Multigene analyses of bilaterian animals corroborate the monophyly of Ecdysozoa, Lophotrochozoa, and Protostomia

Almost a decade ago, a new phylogeny of bilaterian animals was inferred from small-subunit ribosomal RNA (rRNA) that claimed the monophyly of two major groups of protostome animals: Ecdysozoa (e.g., arthropods, nematodes, onychophorans, and tardigrades) and Lophotrochozoa (e.g., annelids, molluscs, platyhelminths, brachiopods, and rotifers). However, it received little additional support. In fact, several multigene analyses strongly argued against this new phylogeny. These latter studies were based on a large amount of sequence data and therefore showed an apparently strong statistical support. Yet, they covered only a few taxa (those for which complete genomes were available), making systematic artifacts of tree reconstruction more probable. Here we expand this sparse taxonomic sampling and analyze a large data set (146 genes, 35,371 positions) from a diverse sample of animals (35 species). Our study demonstrates that the incongruences observed between rRNA and multigene analyses were indeed due to long-branch attraction artifacts, illustrating the enormous impact of systematic biases on phylogenomic studies. A refined analysis of our data set excluding the most biased genes provides strong support in favor of the new animal phylogeny and in addition suggests that urochordates are more closely related to vertebrates than are cephalochordates. These findings have important implications for the interpretation of morphological and genomic data.     

Phylogenetic analyses of nuclear, mitochondrial, and plastid multigene data sets support the placement of Mesostigma in the Streptophyta

All extant green plants belong to 1 of 2 major lineages, commonly known as the Chlorophyta (most of the green algae) and the Streptophyta (land plants and their closest green algal relatives). The scaly green flagellate Mesostigma viride has an important place in the debate on the origin of green plants. However, there have been conflicting results from molecular systematics as to whether Mesostigma diverges before the Chlorophyta/Streptophyta split or is an early diverging flagellate member of the Streptophyta. Previous studies employed either a limited taxon sampling (plastid and mitochondrial genomes) or a small number of phylogenetically informative sites (single nuclear genes). Here, we use large data sets from the nuclear (125 proteins; 29,319 positions), mitochondrial (33 proteins; 6,622 positions), and plastid (50 proteins; 10,137 positions) genomes with an expanded taxon sampling (21, 13, and 28 species, respectively) to reevaluate the phylogenetic position of Mesostigma. Our study supports the placement of Mesostigma in the Streptophyta (as an early diverging lineage) and provides evidence that systematic biases have played a role in generating some of the previous conflicting results. Importantly, we demonstrate that using an increased taxon sampling as well as more realistic models of evolution allows increasing congruence among the nuclear, mitochondrial, and plastid data sets.     

Improving sampling designs for measuring restoration in aquatic habitats

Restoration of degraded habitat is an increasingly important toll for management. Unfortunately, much of the emphasis has been on restoring large structural elements of habitat (e.g. planting vegetation,removing weeds), with little consideration about how well these activities restore ecologically functioning habitat. There has been considerable research in recent years into improving sampling designs and analytical techniques to measure the effects of environmental impacts taking into account the large spatial and temporal variability that occurs naturally in undisturbed habitats. In a similar manner to detection of impacts, restoration needs to be measured as an interaction between spatial and temporal components of variation against a variable background. Very few studies of restoration have explicitly addressed how best to do this. Neither have they attempted to assess the usefulness of some of these new techniques for measuring restoration. This review discusses some of the problems that need to be considered when measuring restoration and the potential value of some of these new methodologies. This revised version was published online in July 2006 with corrections to the Cover Date.     

Finding Optimal Ingroup Topologies and Convexities When the Choice of Outgroups Is Not Obvious

Considerable confusion remains among theoreticians and practicioners of phylogenetic science on the use of outgroup taxa. Here, we show that, despite claims to the contrary, details of the optimal ingroup topology can be changed by switching outgroup taxa. This has serious implications for phylogenetic accuracy. We delineate between the process of outgroup selection and the various possible processes involved in using an outgroup taxon after one has been selected. Criteria are needed for the determination that particular outgroup taxa do not reduce the accuracy of evolutionary tree topologies and inferred character state transformations. We compare previous results from a sensitivity bootstrap analysis of the mitochondrial cytochromebphylogenetic relationships among whales to the results of a Bremer support sensitivity analysis and of a recently developed application of RASA theory to the question of putative outgroup taxon plesiomorphy content.     

Neuronal Morphology: Shape Characteristics and Models

This paper is focused on quantification (morphometry) and modeling of neuronal morphological complexity. First, computer-aided methods for reconstruction, processing, and analysis of raw morphological data are reviewed. Then, topological and metrical measures are touched upon. Fractal measures (together with the extension of multiscale fractal dimension) are presented more explicitly. Models of neuronal arborizations are differentiated between reconstruction models and growth models (stochastic or mechanistic). The growth model approach is discussed in more detail. The methods presented are applied to several types of neurons and shown to have considerable discriminative power. Recent developments stress the importance of these methods for optimizing virtual neuronal trees in view of functional characteristics of the neurons. Neirofiziologiya/Neurophysiology, Vol. 40, No. 4, pp. 366–372, July–August, 2008.     

