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.

Land use improves spatial predictions of mountain plant abundance but not presence-absence

Question Does a land-use variable improve spatial predictions of plant species presence-absence and abundance models at the regional scale in a mountain landscape? Location Western Swiss Alps. Methods Presence-absence generalized linear models (GLM) and abundance ordinal logistic regression models (LRM) were fitted to data on 78 mountain plant species, with topo-climatic and/or land-use variables available at a 25-m resolution. The additional contribution of land use when added to topo-climatic models was evaluated by: (1) assessing the changes in model fit and (2) predictive power, (3) partitioning the deviance respectively explained by the topo-climatic variables and the land-use variable through variation partitioning, and (5) comparing spatial projections. Results Land use significantly improved the fit of presence-absence models but not their predictive power. In contrast, land use significantly improved both the fit and predictive power of abundance models. Variation partitioning also showed that the individual contribution of land use to the deviance explained by presence-absence models was, on average, weak for both GLM and LRM (3.7% and 4.5%, respectively), but changes in spatial projections could nevertheless be important for some species. Conclusions In this mountain area and at our regional scale, land use is important for predicting abundance, but not presence-absence. The importance of adding land-use information depends on the species considered. Even without a marked effect on model fit and predictive performance, adding land use can affect spatial projections of both presence-absence and abundance models.

A stratified approach for modeling the distribution of a threatened ant species in the Swiss National Park

We present models predicting the potential distribution of a threatened ant species, Formica exsecta Nyl., in the Swiss National Park ( SNP). Data to fit the models have been collected according to a random-stratified design with an equal number of replicates per stratum. The basic aim of such a sampling strategy is to allow the formal testing of biological hypotheses about those factors most likely to account for the distribution of the modeled species. The stratifying factors used in this study were: vegetation, slope angle and slope aspect, the latter two being used as surrogates of solar radiation, considered one of the basic requirements of F. exsecta. Results show that, although the basic stratifying predictors account for more than 50% of the deviance, the incorporation of additional non-spatially explicit predictors into the model, as measured in the field, allows for an increased model performance (up to nearly 75%). However, this was not corroborated by permutation tests. Implementation on a national scale was made for one model only, due to the difficulty of obtaining similar predictors on this scale. The resulting map on the national scale suggests that the species might once have had a broader distribution in Switzerland. Reasons for its particular abundance within the SNP might possibly be related to habitat fragmentation and vegetation transformation outside the SNP boundaries.

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.

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.

Are niche-based species distribution models transferable in space?

Aim To assess the geographical transferability of niche-based species distribution models fitted with two modelling techniques. Location Two distinct geographical study areas in Switzerland and Austria, in the subalpine and alpine belts. Methods Generalized linear and generalized additive models (GLM and GAM) with a binomial probability distribution and a logit link were fitted for 54 plant species, based on topoclimatic predictor variables. These models were then evaluated quantitatively and used for spatially explicit predictions within (internal evaluation and prediction) and between (external evaluation and prediction) the two regions. Comparisons of evaluations and spatial predictions between regions and models were conducted in order to test if species and methods meet the criteria of full transferability. By full transferability, we mean that: (1) the internal evaluation of models fitted in region A and B must be similar; (2) a model fitted in region A must at least retain a comparable external evaluation when projected into region B, and vice-versa; and (3) internal and external spatial predictions have to match within both regions. Results The measures of model fit are, on average, 24% higher for GAMs than for GLMs in both regions. However, the differences between internal and external evaluations (AUC coefficient) are also higher for GAMs than for GLMs (a difference of 30% for models fitted in Switzerland and 54% for models fitted in Austria). Transferability, as measured with the AUC evaluation, fails for 68% of the species in Switzerland and 55% in Austria for GLMs (respectively for 67% and 53% of the species for GAMs). For both GAMs and GLMs, the agreement between internal and external predictions is rather weak on average (Kulczynski's coefficient in the range 0.3-0.4), but varies widely among individual species. The dominant pattern is an asymmetrical transferability between the two study regions (a mean decrease of 20% for the AUC coefficient when the models are transferred from Switzerland and 13% when they are transferred from Austria). Main conclusions The large inter-specific variability observed among the 54 study species underlines the need to consider more than a few species to test properly the transferability of species distribution models. The pronounced asymmetry in transferability between the two study regions may be due to peculiarities of these regions, such as differences in the ranges of environmental predictors or the varied impact of land-use history, or to species-specific reasons like differential phenotypic plasticity, existence of ecotypes or varied dependence on biotic interactions that are not properly incorporated into niche-based models. The lower variation between internal and external evaluation of GLMs compared to GAMs further suggests that overfitting may reduce transferability. Overall, a limited geographical transferability calls for caution when projecting niche-based models for assessing the fate of species in future environments.

