Estimation of a Joint Distribution Function with Multivariate Interval‐Censored Data when the Nonparametric MLE is not Unique

A nonparametric estimator of a joint distribution function F₀ of a d‐dimensional random vector with interval‐censored (IC) data is the generalized maximum likelihood estimator (GMLE), where d ≥ 2. The GMLE of F₀ with univariate IC data is uniquely defined at each follow‐up time. However, this is no longer true in general with multivariate IC data as demonstrated by a data set from an eye study. How to estimate the survival function and the covariance matrix of the estimator in such a case is a new practical issue in analyzing IC data. We propose a procedure in such a situation and apply it to the data set from the eye study. Our method always results in a GMLE with a nonsingular sample information matrix. We also give a theoretical justification for such a procedure. Extension of our procedure to Cox's regression model is also mentioned.     

Molecules and Morphology: Conflicts and Congruence within the Fern GenusTrichomanes(Hymenophyllaceae)

The interaction between three independent data sets (anatomy/morphology, cytology, molecules) has been evaluated within the controversial genusTrichomanes(Hymenophyllaceae). Anatomy/morphology, cytology, andrbcL sequences, despite their high and significant level of incongruence, were thus empirically combined with differential weighting in a cladistic analysis withinTrichomanesin order to give an appreciation of the contribution of each data set in the resulting topologies and to study more precisely the nature of potential conflicts. Results show that any standard statistics values (such as bootstrap) do not appear to be objectively useful for the choice of the “best” topology or the “good” clades provided by the combination. This weighting approach reveals three cases: (i) some clades (such as subgenusDidymoglossum) are always retrieved and correspond to the absence of conflicts between the different data, (ii) some new clades (such as subgenusAchomanes) are either provided or reenforced as a “synergetic” result of the combination of the data and (iii) that remaining conflicting clades reflect the persistence of incongruence between data whatever the weighting.     

EDENetworks: A user‐friendly software to build and analyse networks in biogeography,ecology and population genetics

The recent application of graph‐based network theory analysis to biogeography, community ecology and population genetics has created a need for user‐friendly software, which would allow a wider accessibility to and adaptation of these methods. EDENetworks aims to fill this void by providing an easy‐to‐use interface for the whole analysis pipeline of ecological and evolutionary networks starting from matrices of species distributions, genotypes, bacterial OTUs or populations characterized genetically. The user can choose between several different ecological distance metrics, such as Bray‐Curtis or Sorensen distance, or population genetic metrics such as F_ST or Goldstein distances, to turn the raw data into a distance/dissimilarity matrix. This matrix is then transformed into a network by manual or automatic thresholding based on percolation theory or by building the minimum spanning tree. The networks can be visualized along with auxiliary data and analysed with various metrics such as degree, clustering coefficient, assortativity and betweenness centrality. The statistical significance of the results can be estimated either by resampling the original biological data or by null models based on permutations of the data.     

The Association of Physical and Environmental Factors with Abundance and Distribution Patterns of Groupers around Kolombangara Island, Solomon Islands

I collected baseline abundance data on groupers from the reefs of Vavanga village on Kolombangara Island, Solomon Islands. Physical and environmental factors significantly affected the abundance and distribution patterns of groupers. Size and age distribution of groupers varied with depth. Power analysis on the abundance data showed that although power could be calculated to within an acceptable level from a management perspective for abundant species such as the coral hind, Cephalopholis miniata, the same could not be done for larger and naturally scarce species, such as the humpback grouper, Cromileptes altivelis.     

