Long-distance dispersal (LDD) of wind-borne organisms is central to quantifying risk for transgenic escape and gene flow, control of pests and invasions, persistence in fragmented landscapes and species co-existence; yet LDD remains notoriously difficult to define, measure and model. This difficulty has shaped the current paradigm that the frequency and spatial extent of LDD events are almost impossible to predict.
In the September issue of The American Naturalist, G. G. Katul (Duke University) and colleagues introduce a mechanistic analytical model for estimating dispersal kernels of seeds and their escape probability from the canopy, using simplifications to well-established turbulent transport theories. The model parameters--wind statistics, seed release height, and seed terminal velocity--are clearly interpretable and can easily be measured independently of dispersal data, as compared to the synthetic parameters of equivalent phenomenological analytical models that necessitate dispersal data for calibration.
A necessary condition for LDD, seed uplifting and escape from the canopy, along with other key attributes of the dispersal kernel, were reproduced well by the model. To meet the increasing demand for proper evaluation of ecological risk reduction by employing less subjective and more transparent methods, mathematical models should make their assumptions explicit and should realistically incorporate the key biological and physical processes underlying environmental changes.
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At TU Wien, an alternative for resource intensive formwork for the construction of concrete domes was developed. It is now used in a test dome for the Austrian Federal Railways Infrastructure (ÖBB Infrastruktur).
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Many pathogens use certain sugar compounds from their host to help conceal themselves against the immune system. Scientists at the University of Bonn have now, in cooperation with researchers at the University of York in the United Kingdom, analyzed the dynamics of a bacterial molecule that is involved in this process. They demonstrate that the protein grabs onto the sugar molecule with a Pac Man-like chewing motion and holds it until it can be used. Their results could help design therapeutics that could make the protein poorer at grabbing and holding and hence compromise the pathogen in the host. The study has now been published in “Biophysical Journal”.
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UMD, NOAA collaboration demonstrates suitability of in-orbit datasets for weather satellite calibration
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