Responses of seasonal indicators to extreme droughts in southwest China

Significant impact of extreme droughts on human society and ecosystem has occurred in many places of the world, for example, Southwest China (SWC). Considerable research concentrated on analyzing causes and effects of droughts in SWC, but few studies have examined seasonal indicators, such as variations of surface water and vegetation phenology. With the ongoing satellite missions, more and more earth observation data become available to environmental studies. Exploring the responses of seasonal indicators from satellite data to drought is helpful for the future drought forecast and management. This study analyzed the seasonal responses of surface water and vegetation phenology to drought in SWC using the multi-source data including Seasonal Water Area (SWA), Permanent Water Area (PWA), Start of Season (SOS), End of Season (EOS), Length of Season (LOS), precipitation, temperature, solar radiation, evapotranspiration, the Palmer Drought Severity Index (PDSI), the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), Gross Primary Productivity (GPP) and data from water conservancy construction. The results showed that SWA and LOS effectively revealed the development and recovery of droughts. There were two obvious drought periods from 2000 to 2017. In the first period (from August 2003 to June 2007), SWA decreased by 11.81% and LOS shortened by 5 days. They reduced by 21.04% and 9 days respectively in the second period (from September 2009 to June 2014), which indicated that there are more severe droughts in the second period. The SOS during two drought periods delayed by 3~6 days in spring, while the EOS advanced 1~3 days in autumn. All of PDSI, SWA and LOS could reflect the period of droughts in SWC, but the LOS and PDSI were very sensitive to the meteorological events, such as precipitation and temperature, while the SWA performed a more stable reaction to drought and could be a good indicator for the drought periodicity. This made it possible for using SWA in drought forecast because of the strong correlation between SWA and drought. Our results improved the understanding of seasonal responses to extreme droughts in SWC, which will be helpful to the drought monitoring and mitigation for different seasons in this ecologically fragile region

Monitoring of Extreme Agricultural Drought of the Past 20 Years in Southwest China Using GLDAS Soil Moisture

Drought can cause severe agricultural economic losses and hinder social and economic development. To manage drought, the process of drought events needs to be described with the help of an effective drought indicator. As a comprehensive variable, soil moisture is an essential indicator for describing agricultural drought. In this work, the extreme drought events in southwest China were analysed by the Global Land Data Assimilation System (GLDAS) root zone soil moisture data set. To define the drought quantitatively, a Standardized Soil Moisture Drought Index (SSMI) was calculated using the soil moisture data, then used to get the duration, frequency, and severity of drought events in southwest China. The results showed that the frequency and intensity of drought in southwest China had an apparent upward trend before 2014 and an apparent downward trend since 2014. Moreover, there are apparent differences in the frequency and intensity of drought in various regions of southwest China. Yunnan Province is prone to spring drought events. Guangxi Province and Guizhou Province are prone to spring, autumn and winter droughts, and the intensity of autumn and winter droughts is significantly higher than that of spring droughts. The Sichuan-Chongqing border area is prone to summer drought. We found that the monthly variation of soil moisture in different provinces in southwest China is consistent, but the seasonal variation of drought is different. Meanwhile, the performance of the SSMI was compared to the commonly used drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI). The results showed that the SSMI is more sensitive to drought than both SPEI and PDSI in southwest China. The results also demonstrate that GLDAS soil moisture data can be used to study drought at a small regional scale

Longitudinal Changes in the Concentration of Major Human Milk Proteins in the First Six Months of Lactation and Their Effects on Infant Growth

Our knowledge related to human milk proteins is still limited. The present study determined the changes in multiple human milk proteins during the first six months of lactation, investigated the influencing factors of milk proteins, and explored the impact of milk proteins on infant growth. A total of 105 lactating women and their full-term infants from China were prospectively surveyed in this research. Milk samples were collected at 1–5 days, 8–14 days, 1 month, and 6 months postpartum. Concentrations of total protein and α-lactalbumin were measured in all milk samples, and concentrations of lactoferrin, osteopontin, total casein, β-casein, αs−1 casein, and κ-casein were measured in milk from 51 individuals using ultra performance liquid chromatography coupled with mass spectrometry. The concentration of measured proteins in the milk decreased during the first six months of postpartum (p-trend < 0.001). Maternal age, mode of delivery, maternal education, and income impacted the longitudinal changes in milk proteins (p-interaction < 0.05). Concentrations of αs−1 casein in milk were inversely associated with the weight-for-age Z-scores of the infants (1 m: r −0.29, p 0.038; 6 m: r −0.33, p 0.020). In conclusion, the concentration of proteins in milk decreased over the first six months postpartum, potentially influenced by maternal demographic and delivery factors. Milk protein composition may influence infant weights

