Subtropical Monsoon Region Research Articles

Richness, not evenness, of invasive plant species promotes invasion success into native plant communities via selection effects

Native plant communities are often invaded by multiple alien species. It is still unclear how increasing diversity of alien invasive species suppresses the growth of native species and thus contributes to invasion success. In the subtropical monsoon region of southeast China, we experimentally created a native plant community with 18 herbaceous species. One week later, we let it be invaded by either zero (controls without invasion), one, two, four or eight alien plant species, with either high or low species evenness. After a four‐month growth period we harvested the aboveground biomass of each species. We found that increasing invasive species richness significantly increased invasive plant biomass, the biomass of all invasive and native plant species within the community, and invasion success (the ratio of invasive plant biomass to the biomass of all native and invasive plants), but it did not significantly reduce native plant biomass. Experimentally manipulating invasive species evenness did not influence invasion success and did not show any differential suppression effects on native plants. One invasive species,Sesbania cannabina, became dominant in terms of plant biomass, irrespective of its proportion in the alien plant mixtures. Throughout this experiment, effects of invasive species richness on invasion success were mainly due to such selection effects among the invasive species. On the other hand, the unchanged biomass of native species under increasing invasive plant richness suggests the presence of at least partly complementary resource niches between invasive and native species.

Prediction of daily reference crop evapotranspiration in different Chinese climate zones: Combined application of key meteorological factors and Elman algorithm

Reference crop evapotranspiration (ETO) is a key factor for estimating crop water requirements, which guide agricultural irrigation. To improve the accuracy of predicting ETO in different climate zones in China that lack meteorological data, an ETO hybrid model based on K-nearest neighbour (KNN) machine learning algorithm for extracting factor contribution rates is proposed in this study. Meteorological factors with large contribution rates were selected as input, and a prediction model for ETO was established using the Elman daily ETO prediction model. The ETO prediction model was optimised using three optimisation algorithms [Genetic optimization algorithm (GA), Cuckoo optimization algorithm (CS) and Whale optimization algorithm (WOA)] to improve the accuracy of ETO prediction. The results revealed that surface radiation (Rs) is the most important factor in estimating ETO (contribution rate = 0.392–0.626), followed by temperature factors (T; including maximum, minimum, and average temperatures). And each model has the highest accuracy with the input combination of Rs and T. For the different machine learning models, the CS-Elman model had the highest accuracy (RMSE = 0.468–2.235, R2 = 0.567–0.928, MAE = 0.363–1.343, and NSE = 0.345–0.923), and the machine learning model had higher accuracy than the experience model. The CS-Elman model performed more favourably in tropical monsoon and subtropical monsoon regions than that in other areas, and the model performed best at the junction of two climatic zones. The results can provide a theoretical basis for high-precision prediction of ETO in different climate zones in China.

Spatial-Temporal Variation in Paddy Evapotranspiration in Subtropical Climate Regions Based on the SEBAL Model: A Case Study of the Ganfu Plain Irrigation System, Southern China

The surface energy balance algorithm for land (SEBAL) is a commonly used method for estimating evapotranspiration (ET) at a regional scale; however, the cloudy and rainy characteristics of subtropical monsoon regions pose a greater challenge for estimating paddy field ET based on remote sensing technology. To this end, a typical subtropical climate region in southern China (Ganfu Plain irrigation system) was selected as the study area. Subsequently, we evaluated the applicability of the SEBAL model for estimating the ET of paddy fields at the daily scale; derived the interannual variation (2000–2017) characteristics of early, middle, and late rice ET; and finally analyzed the spatial distribution patterns of rice in different hydrological years. The results demonstrated that: (1) the SEBAL model estimated ET accurately on a daily scale, with R2, NSE, and RMSE values of 0.85, 0.81, and 0.84 mm/day, respectively; (2) the ET of paddy fields in the irrigated area was higher in July and August and the interannual trend of ET of early rice was not obvious, with a declining trend observed in middle rice and late rice from 2000 to 2009, which was followed by an increasing trend from 2009 to 2017; and (3) variations in the spatial distribution of ET were significant for early and late rice at different precipitation levels and less obvious for middle rice in wet years but significant in dry years. Overall, this study verified the applicability of the SEBAL model for estimating ET in paddy fields in subtropical regions and provided a basis and reference for the rational allocation of water resources at a regional scale.