Use and misuse of the IUCN Red List Criteria in projecting climate change impacts on biodiversity

Recent attempts at projecting climate change impacts on biodiversity have used the IUCN Red List Criteria to obtain estimates of extinction rates based on projected range shifts. In these studies, the Criteria are often misapplied, potentially introducing substantial bias and uncertainty. These misapplications include arbitrary changes to temporal and spatial scales; confusion of the spatial variables; and assume a linear relationship between abundance and range area. Using the IUCN Red List Criteria to identify which species are threatened by climate change presents special problems and uncertainties, especially for shorter‐lived species. Responses of most species to future climate change are not understood well enough to estimate extinction risks based solely on climate change scenarios and projections of shifts and/or reductions in range areas. One way to further such understanding would be to analyze the interactions among habitat shifts, landscape structure and demography for a number of species, using a combination of models. Evaluating the patterns in the results might allow the development of guidelines for assigning species to threat categories, based on a combination of life history parameters, characteristics of the landscapes in which they live, and projected range changes.     

Log-linear Models for Polytomous Data

The present study discusses two variants of linear logistic models for polytomous variables for ?unordered”? and for ?ordered”? categories (polydimensional and one-dimensional model). The ML-estimation equations and the possibilities to test the validity of the model are given for both. A test for goodness-of-fit (external validity) and a test for equality of the parameter estimates for split data (interval validity) are suggested. In addition, statistical tests for the significance of individual parameters on the basis of the information matrix and likelihood ratio tests for one or more parameters are described. The presentation is completed by an empirical example from the area of audiology.     

Robustness of demographic estimates in studies of plant responses to fire

Abstract For demographic models of resprouting species in relation to fire regimes, spatially separated populations of different ages are usually treated as a chronosequence, and the average behaviour of these populations is used as the estimate of the generalized behaviour of a single population through time. Using the data of Bradstock (1990), we examine the way in which the between-population variability affects the demographic parameters for Banksia serrata (Proteaceae) and thus assess whether the estimates of the shortest inter-fire interval necessary to maintain a stable population size under low and high intensity fires are robust to variation in these parameters. The range of our estimates compares well to the average estimate of Bradstock (1990) for high intensity fires, but not for low intensity fires. However the relevant demographic parameters appear to vary more between populations than they do as a result of the length of the inter-fire intervals, and the specific demographic model discussed here may have only local application.     

How far details are important in ecosystem modelling: the case of multi-limiting nutrients in phytoplankton-zooplankton interactions

We try to answer the question of to what extent details in nutrient uptake and phytoplankton physiology matter for population and community dynamics. To this end, we study how two nutrients interact in limiting phytoplankton growth. A popular formulation uses a product-rule for nutrient uptake, which we compare with that on the basis of synthesizing units. We first fit different nutrient uptake models to a dataset and conclude that the quantitative differences between the models are small. Then we study the sensitivity of phytoplankton growth and zooplankton-phytoplankton interactions (ZPi) models to uptake formulations. Two population models are compared; they are based on different assumptions on the relation between nutrient uptake and phytoplankton growth. We find that the population and community models are sensitive to uptake formulations. According to the uptake formulation used in the ZPi models, qualitative differences can be observed. Indeed, although two models based on functions with similar shapes have close equilibria, these can differ in stability properties. Since stability involves the derivatives of formulas, even if two formulas provide close values, large numerical differences in the stability criterion may occur after derivation. We conclude that mechanistic details can be of importance for community modelling.     

Resolving the phylogeny of lizards and snakes (Squamata) with extensive sampling of genes and species

Squamate reptiles (lizards and snakes) are one of the most diverse groups of terrestrial vertebrates. Recent molecular analyses have suggested a very different squamate phylogeny relative to morphological hypotheses, but many aspects remain uncertain from molecular data. Here, we analyse higher-level squamate phylogeny with a molecular dataset of unprecedented size, including 161 squamate species for up to 44 nuclear genes each (33 717 base pairs), using both concatenated and species-tree methods for the first time. Our results strongly resolve most squamate relationships and reveal some surprising results. In contrast to most other recent studies, we find that dibamids and gekkotans are together the sister group to all other squamates. Remarkably, we find that the distinctive scolecophidians (blind snakes) are paraphyletic with respect to other snakes, suggesting that snakes were primitively burrowers and subsequently re-invaded surface habitats. Finally, we find that some clades remain poorly supported, despite our extensive data. Our analyses show that weakly supported clades are associated with relatively short branches for which individual genes often show conflicting relationships. These latter results have important implications for all studies that attempt to resolve phylogenies with large-scale phylogenomic datasets.     

类群取样与系统发育分析精确度之探索

Appropriate and extensive taxon sampling is one of the most important determinants of accurate phylogenetic estimation. In addition, accuracy of inferences about evolutionary processes obtained from phylogenetic analyses is improved significantly by thorough taxon sampling efforts. Many recent efforts to improve phylogenetic estimates have focused instead on increasing sequence length or the number of overall characters in the analysis, and this often does have a beneficial effect on the accuracy of phylogenetic analyses. However, phylogenetic analyses of few taxa (but each represented by many characters) can be subject to strong systematic biases, which in turn produce high measures of repeatability (such as bootstrap proportions) in support of incorrect or misleading phylogenetic results. Thus, it is important for phylogeneticists to consider both the sampling of taxa, as well as the sampling of characters, in designing phylogenetic studies. Taxon sampling also improves estimates of evolutionary parameters derived from phylogenetic trees, and is thus important for improved applications of phylogenetic analyses. Analysis of sensitivity to taxon inclusion, the possible effects of long-branch attraction, and sensitivity of parameter estimation for model-based methods should be a part of any careful and thorough phylogenetic analysis. Furthermore, recent improvements in phylogenetic algorithms and in computational power have removed many constraints on analyzing large, thoroughly sampled data sets. Thorough taxon sampling is thus one of the most practical ways to improve the accuracy of phylogenetic estimates, as well as the accuracy of biological inferences that are based on these phylogenetic trees.