8 research outputs found

    First records of two remarkable Coleoptera species Cucujus cinnaberinus and Metoecus paradoxus (Coleoptera: Cucujidae, Rhipiphoridae) from the Republic of Karelia (Russia)

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    Viable populations of two remarkable Coleoptera species – Cucujus cinnaberinus (Cucujidae) and Metoecus paradoxus (Rhipiphoridae) are reported for the first time from the Republic of Karelia (Russia). Cucujus cinnaberinus is a threatened species in northern Europe while Metoecus paradoxus is a widespread Palaearctic species actively dispersing northwards. Both species were found in the nature protected areas by the local staff. This evidences the importance of such territories for preserving and monitoring the populations of rare and poorly known species

    ИССЛЕДОВАНИЕ ДИНАМИКИ ТЕРРИТОРИАЛЬНОГО РАСПРОСТРАНЕНИЯ И ЭКОЛОГИИ РЕДКИХ МЛЕКОПИТАЮЩИХ ТАЕЖНОЙ ЕВРАЗИИ (НА ПРИМЕРЕ ЛЕТЯГИ PTEROMYS VOLANS, RODENTIA, PTEROMYIDAE) in English INVESTIGATION OF THE DYNAMICS OF REGIONAL DISTRIBUTION AND ECOLOGY OF RARE MAMMALS TAIGA EURASIA (FOR EXAMPLE Letyago PTEROMYS VOLANS, RODENTIA, PTEROMYIDAE)

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    This study of the spatial distribution and ecology of the flying squirrel during the turn of the 20th century provides a description of new methods and techniques for detecting and accounting flying squirrels in the forest zone of Eurasia. The flying squirrel population area covers the territory of 61 regions of Russia, including Kamchatsky Krai and Chukotka Autonomous District. The number of flying squirrels in Karelia especially to the east – in the Arkhangelsk region and Western Siberia – significantly exceeds that of Finland, but considerable spatial variability in the number is obvious through all the regions: there are areas where this animal is quite abundant, or inhabits all the territory rather evenly, and there are areas where it is completely absent in vast territories even with seemingly favourable conditions. The flying squirrel is quite difficult to study and the reasons of its absence in obviously favourable areas are still to be explained. Some reasons are: the specificity of favourable landscape, forest coverage pattern, trophic relationships with predators and genetic aspect. A number of hypotheses are supposed to be tested in the nearest future. Key words: accounting, flying squirrel, forest zone, home range, spatial distribution.Peer reviewe

    Chronicles of nature calendar, a long-term and large-scale multitaxon database on phenology

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    We present an extensive, large-scale, long-term and multitaxon database on phenological and climatic variation, involving 506,186 observation dates acquired in 471 localities in Russian Federation, Ukraine, Uzbekistan, Belarus and Kyrgyzstan. The data cover the period 1890-2018, with 96% of the data being from 1960 onwards. The database is rich in plants, birds and climatic events, but also includes insects, amphibians, reptiles and fungi. The database includes multiple events per species, such as the onset days of leaf unfolding and leaf fall for plants, and the days for first spring and last autumn occurrences for birds. The data were acquired using standardized methods by permanent staff of national parks and nature reserves (87% of the data) and members of a phenological observation network (13% of the data). The database is valuable for exploring how species respond in their phenology to climate change. Large-scale analyses of spatial variation in phenological response can help to better predict the consequences of species and community responses to climate change.Peer reviewe

    Phenological shifts of abiotic events, producers and consumers across a continent

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    Ongoing climate change can shift organism phenology in ways that vary depending on species, habitats and climate factors studied. To probe for large-scale patterns in associated phenological change, we use 70,709 observations from six decades of systematic monitoring across the former Union of Soviet Socialist Republics. Among 110 phenological events related to plants, birds, insects, amphibians and fungi, we find a mosaic of change, defying simple predictions of earlier springs, later autumns and stronger changes at higher latitudes and elevations. Site mean temperature emerged as a strong predictor of local phenology, but the magnitude and direction of change varied with trophic level and the relative timing of an event. Beyond temperature-associated variation, we uncover high variation among both sites and years, with some sites being characterized by disproportionately long seasons and others by short ones. Our findings emphasize concerns regarding ecosystem integrity and highlight the difficulty of predicting climate change outcomes. The authors use systematic monitoring across the former USSR to investigate phenological changes across taxa. The long-term mean temperature of a site emerged as a strong predictor of phenological change, with further imprints of trophic level, event timing, site, year and biotic interactions.Peer reviewe

    Polymer Micelles with Hydrophobic Core and Ionic Amphiphilic Corona. 2. Starlike Distribution of Charged and Nonpolar Blocks in Corona