Evaluation of nine major satellite soil moisture products in a typical subtropical monsoon region with complex land surface characteristics

Assessing accuracies of satellite soil moisture (SM) products in areas with strong anthropogenic activities, abundant precipitation, and dense vegetation is important but limited. In this study, performances of nine satellite SM products, including the European Space Agency Climate Change Initiative (ESA CCI), and the ascending and descending products of the Advanced Microwave Scanning Radiometer 2 (AMSR2), Chinese Fengyun-3B (FY3B), Chinese Fengyun-3C (FY3C), and Soil Moisture Active Passive (SMAP), were evaluated against in-situ SM in the Yangtze River Delta (YRD) from 2015 to 2018. Results showed that the ESA CCI outperformed other products, with averaged correlation coefficient (R) of 0.522, correlation coefficient for SM anomalies (Rano) of 0.419, and unbiased root mean square error (ubRMSE) of 0.040 m3 m−3, followed by the SMAP_A and SMAP_D. Overestimation was observed in the AMSR2 products (Bias >0.081 m3 m−3), while underestimation was found in the FY3B and FY3C products (Bias < −0.104 m3 m−3). Moreover, R values decreased with the increase in water area percentage (WAP), land cover heterogeneity (GSI), fractional vegetation cover (FVC), and precipitation (PRE). Threshold values were observed at 3% for the WAP, 0.05 for the FVC, and 900 mm yr−1 for the PRE, below which sharp declines of accuracy were observed. The WAP, GSI, and FVC were divided into five sub-classes with their values increasing with the sub-class level (I to V). Correlations coefficients between these perturbing factors and R (correlation between satellite and in-situ SM) increased as sub-class levels increased. Under sub-classes I, II, and III, these three factors had limited influences on accuracies of satellite SM products. However, under sub-classes IV and V, significant impacts of these three perturbing factors were observed. Moreover, when sub-classes of the PRE increased from I to V, correlations between Bias and PRE decreased first and then increased. These findings can help to determine suitable satellite SM products in the YRD and similar areas.

Nation-scale reference evapotranspiration estimation by using deep learning and classical machine learning models in China

Accurately estimating the reference evapotranspiration (ET0) is a basic requirement for precision irrigation and the correct planning of regional water resources. This study aimed to investigate the spatiotemporal variations in ET0 in China and to improve the accuracy of ET0 calculations on different spatiotemporal scales. Meteorological data collected at 100 stations in China during 1961 to 2019 were used to calculate ET0 with the Penman–Monteith model, and the temporal and spatial patterns in ET0-PM were analyzed with the Mann–Kendall nonparametric trend test method. Three machine learning models comprising convolutional neural network (CNN), extreme learning machine (ELM), and multiple adaptive regression splines (MARS), and seven empirical models calibrated with mind evolutionary algorithm (MEA) were compared to assess their suitability for calculating ET0 on different spatiotemporal scales in China. The results showed that the annual mean ET0-PM value (413.29–2772.35 mm) in China gradually increased from north to south and from west to east. ET0 exhibited an upward trend in the temperate continental zone (TCZ) and mountain plateau zone (MPZ) but a downward trend in the temperate monsoon zone (TMZ) and subtropical monsoon region (SMZ). By comparing the global performance indicators (GPI), the machine learning models generally performed better than the empirical models at different spatiotemporal scales. And CNN was the best model for calculating ET0 in terms of the model accuracy and stability. On the daily scale, MARS performed well in MPZ, whereas ELM performed well in TMZ and TCZ. On the monthly scale, MARS performed well in TMZ, whereas ELM performed well in SMZ and MPZ. At the annual scale, the accuracy of ELM was higher than that of MARS.

