Climatic Factors Influencing the Anthrax Outbreak of 2016 in Siberia, Russia.

In 2016, an outbreak of anthrax killing thousands of reindeer and affecting dozens of humans occurred on the Yamal peninsula, Northwest Siberia, after 70 years of epidemiological situation without outbreaks. The trigger of the outbreak has been ascribed to the activation of spores due to permafrost thaw that was accelerated during the summer heat wave. The focus of our study is on the dynamics of local environmental factors in connection with the observed anthrax revival. We show that permafrost was thawing rapidly for already 6 years before the outbreak. During 2011-2016, relatively warm years were followed by cold years with a thick snow cover, preventing freezing of the soil. Furthermore, the spread of anthrax was likely intensified by an extremely dry summer of 2016. Concurrent with the long-term decreasing trend in the regional annual precipitation, the rainfall in July 2016 was less than 10% of its 30-year mean value. We conclude that epidemiological situation of anthrax in the previously contaminated Arctic regions requires monitoring of climatic factors such as warming and precipitation extremes.

A comparison of phenological models of leaf bud burst and flowering of boreal trees using independent observations.

We compared and tested Thermal Time, Sequential, Parallel and Flexible phenological models of leaf bud burst in birch (Betula pendula Roth. and B. pubescens Ehrh.) and flowering in bird cherry (Prunus padus L.) and rowan (Sorbus aucuparia L.). We used phenological records from Oulainen-Ohineva (64 degrees 13' N, 24 degrees 53' E) in central Finland from 1953 to 2002 to estimate model parameters. We tested the models with data collected in all but six years between 1896 and 2002 in southern and central Finland; we divided this dataset into two 50-year datasets. The use of three datasets enabled us to test the models with data that were independent of the parameter fitting data, facilitating robust evaluation of model performance. Several models that fitted the parameterization data well showed poorer performance when tested with the independent data. This may be because the models were over-parameterized and able to adapt to noise in the data in addition to the phenological phenomenon itself. Simple Thermal Time models performed best with independent data, and Sequential and Parallel models were similar in prediction accuracy. Although Thermal Time models simulated boreal phenological events under current climatic conditions, some precautions are needed with simulations of climatic warming. For example, changed conditions may increase the relative importance of chilling in the timing of bud burst under elevated temperature conditions, which could alter the performance of phenological models.