Interpreting eddy covariance data from heterogeneous Siberian tundra : land-cover-specific methane fluxes and spatial representativeness

The non-uniform spatial integration, an inherent feature of the eddy covariance (EC) method, creates a challenge for flux data interpretation in a heterogeneous environment, where the contribution of different land cover types varies with flow conditions, potentially resulting in biased estimates in comparison to the areally averaged fluxes and land cover attributes. We modelled flux footprints and characterized the spatial scale of our EC measurements in Tiksi, a tundra site in northern Siberia. We used leaf area index (LAI) and land cover class (LCC) data, derived from very-high-spatial-resolution satellite imagery and field surveys, and quantified the sensor location bias. We found that methane (CH4) fluxes varied strongly with wind direction (-0.09 to 0.59 mu gCH(4)m(-2) s(-1) on average) during summer 2014, reflecting the distribution of different LCCs. Other environmental factors had only a minor effect on short-term flux variations but influenced the seasonal trend. Using footprint weights of grouped LCCs as explanatory variables for the measured CH4 flux, we developed a multiple regression model to estimate LCC group-specific fluxes. This model showed that wet fen and graminoid tundra patches in locations with topography-enhanced wetness acted as strong sources (1.0 mu gCH(4) m(-2) s(-1) during the peak emission period), while mineral soils were significant sinks (-0.13 mu gCH(4) m(-2) s(-1)). To assess the representativeness of measurements, we upscaled the LCC group-specific fluxes to different spatial scales. Despite the landscape heterogeneity and rather poor representativeness of EC data with respect to the areally averaged LAI and coverage of some LCCs, the mean flux was close to the CH4 balance upscaled to an area of 6.3 km(2), with a location bias of 14 %. We recommend that EC site descriptions in a heterogeneous environment should be complemented with footprint-weighted high-resolution data on vegetation and other site characteristics.Peer reviewe

Multilayered feed forward Artificial Neural Network model to predict the average summer-monsoon rainfall in India

In the present research, possibility of predicting average summer-monsoon rainfall over India has been analyzed through Artificial Neural Network models. In formulating the Artificial Neural Network based predictive model, three layered networks have been constructed with sigmoid non-linearity. The models under study are different in the number of hidden neurons. After a thorough training and test procedure, neural net with three nodes in the hidden layer is found to be the best predictive model.Comment: 19 pages, 1 table, 3 figure

An Improved Quantum Molecular Dynamics Model and its Applications to Fusion Reaction near Barrier

An improved Quantum Molecular Dynamics model is proposed. By using this model, the properties of ground state of nuclei from $^{6}$Li to $^{208}$Pb can be described very well with one set of parameters. The fusion reactions for $^{40}$Ca+$^{90}$Zr, $^{40}$Ca+$^{96}$Zr and $^{48}$Ca+$^{90}$Zr at energy near barrier are studied by this model. The experimental data of the fusion cross sections for $^{40}$Ca+$^{90,96}$Zr at the energy near barrier can be reproduced remarkably well without introducing any new parameters. The mechanism for the enhancement of fusion probability for fusion reactions with neutron-rich projectile or target is analyzed.Comment: 20 pages, 12 figures, 3 table

Dynamic study on fusion reactions for 40,48^{40,48}Ca+90,96^{90,96}Zr around Coulomb barrier

By using the updated improved Quantum Molecular Dynamics model in which a surface-symmetry potential term has been introduced for the first time, the excitation functions for fusion reactions of $^{40,48}$Ca+$^{90,96}$Zr at energies around the Coulomb barrier have been studied. The experimental data of the fusion cross sections for $^{40}$Ca+$^{90,96}$Zr have been reproduced remarkably well without introducing any new parameters. The fusion cross sections for the neutron-rich fusion reactions of $^{48}$Ca+$^{90,96}$Zr around the Coulomb barrier are predicted to be enhanced compared with a non-neutron-rich fusion reaction. In order to clarify the mechanism of the enhancement of the fusion cross sections for neutron-rich nuclear fusions, we pay a great attention to study the dynamic lowering of the Coulomb barrier during a neck formation. The isospin effect on the barrier lowering is investigated. It is interesting that the effect of the projectile and target nuclear structure on fusion dynamics can be revealed to a certain extent in our approach. The time evolution of the N/Z ratio at the neck region has been firstly illustrated. A large enhancement of the N/Z ratio at neck region for neutron-rich nuclear fusion reactions is found.Comment: 21 pages, 7 figures,3 table

Neutron star composition in strong magnetic fields

We study the problem of neutron star composition in the presence of a strong magnetic field. The effects of the anomalous magnetic moments of both nucleons and electrons are investigated in relativistic mean field calculations for a $\beta$-equilibrium system. Since neutrons are fully spin polarized in a large field, generally speaking, the proton fraction can never exceed the field free case. An extremely strong magnetic field may lead to a pure neutron matter instead of a proton-rich matter.Comment: 12 pages, 3 postscript files include

