Evidence for selection on coloration in a Panamanian poison frog: a coalescent-based approach

Aim The strawberry poison frog, Oophaga pumilio, has undergone a remarkable radiation of colour morphs in the Bocas del Toro archipelago in Panama. This species shows extreme variation in colour and pattern between populations that have been geographically isolated for < 10,000 years. While previous research has suggested the involvement of divergent selection, to date no quantitative test has examined this hypothesis. Location Bocas del Toro archipelago, Panama. Methods We use a combination of population genetics, phylogeography and phenotypic analyses to test for divergent selection in coloration in O. pumilio. Tissue samples of 88 individuals from 15 distinct populations were collected. Using these data, we developed a gene tree using the mitochondrial DNA (mtDNA) d-loop region. Using parameters derived from our mtDNA phylogeny, we predicted the coalescence of a hypothetical nuclear gene underlying coloration. We collected spectral reflectance and body size measurements on 94 individuals from four of the populations and performed a quantitative analysis of phenotypic divergence. Results The mtDNA d-loop tree revealed considerable polyphyly across populations. Coalescent reconstructions of gene trees within population trees revealed incomplete genotypic sorting among populations. The quantitative analysis of phenotypic divergence revealed complete lineage sorting by colour, but not by body size: populations showed non-overlapping variation in spectral reflectance measures of body coloration, while variation in body size did not separate populations. Simulations of the coalescent using parameter values derived from our empirical analyses demonstrated that the level of sorting among populations seen in colour cannot reasonably be attributed to drift. Main conclusions These results imply that divergence in colour, but not body size, is occurring at a faster rate than expected under neutral processes. Our study provides the first quantitative support for the claim that strong diversifying selection underlies colour variation in the strawberry poison frog.

Tracing of 15N in a mountain spruce forest: comparison of experimental data with th TRACE model

Despite numerous studies about nitrogen-cycling in forest ecosystems, many uncertainties remain, especially regarding the longer-term nitrogen accumulation. To contribute to filling this gap, the dynamic process-based model TRACE, with the ability to simulate 15N tracer redistribution in forest ecosystems was used to study N cycling processes in a mountain spruce forest of the northern edge of the Alps in Switzerland (Alptal, SZ). Most modeling analyses of N-cycling and C-N interactions have very limited ability to determine whether the process interactions are captured correctly. Because the interactions in such a system are complex, it is possible to get the whole-system C and N cycling right in a model without really knowing if the way the model combines fine-scale interactions to derive whole-system cycling is correct. With the possibility to simulate 15N tracer redistribution in ecosystem compartments, TRACE features a very powerful tool for the validation of fine-scale processes captured by the model. We first adapted the model to the new site (Alptal, Switzerland; long-term low-dose N-amendment experiment) by including a new algorithm for preferential water flow and by parameterizing of differences in drivers such as climate, N deposition and initial site conditions. After the calibration of key rates such as NPP and SOM turnover, we simulated patterns of 15N redistribution to compare against 15N field observations from a large-scale labeling experiment. The comparison of 15N field data with the modeled redistribution of the tracer in the soil horizons and vegetation compartments shows that the majority of fine-scale processes are captured satisfactorily. Particularly, the model is able to reproduce the fact that the largest part of the N deposition is immobilized in the soil. The discrepancies of 15N recovery in the LF and M soil horizon can be explained by the application method of the tracer and by the retention of the applied tracer by the well developed moss layer, which is not considered in the model. Discrepancies in the dynamics of foliage and litterfall 15N recovery were also observed and are related to the longevity of the needles in our mountain forest. As a next step, we will use the final Alptal version of the model to calculate the effects of climate change (temperature, CO2) and N deposition on ecosystem C sequestration in this regionally representative Norway spruce (Picea abies) stand.

Effect of Methodological and Ecological Approaches on Heterogeneity of Nest-Site Selection of a Long-Lived Vulture

The application of scientific-based conservation measures requires that sampling methodologies in studies modelling similar ecological aspects produce comparable results making easier their interpretation. We aimed to show how the choice of different methodological and ecological approaches can affect conclusions in nest-site selection studies along different Palearctic meta-populations of an indicator species. First, a multivariate analysis of the variables affecting nest-site selection in a breeding colony of cinereous vulture (Aegypius monachus) in central Spain was performed. Then, a meta-analysis was applied to establish how methodological and habitat-type factors determine differences and similarities in the results obtained by previous studies that have modelled the forest breeding habitat of the species. Our results revealed patterns in nesting-habitat modelling by the cinereous vulture throughout its whole range: steep and south-facing slopes, great cover of large trees and distance to human activities were generally selected. The ratio and situation of the studied plots (nests/random), the use of plots vs. polygons as sampling units and the number of years of data set determined the variability explained by the model. Moreover, a greater size of the breeding colony implied that ecological and geomorphological variables at landscape level were more influential. Additionally, human activities affected in greater proportion to colonies situated in Mediterranean forests. For the first time, a meta-analysis regarding the factors determining nest-site selection heterogeneity for a single species at broad scale was achieved. It is essential to homogenize and coordinate experimental design in modelling the selection of species' ecological requirements in order to avoid that differences in results among studies would be due to methodological heterogeneity. This would optimize best conservation and management practices for habitats and species in a global context.

