Search Results (5)

The transnational turn in migrant studies emphasizes complexities in migration, partly related to the agency that migrants may exercise. Chapter 44 in the biblical Book of Jeremiah holds a story of migration that is peculiarly insensitive to such aspects: religious practices performed by a local community are condemned, and so are they. Through a series of analytical steps—reflection on historical conditions of migration at the time, on the historical value of the biblical sources, on a cognitive theory of mimesis in narrative, and on praxeological analysis—this study tries to regain a view of migratory complexity and migrants’ agency in that story. The reading uncovers how migrants were “doing community” through their religious practices and through their dispute with the prophet. The story reflects an enduring pattern of struggle between local communities and trans-local forces. It also reflects change in traditional communal patterns due to social changes brought about by migration. Full article

This study investigated using a 160-slice multidetector computed tomography (CT) scanner for conscious image acquisition in dogs with upper airway disease, and describes findings in dogs that had previously undergone soft palate surgery. Seventeen client-owned dogs with upper airway disease were retrospectively reviewed, and classified into three groups: group I, “untreated brachycephalic obstructive airway syndrome (BOAS) patients”; group II, “previously treated BOAS patients”; and group III, “patients with respiratory disease other than BOAS”. Data included signalment, clinical history, direct laryngoscopy and endoscopy findings, previous surgeries and CT findings. CT scans in group I revealed overlong and thickened soft palates in all dogs, and signs of laryngeal collapse in four dogs. Patients in group II exhibited normal soft palate lengths, while patients in group III displayed various findings such as nasopharyngeal narrowing and tracheal collapse. Upper airway examinations under general anaesthesia confirmed most CT findings. This study demonstrates the feasibility and value of conscious CT scanning for assessing upper airway diseases in dogs, providing valuable diagnostic information while eliminating the need for chemical immobilisation, thus reducing patient stress and cost. These findings offer new insight into upper airway anatomy in awake patients, especially in brachycephalic breeds, and lay a foundation for future research. Full article

The scavenging of atmospheric trace gases has been recognized as one of the lifestyle-defining capabilities of microorganisms in terrestrial polar ecosystems. Several metagenome-assembled genomes of as-yet-uncultivated methanotrophic bacteria, which consume atmospheric CH₄ in these ecosystems, have been retrieved in cultivation-independent studies. In this study, we isolated and characterized a representative of these methanotrophs, strain D3K7, from a subarctic soil of northern Russia. Strain D3K7 grows on methane and methanol in a wide range of temperatures, between 5 and 30 °C. Weak growth was also observed on acetate. The presence of acetate in the culture medium stimulated growth at low CH₄ concentrations (~100 p.p.m.v.). The finished genome sequence of strain D3K7 is 4.15 Mb in size and contains about 3700 protein-encoding genes. According to the result of phylogenomic analysis, this bacterium forms a common clade with metagenome-assembled genomes obtained from the active layer of a permafrost thaw gradient in Stordalen Mire, Abisco, Sweden, and the mineral cryosol at Axel Heiberg Island in the Canadian High Arctic. This clade occupies a phylogenetic position in between characterized Methylocapsa methanotrophs and representatives of the as-yet-uncultivated upland soil cluster alpha (USCα). As shown by the global distribution analysis, D3K7-like methanotrophs are not restricted to polar habitats but inhabit peatlands and soils of various climatic zones. Full article

A land cover map of two arctic catchments near the Abisko Scientific Research Station was obtained based on a classification from a Sentinel-2 satellite image and a ground survey performed in July 2022. The two contiguous catchments, Miellajokka and Stordalen, are covered by various ecotypes, from boreal forest to alpine tundra and peatland. Two classification algorithms, support vector machine and random forest, were tested and gave very similar results. The percentage of correctly classified pixels was over 88% in both cases. The developed workflow relies solely on open-source software and acquired ground observations. Space organization was directed by the altitude as demonstrated by the intersection of the land cover with the topography. Comparison between this new land cover map and previous ones based on data acquired between 2008 and 2011 shows some trends in vegetation cover evolution in response to climate change in the considered area. This land cover map is key input data for permafrost modeling and, hence, for the quantification of climate change impacts in the studied area. Full article

Rising global temperatures tied to increases in greenhouse gas emissions are impacting high latitude regions, leading to changes in vegetation composition and feedbacks to climate through increased methane (CH₄) emissions. In subarctic peatlands, permafrost collapse has led to shifts in vegetation species on landscape scales with high spatial heterogeneity. Our goal was to provide a baseline for vegetation distribution related to permafrost collapse and changes in biogeochemical processes. We collected unmanned aerial system (UAS) imagery at Stordalen Mire, Abisko, Sweden to classify vegetation cover types. A series of digital image processing routines were used to generate texture attributes within the image for the purpose of characterizing vegetative cover types. An artificial neural network (ANN) was developed to classify the image. The ANN used all texture variables and color bands (three spectral bands and six metrics) to generate a probability map for each of the eight cover classes. We used the highest probability for a class at each pixel to designate the cover type in the final map. Our overall misclassification rate was 32%, while omission and commission error by class ranged from 0% to 50%. We found that within our area of interest, cover classes most indicative of underlying permafrost (hummock and tall shrub) comprised 43.9% percent of the landscape. Our effort showed the capability of an ANN applied to UAS high-resolution imagery to develop a classification that focuses on vegetation types associated with permafrost status and therefore potentially changes in greenhouse gas exchange. We also used a method to examine the multiple probabilities representing cover class prediction at the pixel level to examine model confusion. UAS image collection can be inexpensive and a repeatable avenue to determine vegetation change at high latitudes, which can further be used to estimate and scale corresponding changes in CH₄ emissions. Full article