Microtopographic drivers of vegetation patterning in blanket peatlands recovering from erosion

Blanket peatlands are globally rare, and many have been severely eroded. Natural recovery and revegetation (‘self-restoration’) of bare peat surfaces are often observed but are poorly understood, thus hampering the ability to reliably predict how these ecosystems may respond to climatic change. We hypothesised that morphometric/topographic-related microclimatic variables may be key controls on successional pathways and vegetation patterning in self-restoring blanket peatlands. We predicted the occurrence probability of four common peatland plant species (Calluna vulgaris, Eriophorum vaginatum, Eriophorum angustifolium, and Sphagnum spp.) using a digital surface model (DSM) generated from drone imagery at a pixel size of 20 cm, a suite of variables derived from the DSM, and an ensemble learning method (random forests). All four species models provided accurate fine-scale predictions of habitat suitability (accuracy > 90%, area under curve (AUC) > 0.9, recall and precision > 0.8). Mean elevation (within a 1 m radius) was often the most influential variable. Topographic position, wind exposure, and the heterogeneity or ruggedness of the surrounding surface were also important for all models, whilst light-related variables and a wetness index were important in the Sphagnum model. Our approach can be used to improve prediction of future responses and sensitivities of peatland recovery to climatic changes and as a tool to identify areas of blanket peatlands that may self-restore successfully without management intervention

The differentiation of snoring mechanisms using sound analysis

Ten subjects known to suffer from heavy snoring but not obstructive sleep apnoea were studied using the technique of sleep nasendoscopy. The mechanism of snoring was noted for each and sound recordings of the snoring noise were made. Six subjects were observed to snore using their soft palate only, three snored using only their tongue base and one snored using a combination of palate and tongue base. The sound recordings were subjected to computer analysis of waveform and frequency. Palatal flutter snoring and tongue base snoring appear to have distinct waveform and frequency patterns which allows them to be differentiated from each other.link_to_subscribed_fulltex

Biomechanics of snoring

A large proportion of the population either snores or suffers the snoring of others. Recent advances with the use of fibre-optic endoscopes have enabled surgeons to observe the inside of the pharynx while a patient is asleep and snoring. In this article we look at the underlying structure of the upper airway and explain, with the use of simple mechanical models, the aerodynamic events occurring inside the upper airway during snoring. © 1995.link_to_subscribed_fulltex