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Atmosphere
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The Response of Plateau Vegetation to Climatic and Anthropogenic Drivers
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The Response of Plateau Vegetation to Climatic and Anthropogenic Drivers

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Biosphere/Hydrosphere/Land–Atmosphere Interactions".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 4042

Special Issue Editors

Dr. Fanhao Meng

E-Mail Website
Guest Editor
College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China
Interests: SWAT model; climate change; hydrological modeling; water balance; landuse and cover change; ecohydrological changes in arid and semi-arid zones
Special Issues, Collections and Topics in MDPI journals
Dr. Min Luo

E-Mail Website
Guest Editor
Inner Mongolia Key Laboratory of Remote Sensing and Geographic Information Systems, Inner Mongolia Normal University, Hohhot 010022, China
Interests: climate change; hydrology and water resources; flood monitoring and simulation; drought; soil moisture; ecological response to extreme climate change
Special Issues, Collections and Topics in MDPI journals
Dr. Wenfeng Chi

E-Mail Website
Guest Editor
College of Resources and Environment Economy, Inner Mongolia University of Finance and Economics, Hohhot 010070, China
Interests: vegetation dynamic monitoring; ecosystem services; landuse and cover change; climate change; soil erosion; urbanization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is a follow-up of the first Special Issue, entitled “Response of Vegetation to Climatic and Anthropogenic Drivers in the Plateau” (https://www.mdpi.com/journal/atmosphere/special_issues/BJNR1SIJR4) published in Atmosphere.

Vegetation is a natural link connecting various spheres and the main body of the terrestrial ecosystem; moreover, it is an indicator of regional climate change and human activities, and plays an important role in regulating carbon, water, and energy cycles. With diverse vegetation types and a complex geographical environment, vegetation growth in the plateau region is more sensitive to climate change and human activities, and is a sensitive and vulnerable zone for global climate change and ecological environment changes. Since the beginning of the Anthropocene, the vegetation ecosystem has been significantly changed by both climate warming and human activities, mainly in the form of glacial retreat, land desertification, and grassland degradation. If humans continue to develop and use the earth's resources unreasonably in the future, it will lead to the gradual depletion of natural resources and further degradation of the ecosystem, which will threaten the ecosystem and ecological security of the plateau region. Therefore, it is of great scientific and practical significance to investigate dynamic changes in plateau vegetation and the interrelationship between vegetation, climate change, and human activities, in order to understand the current state of the global plateau ecosystem, restore ecosystem balance, and promote the sustainable development of the ecosystem.

This Special Issue will focus on papers that contribute to a better understanding of the characteristics of synergistic vegetation–water–soil changes in plateau regions in the context of climate change and increased human activities. Examples topics of interest include (but are not limited to) the following:

  • Response of vegetation (growth, health, phenology, etc.) to climate change and human activities in plateau regions;
  • Relationship between extreme weather changes such as droughts and floods and vegetation biomass;
  • Effects of land use/cover change or ecological engineering on regional vegetation (cover, leaf area index, etc.);
  • Differences in vegetation response to climate change and human activities for different substrate conditions (elevation, slope, etc.);
  • Relationship between environmental factors, such as glacier, snow, permafrost, etc., and vegetation changes in the context of climate warming;
  • Impacts of excessive logging and grazing activities on vegetation;
  • Characteristics of vegetation response to urbanization process;
  • Response of vegetation ecosystem quality to coupled atmosphere–water changes;
  • Climate–vegetation–soil–water–ecosystem feedback mechanisms.

This call solicits process-level studies based on both observations and model simulations. This includes intensive observational field campaign studies, long-term in situ observatories, satellite observations, and simulations from plot-scale process-oriented models or regional/global Earth system models.