Optimization of extreme learning machine model with biological heuristic algorithms to estimate daily reference crop evapotranspiration in different climatic regions of China

Accurate prediction of reference crop evapotranspiration (ET0) is important for regional water resources management and optimal design of agricultural irrigation system. In this study, three hybrid models (PSO-ELM, GA-ELM and ABC-ELM) integrating the extreme learning machine model (ELM) with three biological heuristic algorithms, i.e., PSO, GA and ABC, were proposed for predicting daily ET0 based on daily meteorological data from 2000 to 2019 at twelve representative stations in different climatic zones of China. The performances of the three hybrid ELM models were further compared with the standalone ELM model and three empirical models (Hargreaves, Priestley-Talor and Makkink models). The results showed that the hybrid ELM models (R2 = 0.973–0.999) all performed better than the standalone ELM model (R2 = 0.955–0.989) in four climatic regions in China. The estimation accuracy of the empirical models was relatively lower, with R2 of 0.822–0.887 and RMSE of 0.381–1.951 mm/d. The R2 values of PSO-ELM, GA-ELM and ABC-ELM models were 0.993, 0.986 and 0.981 and the RMSE values were 0.266 mm/d, 0.306 mm/d and 0.404 mm/d, respectively, indicating that the PSO-ELM model had the best performance. When setting Tmax, Tmin and RH as the model inputs, the PSO-ELM model presented better performance in the temperate continental zone (TCZ), subtropical monsoon region (SMZ) and temperate monsoon zone (TMZ) climate zones, with R2 of 0.892, 0866 and 0.870 and RMSE of 0.773 mm/d, 0.597 mm/d and 0.832 mm/d, respectively. The PSO-ELM model also performed in the mountain plateau region (MPZ) when only Tmax and Tmin data were available, with R2 of 0.808 and RMSE of 0.651 mm/d. All the three biological heuristic algorithms effectively improved the performance of the ELM model. Particularly, the PSO-ELM was recommended as a promising model realizing the high-precision estimation of daily ET0 with fewer meteorological parameters in different climatic zones of China.

Precipitation thresholds for iron oxides dissolution and the enhanced Eurasian aridity across the Mid-Pleistocene Transition: Evidence from loess deposits in subtropical China

The extensive loess deposits in southern China (‘Xiashu’ loess) are a valuable paleoclimatic archive in the subtropical monsoon region. We carried out a combined study of iron oxide mineralogy, pedostratigraphy, and magnetostratigraphy of three new loess sections in subtropical China. A detailed comparison of the iron oxides content of the Xiashu loess and the loess of the Chinese Loess Plateau reveals that the iron oxides of paleosol units in the Xiashu loess are partially dissolved. The estimated minimum mean annual precipitation levels required for the dissolution of maghemite, hematite, and goethite and the 95% confidence bounds are ~793 mm (679–907 mm), 728 mm (683–772 mm), and 941 mm (834–1048 mm) respectively. A regional comparison of the stratigraphy and magnetic susceptibility of the loess deposits in subtropical China reveals a general lack of correlation. The relatively low continuity of dust deposition combined with iron oxide dissolution is the main cause of the spatial inconsistency of the stratigraphy and magnetic properties. Magnetostratigraphic analysis reveals a basal age of 1.1 Ma for the loess deposits in subtropical China, which demonstrates that the intensification of aridification of the subtropical regions and a strengthened East Asian winter monsoon began by at least 1.1 Ma. Thus, the loess deposits in subtropical China provide terrestrial evidence from mid−low latitudes for global cooling and enhanced aridity across the Mid-Pleistocene Transition.

Oceanic drivers and empirical prediction of interannual rainfall variability in late summer over Northeast China

Northeast China (NEC) is located between the subtropical monsoon and temperate-frigid monsoon regions and exhibits two successive rainy seasons with different natures: the northeast cold vortex rainy season in early summer (May–June) and the monsoon rainy season in late summer (July–August). Summer rainfall over NEC (NECR) has a fundamental influence on society, yet its successful seasonal prediction remains a long-term scientific challenge to current dynamical models. The poor NECR prediction skill is partly attributed to the large NECR variability at both the interannual and interdecadal time scales. Here, we focus on the oceanic drivers of the late summer NECR variability and associated physical processes at interannual time scale. Then, we establish an empirical prediction model to predict the interannual variability of summer NECR at 1-month lead time (in June). The analysis of observations spanning 40 years (1963–2002) reveals three physically and synergistically influencing predictors of the late summer NECR interannual variability. Above-normal NECR is preceded in the previous spring by (a) warm sea surface temperature (SST) anomalies in the tropical northern Indian Ocean, (b) a positive thermal contrast tendency in the tropical West–East Pacific SST, and (c) a positive tendency of the North Atlantic tripolar SST. These precursors enhance the anomalous low-level anticyclone over the western North Pacific and southerly anomalies over NEC in late summer, which are beneficial to enhancing NECR. An empirical prediction model built on these three predictors achieves a forecast temporal correlation coefficient (TCC) skill of 0.72 for 1961–2019, and a 17-year (2003–2019) independent forecast shows a significant TCC skill of 0.70. The skill is substantially higher than that of five state-of-the-art dynamical models and their ensemble mean for 1979–2019 (TCC = 0.24). These results suggest that the proposed empirical model is a meaningful approach for the prediction of NECR, although the dynamical prediction of NECR has considerable room for improvement.

