Horizontal and elevational phylogeographic patterns of Himalayan and Southeast Asian forest passerines (Aves: Passeriformes)

Aim Zoogeographic patterns in the Himalayas and their neighbouring Southeast Asian mountain ranges include elevational parapatry and ecological segregation, particularly among passerine bird species. We estimate timings of lineage splits among close relatives from the north Palaearctic, the Sino‐Himalayan mountain forests and from adjacent Southeast Asia. We also compare phylogeographic affinities and timing of radiation among members of avian communities from different elevational belts. Location East Asia. Methods We reconstructed molecular phylogenies based on a mitochondrial marker (cytochrome b) and multilocus data sets for seven passerine groups: Aegithalidae, Certhiidae (Certhia), Fringillidae (Pyrrhula), Paridae (Periparus), Phylloscopidae, Regulidae and Timaliidae (Garrulax sensu lato). Molecular dating was carried out using a Bayesian approach applying a relaxed clock in beast . Time estimates were inferred from three independent calibrations based on either a fixed mean substitution rate or fixed node ages. The biogeographic history of each group was reconstructed using a parsimony‐based approach. Results Passerine radiation in Southeast Asia can be divided into roughly three major phases of separation events. We infer that an initial Miocene radiation within the Southeast Asian region included invasions of (sub)tropical faunal elements from the Indo‐Burmese region to the Himalayan foothills and further successive invasions to Central Asia and Taiwan towards the early Pliocene. During two further Pliocene/Pleistocene phases, the subalpine mountain belt of the Sino‐Himalayas was initially invaded by boreal species with clear phylogenetic affinities to the north Palaearctic taiga belt. Most terminal splits between boreal Himalayan/Chinese sister taxa were dated to the Pleistocene. Main conclusions Extant patterns of elevational parapatry and faunal transition in the Sino‐Himalayas originated from successive invasions from different climatic regions. The initiation of Southeast Asian passerine diversification and colonization of the Himalayan foothills in the mid‐Miocene coincides with the postulated onset of Asian monsoon climate and the resulting floral and faunal turnovers. Patterns of elevational parapatry were established by southward invasions of boreal avifaunal elements to the subalpine Sino‐Himalayan forest belt that were strongly connected to climate cooling towards the end of the Pliocene. Current patterns of allopatry and parapatry in boreal species (groups) were shaped through Pleistocene forest fragmentation in East Asia.     

Smoothed quantile regression analysis of competing risks

Censored quantile regression models, which offer great flexibility in assessing covariate effects on event times, have attracted considerable research interest. In this study, we consider flexible estimation and inference procedures for competing risks quantile regression, which not only provides meaningful interpretations by using cumulative incidence quantiles but also extends the conventional accelerated failure time model by relaxing some of the stringent model assumptions, such as global linearity and unconditional independence. Current method for censored quantile regressions often involves the minimization of the L₁‐type convex function or solving the nonsmoothed estimating equations. This approach could lead to multiple roots in practical settings, particularly with multiple covariates. Moreover, variance estimation involves an unknown error distribution and most methods rely on computationally intensive resampling techniques such as bootstrapping. We consider the induced smoothing procedure for censored quantile regressions to the competing risks setting. The proposed procedure permits the fast and accurate computation of quantile regression parameter estimates and standard variances by using conventional numerical methods such as the Newton–Raphson algorithm. Numerical studies show that the proposed estimators perform well and the resulting inference is reliable in practical settings. The method is finally applied to data from a soft tissue sarcoma study.     

