The evolutionary diversification of parrots supports a taxon pulse model with multiple trans-oceanic dispersal events and local radiations

Vicariance is thought to have played a major role in the evolution of modern parrots. However, as the relationships especially of the African taxa remained mostly unresolved, it has been difficult to draw firm conclusions about the roles of dispersal and vicariance. Our analyses using the broadest taxon sampling of old world parrots ever based on 3219 bp of three nuclear genes revealed well-resolved and congruent phylogenetic hypotheses. Agapornis of Africa and Madagascar was found to be the sister group to Loriculus of Australasia and Indo-Malayasia and together they clustered with the Australasian Loriinae, Cyclopsittacini and Melopsittacus. Poicephalus and Psittacus from mainland Africa formed the sister group Of the Neotropical Arini and Coracopsis from Madagascar and adjacent islands may be the closest relative of Psittrichas from New Guinea. These biogeographic relationships are best explained by independent colonization of the African continent via trans-oceanic dispersal from Australasia and Antarctica in the Paleogene following what may have been vicariance events in the late Cretaceous and/or early Paleogene. Our data support a taxon pulse model for the diversification of parrots whereby trans-oceanic dispersal played a more important role than previously thought and was the prerequisite for range expansion into new continents. (C) 2009 Elsevier Inc. All rights reserved

Simulation of Drosophila circadian oscillations, mutations, and light responses by a model with VRI, PDP-1, and CLK.

A model of Drosophila circadian rhythm generation was developed to represent feedback loops based on transcriptional regulation of per, Clk (dclock), Pdp-1, and vri (vrille). The model postulates that histone acetylation kinetics make transcriptional activation a nonlinear function of [CLK]. Such a nonlinearity is essential to simulate robust circadian oscillations of transcription in our model and in previous models. Simulations suggest that two positive feedback loops involving Clk are not essential for oscillations, because oscillations of [PER] were preserved when Clk, vri, or Pdp-1 expression was fixed. However, eliminating positive feedback by fixing vri expression altered the oscillation period. Eliminating the negative feedback loop in which PER represses per expression abolished oscillations. Simulations of per or Clk null mutations, of per overexpression, and of vri, Clk, or Pdp-1 heterozygous null mutations altered model behavior in ways similar to experimental data. The model simulated a photic phase-response curve resembling experimental curves, and oscillations entrained to simulated light-dark cycles. Temperature compensation of oscillation period could be simulated if temperature elevation slowed PER nuclear entry or PER phosphorylation. The model makes experimental predictions, some of which could be tested in transgenic Drosophila.

Lepton Flavor Violation in the Standard Model with general Dimension-Six Operators

We study lepton flavor observables in the Standard Model (SM) extended with all dimension-6 operators which are invariant under the SM gauge group. We calculate the complete one-loop predictions to the radiative lepton decays μ → eγ, τ → μγ and τ → eγ as well as to the closely related anomalous magnetic moments and electric dipole moments of charged leptons, taking into account all dimension-6 operators which can generate lepton flavor violation. Also the 3-body flavor violating charged lepton decays τ ± → μ ± μ + μ −, τ ± → e ± e + e −, τ ± → e ± μ + μ −, τ ± → μ ± e + e −, τ ± → e ∓ μ ± μ ±, τ ± → μ ∓ e ± e ± and μ ± → e ± e + e − and the Z 0 decays Z 0 → ℓ+iℓ−j are considered, taking into account all tree-level contributions.

Past and future evolution of Abies alba forests in Europe - comparison of a dynamic vegetation model with palaeo data and observations

Information on how species distributions and ecosystem services are impacted by anthropogenic climate change is important for adaptation planning. Palaeo data suggest that Abies alba formed forests under significantly warmer-than-present conditions in Europe and might be a native substitute for widespread drought-sensitive temperate and boreal tree species such as beech (Fagus sylvatica) and spruce (Picea abies) under future global warming conditions. Here, we combine pollen and macrofossil data, modern observations, and results from transient simulations with the LPX-Bern dynamic global vegetation model to assess past and future distributions of A. alba in Europe. LPX-Bern is forced with climate anomalies from a run over the past 21 000 years with the Community Earth System Model, modern climatology, and with 21st-century multimodel ensemble results for the high-emission RCP8.5 and the stringent mitigation RCP2.6 pathway. The simulated distribution for present climate encompasses the modern range of A. alba, with the model exceeding the present distribution in north-western and southern Europe. Mid-Holocene pollen data and model results agree for southern Europe, suggesting that at present, human impacts suppress the distribution in southern Europe. Pollen and model results both show range expansion starting during the Bølling–Allerød warm period, interrupted by the Younger Dryas cold, and resuming during the Holocene. The distribution of A. alba expands to the north-east in all future scenarios, whereas the potential (currently unrealized) range would be substantially reduced in southern Europe under RCP8.5. A. alba maintains its current range in central Europe despite competition by other thermophilous tree species. Our combined palaeoecological and model evidence suggest that A. alba may ensure important ecosystem services including stand and slope stability, infrastructure protection, and carbon sequestration under significantly warmer-than-present conditions in central Europe.

A Dynamic Stochastic Frontier Production Model with Time-Varying Efficiency

In this paper we introduce technical efficiency via the intercept that evolve over time as a AR(1) process in a stochastic frontier (SF) framework in a panel data framework. Following are the distinguishing features of the model. First, the model is dynamic in nature. Second, it can separate technical inefficiency from fixed firm-specific effects which are not part of inefficiency. Third, the model allows one to estimate technical change separate from change in technical efficiency. We propose the ML method to estimate the parameters of the model. Finally, we derive expressions to calculate/predict technical inefficiency (efficiency).

Monetary Policy in a Portfolio Balance Model with Endogenous Physical Capital

We develop a portfolio balance model with real capital accumulation. The introduction of real capital as an asset as well as a good produced and demanded by firms enriches extant portfolio balance models of exchange rate determination. We show that expansionary monetary policy causes exchange rate overshooting, not once, but twice; the secondary repercussion comes through the reaction of firms to changed asset prices and the firms' decisions to invest in real capital. The model sheds further light on the volatility of real and nominal exchange rates, and it suggests that changes in corporate sector profitability may affect exchange rates through portfolio diversification in corporate securities.

Simulation study of joint transition and Weibull survival model with shared parameters

This study investigates a theoretical model where a longitudinal process, that is a stationary Markov-Chain, and a Weibull survival process share a bivariate random effect. Furthermore, a Quality-of-Life adjusted survival is calculated as the weighted sum of survival time. Theoretical values of population mean adjusted survival of the described model are computed numerically. The parameters of the bivariate random effect do significantly affect theoretical values of population mean. Maximum-Likelihood and Bayesian methods are applied on simulated data to estimate the model parameters. Based on the parameter estimates, predicated population mean adjusted survival can then be calculated numerically and compared with the theoretical values. Bayesian method and Maximum-Likelihood method provide parameter estimations and population mean prediction with comparable accuracy; however Bayesian method suffers from poor convergence due to autocorrelation and inter-variable correlation. ^