Tree cover at fine and coarse spatial grains interacts with shade tolerance to shape plant species distributions across the Alps

The role of competition for light among plants has long been recognized at local scales, but its potential importance for plant species' distribution at larger spatial scales has largely been ignored. Tree cover acts as a modulator of local abiotic conditions, notably by reducing light availability below the canopy and thus the performance of species that are not adapted to low-light conditions. However, this local effect may propagate to coarser spatial grains. Using 6,935 vegetation plots located across the European Alps, we fit Generalized Linear Models (GLM) for the distribution of 960 herbs and shrubs species to assess the effect of tree cover at both plot and landscape grain sizes (~ 10-m and 1-km, respectively). We ran four models with different combinations of variables (climate, soil and tree cover) for each species at both spatial grains. We used partial regressions to evaluate the independent effects of plot- and landscape-scale tree cover on plant communities. Finally, the effects on species' elevational range limits were assessed by simulating a removal experiment comparing the species' distribution under high and low tree cover. Accounting for tree cover improved model performance, with shade-tolerant species increasing their probability of presence at high tree cover whereas shade-intolerant species showed the opposite pattern. The tree cover effect occurred consistently at both plot and landscape spatial grains, albeit strongest at the former. Importantly, tree cover at the two grain sizes had partially independent effects on plot-scale plant communities, suggesting that the effects may be transmitted to coarser grains through meta-community dynamics. At high tree cover, shade-intolerant species exhibited elevational range contractions, especially at their upper limit, whereas shade-tolerant species showed elevational range expansions at both limits. Our findings suggest that the range shifts for herb and shrub species may be modulated by tree cover dynamics.

Case management for emergency department frequent users : a randomized controlled trial

Background: Emergency department frequent users (EDFUs) account for a disproportionally high number of emergency department (ED) visits, contributing to overcrowding and high health-care costs. At the Lausanne University Hospital, EDFUs account for only 4.4% of ED patients, but 12.1% of all ED visits. Our study tested the hypothesis that an interdisciplinary case management intervention red. Methods: In this randomized controlled trial, we allocated adult EDFUs (5 or more visits in the previous 12 months) who visited the ED of the University Hospital of Lausanne, Switzerland between May 2012 and July 2013 either to an intervention (N=125) or a standard emergency care (N=125) group and monitored them for 12 months. Randomization was computer generated and concealed, and patients and research staff were blinded to the allocation. Participants in the intervention group, in addition to standard emergency care, received case management from an interdisciplinary team at baseline, and at 1, 3, and 5 months, in the hospital, in the ambulatory care setting, or at their homes. A generalized, linear, mixed-effects model for count data (Poisson distribution) was applied to compare participants' numbers of visits to the ED during the 12 months (Period 1, P1) preceding recruitment to the numbers of visits during the 12 months monitored (Period 2, P2).

Derivation of an observer model adapted to irregular signals based on convolution channels.

Anthropomorphic model observers are mathe- matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal.

Female adolescents' views on a youth-friendly clinic.

