Novel methods improve prediction of species' distributions from occurrence data

Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

The effects of dominance, regular inbreeding and sampling design on Q(ST), an estimator of population differentiation for quantitative traits.

To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.

Nanosized Nb-TiO2 gas sensors derived from alkoxides hydrolization

Nanocrystalline TiO2 modified with Nb has been produced through the sol-gel technique. Nanopowders have been obtained by means of the hydrolysis of pure alkoxides with deionized water and peptization of the resulting hydrolysate with diluted acid nitric at 100 C. The addition of Nb stabilizes the anatase phase to higher temperatures. XRD spectra of the undoped and the Nb-doped samples show that the undoped sample has been almost totally converted to rutile at 600 C, meanwhile the doped samples present still a low percentage of rutile phase. Nanocrystalline powders stabilized at 600 C with grain sizes of about 17 nm have successfully been synthesized by the addition of Nb with a concentration of 2% at., which appears to be an adequate additive concentration to improve the gas sensor performances, such as it is suggested by the catalytic conversion efficiency experiments performed from FTIR measurements. FTIR absorbance spectra show that catalytic conversion of CO occurs at lower temperatures when niobium is introduced. The electrical response of the films to different concentrations of CO and ethanol has been monitored in dry and wet environments in order to test the influence of humidity in the sensor response. The addition of Nb decreases the working temperature and increases the stability of the layers. Also, large enhancement of the response time is obtained even with lower working temperatures. Moreover, humidity effects on the gas sensor response toward CO and ethanol are less important in Nb-doped samples than in the undoped ones.

Comparative effects of GLP-1-(7-36) amide, oxyntomodulin and glucagon on rabbit gastric parietal cell function.

We have investigated in vitro, the effects of glucagon-like peptide-1-(7-36) amide (GLP-1-(7-36) amide), oxyntomodulin and glucagon on two rabbit parietal cell-enriched fractions (F3, F3n), with parietal cell contents of 60% and 88%, respectively. Histamine (10(-5) M) stimulated [14C]aminopyrine accumulation to an amount of 850% in excess of the basal level, whereas GLP-1-(7-36) amide (10(-7) M) and oxyntomodulin (10(-6) M) induced increases of 50% and 30%, respectively. With a histamine concentration of 10(-6) M, [14C]aminopyrine accumulation was stimulated to 498% in excess of the basal level; GLP-1-(7-36) amide (10(-7) M) and oxyntomodulin (10(-7) M) induced increases of 18% and 15%, respectively. With these parameters, oxyntomodulin[19-37] and glucagon were without effect. Specific binding of [125I]GLP-1-(7-36) amide to parietal cell plasma membranes was inhibited dose-dependently by GLP-1-(7-36) amide, oxyntomodulin and glucagon with inhibitory concentrations of 0.25 nM, 65 nM and 800 nM, respectively. No specific binding of [125I]oxyntomodulin or [125I]glucagon was detectable. GLP-1-(7-36) amide receptor mRNA was only detected in parietal cell-enriched fractions. GLP-1-(7-36) amide, oxyntomodulin and glucagon stimulated parietal cell cAMP production to similar maximal levels with median values close to 0.28 nM, 10.5 nM and 331.7 nM, whereas oxyntomodulin[19-37] had no effect. The maximal cAMP production induced by GLP-1-(7-36) amide, oxyntomodulin or glucagon was additive to that induced by histamine.(ABSTRACT TRUNCATED AT 250 WORDS)

Combination of MRI and dynamic FET PET for initial glioma grading.

AIM: MRI and PET with 18F-fluoro-ethyl-tyrosine (FET) have been increasingly used to evaluate patients with gliomas. Our purpose was to assess the additive value of MR spectroscopy (MRS), diffusion imaging and dynamic FET-PET for glioma grading. PATIENTS, METHODS: 38 patients (42 ± 15 aged, F/M: 0.46) with untreated histologically proven brain gliomas were included. All underwent conventional MRI, MRS, diffusion sequences, and FET-PET within 3±4 weeks. Performances of tumour FET time-activity-curve, early-to-middle SUVmax ratio, choline / creatine ratio and ADC histogram distribution pattern for gliomas grading were assessed, as compared to histology. Combination of these parameters and respective odds were also evaluated. RESULTS: Tumour time-activity-curve reached the best accuracy (67%) when taken alone to distinguish between low and high-grade gliomas, followed by ADC histogram analysis (65%). Combination of time-activity-curve and ADC histogram analysis improved the sensitivity from 67% to 86% and the specificity from 63-67% to 100% (p < 0.008). On multivariate logistic regression analysis, negative slope of the tumour FET time-activity-curve however remains the best predictor of high-grade glioma (odds 7.6, SE 6.8, p = 0.022). CONCLUSION: Combination of dynamic FET-PET and diffusion MRI reached good performance for gliomas grading. The use of FET-PET/MR may be highly relevant in the initial assessment of primary brain tumours.

