Altai-Sayan Mountain Country Research Articles

DEEP PROCESS-DATA MINING FOR BUILDING OF ANALYTICAL MODELS: 2. INFLUENCE OF WINTER-SPRING TEMPERATURES AND PRECIPITATION ON SPRING FLOOD EXTREMES FOR MOUNTAIN RIVERS

Using the standard methodology for deep process-data mining called system- analytical modeling, we have built a high-performance process-driven (analytical) model for description of winter-spring temperatures and precipitation influence on spring flood extremes for mountain rivers. In April, flood discharge peaks (with ice motion) cause emergency inun- dations and pose a constant threat to local population. The effect of the landscape structure of river basins, winter-spring temperatures and precipitation on spring flood discharge peaks and troughs (SFDP and SFDT) for April 1951–2020 was analyzed by the example of 34 medium and small rivers of the Altai-Sayan mountain country. We identified nontrivial SFDP/SFDT dependences on meteorological conditions, proposed their physical-hydrological substantia- tions and determined SFDP/SFDT sensitivities to meteorological factor variations as con- tributions to the observed SFDP/SFDT variances. The contributions of winter and spring precipitation, winter air temperatures and spring ones for SFDP/SFDT variances made up 34.7, 21.9, 7.8, 6.1% and 13.6, 18.8, 6.6, 1.5%, respectively.

DEEP PROCESS-DATA MINING FOR BUILDING OF ANALYTICAL MODELS: 1. MEDIUM-TERM FORECAST OF SPRING FLOOD EXTREMES FOR MOUNTAIN RIVERS

A standard methodology of deep process-data mining for building high-performance process-driven (analytical) models of complex natural systems was proposed. The method- ology (called as system-analytical modeling) is based on a system-hierarchical approach and deep mining of large datasets providing both extraction of the information hidden in such datasets and quantitative characterization of real processes occurring in natural systems. With its help, deep process-data mining of data (1951–2020) on spring flood discharge peaks and troughs (with ice motion) on 34 mountain rivers of the Altai-Sayan mountain country was performed. An analytical hydrological model of high performance (Nash-Sutcliffe criterion NSE = 0.78) was developed for the annual medium-term forecasting of discharge peaks and troughs in April using the data on meteorological conditions of the recent autumn and current winter periods. Flood peaks depend on autumn-winter precipitation (which determines 29% of the peak variance), landscape structure of river basins (14%), and winter air temperatures (0.8%). Spring floods on mountain rivers often threaten the life of local population that makes the developed model topical.

High-Performance Forecasting of Spring Flood in Mountain River Basins with Complex Landscape Structure

We propose the methodology of building the process-driven models for medium-term forecasting of spring floods (including catastrophic ones) in the mountainous areas, the hydrological analysis of which is usually much more complicated in contrast to plains. Our methodology is based on system analytical modeling of complex hydrological processes in 34 river basins of the Altai-Sayan mountain country. Consideration of 13 types of landscapes as autonomous hydrological subsystems influencing rivers’ runoff (1951–2020) allowed us to develop the universal predictive model for the most dangerous April monthly runoff (with ice motion), which is applicable to any river basin. The input factors of the model are the average monthly air temperature and monthly precipitation for the current autumn–winter period, as well as the data on the basin landscape structure and relief calculated by GIS tools. The established universal dependences of hydrological runoffs on meteorological factors are quite complex and formed under influence of solar radiation and physical–hydrological patterns of melting snow cover, moistening, freezing, and thawing of soils. The model shows the greatest sensitivity of April floods to the landscape composition of river basins (49% of common flood variance), then to autumn precipitation (9%), winter precipitation (3%), and finally, to winter air temperature (0.7%). When it is applied to individual river basins, the forecast quality is very good, with the Nesh–Sutcliffe coefficient NSE = 0.77. In terms of the accuracy of process-driven predictive hydrological models for the mountainous areas, the designed model demonstrates high-class performance.

