Range size-abundance relationships in Australian passerines

Aim  To investigate the relationship between geographical range size and abundance (population density) in Australian passerines.
Location  Australia (including Tasmania).
Methods   We analysed the relationship between range size and local abundance for 272 species of Australian passerines, across the whole order and within families. We measured abundance as mean and maximum abundance, and used a phylogenetic generalized least-squares regression method within a maximum-likelihood framework to control for effects of phylogeny. We also analysed the relationship within seven different habitat types.
Results  There was no correlation between range size and abundance for the whole set of species across all habitats. Analyses within families revealed some strong correlations but showed no consistent pattern. Likewise we found little evidence for any relationship or conflicting patterns in different habitats, except that woodland/forest habitat species exhibit a negative correlation between mean abundance and range size, whilst species in urban habitats exhibit a significant positive relationship between maximum abundance and range size. Despite the general lack of correlation, the raw data plots of range size and abundance in this study occupied a triangular space, with narrowly distributed species exhibiting a greater variation in abundances than widely distributed species. However, using a null model analysis, we demonstrate that this was due to a statistical artefact generated by the frequency distributions for the individual variables.
Conclusions   We find no evidence for a positive range size-abundance relationship among Australian passerines. This absence of a relationship cannot be explained by any conflicting effects introduced by comparing across different habitats, nor is it explained by the fact that large proportions of Australia are arid. We speculate that the considerable isolation and evolutionary age of Australian passerines may be an explanatory factor.

Pheromone production, male abundance, body size, and the evolution of elaborate antennae in moths

The males of some species of moths possess elaborate feathery antennae. It is widely assumed that these striking morphological features have evolved through selection for males with greater sensitivity to the female sex pheromone, which is typically released in minute quantities. Accordingly, females of species in which males have elaborate (i.e., pectinate, bipectinate, or quadripectinate) antennae should produce the smallest quantities of pheromone. Alternatively, antennal morphology may be associated with the chemical properties of the pheromone components, with elaborate antennae being associated with pheromones that diffuse more quickly (i.e., have lower molecular weights). Finally, antennal morphology may reflect population structure, with low population abundance selecting for higher sensitivity and hence more elaborate antennae. We conducted a phylogenetic comparative analysis to test these explanations using pheromone chemical data and trapping data for 152 moth species. Elaborate antennae are associated with larger body size (longer forewing length), which suggests a biological cost that smaller moth species cannot bear. Body size is also positively correlated with pheromone titre and negatively correlated with population abundance (estimated by male abundance). Removing the effects of body size revealed no association between the shape of antennae and either pheromone titre, male abundance, or mean molecular weight of the pheromone components. However, among species with elaborate antennae, longer antennae were typically associated with lower male abundances and pheromone compounds with lower molecular weight, suggesting that male distribution and a more rapidly diffusing female sex pheromone may influence the size but not the general shape of male antennae.

Sexual selection and the evolution of complex color patterns in dragon lizards

Many species have elaborate and complex coloration and patterning, which often differ between the sexes. Sexual selection may increase the size or intensity of color patches (elaboration) in one sex or drive the evolution of novel signal elements (innovation). The latter potentially increases color pattern complexity. Color pattern complexity may also be influenced by ecological factors related to predation and environment; however, very few studies have investigated the effects of both sexual and natural selection on color pattern complexity across species. We used a phylogenetic comparative approach to examine these effects in 85 species and subspecies of Australian dragon lizards (family Agamidae). We quantified color pattern complexity by adapting the Shannon–Wiener diversity index. There were clear sex differences in color pattern complexity, which were positively correlated with both sexual dichromatism and sexual size dimorphism, consistent with the idea that sexual selection plays a significant role in the evolution of color pattern complexity. By contrast, we found little evidence of a link between environmental factors and color pattern complexity on body regions exposed to predators. Our results suggest that sexual selection rather than natural selection has led to increased color pattern complexity in males.