Integrating a global agro-climatic classification with bioregional boundaries in Australia

Aim Stratification of major differences in the biophysical features of landscapes at the continental scale is necessary to collectively assess local observations of landscape response to management actions for consistency and difference. Such a stratification is an important step in the development of generalizations concerning how landscapes respond to different management regimes. As part of the development of a comparative framework for this purpose, we propose a climate classification adapted from an existing broad scale global agro‐climatic classification, which is closely aligned with natural vegetation formations and common land uses across Australia. Location The project considered landscapes across the continent of Australia. Methods The global agro‐climatic classification was adapted by using elevation‐dependent thin plate smoothing splines to clarify the spatial extents of the 18 global classes found in Australia. The clarified class boundaries were interpolated from known classes at 822 points across Australia. These classes were then aligned with the existing bioregional classification, Interim Biogeographic Regionalization for Australia IBRA 5.1. Results The aligned climate classes reflect major patterns in plant growth temperature and moisture indices and seasonality. These in turn reflect broad differences in cropping and other land use characteristics. Fifty‐two of the 85 bioregions were classified entirely into one of the 18 agro‐climatic classes. The remaining bioregions were classified according to sub‐bioregional boundaries. A small number of these sub‐bioregions were split to better reflect agro‐climatic boundaries. Main conclusions The agro‐climatic classification provided an explicit global context for the analysis. The topographic dependence of the revised climate class boundaries clarified the spatial extents of poorly sampled highland classes and facilitated the alignment of these classes with the bioregional classification. This also made the classification amenable to explicit application. The bioregional and subregional boundaries reflect discontinuities in biophysical features. These permit the integrated classification to reflect major potential differences in landscape function and response to management. The refined agro‐climatic classification and its integration with the IBRA bioregions are both available for general use and assessment.     

Angiosperm divergence times: the effect of genes, codon positions, and time constraints

An understanding of the evolution of modern terrestrial ecosystems requires an understanding of the dynamics associated with angiosperm evolution, including the timing of their origin and diversification into their extraordinary present-day diversity. Molecular estimates of angiosperm age have varied widely, and many substantially predate the Early Cretaceous fossil appearance of the group. In this study, the effect of different genes, codon positions, and chronological constraints on node ages are examined on divergence time estimates across seed plants, with a special focus on angiosperms. Penalized likelihood was used to estimate divergence times on a phylogenetic hypothesis for seed plants derived from Bayesian analysis, with branch lengths estimated with maximum likelihood. The plastid genes atpB, psaA, psbB, and rbcL were used individually and in combination, using first and second, third, and the three codon positions, including and excluding age constraints on 20 nodes derived from a critical examination of the land-plant fossil record. The optimal level of rate smoothing according to each unconstrained and constrained dataset was obtained with penalized likelihood. Tests for a molecular clock revealed significantly unclocklike rates in all datasets. Addition of fossil constraints resulted in even greater departures from constancy. Consistently with significant deviations from a clock, estimated optimal smoothing values were low, but a strict correlation between rate heterogeneity and optimal smoothing value was not found. Age estimates for nodes across the phylogeny varied, sometimes substantially, with gene and codon position. Nevertheless, estimates based on the four concatenated genes are very similar to the mean of the four individual gene estimates. For any given node, unconstrained age estimates are more variable than constrained estimates and are frequently younger than well-substantiated fossil members of the clade. Constrained estimates of ages of clades are older than unconstrained estimates and oldest fossil representatives, sometimes substantially so. Angiosperm age estimates decreased as rate smoothing increased. Whereas the range of unconstrained angiosperm age estimates spans the fossil age of the clade, the range of constrained estimates is narrower (and older) than the earliest angiosperm fossils. Results unambiguously indicate the relevance of constraints in reducing the variability of ages derived from different partitions of the data and diminishing the effect of the smoothing parameter. Constrained optimizations of divergence times and substitution rates across the phylogeny suggest appreciably different evolutionary dynamics for angiosperms and for gymnosperms. Whereas the gymnosperm crown group originated shortly after the origin of seed plants, a long time elapsed before the origin of crown group angiosperms. Although absolute age estimates of angiosperms and angiosperm clades are older than their earliest fossils, the estimated pace of phylogenetic diversification largely agrees with the rapid appearance of angiosperm lineages in stratigraphic sequences.     

