Xiaodong Wu

Environmental controls on soil organic carbon and nitrogen stocks in the high-altitude arid western Qinghai-Tibetan Plateau permafrost region

While permafrost in the circum-Artic has great influence on soil organic carbon (SOC) and total nitrogen (TN) stocks, this might not be the case in low-latitude arid permafrost regions. We test this hypothesis in the western Qinghai-Tibetan Plateau (QTP) permafrost region. Fifty-nine soil profiles were analyzed to examine the SOC and TN distribution and the controlling factors in western QTP, which is a desert steppe ecoregion. Mean stocks of SOC (5.29 kg m−2) and TN (0.56 kg m−2) for the top 200 cm in this area were lower than those of the east QTP and circum-Arctic regions. The SOC and TN stocks under vegetative cover with permafrost conditions were significantly higher than those of desert conditions. The SOC and TN stocks for the layers of different depths were related to the content of clay, silt, and moisture. Although the active layer thickness (ALT) had a significant negative correlation to soil moisture, the ALT explained little or no variance in the SOC and TN stocks. The results showed that in the vast permafrost regions of the western QTP, the SOC and TN stocks are very low, and the main controlling factors for the SOC and TN are soil texture, moisture, and vegetation type. The SOC pool in this area may not be as vulnerable to degradation associated with climate warming and thus not emit greenhouse gases at the same rate as other permafrost regions. The different response of the SOC in this region should be considered in carbon cycling models.

Vertical patterns and controls of soil nutrients in alpine grassland: Implications for nutrient uptake

Vertical patterns and determinants of soil nutrients are critical to understand nutrient cycling in high-altitude ecosystems; however, they remain poorly understood in the alpine grassland due to lack of systematic field observations. In this study, we examined vertical distributions of soil nutrients and their influencing factors within the upper 1m of soil, using data of 68 soil profiles surveyed in the alpine grassland of the eastern Qinghai-Tibet Plateau. Soil organic carbon (SOC) and total nitrogen (TN) stocks decreased with depth in both alpine meadow (AM) and alpine steppe (AS), but remain constant along the soil profile in alpine swamp meadow (ASM). Total phosphorus, Ca2+, and Mg2+ stocks slightly increased with depth in ASM. K+ stock decreased with depth, while Na+ stock increased slightly with depth among different vegetation types; however, SO42- and Cl- stocks remained relatively uniform throughout different depth intervals in the alpine grassland. Except for SOC and TN, soil nutrient stocks in the top 20cm soils were significantly lower in ASM compared to those in AM and AS. Correlation analyses showed that SOC and TN stocks in the alpine grassland positively correlated with vegetation coverage, soil moisture, clay content, and silt content, while they negatively related to sand content and soil pH. However, base cation stocks revealed contrary relationships with those environmental variables compared to SOC and TN stocks. These correlations varied between vegetation types. In addition, no significant relationship was detected between topographic factors and soil nutrients. Our findings suggest that plant cycling and soil moisture primarily control vertical distributions of soil nutrients (e.g. K) in the alpine grassland and highlight that vegetation types in high-altitude permafrost regions significantly affect soil nutrients.

Modeling ground surface temperature by means of remote sensing data in high-altitude areas: test in the central Tibetan Plateau with application of moderate-resolution imaging spectroradiometer Terra/Aqua land surface temperature and ground-based infrared radiometer

Abstract Ground surface temperature (GST) is a crucial parameter of surface energy budgets and controls the thermal state of the active layer and permafrost in permafrost regions. However, with limited observed datasets available for the Tibetan Plateau, a greater bias existed for GST products from remote sensing data. Model validation (the whole year 2012 data) showed that all three models performed well, with a determination ( R 2 ), mean error, mean absolute error, and root mean squared error of 0.86 to 0.93, − 0.61 to 1°C, 2.28 to 3.06°C, and 2.96 to 3.83°C, respectively. The model established by observations of Terra and Aqua satellites during the daytime and nighttime showed the highest correlation, with R 2 values ranging from 0.91 to 0.93, as well as the lowest MAE and RMSE of 2.28 to 2.42 and 2.96 to 3.05°C, respectively. However, the application of this model substantially reduced the available pixels. Models established with the automatic weather station observations at the satellite overpass times performed better than those using the moderate-resolution imaging spectroradiometer land surface temperature observations. The results might be useful to produce a more reliable dataset for monitoring and modeling permafrost changes.

Modeling permafrost properties in the Qinghai-Xizang (Tibet) Plateau

Water and heat dynamics in the active layer at a monitoring site in the Tanggula Mountains, located in the permafrost region of the Qinghai-Xizang (Tibet) Plateau (QXP), were studied using the physical-process-based COUPMODEL model, including the interaction between soil temperature and moisture under freeze-thaw cycles. Meteorological, ground temperature and moisture data from different depths within the active layer were used to calibrate and validate the model. The results indicate that the calibrated model satisfactorily simulates the soil temperatures from the top to the bottom of the soil layers as well as the moisture content of the active layer in permafrost regions. The simulated soil heat flux at depths of 0 to 20 cm was consistent with the monitoring data, and the simulations of the radiation balance components were reasonable. Energy consumed for phase change was estimated from the simulated ice content during the freeze/thaw processes from 2007 to 2008. Using this model, the active layer thickness and the energy consumed for phase change were predicted for future climate warming scenarios. The model predicts an increase of the active layer thickness from the current 330 cm to approximately 350–390 cm as a result of a 1–2°C warming. However, the effect active layer thickness of more precipitation is limited when the precipitation is increased by 20%–50%. The COUPMODEL provides a useful tool for predicting and understanding the fate of permafrost in the QXP under a warming climate.

