Early-spring soil warming partially offsets the enhancement of alpine grassland aboveground productivity induced by warmer growing seasons on the Qinghai-Tibetan Plateau

Aims

The response of vegetation productivity to global warming is becoming a worldwide concern. While most reports on responses to warming trends are based on measured increases in air temperature, few studies have evaluated long-term variation in soil temperature and its impacts on vegetation productivity. Such impacts are especially important for high-latitude or high-altitude regions, where low temperature is recognized as the most critical limitation for plant growth.

Methods

We used Partial Least Squares regression to correlate long-term aboveground net primary productivity (ANPP) data of an alpine grassland on the Qinghai-Tibetan Plateau with daily air and soil temperatures during 1997–2011. We also analyzed temporal trends for air temperature and soil temperature at different depths.

Results

Soil temperatures have steadily increased at a rate of 0.4–0.9 °C per decade, whereas air temperatures showed no significant trend between 1997 and 2011. While temperature increases during the growing season (May–August) promoted aboveground productivity, warming before the growing season (March–April) had a negative effect on productivity. The negative effect was amplified in the soil layers, especially at 15 cm depth, where variation in aboveground productivity was dominated by early-spring soil warming, rather than by increasing temperature during the growing season.

Conclusions

Future warming, especially in winter and spring, may further reduce soil water availability in early spring, which may slow down or even reverse the increases in grassland aboveground productivity that have widely been reported on the Qinghai-Tibetan Plateau.

     

Interaction of the yeast Pso5/Rad16 and Sgs1 proteins: influences on DNA repair and aging.

The interaction trap method was used to isolate putative binding partners of Rad16/Pso5, a protein responsible for repair of silent DNA. One of the interactors found was Sgs1, a DNA helicase influencing the life span of Saccharomyces cerevisiae, with homology to the human BLM, WRN and RECQL4 proteins. Using the same fusion proteins from the two-hybrid screening, we show evidence that both proteins also interact in vitro. We tested isogenic strains, containing mutant alleles of the two genes in single and double mutant combination, for phenotypic similarity. Life span in sgs1Delta single and sgs1Delta rad16Delta double mutants is about 40% of that of WT, and the rad16/pso5Delta single mutant also had its life span reduced to 75%. Sensitivity to different mutagens, whose lesions are poorly repaired in rad16/pso5Delta mutants, was tested in sgs1Delta mutants. The sgs1Delta conferred sensitivity to MMS, H2O2 and was moderately sensitive to UV(254nm) (UVC) and 4-NQO. An epistatic interaction between rad16 and sgs1 mutations after UVC, 4-NQO and H2O2 was observed. Moreover, we found that in a top3 background, functional Sgs1p and Rad16p apparently channel MMS, 4-NQO and H2O2 induced lesions into aberrant DNA repair. Our results demonstrate that Sgs1 is not only involved in genome stability, somatic recombination and aging, but is also implicated, together with Rad16/Pso5, in the repair of specific DNA damage.     

The Arabidopsis dwf7/ste1 mutant is defective in the delta7 sterol C-5 desaturation step leading to brassinosteroid biosynthesis.

Lesions in brassinosteroid (BR) biosynthetic genes result in characteristic dwarf phenotypes in plants. Understanding the regulation of BR biosynthesis demands continued isolation and characterization of mutants corresponding to the genes involved in BR biosynthesis. Here, we present analysis of a novel BR biosynthetic locus, dwarf7 (dwf7). Feeding studies with BR biosynthetic intermediates and analysis of endogenous levels of BR and sterol biosynthetic intermediates indicate that the defective step in dwf7-1 resides before the production of 24-methylenecholesterol in the sterol biosynthetic pathway. Furthermore, results from feeding studies with 13C-labeled mevalonic acid and compactin show that the defective step is specifically the Delta7 sterol C-5 desaturation, suggesting that dwf7 is an allele of the previously cloned STEROL1 (STE1) gene. Sequencing of the STE1 locus in two dwf7 mutants revealed premature stop codons in the first (dwf7-2) and the third (dwf7-1) exons. Thus, the reduction of BRs in dwf7 is due to a shortage of substrate sterols and is the direct cause of the dwarf phenotype in dwf7.     

