University of Arkansas

About: University of Arkansas is a education organization based out in Fayetteville, Arkansas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 17225 authors who have published 33329 publications receiving 941102 citations. The organization is also known as: Arkansas & UA.

Qualitative Analysis Techniques for the Review of the Literature

Abstract: In this article, we provide a framework for analyzing and interpreting sources that inform a literature review or, as it is more aptly called, a research synthesis. Specifically, using Leech and Onwuegbuzie’s (2007, 2008) frameworks, we delineate how the following four major source types inform research syntheses: talk, observations, drawings/photographs/videos, and documents. We identify 17 qualitative data analysis techniques that are optimal for analyzing one or more of these source types. Further, we outline the role that the following five qualitative data analysis techniques can play in the research synthesis: constant comparison analysis, domain analysis, taxonomic analysis, componential analysis, and theme analysis. We contend that our framework represents a first step in an attempt to help literature reviewers analyze and interpret literature in an optimally rigorous way. Keywords: Review of the Literature, Research Synthesis, Qualitative Analysis, Constant Comparison Analysis, Domain Analysis, Taxonomic Analysis, Componential Analysis, Theme Analysis

Avoiding Pitfalls of Using Species-Distribution Models in Conservation Planning

Abstract: : Museum records have great potential to provide valuable insights into the vulnerability, historic distribution, and conservation of species, especially when coupled with species-distribution models used to predict species' ranges. Yet, the increasing dependence on species-distribution models in identifying conservation priorities calls for a more critical evaluation of model robustness. We used 11 bird species of conservation concern in Brazil's highly fragmented Atlantic Forest and data on environmental conditions in the region to predict species distributions. These predictions were repeated for five different model types for each of the 11 bird species. We then combined these species distributions for each model separately and applied a reserve-selection algorithm to identify priority sites. We compared the potential outcomes from the reserve selection among the models. Although similarity in identification of conservation reserve networks occurred among models, models differed markedly in geographic scope and flexibility of reserve networks. It is essential for planners to evaluate the conservation implications of false-positive and false-negative errors for their specific management scenario before beginning the modeling process. Reserve networks selected by models that minimized false-positive errors provided a better match with priority areas identified by specialists. Thus, we urge caution in the use of models that overestimate species' occurrences because they may misdirect conservation action. Our approach further demonstrates the great potential value of museum records to biodiversity studies and the utility of species-distribution models to conservation decision-making. Our results also demonstrate, however, that these models must be applied critically and cautiously. Resumen: Los registros de museos tienen un gran valor potencial al proporcionar entendimiento sobre la vulnerabilidad, distribucion historica y conservacion de especies, especialmente cuando se combinan con modelos de distribucion de especies utilizados para predecir los rangos de distribucion de las especies. No obstante, la mayor dependencia sobre los modelos de distribucion de especies para la identificacion de prioridades de conservacion requiere una evaluacion critica de la robustez del modelo. Utilizamos 11 especies de aves de interes para la conservacion en el muy fragmentado Bosque Atlantico en Brasil asi como datos de condiciones ambientales en la region para predecir la distribucion de las especies. Estas predicciones fueron repetidas para cinco tipos diferentes de modelos para cada una de las 11 especies de aves. Luego combinamos estas distribuciones de especies para cada modelo por separado y aplicamos un algoritmo de seleccion de reservas para identificar sitios prioritarios. Comparamos los resultados potenciales de la seleccion de reservas entre modelos. Aunque hubo similitud entre los modelos en la identificacion de redes de reservas, los modelos difirieron marcadamente en el alcance geografico y la flexibilidad de las redes de reservas. Es de importancia fundamental para los planificadores evaluar las implicaciones sobre la conservacion de errores falsos positivos y falsos negativos para su escenario de manejo especifico antes de comenzar el proceso de modelado. Las redes de reservas seleccionadas por modelos que minimizaron los errores falsos positivos proporcionaron mejor correspondencia con las areas prioritarias identificadas por especialistas. Por lo tanto, instamos a tener precaucion con el uso de modelos que sobreestiman la ocurrencia de especies porque pueden desviar las acciones de conservacion. Nuestro metodo demuestra ademas el gran potencial de los registros de museos en estudios de biodiversidad y la utilidad de los modelos de distribucion de especies para la toma de decisiones de conservacion. Sin embargo, nuestros resultados demuestran que estos modelos deben ser aplicados critica y cuidadosamente.

IS6110, an IS-like element of Mycobacterium tuberculosis complex.

Abstract: Mobile genetic elements are useful genetic tools. They have been found in most organisms which have been examined (for recent reviews see 1). /S900 was isolated from M. paratuberculosis (2) and IS6100 from a M. fortuitum strain (our unpublished results). IS elements have been used as taxonomic markers useful for diagnostic purposes, (2, 3). From a IA. tuberculosis cosmid library constructed in pHC79 (4), an IS-like element, 1S6110, was identified as a repeated sequence, by screening the library with labelled M. tuberculosis total DNA. This sequence (1361 nt) possesses characteristics of IS elements, i.e., inverted (28bp with 3 mismatched bp) and direct (3bp) repeats of the target sequence at its extremities. A search in the EMBL data bank has revealed homologies with IS3411, an insertion element from E. coli (5). Cross-hybridization was observed between 1S6110 and a repeated sequence previously isolated from M. tuberculosis (6). IS6110 has been found in M. tuberculosis and M. bovis but not in any of the other mycobacteria tested (our unpublished data). Therefore, IS6110 will be used as probe for the identification of the M. tuberculosis complex. ACKNOWLEDGEMENTS