Temporal variations and evaporation control effect of the stable isotope composition of precipitation in the subtropical monsoon climate region, Southwest China

Stable hydrogen and oxygen isotopes in precipitation, which are sensitive to climate change and the water cycle, are widely used as natural tracers to investigate hydrological processes and paleoclimate reconstruction. High resolution event-based precipitation sampling was conducted in Guilin, a subtropical monsoon climate region in Southwest China, from 2010 to 2016 to identify the temporal variability of stable isotopes of precipitation and its dominant meteorological factors. The results showed that the stable isotopes of precipitation exhibited significant seasonal variability, with lower values in the wet season and higher values in the dry season, reflecting the changes in the character of precipitation in response to seasonal variability of the moisture sources and atmospheric dynamics. δ18O values were significantly negatively correlated with temperature and potential evapotranspiration (ET0) on the daily and monthly timescales; however, there was no significant correlation between monthly δ18O and the amount of rainfall. Multivariate regression analysis showed that when temperature, precipitation amount and ET0 were considered, 39% of the variability of the monthly oxygen isotope composition of precipitation was explained. Monthly mean temperature had a higher covariation with precipitation δ18O, indicating that the variations of precipitation isotope were more dependent on temperature, but not substantially dependent on the amount effect of rainfall. Howerver, the main influence of meteorological factors on the isotopic variations of precipitation varied seasonally. Temperature strongly influenced the isotopic composition of precipitation in summer, while the amount effect was prominent due to the enhanced convective activity characterized by more depleted δ18O values. Although evapotranspiration is a minor contributor of precipitation isotope variability, the impact of evapotranspiration on the enrichment of precipitation isotopes in autumn is a substantial control and should be considered, which makes a major contribution to compensate for the depletion in heavy isotopes of rainfall. The non-linear relationship between d-excess and ET0 was attributed to the variable contribution of large-scale convective moisture and local evaporation, as well as water vapor transfer processes. The response of precipitation stable isotopes to convective events was characterized by distinct stage patterns, associated with the water vapor sources and physical processes during rainout. The significant depletion of precipitation δ18O values during convective events was not due to the ‘amount effect’, but due to large-scale convection activity. These findings provide further insight into intraevent-scale isotopic variations associated with organized convection and their key influencing factors, which ultimately improves our interpretation of the paleoclimate records in subtropical monsoon regions.

Changes in the Impacts of Topographic Factors, Soil Texture, and Cropping Systems on Topsoil Chemical Properties in the Mountainous Areas of the Subtropical Monsoon Region from 2007 to 2017: A Case Study in Hefeng, China.

Understanding the spatial pattern of soil chemical properties (SCPs) together with topological factors and soil management practices is essential for land management. This study examines the spatial changes in soil chemical properties and their impact on China’s subtropical mountainous areas. In 2007 and 2017, 290 and 200 soil samples, respectively, were collected in Hefeng County, a mountainous county in central China. We used descriptive statistics and geostatistical methods, including ANOVA, semivariance, Moran’s I, and fractal dimensions, to analyze the characteristics and spatial autocorrelation changes in soil organic matter (OM), available phosphorus (AP), available potassium (AK), and pH value from 2007 to 2017. We explored the relationship between each SCP and the relationship between SCPs with topographic parameters, soil texture, and cropping systems. The results show that the mean value of soil OM, AP, AK, and pH in Hefeng increased from 2007 to 2017. The spatial variation and spatial dependency of each SCP in 2007, excluding AP and AK in 2007, were higher than in 2017. The soil in areas with high topographic relief, profile curvature, and planform curvature had less AP, AK, and pH. Soil at higher elevation had lower OM (r = −0.197, p < 0.01; r = −0.334, p < 0.01) and AP (r = −0.043, p < 0.05; r = −0.121, p < 0.05) and higher AK (r = −0.305, p < 0.01; r = 0.408, p < 0.01) in 2007 and 2017. Soil OM and AK in 2007 were significantly (p < 0.05) correlated with soil texture (p < 0.05). In contrast, oil AP and soil pH in 2007 and all SCPs in 2017 were poorly correlated with soil texture. The cropping systems played an important role in affecting all SCPs in 2007 (p < 0.01), while they only significantly affected AK in 2017 (p < 0.05). Our findings demonstrate that both topological factors, that is, the changes in cropping management and the changes in acid rain, impact soil chemical properties. The local government should place more focus on reducing soil acid amounts, soil AP content, and soil erosion by improving water conservancy facilities.

