Lithogenesis of vend-cambrian deposits of southwest slope of Baikitskaya anteclase (based on the study of the section of the Irinchiminskaya parametrical well 155 in East Siberia)

The results of the study of sedimentation conditions and the subsequent diagenetic, catagenetic and imposed epigenetic rock transformations in the section have been examined. The display in the cut of epigenetic changes of rock and expansion of bitumoids point to the perspectivity of the territory and oil-and-gas-bearing capacit

Lithogenesis of vend-cambrian deposits of southwest slope of Baikitskaya anteclase (based on the study of the section of the Irinchiminskaya parametrical well 155 in East Siberia)

The results of the study of sedimentation conditions and the subsequent diagenetic, catagenetic and imposed epigenetic rock transformations in the section have been examined. The display in the cut of epigenetic changes of rock and expansion of bitumoids point to the perspectivity of the territory and oil-and-gas-bearing capacit

Topology and seasonal evolution of the network of extreme precipitation over the Indian subcontinent and Sri Lanka

This paper employs a complex network approach to determine the topology and evolution of the network of extreme precipitation that governs the organization of extreme rainfall before, during, and after the Indian Summer Monsoon (ISM) season. We construct networks of extreme rainfall events during the ISM (June-September), post-monsoon (October-December), and pre-monsoon (March-May) periods from satellite-derived (Tropical Rainfall Measurement Mission, TRMM) and rain-gauge interpolated (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE) data sets. The structure of the networks is determined by the level of synchronization of extreme rainfall events between different grid cells throughout the Indian subcontinent. Through the analysis of various complex-network metrics, we describe typical repetitive patterns in North Pakistan (NP), the Eastern Ghats (EG), and the Tibetan Plateau (TP). These patterns appear during the pre-monsoon season, evolve during the ISM, and disappear during the post-monsoon season. These are important meteorological features that need further attention and that may be useful in ISM timing and strength prediction

Topology and seasonal evolution of the network of extreme precipitation over the Indian subcontinent and Sri Lanka

Peer reviewedPublisher PD

On the influence of spatial sampling on climate networks

Peer reviewedPublisher PD

Characterizing the evolution of climate networks

Complex network theory has been successfully applied to understand the structural and functional topology of many dynamical systems from nature, society and technology. Many properties of these systems change over time, and, consequently, networks reconstructed from them will, too. However, although static and temporally changing networks have been studied extensively, methods to quantify their robustness as they evolve in time are lacking. In this paper we develop a theory to investigate how networks are changing within time based on the quantitative analysis of dissimilarities in the network structure. Our main result is the common component evolution function (CCEF) which characterizes network development over time. To test our approach we apply it to several model systems, ErdA's-Rényi networks, analytically derived flow-based networks, and transient simulations from the START model for which we control the change of single parameters over time. Then we construct annual climate networks from NCEP/NCAR reanalysis data for the Asian monsoon domain for the time period of 1970-2011 CE and use the CCEF to characterize the temporal evolution in this region. While this real-world CCEF displays a high degree of network persistence over large time lags, there are distinct time periods when common links break down. This phasing of these events coincides with years of strong El Niño/Southern Oscillation phenomena, confirming previous studies. The proposed method can be applied for any type of evolving network where the link but not the node set is changing, and may be particularly useful to characterize nonstationary evolving systems using complex networks

Inquiline insects of the honey bee Apis mellifera in Western Siberia (Hymenoptera, Apidae)

The multi-species associations of insects (symbiocenosis) in honey bee hives currently include more than 15 orders of Insecta. We present the results of studying the inquilines of bee hives in the south of Western Siberia. In the honeybee hives of this region 37 insect species from 8 orders (Dermaptera, Thysanoptera, Psocoptera, Hemiptera, Coleoptera, Hymenoptera, Lepidoptera, Diptera) were identified. Inquiline insects were observed in 77% of hives in 81.5% of the studied apiaries. Coleoptera prevailed among the orders, accounting for 94% of observations. The overall eudominant was Cryptophagus scanicus (Linnaeus, 1758) (87.8%); the subdominants were Dermestes lardarius Linnaeus, 1758 and Contacyphon variabilis (Thunberg, 1787). The smallest number of insect species can be attributed to specific groups. These are C. scanicus, a detritophage that primarily feeds on mold fungi hyphae, but can also consume bee supplies; and Galleria melonella (Linnaeus, 1758), a widespread pest of bee colonies, that feeds on bee bread, honey, wax and bee brood. The facultative group includes detritophages, pollen- and honey-feeding species, that find suitable conditions for feeding and developing in beehives (Vespidae, Formicidae, etc.). Representatives of accidental group were the most diverse in species composition and type of nutrition but they were always individually found in hives. In total, 42 species of insects are currently recorded in the beehives of Western Siberia

Characterizing the evolution of climate networks

Peer reviewedPublisher PD

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

We introduce the \texttt{pyunicorn} (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. \texttt{pyunicorn} is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics or network surrogates. Additionally, \texttt{pyunicorn} provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis (RQA), recurrence networks, visibility graphs and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.Comment: 28 pages, 17 figure