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Soils harbor highly diverse microbial communities that are critical to soil health, but agriculture has caused extensive land use conversion resulting in negative effects on critical ecosystem processes. However, the responses and adaptations of microbial communities to land use conversion have not yet been understood. Here, we examined the effects of land conversion for long-term crop use on the network complexity and stability of soil microbial communities over 19 months. Despite reduced microbial biodiversity in comparison with native tallgrass prairie, conventionally tilled (CT) cropland significantly increased network complexity such as connectivity, connectance, average clustering coefficient, relative modularity, and the number of species acting at network hubs and connectors as well as resulted in greater temporal variation of complexity indices. Molecular ecological networks under CT cropland became significantly more robust and less vulnerable, overall increasing network stability. The relationship between network complexity and stability was also substantially strengthened due to land use conversion. Lastly, CT cropland decreased the number of relationships between network structure and environmental properties instead being strongly correlated to management disturbances. These results indicate that agricultural disturbance generally increases the complexity and stability of species “interactions”, possibly as a trade-off for biodiversity loss to support ecosystem function when faced with frequent agricultural disturbance.

Understanding sub‐daily precipitation extremes (SPEs) can provide scientific insights for taking effective measures to mitigate climate risks. Leveraging gauge observations at hourly precipitation in 2,312 meteorological stations and extreme sub‐daily precipitation indices (ESPIs), we investigate the changes of SPEs in flooding season of 1971–2022 in China. On country scale, the occurrences and intensity of SPEs have significantly increased and even accelerated since the 21st century, suggesting increases in 2010s by 15%–38% compared with that in 1970s. The SPE risks for 20‐year and 50‐year return‐period increased by 2–4 and 8–20 times in 2001–2022 compared with that in 1971–2000, respectively. Over 80% stations are found to have positive trends in all ESPIs. On regional scale, seven sub‐regions experienced significant increases in ESPIs with larger magnitudes in the East China. The enlarged 500‐hPa geopotential height, 700‐hPa pseudoequivalent potential temperature, 700‐hPa specific humidity, saturated vapor pressure and urbanization ratio may be bonded to more SPEs. Plain Language Summary Short‐term precipitation extremes have serious impacts on human safety, agriculture, energy, and infrastructure. It is very urgent to understand their variations and underlying mechanisms for policy‐makers to take effective approaches to mitigate extreme precipitation‐related risks. Here, we investigate the spatio‐temporal changes of sub‐daily precipitation extremes in the flooding season of 1971–2022 in China. We examine six metrics of extreme sub‐daily precipitation based on hourly observation data. We find that the occurrences and intensity of SPEs have significantly increased during the recent 52 years with acceleration since the 21st century on both country and regional level. The once‐in‐20‐year and once‐in‐50‐year events in 2001–2022 increased by 2–4 and 8–20 times compared with that in 1971–2000, respectively. The larger upward magnitudes of ESPIs are mainly located in the East China. In the era of rapid global warming, thermodynamic effects of abnormal atmospheric circulation and rapid urbanization possibly facilitate the occurrences of more SPEs in China. Key Points Sub‐daily precipitation extremes have substantially increased over China during 1971–2022, even accelerating since the 21st century Most of China exhibits consistent upward trends in all extreme sub‐daily precipitation indices with lager magnitudes in the East China Thermodynamic effects of abnormal atmospheric circulation and urbanization are possibly boned to increased sub‐daily precipitation extremes

The North China Plain (NCP) has been suffering from groundwater storage (GWS) depletion and land subsidence for a long period. This paper collects data on GWS changes and land subsidence from in situ groundwater-level measurements, literature, and satellite observations to provide an overview of the evolution of the aquifer system during 1971–2015 with a focus on the sub-regional variations. It is found that the GWS showed a prolonged declining rate of −17.8 ± 0.1 mm/yr during 1971–2015, with a negative correlation to groundwater abstraction before year ~2000 and a positive correlation after ~2000. Statistical correlations between subsidence rate and the GWS anomaly (GWSA), groundwater abstraction, and annual precipitation show that the land subsidence in three sub-regions (Beijing, Tianjin, and Hebei) represents different temporal variations due to varying driver factors. Continuous drought caused intensive GWS depletion (−76.1 ± 6.5 mm/yr) and land subsidence in Beijing during 1999–2012. Negative correlations between total groundwater abstraction and land subsidence exhibited after the 1980s indicate that it may be questionable to infer subsidence from regional abstraction data. Instead, the GWSA generally provides a reliable correlation with subsidence. This study highlights the spatio-temporal variabilities of GWS depletion and land subsidence in the NCP under natural and anthropogenic impacts, and the importance of GWS changes for understanding land subsidence development.