Brains and bravery: little evidence of a relationship between brain size and flightiness in shorebirds

The ability of birds to perceive, assess and appropriately respond to the presence of relatively novel threats is important to their survival. We hypothesized that the cognitive capacity of birds will influence their ability for accurate response to novelty. We used brain volume as a surrogate for cognitive capacity and postulated that larger brained birds would moderate their responses when presented with a benign, frequently occurring stimulus, such as a person, because they would habituate more readily. We conducted phylogenetic generalized least square regression to investigate the relationship between brain volume and flight initiation distance (FID; the distance to which a bird can be approached before initiating escape behaviour), while controlling for confounding factors including body size (body mass and wing length) and migration status. We compared seven different models using combinations of these parameters using Akaike's information criterion to determine the best approximating model(s) explaining FID. The two best-supported models included only wing length and only body mass with Akaike weights of 0.396 and 0.311 respectively. No model including brain volume had an Akaike weight greater than 0.083 and brain volume was poorly correlated with FID in models after controlling for body mass. Thus, brain volume does not appear to strongly relate to bravery among these shorebirds.

On the asymptotic distribution of the Dickey Fuller-GLS test statistic

In a very influential paper, Elliott et al. [Efficient tests for an autoregressive unit root. Econometrica. 1996;64:813–836] show that no uniformly most powerful test for the unit root testing problem exits, derive the relevant power envelope and characterize a family of point-optimal tests. As a by-product, they also propose a ‘generalized least squares (GLS) detrended’ version of the conventional Dickey–Fuller test, denoted DF-GLS, that has since then become very popular among practitioners, much more so than the point-optimal tests. In view of this, it is quite strange to find that, while conjectured in Elliott et al. [Efficient tests for an autoregressive unit root. Econometrica. 1996;64:813–836], so far there seems to be no formal proof of the asymptotic distribution of the DF-GLS test statistic. By providing three separate proofs, the current paper not only substantiates the required result, but also provides insight regarding the pros and cons of different methods of proof.

On the importance of the first observation in GLS detrending in unit root testing

First-differencing is generally taken to imply the loss of one observation, the first, or at least that the effect of ignoring this observation is asymptotically negligible. However, this is not always true, as in the case of generalized least squares (GLS) detrending. In order to illustrate this, the current article considers as an example the use of GLS detrended data when testing for a unit root. The results show that the treatment of the first observation is absolutely crucial for test performance, and that ignorance causes test break-down.

Optimal IV estimation of systems with stochastic regressors and var disturbances with applications to dynamic systems

This paper considers the general problem of Feasible Generalized Least Squares Instrumental Variables (FG LS IV) estimation using optimal instruments. First we summarize the sufficient conditions for the FG LS IV estimator to be asymptotic ally equivalent to an optimal G LS IV estimator. Then we specialize to stationary dynamic systems with stationary VAR errors, and use the sufficient conditions to derive new moment conditions for these models. These moment conditions produce useful IVs from the lagged endogenous variables, despite the correlation between errors and endogenous variables. This use of the information contained in the lagged endogenous variables expands the class of IV estimators under consideration and there by potentially improves both asymptotic and small-sample efficiency of the optimal IV estimator in the class. Some Monte Carlo experiments compare the new methods with those of Hatanaka [1976]. For the DG P used in the Monte Carlo experiments, asymptotic efficiency is strictly improved by the new IVs, and experimental small-sample efficiency is improved as well.

O endividamento direto e o spread bancário ao longo dos ciclos econômicos: o caso das firmas brasileiras e a crise de 2009

A concessão de crédito bancário demanda esforço do agente credor que se dedica de forma ativa na obtenção de informações relativas à firma, até então não disponíveis ao público. Dado o hold up power do banco detentor de informações não públicas, este deveria poder cobrar spreads mais altos do que seria justificado unicamente pelo risco de crédito do tomador ao longo dos ciclos econômicos, sendo tal dinâmica mais acentuada em cenários de crise. Testa-se aqui esta hipótese e para isso são comparadas as variações do spread bancário médio da dívida de empresas brasileiras com diferentes composições de endividamento, levando-se em conta sua dependência do crédito bancário. Foram criadas: i) uma variável dummy identificando o acesso ao crédito direto para que se pudesse avaliar o seu efeito nos spreads; ii) outra dummy identificando cenários de recessão que permite avaliar o impacto do ciclo econômico nos spreads e iii) dummy interação que viabilizou o estudo do efeito combinado das duas variáveis anteriores. Fatores de risco individuais da firma, tais como tamanho, nível de alavancagem e sua natureza em termos de restrição a crédito foram controlados na análise. Os dados foram organizados em painel com os quais foi montada regressão linear valendo-se da técnica Estimated Generalized Least Squares (EGLS), alternativa ao Least Squares (LS) clássico. Encontrou-se evidência estatística de que em cenários de recessão econômica o acesso ao mercado direto de crédito traz efeito benéfico sobre os spreads bancários pagos pelas firmas.

