Hunting Selectivity and Its Influence on the Structure of Sable Populations in the Cis-Ural Region

The structure of commercial sable samples from the Cis-Ural region was studied taking into account hunting method (shooting or trapping). The proportion of adult animals was found to be significantly lower in samples taken during the first half of the hunting season, compared to the second half, indicating predominant harvesting of young animals. To estimate the degree of hunting selectivity (I), the ratios of demographic groups among shot and trapped animals were calculated. The results confirmed the fact of selective hunting for underyearlings both by shooting (I = 1.49–1.60 for the Cis-Ural region and I = 2.46–3.37 for the Western Sayan Mountains) and by trapping (I = 2.80–4.37), especially during the first half of winter. Samples taken during the second half of the season were characterized by prevalence of adult animals making up the reproductive core of the population (I = 1.43–2.07). It is considered that the process of reproduction in Cis-Ural sable populations in the 1960s to 1980s was stimulated by intensive commercial hunting. To maintain reproduction of sable populations at a safe level, it is necessary to reduce the period of hunting in the first quarter of the year. It is proposed to use the phenomenon of hunting selectivity for managing sable populations, regulating their exploitation, and improving the economic productivity of habitats. Commercial hunting in terms of its impact on the population can act as a factor of conscious or unconscious artificial selection.     

Variation in the Composition of Secondary Metabolites in <Emphasis Type="Italic">Flavocetraria</Emphasis> Lichens from Western Siberia

The composition and contents of secondary metabolites in Flavocetraria lichens from Eastern Siberia were analyzed using herbarium specimens. Based on the composition of identified metabolites, three F. cucullata chemotypes and two F. nivalis chemotypes were distinguished. Distinct geographic differentiation between the F. cucullata chemotypes was revealed, probably reflecting their adaptation to environmental conditions. The content of usnic acid in F. cucullata thalli was found to correlate with the latitude of growing region. This may be regarded as evidence for a protective role of this metabolite in lichens growing at high latitudes and exposed to excess solar irradiation during the polar day.     

Assessment of the State of Lung Lichen, <Emphasis Type="Italic">Lobaria pulmonaria</Emphasis> (L.) Hoffm., in Forest Communities with Different Times Since Disturbance in the Northeast of European Russia

Quantitative parameters of cenopopulations of Lobaria pulmonaria, an endangered cyanolichen, have been studied in spruce phytocenoses of Karelia recovering after disturbance through the successional stage of aspen stands for a period ranging from 80 to 450 years. The results show that, as the time since disturbance increases, the total number of L. pulmonaria thalli and the number of colonized substrate units increase as well, with no stabilization of these parameters being observed in the series of communities studied. The total area of thalli in the phytocenoses is restored within approximately 200 years after the last disturbance. In old-growth forests (>400 years), L. pulmonaria thalli colonize a broad spectrum of tree species in different life states, including lower branches of young spruce trees. Even if they serve as temporary substrates, this can markedly strengthen the potential of the species for further expansion within the community in case of shortage in the main phorophyte (aspen). Thus, the proportion of regressive populations decreases, while that of colonizing populations increases, which is indicative of successful reproduction of the species.     

Assimilation of conventional and satellite wind observations in a mesoscale atmospheric model for studying atmospheric dispersion

A mesoscale atmospheric model PSU/NCAR MM5 is used to provide operational weather forecasts for a nuclear emergency response decision support system on the southeast coast of India. In this study the performance of the MM5 model with assimilation of conventional surface and upper-air observations along with satellite derived 2-d surface wind data from QuickSCAT sources is examined. Two numerical experiments with MM5 are conducted: one with static initialization using NCEP FNL data and second with dynamic initialization by assimilation of observations using four dimensional data assimilation (FDDA) analysis nudging for a pre-forecast period of 12 h. Dispersion simulations are conducted for a hypothetical source at Kalpakkam location with the HYSPLIT Lagrangian particle model using simulated wind field from the above experiments. The present paper brings out the differences in the atmospheric model predictions and the differences in dispersion model results from control and assimilation runs. An improvement is noted in the atmospheric fields from the assimilation experiment which has led to significant alteration in the trajectory positions, plume orientation and its distribution pattern. Sensitivity tests using different PBL and surface parameterizations indicated the simple first order closure schemes (Blackadar, MRF) coupled with the simple soil model have given better results for various atmospheric fields. The study illustrates the impact of the assimilation of the scatterometer wind and automated weather stations (AWS) observations on the meteorological model predictions and the dispersion results.     