Integration of molecular, ecological, morphological and endosymbiont data for species delimitation within the Pnigalio soemius complex (Hymenoptera: Eulophidae)

Integrative taxonomy is a recently developed approach that uses multiple lines of evidence such as molecular, morphological, ecological and geographical data to test species limits, and it stands as one of the most promising approaches to species delimitation in taxonomically difficult groups. The Pnigalio soemius complex (Hymenoptera: Eulophidae) represents an interesting taxonomical and ecological study case, as it is characterized by a lack of informative morphological characters, deep mitochondrial divergence, and is susceptible to infection by parthenogenesis‐inducing Rickettsia. We tested the effectiveness of an integrative taxonomy approach in delimiting species within the P. soemius complex. We analysed two molecular markers (COI and ITS2) using different methods, performed multivariate analysis on morphometric data and exploited ecological data such as host–plant system associations, geographical separation, and the prevalence, type and effects of endosymbiont infection. The challenge of resolving different levels of resolution in the data was met by setting up a formal procedure of data integration within and between conflicting independent lines of evidence. An iterative corroboration process of multiple sources of data eventually indicated the existence of several cryptic species that can be treated as stable taxonomic hypotheses. Furthermore, the integrative approach confirmed a trend towards host specificity within the presumed polyphagous P. soemius and suggested that Rickettsia could have played a major role in the reproductive isolation and genetic diversification of at least two species.     

sampbias,a method for quantifying geographic sampling biases in species distribution data

Geo‐referenced species occurrences from public databases have become essential to biodiversity research and conservation. However, geographical biases are widely recognized as a factor limiting the usefulness of such data for understanding species diversity and distribution. In particular, differences in sampling intensity across a landscape due to differences in human accessibility are ubiquitous but may differ in strength among taxonomic groups and data sets. Although several factors have been described to influence human access (such as presence of roads, rivers, airports and cities), quantifying their specific and combined effects on recorded occurrence data remains challenging. Here we present sampbias, an algorithm and software for quantifying the effect of accessibility biases in species occurrence data sets. sampbias uses a Bayesian approach to estimate how sampling rates vary as a function of proximity to one or multiple bias factors. The results are comparable among bias factors and data sets. We demonstrate the use of sampbias on a data set of mammal occurrences from the island of Borneo, showing a high biasing effect of cities and a moderate effect of roads and airports. sampbias is implemented as a well‐documented, open‐access and user‐friendly R package that we hope will become a standard tool for anyone working with species occurrences in ecology, evolution, conservation and related fields.     

Can vector summation describe the orientation system of juvenile ospreys and honey buzzards? – An analysis of ring recoveries and satellite tracking

Juvenile bird migrants are generally believed to use a clock‐and‐compass migratory orientation strategy. According to such a strategy migrants accomplish their migration by flying a number of successive flight steps with direction and number of steps controlled by an endogenous programme. One powerful way of testing this is by comparing predictions from a model of such a strategy with observed patterns. We used data from ringing and satellite‐based radio telemetry to investigate the orientation system of juvenile ospreys (Pandion haliaetus) and honey buzzards (Pernis apivorus) migrating from Sweden to tropical west Africa. The ring recoveries showed a much larger scatter in the orientation of ospreys than of honey buzzards, but there was only a slight such difference in the satellite tracks. These tracks of individuals of both species were rather straight with a high directional concentration per step. The honey buzzard data showed a close fit to a simple vector summation model, which is expected if birds follow a clock‐and‐compass strategy. However, the osprey data did not fit such a simple model, as ring recoveries showed a significantly greater deviation at short distances than predicted on the basis of long distance data. Satellite tracking also indicated less concentrated orientation on short distances. The pattern observed for the osprey can generally be explained by an extended vector summation model, including an important element of pre‐migration dispersal. The existence of extensive dispersal in the osprey stands in contrast to the apparent absence of such dispersal in the honey buzzard. The explanation for this difference between the species is unclear. The model of orientation by vector summation is very sensitive to the existence of differences in mean direction between individuals. Assuming such differences, as tentatively indicated by the satellite tracking data, makes simple compass orientation by vector summation inconsistent with the distribution of ring recoveries at long distances, with a high proportion of misoriented birds falling outside the normal winter range.     

A method for the estimation of parameters for natural stage-structured populations

A relatively simple method is proposed for the estimation of parameters of stage-structured populations from sample data for situation where (a) unit time survival rates may vary with time, and (b) the distribution of entry times to stage 1 is too complicated to be fitted with a simple parametric model such as a normal or gamma distribution. The key aspects of this model are that the entry time distribution is approximated by an exponential function withp parameters, the unit time survival rates in stages are approximated by anr parameter exponential polynomial in the stage number, and the durations of stages are assumed to be the same for all individuals. The new method is applied to four Zooplankton data sets, with parametric bootstrapping used to assess the bias and variation in estimates. It is concluded that good estimates of demographic parameters from stagefrequency data from natural populations will usually only be possible if extra information such as the durations of stages is known.     

