Benchmark Dose Profiles for Joint‐Action Quantal Data in Quantitative Risk Assessment

Summary Benchmark analysis is a widely used tool in public health risk analysis. Therein, estimation of minimum exposure levels, called Benchmark Doses (BMDs), that induce a prespecified Benchmark Response (BMR) is well understood for the case of an adverse response to a single stimulus. For cases where two agents are studied in tandem, however, the benchmark approach is far less developed. This article demonstrates how the benchmark modeling paradigm can be expanded from the single‐dose setting to joint‐action, two‐agent studies. Focus is on response outcomes expressed as proportions. Extending the single‐exposure setting, representations of risk are based on a joint‐action dose–response model involving both agents. Based on such a model, the concept of a benchmark profile (BMP) – a two‐dimensional analog of the single‐dose BMD at which both agents achieve the specified BMR – is defined for use in quantitative risk characterization and assessment. The resulting, joint, low‐dose guidelines can improve public health planning and risk regulation when dealing with low‐level exposures to combinations of hazardous agents.     

Inferring the evolutionary history of divergence despite gene flow in a lizard species,Scincella lateralis (Scincidae), composed of cryptic lineages

Although recent radiations are fruitful for studying the process of speciation, they are difficult to characterize and require the use of multiple loci and analytical methods that account for processes such as gene flow and genetic drift. Using multilocus sequence data, we combine hierarchical cluster analysis, coalescent species tree inference, and isolation‐with‐migration analysis to investigate evolutionary relationships among cryptic lineages of North American ground skinks. We also estimate the extent that gene flow has accompanied or followed diversification, and also attempt to account for and minimize the influence of gene flow when reconstructing relationships. The data best support seven largely parapatric populations that are broadly concordant with mitochondrial (mt)DNA phylogeography throughout most of the species range, although they fail to fully represent extensive mtDNA divergence along the Gulf Coast. Relationships within and among three broad geographical groups are well supported, despite evidence of gene flow among them. Rejection of an allopatric divergence model partially depends on the inclusion of samples from near parapatric boundaries in the analyses, suggesting that allopatric divergence followed by recent migration may best explain migration rate estimates. Accounting for geographical variation in patterns of gene flow can improve estimates of migration–divergence parameters and minimize the influence of contemporary gene flow on phylogenetic inference. © 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, ?? , ??–??.     

Modelling the global distribution of fungal species: new insights into microbial cosmopolitanism

Microbes are usually believed to have cosmopolitan distributions. However, for estimating the global distributions of microorganisms, discriminating among cryptic species and eliminating undersampling biases are important challenges. We used a novel approach to address these problems and infer the global distribution of a given fungal ecological guild. We collected mushroom‐forming fungi from Yakushima, Japan. We sequenced the internal transcribed spacer 2 (ITS2) from these samples and queried their sequences against GenBank. After identifying similar sequences, we tracked down the geographical origins of samples that yielded those sequences. We used Bayesian zero‐inflated models to allow for species whose DNA sequences have not yet been deposited in GenBank. Results indicated that the geographical distribution of ectomycorrhizal (ECM) fungi was strongly constrained by host specificity, resulting in the occurrence of these fungi intensively in the neighbouring regions. On the other hand, saprotrophic (SAP) fungi were less constrained by climatic conditions, resulting in a much broader distribution range. We inferred that differences in constraints during colonization between ECM and SAP fungi were responsible for the different geographical distribution ranges. We hypothesize that the degree of host/habitat specificity and the degree of isolation of potentially suitable habitats determine microbial biogeographic patterns.     