Effects of the leaf functional traits of coniferous and broadleaved trees in subtropical monsoon regions on PM2.5 dry deposition velocities

Plants can intercept airborne particulate matter through deposition. Different types of plants exhibit different functional leaf traits, which can affect the dry deposition velocity (Vd). However, the most crucial leaf traits of coniferous and broadleaved trees remain unidentified. In this study, we selected 18 typical plants from the subtropical monsoon regions, where PM2.5 (fine particulate matter with a diameter of ≤2.5 μm) concentrations are relatively high, and classified them into coniferous and broadleaved categories. Subsequently, we analyzed the relationships between Vd and leaf surface free energy (SFE), single leaf area (LAs), surface roughness (SR), specific leaf area (SLA), epicuticular wax content (EWC), and width-to-length ratio (W/L). The results indicated that most coniferous trees exhibited a high Vd. The correlation analysis revealed that SFE, SR, LAs, and W/L were the key factors that affected the Vd of all the tested species. SFE and SLA had the strongest influence on the Vd of broadleaved trees, whereas LAs and SLA had the strongest effect on that of coniferous trees. Most coniferous trees had a high SLA, which can reduce water loss and hinder particle deposition. However, the stiff leaves of coniferous trees fluttered less, resulting in a larger leaf area that enhanced the capture efficiency. The leaf structure of broadleaved trees is more flexible, resulting in erratic flutter, which may impede deposition and lead to high resuspension. Coniferous and broadleaved trees may have different dominant leaf traits that affect particle deposition.

Effects of water vapor source and local environmental factors on the hydrogen and oxygen isotopic compositions of precipitation in Huitong, Hunan Province, China

Deuterium (D) and oxygen-18 (18O) are common environmental tracers in water. Understanding the isotopic compositions of precipitation is necessary for further studies on local and global water cycling processes. To reveal the mechanism of isotopic compositions of precipitation in subtropical monsoon region in response to environmental changes, we collected 49 precipitation samples and recorded related environmental factors from May 2017 to August 2019 in Huitong field station of Chinese Academy of Sciences in Hunan Province. We analyzed the temporal variations in D and 18O values in precipitation and analyzed the influence of water vapor source and local environmental factor on stable isotopic compositions of precipitation. The local meteoric water line was established as δD=(7.45±0.17)δ18O+(10.10±1.25) (R2=0.93, P<0.01), the slope of which was slightly lower than China's meteoric water line and the global meteoric line. The D and 18O values of precipitation samples were closely coupled with local meteorological conditions and dominant moisture sources. The 18O and D contents were depleted during summer monsoon season but enriched during winter monsoon season. During the summer monsoon and post-monsoon seasons, precipitation in this area came mainly from the Bay of Bengal, the South China Sea, and the West Pacific at three different types of air pressure, which lead to the similarity of the D-excess value of the precipitation to global average. The lower intercept of meteoric water line and the higher D-excess value for precipitation during the winter monsoon season resulted from moisture from remote westerly air masses, degenerated tropical marine air masses from the Bay of Bengal, and inland moisture in the pre-monsoon period, which were also affected by local environmental factors.

