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The stability of winter wheat-flowering-date is crucial for ensuring consistent and robust crop performance across diverse climatic conditions. However, the impact of climate change on wheat-flowering-dates remains uncertain. This study aims to elucidate the influence of climate change on wheat-flowering-dates, predict how projected future climate conditions will affect flowering date stability, and identify the most stable wheat genotypes in the study region. We applied a multi-locus genotype-based (MLG-based) model for simulating wheat-flowering-dates, which we calibrated and evaluated using observed data from the Northern China winter wheat region (NCWWR). This MLG-based model was employed to project flowering dates under different climate scenarios. The simulated flowering dates were then used to assess the stability of flowering dates under varying allelic combinations in projected climatic conditions. Our MLG-based model effectively simulated flowering dates, with a root mean square error (RMSE) of 2.3 days, explaining approximately 88.5 % of the genotypic variation in flowering dates among 100 wheat genotypes. We found that, in comparison to the baseline climate, wheat-flowering-dates are expected to shift earlier within the target sowing window by approximately 11 and 14 days by 2050 under the Representative Concentration Pathways 4.5 (RCP4.5) and RCP8.5 climate scenarios, respectively. Furthermore, our analysis revealed that wheat-flowering-date stability is likely to be further strengthened under projected climate scenarios due to early flowering trends. Ultimately, we demonstrate that the combination of Vrn and Ppd genes, rather than individual Vrn or Ppd genes, plays a critical role in wheat-flowering-date stability. Our results suggest that the combination of Ppd-D1a with winter genotypes carrying the vrn-D1 allele significantly contributes to flowering date stability under current and projected climate scenarios. These findings provide valuable insights for wheat breeders and producers under future climatic conditions.

The activity of methanogens and related bacteria which inhabit the coal beds is essential for stimulating new biogenic coal bed methane (CBM) production from the coal matrix. In this study, the microbial community structure and methanogenesis were investigated in Southern Qinshui Basin in China, and the composition and stable isotopic ratios of CBM were also determined. Although geochemical analysis suggested a mainly thermogenic origin for CBM, the microbial community structure and activities strongly implied the presence of methanogens in situ. 454 pyrosequencing analysis combined with methyl coenzyme-M reductase (mcrA) gene clone library analysis revealed that the archaeal communities in the water samples from both coal seams were similar, with the dominance of hydrogenotrophic methanogen Methanobacterium. The activity and potential of these populations to produce methane were confirmed by the observation of methane production in enrichments supplemented with H2 + CO2 and formate, and the only archaea successfully propagated in the tested water samples was from the genus Methanobacterium. 454 pyrosequencing analysis also recovered the diverse bacterial communities in the water samples, which have the potential to play a role in the coal biodegradation fueling methanogens. These results suggest that the biogenic CBM was generated by coal degradation via the hydrogenotrophic methanogens and related bacteria, which also contribute to the huge CBM reserves in Southern Qinshui Basin, China.

3-(Hydroxy(phenyl)phosphoryl)propanoic acid (HPA) has a strong coordination ability for Zn2+/metal anodes which not only form sphere micelles that promote the uniform transmission of Zn2+ but also enhance the preferential adsorption on anodes.

AbstractMountain treelines are thought to be sensitive to climate change. However, how climate impacts mountain treelines is not yet fully understood as treelines may also be affected by other human activities. Here, we focus on “closed‐loop” mountain treelines (CLMT) that completely encircle a mountain and are less likely to have been influenced by human land‐use change. We detect a total length of ~916,425 km of CLMT across 243 mountain ranges globally and reveal a bimodal latitudinal distribution of treeline elevations with higher treeline elevations occurring at greater distances from the coast. Spatially, we find that temperature is the main climatic driver of treeline elevation in boreal and tropical regions, whereas precipitation drives CLMT position in temperate zones. Temporally, we show that 70% of CLMT have moved upward, with a mean shift rate of 1.2 m/year over the first decade of the 21st century. CLMT are shifting fastest in the tropics (mean of 3.1 m/year), but with greater variability. Our work provides a new mountain treeline database that isolates climate impacts from other anthropogenic pressures, and has important implications for biodiversity, natural resources, and ecosystem adaptation in a changing climate.