Nanosized Nb-TiO2 gas sensors derived from alkoxides hydrolization

Nanocrystalline TiO2 modified with Nb has been produced through the sol-gel technique. Nanopowders have been obtained by means of the hydrolysis of pure alkoxides with deionized water and peptization of the resulting hydrolysate with diluted acid nitric at 100 C. The addition of Nb stabilizes the anatase phase to higher temperatures. XRD spectra of the undoped and the Nb-doped samples show that the undoped sample has been almost totally converted to rutile at 600 C, meanwhile the doped samples present still a low percentage of rutile phase. Nanocrystalline powders stabilized at 600 C with grain sizes of about 17 nm have successfully been synthesized by the addition of Nb with a concentration of 2% at., which appears to be an adequate additive concentration to improve the gas sensor performances, such as it is suggested by the catalytic conversion efficiency experiments performed from FTIR measurements. FTIR absorbance spectra show that catalytic conversion of CO occurs at lower temperatures when niobium is introduced. The electrical response of the films to different concentrations of CO and ethanol has been monitored in dry and wet environments in order to test the influence of humidity in the sensor response. The addition of Nb decreases the working temperature and increases the stability of the layers. Also, large enhancement of the response time is obtained even with lower working temperatures. Moreover, humidity effects on the gas sensor response toward CO and ethanol are less important in Nb-doped samples than in the undoped ones.

Herramientas estadísticas para el estudio de perfiles de riesgo

En este documento se ilustra de un modo práctico, el empleo de tres instrumentos que permiten al actuario definir grupos arancelarios y estimar premios de riesgo en el proceso que tasa la clase para el seguro de no vida. El primero es el análisis de segmentación (CHAID y XAID) usado en primer lugar en 1997 por UNESPA en su cartera común de coches. El segundo es un proceso de selección gradual con el modelo de regresión a base de distancia. Y el tercero es un proceso con el modelo conocido y generalizado de regresión linear, que representa la técnica más moderna en la bibliografía actuarial. De estos últimos, si combinamos funciones de eslabón diferentes y distribuciones de error, podemos obtener el aditivo clásico y modelos multiplicativos

Decay of an unstable state in the presence of multiplicative noise

The phenomenon of anomalous fluctuations associated with the decay of an unstable state is analyzed in the presence of multiplicative noise. A theory is presented and compared with a numerical simulation. Our results allow us to distinguish the roles of additive and multiplicative noise in the nonlinear relaxation process. We suggest the use of experiments on transient dynamics to understand the effect of these two sources of noise in problems in which parametric noise is thought to be important, such as dye lasers.

Effects of external noise on the Swift-Hohenberg Equation

The Swift-Hohenberg equation is studied in the presence of a multiplicative noise. This stochastic equation could describe a situation in which a noise has been superimposed on the temperature gradient between the two plates of a Rayleigh-Bnard cell. A linear stability analysis and numerical simulations show that, in constrast to the additive-noise case, convective structures appear in a regime in which a deterministic analysis predicts a homogeneous solution.

High-Momentum Response of Liquid 3He

A final-state-effects formalism suitable to analyze the high-momentum response of Fermi liquids is presented and used to study the dynamic structure function of liquid 3He. The theory, developed as a natural extension of the Gersch-Rodriguez formalism, incorporates the Fermi statistics explicitly through a new additive term which depends on the semidiagonal two-body density matrix. The use of a realistic momentum distribution, calculated using the diffusion Monte Carlo method, and the inclusion of this additive correction allows for good agreement with available deep-inelastic neutron scattering data.

Familiality and SNP heritability of age at onset and episodicity in major depressive disorder.

BACKGROUND: Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability). METHOD: For investigating familiality, we used 691 families with 2-5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software. RESULTS: Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity. CONCLUSIONS: AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.

Kinematic reduction of reaction-diffusion fronts with multiplicative noise. Derivation of stochastic sharp-interface equations

We study the dynamics of generic reaction-diffusion fronts, including pulses and chemical waves, in the presence of multiplicative noise. We discuss the connection between the reaction-diffusion Langevin-like field equations and the kinematic (eikonal) description in terms of a stochastic moving-boundary or sharp-interface approximation. We find that the effective noise is additive and we relate its strength to the noise parameters in the original field equations, to first order in noise strength, but including a partial resummation to all orders which captures the singular dependence on the microscopic cutoff associated with the spatial correlation of the noise. This dependence is essential for a quantitative and qualitative understanding of fluctuating fronts, affecting both scaling properties and nonuniversal quantities. Our results predict phenomena such as the shift of the transition point between the pushed and pulled regimes of front propagation, in terms of the noise parameters, and the corresponding transition to a non-Kardar-Parisi-Zhang universality class. We assess the quantitative validity of the results in several examples including equilibrium fluctuations and kinetic roughening. We also predict and observe a noise-induced pushed-pulled transition. The analytical predictions are successfully tested against rigorous results and show excellent agreement with numerical simulations of reaction-diffusion field equations with multiplicative noise.

Growth of unstable interfaces in disordered media

The effects of a disordered medium in the growth of unstable interfaces are studied by means of two local models with multiplicative and additive quenched disorder, respectively. For short times and large pushing the multiplicative quenched disorder is equivalent to a time-dependent noise. In this regime, the linear dispersion relation contains a destabilizing contribution introduced by the noise. For long times, the interface always gets pinned. We model the systematics of the pinned shapes by means of an effective nonlinear model. These results show good agreement with numerical simulations. For the additive noise we find numerically that a depinning transition occurs.

Colored noise in spatially extended systems

We study the effects of time and space correlations of an external additive colored noise on the steady-state behavior of a time-dependent Ginzburg-Landau model. Simulations show the existence of nonequilibrium phase transitions controlled by both the correlation time and length of the noise. A Fokker-Planck equation and the steady probability density of the process are obtained by means of a theoretical approximation.

Building predictive models of soil particle-size distribution

Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index). The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd) of soils in regions of complex geology.