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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.

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.

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.

Climate warming is expected to increase growth and expansion of evergreen vegetation in many cold regions, with substantial influences on ecological and atmospheric processes. Nevertheless, the direction and magnitude of changes in productivity (greenness) of evergreen vegetation, as well as their potential drivers, remain unclear in many parts of the world. The woody evergreen vegetation on the Tibetan Plateau influences ecosystems and land surface processes, affecting regional and continental weather and climate through regulating land-air interactions. Here, we show that the remotely-sensed winter greenness of evergreen vegetation increased by 9.8% over 2000-2021 on the Tibetan Plateau, with significant (P < 0.05) greening across 55.8% of the areas with evergreen vegetation, which is more widespread than the increase of summer peak greenness, suggesting upslope shifts in treelines and shrublines and encroachment by evergreen woody plants. While our results show that warming was the principal climate driver of greening, the spatial pattern of greening was more related to the temperature sensitivity of greenness rather than temperature trends. Positive impacts of increasing precipitation on greenness were observed in a few areas classified as grasslands. Moreover, the magnitude of winter greening on the plateau was larger than that of the greening in the Arctic, where warming was faster, which indicates higher level of sensitivity of greenness to temperature of evergreen vegetation on the Tibetan Plateau. Our results highlight the high sensitivity of evergreen vegetation to climate warming and provide a new foundation for improving the understanding the responses and feedbacks of the Tibetan Plateau ecosystem to climate change.