19 research outputs found
Habitat Preferences of Butterflies in the Bumbuna Forest, Northern Sierra Leone
The habitat preferences of the butterfly fauna were studied in the Bumbuna Forest Reserve in northern Sierra Leone. The intact forest reserve and a secondary forest regrowth, disturbed as a result of slash-and-burn agriculture, were compared to savanna habitats. Of the 290 specimens collected, 195 butterfly species were included, of which significant proportion were Nymphalidae. Of the 147 forest species, 111 (75.5%) showed preferences for the forest habitats, while 70 (47.6%) and 34 (23.1%) preferred disturbed and savannah habitats, respectively. Numerically, a comparable proportion of savannah species were recorded in the 18 disturbed (73.9%) and 16 savannah habitats (63.2%). Accumulated species richness and diversity indices were lower in the disturbed habitats compared to the forest reserve, but lowest in the savanna habitats. However, a large proportion of forest species, especially those with either a more restricted geographic range or species for which no information on geographic distribution was available, were exclusively captured in the forest patches. The survey indicated the presence of a rich butterfly fauna, which should be systematically collected for further research and study in order to build a good taxonomic database for Sierra Leone
Comparação entre os métodos de extração de metacercárias de Ascocotyle sp (Trematoda: Digenea) dos tecidos de Mugil liza Valenciennes, 1836 (Teleostei: Mugilidae)
Big data, qualitative style:A breadth‑and‑depth method for working with large amounts of secondary qualitative data
Archival storage of data sets from qualitative studies presents opportunities for combining small-scale data sets for reuse/secondary analysis. In this paper, we outline our approach to combining multiple qualitative data sets and explain why working with a corpus of 'big qual' data is a worthwhile endeavour. We present a new approach that iteratively combines recursive surface thematic mapping and in-depth interpretive work. Our breadth-and-depth method involves a series of steps: 1) surveying archived data sets to create a new assemblage of data; 2) recursive surface thematic mapping in dialogue with 3) preliminary ‘test pit’ analysis, remapping and repetition of preliminary analysis; and 4) in-depth analysis of the type that is familiar to most qualitative researchers. In so doing, we show how qualitative researchers can conduct ‘big qual’ analysis while retaining the distinctive order of knowledge about social processes that is the hallmark of rigorous qualitative research, with its integrity of attention to nuanced context and detail
The potential mechanistic link between allergy and obesity development and infant formula feeding
Does DNA methylation in the promoter region of the ATXN3 gene modify age at onset in MJD (SCA3) patients?
Phanerozoic thermochronology record of Afro-Arabia through space and time
Low-temperature thermochronology has been widely used in eastern Africa and Arabia (Afro-Arabia) to investigate the long-term thermal evolution of the crust in response to Phanerozoic tectonism. Yet, utilisation of this invaluable thermochronology record to inform numerical investigations into the long-term tectonothermal, geodynamic and landscape evolution of the region has been limited by the dispersion of these data across numerous disparate case studies. Here, we present a relational database of apatite (1787), zircon (68) and titanite fission-track (97) analyses, and apatite (1,945), zircon (3310), and titanite (U-Th)/He (83) ages, including 465 new fission-track and 2,583 new single-grain (U-Th)/He analyses from the region. Where available, all detailed data needed for performing thermal history modelling are presented. Also included are 668 digitised thermochronology-derived thermal history simulations. Collectively, this comprehensive database records the Phanerozoic thermal evolution of Afro-Arabia through space and time. The machine-readable database is made publicly available through the EarthBank platform, enabling 4D (3D through time) geospatial data interrogation