Enhanced Atlantic subpolar gyre variability through baroclinic threshold in a coarse resolution model

Direct observations, satellite measurements and paleo records reveal strong variability in the Atlantic subpolar gyre on various time scales. Here we show that variations of comparable amplitude can only be simulated in a coupled climate model in the proximity of a dynamical threshold. The threshold and the associated dynamic response is due to a positive feedback involving increased salt transport in the subpolar gyre and enhanced deep convection in its centre. A series of sensitivity experiments is performed with a coarse resolution ocean general circulation model coupled to a statistical-dynamical atmosphere model which in itself does not produce atmospheric variability. To simulate the impact of atmospheric variability, the model system is perturbed with freshwater forcing of varying, but small amplitude and multi-decadal to centennial periodicities and observational variations in wind stress. While both freshwater and wind-stress-forcing have a small direct effect on the strength of the subpolar gyre, the magnitude of the gyre's response is strongly increased in the vicinity of the threshold. Our results indicate that baroclinic self-amplification in the North Atlantic ocean can play an important role in presently observed SPG variability and thereby North Atlantic climate variability on multi-decadal scales.

Effects of local continuous release of brain derived neurotrophic factor (BDNF) on peripheral nerve regeneration in a rat model

The purpose of this study was to evaluate the effect of continuously released BDNF on peripheral nerve regeneration in a rat model. Initial in vitro evaluation of calcium alginate prolonged-release-capsules (PRC) proved a consistent release of BDNF for a minimum of 8 weeks. In vivo, a worst case scenario was created by surgical removal of a 20-mm section of the sciatic nerve of the rat. Twenty-four autologous fascia tubes were filled with calcium alginate spheres and sutured to the epineurium of both nerve ends. The animals were divided into 3 groups. In group 1, the fascial tube contained plain calcium alginate spheres. In groups 2 and 3, the fascial tube contained calcium alginate spheres with BDNF alone or BDNF stabilized with bovine serum albumin, respectively. The autocannibalization of the operated extremity was clinically assessed and documented in 12 additional rats. The regeneration was evaluated histologically at 4 weeks and 10 weeks in a blinded manner. The length of nerve fibers and the numbers of axons formed in the tube was measured. Over a 10-week period, axons have grown significantly faster in groups 2 and 3 with continuously released BDNF compared to the control. The rats treated with BDNF (groups 2 and 3) demonstrated significantly less autocannibalization than the control group (group 1). These results suggest that BDNF may not only stimulate faster peripheral nerve regeneration provided there is an ideal, biodegradable continuous delivery system but that it significantly reduces the neuropathic pain in the rat model.

Adjunctive local antibiotic therapy in the treatment of peri-implantitis II: clinical and radiographic outcomes

AIM: To monitor over 12 months clinical and radiographic changes occurring after adjunctive local delivery of minocycline microspheres for the treatment of peri-implantitis. MATERIAL AND METHODS: In 25 partially edentulous subjects, 31 implants diagnosed with peri-implantitis were treated. Three weeks after oral hygiene instruction, mechanical debridement and local antiseptic cleansing using 0.2% chlorhexidine gel, baseline (Day 0) parameters were recorded. Minocycline microspheres (Arestin) were locally delivered to each implant site with bone loss and a probing pocket depth (PPD) >or=5 mm. Rescue therapy with Arestin was allowed at Days 180 and 270 at any site exhibiting an increase in PPD>or=2 mm from the previous visit. The following clinical parameters were recorded at four sites/implant at Day 0, 10, 30, 60, 90, 180, 270 and 360: PPD, clinical attachment level (CAL), bleeding on probing (BOP) and plaque index (PlI). RESULTS: Six implants in six subjects were either rescued or exited because of persisting active peri-implantitis. Successful implants showed a statistically significant reduction in both PPD and percentage of sites with BOP between baseline and Day 360 (P<0.05). At mesial implant sites, the mean PPD reduction amounted to 1.6 mm (95% CI: 0.9-2.2 mm, P<0.001) and was accompanied by a statistically significant reduction of the BOP value (P<0.001). Binary regression analysis showed that the clinical parameters and smoking history could not discriminate between successfully treated and rescued or exited implants at any observation time point. CONCLUSION: Non-surgical mechanical treatment of peri-implantitis lesions with adjunctive local delivery of microencapsulated minocycline led to positive effects on clinical parameters up to 12 months.

