Arbuscular mycorrhizas are present on Spitsbergen.

A previous study of 76 plant species on Spitsbergen in the High Arctic concluded that structures resembling arbuscular mycorrhizas were absent from roots. Here, we report a survey examining the roots of 13 grass and forb species collected from 12 sites on the island for arbuscular mycorrhizal (AM) colonisation. Of the 102 individuals collected, we recorded AM endophytes in the roots of 41 plants of 11 species (Alopecurus ovatus, Deschampsia alpina, Festuca rubra ssp. richardsonii, putative viviparous hybrids of Poa arctica and Poa pratensis, Poa arctica ssp. arctica, Trisetum spicatum, Coptidium spitsbergense, Ranunculus nivalis, Ranunculus pygmaeus, Ranunculus sulphureus and Taraxacum arcticum) sampled from 10 sites. Both coarse AM endophyte, with hyphae of 5-10 µm width, vesicles and occasional arbuscules, and fine endophyte, consisting of hyphae of 1-3 µm width and sparse arbuscules, were recorded in roots. Coarse AM hyphae, vesicles, arbuscules and fine endophyte hyphae occupied 1.0-30.7, 0.8-18.3, 0.7-11.9 and 0.7-12.8% of the root lengths of colonised plants, respectively. Principal component analysis indicated no associations between the abundances of AM structures in roots and edaphic factors. We conclude that the AM symbiosis is present in grass and forb roots on Spitsbergen.

Modelling seasonal influenza: the role of weather and punctuated antigenic drift.

Seasonal influenza appears as annual oscillations in temperate regions of the world, yet little is known as to what drives these annual outbreaks and what factors are responsible for their inter-annual variability. Recent studies suggest that weather variables, such as absolute humidity, are the key drivers of annual influenza outbreaks. The rapid, punctuated, antigenic evolution of the influenza virus is another major factor. We present a new framework for modelling seasonal influenza based on a discrete-time, age-of-infection, epidemic model, which allows the calculation of the model's likelihood function in closed form. This framework may be used to perform model inference and parameter estimation rigorously. The modelling approach allows us to fit 11 years of Israeli influenza data, with the best models fitting the data with unusually high correlations in which r > 0.9. We show that using actual weather to modulate influenza transmission rate gives better results than using the inter-annual means of the weather variables, providing strong support for the role of weather in shaping the dynamics of influenza. This conclusion remains valid even when incorporating a more realistic depiction of the decay of immunity at the population level, which allows for discrete changes in immunity from year to year.