OBJECTIVE: To assess satisfaction among female patients of a youth friendly clinic and to determine with which factors this was associated. METHODS: A cross-sectional survey was conducted in an adolescent clinic in Lausanne, Switzerland, between March and May 2008. All female patients who had made at least one previous visit were eligible. Three hundred and eleven patients aged 12-22 years were included. We performed bivariate analysis to compare satisfied and non-satisfied patients and constructed a log-linear model. RESULTS: Ninety-four percent of patients were satisfied. Satisfied female adolescents were significantly more likely to feel that their complaints were heard, that the caregiver understood their problems, to have no change of physician, to have received the correct treatment/help and to follow the caregiver's advice. The log-linear model highlighted four factors directly linked with patient satisfaction: outcome of care, continuity of care, adherence to treatment and the feeling of being understood. CONCLUSIONS: The main point for female adolescent patient satisfaction lies in a long term, trustworthy relationship with their caregiver. Confidentiality and accessibility were secondary for our patients.

Modelling the distribution of bats in relation to landscape structure in a temperate mountain environment

1. Landscape modification is often considered the principal cause of population decline in many bat species. Thus, schemes for bat conservation rely heavily on knowledge about species-landscape relationships. So far, however, few studies have quantified the possible influence of landscape structure on large-scale spatial patterns in bat communities. 2. This study presents quantitative models that use landscape structure to predict (i) spatial patterns in overall community composition and (ii) individual species' distributions through canonical correspondence analysis and generalized linear models, respectively. A geographical information system (GIS) was then used to draw up maps of (i) overall community patterns and (ii) distribution of potential species' habitats. These models relied on field data from the Swiss Jura mountains. 3. Fight descriptors of landscape structure accounted for 30% of the variation in bat community composition. For some species, more than 60% of the variance in distribution could be explained by landscape structure. Elevation, forest or woodland cover, lakes and suburbs, were the most frequent predictors. 4. This study shows that community composition in bats is related to landscape structure through species-specific relationships to resources. Due to their nocturnal activities and the difficulties of remote identification, a comprehensive bat census is rarely possible, and we suggest that predictive modelling of the type described here provides an indispensable conservation tool.

Copeptin Levels Remain Unchanged during the Menstrual Cycle.

BACKGROUND: Copeptin, a surrogate marker for arginin vasopressin production, is evaluated as an osmo-dependent stress and inflammatory biomarker in different diseases. We investigated copeptin during the menstrual cycle and its relationship to sex hormones, markers of subclinical inflammation and estimates of body fluid. METHODS: In 15 healthy women with regular menstrual cycles, blood was drawn on fifteen defined days of their menstrual cycle and was assayed for copeptin, progesterone, estradiol, luteinizing hormone, high-sensitive C-reactive protein, tumor necrosis factor-alpha and procalcitonin. Symptoms of fluid retention were assessed on each visit, and bio impedance analysis was measured thrice to estimate body fluid changes. Mixed linear model analysis was performed to assess the changes of copeptin across the menstrual cycle and the relationship of sex hormones, markers of subclinical inflammation and estimates of body fluid with copeptin. RESULTS: Copeptin levels did not significantly change during the menstrual cycle (p = 0.16). Throughout the menstrual cycle, changes in estradiol (p = 0.002) and in the physical premenstrual symptom score (p = 0.01) were positively related to copeptin, but changes in other sex hormones, in markers of subclinical inflammation or in bio impedance analysis-estimated body fluid were not (all p = ns). CONCLUSION: Although changes in estradiol and the physical premenstrual symptom score appear to be related to copeptin changes, copeptin does not significantly change during the menstrual cycle.

Genomics of the divergence continuum in an African plant biodiversity hotspot, I: drivers of population divergence in Restio capensis (Restionaceae).

Understanding the drivers of population divergence, speciation and species persistence is of great interest to molecular ecology, especially for species-rich radiations inhabiting the world's biodiversity hotspots. The toolbox of population genomics holds great promise for addressing these key issues, especially if genomic data are analysed within a spatially and ecologically explicit context. We have studied the earliest stages of the divergence continuum in the Restionaceae, a species-rich and ecologically important plant family of the Cape Floristic Region (CFR) of South Africa, using the widespread CFR endemic Restio capensis (L.) H.P. Linder & C.R. Hardy as an example. We studied diverging populations of this morphotaxon for plastid DNA sequences and >14 400 nuclear DNA polymorphisms from Restriction site Associated DNA (RAD) sequencing and analysed the results jointly with spatial, climatic and phytogeographic data, using a Bayesian generalized linear mixed modelling (GLMM) approach. The results indicate that population divergence across the extreme environmental mosaic of the CFR is mostly driven by isolation by environment (IBE) rather than isolation by distance (IBD) for both neutral and non-neutral markers, consistent with genome hitchhiking or coupling effects during early stages of divergence. Mixed modelling of plastid DNA and single divergent outlier loci from a Bayesian genome scan confirmed the predominant role of climate and pointed to additional drivers of divergence, such as drift and ecological agents of selection captured by phytogeographic zones. Our study demonstrates the usefulness of population genomics for disentangling the effects of IBD and IBE along the divergence continuum often found in species radiations across heterogeneous ecological landscapes.