Dr. Fanhao Meng
Dr. Min Luo
Dr. Wenfeng Chi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • vegetation degradation
  • land use and cover change
  • climate change impact
  • deforestation
  • extreme climate factors
  • droughts and floods
  • Plateau vegetation

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Published Papers (5 papers)

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Research

23 pages, 6812 KB  
Article
Causality-Constrained XGBoost–SHAP Reveals Nonlinear Drivers and Thresholds of kNDVI Greening on the Loess Plateau (2000–2019)
by Yue Li, Hebing Zhang, Yiheng Jiao, Xuan Liu and Yinsuo Sun
Atmosphere 2026, 17(3), 297; https://doi.org/10.3390/atmos17030297 - 15 Mar 2026
Viewed by 517
Abstract
The Loess Plateau has experienced persistent vegetation greening over the past two decades, yet this recovery has occurred under a concurrent intensification of atmospheric evaporative demand and drying. This raises a key land–atmosphere question: which hydroclimatic processes most strongly constrain greening, and where [...] Read more.
The Loess Plateau has experienced persistent vegetation greening over the past two decades, yet this recovery has occurred under a concurrent intensification of atmospheric evaporative demand and drying. This raises a key land–atmosphere question: which hydroclimatic processes most strongly constrain greening, and where do vegetation responses shift across environmental regimes? To address this issue, we integrated spatiotemporal trend analysis, Geographical Convergent Cross Mapping (GCCM)-based directional attribution, and an interpretable machine-learning framework combining Extreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP) to diagnose the dominant controls and threshold-like response patterns of vegetation activity. Using 1 km kernel Normalized Difference Vegetation Index (kNDVI) and eight hydroclimatic variables during 2000–2019, we found that regionally averaged kNDVI increased from 0.099 in 2000 to 0.164 in 2019, with a significant trend of 0.003 year−1, and greening trends covered 65.503% of the Loess Plateau. Over the same period, Vapor Pressure Deficit (VPD) increased from 0.142 to 0.275 kPa (+0.133 kPa), indicating that vegetation recovery did not occur under a more humid atmospheric background. GCCM results consistently showed stronger directional influence from hydroclimatic drivers to kNDVI than the reverse, with evaporation and thermal conditions, especially Tmin, emerging as the dominant constraints, followed by Tmax, VPD, and wind speed, whereas precipitation showed comparatively weaker recoverable influence. The tuned XGBoost model achieved strong out-of-sample performance (R2 = 0.9611, RMSE = 0.0188, MAE = 0.0131), and SHAP revealed clear nonlinear thresholds: evaporation and Tmin shifted into persistently positive contribution regimes beyond 302 mm and −17.6 °C, respectively; Tmax became predominantly inhibitory beyond −1.9 °C, and Palmer Drought Severity Index (PDSI) exhibited a multi-stage non-monotonic transition around −0.7. These results provide a coherent evidence chain linking directional influence, relative contribution, and threshold boundaries, offering quantitative support for identifying climate-sensitive zones and restoration risk regimes under continued warming and rising atmospheric dryness. Full article
(This article belongs to the Special Issue The Response of Plateau Vegetation to Climatic and Anthropogenic Drivers)
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13 pages, 3422 KB  
Article
Emission, Transport, and Deposition Mechanisms for a Severe Summer Dust Storm Originating in Southern Mongolia
by Lunga Su, Mei Yong, Zuowei Xie, Cholaw Bueh, Dongmei Song and Xin Sun
Atmosphere 2026, 17(3), 240; https://doi.org/10.3390/atmos17030240 - 26 Feb 2026
Viewed by 560
Abstract
This study investigated an intense and unusual summer transboundary dust storm event that occurred between 21 and 23 June 2024. By integrating remote sensing observations, reanalysis data, WRF-Chem simulations, and LAGRANTO trajectory tracking, we systematically revealed the dust emission, transport, deposition, and formation [...] Read more.
This study investigated an intense and unusual summer transboundary dust storm event that occurred between 21 and 23 June 2024. By integrating remote sensing observations, reanalysis data, WRF-Chem simulations, and LAGRANTO trajectory tracking, we systematically revealed the dust emission, transport, deposition, and formation mechanisms of this event. The dust primarily originated from the Gobi region of southern Mongolia, where concentrations exceeded 10,000 µg m−3, and decayed exponentially as the Mongolian cyclone moved southeastward. Post border-crossing into China, the event transitioned to blowing and floating dust, with concentrations decreasing significantly. During transport, dry deposition dominated the source area and the frontal part of the transport path in the early stages, while wet deposition was associated with the precipitation system of the Mongolian cyclone and concentrated north and east of the cyclone’s track. On 21 June 2024, the average wind speed in the source region reached 11.35 ms−1, the highest recorded in the past 45 years. This was attributed to surface anomalies, including reduced soil moisture, poor vegetation cover, higher temperatures, and decreased precipitation relative to the multi-year average. The comprehensive application of multi-source data and models in this work elucidates the full lifecycle of this rare summer dust event, providing scientific insights into the atmospheric processes governing extreme dust events and their transboundary impacts. Full article