Background The influence of genetic variation on complex diseases is potentially mediated through a range of highly dynamic epigenetic processes exhibiting temporal variation during development and later life. Here we present a catalogue of the genetic influences on DNA methylation (methylation quantitative trait loci (mQTL)) at five different life stages in human blood: children at birth, childhood, adolescence and their mothers during pregnancy and middle age. Results We show that genetic effects on methylation are highly stable across the life course and that developmental change in the genetic contribution to variation in methylation occurs primarily through increases in environmental or stochastic effects. Though we map a large proportion of the cis -acting genetic variation, a much larger component of genetic effects influencing methylation are acting in trans . However, only 7 % of discovered mQTL are trans -effects, suggesting that the trans component is highly polygenic. Finally, we estimate the contribution of mQTL to variation in complex traits and infer that methylation may have a causal role consistent with an infinitesimal model in which many methylation sites each have a small influence, amounting to a large overall contribution. Conclusions DNA methylation contains a significant heritable component that remains consistent across the lifespan. Our results suggest that the genetic component of methylation may have a causal role in complex traits. The database of mQTL presented here provide a rich resource for those interested in investigating the role of methylation in disease.

Projecting how the East Asian summer monsoon (EASM) rainfall will change with global warming is essential for human sustainability. Reconstructing Holocene climate can provide critical insight into its forcing and future variability. However, quantitative reconstructions of Holocene summer precipitation are lacking for tropical and subtropical China, which is the core region of the EASM influence. Here we present high-resolution annual and summer rainfall reconstructions covering the whole Holocene based on the pollen record at Xinjie site from the lower Yangtze region. Summer rainfall was less seasonal and ~ 30% higher than modern values at ~ 10–6 cal kyr BP and gradually declined thereafter, which broadly followed the Northern Hemisphere summer insolation. Over the last two millennia, however, the summer rainfall has deviated from the downward trend of summer insolation. We argue that greenhouse gas forcing might have offset summer insolation forcing and contributed to the late Holocene rainfall anomaly, which is supported by the TraCE-21 ka transient simulation. Besides, tropical sea-surface temperatures could modulate summer rainfall by affecting evaporation of seawater. The rainfall pattern concurs with stalagmite and other proxy records from southern China but differs from mid-Holocene rainfall maximum recorded in arid/semiarid northern China. Summer rainfall in northern China was strongly suppressed by high-northern-latitude ice volume forcing during the early Holocene in spite of high summer insolation. In addition, the El Niño/Southern Oscillation might be responsible for droughts of northern China and floods of southern China during the late Holocene. Furthermore, quantitative rainfall reconstructions indicate that the Paleoclimate Modeling Intercomparison Project (PMIP) simulations underestimate the magnitude of Holocene precipitation changes. Our results highlight the spatial and temporal variability of the Holocene EASM precipitation and potential forcing mechanisms, which are very helpful for calibration of paleoclimate models and prediction of future precipitation changes in East Asia in the scenario of global warming.

The Three Gorges Dam (TGD), located upstream of the Yangtze River, is the largest hydroelectric project in the world. The operation of TGD has changed the spatial and temporal distribution of streamflow in the middle and lower Yangtze River. The operation of TGD can also have varying degrees of impact on groundwater due to stream–aquifer interactions. Jianghan Plain is a major farming area in southern China, where groundwater is a critical source for domestic and agricultural use. Therefore, it is important to study the impact of the operation of TGD on the groundwater level in Jianghan Plain. Based on the STL algorithm, this study examined the interannual, annual, and random variations of groundwater levels in Jianghan Plain, analyzed and quantified the impacts of various factors including the operation of TGD that cause the spatial and temporal variation of the groundwater level. The results show that the operation of TGD can reduce the amplitude of the groundwater level and the frequency of extreme values. From upstream to downstream, the impact of TGD operation on the groundwater level shows a decreasing trend. The operation of TGD has a strong impact on the interannual variation within 6.71 km and annual variation within 5.77 km from the Yangtze River. The conclusions of this study can provide recommendations for local governments to develop groundwater management policies.

