Morphological comparisons of metacarpal I for Australovenator wintonensis and Rapator ornitholestoides: implications for their taxonomic relationships

WHITE, M.A., FALKINGHAM, P.L., COOK, A.G., HOCKNULL, S.A. & ELLIOTT, D.A., 2013. Morphological comparisons of metacarpal I for Australovenator wintonensis and Rapator ornitholestoides: implications for their taxonomic relationships. Alcheringa 37, 1 - 7. ISSN 0311-5518.

Various comparisons of left metacarpal I of the Australovenator wintonensis holotype have been made with Rapator ornitholestoides. These specimens were identified as being morphologically more similar than either was to that of the neovenatorid Megaraptor namunhuaiquii. Owing to the poor preservation of A. wintonensis and R. ornitholestoides, distinct morphological separation between the two appeared minimal. The recent discovery of a near perfectly preserved right metacarpal I of A. wintonensis enables a direct and accurate comparison with R. ornitholestoides. Distinct morphological differences exist between the metacarpals of the two species. A re-evaluation of the age of the A. wintonensis holotype site (AODL 85 ‘Matilda Site’) with zircon dating reveals a maximum age of 95 Ma, 10 Ma younger than the Griman Creek Formation at Lightning Ridge, from which R. ornitholestoides was recovered. This age difference detracts from the probability that the specimens belong to the same genus.

Matt A. White? [fossilised@hotmail.com], School of Engineering, The University of Newcastle, Callaghan, New South Wales 2308, Australia; Peter L. Falkingham? [pfalkingham@rvc.ac.uk], Department of Comparative Biomedical Sciences, Structure and Motion Laboratory, Royal Veterinary College, London, UK; Alex G. Cook [alex.cook@y7mail.com] and Scott A. Hocknull [scott.hocknull@qm.qld.gov.au], Ancient environments, Queensland Museum, Hendra, Queensland, 4011, Australia; David A. Elliott [david.elliott@aaod.com.au], Australian Age of Dinosaurs Museum of Natural History, The Jump Up, Winton, Queensland, 4735, Australia. ?Also affiliated with Australian Age of Dinosaurs Museum of Natural History, The Jump Up, Winton, Queensland 4735, Australia. ?Also affiliated with Department of Ecology and Evolutionary Biology, Division of Biology and Medicine, Brown University, USA. Received 22.9.2012; revised 13.1.2013; accepted 17.1.2013.     

Something Borrowed and Something New?: Welfare Reform and Social Science

William M. Epstein, Welfare in America : How Social Science Fails the Poor.
Herbert J. Gans, The War Against the Poor : The Underclass and Antipoverty Policy
Joel F. Handler, The Poverty of Welfare Reform     

Seasonal weather sensitivity,temperature thresholds,and climate change impacts for park visitation

Historical park visitation and weather data, taken at the daily time scale from 2000 to 2009 for Pinery Provincial Park in southern Ontario (Canada), were analysed as an objective measure of the weather sensitivity, temperature thresholds, and potential impacts of projected climate change for park visitation. Three seasonal weather-visitation models were constructed using multivariable linear regression (peak, shoulder, off-season). To account for both natural and institutional seasonality, the weather-visitation models included both climatic (temperature, precipitation) and social (weekends, holidays) variables, which demonstrated equably comparable effects on visitation across the three models. Critical temperature thresholds were identified for each season using one-way analysis of variance to determine the range of temperatures within which the threshold was evident; the specific degree of temperature associated with the threshold was identified within the seasonal regression models. Temperatures over 33 °C during the peak season and over 29 °C during the shoulder season indicated critical thresholds at which point conditions that were ‘too hot’ for some caused a decline in visitation. Furthermore, temperatures below 11 °C indicated another critical threshold, where conditions were ‘too cold’ for most and therefore park visitation was less sensitive to temperature variability below this threshold. A partial sensitivity analysis for the impact of a warmer, wetter climate on park visitation was conducted, illustrating the effect of a 1 °C to 5 °C warming in maximum temperatures, coupled with a 5% to 15% increase in total precipitation. In response to projected climate change, the weather-visitation models suggested that for each additional degree of warming experienced, despite the negative effects of increasing precipitation and more frequent heat extremes, annual park visitation could increase by 3.1%, annually. The projected increase in park visitation as a result of rising temperatures was mainly associated with shoulder season visitation, with only minor increases in peak season visitation.     

Bayesian Areal Wombling for Geographical Boundary Analysis

In the analysis of spatially referenced data, interest often focuses not on prediction of the spatially indexed variable itself, but on boundary analysis , that is, the determination of boundaries on the map that separate areas of higher and lower values. Existing boundary analysis methods are sometimes generically referred to as wombling , after a foundational article by Womble (1951). When data are available at point level (e.g., exact latitude and longitude of disease cases), such boundaries are most naturally obtained by locating the points of steepest ascent or descent on the fitted spatial surface (Banerjee, Gelfand, and Sirmans 2003). In this article, we propose related methods for areal data (i.e., data which consist only of sums or averages over geopolitical regions). Such methods are valuable in determining boundaries for data sets that, perhaps due to confidentiality concerns, are available only in ecological (aggregated) format, or are only collected this way (e.g., delivery of health-care or cost information). After a brief review of existing algorithmic techniques (including that implemented in the commercial software BoundarySeer), we propose a fully model-based framework for areal wombling, using Bayesian hierarchical models with posterior summaries computed using Markov chain Monte Carlo methods. We explore the suitability of various existing hierarchical and spatial software packages (notably S-plus and WinBUGS) to the task, and show the approach's superiority over existing nonstochastic alternatives, both in terms of utility and average mean square error behavior. We also illustrate our methods (as well as the solution of advanced modeling issues such as simultaneous inference) using colorectal cancer late detection data collected at the county level in the state of Minnesota.     

The Location Choice of Employment‐based Immigrants among U.S. Metro Areas*

Abstract. This paper examines the initial location choice of legal employment‐based immigrants to the United States using Immigration and Naturalization Service data on individual immigrants, as well as economic, demographic, and social data to characterize the 298 metropolitan areas we define as the universal choice set. Focusing on interactions between place characteristics and immigrant characteristics, we provide multinomial logit model estimates for the location choices of about 38,000 employment‐based immigrants to the United States in 1995, focusing on the top 10 source countries. We find that, as groups, immigrants from nearly all countries are attracted to large cities with superior climates, and to cities with relatively well‐educated adults and high wages. We also find evidence that employment‐based immigrants tend to choose cities where there are relatively few immigrants of nationalities other than their own. However, when we introduce interaction terms to account for the sociodemographic characteristics of the individual immigrants, we find that the estimated effects of location destination factors can reverse as one takes account of the age, gender, marital status, and previous occupation of the immigrants.