A genetically explicit model of speciation by sensory drive within a continuous population in aquatic environments

BACKGROUND: The sensory drive hypothesis predicts that divergent sensory adaptation in different habitats may lead to premating isolation upon secondary contact of populations. Speciation by sensory drive has traditionally been treated as a special case of speciation as a byproduct of adaptation to divergent environments in geographically isolated populations. However, if habitats are heterogeneous, local adaptation in the sensory systems may cause the emergence of reproductively isolated species from a single unstructured population. In polychromatic fishes, visual sensitivity might become adapted to local ambient light regimes and the sensitivity might influence female preferences for male nuptial color. In this paper, we investigate the possibility of speciation by sensory drive as a byproduct of divergent visual adaptation within a single initially unstructured population. We use models based on explicit genetic mechanisms for color vision and nuptial coloration. RESULTS: We show that in simulations in which the adaptive evolution of visual pigments and color perception are explicitly modeled, sensory drive can promote speciation along a short selection gradient within a continuous habitat and population. We assumed that color perception evolves to adapt to the modal light environment that individuals experience and that females prefer to mate with males whose nuptial color they are most sensitive to. In our simulations color perception depends on the absorption spectra of an individual's visual pigments. Speciation occurred most frequently when the steepness of the environmental light gradient was intermediate and dispersal distance of offspring was relatively small. In addition, our results predict that mutations that cause large shifts in the wavelength of peak absorption promote speciation, whereas we did not observe speciation when peak absorption evolved by stepwise mutations with small effect. CONCLUSION: The results suggest that speciation can occur where environmental gradients create divergent selection on sensory modalities that are used in mate choice. Evidence for such gradients exists from several animal groups, and from freshwater and marine fishes in particular. The probability of speciation in a continuous population under such conditions may then critically depend on the genetic architecture of perceptual adaptation and female mate choice.

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.

Evolutionary demography of long-lived monocarpic perennials: a time-lagged integral projection model

1. The evolution of flowering strategies (when and at what size to flower) in monocarpic perennials is determined by balancing current reproduction with expected future reproduction, and these are largely determined by size-specific patterns of growth and survival. However, because of the difficulty in following long-lived individuals throughout their lives, this theory has largely been tested using short-lived species (< 5 years). 2. Here, we tested this theory using the long-lived monocarpic perennial Campanula thyrsoides which can live up to 16 years. We used a novel approach that combined permanent plot and herb chronology data from a 3-year field study to parameterize and validate integral projection models (IPMs). 3. Similar to other monocarpic species, the rosette leaves of C. thyrsoides wither over winter and so size cannot be measured in the year of flowering. We therefore extended the existing IPM framework to incorporate an additional time delay that arises because flowering demography must be predicted from rosette size in the year before flowering. 4. We found that all main demographic functions (growth, survival probability, flowering probability and fecundity) were strongly size-dependent and there was a pronounced threshold size of flowering. There was good agreement between the predicted distribution of flowering ages obtained from the IPMs and that estimated in the field. Mostly, there was good agreement between the IPM predictions and the direct quantitative field measurements regarding the demographic parameters lambda, R-0 and T. We therefore conclude that the model captures the main demographic features of the field populations. 5. Elasticity analysis indicated that changes in the survival and growth function had the largest effect (c. 80%) on lambda and this was considerably larger than in short-lived monocarps. We found only weak selection pressure operating on the observed flowering strategy which was close to the predicted evolutionary stable strategy. 6. Synthesis. The extended IPM accurately described the demography of a long-lived monocarpic perennial using data collected over a relatively short period. We could show that the evolution of flowering strategies in short- and long-lived monocarps seem to follow the same general rules but with a longevity-related emphasis on survival over fecundity.