Tree stems from wetland, floodplain and upland forests can produce and emit methane (CH₄). Tree CH₄ stem emissions have high spatial and temporal variability, but there is no consensus on the biophysical mechanisms that drive stem CH₄ production and emissions. Here, we summarize up to 30 opportunities and challenges for stem CH₄ emissions research, which, when addressed, will improve estimates of the magnitudes, patterns and drivers of CH₄ emissions and trace their potential origin.We identified the need: (1) for both long-term, high-frequency measurements of stem CH₄ emissions to understand the fine-scale processes, alongside rapid large-scale measurements designed to understand the variability across individuals, species and ecosystems; (2) to identify microorganisms and biogeochemical pathways associated with CH₄ production; and (3) to develop a mechanistic model including passive and active transport of CH₄ from the soil–tree–atmosphere continuum. Addressing these challenges will help to constrain the magnitudes and patterns of CH₄ emissions, and allow for the integration of pathways and mechanisms of CH₄ production and emissions into process-based models. These advances will facilitate the upscaling of stem CH₄ emissions to the ecosystem level and quantify the role of stem CH₄ emissions for the local to global CH₄ budget.

Global warming is resulting in increased frequency of weather extremes. Root-associated fungi play important roles in terrestrial biogeochemical cycling processes, but the way in which they are affected by extreme weather is unclear. Here, we performed long-term field monitoring of the root-associated fungus community of a short rotation coppice willow plantation, and compared community dynamics before and after a once in 100 yr rainfall event that occurred in the UK in 2012. Monitoring of the root-associated fungi was performed over a 3-yr period by metabarcoding the fungal internal transcribed spacer (ITS) region. Repeated soil testing and continuous climatic monitoring supplemented community data, and the relative effects of environmental and temporal variation were determined on the root-associated fungal community. Soil saturation and surface water were recorded throughout the early growing season of 2012, following extreme rainfall. This was associated with a crash in the richness and relative abundance of ectomycorrhizal fungi, with each declining by over 50%. Richness and relative abundance of saprophytes and pathogens increased. We conclude that extreme rainfall events may be important yet overlooked determinants of root-associated fungal community assembly. Given the integral role of ectomycorrhizal fungi in biogeochemical cycles, these events may have considerable impacts upon the functioning of terrestrial ecosystems.

• Leaf mass per area (LMA) is a key plant trait, reflecting tradeoffs between leaf photosynthetic function, longevity, and structural investment. Capturing spatial and temporal variability in LMA has been a long-standing goal of ecological research and is an essential component for advancing Earth system models. Despite the substantial variation in LMA within and across Earth’s biomes, an efficient, globally generalizable approach to predict LMA is still lacking. • We explored the capacity to predict LMA from leaf spectra across much of the global LMA trait space, with values ranging from 17 to 393 gm–2. Our dataset contained leaves from a wide range of biomes from the high Arctic to the tropics, included broad- and needleleaf species, and upper- and lower-canopy (i.e. sun and shade) growth environments. • Here we demonstrate the capacity to rapidly estimate LMA using only spectral measurements across a wide range of species, leaf age and canopy position from diverse biomes. Our model captures LMA variability with high accuracy and low error (R² = 0.89; root mean square error (RMSE) = 15.45 gm–2). • Our finding highlights the fact that the leaf economics spectrum is mirrored by the leaf optical spectrum, paving the way for this technology to predict the diversity of LMA in ecosystems across global biomes.

Climate gradients shape spatial variation in the richness and composition of plant communities. Given future predicted changes in climate means and variability, and likely regional variation in the magnitudes of these changes, it is important to determine how temporal variation in climate influences temporal variation in plant community structure. Here, we evaluated how species richness, turnover, and composition of grassland plant communities responded to interannual variation in precipitation by synthesizing long-term data from grasslands across the United States. We found that mean annual precipitation (MAP) was a positive predictor of species richness across sites, but a positive temporal relationship between annual precipitation and richness was only evident within two sites with low MAP. We also found higher average rates of species turnover in dry sites that in turn had a high proportion of annual species, although interannual rates of species turnover were surprisingly high across all locations. Annual species were less abundant than perennial species at nearly all sites, and our analysis showed that the probability of a species being lost or gained from one year to the next increased with decreasing species abundance. Bray-Curtis dissimilarity from one year to the next, a measure of species composition change that is influenced mainly by abundant species, was insensitive to precipitation at all sites. These results suggest that the richness and turnover patterns we observed were driven primarily by rare species, which comprise the majority of the local species pools at these grassland sites. These findings are consistent with the idea that short-lived and less abundant species are more sensitive to interannual climate variability than longer-lived and more abundant species. We conclude that, among grassland ecosystems, xeric grasslands are likely to exhibit the greatest responsiveness of community composition (richness and turnover) to predicted future increases in interannual precipitation variability. Over the long term, species composition may shift to reflect spatial patterns of mean precipitation; however, perennial-dominated systems will be buffered against rising interannual variation, while systems that have a large number of rare, annual species will show the greatest temporal variability in species composition in response to rising interannual variability in precipitation.