Recent population decline and selection shape diversity of taxol-related genes

Taxanes are defensive metabolites produced by Taxus species (yews) and used in anticancer therapies. Despite their medical interest, patterns of natural diversity in taxane-related genes are unknown. We examined variation at five main genes of Taxus baccata in the Iberian Peninsula, a region where unique yew genetic resources are endangered. We looked at several gene features and applied complementary neutrality tests, including diversity/divergence tests, tests solely based on site frequency spectrum (SFS) and Zeng's compound tests. To account for specific demography, microsatellite data were used to infer historical changes in population size based on an Approximate Bayesian Computation (ABC) approach. Polymorphism-divergence tests pointed to positive selection for genes TBT and TAT and balancing selection for DBAT. In addition, neutrality tests based on SFS found that while a recent reduction in population size may explain most statistics' values, selection may still be in action in genes TBT and DBAT, at least in some populations. Molecular signatures on taxol genes suggest the action of frequent selective waves with different direction or intensity, possibly related to varying adaptive pressures produced by the host-enemy co-evolution on defence-related genes. Such natural selection processes may have produced taxane variants still undiscovered.     

Inferring subjective states through the observation of actions

Estimating another person''s subjective confidence is crucial for social interaction, but how this inference is achieved is unknown. Previous research has demonstrated that the speed at which people make decisions is correlated with their confidence in their decision. Here, we show that (i) subjects are able to infer the subjective confidence of another person simply through the observation of their actions and (ii) this inference is dependent upon the performance of each subject when executing the action. Crucially, the latter result supports a model in which motor simulation of an observed action mediates the successful understanding of other minds. We conclude that kinematic understanding allows access to the higher-order cognitive processes of others, and that this access plays a central role in social interactions.     

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties¹. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties².Many innovative and useful methods currently exist for creating novel objects and object categories^3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings.First, shape variations are generally imposed by the experimenter^5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints.Second, the existing methods have difficulty capturing the shape complexity of natural objects^11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases.Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or ''tuned''). This allows one to formulate the underlying object recognition tasks in quantitative terms.Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called ''digital embryos'' by simulating the biological process of embryogenesis¹⁴. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection^9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics^15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects^9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be ''printed'' as haptic objects using a conventional 3-D prototyper.We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a ''proof of principle'' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have.Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.     

Are responses of herbivores to environmental variability spatially consistent in alpine ecosystems?

Animal responses to global climate variation might be spatially inconsistent. This may arise from spatial variation in factors limiting populations' growth or from differences in the links between global climate patterns and ecologically relevant local climate variation. For example, the North Atlantic Oscillation (NAO) has a spatially consistent relation to temperature, but inconsistent spatial relation to snow depth in Scandinavia. Furthermore, there are multiple mechanistic ways by which climate may limit animal populations, involving both direct effects through thermoregulation and indirect pathways through trophic interactions. It is conceptually appealing to directly model the predicted mechanistic links. This includes the use of climate variables mimicking such interactions, for example, to use growing degree days (GDD) as a proxy for plant growth rather than average monthly temperature. Using a unique database of autumn body mass of 83331 domestic lambs from the period 1992–2007 in four alpine ranges in Norway, we demonstrate the utility of hierarchical, mechanistic path models fitted using a Bayesian approach to analyse explicitly predicted relationships among environmental variables and between lamb body mass and the environmental variables. We found large spatial variation in strength of responses of autumn lamb body mass to the NAO, to a proxy for plant growth in spring (the Normalized Difference Vegetation Index, NDVI) and effects even differed in direction to local summer climate. Average local temperature outperformed GDD as a predictor of the NDVI, whereas the NAO index in two areas outperformed local weather variables as a predictor of lamb body mass, despite the weaker mechanistic link. Our study highlights that spatial variation in strength of herbivore responses may arise from several processes. Furthermore, mechanistically more appealing measures do not always increase predictive power due to scale of measurement and since global measures may provide more relevant “weather packages” for larger scales.     