Recognition of Changes in Air and Soil Temperatures at a Station Typical of China’s Subtropical Monsoon Region (1961–2018)

Trends in soil temperature are important but rarely reported indicators of climate change. Based on daily air and soil temperatures (depth: 0, 20, 80, and 320 cm) recorded at the Nanchang Weather Station (1961–2018), this study investigated the variation trend, abrupt changes, and years of anomalous annual and seasonal mean air and soil temperatures. The differences and relationships between annual air and soil temperatures were also analyzed. The results showed close correlations between air temperature and soil temperature at different depths. Annual and seasonal mean air and soil temperatures mainly displayed significant trends of increase over the past 58 years, although the rise of the mean air temperature and the mean soil temperature was asymmetric. The rates of increase in air temperature and soil temperature (depth: 0, 20, and 80 cm) were most obvious in spring; the most significant increase in soil temperature at the depth of 320 cm was in summer. Mean soil temperature displayed a decreasing trend with increasing soil depth in both spring and summer. Air temperature was lower than the soil temperature at depths of 0 and 20 cm but higher than the soil temperature at depths of 80 and 320 cm in spring and summer. Mean ground temperature had a rising trend with increasing soil depth in autumn and winter. Air temperature was lower than the soil temperature at all depths in autumn and winter. Years with anomalously low air temperature and soil temperature at depths of 0, 20, 80, and 320 cm were relatively consistent in winter. Years with anomalous air and soil temperatures (depths: 0, 20, and 80 cm) were generally consistent; however, the relationship between air temperature and soil temperature at 320 cm depth was less consistent. The findings provide a basis for understanding and assessing climate change impact on terrestrial ecosystems.

Cold and heat climatic variations reduce indigenous goat birth weight and enhance pre-weaning mortality in subtropical monsoon region of China.

The subtropical monsoon climate characterized by high or low temperature and humidity can induce cold and heat stress for newborn animals, which results in adverse effect on birth weight and even pre-weaning mortality. However, this early growth performance on indigenous goats is affected by cold and heat climatic environments and is still unclear in subtropical climate. In this study, we continuously measured (July 2011 to June 2016) the birth weight and mortality of an indigenous goat species (n = 530), and collected temperature, humidity, temperature-humidity index (THI) in original farming area, Chongqing, southwest China. As the result, the mean birth weights in cold months (January and February, mean temperature < 10 °C and THI < 56) and heat months (July and August, mean temperature > 29 °C and THI > 76) were significantly lower (P < 0.05) compared to the other months (June and October, mean temperature = 16~25 °C and THI = 61~75). Meanwhile, the birth weight was positively correlated (P < 0.01) with gestational THI from November to May, and was negatively correlated (P < 0.01) with those parameters from June to October, respectively. The maximum pre-weaning mortality, occurring in the 1st month after birth, is 16.17 ± 2.56%. However, when the birth weight was 20% lower than annual average (2.09 ± 0.54 kg), the mortality was significantly enhanced (P < 0.01) to 46%. In addition, cold and heat climates respectively enhanced mortality in the 1st month and 2nd~4th months after birth. In conclusion, annually chronic heat and cold climates could play important roles in lowering birth weight and their survival in subtropical monsoon region. Low birth weight and cold temperature play critical role to contribute the advent of higher mortality after birth. Our results potentially provide the appropriate ranges of temperature (16~26 °C) and THI (61~75) as pregnant goat and kids raising condition to avoid these negative influences.

Silting patterns in the reservoirs of small‐ and medium‐sized earthen check dams in humid subtropical monsoon regions

ABSTRACTSilting of reservoirs is a ubiquitous process whenever water is impounded. Despite substantial work on the rates of silting, the spatial pattern of silting in reservoirs is not clearly understood. While it is anticipated that the variability of silting increases with decreasing reservoir size, not much is known about siltation in subtropical humid regions affected by monsoon rainfall. This paper presents the initial results of geomorphic analysis of six earthen check dams in the Shiwalik foothills of the Himalayas (India) in areas that are inhabited by high proportions of disempowered populations. These check dams include three small‐sized dams (Dhamala‐II, Rel Majra and Sukhomajri‐II) and three medium‐sized dams (Bunga‐I, Parachh‐II and Siswan). Field data were collected from each reservoir. The methods used included spatial interpolations of bed depth and silt thickness in each reservoir, Structure from Motion photogrammetry to extract multiple channel cross‐sections from photographic scans along tributary mouths, texture analysis of bed and bank materials, and visual observations of hill slopes around the check dams. Based on this study, silt tended to concentrate either in the middle portion of the reservoir or near the dam; however, silt accumulation did not always occur along the dam or in the deepest portion of the reservoirs. Areas located downstream from these check dams are heavily used for various human activities and the channel network has almost been eliminated. While these earthen check dams may be cost‐effective tools for water conservation in economically marginalized areas, if abandoned, these structures may pose a physical hazard to downstream communities. © 2019 John Wiley &amp; Sons, Ltd. © 2019 John Wiley &amp; Sons, Ltd.

