Yongge Li

Dr. Yongge Li


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 January 2022 in Remote Sensing
Verified
Journal Article
Open access
PDF file
YLYongge Li
Yongge Li
WLWei Liu
Wei Liu
Feng QiFeng Qi
Feng Qi
Meng ZhuMeng Zhu
Meng Zhu
Linshan YangLinshan Yang
Linshan Yang
Jutao ZhangJutao Zhang
Jutao Zhang
Ecosystem services in arid inland regions are significantly affected by climate change and land use/land cover change associated with agricultural activity. However, the dynamics and relationships of ecosystem services affected by natural and anthropogenic drivers in inland regions are still less understood. In this study, the spatiotemporal patterns of ecosystem services in the Hexi Region were quantified based on multiple high-resolution datasets, the InVEST model and the Revised Wind Erosion Equation (RWEQ) model. In addition, the trade-offs and synergistic relationships among multiple ecosystem services were also explored by Pearson correlation analysis and bivariate spatial autocorrelation, and redundancy analysis (RDA) was also employed to determine the environmental drivers of these services and interactions. The results showed that most ecosystem services had a similar spatial distribution pattern with an increasing trend from northwest to southeast. Over the past 40 years, ecosystem services in the Hexi Region have improved significantly, with the water retention and soil retention increasing by 87.17 × 108 m3 and 287.84 × 108 t, respectively, and the sand fixation decreasing by 369.17 × 104 t. Among these ecosystem services, strong synergistic relationships were detected, while the trade-offs were found to be weak, and showed significant spatial heterogeneity in the Hexi Region. The spatial synergies and trade-offs in the Qilian Mountains were 1.02 and 1.37 times higher than those in the Hexi Corridor, respectively. Human activities were found to exacerbate the trade-offs between ecosystem services by increasing water consumption in the Hexi Corridor, with the exception of carbon storage. In particular, there were significant tradeoffs between food production and water retention, and between soil retention and habitat quality in the oases of the Hexi Corridor, which is affected by rapid population growth and cropland expansion. Additionally, precipitation, temperature and vegetation cover in the Qilian Mountains have increased significantly over the past four decades, and these increases significantly contributed to the enhancements in water retention, carbon storage, habitat quality, soil retention and food production. Nevertheless, the amount of sand fixation significantly decreased, and this was probably associated with the reduction in wind speed over the past four decades. Our results highlighted the importance of climate wetting and water resource management in the enhancement of ecosystem services and the mitigation of food production trade-offs for arid inland regions.

4 December 2021 in Forests
Verified
Journal Article
Open access
PDF file
WLWei Liu
Wei Liu
Meng ZhuMeng Zhu
Meng Zhu
YLYongge Li
Yongge Li
Jutao ZhangJutao Zhang
Jutao Zhang
Linshan YangLinshan Yang
Linshan Yang
Chengqi ZhangChengqi Zhang
Chengqi Zhang
Soil organic carbon (SOC) simply cannot be managed if its amounts, changes and locations are not well known. Thus, evaluations of the spatio-temporal dynamics of SOC stock under future climate change are crucial for the adaptive management of regional carbon sequestration. Here, we evaluated the dynamics of SOC stock to a 60 cm depth in the middle Qilian Mountains (1755–5051 m a.s.l.) by combining systematic measurements from 138 sampling sites with a machine learning model. Our results reveal that the combination of systematic measurements with the machine learning model allowed spatially explicit estimates of SOC change to be made. The average SOC stock in the middle Qilian Mountains was expected to decrease under future climate change, while the size and direction of SOC stock changes seemed to be elevation-dependent. Specifically, in comparison with the 2000s, the mean annual precipitation was projected to increase by 18.37, 19.80 and 30.80 mm, and the mean annual temperature was projected to increase by 1.9, 2.4 and 2.9 °C under the Representative Concentration Pathway (RCP) 2.6 (low-emissions pathway), RCP4.5 (low-to-moderate-emissions pathway), and RCP8.5 (high-emissions pathway) scenarios by the 2050s, respectively. Accordingly, the area-weighted SOC stock and total storage for the whole study area were estimated to decrease by 0.43, 0.63 and 1.01 kg m–2 and 4.55, 6.66 and 10.62 Tg under the RCP2.6, RCP4.5 and RCP8.5 scenarios, respectively. In addition, the mid-elevation zones (3100–3900 m), especially the subalpine shrub-meadow Mollic Leptosols, were projected to experience the most intense carbon loss. However, the higher elevation zones (>3900 m), especially the alpine desert zone, were characterized by significant carbon accumulation. As for the low-elevation zones (<2900 m), SOC was projected to be less varied under future climate change scenarios. Thus, the mid-elevation zones, especially the subalpine shrub-meadows and Mollic Leptosols, should be given priority in terms of reducing CO2 emissions in the Qilian Mountains.