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    Mixed polymer micelles with hydrophobic polystyrene (PS) core and ionic amphiphilic poly­(4-vinylpyridine)/poly­(N-ethyl-4-vinylpyridinium bromide) corona (P4VP/PEVP) spontaneously self-assembled from mixtures of PS-<i>b</i>-PEVP and PS-<i>b</i>-P4VP macromolecules in dimethylformamide/methanol/water selective solvent. The fraction of PEVP units in corona was β = [PEVP]/([PEVP] + [P4VP]) = 0.05–1.0. Micelles were transferred into pure water via dialysis technique and pH was adjusted to 9, where P4VP blocks are insoluble. Structural characteristics of micelles as a function of corona composition β were investigated. Methods of dynamic and static light scattering, electrophoretic mobility measurements, sedimentation velocity, transmission electron microscopy, and UV spectrophotometry were applied. Spherical morphology with core (PS)–shell (P4VP)–corona (PEVP) organization was postulated. Micelles demonstrated a remarkable inflection in structural characteristics near β ∼ 0.5–0.7. Above this region, aggregation number (<i>m</i>), core and corona radii of mixed micelles coincided with those of individual PS-<i>b</i>-PEVP micelles. When β decreased below 0.5, dramatic growth of aggregation number was observed, accompanied by growth in micelle size and stretching PEVP chains. At β below 0.2, dispersions of mixed micelles were unstable and easily precipitated upon addition of NaCl. Scaling relationships between micelle characteristics and β were obtained via minimization the micelle free energy, taking into account electrostatic, osmotic, volume, and surface contributions. Theoretical estimations predicted dramatic influence of β on aggregation number, <i>m</i> ∼ β<sup>–3</sup>. This result is in general agreement with experimental data and confirms the correctness of the core–shell–corona model. The inflection in micelle characteristics entails drastic changes in micelle dispersion stability in the presence of oppositely charged polymeric (sodium polymethacrylate) or amphiphilic (sodium dodecyl sulfate) complexing agents

    Polymer Micelles with Hydrophobic Core and Ionic Amphiphilic Corona. 1. Statistical Distribution of Charged and Nonpolar Units in Corona

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    Polymer micelles with hydrophobic polystyrene (PS) core and ionic amphiphilic corona from charged <i>N</i>-ethyl-4-vinylpyridinium bromide (EVP) and uncharged 4-vinylpyridine (4VP) units spontaneously self-assembled from PS-<i>block</i>-poly­(4VP-<i>stat</i>-EVP) macromolecules in mixed dimethylformamide/methanol/water solvent. The fraction of statistically distributed EVP units in corona-forming block is β = [EVP]/([EVP]+[4VP]) = 0.3–1. Micelles were transferred into water via dialysis technique, and pH was adjusted to 9, where 4VP is insoluble. Structural characteristics of micelles were investigated both experimentally and theoretically as a function of corona composition β. Methods of dynamic and static light scattering, electrophoretic mobility measurements, sedimentation velocity, transmission electron microscopy, and UV spectrophotometry were applied. All micelles possessed spherical morphology. The aggregation number, structure, and electrophoretic mobility of micelles changed in a jumplike manner near β ∼ 0.6–0.75. Below and above this region, micelle characteristics were constant or insignificantly changed upon β. Theoretical dependencies for micelle aggregation number, corona dimensions, and fraction of small counterions outside corona versus β were derived via minimization the micelle free energy, taking into account surface, volume, electrostatic, and elastic contributions of chain units and translational entropy of mobile counterions. Theoretical estimations also point onto a sharp structural transition at a certain corona composition. The abrupt reorganization of micelle structure at β ∼ 0.6–0.75 entails dramatic changes in micelle dispersion stability in the presence of NaCl or in the presence of oppositely charged polymeric (sodium polymethacrylate) or amphiphilic (sodium dodecyl sulfate) complexing agents

    Dynamics of regional distribution and ecology investigation of rare mammals of taiga Eurasia (case study of flying squirrel Pteromys volans, Rodentia, Pteromyidae)

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    This study of the spatial distribution and ecology of the flying squirrel during the turn of the 20th century provides a description of new methods and techniques for detecting and accounting flying squirrels in the forest zone of Eurasia. The flying squirrel population area covers the territory of 61 regions of Russia, including Kamchatsky Krai and Chukotka Autonomous District. The number of flying squirrels in Karelia especially to the east – in the Arkhangelsk region and Western Siberia – significantly exceeds that of Finland, but considerable spatial variability in the number is obvious through all the regions: there are areas where this animal is quite abundant, or inhabits all the territory rather evenly, and there are areas where it is completely absent in vast territories even with seemingly favourable conditions. The flying squirrel is quite difficult to study and the reasons of its absence in obviously favourable areas are still to be explained. Some reasons are: the specificity of favourable landscape, forest coverage pattern, trophic relationships with predators and genetic aspect. A number of hypotheses are supposed to be tested in the nearest future

    Differences in spatial versus temporal reaction norms for spring and autumn phenological events

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    For species to stay temporally tuned to their environment, they use cues such as the accumulation of degree-days. The relationships between the timing of a phenological event in a population and its environmental cue can be described by a population-level reaction norm. Variation in reaction norms along environmental gradients may either intensify the environmental effects on timing (cogradient variation) or attenuate the effects (countergradient variation). To resolve spatial and seasonal variation in species' response, we use a unique dataset of 91 taxa and 178 phenological events observed across a network of 472 monitoring sites, spread across the nations of the former Soviet Union. We show that compared to local rates of advancement of phenological events with the advancement of temperature-related cues (i.e., variation within site over years), spatial variation in reaction norms tend to accentuate responses in spring (cogradient variation) and attenuate them in autumn (countergradient variation). As a result, among-population variation in the timing of events is greater in spring and less in autumn than if all populations followed the same reaction norm regardless of location. Despite such signs of local adaptation, overall phenotypic plasticity was not sufficient for phenological events to keep exact pace with their cues-the earlier the year, the more did the timing of the phenological event lag behind the timing of the cue. Overall, these patterns suggest that differences in the spatial versus temporal reaction norms will affect species' response to climate change in opposite ways in spring and autumn
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