THE INFLUENCE OF WINTER-SPRING TEMPERATURES AND PRECIPITATION ON THE SPRING FLOOD WAVE

The complex influence of meteorological conditions on the first (April) wave of spring-summer flooding of the mountain rivers was studied by the example of 34 mid-size and small rivers of the Altai-Sayan mountain country covering more than 2,000,000 km2 of the Central Asia territory. System-analytical modeling was employed to describe the complex dependence of April river runoff on air temperatures and precipitation for December-April. The impact of factors was quantitatively assessed through solving the inverse mathematical problem and using 1,760 values of river runoff for 1951-2019, meteorological data and carto- graphic information on the relief and landscape structure of river basins calculated in ArcGIS 10.2. Precipitation accumulated in December-March as snow cover had a positive effect on runoff only in case of proximity of winter temperatures to their long-term mean values. At low April temperatures, river runoff increased along with the growth of current precipitation, while at temperature rise it decreased. The established dependencies of the first flood wave on meteorological factors are of great importance for effective preventing adverse effects of spring floods in the mountain regions.

Moss occurrences in Salair-Kuznetsk Region (Altai-Sayan mountain country).

BackgroundIn the flora of large regions, mosses comprise about a quarter of the total diversity of higher plants. However, now mosses are the least studied group of higher plants. Data on moss species distribution are fragmentary, especially in Russia with its vast expanse and low density of botanists.The author for many years has been studying the bryoflora of various areas of the Salair-Kuznetsk Region. In addition to the herbarium collection, the author's bryological relevés were organised as a Database. It stores all the assembled information for the years about the locations of the species, including when the specimens were not placed in the herbarium.The article describes three datasets that were arranged from the author's databases for three geomorphological units in the northwest of Altai-Sayan mountain country (South Siberia). Together, these three units are combined into the Salair-Kuznetsk Region. The datasets are:1. Moss occurrences in the Kuznetsk upland.The dataset consists of 3940 occurrence records and includes both preserved specimens (1135) and ‘human observations’ of the author (2805). The material was collected mainly from 1992-2011; some samples collected by A. N. Vasiliev in 1970-1971 (165) were also taken into account. A total of 312 moss taxa belonging to 135 genera and 41 families are reported for the region.2. Moss occurrences in Salair Ridge.The dataset consists of 2442 occurrence records and includes both preserved specimens (553) and ‘human observations’ of the author (1889). The material was collected mainly from 1992-1996; a total of 231 moss taxa belonging to 119 genera and 35 families are reported for the region.3. Moss occurrences in Kuznetsk Depression.The dataset consists of 1690 occurrence records and includes both preserved specimens (281) and ‘human observations’ of the author (1409). The material was collected mainly from 2007-2014; a total of 155 moss taxa belonging to 85 genera and 30 families are reported for the region.All the records are geo-linked. The uncertainty of coordinates in metres varies from 500.0-10000.0 m for the earliest records that are geo-linked by topo-map, to 10.0-100.0 m for records after 2003 that are geo-linked by GPS.New informationThe article summarises the results of the author's long-term bryological investigations in the Salair-Kuznetsk Region (northwest of Altai-Sayan mountain country, South Siberia).In total, 8072 occurrence records for 366 moss species from 148 genera and 41 families are published for the territory. The datasets contribute to filling gaps in the moss species distribution and ecology.

Age of the Chibit Glaciation in Gornyi Altai

New results of Optically-Stimulated Luminescence (OSL) dating that make it possible to clarify the age of the Chibitskii glaciation in the Altai Mountains are reported. Three dates were obtained from the upper part of the lacustrine–glacial Baratal sands, logically distributed within the chronological interval from 21.0 to 14.4 ka. Fluvioglacial sands from the drift moraines of the last Kuekhtanar glacier, three OSL-ages of which are in the interval of 30–24 ka, correlate with the Baratal limnoglacial. The origin of Sukor Lake is associated with the Sukor landslide, which dammed the Chuya River valley. According to eight OSL dates, which have been obtained for the Sukor sands, the dammed Sukor Lake existed in the interval from 16 to 11 ka. New OSL dates provide a more reliable reconstruction of the Chibit glaciation age and the position of the corresponding sediments in the Quaternary stratigraphic chart of the Altai–Sayan Mountain Country, as corresponding to the Last Glacial Maximum (LGM), i.e., the fourth stage of the Upper Neopleistocene of the Russian stratigraphic chart.