30 October 2022 in Sustainability
Verified
Journal Article
Open access
PDF file
YLYongge Li
Yongge Li
WLWei Liu
Wei Liu
Feng QiFeng Qi
Feng Qi
Meng ZhuMeng Zhu
Meng Zhu
Jutao ZhangJutao Zhang
Jutao Zhang
XYXinwei Yin
Xinwei Yin
Land-use and climate changes can exert significant influences on ecosystem services value (ESV). However, interactions of these drivers in shaping the ESV remain unclear in arid inland regions. In this study, dynamic changes in ESV from 1980 to 2050 in the Hexi Regions were evaluated by integrating land-use change and other environmental factors using the equivalent factor method, local spatial autocorrelation analysis, and a geographical detector. Our results showed that the spatial distribution of ESV increased in the northwest to southeast regions of the study area. The area-weighted mean ESV of the Qilian Mountains (i.e., mountainous regions) was about 10.27–11.97-fold higher than that of the Hexi Corridor (i.e., plain regions) during the study period. As for the ecological protection (EP) scenario, from 2020 to 2050, the total ESV increase was estimated to be larger than that under the natural development (ND) and rapid urbanization (RU) scenarios. Particularly, under the EP scenario, by 2050, the enhancement of ESV in the Qilian Mountains mainly resulted from the expansion of forests, shrubs, grasslands, and water. The geographical detector indicated that LUCC was the dominant driver of the spatial heterogeneity of ESV, followed by climate and vegetation. Specifically, LUCC explained 35.39% and 80.06% of the total variation in the ESV for the Hexi Corridor and the Qilian Mountains, respectively. Natural drivers, such as temperature, precipitation, evapotranspiration, and soil organic carbon, were assumed to exert larger impacts on ESV in the mountainous regions than in the corridor. By contrast, anthropogenic factors played more significant roles in altering the ESV patterns for the corridor. Our research highlighted the importance of ecological protection in improving ESV in the future and emphasized that the difference in driving factors of ESV between mountainous and plain regions should be considered in terms of the ecosystem management for the inland regions of northwestern China.

20 May 2025 in Remote Sensing
Verified
Journal Article
Open access
PDF file
YLYongge Li
Yongge Li
WLWei Liu
Wei Liu
Meng ZhuMeng Zhu
Meng Zhu
Feng QiFeng Qi
Feng Qi
Linshan YangLinshan Yang
Linshan Yang
XYXinwei Yin
Xinwei Yin
The coupling coordination relationship between ecosystem services supply–demand and human well-being in arid inland regions is increasingly vulnerable to imbalance risks under the combined pressures of climate change and intensified anthropogenic activities. Here, we assessed dynamic changes in ecosystem services supply–demand, human well-being, their coupling relationships and influencing factors in the Hexi Regions by integrating remote sensing data, ecological model, ecosystem services supply–demand ratio (ESDR), coupling coordination degree (CCD) model, and the partial least squares structural equation modeling (PLS-SEM). Our results showed that the six key ecosystem services supply, demand, and ESDR in the Hexi Regions from 1990 to 2020 exhibited greater ecosystem services surplus in the Qilian Mountains and stronger deficits in urban and surrounding areas of the Hexi Corridor. The deficit of water yield accounted for 32% in the Hexi Corridor with large cropland irrigated, four times that of the Qilian Mountains, indicating a serious supply–demand mismatch in space and time. Additionally, survival-oriented human well-being across regions is still dominant. Overall, the coupling relationship between ESDR and human well-being in the Hexi Regions progressed towards a high level of coordination, with higher values observed in the oases of the Hexi Corridor and the central and eastern Qilian Mountains. The ESDR of food production and water yield showed a higher coupling coordination level with human well-being in the Qilian Mountains, where the CCD was generally exceeded by 0.7. Climate, vegetation, and land use intensity were key drivers of spatial heterogeneity in CCD. Human well-being made a greater contribution to CCD than other elements in the influence paths. Our results can provide a reference for promoting coordinated development of the ecological environment and sustainable human well-being in arid inland regions.