Some Characteristics of Permafrost and Its Distribution in the Gaize Area on the Qinghai—Tibet Plateau, China

ABSTRACT An investigation of permafrost in the Gaize area in the west Qinghai—Tibet Plateau in China was conducted in October and November of 2010 and 2011. It was found that mean annual ground temperature was >-1 °C with a permafrost thickness of <60 m in the widespread alpine steppe below an altitude of 5400 m a.s.l. The active layer thickness was usually deeper than 3 m with a maximum of about 5.7 m. Overall, the ice/water content of the top 15 m of frozen soil was usually <10%. The altitudinal limit of permafrost in the alpine steppe was about 5100, 5000, and 4950 m a.s.l. on south-, east-west-, and north-facing slopes, respectively. A permafrost map was constructed using the ARCGIS platform and topographic information from the TOPO 30 digital elevation model. Statistical analysis of the map revealed that permafrost is primarily distributed in the hilly/mountainous areas of Gaize, covering 51% of the study area. The area of permafrost in this map is considerably less than in the Permafrost Map of the Qinghai—Tibet Plateau drawn in 1996. Further analysis revealed that the large difference between the two maps could be attributed to both errors in the earlier mapping method and permafrost degradation.

Soil organic matter fractions under different vegetation types in permafrost regions along the Qinghai-Tibet Highway, north of Kunlun Mountains, China

As a key attribute of soil quality, soil organic matter (SOM) and its different fractions play an important role in regulating soil nutrient cycling and soil properties. This study evaluated the soil carbon (C) and nitrogen (N) concentrations in different SOM fractions (light- and heavy fractions, microbial biomass) under different vegetation types and analyzed their influencing factors in continuous permafrost regions along the Qinghai-Tibet Highway in the North of Kunlun Mountains, China. Soil samples were collected in pits under four vegetation types — Alpine swamp meadow (ASM), Alpine meadow (AM), Alpine steppe (AS) and Alpine desert (AD) — at the depth of 0-50 cm. The vegetation coverage was the highest at ASM and AM, followed by AS and AD. The results indicated that the concentrations of light fraction carbon (LFC) and nitrogen (LFN), and microbial biomass carbon (MBC) and nitrogen (MBN) decreased as follows: ASM >AM >AS >AD, with the relatively stronger decrease of LFC, whereas the heavy fraction carbon (HFC) and nitrogen (HFN) concentrations were lower in AS soils than in the AD soils. The relatively higher proportions of LFC/SOC and MBC/SOC in the 0-10 cm depth under the ASM soils are mainly resulted from its higher substrate input and soil moisture content. Correlation analysis demonstrated that aboveground biomass, soil moisture content, soil organic carbon (SOC) and total nitrogen (TN) positively correlated to LFC, LFN, HFC, HFN, MBC and MBN, while pH negatively correlated to LFC, LFN, HFC, HFN, MBC and MBN. There was no relationship between active layer thickness and SOM fractions, except for the LFC. Results suggested that vegetation cover, soil moisture content, and SOC and TN concentrations were significantly correlated with the amount and availability of SOM fractions, while permafrost had less impact on SOM fractions in permafrost regions of the central Qinghai-Tibet Plateau.

Numerical Modeling of the Active Layer Thickness and Permafrost Thermal State Across Qinghai‐Tibetan Plateau

The dynamics of permafrost (including the permafrost thermal state and active layer thicknesses (ALT)) across the Qinghai-Tibetan Plateau (QTP) have not been well understood on a large scale. Here, we simulate the ALT and permafrost thermal state using the Geophysical Institute Permafrost Lab Version 2 (GIPL2) model across the QTP. Based on the single-point simulations, the model is upscaled to the entire QTP. The upscaled model is validated with five investigated regions (IRs), including Wenquan (WQIR), Gaize (GZIR), Aerjin (AEJIR), Xikunlun (XKLIR) and Qinghai-Tibetan highway (G109IR). The results show that the modified GIPL2 model improves the accuracy of the permafrost thermal state simulations. Due to our simulated results on the QTP, the average ALT is of 2.30 m (2.21 - 2.40 m). The ALT decreases with an increase in the altitude and decreases from the southeast to the northwest. The ALT is thin in the central QTP, but it is thick in the high-elevation mountain areas and some areas surrounding glaciers and lakes. The largest ALT is found in the border areas between permafrost and seasonally frozen ground regions. The simulated results of the MAGT (the mean annual ground temperature) indicate that most of the permafrost is sub-stable, which is sensitive to climate warming. The simulated results would be of great significance on assessing the impacts of permafrost dynamics on local hydrology, ecology, and engineering construction.

