Use of genetic,climatic, and microbiological data to inform reintroduction of a regionally extinct butterfly

Species reintroductions are increasingly used as means of mitigating biodiversity loss. Besides habitat quality at the site targeted for reintroduction, the choice of source population can be critical for success. The butterfly Melanargia russiae (Esper´s marbled white) was extirpated from Hungary over 100 years ago, and a reintroduction program has recently been approved. We used museum specimens of this butterfly, mitochondrial DNA data (mtDNA), endosymbiont screening, and climatic‐similarity analyses to determine which extant populations should be used for its reintroduction. The species displayed 2 main mtDNA lineages across its range: 1 restricted to Iberia and southern France (Iberian lineage) and another found throughout the rest of its range (Eurasian lineage). These 2 lineages possessed highly divergent wsp alleles of the bacterial endosymbiont Wolbachia. The century‐old Hungarian specimens represented an endemic haplotype belonging to the Eurasian lineage, differing by one mutation from the Balkan and eastern European populations. The Hungarian populations of M. russiae occurred in areas with a colder and drier climate relative to most sites with extant known populations. Our results suggest the populations used for reintroduction to Hungary should belong to the Eurasian lineage, preferably from eastern Ukraine (genetically close and living in areas with the highest climatic similarity). Materials stored in museum collections can provide unique opportunities to document historical genetic diversity and help direct conservation.     

Effects of water velocity on bulk water quality and biofilm population structure in drinking water distribution systems北大核心CSCD

To study the effect of flow velocity on drinking water distribution systems, bulk water quality was monitored over 28 days, biomass was measured, and 16S rDNA was sequenced on the 28th day using a water distribution simulation system. The relationship between bulk water quality and biofilm was statistically analyzed. Flow velocity of 0.5 m/s yielded the most total organic carbon (TOC) (5.26 ± 0.17 mg/L) in the bulk water, the most bulk water bacteria (lg (n+1/mL-1) = 4.79 ± 0.02), the worst bulk water quality, and the most biofilm bacteria (lg (n+1/cm-2) = 5.48 ± 0.06). A Pearson correlation analysis showed the total number of biofilm bacteria was positively correlated with conductivity (R = 0.73, P < 0.01), turbidity (R = 0.87, P < 0.001), TOC (R = 0.94, P < 0.001), and total bacteria (R = 0.92, P < 0.001), and was negatively correlated with residual chlorine (R = -0.68, P < 0.05). Biofilm diversity was high under the low (0.1 m/s) and high (2.5 m/s) flow rates, but the bacterial diversity of biofilm was the lowest at the 0.5 m/s flow rate, in which Proteobacteria dominated the biofilm community structure. These results suggest that flow velocity affects bulk water quality and biofilm population structure, and water quality and biofilm population structure are interrelated, which provides the theoretical basis for research on biofilms in drinking water distribution systems. © 2018 Science Press. All rights reserved.     

Spatial variability in soil water and salinity in Tamarix community in a semiarid saline region of the upper Yellow River北大核心CSCD

Tamarix is widely distributed in semiarid saline regions of the upper Yellow River. The community of Tamarix affects the spatial distribution of soil water and salinity. It is important to explore the dynamic response relationship of Tamarix community and spatial distribution of soil water and salinity in order to evaluate the effects of vegetation community construction and ecological restoration in this region. The natural Tamarix community in the secondary saline-alkali land of the Ningxia Yellow River Irrigation Area was investigated in July 2016. Classical statistics and geostatistics were used to analyze the spatial distribution characteristics of soil water and salinity. The results showed that the soil water content was relatively low (1.98%-7.55%), whereas the soil salinity was high (average conductivity 10.28-25.38 mS/cm) in the study area. The variability coefficient range of soil water and salinity was 36.1%-83.7%, both with moderate variations. Furthermore, the variation degree of soil salinity decreased with the increase in soil depth. The soil water and salinity had obvious spatial structure characteristics, which was mainly affected by structural factors or structural factors associated with stochastic factors. The coefficients of nugget were 0.04%-49.88%, indicating the strong spatial correlation. The spatial distribution of soil water and salinity in Tamarix community showed a patchy pattern; the soil water and salinity distribution in the areas with high Tamarix growing density were considerably high. The correlation analysis showed that there was a positive correlation between soil water and salinity in the study area. In conclusion, soil water and salinity restrict the distribution and growth of Tamarix. Furthermore, the distribution and growth of Tamarix enhanced the spatial variability of soil water and salinity. Keywords. © 2018 Science Press. All rights reserved.     

Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches

Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325–1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R² (LL R²) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design.