1,063 research outputs found
Urban grasslands support threatened water voles
Urbanisation is often linked with habitat loss and a reduction in species richness but some species may be able to adapt to urban environments. Water voles Arvicola amphibius, a rapidly declining species in the UK, have recently been recorded in isolated grassland habitats in Glasgow, Scotland’s largest city (human population 1.2 million). The aim of this study was to determine the distribution and habitat characteristics of water vole populations occupying these dry grasslands. Field work was undertaken from March to October 2014 in a 34 km2 study area located 3 km east of the city centre. Field sign transects recorded water vole presence in 21/65 (32%) and 19/62 (31%) surveyed sites in spring and autumn, respectively. Vole occupancy increased with distance from water and was greatest in parkland, followed by sites with rank vegetation and roadside habitats. Occupancy was lower where signs of predators were recorded but surprisingly occupancy was found to be greater in the most disturbed sites, perhaps linked to the fact that many of these sites were public parks containing suitable grassland. Sites occupied by water voles were classed as neutral grasslands with species composition dominated by two main species. The number of grassland sites occupied by water voles, especially within public areas suggests that careful management of these urban grassland habitats will benefit the conservation of this highly threatened species in the UK
Clustering South African households based on their asset status using latent variable models
The Agincourt Health and Demographic Surveillance System has since 2001
conducted a biannual household asset survey in order to quantify household
socio-economic status (SES) in a rural population living in northeast South
Africa. The survey contains binary, ordinal and nominal items. In the absence
of income or expenditure data, the SES landscape in the study population is
explored and described by clustering the households into homogeneous groups
based on their asset status. A model-based approach to clustering the Agincourt
households, based on latent variable models, is proposed. In the case of
modeling binary or ordinal items, item response theory models are employed. For
nominal survey items, a factor analysis model, similar in nature to a
multinomial probit model, is used. Both model types have an underlying latent
variable structure - this similarity is exploited and the models are combined
to produce a hybrid model capable of handling mixed data types. Further, a
mixture of the hybrid models is considered to provide clustering capabilities
within the context of mixed binary, ordinal and nominal response data. The
proposed model is termed a mixture of factor analyzers for mixed data (MFA-MD).
The MFA-MD model is applied to the survey data to cluster the Agincourt
households into homogeneous groups. The model is estimated within the Bayesian
paradigm, using a Markov chain Monte Carlo algorithm. Intuitive groupings
result, providing insight to the different socio-economic strata within the
Agincourt region.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS726 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Molecular characterization of Trichomonas gallinae isolates recovered from the Canadian Maritime provinces’ wild avifauna reveals the presence of the genotype responsible for the European finch trichomonosis epidemic and additional strains
Finch trichomonosis, caused by Trichomonas gallinae, emerged in the Canadian Maritime provinces in 2007 and has since caused ongoing mortality in regional purple finch (Carpodacus purpureus) and American goldfinch (Carduelis tristis) populations. Trichomonas gallinae was isolated from (1) finches and rock pigeons (Columbia livia) submitted for post-mortem or live-captured at bird feeding sites experiencing trichomonosis mortality; (2) bird seed at these same sites; and (3) rock pigeons live-captured at known roosts or humanely killed. Isolates were characterized using internal transcribed spacer (ITS) region and iron hydrogenase (Fe-hyd) gene sequences. Two distinct ITS types were found. Type A was identical to the UK finch epidemic strain and was isolated from finches and a rock pigeon with trichomonosis; apparently healthy rock pigeons and finches; and bird seed at an outbreak site. Type B was obtained from apparently healthy rock pigeons. Fe-hyd sequencing revealed six distinct subtypes. The predominant subtype in both finches and the rock pigeon with trichomonosis was identical to the UK finch epidemic strain A1. Single nucleotide polymorphisms in Fe-hyd sequences suggest there is fine-scale variation amongst isolates and that finch trichomonosis emergence in this region may not have been caused by a single spill-over event
The depth of Sooty Shearwater Ardenna grisea burrows varies with habitat and increases with competition for space
The Sooty Shearwater Ardenna grisea, an abundant but declining petrel, is one of many seabird species that construct breeding burrows, presumably because these confer protection from predators and the elements. Little is known about the causes of variation in Sooty Shearwater burrow architecture, which can differ markedly both within and between breeding sites. We hypothesize that burrow architecture varies in response to habitat type and competition for space. To address these hypotheses, we recorded Sooty Shearwater burrow dimensions on Kidney Island, the largest Sooty Shearwater colony in the Falkland Islands, South Atlantic, and modelled these as functions of burrow density (a proxy for competition) and habitat indices. Our models suggest that Sooty Shearwaters burrow further underground in response to competition for breeding space, and that soil underlying dense tussac grass Poa flabellata is more easily excavated than other substrates, indicating how vegetation restoration could aid the conservation of this species
The openVA Toolkit for Verbal Autopsies
Verbal autopsy (VA) is a survey-based tool widely used to infer cause of
death (COD) in regions without complete-coverage civil registration and vital
statistics systems. In such settings, many deaths happen outside of medical
facilities and are not officially documented by a medical professional. VA
surveys, consisting of signs and symptoms reported by a person close to the
decedent, are used to infer the cause of death for an individual, and to
estimate and monitor the cause of death distribution in the population. Several
classification algorithms have been developed and widely used to assign cause
of death using VA data. However, The incompatibility between different
idiosyncratic model implementations and required data structure makes it
difficult to systematically apply and compare different methods. The openVA
package provides the first standardized framework for analyzing VA data that is
compatible with all openly available methods and data structure. It provides an
open-sourced, R implementation of several most widely used VA methods. It
supports different data input and output formats, and customizable information
about the associations between causes and symptoms. The paper discusses the
relevant algorithms, their implementations in R packages under the openVA
suite, and demonstrates the pipeline of model fitting, summary, comparison, and
visualization in the R environment
Supplementary materials for "Bayesian factor models for probabilistic cause of death assessment with verbal autopsies"
Supplementary materials for "Bayesian factor models for probabilistic cause of death assessment with verbal autopsies": p. 1-
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