Selection on floral traits through male fertility in a natural plant population

Most studies on selection in plants estimate female fitness components and neglect male mating success, although the latter might also be fundamental to understand adaptive evolution. Information from molecular genetic markers can be used to assess determinants of male mating success through parentage analyses. We estimated paternal selection gradients on floral traits in a large natural population of the herb Mimulus guttatus using a paternity probability model and maximum likelihood methods. This analysis revealed more significant selection gradients than a previous analysis based on regression of estimated male fertilities on floral traits. There were differences between results of univariate and multivariate analyses most likely due to the underlying covariance structure of the traits. Multivariate analysis, which corrects for the covariance structure of the traits, indicated that male mating success declined with distance from and depended on the direction to the mother plants. Moreover, there was directional selection for plants with fewer open flowers which have smaller corollas, a smaller anther-stigma separation, more red dots on the corolla and a larger fluctuating asymmetry therein. For most of these traits, however, there was also stabilizing selection indicating that there are intermediate optima for these traits. The large number of significant selection gradients in this study shows that even in relatively large natural populations where not all males can be sampled, it is possible to detect significant paternal selection gradients, and that such studies can give us valuable information required to better understand adaptive plant evolution.

A Combinatorial Approach to the Variable Selection in Multiple Linear Regression: Analysis of Selwood et al Data set -A Case Study.

A combinatorial protocol (CP) is introduced here to interface it with the multiple linear regression (MLR) for variable selection. The efficiency of CP-MLR is primarily based on the restriction of entry of correlated variables to the model development stage. It has been used for the analysis of Selwood et al data set [16], and the obtained models are compared with those reported from GFA [8] and MUSEUM [9] approaches. For this data set CP-MLR could identify three highly independent models (27, 28 and 31) with Q2 value in the range of 0.632-0.518. Also, these models are divergent and unique. Even though, the present study does not share any models with GFA [8], and MUSEUM [9] results, there are several descriptors common to all these studies, including the present one. Also a simulation is carried out on the same data set to explain the model formation in CP-MLR. The results demonstrate that the proposed method should be able to offer solutions to data sets with 50 to 60 descriptors in reasonable time frame. By carefully selecting the inter-parameter correlation cutoff values in CP-MLR one can identify divergent models and handle data sets larger than the present one without involving excessive computer time.

How Minds Work: A Cognitive Theory of Everything - a Tutorial on the IDA Model of Cognition

The IDA model of cognition is a fully integrated artificial cognitive system reaching across the full spectrum of cognition, from low-level perception/action to high-level reasoning. Extensively based on empirical data, it accurately reflects the full range of cognitive processes found in natural cognitive systems. As a source of plausible explanations for very many cognitive processes, the IDA model provides an ideal tool to think with about how minds work. This online tutorial offers a reasonably full account of the IDA conceptual model, including background material. It also provides a high-level account of the underlying computational “mechanisms of mind” that constitute the IDA computational model.

On Transport Service Selection in Intermodal Rail/Road Distribution Networks

Intermodal rail/road freight transport constitutes an alternative to long-haul road transport for the distribution of large volumes of goods. The paper introduces the intermodal transportation problem for the tactical planning of mode and service selection. In rail mode, shippers either book train capacity on a per-unit basis or charter block trains completely. Road mode is used for short-distance haulage to intermodal terminals and for direct shipments to customers. We analyze the competition of road and intermodal transportation with regard to freight consolidation and service cost on a model basis. The approach is applied to a distribution system of an industrial company serving customers in eastern Europe. The case study investigates the impact of transport cost and consolidation on the optimal modal split.

Statistical inference for the optimal approximating model

In the setting of high-dimensional linear models with Gaussian noise, we investigate the possibility of confidence statements connected to model selection. Although there exist numerous procedures for adaptive (point) estimation, the construction of adaptive confidence regions is severely limited (cf. Li in Ann Stat 17:1001–1008, 1989). The present paper sheds new light on this gap. We develop exact and adaptive confidence regions for the best approximating model in terms of risk. One of our constructions is based on a multiscale procedure and a particular coupling argument. Utilizing exponential inequalities for noncentral χ2-distributions, we show that the risk and quadratic loss of all models within our confidence region are uniformly bounded by the minimal risk times a factor close to one.