Survival Analysis with Large Dimensional Covariates: An Application in Microarray Studies

Use of microarray technology often leads to high-dimensional and low- sample size data settings. Over the past several years, a variety of novel approaches have been proposed for variable selection in this context. However, only a small number of these have been adapted for time-to-event data where censoring is present. Among standard variable selection methods shown both to have good predictive accuracy and to be computationally efficient is the elastic net penalization approach. In this paper, adaptation of the elastic net approach is presented for variable selection both under the Cox proportional hazards model and under an accelerated failure time (AFT) model. Assessment of the two methods is conducted through simulation studies and through analysis of microarray data obtained from a set of patients with diffuse large B-cell lymphoma where time to survival is of interest. The approaches are shown to match or exceed the predictive performance of a Cox-based and an AFT-based variable selection method. The methods are moreover shown to be much more computationally efficient than their respective Cox- and AFT- based counterparts.

On the Behaviour of Marginal and Conditional Akaike Information Criteria in Linear Mixed Models

In linear mixed models, model selection frequently includes the selection of random effects. Two versions of the Akaike information criterion (AIC) have been used, based either on the marginal or on the conditional distribution. We show that the marginal AIC is no longer an asymptotically unbiased estimator of the Akaike information, and in fact favours smaller models without random effects. For the conditional AIC, we show that ignoring estimation uncertainty in the random effects covariance matrix, as is common practice, induces a bias that leads to the selection of any random effect not predicted to be exactly zero. We derive an analytic representation of a corrected version of the conditional AIC, which avoids the high computational cost and imprecision of available numerical approximations. An implementation in an R package is provided. All theoretical results are illustrated in simulation studies, and their impact in practice is investigated in an analysis of childhood malnutrition in Zambia.

Orthotopic transplantation of v-src-expressing glioma cell lines into immunocompetent mice: establishment of a new transplantable in vivo model for malignant glioma

OBJECT: The aim of this study was to develop and characterize a new orthotopic, syngeneic, transplantable mouse brain tumor model by using the cell lines Tu-9648 and Tu-2449, which were previously isolated from tumors that arose spontaneously in glial fibrillary acidic protein (GFAP)-v-src transgenic mice. METHODS: Striatal implantation of a 1-microl suspension of 5000 to 10,000 cells from either clone into syngeneic B6C3F1 mice resulted in tumors that were histologically identified as malignant gliomas. Prior subcutaneous inoculations with irradiated autologous cells inhibited the otherwise robust development of a microscopically infiltrating malignant glioma. Untreated mice with implanted tumor cells were killed 12 days later, when the resultant gliomas were several millimeters in diameter. Immunohistochemically, the gliomas displayed both the astroglial marker GFAP and the oncogenic form of signal transducer and activator of transcription-3 (Stat3). This form is called tyrosine-705 phosphorylated Stat3, and is found in many malignant entities, including human gliomas. Phosphorylated Stat3 was particularly prominent, not only in the nucleus but also in the plasma membrane of peripherally infiltrating glioma cells, reflecting persistent overactivation of the Janus kinase/Stat3 signal transduction pathway. The Tu-2449 cells exhibited three non-random structural chromosomal aberrations, including a deletion of the long arm of chromosome 2 and an apparently balanced translocation between chromosomes 1 and 3. The GFAP-v-src transgene was mapped to the pericentromeric region of chromosome 18. CONCLUSIONS: The high rate of engraftment, the similarity to the high-grade malignant glioma of origin, and the rapid, locally invasive growth of these tumors should make this murine model useful in testing novel therapies for human malignant gliomas.

Species-level selection reduces selfishness through competitive exclusion

Adaptation does not necessarily lead to traits which are optimal for the population. This is because selection is often the strongest at the individual or gene level. The evolution of selfishness can lead to a 'tragedy of the commons', where traits such as aggression or social cheating reduce population size and may lead to extinction. This suggests that species-level selection will result whenever species differ in the incentive to be selfish. We explore this idea in a simple model that combines individual-level selection with ecology in two interacting species. Our model is not influenced by kin or trait-group selection. We find that individual selection in combination with competitive exclusion greatly increases the likelihood that selfish species go extinct. A simple example of this would be a vertebrate species that invests heavily into squabbles over breeding sites, which is then excluded by a species that invests more into direct reproduction. A multispecies simulation shows that these extinctions result in communities containing species that are much less selfish. Our results suggest that species-level selection and community dynamics play an important role in regulating the intensity of conflicts in natural populations.