Good-quality Long-term Forecast of Spring-summer Flood Runoff for Mountain Rivers

The universal simulation model was developed with the use of system-analytical modeling to ensure a long-term forecast of mountain river runoff during spring-summer floods. Prediction quality of this SAM-model is characterized by Nash-Sutcliffe efficiency of 0.68–0.88 and is very high for long-term flood forecasts, including ones for inundations and mountain reservoirs filling in spring. The model was tested on the example of 34 medium and small rivers (1630 values of runoff observations for 1951–2016) located in the Altai-Sayan mountain country (2,000,000 km2). Its input factors include monthly precipitation, monthly mean air temperature, GIS data on landscape structure and orography of river basins. Meteorological factors are calculated as percentage of their “in situ” long-term mean values averaged for the whole study area. This helps to explain and quantify the influence of autumn-winter-spring soaking, freezing and thawing of mountain landscape soils on spring-summer flood. We apply a simple novel method to evaluate model sensitivity to variations in environmental factors expressed in terms of their contribution to variance of the observed flood runoff. It turns out that sensitivity of the latter decreases in the following sequence of factors: autumn precipitation, landscape structure of river basins, winter precipitation, winter air temperature, landscape altitude. The developed SAM-model provides a three-month lead-time estimate of runoff in a high water period with the threefold less variance as compared to forecasts based on the observed long-term mean values.

Биоклиматические ресурсы рекреационного природопользования Алтае-Саянской горной страны в летний период

Биоклиматические ресурсы рекреационного природопользования Алтае-Саянской горной страны в летний период

Annual range of temperature and precipitation forecast for Altai-Sayan mountain country

Analysis and long-term forecasting of climatic characteristics of the mountains is laborious and extremely difficult due to complex vertical and horizontal differentiation of climatic fields and insufficient number of weather stations in the region. We have developed a method for statistical forecast of average monthly temperature in the surface air layer and monthly precipitation for the mountain areas with an annual lead time.
 The method is based on the description of monthly dynamics of the mentioned factors expressed in percent of their average annual monthly values measured in situ. Such a dynamics remains the same throughout the study territory, regardless of its height and exposure. To convert the relative values of temperature and precipitation into their conventional units of measurements (C and mm) one needs just mean annual January and July values of air temperature and precipitation for the territory under study. By the example of the Altai-Sayan mountain country, it is shown that the use of observation data for 67 years obtained from several reference weather stations ensure reliable prediction. The forecast is equally true for any part of the mountainous country due to spatial generalization of relative changes in these factors. The universal criterion A for assessing the quality of various predictive methods (including those, which do not use the model quality indices RSR and NashSutcliffe) is proposed.
 The criterion is the error of predictive method Sdiff normalized by standard deviation Sobs of observations from their average and equals to Sdiff/ Sobs. It is associated with NSE and RSR indices through dependencies RSR = A and NSE = 1RSR2 = 12A2. The proposed criterion was used in assessing the quality of temperature and precipitation forecasts; it was close to the theoretically best one for statistical prognoses.

Spatial year-ahead forecast of air temperature and precipitation in large mountain areas

The method for spatial reconstruction of monthly mean air temperature and monthly precipitation is proposed for large mountain areas. Meteorological factor dynamics is described in percent of long-term monthly average values measured “in situ”. It is almost independent of height, exposure and climate of characterized sites and remains the same throughout the mountainous territory. By the example of the Altai-Sayan mountain country covering more than 2,500,000 km2, we averaged (spatially generalized) the data of 11 weather stations and obtained the country's long-term dynamics of monthly mean air temperature and monthly precipitation for 1951–2016. Using a simple moving average of 6–7 recent years of stations observations, we provide a reliable year-ahead prediction of a factor value for any spot of the country without additional data. Modification of RSR and Nash–Sutcliffe efficiency indices is proposed to correct their shortcomings in assessing the quality of various predictive methods and models. The developed method of four-season weather forecast has the quality close to the theoretically best for statistical forecasts.