Comparability of clinical wear measurements by optical 3D laser scanning in two different centers.

OBJECTIVE: The purpose of this study was to compare the use of different variables to measure the clinical wear of two denture tooth materials in two analysis centers. METHODS: Twelve edentulous patients were provided with full dentures. Two different denture tooth materials (experimental material and control) were placed randomly in accordance with the split-mouth design. For wear measurements, impressions were made after an adjustment phase of 1-2 weeks and after 6, 12, 18, and 24 months. The occlusal wear of the posterior denture teeth of 11 subjects was assessed in two study centers by use of plaster replicas and 3D laser-scanning methods. In both centers sequential scans of the occlusal surfaces were digitized and superimposed. Wear was described by use of four different variables. Statistical analysis was performed after log-transformation of the wear data by use of the Pearson and Lin correlation and by use of a mixed linear model. RESULTS: Mean occlusal vertical wear of the denture teeth after 24 months was between 120μm and 212μm, depending on wear variable and material. For three of the four variables, wear of the experimental material was statistically significantly less than that of the control. Comparison of the two study centers, however, revealed correlation of the wear variables was only moderate whereas strong correlation was observed among the different wear variables evaluated by each center. SIGNIFICANCE: Moderate correlation was observed for clinical wear measurements by optical 3D laser scanning in two different study centers. For the two denture tooth materials, wear measurements limited to the attrition zones led to the same qualitative assessment.

Substitution of (R,S)-methadone by (R)-methadone: Impact on QTc interval.

Methadone is administered as a chiral mixture of (R,S)-methadone. The opioid effect is mainly mediated by (R)-methadone, whereas (S)-methadone blocks the human ether-à-go-go-related gene (hERG) voltage-gated potassium channel more potently, which can cause drug-induced long QT syndrome, leading to potentially lethal ventricular tachyarrhythmias. To investigate whether substitution of (R,S)-methadone by (R)-methadone could reduce the corrected QT (QTc) interval, (R,S)-methadone was replaced by (R)-methadone (half-dose) in 39 opioid-dependent patients receiving maintenance treatment for 14 days. (R)-methadone was then replaced by the initial dose of (R,S)-methadone for 14 days (n = 29). Trough (R)-methadone and (S)-methadone plasma levels and electrocardiogram measurements were taken. The Fridericia-corrected QT (QTcF) interval decreased when (R,S)-methadone was replaced by a half-dose of (R)-methadone; the median (interquartile range [IQR]) values were 423 (398-440) milliseconds (ms) and 412 (395-431) ms (P = .06) at days 0 and 14, respectively. Using a univariate mixed-effect linear model, the QTcF value decreased by a mean of -3.9 ms (95% confidence interval [CI], -7.7 to -0.2) per week (P = .04). The QTcF value increased when (R)-methadone was replaced by the initial dose of (R,S)-methadone for 14 days; median (IQR) values were 424 (398-436) ms and 424 (412-443) ms (P = .01) at days 14 and 28, respectively. The univariate model showed that the QTcF value increased by a mean of 4.7 ms (95% CI, 1.3-8.1) per week (P = .006). Substitution of (R,S)-methadone by (R)-methadone reduces the QTc interval value. A safer cardiac profile of (R)-methadone is in agreement with previous in vitro and pharmacogenetic studies. If the present results are confirmed by larger studies, (R)-methadone should be prescribed instead of (R,S)-methadone to reduce the risk of cardiac toxic effects and sudden death.