Selection criteria for selective dorsal rhizotomy in children with spastic cerebral palsy: a systematic review of the literature

AIM Information regarding the selection procedure for selective dorsal rhizotomy (SDR) in children with spastic cerebral palsy (CP) is scarce. Therefore, the aim of this study was to summarize the selection criteria for SDR in children with spastic CP. METHOD A systematic review was carried out using the following databases: MEDLINE, CINAHL, EMBASE, PEDro, and the Cochrane Library. Additional studies were identified in the reference lists. Search terms included 'selective dorsal rhizotomy', 'functional posterior rhizotomy', 'selective posterior rhizotomy', and 'cerebral palsy'. Studies were selected if they studied mainly children (<18y of age) with spastic CP, if they had an intervention of SDR, if they had a detailed description of the selection criteria, and if they were in English. The levels of evidence, conduct of studies, and selection criteria for SDR were scored. RESULTS Fifty-two studies were included. Selection criteria were reported in 16 International Classification of Functioning, Disability and Health model domains including 'body structure and function' (details concerning spasticity [94%], other movement abnormalities [62%], and strength [54%]), 'activity' (gross motor function [27%]), and 'personal and environmental factors' (age [44%], diagnosis [50%], motivation [31%], previous surgery [21%], and follow-up therapy [31%]). Most selection criteria were not based on standardized measurements. INTERPRETATION Selection criteria for SDR vary considerably. Future studies should describe clearly the selection procedure. International meetings of experts should develop more uniform consensus guidelines, which could form the basis for selecting candidates for SDR.

A Coordinated and Systematic Model for Adopting, Implementing and Maintaining Effective Sexual Health Education Programs in Schools

Getting evidence-based sexual health education activities into schools can be a complicated process. Working models that assist our educational system in the selection, implementation, and maintenance of effective school-based adolescent health programs are needed. Replicating sexual health programs in school-based settings: A model for schools provides a comprehensive and applied approach that engages all of the important stakeholders within a school district. The results from this study hold much potential to inform Texas and the nation about how a coordinated and practical model can assist school districts to increase the use of evidence-based programs addressing teen pregnancy prevention and sexual health issues.

Frequency-Dependent Selection Predicts Patterns of Radiations and Biodiversity

Most empirical studies support a decline in speciation rates through time, although evidence for constant speciation rates also exists. Declining rates have been explained by invoking pre-existing niches, whereas constant rates have been attributed to non-adaptive processes such as sexual selection and mutation. Trends in speciation rate and the processes underlying it remain unclear, representing a critical information gap in understanding patterns of global diversity. Here we show that the temporal trend in the speciation rate can also be explained by frequency-dependent selection. We construct a frequency-dependent and DNA sequence-based model of speciation. We compare our model to empirical diversity patterns observed for cichlid fish and Darwin's finches, two classic systems for which speciation rates and richness data exist. Negative frequency-dependent selection predicts well both the declining speciation rate found in cichlid fish and explains their species richness. For groups like the Darwin's finches, in which speciation rates are constant and diversity is lower, speciation rate is better explained by a model without frequency-dependent selection. Our analysis shows that differences in diversity may be driven by incipient species abundance with frequency-dependent selection. Our results demonstrate that genetic-distance-based speciation and frequency-dependent selection are sufficient to explain the high diversity observed in natural systems and, importantly, predict decay through time in speciation rate in the absence of pre-existing niches.

Sexual dimorphism and directional sexual selection on aposematic signals in a poison frog

It is commonly assumed that natural selection imposed by predators is the prevailing force driving the evolution of aposematic traits. Here, we demonstrate that aposematic signals are shaped by sexual selection as well. We evaluated sexual selection for coloration brightness in populations of the poison frog Oophaga [Dendrobates] pumilio in Panama's Bocas del Toro archipelago. We assessed female preferences for brighter males by manipulating the perceived brightness of spectrally matched males in two-way choice experiments. We found strong female preferences for bright males in two island populations and weaker or ambiguous preferences in females from mainland populations. Spectral reflectance measurements, coupled with an O. pumilio-specific visual processing model, showed that O. pumilio coloration was significantly brighter in island than in mainland morphs. In one of the island populations (Isla Solarte), males were significantly more brightly colored than females. Taken together, these results provide evidence for directional sexual selection on aposematic coloration and document sexual dimorphism in vertebrate warning coloration. Although aposematic signals have long been upheld as exemplars of natural selection, our results show that sexual selection should not be ignored in studies of aposematic evolution.