Climatic and environmental controls on stable isotopes in atmospheric water vapor near the surface observed in Changsha, China

Continuous measurements were made of isotopic compositions in atmospheric water vapor (δv) and in atmospheric precipitation (δp) near the surface in the subtropical monsoon region (Changsha, China) from October 2014 to March 2017 to investigate the change characteristics of vapor isotopes and their interactions with precipitation isotopes. On a diurnal time scale, the δ18Ov values were more negative in the daytime and more positive at night, and the change in dv was reversed during non-rainy days; however, the δ18Ov values were more positive in the daytime and more negative at night, and the variation in dv was not significant during rainy days. On a seasonal time scale, affected by distinctive moisture sources, the vapor isotopes had obvious seasonal variations, with higher δ18Ov and dv values occurring in cold seasons than in warm seasons. There were generally consistent and significant negative linear relationships of dv with temperature and absolute humidity, but the linear relationships between δ18Ov and meteorological factors were variable on the different time scales, which was closely associated with the local weather conditions on the short time scales from diurnal to intra-seasonal and movements of air masses with distinct thermodynamic properties on seasonal and sometimes intra-seasonal time scales. Although the change trend of daily δ18Ov closely approximated that of δ18Op, δ18Op experienced significant relative enrichment compared to δ18Ov, with an average enrichment of 9.18‰. Overall, the isotopic compositions of atmospheric water vapor were in equilibrium with those of precipitation while rainfall events occurred, except for those in the cold season in 2014, and when tracing short-duration weather events, δ18Ov provided more details and information related to weather processes than δ18Op.

Grassland Carbon Budget and Its Driving Factors of the Subtropical and Tropical Monsoon Region in China During 1961 to 2013

The southern grasslands are an integral part of the grassland ecosystems of China and play an essential role in the terrestrial carbon cycle of the country. We reproduced the spatiotemporal dynamics of the carbon budget of southern grasslands from 1961 to 2013 using the Terrestrial Ecosystem Model and our results showed that the annual carbon budget varied from −8.12 to 6.16 Tg C y−1 with an annual average of 0.45 Tg C y−1 during the study period. Overall, southern grasslands acted as a weak carbon sink and sequestrated 23.83 Tg C from 1961 to 2013. At the seasonal scale, southern grasslands acted as a carbon sink in wet seasons but as a carbon source in dry seasons. During the study period, temperature and precipitation were the main factors driving carbon budget dynamics at the seasonal scale, while soil moisture was the main driving factor at the annual scale. Over the entire study region, 71.81% of the area switched to being a carbon sink while only 5.90% remained stable and the strong carbon sinks were mainly found in the southern, northern and western areas of the southern grasslands.

Carbon accumulation in Dahu Swamp in the eastern Nanling Mountains (south China) and its implications for hydroclimatic variability over the past 47 000 years

Wetlands act as persistent natural carbon sinks over long time scales. Understanding the response of these carbon reservoirs to climate change is critical to assessing potential climate feedbacks. We conducted a study of an 860‐cm‐long sediment core in Dahu Swamp in south China to determine how the carbon accumulation rate (CAR) has varied as a function of palaeohydrology and palaeoclimate over the past 47 000 years. From an orbital time scale, our results show that the CAR in Dahu Swamp is relatively low in the wet periods of Marine Isotope Stage 3 (MIS 3) (mean: 46.7 gC m−2 a−1) and MIS 1 (mean: 28.2 gC m−2 a−1), compared to the dry periods of MIS 2 (mean: 59.9 gC m−2 a−1). At centennial and millennial scales, the highest CARs of Dahu Swamp mainly occur in organic‐rich silt or clay (gyttja) layers, which correspond to the relatively dry climate (e.g. c. 48 000–41 000, c. 33 000–32 000, c. 15 800–14 900 and c. 4400–4250 cal. a BP). The CAR of Dahu Swamp is mainly controlled by local hydrological variations that are closely related to the East Asian summer monsoon (EASM) intensity, which may be co‐influenced by orbitally induced summer insolation forcing and internal feedback processes (e.g. Atlantic Meridional Overturning Circulation and El Niño/Southern Oscillation). Based on comparison with the CARs in monsoonal regions of China, we consider that precipitation may be the key factor for wetland CAR in EASM areas, whereas temperature is more important in Qinghai–Tibetan Plateau regions under Indian summer monsoon influence. The CAR of Dahu Swamp provides valuable records of wetland carbon accumulation dynamics in subtropical monsoon regions, which contradict the traditional patterns in global northern wetlands.

