Response of CO2 and H2O fluxes in a mountainous tropical rainforest in equatorial Indonesia to El Niño events
The possible impact of El Niño–Southern Oscillation (ENSO) events on the main components of CO2 and H2O fluxes between the tropical rainforest and the atmosphere is investigated. The fluxes were continuously measured in an old-growth mountainous tropical rainforest in Central Sulawesi in Indonesia using the eddy covariance method for the period from January 2004 to June 2008. During this period, two episodes of El Niño and one episode of La Niña were observed. All these ENSO episodes had moderate intensity and were of the central Pacific type. The temporal variability analysis of the main meteorological parameters and components of CO2 and H2O exchange showed a high sensitivity of evapotranspiration (ET) and gross primary production (GPP) of the tropical rainforest to meteorological variations caused by both El Niño and La Niña episodes. Incoming solar radiation is the main governing factor that is responsible for ET and GPP variability. Ecosystem respiration (RE) dynamics depend mainly on the air temperature changes and are almost insensitive to ENSO. Changes in precipitation due to moderate ENSO events did not have any notable effect on ET and GPP, mainly because of sufficient soil moisture conditions even in periods of an anomalous reduction in precipitation in the region.
Many environmental stimuli present a quasi-rhythmic structure at different timescales that the brain needs to decompose and integrate. Cortical oscillations have been proposed as instruments of sensory de-multiplexing, i.e., the parallel processing of different frequency streams in sensory signals. Yet their causal role in such a process has never been demonstrated. Here, we used a neural microcircuit model to address whether coupled theta–gamma oscillations, as observed in human auditory cortex, could underpin the multiscale sensory analysis of speech. We show that, in continuous speech, theta oscillations can flexibly track the syllabic rhythm and temporally organize the phoneme-level response of gamma neurons into a code that enables syllable identification. The tracking of slow speech fluctuations by theta oscillations, and its coupling to gamma-spiking activity both appeared as critical features for accurate speech encoding. These results demonstrate that cortical oscillations can be a key instrument of speech de-multiplexing, parsing, and encoding.
Near-annual pollen records for the last 100 years were obtained from a 65-cm peat monolith from a raised peat bog in the Central Forest State Natural Biosphere Reserve (southern part of the Valdai Hills, European Russia) and compared with the available long-term meteorological observations. An age–depth model for the peat monolith was constructed by 210Pb and 137Cs dating. Cross-correlation and the Granger causality analysis indicated a broad range of statistically significant correlations between the pollen accumulation rate (PAR) of the main forest-forming trees and shrubs (Picea, Pinus, Betula, Tilia, Quercus, Ulmus, Alnus, and Corylus) and the air temperature and precipitation during the previous 3 years. Results showed that high air temperatures during the growing season (May–September) in the year prior to the flowering led to an increase in pollen productivity of the main tree species. The statistically significant correlation between the PAR of trees and shrubs and winter precipitation of the current and previous years could reflect the influence of winter precipitation on soil water availability and as a result on tree growth and functioning in the spring.
This article presents results of the study on economic and statistical justification for improvement of water and environmental management of an industrial enterprise. As a main tool the authors applied - was the method for modeling time series using stationary stochastic processes. The models of the integrated auto-regression and moving average, seasonally adjusted were used as the base. The models of fractionally integrated processes and models of autoregressive conditional heteroskedasticity were tested to reflect the long memory of indicators with characteristics of past period (levels and variations). Analysis of dynamic links was based on vector autoregression model. The authors demonstrated that for all the analyzed indicators of pollution, along with the apparent lack of mid-level trend, there is a considerable variability of values, which manifested in both annual and non-seasonal cyclical and structural changes. The longstanding interrelations between the individual indicators were revealed - for most of them the damping effect of a single excess discharge of any other indicator lasted for at least a year. The article proves sufficiency of the applied econometric tools which have determined the possibility for reliable forecasting the wastewater quality along with optimization of the measures for preventing excessive discharges. Identifying the character of the periodicity of the discharges with account to seasonality, as well as the synergistic effect of contamination indicated the possibility of increasing the efficiency of water treatment process by selecting the optimum costs. The identification of the inertia of the processes of pollution of individual indicators, testified to their possible aggregation from different sources to the necessity of strengthening of control over wastewater discharges for each anthropogenic source and the natural background contamination. Determining the dynamic interrelations between the individual polluters justified a reasonable opportunity to improve the pool cleanability with regard to the structure and duration of those relations.
One of the key advances in genome assembly that has led to a significant improvement in contig lengths has been improved algorithms for utilization of paired reads (mate-pairs). While in most assemblers, mate-pair information is used in a post-processing step, the recently proposed Paired de Bruijn Graph (PDBG) approach incorporates the mate-pair information directly in the assembly graph structure. However, the PDBG approach faces difficulties when the variation in the insert sizes is high. To address this problem, we first transform mate-pairs into edge-pair histograms that allow one to better estimate the distance between edges in the assembly graph that represent regions linked by multiple mate-pairs. Further, we combine the ideas of mate-pair transformation and PDBGs to construct new data structures for genome assembly: pathsets and pathset graphs.