Regional Development: New Challenges for Engineering Education (SYNERGY-2021 Conference Results Review)

The article summarizes the results of the plenary session of the international network conference “Regional development: new challenges for engineering education – SYNERGY-2021”, held at Kazan National Research Technological University from October 19 to 20, 2021. The forum which brought together representatives of universities and industrial enterprises of Russia and abroad was devoted to the issue of training engineers for the petrochemical industry. Among the participants were representatives of international societies for engineering education, ten national research universities and seven supporting universities of PJSC Gazprom, state authorities and industrial enterprises of Tatarstan. It was possible to observe the work of the plenary session in real time via the Internet in all the supporting universities of Gazprom. The event was organized by the Ministry of Science and Higher Education of the Russian Federation, the International Society for Engineering Pedagogy (IGIP), the Association of Engineering Education of Russia (AIOR), as well as the Ministry of Industry and Trade of the Republic of Tatarstan and Kazan National Research Technological University. Gazprom PJSC became the general sponsor. In total, the conference gathered more than 450 participants (380 online and 85 in person) from 40 universities in Russia, the USA, Great Britain, Germany, Portugal, Finland, Poland, Kazakhstan, Belarus, Armenia, Latvia, and Estonia. Representatives of 7 industrial enterprises spoke, 77 reports were made

Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra - coupling field observations with remote sensing data

Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm(-3) in bare soil and lichen tundra and 89 g dm(-3) in other LCTs. Total moss biomass varied from 0 to 820 gm(-2), total vascular shoot mass from 7 to 112 gm(-2) and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 degrees C in bare soil and lichen tundra, and varied from 5 to 9 degrees C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14-34% of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6-15% of variation. NDVI captured variation in vascular LAI better than in moss biomass, but while this difference was significant with late season NDVI, it was minimal with early season NDVI. For this reason, soil attributes associated with moss mass were better captured by early season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. The LCT map we produced had low to moderate uncertainty in predictions for plant and soil properties except for moss biomass and bare soil and lichen tundra LCTs. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM % and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance, topography or a LCT map. Despite the general accuracy of landscape level predictions in our LCT approach, this indicates challenges in the spatial extrapolation of some of those vegetation and soil attributes that are relevant for the regional ecosystem and global climate models.Peer reviewe

Contrasting consequences of climate change for migratory geese:Predation, density dependence and carryover effects offset benefits of high-arctic warming

Climate change is most rapid in the Arctic, posing both benefits and challenges for migratory herbivores. However, population-dynamic responses to climate change are generally difficult to predict, due to concurrent changes in other trophic levels. Migratory species are also exposed to contrasting climate trends and density regimes over the annual cycle. Thus, determining how climate change impacts their population dynamics requires an understanding of how weather directly or indirectly (through trophic interactions and carryover effects) affects reproduction and survival across migratory stages, while accounting for density dependence. Here, we analyse the overall implications of climate change for a local non-hunted population of high-arctic Svalbard barnacle geese, Branta leucopsis, using 28 years of individual-based data. By identifying the main drivers of reproductive stages (egg production, hatching and fledging) and age-specific survival rates, we quantify their impact on population growth. Recent climate change in Svalbard enhanced egg production and hatching success through positive effects of advanced spring onset (snow melt) and warmer summers (i.e. earlier vegetation green-up) respectively. Contrastingly, there was a strong temporal decline in fledging probability due to increased local abundance of the Arctic fox, the main predator. While weather during the non-breeding season influenced geese through a positive effect of temperature (UK wintering grounds) on adult survival and a positive carryover effect of rainfall (spring stopover site in Norway) on egg production, these covariates showed no temporal trends. However, density-dependent effects occurred throughout the annual cycle, and the steadily increasing total flyway population size caused negative trends in overwinter survival and carryover effects on egg production. The combination of density-dependent processes and direct and indirect climate change effects across life history stages appeared to stabilize local population size. Our study emphasizes the need for holistic approaches when studying population-dynamic responses to global change in migratory species.</p

Superdeformed and Triaxial States in Ca 42

Shape parameters of a weakly deformed ground-state band and highly deformed slightly triaxial sideband in ^{42}Ca were determined from E2 matrix elements measured in the first low-energy Coulomb excitation experiment performed with AGATA. The picture of two coexisting structures is well reproduced by new state-of-the-art large-scale shell model and beyond-mean-field calculations. Experimental evidence for superdeformation of the band built on 0_{2}^{+} has been obtained and the role of triaxiality in the A∼40 mass region is discussed. Furthermore, the potential of Coulomb excitation as a tool to study superdeformation has been demonstrated for the first time