Linking local ecological knowledge and habitat modelling to predict absolute species abundance on large scales

Assessing the spatial structure of abundance of a species is a basic requirement to carry out adequate conservation strategies. However, existing attempts to predict species abundance, particularly in absolute units and on large scales, are scarce and have led to weak results. In this work we present a scheme to obtain, in an affordable way, a predictive model of absolute animal abundance on large scales based on the modelling of data obtained from local ecological knowledge (LEK) and its calibration. To exemplify this scheme, we build and validate a predictive absolute abundance model of the endangered terrestrial tortoise Testudo graeca in Southeast Iberian Peninsula. For that purpose, we collected distribution and relative abundance data of T. graeca using a low cost methodology, such as LEK, by means of interviewing shepherds. The information from LEK was employed to build a predictive habitat-based model of relative abundance. The relative abundance model was transformed into an absolute abundance model by means of calibration with a classical absolute abundance sampling method such as distance sampling. The obtained absolute abundance model predicted the observed absolute abundances values well in independent locations when compared with other works (R ² = 36%) and thus can offer a cost-effective predictive ability. Our results show that reliable habitat-based predictive maps of absolute species abundance on regional scales can be obtained starting from low cost sampling methods of relative abundance, such as LEK, and its calibration.     

A Partitioning Deletion/Substitution/Addition Algorithm for Creating Survival Risk Groups

Summary Accurately assessing a patient’s risk of a given event is essential in making informed treatment decisions. One approach is to stratify patients into two or more distinct risk groups with respect to a specific outcome using both clinical and demographic variables. Outcomes may be categorical or continuous in nature; important examples in cancer studies might include level of toxicity or time to recurrence. Recursive partitioning methods are ideal for building such risk groups. Two such methods are Classification and Regression Trees (CART) and a more recent competitor known as the partitioning Deletion/Substitution/Addition (partDSA) algorithm, both of which also utilize loss functions (e.g., squared error for a continuous outcome) as the basis for building, selecting, and assessing predictors but differ in the manner by which regression trees are constructed. Recently, we have shown that partDSA often outperforms CART in so‐called “full data” settings (e.g., uncensored outcomes). However, when confronted with censored outcome data, the loss functions used by both procedures must be modified. There have been several attempts to adapt CART for right‐censored data. This article describes two such extensions for partDSA that make use of observed data loss functions constructed using inverse probability of censoring weights. Such loss functions are consistent estimates of their uncensored counterparts provided that the corresponding censoring model is correctly specified. The relative performance of these new methods is evaluated via simulation studies and illustrated through an analysis of clinical trial data on brain cancer patients. The implementation of partDSA for uncensored and right‐censored outcomes is publicly available in the R package, partDSA .     

Feeding habits of <Emphasis Type="Italic">Bathydraco marri</Emphasis> (Pisces,Notothenioidei, Bathydraconidae) from the Ross Sea,Antarctica

In comparison with other bathydraconids, all species of the genus Bathydraco are poorly known from an ecological perspective. The diet of juvenile Bathydraco marri Norman, 1938 was studied for the first time in specimens collected in the southwestern Ross Sea during summer 1998. Fish were collected in a single otter trawl catch at 330–340 m depth. The stomach content analysis showed that this species fed exclusively on crustaceans. Overall, 20 prey taxa were identified to genus or species level. Mysids, amphipods and copepods were the most important prey in decreasing order of importance. Other prey, such as Euphausia superba, isopods and tanaids were eaten occasionally and in very small amounts. A multivariate analysis was applied to feeding data to assess ontogenetic or sex-related changes in diet. No difference was detected between sexes, whereas diet of small and large fish differed in some degree. An ontogenetic shift from small and pelagic crustaceans such as copepods to benthic–benthopelagic prey such as amphipods and mysids was observed. Relating present results with published data on physiological characteristics of B. marri, it was possible to infer their feeding behaviour and mode of life. Like other bathydraconids, this species appeared to be an inactive and sluggish fish, which relied on more or less motile benthic or epibenthic prey adopting a “sit and wait” feeding strategy. On the other hand, smaller fish seem to be more active, feeding also on pelagic prey such as copepods that can be seasonally abundant, thus reducing the intraspecific competition for food.     