Linear and non-linear relationships mapping the Henry’s law parameters of organic pesticides

This work aims to predict the air to water partitioning for 96 organic pesticides by means of the Quantitative Structure–Property Relationships Theory. After performing structural feature selection with Genetics Algorithms and Replacement Method linear approaches, it is found that among the most important molecular features appears the Moriguchi octanol–water partition coefficient, and higher lipophilicities would lead to compounds having higher Henry’s law constants. We also compare the statistical performance achieved by four fully-connected Feed-Forward Multilayer Perceptrons Artificial Neural Networks. The statistical results found reveal that the best performing model uses the Levenberg–Marquardt with Bayesian regularization (BR) weighting function for achieving the most accurate predictions.     

Monitoring Regional Riparian Forest Cover Change Using Stratified Sampling and Multiresolution Imagery1

Claggett, Peter R., Judy A. Okay, and Stephen V. Stehman, 2010. Monitoring Regional Riparian Forest Cover Change Using Stratified Sampling and Multiresolution Imagery. Journal of the American Water Resources Association (JAWRA) 46(2):334-343. DOI: 10.1111/j.1752-1688.2010.00424.x Abstract: The Chesapeake Bay watershed encompasses 165,760 km² of land area with 464,098 km of rivers and streams. As part of the Chesapeake Bay restoration effort, state and federal partners have committed to restoring 26,000 miles (41,843 km) of riparian forest buffers. Monitoring trends in riparian forest buffers over large areas is necessary to evaluate the efficacy of these restoration efforts. A sampling approach for estimating change in riparian forest cover from 1993/1994 to 2005 was developed and implemented in Anne Arundel County, Maryland, to exemplify a method that could be applied throughout the Bay watershed. All stream reaches in the county were stratified using forest cover change derived from Landsat imagery. A stratified random sample of 219 reaches was selected and forest cover change within the riparian buffer of each sampled reach was interpreted from high-resolution aerial photography. The estimated footprint of gross change in riparian forest cover (i.e., the sum of gross gain and gross loss) for the county was 1.83% (SE = 0.22%). Stratified sampling taking advantage of a priori knowledge of locations of change proved to be a practical and efficient protocol for estimating riparian forest buffer change at the county scale and the protocol would readily extend to much broader scale monitoring.     

Aerosol speciation and mass prediction from toluene oxidation under high NOx conditions

A kinetically based gas-particle partitioning box model is used to highlight the importance of parameter representation in the prediction of secondary organic aerosol (SOA) formation following the photo-oxidation of toluene. The model is initialized using experimental data from York University's indoor smog chamber and provides a prediction of the total aerosol yield and speciation. A series of model sensitivity experiments were performed to study the aerosol speciation and mass prediction under high NO_x conditions (VOC/NO_x = 0.2). Sensitivity experiments indicate vapour pressure estimation to be a large area of weakness in predicting aerosol mass, creating an average total error range of 70 μg m^?3 (range of 5–145 μg m^?3), using two different estimation methods. Aerosol speciation proved relatively insensitive to changes in vapour pressure. One species, 3-methyl-6-nitro-catechol, dominated the aerosol phase regardless of the vapour pressure parameterization used and comprised 73–88% of the aerosol by mass. The dominance is associated with the large concentration of 3-methyl-6-nitro-catechol in the gas-phase. The high NO_x initial conditions of this study suggests that the predominance of 3-methyl-6-nitro-catechol likely results from the cresol-forming branch in the Master Chemical Mechanism taking a significant role in secondary organic aerosol formation under high NO_x conditions. Further research into the yields and speciation leading to this reaction product is recommended.     

Quantifying trace gas emissions from composite landscapes: A mass-budget approach with aircraft measurements

Quantifying trace gas emissions and the influence of surface exchange processes on the atmosphere is a necessary step towards the control of global greenhouse gas emissions and reliability of air quality models. This paper proposes a procedure based on the mass balance method and implemented on highly resolved aircraft data. It allows one to estimate surface exchanges on areas of several km² and heterogeneous features exploiting the characteristics of convective boundary layer during steady state conditions that permit the estimation of emission/absorption terms as functions of advective fluxes only. A nonparametric approach is adopted and the fluxes on the surface of a virtual box surrounding the area of interest are reconstructed on the basis of scalar densities and wind vectors using Shepard functions. Two different techniques are also proposed to face lack of data on the top surface of the box. The method has been applied to experimental data coming from measurement campaigns on two different sites. It provides realistic estimates of the CO₂ emission/absorption in the considered areas that are in good agreement with CO₂ fluxes evaluated by Airborne Eddy Covariance and confirm the suitability of the proposed approach for the assessment of turbulent exchange of trace gases by composite landscapes. Uncertainties on the estimated emissions due to both propagation of the experimental error and interpolation have been quantified by bootstrap analysis as 6%.