Quantifying the Contributions of Climate Change and Human Activities to Water Volume in Lake Qinghai, China

Lake Qinghai has shrunk and then expanded over the past few decades. Quantifying the contributions of climate change and human activities to lake variation is important for water resource management and adaptation to climate change. In this study, we calculated the water volume change of Lake Qinghai, analyzed the climate and land use changes in Lake Qinghai catchment, and distinguished the contributions of climate change and local human activities to water volume change. The results showed that lake water volume decreased by 9.48 km3 from 1975 to 2004 and increased by 15.18 km3 from 2005 to 2020. The climate in Lake Qinghai catchment is becoming warmer and more pluvial, and the changes in land use have been minimal. Based on the Soil and Water Assessment Tool (SWAT), land use change, climate change and interaction effect of them contributed to 7.46%, 93.13% and −0.59%, respectively, on the variation in surface runoff into the lake. From the perspective of the water balance, we calculated the proportion of each component flowing into and out of the lake and found that the contribution of climate change to lake water volume change was 97.55%, while the local human activities contribution was only 2.45%. Thus, climate change had the dominant impact on water volume change in Lake Qinghai

Impact of Future Climate and Land Use Changes on Runoff in a Typical Karst Basin, Southwest China

Climate change and land use change are the two main factors affecting the regional water cycle and water resources management. However, runoff studies in the karst basin based on future scenario projections are still lacking. To fill this gap, this study proposes a framework consisting of a future land use simulation model (FLUS), an automated statistical downscaling model (ASD), a soil and water assessment tool (SWAT) and a multi-point calibration strategy. This frameword was used to investigate runoff changes under future climate and land use changes in karst watersheds. The Chengbi River basin, a typical karst region in southwest China, was selected as the study area. The ASD method was developed for climate change projections based on the CanESM5 climate model. Future land use scenarios were projected using the FLUS model and historical land use data. Finally, the SWAT model was calibrated using a multi-site calibration strategy and was used to predict future runoff from 2025–2100. The results show that: (1) the developed SWAT model obtained a Nash efficiency coefficient of 0.83, which can adequately capture the spatial heterogeneity characteristics of karst hydro-climate; (2) land use changes significantly in all three future scenarios, with the main phenomena being the interconversion of farmland and grassland in SSPs1-2.6, the interconversion of grassland, farmland and artificial surfaces in SSPs2-4.5 and the interconversion of woodland, grassland and artificial surfaces in SSPs5-8.5; (3) the average annual temperature will show an upward trend in the future, and the average annual precipitation will increase by 11.53–14.43% and (4) the future annual runoff will show a significant upward trend, with monthly runoff mainly concentrated in July–September. The variability and uncertainty of future runoff during the main-flood period may increase compared to the historical situation. The findings will benefit future water resources management and water security in the karst basin

Herbal formula BaWeiBaiDuSan alleviates polymicrobial sepsis-induced liver injury via increasing the gut microbiota Lactobacillus johnsonii and regulating macrophage anti-inflammatory activity in mice

Sepsis-induced liver injury (SILI) is an important cause of septicemia deaths. BaWeiBaiDuSan (BWBDS) was extracted from a formula of Panax ginseng C. A. Meyer, Lilium brownie F. E. Brown ex Miellez var. viridulum Baker, Polygonatum sibiricum Delar. ex Redoute, Lonicera japonica Thunb., Hippophae rhamnoides Linn., Amygdalus Communis Vas, Platycodon grandiflorus (Jacq.) A. DC., and Cortex Phelloderdri. Herein, we investigated whether the BWBDS treatment could reverse SILI by the mechanism of modulating gut microbiota. BWBDS protected mice against SILI, which was associated with promoting macrophage anti-inflammatory activity and enhancing intestinal integrity. BWBDS selectively promoted the growth of Lactobacillus johnsonii (L. johnsonii) in cecal ligation and puncture treated mice. Fecal microbiota transplantation treatment indicated that gut bacteria correlated with sepsis and was required for BWBDS anti-sepsis effects. Notably, L. johnsonii significantly reduced SILI by promoting macrophage anti-inflammatory activity, increasing interleukin-10+ M2 macrophage production and enhancing intestinal integrity. Furthermore, heat inactivation L. johnsonii (HI-L. johnsonii) treatment promoted macrophage anti-inflammatory activity and alleviated SILI. Our findings revealed BWBDS and gut microbiota L. johnsonii as novel prebiotic and probiotic that may be used to treat SILI. The potential underlying mechanism was at least in part, via L. johnsonii-dependent immune regulation and interleukin-10+ M2 macrophage production