Background: Understanding the mechanisms that influence grazing selectivity in patchy environments is vital to promote sustainable production and conservation of cultivated and natural grasslands. To better understand how patch size and spatial dynamics influence selectivity in cattle, we examined grazing selectivity under 9 different treatments by offering alfalfa and fescue in patches of 3 sizes spaced with 1, 4, and 8 m between patches along an alley. We hypothesized that (1) selectivity is driven by preference for the forage species that maximizes forage intake over feeding scales ranging from single bites to patches along grazing paths, (2) that increasing patch size enhances selectivity for the preferred species, and that (3) increasing distances between patches restricts selectivity because of the aggregation of scale-specific behaviours across foraging scales.
Results: Cows preferred and selected alfalfa, the species that yielded greater short-term intake rates (P < 0.0001) and greater daily intake potential. Selectivity was not affected by patch arrangement, but it was scale dependent. Selectivity tended to emerge at the scale of feeding stations and became strongly significant at the bite scale, because of differences in bite mass between plant species. Greater distance between patches resulted in longer patch residence time and faster speed of travel but lower overall intake rate, consistent with maximization of intake rate. Larger patches resulted in greater residence time and higher intake rate.
Conclusion: We conclude that patch size and spacing affect components of intake rate and, to a lesser extent, the selectivity of livestock at lower hierarchies of the grazing process, particularly by enticing livestock to make more even use of the available species as patches are spaced further apart. Thus, modifications in the spatial pattern of plant patches along with reductions in the temporal and spatial allocation of grazing may offer opportunities to improve uniformity of grazing by livestock and help sustain biodiversity and stability of plant communities.
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http://dx.doi.org/10.1186/1472-6785-9-9 | DOI Listing |
Sci Rep
December 2024
College of Sports, Beihua University, Jilin, 132000, China.
In order to eliminate the impact of camera viewpoint factors and human skeleton differences on the action similarity evaluation and to address the issue of human action similarity evaluation under different viewpoints, a method based on deep metric learning is proposed in this article. The method trains an automatic encoder-decoder deep neural network model by means of a homemade synthetic dataset, which maps the 2D human skeletal key point sequence samples extracted from motion videos into three potential low-dimensional dense spaces. Action feature vectors independent of camera viewpoint and human skeleton structure are extracted in the low-dimensional dense spaces, and motion similarity metrics are performed based on these features, thereby effectively eliminating the effects of camera viewpoint and human skeleton size differences on motion similarity evaluation.
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December 2024
Departamento de Biodiversidade, Universidade Estadual Paulista, Rio Claro, SP, Brazil.
Ecological Corridors (ECs) are proposed as cost-effective solutions to improve ecological connectivity in fragmented landscapes. Planning the implementation of ECs must take into account landscape features as they affect the viability of the endeavor and the ECs associated costs. A novel set of geoprocessing tools were used to assess (i) economic viability; (ii) socioeconomic cost-effectiveness; and (iii) to determine priority targets for ECs establishment in a highly fragmented region of Atlantic Forest.
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November 2024
University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
The achievable spatial resolution of C metabolic images acquired with hyperpolarized C-pyruvate is worse than H images typically by an order of magnitude due to the rapidly decaying hyperpolarized signals and the low gyromagnetic ratio of C. This study is to develop and characterize a volumetric patch-based super-resolution reconstruction algorithm that enhances spatial resolution C cardiac MRI by utilizing structural information from H MRI. The reconstruction procedure comprises anatomical segmentation from high-resolution H MRI, calculation of a patch-based weight matrix, and iterative reconstruction of high-resolution multi-slice C MRI.
View Article and Find Full Text PDFJ Neuropathol Exp Neurol
December 2024
Department of Pathology and Laboratory Medicine, University of California Davis, Sacramento, CA, United States.
Microinfarcts and microhemorrhages are characteristic lesions of cerebrovascular disease. Although multiple studies have been published, there is no one universal standard criteria for the neuropathological assessment of cerebrovascular disease. In this study, we propose a novel application of machine learning in the automated screening of microinfarcts and microhemorrhages.
View Article and Find Full Text PDFCase Rep Dent
December 2024
Department of Paediatric Dentistry, Selayang Hospital (Ministry of Health), Batu Caves, Selangor, Malaysia.
Infantile haemangioma (IH) is the most common childhood tumour, often developing in the head and neck region. It may cause disfigurement, functional impairment, or tooth developmental issues when it is present in the oral cavity. We report a case of a 2-month-old boy referred to the paediatric dentistry team with a segmental IH involving the left periorbital, cheek, and hard palate.
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