Predicting patch occupancy in fragmented landscapes at the rangewide scale for an endangered species: an example of an American warbler

AIM: Our objective was to identify the distribution of the endangered golden-cheeked warbler (Setophaga chrysoparia) in fragmented oak-juniper woodlands by applying a geoadditive semiparametric occupancy model to better assist decision-makers in identifying suitable habitat across the species breeding range on which conservation or mitigation activities can be focused and thus prioritize management and conservation planning. LOCATION: Texas, USA. METHODS: We used repeated double-observer detection/non-detection surveys of randomly selected (n = 287) patches of potential habitat to evaluate warbler patch-scale presence across the species breeding range. We used a geoadditive semiparametric occupancy model with remotely sensed habitat metrics (patch size and landscape composition) to predict patch-scale occupancy of golden-cheeked warblers in the fragmented oak-juniper woodlands of central Texas, USA. RESULTS: Our spatially explicit model indicated that golden-cheeked warbler patch occupancy declined from south to north within the breeding range concomitant with reductions in the availability of large habitat patches. We found that 59% of woodland patches, primarily in the northern and central portions of the warbler's range, were predicted to have occupancy probabilities ≤0.10 with only 3% of patches predicted to have occupancy probabilities >0.90. Our model exhibited high prediction accuracy (area under curve = 0.91) when validated using independently collected warbler occurrence data. MAIN CONCLUSIONS: We have identified a distinct spatial occurrence gradient for golden-cheeked warblers as well as a relationship between two measurable landscape characteristics. Because habitat-occupancy relationships were key drivers of our model, our results can be used to identify potential areas where conservation actions supporting habitat mitigation can occur and identify areas where conservation of future potential habitat is possible. Additionally, our results can be used to focus resources on maintenance and creation of patches that are more likely to harbour viable local warbler populations.     

Causal inference in biomolecular pathways using a Bayesian network approach and an Implicit method

We introduce here the concept of Implicit networks which provide, like Bayesian networks, a graphical modelling framework that encodes the joint probability distribution for a set of random variables within a directed acyclic graph. We show that Implicit networks, when used in conjunction with appropriate statistical techniques, are very attractive for their ability to understand and analyze biological data. Particularly, we consider here the use of Implicit networks for causal inference in biomolecular pathways. In such pathways, an Implicit network encodes dependencies among variables (proteins, genes), can be trained to learn causal relationships (regulation, interaction) between them and then used to predict the biological response given the status of some key proteins or genes in the network. We show that Implicit networks offer efficient methodologies for learning from observations without prior knowledge and thus provide a good alternative to classical inference in Bayesian networks when priors are missing. We illustrate our approach by an application to simulated data for a simplified signal transduction pathway of the epidermal growth factor receptor (EGFR) protein.     

Molecular phylogeny of New World sheath-tailed bats (Emballonuridae: Diclidurini) based on loci from the four genetic transmission systems in mammals

Multiple unlinked loci are surveyed in a methodological approach for mammalian systematics that uses genes from the four pathways of genetic transmission: mitochondrial, autosomal, and X and Y sex chromosomes. Each of these components has different properties, such as effective population size, mutation rate, and recombination, that result in a robust hypothesis of evolutionary history. The utility of this experimental design is tested with bats in the family Emballonuridae and the hypothesis that the New World taxa are monophyletic. Parsimony and Bayesian analyses of the individual data sets give generally congruent topologies with high bootstrap proportions and posterior probabilities for monophyletic clades representing species and genera. The mitochondrial gene has significantly faster rates of substitution, higher levels of homoplasy, and a greater degree of saturation than the nuclear genes that contributed to the loss of phylogenetic signal at deeper branches of the tree. However, there is better resolution and support for the more slowly evolving nuclear introns including a New World clade, indicating a single origin of emballonurid bats in the Neotropics (tribe Diclidurini). One novel subtribe has a hard basal polytomy that is unresolved for all of the nuclear partitions, suggesting a rapid burst of evolution during the diversification of genera.  © 2008 The Linnean Society of London, Biological Journal of the Linnean Society , 2008, 93 , 189–209.