Wolf habitat selection at the territory level : seasonal and interannual variation and influence on reproductive success

Habitat selection has been one of the main research topics in ecology for decades. Nevertheless, many aspects of habitat selection still need to be explored. In particular, previous studies have overlooked the importance of temporal variation in habitat selection and the value of including data on reproductive success in order to describe the best quality habitat for a species. We used data collected from radiocollared wolves in Yellowstone National Park (USA), between 1996 and 2008, to describe wolf habitat selection. In particular, we aimed to identify i) seasonal differences in wolf habitat selection, ii) factors influencing interannual variation in habitat selection, and iii) the effect of habitat selection on wolf reproductive success. We used probability density functions to describe wolf habitat use and habitat coverages to represent the habitat available to wolves. We used regression analysis to connect habitat use with habitat characteristics and habitat selection with reproductive success. Our most relevant result was discovering strong interannual variability in wolf habitat selection. This variability was in part explained by pack identity and differences in litter size and leadership of a pack between two years (summer) and in pack size and precipitation (winter). We also detected some seasonal differences. Wolves selected open habitats, intermediate elevations, intermediate distances from roads, and avoided steep slopes in late winter. They selected areas close to roads and avoided steep slopes in summer. In early winter, wolves selected wetlands, herbaceous and shrub vegetation types, and areas at intermediate elevation and distance from roads. Surprisingly, the habitat characteristics selected by wolves were not useful in predicting reproductive success. We hypothesize that interannual variability in wolf habitat selection may be too strong to detect effects on reproductive success. Moreover, prey availability and competitor pressure may also have an influence on wolf reproductive success, which we did not assess. This project demonstrated how important temporal variation is in shaping patterns of habitat selection. We still believe in the value of running long-term studies, but the effect of temporal variation should always be taken into account.

Implementation of a phenomenological evaporation model into a porous network simulation for water management in low temperature fuel cells

A phenomenological transition film evaporation model was introduced to a pore network model with the consideration of pore radius, contact angle, non-isothermal interface temperature, microscale fluid flows and heat and mass transfers. This was achieved by modeling the transition film region of the menisci in each pore throughout the porous transport layer of a half-cell polymer electrolyte membrane (PEM) fuel cell. The model presented in this research is compared with the standard diffusive fuel cell modeling approach to evaporation and shown to surpass the conventional modeling approach in terms of predicting the evaporation rates in porous media. The current diffusive evaporation models used in many fuel cell transport models assumes a constant evaporation rate across the entire liquid-air interface. The transition film model was implemented into the pore network model to address this issue and create a pore size dependency on the evaporation rates. This is accomplished by evaluating the transition film evaporation rates determined by the kinetic model for every pore containing liquid water in the porous transport layer (PTL). The comparison of a transition film and diffusive evaporation model shows an increase in predicted evaporation rates for smaller pore sizes with the transition film model. This is an important parameter when considering the micro-scaled pore sizes seen in the PTL and becomes even more substantial when considering transport in fuel cells containing an MPL, or a large variance in pore size. Experimentation was performed to validate the transition film model by monitoring evaporation rates from a non-zero contact angle water droplet on a heated substrate. The substrate was a glass plate with a hydrophobic coating to reduce wettability. The tests were performed at a constant substrate temperature and relative humidity. The transition film model was able to accurately predict the drop volume as time elapsed. By implementing the transition film model to a pore network model the evaporation rates present in the PTL can be more accurately modeled. This improves the ability of a pore network model to predict the distribution of liquid water and ultimately the level of flooding exhibited in a PTL for various operating conditions.

Simulating the evolution of a clonal trait in plants with sexual and vegetative reproduction

Aims Phenotypic optimality models neglect genetics. However, especially when heterozygous genotypes ire fittest, evolving allele, genotype and phenotype frequencies may not correspond to predicted optima. This was not previously addressed for organisms with complex life histories. Methods Therefore, we modelled the evolution of a fitness-relevant trait of clonal plants, stolon internode length. We explored the likely case of air asymmetric unimodal fitness profile with three model types. In constant selection models (CSMs), which are gametic, but not spatially explicit, evolving allele frequencies in the one-locus and five-loci cases did not correspond to optimum stolon internode length predicted by the spatially explicit, but not gametic, phenotypic model. This deviation was due to the asymmetry of the fitness profile. Gametic, spatially explicit individual-based (SEIB) modeling allowed us relaxing the CSM assumptions of constant selection with exclusively sexual reproduction. Important findings For entirely vegetative or sexual reproduction, predictions. of the gametic SEIB model were close to the ones of spatially explicit CSMs gametic phenotypic models, hut for mixed modes of reproduction they appoximated those of gametic, not spatially explicit CSMs. Thus, in contrast to gametic SEIB models, phenotypic models and, especially for few loci, also CSMs can be very misleading. We conclude that the evolution of trails governed by few quantitative trait loci appears hardly predictable by simple models, that genetic algorithms aiming at technical optimization may actually, miss the optimum and that selection may lead to loci with smaller effects, in derived compared with ancestral lines.