An adaptive bivariate kernel smoothing method for determining instars of Austrosimulium tillyardianum (Diptera: Simuliidae) larvae

1. In insects, instar determination is generally based on the frequency distribution of sclerotised body part measurements. Commonly used univariate methods, such as histograms and univariate kernel smoothing, are not sufficient to reflect the distribution of the measurements, because development of sclerotised body parts is multidimensional. 2. This study used an adaptive bivariate kernel smoothing method, based on 10 pairs of separating variables, to differentiate instars of Austrosimulium tillyardianum (Diptera: Simuliidae) larvae in two‐dimensional space. A variable bandwidth matrix was used and separation lines between instars were defined. Using the Crosby growth ratio, Brooks' rule and the new standard recently proposed, larvae were separated into nine instars. It was found that, using the bivariate kernel smoothing method, the clustering accuracy and determination of separation lines as instar class limits were higher than those associated with the univariate kernel smoothing method. With the exceptions of the paired separating variables, head capsule length and antennal segment 3 length (AS3L), the mean probabilities of correct classifications was > 85%. The pair of separating variables that yielded the greatest classification accuracy comprised mandible length (ML) and AS3L, which had mean probabilities of 0.8984. The clustering accuracy was higher for early‐ and late‐instar larvae, but lower for instars 6 and 7. The adaptive bivariate kernel smoothing method was better than univariate methods for instar determination, especially in the detection of divisions between instars and identification of a larval instar.     

Body size and food web structure: testing the equiprobability assumption of the cascade model

The cascade model successfuly predicts many patterns in reported food webs. A key assumption of this model is the existence of a predetermined trophic hierarchy; prey are always lower in the hierarchy than their predators. At least three studies have suggested that, in animal food webs, this hierarchy can be explained to a large extent by body size relationships. A second assumption of the standard cascade model is that trophic links not prohibited by the hierarchy occur with equal probability. Using nonparametric contingency table analyses, we tested this ”equiprobability hypothesis” in 16 published animal food webs for which the adult body masses of the species had been estimated. We found that when the hierarchy was based on body size, the equiprobability hypothesis was rejected in favor of an alternative, ”predator-dominance” hypothesis wherein the probability of a trophic link varies with the identity of the predator. Another alternative to equiprobabilty is that the probability of a trophic link depends upon the ratio of the body sizes of the two species. Using nonparametric regression and liklihood ratio tests, we show that a size-ratio based model represents a significant improvement over the cascade model. These results suggest that models with heterogeneous predation probabilities will fit food web data better than the homogeneous cascade model. They also suggest a new way to bridge the gap between static and dynamic food web models. Received: 3 February 1999 / Accepted: 26 October 1999     

Statistical analysis of temporal evolution in single-neuron firing rates

A fundamental methodology in neurophysiology involves recording the electrical signals associated with individual neurons within brains of awake behaving animals. Traditional statistical analyses have relied mainly on mean firing rates over some epoch (often several hundred milliseconds) that are compared across experimental conditions by analysis of variance. Often, however, the time course of the neuronal firing patterns is of interest, and a more refined procedure can produce substantial additional information. In this paper we compare neuronal firing in the supplementary eye field of a macaque monkey across two experimental conditions. We take the electrical discharges, or 'spikes', to be arrivals in a inhomogeneous Poisson process and then model the firing intensity function using both a simple parametric form and more flexible splines. Our main interest is in making inferences about certain characteristics of the intensity, including the timing of the maximal firing rate. We examine data from 84 neurons individually and also combine results into a hierarchical model. We use Bayesian estimation methods and frequentist significance tests based on a nonparametric bootstrap procedure. We are thereby able to conclude that a substantial fraction of the neurons exhibit important temporal differences in firing intensity across the two conditions, and we quantify the effect across the population of neurons.     

北美CHIHUAHUAN荒漠啮齿动物群落动态III．变量的频次分布和预测

本文用х²方和柯尔莫哥洛夫检验分析了北美Chihuahuan荒漠啮齿动物群落6个生态学变量的频次分布,并用移动平均和指数平滑方法拟合了这些变量的动态变化。结果显示：1)结合种群密度、生物量、物种均匀性和生物量均匀性服从正态分布;2)物种数和物种多样性的频次为向右偏斜的分布,无法用常见的理论分布来近似表示;3)单移动平均和双移动平均分别较好地描述了物种多样性和物种均匀性;4)其余4个变量可用单指数平滑来较好的描述．