Пространственно-фенотипическая структура популяций белки обыкновенной (Sciurus vulgaris) на Алтае-Саянском участке ареала

Пространственно-фенотипическая структура популяций белки обыкновенной (Sciurus vulgaris) на Алтае-Саянском участке ареала

СОДЕРЖАНИЕ ХИМИЧЕСКИХ ЭЛЕМЕНТОВ В ПОЧВАХ И ПОВЕРХНОСТНЫХ ВОДАХ ПЛОСКОГОРЬЯ УКОК (ЮГО-ВОСТОЧНЫЙ АЛТАЙ)

Актуальность исследования обусловлена слабой изученностью химического состава почв и поверхностных вод плоскогорья Укок, являющегося объектом всемирного наследия ЮНЕСКО. Цель: изучить уровни содержания химических элементов в почвах и поверхностных водах центральной, южной и юго-восточной части плоскогорья Укок и дать эколого-биогеохимическую оценку этой малоизученной территории. Объекты: основные типы почв (криоаридные и горные лугово-степные, горные луговые, горные тундровые) и поверхностные воды (реки Жумалы, Калгуты, Аргамжи, Ак-Алаха, Тархата и озеро Укок) плоскогорья Укок (Республика Алтай, Российская Федерация). Методы. Содержание металлов в почвах определено методом эмиссионного спектрального анализа в Институте геологии и минералогии СО РАН, общее содержание микроэлементов в природных водах – в химико-аналитическом центре ИВЭП СО РАН спектрометрическим методом с использованием электротермической атомизации. Результаты. Представлен химический состав различных типов почв и поверхностных вод высокогорного плоскогорья Укок. Уровни содержания химических элементов в почвах плоскогорья не превышают их кларков в почвенном покрове и соответствуют их концентрациям в горно-тундровых почвах Алтая. Исключением являются почвы и почвообразующие породы над Калгутинским W-Mo-V-Cu месторождением, где отмечается аномально высокое содержание вольфрама – до 30–60 мг/кг. С ореолами рассеяния и воздействием отвалов штольни и хвостохранилища обогатительной фабрики этого месторождения мы связываем повышенное содержание Cu в водах реки Калгуты – 16 мкг/дм3 и в почвах бассейна. Почвы плоскогорья отличаются невысоким валовым содержанием P и Са, но обогащены калием – его содержание превышает 2 % в большинстве образцов. Концентрация фосфора в почвах плоскогорья Укок возрастает с запада на восток, от выровненной (центральной) части к горным окаймлениям, что обусловлено фосфоритоносностью коренных пород Алтае-Саянской горной страны. Низкие значения элювиально-аккумулятивных коэффициентов большинства металлов в изученных почвах плоскогорья могут служить показателем отсутствия на данный момент здесь выраженного антропогенного загрязнения. Содержание большинства элементов в почвах увеличивается c глубиной. В горно-тундровых торфянистых почвах под ерником обнаружена биогенная аккумуляция Mn. Для степных почв отмечено некоторое накопление в поверхностных горизонтах Zn, Cr, V и Ni. Наиболее равномерным распределением отличается Pb и Zn. Исходная неоднородность моренных и озерно-ледниковых отложений определяет разнообразие внутрипрофильного распределения металлов в почвах, на них сформированных. Не выявлено четкой зависимости содержания большинства макро- и микроэлементов в поверхностных водах от уровня их концентраций в почвах. Тем не менее отмечено повышение интенсивность водной миграции железа в заболоченных ландшафтах Бертекской части бассейна реки Ак-Алаха, в водах которой обнаружено его наиболее высокое содержание.

Taxonomic structure of local floras in Sidinskiy and Pribaitakskiy steppes (Krasnoyarsk region)

Sidinskiy and Pribaitakskiy steppes are the part of the Minusinsk province of the Altai-Sayan mountain country. On the territory of steppes 12 local floras (LF) were marked and examined using the same method. Studies were carried out according to the recommendations of A.I. Tolmachev (1931): identification of different types of ecotypes of LF, the full species composition of ecotypes (flora inventory), tracking the completeness of detection in LF. In the Sidinskiy steppe the number of families in the LF varies from 25 (Syida) to 43 (v. Alha), in the Pribaitakskiy steppe there is a big difference in the number of families in the LF from 31 (Krasnoyarsk reservoir, Tuba) to 65 (Mayak, Idra). The leading families in the local steppe flora are Asteraceae, Poaceae, Fabaceae. The Fabaceae family ranks third in the top of ten families in 50 % of LF, determining the type of flora as the Mediterranean-Central Asian (Fabaceae-type). Different types of LF allow to determine the type of all steppe flora as mixed, combining features of boreal (Asteraceae-Poaceae- type) and steppes flora (Fabaceae-type) with close ties with Central European floras (Rosaceae-type). 4 distinct levels of species richness are determined: 1 − 496-544; 2 − 408-413; 3 − 319-374; 4 − 279-298 species.