Modeling Hydrothermal Transfer Processes in Permafrost Regions of Qinghai-Tibet Plateau in China

Hydrothermal processes are key components in permafrost dynamics; these processes are integral to global warming. In this study the coupled heat and mass transfer model for (CoupModel) the soil-plant-atmosphere-system is applied in high-altitude permafrost regions and to model hydrothermal transfer processes in freeze-thaw cycles. Measured meteorological forcing and soil and vegetation properties are used in the CoupModel for the period from January 1, 2009 to December 31, 2012 at the Tanggula observation site in the Qinghai-Tibet Plateau. A 24-h time step is used in the model simulation. The results show that the simulated soil temperature and water content, as well as the frozen depth compare well with the measured data. The coefficient of determination (R2) is 0.97 for the mean soil temperature and 0.73 for the mean soil water content, respectively. The simulated soil heat flux at a depth of 0–20 cm is also consistent with the monitored data. An analysis is performed on the simulated hydrothermal transfer processes from the deep soil layer to the upper one during the freezing and thawing period. At the beginning of the freezing period, the water in the deep soil layer moves upward to the freezing front and releases heat during the freezing process. When the soil layer is completely frozen, there are no vertical water exchanges between the soil layers, and the heat exchange process is controlled by the vertical soil temperature gradient. During the thawing period, the downward heat process becomes more active due to increased incoming shortwave radiation at the ground surface. The melt water is quickly dissolved in the soil, and the soil water movement only changes in the shallow soil layer. Subsequently, the model was used to provide an evaluation of the potential response of the active layer to different scenarios of initial water content and climate warming at the Tanggula site. The results reveal that the soil water content and the organic layer provide protection against active layer deepening in summer, so climate warming will cause the permafrost active layer to become deeper and permafrost degradation.

Spatiotemporal changes of freezing/thawing indices and their response to recent climate change on the Qinghai–Tibet Plateau from 1980 to 2013

The spatial and temporal changes of the ground surface freezing indices (GFIs), ground surface thawing indices (GTIs), air freezing indices (AFIs), and air thawing indices (ATIs) in permafrost and seasonally frozen ground regions of the Qinghai–Tibet Plateau (QTP) were analyzed based on the daily ground surface and air temperatures from 69 meteorological stations using the Mann–Kendall test and Sen’s slope estimate. The spatial patterns of the freezing indices (FIs) and thawing indices (TIs) are nearly negatively correlated. On the annual scale, the GFI and GTI are greater than the AFI and ATI in both permafrost and seasonally frozen ground regions. The marked upward and downward trends have been observed for the time series of TI and FI, respectively, since 1998 on the QTP. Moreover, GFI and AFI decrease more significantly in permafrost regions than in seasonally frozen ground regions; the increasing rate of GTI and ATI in the seasonally frozen ground regions is greater than that in the permafrost regions. In permafrost regions, the downward trend of FI is greater than the upward trend of TI. However, the upward trend of TI shows a more drastic change than the FI in the seasonally frozen ground regions. The results indicate that the warming in the permafrost regions is more pronounced in winter than in the other seasons. The summer warming is more pronounced than the other seasons in the seasonally frozen ground regions. The decreasing rate of AFI and GFI increases as the altitude rises, while they decrease with increasing ATI. The average decreasing rate of GFI is greater than that of the AFI in different altitudinal zones. The greatest decrease of FI occurs in permafrost regions in the hinterland of the QTP, which indicates the dominant winter warming in this region. The downward trend of FI and upward trend of TI are responsible for the reported permafrost degradation on the QTP.

Soil moisture and texture primarily control the soil nutrient stoichiometry across the Tibetan grassland

Soil nutrient stoichiometry and its environmental controllers play vital roles in understanding soil-plant interaction and nutrient cycling under a changing environment, while they remain poorly understood in alpine grassland due to lack of systematic field investigations. We examined the patterns and controls of soil nutrients stoichiometry for the top 10cm soils across the Tibetan ecosystems. Soil nutrient stoichiometry varied substantially among vegetation types. Alpine swamp meadow had larger topsoil C:N, C:P, N:P, and C:K ratios compared to the alpine meadow, alpine steppe, and alpine desert. In addition, the presence or absence of permafrost did not significantly impact soil nutrient stoichiometry in Tibetan grassland. Moreover, clay and silt contents explained approximately 32.5% of the total variation in soil C:N ratio. Climate, topography, soil properties, and vegetation combined to explain 10.3-13.2% for the stoichiometry of soil C:P, N:P, and C:K. Furthermore, soil C and N were weakly related to P and K in alpine grassland. These results indicated that the nutrient limitation in alpine ecosystem might shifts from N-limited to P-limited or K-limited due to the increase of N deposition and decrease of soil P and K contents under the changing climate conditions and weathering stages. Finally, we suggested that soil moisture and mud content could be good predictors of topsoil nutrient stoichiometry in Tibetan grassland.