Consistency of global warming trends strengthened since 1880s

The unprecedented 2022 extreme summer heatwaves increased harmful cyanobacteria blooms

Heatwaves are increasing and expected to intensify in coming decades with global warming. However, direct evidence and knowledge of the mechanisms of the effects of heatwaves on harmful cyanobacteria blooms are limited and unclear. In 2022, we measured chlorophyll-a (Chla) at 20-s intervals based on a novel ground-based proximal sensing system (GBPSs) in the shallow eutrophic Lake Taihu and combined in situ Chla measurements with meteorological data to explore the impacts of heatwaves on cyanobacterial blooms and the potential relevant mechanisms. We found that three unprecedented summer heatwaves (July 4-15, July 22-August 16, and August 18-23) lasting a total of 44 days were observed with average maximum air temperatures (MATs) of 38.1 ± 1.9 °C, 38.7 ± 1.9 °C, and 40.2 ± 2.1 °C, respectively, and that these heatwaves were characterized by high air temperature, strong PAR, low wind speed and rainfall. The daily Chla significantly increased with increasing MAT and photosynthetically active radiation (PAR) and decreasing wind speed, revealing a clear promotion effect on harmful cyanobacteria blooms from the heatwaves. Moreover, the combined effects of high temperature, strong PAR and low wind, enhanced the stability of the water column, the light availability and the phosphorus release from the sediment which ultimately boosted cyanobacteria blooms. The projected increase in heatwave occurrence under future climate change underscores the urgency of reducing nutrient input to eutrophic lakes to combat cyanobacteria growth and of improving early warning systems to ensure secure water management.

Bacterial Diversity Analysis and Screening for ACC Deaminase-Producing Strains in Moss-Covered Soil at Different Altitudes in Tianshan Mountains-A Case Study of Glacier No. 1

The elevation of the snowline of the No. 1 Glacier in the Tianshan Mountains is increasing due to global warming, which has created favorable conditions for moss invasion and offers an opportunity to investigate the synergistic effects of incipient succession by mosses, plants, and soils. In this study, the concept of altitude distance was used instead of succession time. To investigate the changes of bacterial-community diversity in moss-covered soils during glacial degeneration, the relationship between bacterial community structure and environmental factors was analyzed and valuable microorganisms in moss-covered soils were explored. To do so, the determination of soil physicochemical properties, high-throughput sequencing, the screening of ACC-deaminase-producing bacteria, and the determination of ACC-deaminase activity of strains were performed on five moss-covered soils at different elevations. The results showed that the soil total potassium content, soil available phosphorus content, soil available potassium content, and soil organic-matter content of the AY3550 sample belt were significantly different compared with those of other sample belts (p < 0.05). Secondly, there was a significant difference (p < 0.05) in the ACE index or Chao1 index between the moss-covered-soil AY3550 sample-belt and the AY3750 sample-belt bacterial communities as the succession progressed. The results of PCA analysis, RDA analysis, and cluster analysis at the genus level showed that the community structure of the AY3550 sample belt and the other four sample belts differed greatly and could be divided into two successional stages. The enzyme activities of the 33 ACC-deaminase-producing bacteria isolated and purified from moss-covered soil at different altitudes ranged from 0.067 to 4.7375 U/mg, with strains DY1-3, DY1-4, and EY2-5 having the highest enzyme activities. All three strains were identified as Pseudomonas by morphology, physiology, biochemistry, and molecular biology. This study provides a basis for the changes in moss-covered soil microhabitats during glacial degradation under the synergistic effects of moss, soil, and microbial communities, as well as a theoretical basis for the excavation of valuable microorganisms under glacial moss-covered soils.

Nonlinear Mixed Effect Model Used in a Simulation of the Impact of Climate Change on Height Growth of Cyclobalanopsis glauca

Localized climate is sensitive to terrain, underlying surface material, building distribution, green coverage and CO2 emissions. The Regional Climate Model (RegCM) was used to make a statistical detailed analysis of the climate change data in a specific study area to obtain fine-scale distribution of climatic elements data over time. The effects of climate change factors on height growth trends of a climate-sensitive tree species (Cyclobalanopsis glauca) were simulated based on historical climate base line data (1961–2010) and future climate change (2010–2100) predictions. Cyclobalanopsis glauca growth trends were simulated and analyzed by using a nonlinear mixed effect model (NLME). The results showed that under the RCP8.5 emissions scenario, the growth promotion effect on the height growth of Cyclobalanopsis glauca will be obvious. Under RCP4.5 and RCP2.6 emissions scenarios, although the inhibition intensity is not exactly the same, height growth will still be inhibited to a certain extent, which may lead to the gradual extinction of this species, affecting the composition of dominant tree species in the study area. The results indirectly reflect the impact of climate change on tree species diversity in the future.

Response of Precipitation in Tianshan to Global Climate Change Based on the Berkeley Earth and ERA5 Reanalysis Products

Global climate change has readjusted a global-scale precipitation distribution in magnitude and timing. In mountainous areas, meteorological stations and observation data are very limited, making it difficult to accurately understand the response of precipitation to global climate change. Based on ECMWF Reanalysis v5 precipitation products, Berkeley Earth global temperature, and typical atmospheric circulation indexes, we integrated a gradient descent-nonlinear regression downscaling model, cross wavelet transform, and wavelet correlation method to analyze the precipitation response in Tianshan to global climate change. This study provides a high-resolution (90 m × 90 m) precipitation dataset in Tianshan and confirms that global warming, the North Pacific Pattern (NP), the Western Hemisphere Warm Pool (WHWP), and the Atlantic Multidecadal Oscillation (AMO) are related to the humidification of Tianshan over the past 40 years. The precipitation in Tianshan and global temperature have a resonance period of 8–15 months, and the correlation coefficient is above 0.9. In Tianshan, spring precipitation is determined mainly by AMO, North Tropical Atlantic Sea Level Temperature, Pacific Interdecadal Oscillation (PDO), Tropical North Atlantic Index, WHWP, NP, summer by NP, North Atlantic Oscillation, and PDO, autumn by AMO, and winter by Arctic Oscillation. This research can serve the precipitation forecast of Tianshan and help in the understanding of the regional response to global climate change.

Recent leveling off of vegetation greenness and primary production reveals the increasing soil water limitations on the greening Earth

Global vegetation photosynthesis and productivity have increased substantially since the 1980s, but this trend is heterogeneous in both time and space. Here, we categorize the secular trend in global vegetation greenness into sustained greening, sustained browning and greening-to-browning. We found that by 2016, increased global vegetation greenness had begun to level off, with the area of browning increasing in the last decade, reaching 39.0 million km² (35.9% of the world's vegetated area). This area is larger than the area with sustained increasing growth (27.8 million km², 26.4%); thus, 12.0% ± 3.1% (0.019 ± 0.004 NDVI a^-1) of the previous earlier increase has been offset since 2010 (2010-2016, P < 0.05). Global gross primary production also leveled off, following the trend in vegetation greenness in time and space. This leveling off was caused by increasing soil water limitations due to the spatial expansion of drought, whose impact dominated over the impacts of temperature and solar radiation. This response of global gross primary production to soil water limitation was not identified by land submodels within Earth system models. Our results provide empirical evidence that global vegetation greenness and primary production are offset by water stress and suggest that as global warming continues, land submodels may overestimate the world's capacity to take up carbon with global vegetation greening.