30 June 2023 in Remote Sensing
Verified
Journal Article
Open access
PDF file
XLXuejiao Li
Xuejiao Li
Jutao ZhangJutao Zhang
Jutao Zhang
Feng QiFeng Qi
Feng Qi
WLWei Liu
Wei Liu
YAYong Ao
Yong Ao
THTuo Han
Tuo Han
As a major component of water cycle, the accuracy quantification of different precipitation products is critical for evaluating climate change and ecosystem functions. However, a lack of evidence is available to choose a precise precipitation product in relative applications. Here, to solve this limit, we analyze the spatiotemporal pattern and accuracy of four precipitation products, including CHIRPS V2.0, PERSIANN-CDR, ECMWF ERA5-Land, and GLDAS_NOAH025_3H, over China during the period of 1981–2020, based on the five precipitation traits (i.e., spatial pattern of multi-year average, annual trend, seasonality, frequency, and intensity), and meteorological gauge observations are taken as the benchmark. Our results show that, compared to other products, CHIRPS data has the strongest ability to present spatial pattern of multi-year average precipitation, especially in most parts of northeastern and southern China, and ERA5 has the weakest ability to simulate the multi-year average precipitation. All four precipitation products can accurately depict the spatial pattern of seasonality, among which CHIRPS and ERA5 have the highest and lowest fitting ability, respectively, but four products poorly describe the spatial pattern of precipitation intensity and frequency at a daily scale. These products only correctly predict the interannual precipitation trend in some local areas. Our findings provide evidences to select high-quality precipitation data, and could help to improve the accuracy of relative geophysical models.

24 July 2026 in Forests
Verified
Journal Article
Open access
PDF file
MZMengxu Zhang
Mengxu Zhang
YCYuqing Chen
Yuqing Chen
YLYongge Li
Yongge Li
Meng ZhuMeng Zhu
Meng Zhu
Plant diversity is often expected to enhance soil organic carbon (SOC) storage through greater and more heterogeneous plant inputs, but its relationships with functionally distinct SOC fractions in natural forests remain uncertain. This study compiled published SOC fraction data from 341 surface soil observations in natural forests across China and spatially matched these records with gridded plant alpha diversity, forest age, climate, topographic and soil properties datasets to evaluate biotic and abiotic associations with SOC, particulate organic carbon (POC), mineral-associated organic carbon (MAOC) and MAOC/SOC. Linear regression, multiple regression, piecewise structural equation modelling and stratified analyses were used to evaluate whether plant diversity was associated with the absolute accumulation and relative stabilization of SOC fractions. Plant alpha diversity was negatively associated with ln[SOC], ln[POC] and ln[MAOC] at the national scale, whereas its bivariate relationship with MAOC/SOC was weak. After accounting for forest age and environmental covariates, plant alpha diversity remained negatively related to the absolute contents of SOC fractions while showing a positive association with MAOC/SOC. Forest age was positively associated with ln[SOC], ln[POC] and ln[MAOC], and POC was more strongly related to plant diversity and forest age than MAOC. In contrast, MAOC and MAOC/SOC were more strongly associated with mineral protection potential, soil pH and precipitation background. Structural equation models indicated that mineral protection potential and mean annual precipitation were associated with greater MAOC accumulation and SOC allocation to the mineral-associated fraction, whereas temperature and topography were linked to MAOC partly through indirect associations with soil physicochemical conditions. Stratified analyses showed that plant diversity associations varied among forest types and climatic backgrounds. Additional interaction models showed that mineral protection potential significantly moderated the associations between plant alpha diversity and ln[SOC], ln[POC] and ln[MAOC], with negative diversity associations weakening under higher mineral protection potential. These findings indicate that plant diversity associations with SOC fractions in natural forests cannot be interpreted as universally positive input relationships. Instead, their direction and strength depend on hydroclimatic context and soil mineral protection, especially for the absolute accumulation of SOC fractions.