Sliding window discretization: A new method for multiple band matching of bacterial genotyping fingerprints

Microbiologists have traditionally applied hierarchical clustering algorithms as their mathematical tool of choice to unravel the taxonomic relationships between micro-organisms. However, the interpretation of such hierarchical classifications suffers from being subjective, in that a variety of ad hoc choices must be made during their construction. On the other hand, the application of more profound and objective mathematical methods—such as the minimization of stochastic complexity—for the classification of bacterial genotyping fingerprints data is hampered by the prerequisite that such methods only act upon vectorized data. In this paper we introduce a new method, coined sliding window discretization, for the transformation of genotypic fingerprint patterns into binary vector format. In the context of an extensive amplified fragment length polymorphism (AFLP) data set of 507 strains from the Vibrionaceae family that has previously been analysed, we demonstrate by comparison with a number of other discretization methods that this new discretization method results in minimal loss of the original information content captured in the banding patterns. Finally, we investigate the implications of the different discretization methods on the classification of bacterial genotyping fingerprints by minimization of stochastic complexity, as it is implemented in the BinClass software package for probabilistic clustering of binary vectors. The new taxonomic insights learned from the resulting classification of the AFLP patterns will prove the value of combining sliding window discretization with minimization of stochastic complexity, as an alternative classification algorithm for bacterial genotyping fingerprints.     

Bayesian knowledge integration for an in vitro–in vivo correlation model

The primary goal of “in vitro–in vivo correlation” (IVIVC) is the reliable prediction of the in vivo serum concentration‐time course, based on the in vitro drug dissolution or release profiles. IVIVC methods are particularly appropriate for formulations that are released over an extended period of time or with a lag in absorption and may support approving a change in formulation of a drug without additional bioequivalence trials in human subjects. Most of the current IVIVC models are assessed using frequentist methods, such as linear regression, based on averaged data and entail complex and potentially unstable mathematical deconvolution. The proposed IVIVC approach includes (a) a nonlinear‐mixed effects model for the in vitro release data; (b) a population pharmacokinetic (PK) compartment model for the in vivo immediate release (IR) data; and (c) a system of ordinal differential equations (ODEs), containing the submodels (a) and (b), which approximates and predicts the in vivo controlled release (CR) data. The innovation in this paper consists of splitting the parameter space between submodels (a) and (b) versus (c). Subsequently, the uncertainty on these parameters is accounted for using a Bayesian framework, that is estimates from the first two submodels serve as priors for the Bayesian hierarchical third submodel. As such, the Bayesian method explained ensures a natural integration and transfer of knowledge between various sources of information, balancing possible differences in sample size and parameter uncertainty of in vitro and in vivo studies. Consequently, it is a very flexible approach yielding results for a broad range of data situations. The application of the method is demonstrated for a transdermal patch (TD).     

Worldwide invasion of vector mosquitoes: present European distribution and challenges for Spain

An Asiatic mosquito species, Aedes albopictus, began to spread worldwide in the 1970s thanks to marine transport of tires and other goods, leading to colonization of many areas of the world. This species is a vector of major human diseases such as Dengue, Yellow Fever and the West Nile virus. In Europe, it was established in Albania and Italy and has been detected in other countries such as France; no records exist for Spain as yet. Colonization by Aedes albopictus is a major public health concern considering that the West Nile virus and several other viruses are known to circulate sporadically in the Mediterranean. Additionally, the parent species Aedes aegypti was the vector causing severe outbreaks of Dengue and Yellow Fever two centuries ago. Although Ae. aegypti was also introduced, it was eradicated from Spain. Both mosquitoes shared habitat types, diseases transmitted and many bionomic data. This article contains a review of the present Ae. albopictusdistribution range worldwide and discusses the likelihood of an establishment in Spain in view of climatological and geographical data. This revised version was published online in July 2006 with corrections to the Cover Date.     