Rock outcrops in the southeastern part of the West Siberian plain as the northern limit of distribution and refuge of rare moss species

Foothill plains along the northwest periphery of Altai–Sayan Mountain Country are the northern limit of stony substrates in the West Siberian longitudinal sector. Rock outcrops in this area are rare; their areas usually do not exceed few dozens of square meters. Despite small areas, the rocky outcrops keep nearly half of the foothill moss flora. 119 moss species were recorded in the rocky habitat; 26 of them are rare both in Western Siberia and in its mountain ringing. An annotated list of species is given. Features of species distribution in the longitudinal sector of West Siberia are discussed.

THE FAUNA OF CADDISFLIES (TRICHOPTERA: INSECTA) OF THE ULBA RIVER BASIN (SOUTH-WESTERN ALTAI)

The rivers of South-West Altai are poorly-studied by entomologists. To analyze the fauna composition and spatial distribution of caddisflies in watercourses of the Ulba river basin (South-Western Altai), the hydrobiological studies in 11 streams of the basin were performed in 2002-2013. The river basin is distinguished by high species richness of caddisflies. Here, 64 species of caddisflies from 38 genera and 19 families that is 48% of the species and 67% of the genera found in Kazakhstan are present. In the Ulba caddisflies fauna, the Transpalaearctic species (41%) dominate, a large quantity (33%) falls on Western Palaearctic ones. East Palaearctic species form 20% of the fauna, while the Altai and Siberia species – 6%. It is shown that despite the prevalence of widely distributed Transpalaearctic elements, the caddisflies fauna of South-Western Altai is hardly similar to that of the Altai-Sayan Mountain Country. Geographically approximate regions of Altai show the best similarity. The analysis of similarity of caddisflies species lists for some streams of South-Western Altai is evidence of a decisive role of abiotic factors of river biocenoses in the Trichoptera fauna formation. The suggestion has been made that ecological factors are critical in spatial distribution of caddisflies in the rivers of South-Western Altai. It is noted that composition and community structure of caddisflies depend on the level of anthropogenic transformation of rivers. The species richness of caddisflies and their share in total biomass of zoobenthos from river sites located below discharge points of polluted waters are reduced. The revealed features of caddisflies communities transformation in the impact zone call for modification of biotic indices used for assessing ecological state of rivers in the region.

Spatial-typological heterogeneity and environmental organization of the summer population of birds in the Middle Region of Northern Eurasia

The area under study covered the West Siberian Plain from the Urals to the Yenisei River and the same band to the southern borders of the former Soviet Union in 1991, including a part of the Altai-Sayan mountain country, Kazakhstan, Uzbekistan, Turkmenistan, and the whole of Kyrgyzstan and Tajikistan. The results of ornithogeographic surveys carried out on routes with a length of 63000 km in 3140 habitats from May 16 to July 31 in the period from 1936 to 2013 were analyzed for this territory. More than 110 specialists took part in the study. The collected data were averaged according to the contours of natural-geographical maps. The subsequent cluster analysis revealed the presence of three systems (series) of bird communities in undeveloped and developed lands, as well as in water and riparian areas. Eight types of communities were distinguished within the first system: 1—tundra type; 2—forest-tundra type; 3—forest type; 4 and 5—West Siberian meadow-steppe and semidesert-steppe types; 6 and 7—Middle Asian northern desert-steppe and southern desert types; 8—high-mountain type. The borders of their distribution do not coincide with the zonal borders. Seven and six types of communities were distinguished in the second and third systems, respectively. A part of them was divided into 29 subtypes in total. The revealed heterogeneity of bird communities is largely determined by 12 environmental factors. The greatest correlation was detected for forestation, buildup, and watering. The multiple correlation of the bird population variability with all the identified environmental factors amounted to about 54 ± 1% of variance in the similarity matrix, which approximately corresponds to the correlation coefficient of 0.74.