Effects of different types of low‐intensity management on plant‐pollinator interactions in Estonian grasslands

In the face of global pollinator decline, extensively managed grasslands play an important role in supporting stable pollinator communities. However, different types of extensive management may promote particular plant species and thus particular functional traits. As the functional traits of flowering plant species (e.g., flower size and shape) in a habitat help determine the identity and frequency of pollinator visitors, they can also influence the structures of plant−pollinator interaction networks (i.e., pollination networks). The aim of this study was to examine how the type of low‐intensity traditional management influences plant and pollinator composition, the structure of plant−pollinator interactions, and their mediation by floral and insect functional traits. Specifically, we compared mown wooded meadows to grazed alvar pastures in western Estonia. We found that both management types fostered equal diversity of plants and pollinators, and overlapping, though still distinct, plant and pollinator compositions. Wooded meadow pollination networks had significantly higher connectance and specialization, while alvar pasture networks achieved higher interaction diversity at a standardized sampling of interactions. Pollinators with small body sizes and short proboscis lengths were more specialized in their preference for particular plant species and the specialization of individual pollinators was higher in alvar pastures than in wooded meadows. All in all, the two management types promoted diverse plant and pollinator communities, which enabled the development of equally even and nested pollination networks. The same generalist plant and pollinator species were important for the pollination networks of both wooded meadows and alvar pastures; however, they were complemented by management‐specific species, which accounted for differences in network structure. Therefore, the implementation of both management types in the same landscape helps to maintain high species and interaction diversity.     

Using Median Lines in Robust Bivariate Data Analysis

Methods for robust comparison of bivariate errors-in-variables are considered. The concept of median lines is introduced for the robust estimation of principal components. Median lines separate the bivariate sample space into two equally sized parts. Statistical properties of the model parameters are derived. Robust residual analysis assesses linear relationships as well as goodness of fit and allows for the detection of potential outliers. Special emphasis is laid on graphical methods. A bivariate box-plot is proposed for exploratory data analysis. The median lines procedure is illustrated by a real example.     

A pigtailed macaque model of Kyasanur Forest disease virus and Alkhurma hemorrhagic disease virus pathogenesis

Kyasanur Forest disease virus (KFDV) and the closely related Alkhurma hemorrhagic disease virus (AHFV) are emerging flaviviruses that cause severe viral hemorrhagic fevers in humans. Increasing geographical expansion and case numbers, particularly of KFDV in southwest India, class these viruses as a public health threat. Viral pathogenesis is not well understood and additional vaccines and antivirals are needed to effectively counter the impact of these viruses. However, current animal models of KFDV pathogenesis do not accurately reproduce viral tissue tropism or clinical outcomes observed in humans. Here, we show that pigtailed macaques (Macaca nemestrina) infected with KFDV or AHFV develop viremia that peaks 2 to 4 days following inoculation. Over the course of infection, animals developed lymphocytopenia, thrombocytopenia, and elevated liver enzymes. Infected animals exhibited hallmark signs of human disease characterized by a flushed appearance, piloerection, dehydration, loss of appetite, weakness, and hemorrhagic signs including epistaxis. Virus was commonly present in the gastrointestinal tract, consistent with human disease caused by KFDV and AHFV where gastrointestinal symptoms (hemorrhage, vomiting, diarrhea) are common. Importantly, RNAseq of whole blood revealed that KFDV downregulated gene expression of key clotting factors that was not observed during AHFV infection, consistent with increased severity of KFDV disease observed in this model. This work characterizes a nonhuman primate model for KFDV and AHFV that closely resembles human disease for further utilization in understanding host immunity and development of antiviral countermeasures.     

Using squat testing to predict training loads for the deadlift, lunge, step-up, and leg extension exercises

The purpose of this study was to determine whether there is a linear relationship between the squat and a variety of quadriceps resistance training exercises for the purpose of creating prediction equations for the determination of quadriceps exercise loads based on the squat load. Six-repetition maximums (RMs) of the squat, as well as four common resistance training exercises that activate the quadriceps including the deadlift, lunge, step-up, and leg extension, were determined for each subject. Subjects included 21 college students. Data were evaluated using linear regression analysis to predict quadriceps exercise loads from 6RM squat data and were cross-validated with the prediction of sum of squares statistic. Analysis of the data revealed that the squat is a significant predictor of loads for the dead lift (R2 = 0.81, standard error of the estimate [SEE] = 12.50 kg), lunge (R2 = 0.62, SEE = 12.57 kg), step-up (R2 = 0.71, SEE = 9.58 kg), and leg extension (R2=0.67, SEE = 10.26 kg) exercises. Based on the analysis of the data, the following 6RM prediction equations were devised for each exercise: (a) deadlift load = squat load (0.83) + 14.92 kg, (b) lunge load = squat load (0.52) + 14.82 kg, (c) step-up load = squat load (0.50) + 3.32 kg, and (d) leg extension load = squat load (0.48) + 9.58 kg. Results from testing core exercises such as the squat can provide useful data for the assignment of loads for other exercises.