and to discuss the results from a conservation perspective. A more general aim is to assess the impact of fire as a natural factor influencing the vegetation of the southern slopes of the Alps. Locations: Alps, southern Switzerland. Methods: Presence-absence data to fit the model were obtained from the most recent field mapping of C. salviifolius. The quantitative environmental predictors used in this study include topographic, climatic and disturbance (fire) predictors. Models were fitted by logistic regression and evaluated by jackknife and bootstrap approaches. Changes in fire regime were simulated by increasing the time-return interval of fire (simulating longer periods without fire). Two scenarios were considered: no fire in the past 15 years; or in the past 35 years. Results: Rock cover, slope, topographic position, potential evapotranspiration and time elapsed since the last fire were selected in the final model. The Nagelkerke R-2 of the model for C. salviifolius was 0.57 and the Jackknife area under the curve evaluation was 0.89. The bootstrap evaluation revealed model robustness. By increasing the return interval of fire by either up to 15 years, or 35 years, the modelled C. salviifolius population declined by 30-40%, respectively. Main conclusions: Although fire plays a significant role, topography and rock cover appear to be the most important predictors, suggesting that the distribution of C. salviifolius in the southern Swiss Alps is closely related to the availability of supposedly competition-free sites, such as emerging bedrock, ridge locations or steep slopes. Fire is more likely to play a secondary role in allowing C. salviifolius to extend its occurrence temporarily, by increasing germination rates and reducing the competition from surrounding vegetation. To maintain a viable dormant seed bank for C. salviifolius, conservation managers should consider carrying out vegetation clearing and managing wild fire propagation to reduce competition and ensure sufficient recruitment for this species.

An index to identify stroke-related vs incidental patent foramen ovale in cryptogenic stroke.

OBJECTIVE: We aimed to create an index to stratify cryptogenic stroke (CS) patients with patent foramen ovale (PFO) by their likelihood that the stroke was related to their PFO. METHODS: Using data from 12 component studies, we used generalized linear mixed models to predict the presence of PFO among patients with CS, and derive a simple index to stratify patients with CS. We estimated the stratum-specific PFO-attributable fraction and stratum-specific stroke/TIA recurrence rates. RESULTS: Variables associated with a PFO in CS patients included younger age, the presence of a cortical stroke on neuroimaging, and the absence of these factors: diabetes, hypertension, smoking, and prior stroke or TIA. The 10-point Risk of Paradoxical Embolism score is calculated from these variables so that the youngest patients with superficial strokes and without vascular risk factors have the highest score. PFO prevalence increased from 23% (95% confidence interval [CI]: 19%-26%) in those with 0 to 3 points to 73% (95% CI: 66%-79%) in those with 9 or 10 points, corresponding to attributable fraction estimates of approximately 0% to 90%. Kaplan-Meier estimated stroke/TIA 2-year recurrence rates decreased from 20% (95% CI: 12%-28%) in the lowest Risk of Paradoxical Embolism score stratum to 2% (95% CI: 0%-4%) in the highest. CONCLUSION: Clinical characteristics identify CS patients who vary markedly in PFO prevalence, reflecting clinically important variation in the probability that a discovered PFO is likely to be stroke-related vs incidental. Patients in strata more likely to have stroke-related PFOs have lower recurrence risk.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Residence time, expansion toward the equator in the invaded range and native range size matter to climatic niche shifts in non-native species

Aim Identifying climatic niche shifts and their drivers is important to accurately predict the risk of biological invasions. The niches of non-native plants and birds have recently been assessed in large-scale multi-species studies, but such large-scale tests are lacking for non-native reptiles and amphibians (herpetofauna). Furthermore, little is known about the factors contributing to niche shifts when they occur. Based on the occurrence of 71 reptile and amphibian species, we compared native and non-native realized niches in 101 invaded ranges at a worldwide scale and identified the factors that affect niche shifts. Location The world except the Antarctic. Methods We assessed climatic niche dynamics in a gridded environmental space allowing the quantification of niche overlap and expansion into climatic conditions not colonized by the species in their native range. We analyzed the factors affecting niche shifts using a model averaging approach based on generalized linear mixed-effects models. Results Approximately 57% of the invaded ranges (51% for amphibians and 61% for reptiles) showed niche shifts (≥10% expansion in the realized climatic niche). Island endemics, species introduced to Oceania and invaded ranges outside the native biogeographic realm showed a higher proportion of niche shifts. Niche shifts were more likely for species that had smaller native range sizes, were introduced earlier into a new range or invaded areas located at lower latitudes than the native range. Main conclusions The proportion of niche shifts for non-native herpetofauna was higher than those for Holarctic non-native plants and European non-native birds. The 'climate matching hypothesis' should be used with caution for species shifting their niche because it could underestimate the risk of their establishment.

Importance of abiotic stress as a range-limit determinant for European plants: insights from species' responses to climatic gradients

Aim We examined whether species occurrences are primarily limited by physiological tolerance in the abiotically more stressful end of climatic gradients (the asymmetric abiotic stress limitation (AASL) hypothesis) and the geographical predictions of this hypothesis: abiotic stress mainly determines upper-latitudinal and upper-altitudinal species range limits, and the importance of abiotic stress for these range limits increases the further northwards and upwards a species occurs. Location Europe and the Swiss Alps. Methods The AASL hypothesis predicts that species have skewed responses to climatic gradients, with a steep decline towards the more stressful conditions. Based on presence-absence data we examined the shape of plant species responses (measured as probability of occurrence) along three climatic gradients across latitudes in Europe (1577 species) and altitudes in the Swiss Alps (284 species) using Huisman-Olff-Fresco, generalized linear and generalized additive models. Results We found that almost half of the species from Europe and one-third from the Swiss Alps showed responses consistent with the predictions of the AASL hypothesis. Cold temperatures and a short growing season seemed to determine the upper-latitudinal and upper-altitudinal range limits of up to one-third of the species, while drought provided an important constraint at lower-latitudinal range limits for up to one-fifth of the species. We found a biome-dependent influence of abiotic stress and no clear support for abiotic stress as a stronger upper range-limit determinant for species with higher latitudinal and altitudinal distributions. However, the overall influence of climate as a range-limit determinant increased with latitude. Main conclusions Our results support the AASL hypothesis for almost half of the studied species, and suggest that temperature-related stress controls the upper-latitudinal and upper-altitudinal range limits of a large proportion of these species, while other factors including drought stress may be important at the lower range limits.

Maintenance of biodiversity in vineyard-dominated landscapes: a case study on larval salamanders

Alteration of natural habitats as a result of agricultural intensification is detrimental for wildlife. There is, however, growing evidence that land use and management can be wildlife friendly. In Europe, agricultural areas cover two-thirds of the land and therefore play a major role in maintaining biodiversity. Agricultural land use is very intense in vineyard-dominated landscapes but there are no refuges for wildlife in the form of ecological compensation areas. In our study, we assessed spatial variation in abundance of salamander (Salamandra salamandra) larvae in relation to land use and stream characteristics in vineyard-dominated landscapes. Abundance of larval salamanders depended positively on weirs, amount of riparian vegetation along the streams and environment-friendly agricultural practice in the vineyards. Surprisingly, road density also had positive effects, presumably through indirect effects (stone walls along roads may serve as refugia). Thus, abundance is determined by characteristics of both the aquatic and terrestrial habitats. Our results suggest that fire salamanders can persist in landscapes dominated by intensive agriculture like viticulture, indicate wildlife-friendly management options and highlight that man-made habitat can be valuable for wildlife.