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Tree stand dynamics, changes in the ground vegetation and soils, and species diversity of wood-decaying fungi were studied in pristine middle boreal spruce forests affected by a surface fire in the Vodlozersky National Park (Arkhangelsk Region, Russia) in 2011. In the third year after the fire, the burnt area was dominated by birch, which contributed an average of 72% to the total amount of major tree species regeneration. In sites affected by a high-severity fire, the ground vegetation cover did not exceed 40%, with Chamaenerion angustifolium (L.) Scop. and Marchantia polymorpha L. dominating in the first years after. By the tenth year, the diversity of the newly forming tree layer increased from 5 to 11 species and natural thinning of deciduous tree regeneration was already underway, although its amount was still over 100,000 plants per hectare throughout. By the end of the first post-fire decade, Picea abies (L.) H. Karst. and Pinus sylvestris L. accounted for 11% of the total regeneration. The occurrence and cover of pyrogenic species Chamaenerion angustifolium and Marchantia polymorpha declined sharply at this stage. Vegetation in sites affected by mid-severity fire was mostly regenerating through propagation of the survivor Avenella flexuosa (L.) Drejer, Vaccinium myrtillus L., V. vitis-idaea, etc. In the burnt area, the species diversity of wood-destroying fungi was reduced compared to the adjacent unburned areas, and it was the same in both heavily and moderately burnt areas. This is probably due to the fact that the downed deadwood in post-fire sites was trunks of the same age and in the same degree of decay whereas the total amount of downed deadwood in the control (unburnt forest) was lower but featuring all stages of decay and, furthermore, there were plenty of fungi-populated dead standing and weakened overmature trees.

The Sakha Republic (Yakutia) has a large territory that covers various climatic zones and a network of water bodies and thus is exposed to a wide range of natural emergencies. The most typical of them is spring-summer floods that cause flooding of vast territories, facilities and infrastructure, thus causing enormous damage to the economy; it determines relevance of developing and perfecting flood prediction methods to reduce the hazard level and possible damage. This research presents application of multiparametric models and neuron networks for development of a predictive model that allows forecasting the spring flooding hazard from statistical data accumulated through 44 years of observation and regressive modeling. The proposed methods allow evaluating the spring flood water levels as a function of various factors (thickness of ice, temperature, etc.) with sufficient accuracy, as confirmed with the results of predicting maximum water levels for two segments of the Lena River. Selection of the river course segments was determined by nearby location of potentially hazardous facilities whose flooding may cause significant property loss. Factors influencing spring flood levels have been determined.

Охарактеризовано общее распространение редкого, находящегося под угрозой исчезновения вида Chara strigosa A. Braun ( Streptophyta: Chavales), приведены все известные местонахождения в России, включая новые на севере Дальнего Востока, в Восточной Сибири, Алтае, центральной части Восточно-Европейской равнины и юго-восточной Фенноскандии. Они существенно дополняют представления о восточной части ареала этого ледникового реликта и заполняют существующие пробелы между восточноевропейскими и южноуральскими местонахождениями. На основе опубликованных и оригинальных данных составлена карта ареала. Приведено подробное морфологическое описание изученных образцов. Оценена возможность устойчивого существования популяций вида в отдельных регионах. Как редкий вид с узким экологическим диапазоном, включенный в Красную книгу России, C. strigosa нуждается в охране на территории Архангельской, Иркутской, Магаданской, Новгородской, Псковской, Тверской, Челябинской, Ярославской областей, Забайкальского края, Республик Алтай, Бурятия, Карелия и Марий Эл.