Mosses of Salair-Kuznetsk region (Altai-Sayan mountain country) and adjacent plains of West Siberia

Mosses of Salair-Kuznetsk region (Altai-Sayan mountain country) and adjacent plains of West Siberia

Database of Siberian Vegetation (DSV)

A first variant of Database of Siberian Vegetation (DSV; GIVD ID AS-RU-002) was created in 1994 in the Laboratory of Geobotany of the Central Siberian Botanical Garden of the Siberian Branch of RAS (CSBG SB RAS). Now it is located at the Geosystem research laboratory of CSBG SB RAS and in Tomsk State University. DSV contains geobotanical releves from Western and Eastern Siberia (incl. Republic Sakha – Yakutia), Altai-Sayan Mountain Country and Transbaicalia. Releve sets from the Inner Mongolia province of China and the north of Kazakhstan Republic are also included but are not numerous. The main part of the database represents different types of steppe communities: meadow steppes, typical and desertified steppes, cryophyte steppes. Numerous sets comprise forests, meadows and wetlands as well as diverse intrazonal vegetation developed on rocky, sandy and salty habitats. The main purposes of database are developing a syntaxonomy of North Asia, analysing biogeography features of the Siberian flora and vegetation, development of plant indicator values and the ecological analysis of vegetation, vegetation mapping based on remote sensing data and creation of a Geographic Information System. DSV is supported by IBIS software (Integrated Botanical Information System), which provides data storage, data analysis and data exchange

Картографирование динамики растительного покрова Саяно-Шушенского заповедника

The character of forest dynamics in the last century may be traced on the key area of the Altai-Sayan mountain country — the Sayan-Shushensky Biosphere Reserve of total area 389 000 ha. It is situated at the border of humid mountain region of South Siberia and the arid areas of Tuva. The basement for creation of prognosis map of potential state of the Reserve vegetation cover for 2050 year includes: 1) the data on inventory, ages structure, and conditions of forests; 2) the results of the earlier studies of dynamics of mountain open woodlands; 3) materials of dendroclimatic investigations at the upper and lower forest boundaries in the Sayan Mts.; 4) prognosis of climatologists. While classifying the Reserve vegetation, 1500 biogeocoenoses have been united into 362 types of biogeocoenoses which have been included into 112 groups of associations identified in altitudinal vegetation belts: goltsy, meadows and shrub thickets; high elevation open woodlands; mountain taiga; subtaiga—forest- steppe complexes. Local expansion of forest boundaries, at the expense of forming the 40— 80 years old forest stands in goltsy and open woodlands, testifies to climate warming, and a rise of the subtaiga—forest-steppe pine and larch forests of the 40—80 years old is the evidence of climate humification in this region during the last century. According to the prognoses of climatologists this tendency will continue in the future 50 years. On the territory of the Sayan-Shushensky Reserve, within the strip of 200 m width at the age of steppefied forests as well as within the steppes with shrubs, mesophilous species will be developed in the shrub, herb-dwarf shrub and moss cover. Under protection of shrubs, young open stands of larch and pine will spring up (on the area of 200 ha) and in subtaiga forests Abies sibirica and Pinus sibirica will appear among the regrowth. Under canopy of the mountain taiga and the subtaiga larch forests, the second layer of dark needle-leaved species will be formed. In the places of present pyrogenic derivatives — birch and aspen forests — the fir forest with admixture of Pinus sibirica and Picea obovata will be restored. On the area of 49 322 ha, occupied by mountain woodlands (87% of the total area), the closed mountain taiga forest of Pinus sibirica will spread. The area of goltsy and shrub thickets will decrease by 44.4% (19 214 ha), being replaced by the high elevation open woodlands of Pinus sibirica and Larix sibirica. In accordance with changes in vegetation cover the boundary between the Altai-Sayan and the Central-Asian forest areas within the Reserve's territory will deviate from the modern one approximately by 25 km.