Two types of summertime heating over Asian large-scale orography and excitation of potential-vorticity forcing II. Sensible heating over Tibetan-Iranian Plateau

Based on analysis and simulation, the interaction of thermal forcing between the Tibetan Plateau (TP) and Iranian Plateau (IP) in summer is investigated. Associated influences on water vapor transport in the Asian subtropical monsoon region and the formation of a cold center in the lower stratosphere over Eurasia are also investigated. Results show that surface sensible heating (SH) over the two plateaus not only have mutual influences but also feedback to each other. SH over the IP can reduce the SH and increase the LH over the TP, whereas the SH over the TP can increase surface heating over the IP, thereby reaching quasi-equilibrium among the SH and LH over the TP, IP SH and atmosphere vertical motion. Therefore, the so-called Tibetan-Iranian Plateau coupling system (TIPS) is constructed, which influences atmosphere circulation. In the TIPS system, interaction between surface SH and LH over the TP plays a leading role. SH of the IP and TP influences on other regions not only have superimposed effects but also mutually offset. Accounting for contributions to the convergence of water vapor transport in the Asian subtropical monsoon region, TP SH contributes more than twice that of the IP. The combined influence of SH over TP and IP represents the major contribution to the convergence of water vapor transport in that region. In addition, the heating effect of TIPS increases the upper tropospheric temperature maximum and lifts the tropopause, cooling the lower stratosphere. Combined with large-scale thermal forcing of the Eurasian continent, the TIPS produces a strong anticyclonic circulation and the South Asian High that warms the upper troposphere and cools the lower stratosphere, thereby affecting regional and global weather and climate.

Regional Climate Modeling of Vegetation Feedbacks on the Asian–Australian Monsoon Systems

Abstract This study explores the hypothesis that subtropical and tropical monsoon regions exhibit unique responses to vegetation feedbacks. Using the Community Climate System Model (CCSM), M. Notaro et al. concluded that reduced vegetation cover led to an earlier subtropical Chinese monsoon and a delayed, weaker tropical Australian monsoon, yet significant climate and leaf area index (LAI) biases obfuscated the hypothesis’s reliability. To address these concerns, the Regional Climate Model, version 4 (RegCM4), likewise coupled to the Community Land Model but with “observed” LAI boundary conditions, is applied across China and Australia. The model matches the observed dominance of crops, grass, and evergreen trees in southern China and grass and shrubs in northern Australia. The optimal model configuration is determined and applied in control runs for 1960–2013. Monsoon region LAI is modified in a RegCM4 ensemble, aimed at contrasting vegetation feedbacks between tropical and subtropical regions. Greater LAI supports reductions in albedo, temperature, wind speed, boundary layer height, ascending motion, and midlevel clouds and increases in diurnal temperature range (DTR), wind stress, evapotranspiration (ET), specific humidity, and low clouds. In response to greater LAI, rainfall is enhanced during Australia’s pre-to-midmonsoon season but not for China. Modified LAI leads to dramatic changes in the temporal distribution and intensity of Australian rain events. Heterogeneous responses to biophysical feedbacks include amplified impacts (e.g., increased ET and DTR) across China’s croplands and Australia’s shrublands. Inconsistencies between China’s monsoonal responses in the present RegCM4 study and prior CCSM study of M. Notaro et al. are attributed to CCSM’s excessive forest cover and LAI, exaggerated roughness mechanism, and deficient ET response.