Análise espacial e temporal de atributos do solo e da produtividade das culturas visando manejo específico em áreas agrícolas

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

A Spatial and Temporal Prediction Model of Corn Grain Yield as a Function of Soil Attributes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Regression with autocorrelated data: A study of time trend of global infant mortality rate

The infant mortality rate (IMR) is considered to be one of the most important indices of a country's well-being. Countries around the world and other health organizations like the World Health Organization are dedicating their resources, knowledge and energy to reduce the infant mortality rates. The well-known Millennium Development Goal 4 (MDG 4), whose aim is to archive a two thirds reduction of the under-five mortality rate between 1990 and 2015, is an example of the commitment. ^ In this study our goal is to model the trends of IMR between the 1950s to 2010s for selected countries. We would like to know how the IMR is changing overtime and how it differs across countries. ^ IMR data collected over time forms a time series. The repeated observations of IMR time series are not statistically independent. So in modeling the trend of IMR, it is necessary to account for these correlations. We proposed to use the generalized least squares method in general linear models setting to deal with the variance-covariance structure in our model. In order to estimate the variance-covariance matrix, we referred to the time-series models, especially the autoregressive and moving average models. Furthermore, we will compared results from general linear model with correlation structure to that from ordinary least squares method without taking into account the correlation structure to check how significantly the estimates change.^

Analysis of life expectancy using linear and nonlinear models

Life expectancy has consistently increased over the last 150 years due to improvements in nutrition, medicine, and public health. Several studies found that in many developed countries, life expectancy continued to rise following a nearly linear trend, which was contrary to a common belief that the rate of improvement in life expectancy would decelerate and was fit with an S-shaped curve. Using samples of countries that exhibited a wide range of economic development levels, we explored the change in life expectancy over time by employing both nonlinear and linear models. We then observed if there were any significant differences in estimates between linear models, assuming an auto-correlated error structure. When data did not have a sigmoidal shape, nonlinear growth models sometimes failed to provide meaningful parameter estimates. The existence of an inflection point and asymptotes in the growth models made them inflexible with life expectancy data. In linear models, there was no significant difference in the life expectancy growth rate and future estimates between ordinary least squares (OLS) and generalized least squares (GLS). However, the generalized least squares model was more robust because the data involved time-series variables and residuals were positively correlated. ^

Data compilation of hummingbird-pollinated plant species in the Brazilian Atlantic rain forest

We studied the relationship between flower size and nectar properties of hummingbird-visited flowers in the Brazilian Atlantic Forest. We analysed the nectar volume and concentration as a function of corolla length and the average bill size of visitors for 150 plant species, using the phylogenetic generalized least squares (PGLS) to control for phylogenetic signals in the data. We found that nectar volume is positively correlated with corolla length due to phylogenetic allometry. We also demonstrated that larger flowers provide better rewards for long-billed hummingbirds. Regardless of the causal mechanisms, our results support the hypothesis that morphological floral traits that drive partitioning among hummingbirds correspond to the quantity of resources produced by the flowers in the Atlantic Forest. We demonstrate that the relationship between nectar properties and flower size is affected by phylogenetic constraints and thus future studies assessing the interaction between floral traits need to control for phylogenetic signals in the data.

Variance-balanced designs under interference for dependent observations

It is shown that variance-balanced designs can be obtained from Type I orthogonal arrays for many general models with two kinds of treatment effects, including ones for interference, with general dependence structures. These designs can be used to obtain optimal and efficient designs. Some examples and design comparisons are given. (C) 2002 Elsevier B.V. All rights reserved.