DIVERSITY AND PHYLOGENETIC PLACEMENT OF BRACTEACOCCUS TEREG (CHLOROPHYCEAE,CHLOROPHYTA) BASED ON 18S RIBOSOMAL RNA GENE SEQUENCE DATA1

Sequence data from the nuclear small-subunit ribosomal RNA gene was obtained for nine strains of Bracteacoccus Tereg, representing at least five morphological species and four distinct geographic locations. These, along with sequence data from two additional chlorophycean taxa, Spongiochloris spongiosa Starr and Ascochloris multinucleata Bold et MacEntee, and 48 published sequences from green algal taxa, were used to determine the phylogenetic placement of Bracteacoccus with respect to other chlorophycean green algae. Results support the monophyly of Bracteacoccus strains, contrasting with patterns observed so far for many other coccoid green algae. The range of variation among Bracteacoccus strains is similar to that of other congeners. Basal body orientation in Bracteacoccus has been interpreted as clockwise; however, the 18S data point to a relationship between Bracteacoccus and taxa with the directly opposed configuration of the flagellar apparatus. No close relationship was found to the multinucleated green coccoids with clockwise orientation of basal bodies, such as Spongiochloris, or to those with parallel basal bodies, such as Spermatozopsis. However, 18S data confirm that the motile and vegetative cells of Bracteacoccus are structurally distinct from the representatives of sphaeroplealean families currently studied. It is premature to reclassify Bracteacoccus until 18S comparisons can be made with additional sphaeroplealean taxa and with algae with similar flagellar structure such as Dictyochloris and Heterochlamydomonas.     

Permutation – based statistical tests for multiple hypotheses

Background  

Genomics and proteomics analyses regularly involve the simultaneous test of hundreds of hypotheses, either on numerical or categorical data. To correct for the occurrence of false positives, validation tests based on multiple testing correction, such as Bonferroni and Benjamini and Hochberg, and re-sampling, such as permutation tests, are frequently used. Despite the known power of permutation-based tests, most available tools offer such tests for either t-test or ANOVA only. Less attention has been given to tests for categorical data, such as the Chi-square. This project takes a first step by developing an open-source software tool, Ptest, that addresses the need to offer public software tools incorporating these and other statistical tests with options for correcting for multiple hypotheses.     

Informatics for mutagenesis: the design of Mutabase—a distributed data recording system for animal husbandry, mutagenesis, and phenotypic analysis

The increasing use of high-throughput methods for the production of biologically important information and the increasing diversity of that information pose considerable bioinformatics challenges. These challenges will be met by implementing electronic data management systems not only to capture the data, but increasingly to provide a platform for data integration and mining as we enter the post-genomic era. We discuss the design and implementation of such a data capture system, `Mutabase', as a model of how such electronic systems might be designed and implemented. Mutabase was created in support of a large-scale, phenotype-driven mouse mutagenesis program at MRC Mammalian Genetics Unit, Harwell, in collaboration with SmithKline Beecham Pharmaceuticals, Queen Mary and Westfield College, London, and Imperial College of Science, Technology and Medicine, London. The aim of this mutagenesis project is to make a significant contribution to the existing mouse mutant resource, closing the phenotype gap and providing many more models for fundamental research and disease modeling. Mutabase records experimental details at the `point of generation' and provides a number of dissemination and analysis tools for the experimental data, as well as providing a means of assessing various aspects of progress of the program. Mutabase uses a hypertext-based interface to provide interaction between a number of intranet-based client workstations and a central industrial strength database. Mutabase utilizes a variety of techniques in order to implement the user interface system including Perl/CGI, Java Servlets, and an experimental CORBA server. We discuss the relative merits of these methods in the context of the need to provide sound informatics approaches for the support of systematic mutagenesis programs. Received: 16 December 1999 / Accepted: 17 December 1999