Development of a Bayesian Joint Logistic Model to Better Study the Association between Haplotypes and Disease

In 2011, there will be an estimated 1,596,670 new cancer cases and 571,950 cancer-related deaths in the US. With the ever-increasing applications of cancer genetics in epidemiology, there is great potential to identify genetic risk factors that would help identify individuals with increased genetic susceptibility to cancer, which could be used to develop interventions or targeted therapies that could hopefully reduce cancer risk and mortality. In this dissertation, I propose to develop a new statistical method to evaluate the role of haplotypes in cancer susceptibility and development. This model will be flexible enough to handle not only haplotypes of any size, but also a variety of covariates. I will then apply this method to three cancer-related data sets (Hodgkin Disease, Glioma, and Lung Cancer). I hypothesize that there is substantial improvement in the estimation of association between haplotypes and disease, with the use of a Bayesian mathematical method to infer haplotypes that uses prior information from known genetics sources. Analysis based on haplotypes using information from publically available genetic sources generally show increased odds ratios and smaller p-values in both the Hodgkin, Glioma, and Lung data sets. For instance, the Bayesian Joint Logistic Model (BJLM) inferred haplotype TC had a substantially higher estimated effect size (OR=12.16, 95% CI = 2.47-90.1 vs. 9.24, 95% CI = 1.81-47.2) and more significant p-value (0.00044 vs. 0.008) for Hodgkin Disease compared to a traditional logistic regression approach. Also, the effect sizes of haplotypes modeled with recessive genetic effects were higher (and had more significant p-values) when analyzed with the BJLM. Full genetic models with haplotype information developed with the BJLM resulted in significantly higher discriminatory power and a significantly higher Net Reclassification Index compared to those developed with haplo.stats for lung cancer. Future analysis for this work could be to incorporate the 1000 Genomes project, which offers a larger selection of SNPs can be incorporated into the information from known genetic sources as well. Other future analysis include testing non-binary outcomes, like the levels of biomarkers that are present in lung cancer (NNK), and extending this analysis to full GWAS studies.

Detection and sequence analysis of a nickel-induced mutation in a retroviral model system

We have developed a novel way to assess the mutagenicity of environmentally important metal carcinogens, such as nickel, by creating a positive selection system based upon the conditional expression of a retroviral transforming gene. The target gene is the v-mos gene in MuSVts110, a murine retrovirus possessing a growth temperature dependent defect in expression of the transforming gene due to viral RNA splicing. In normal rat kidney cells infected with MuSVts110 (6m2 cells), splicing of the MuSVts110 RNA to form the mRNA from which the transforming protein, p85$\sp{\rm gag-mos}$, is translated is growth-temperature dependent, occurring at 33 C and below but not at 39 C and above. This splicing "defect" is mediated by cis-acting viral sequences. Nickel chloride treatment of 6m2 cells followed by growth at 39 C, allowed the selection of "revertant" cells which constitutively express p85$\sp{\rm gag-mos}$ due to stable changes in the viral RNA splicing phenotype, suggesting that nickel, a carcinogen whose mutagenicity has not been well established, could induce mutations in mammalian genes. We also show by direct sequencing of PCR-amplified integrated MuSVts110 DNA from a 6m2 nickel-revertant cell line that the nickel-induced mutation affecting the splicing phenotype is a cis-acting 70-base duplication of a region of the viral DNA surrounding the 3$\sp\prime$ splice site. These findings provide the first example of the molecular basis for a nickel-induced DNA lesion and establish the mutagenicity of this potent carcinogen. ^