Separating the climatic signal from tree-ring width and maximum latewood density records

We propose a technique for separating the climatic signal which is contained in two tree-ring parameters widely used in dendroclimatology. The method is based on the removal of the relationship between tree-ring width (TRW) and maximum latewood density (MXD) observed for narrow tree rings from high latitudes. The new technique is tested on data from three larch stands located along the northern timberline in Eurasia. Correlations were calculated between the temperatures of pentads (five consecutive days), TRW chronologies and MXD chronologies calculated according to the standard and proposed methods. The analysis confirms the great importance of summer temperature for tree radial growth and tree-ring formation. TRW is positively correlated with the temperature of four to eight pentads (depending on the region) at the beginning of the growth season, but MXD as obtained by the standard technique is correlated with temperature over a much longer period. For maximum density series from which the relationship between MXD and TRW has been removed (MXD′), there is a clear correlation with temperatures in the second part of the growing season. These results are consistent with the known dynamics of tree-ring growth in high latitudes and mechanisms of tree-ring formation.     

Co‐occurrence patterns of trees along macro‐climatic gradients and their potential influence on the present and future distribution of Fagus sylvatica L.

Aim During recent and future climate change, shifts in large‐scale species ranges are expected due to the hypothesized major role of climatic factors in regulating species distributions. The stress‐gradient hypothesis suggests that biotic interactions may act as major constraints on species distributions under more favourable growing conditions, while climatic constraints may dominate under unfavourable conditions. We tested this hypothesis for one focal tree species having three major competitors using broad‐scale environmental data. We evaluated the variation of species co‐occurrence patterns in climate space and estimated the influence of these patterns on the distribution of the focal species for current and projected future climates. Location Europe. Methods We used ICP Forest Level 1 data as well as climatic, topographic and edaphic variables. First, correlations between the relative abundance of European beech (Fagus sylvatica) and three major competitor species (Picea abies, Pinus sylvestris and Quercus robur) were analysed in environmental space, and then projected to geographic space. Second, a sensitivity analysis was performed using generalized additive models (GAM) to evaluate where and how much the predicted F. sylvatica distribution varied under current and future climates if potential competitor species were included or excluded. We evaluated if these areas coincide with current species co‐occurrence patterns. Results Correlation analyses supported the stress‐gradient hypothesis: towards favourable growing conditions of F. sylvatica, its abundance was strongly linked to the abundance of its competitors, while this link weakened towards unfavourable growing conditions, with stronger correlations in the south and at low elevations than in the north and at high elevations. The sensitivity analysis showed a potential spatial segregation of species with changing climate and a pronounced shift of zones where co‐occurrence patterns may play a major role. Main conclusions Our results demonstrate the importance of species co‐occurrence patterns for calibrating improved species distribution models for use in projections of climate effects. The correlation approach is able to localize European areas where inclusion of biotic predictors is effective. The climate‐induced spatial segregation of the major tree species could have ecological and economic consequences.     

Arsenic Bioaccumulation in Freshwater Fishes

The arsenic ambient water quality criterion (AWQC) for protection of human health via ingestion of aquatic organisms is currently 0.14 μ g/L. This AWQC is derived using a bioconcentration factor (BCF) of 44, which is a consumption-weighted average based on two data points for oysters and fish that was proposed by the U.S. Environmental Protection Agency in 1980 for broad application to freshwater and marine environments. This BCF is based on the assumption that bioaccumulation is a simple linear function of the exposure concentration. In the nearly quarter of a century since this BCF was promulgated, there have been additions to the arsenic bioaccumulation database and a broader scientific understanding of bioaccumulation mechanisms and how they can be applied to estimating tissue concentrations in aquatic organisms. From this database, we identified 12 studies of arsenic bioaccumulation in freshwater fishes in order to explore differences in laboratory-generated BCFs and field-generated bioaccumulation factors (BAFs) and to assess their relationship to arsenic concentrations in water. Our analysis indicates that arsenic concentrations in tissue and arsenic BAFs may be power functions of arsenic concentration in water. A power function indicates that the highest BCF values may occur at low background levels and may decrease as environmental concentrations increase above the ambient range.     

Subcellular distribution of enzymes in the yeast Saccharomycopsis lipolytica, grown on n-hexadecane,with special reference to the ω-hydroxylase

The subcellular localization of the ω-hydroxylase of Saccharomycopsis lipolytica was assessed by the analytical fractionation technique, originally described by de Duve C., Pressman, B.C., Gianetto, R., Wattiaux, R. and Appelmans, F., and hitherto little, if at all, applied to yeast. Protoplasts were separated in six fractions by differential centrifugation. Some of these fractions were further fractioned by density gradient centrifugation. The distribution of ω-hydroxylase and 15 other constituents chosen as possible markers of its subcellular membranes has been established. ω-Hydroxylase resulted in being bound to a membrane that containes also cytochrome P-450 and NADPH-cytochrome c reductase. This membrane clearly differs from five other subcellular entities. (1) Mitochondria were characterized by particulate malate dehydrogenase, particulate Antimycin A-insensitive NADH-cytochrome c reductase, oligomycin-sensitive and K⁺-stimulated ATPase pH 9. (2) Most if not all of the catalase and urate oxidase is peroxisomal. (3) Free ribosomes account for most RNA. (4) Nucleoside diphosphatase is for the first time reported in a yeast and appears to belong to an homogeneous population of small membranes. (5) The soluble compartment contains magnesium pyrophosphatase, alkaline phosphatase, 5′-nucleotidase and part of the NADH-cytochrome c reductase. Latent arylesterase and ATPase pH7 have an unspecific distribution. Alkaline phosphodiesterase I has not been detected.     

Evaluation of integrating topographic wetness index with backscattering coefficient of TerraSAR-X image for soil moisture estimation in a mountainous region

The estimation of soil moisture by using the backscattering coefficient of radar in a mountainous region is a challenging task due to the complex topography, which impacts the distribution of soil moisture and changes the backscattering coefficient. Complicated terrain can disturb empirical moisture estimation models, thereby, the resulting estimates of soil moisture are very unlikely reliable. This article proposed an innovative way of integration of the topographic wetness index (TWI) and the backscattering coefficient of soil obtained from the TerraSAR-X image, which improves the accuracy of measurement of the soil moisture. The standard estimation error and the coefficient of determination from the model were used to evaluate the performance of TWI. Our results show that the standard estimation error was decreased from: (1) 4.0% to 3.3% cm³ cm⁻³ at a depth of 5 cm and (2) 4.5% to 3.9% cm³ cm⁻³ at a depth of 10 cm. The most reliable estimation was observed at a depth of 5 cm, when it was compared with those of 0–5 cm, 10 cm and 15 cm. The TWI from the digital elevation model (DEM) is useful as a constraint condition for modeling work. This article concludes that the integration of the backscattering coefficient of soil with TWI can significantly reduce the uncertainty in the estimation of soil moisture in a mountainous region.