(This article belongs to the Special Issue The Response of Plateau Vegetation to Climatic and Anthropogenic Drivers)
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20 pages, 1908 KB  
Article
Research on Real-Time Rainfall Intensity Monitoring Methods Based on Deep Learning and Audio Signals in the Semi-Arid Region of Northwest China
by Yishu Wang, Hongtao Jiang, Guangtong Liu, Qiangqiang Chen and Mengping Ni
Atmosphere 2026, 17(2), 131; https://doi.org/10.3390/atmos17020131 - 26 Jan 2026
Viewed by 545
Abstract
With the increasing frequency extreme weather events associated with climate change, real-time monitoring of rainfall intensity is critical for water resource management, disaster warning, and other applications. Traditional methods, such as ground-based rain gauges, radar, and satellites, face challenges like high costs, low [...] Read more.
With the increasing frequency extreme weather events associated with climate change, real-time monitoring of rainfall intensity is critical for water resource management, disaster warning, and other applications. Traditional methods, such as ground-based rain gauges, radar, and satellites, face challenges like high costs, low resolution, and monitoring gaps. This study proposes a novel real-time rainfall intensity monitoring method based on deep learning and audio signal processing, using acoustic features from rainfall to predict intensity. Conducted in the semi-arid region of Northwest China, the study employed a custom-designed sound collection device to capture acoustic signals from raindrop-surface interactions. The method, combining multi-feature extraction and regression modeling, accurately predicted rainfall intensity. Experimental results revealed a strong linear relationship between sound pressure and rainfall intensity (r = 0.916, R2 = 0.838), with clear nonlinear enhancement of acoustic energy during heavy rainfall. Compared to traditional methods like CML and radio link techniques, the acoustic approach offers advantages in cost, high-density deployment, and adaptability to complex terrain. Despite some limitations, including regional and seasonal biases, the study lays the foundation for future improvements, such as expanding sample coverage, optimizing sensor design, and incorporating multi-source data. This method holds significant potential for applications in urban drainage, agricultural irrigation, and disaster early warning. Full article
(This article belongs to the Special Issue The Response of Plateau Vegetation to Climatic and Anthropogenic Drivers)
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22 pages, 4374 KB  
Article
Drivers and Future Regimes of Runoff and Hydrological Drought in a Critical Tributary of the Yellow River Under Climate Change
by Yu Wang, Yong Wang, Wenya Fang, Yuhan Zhao, Ying Zhou and Fangting Wang
Atmosphere 2025, 16(12), 1327; https://doi.org/10.3390/atmos16121327 - 24 Nov 2025
Viewed by 731
Abstract
China’s Yellow River basin encounters widespread risks of reduced runoff and intensified hydrological drought. This study focuses on the middle and upper reaches of the Dahei River, the Yellow River’s primary tributary. In this region, the Soil & Water Assessment Tool (SWAT) hydrological [...] Read more.
China’s Yellow River basin encounters widespread risks of reduced runoff and intensified hydrological drought. This study focuses on the middle and upper reaches of the Dahei River, the Yellow River’s primary tributary. In this region, the Soil & Water Assessment Tool (SWAT) hydrological model was employed to simulate hydrological processes, identify runoff changes and hydrological drought characteristics, and conduct attribution analysis from 1983 to 2022, as well as to project trends over the next 40 years. The results indicate that total runoff during the impact period (1999–2022) decreased by 55.26% compared to the baseline period (1983–1998). Climate change accounted for a contribution rate of 38.6% to this decline, while human activities accounted for 61.4%. Additionally, climate primarily altered surface runoff (SURQ) and lateral groundwater flow (LATQ) through precipitation changes, while land use had a predominant influence on total runoff volume by modifying SURQ. Both factors exhibited relatively minor effects on LATQ. Moreover, human activities contribute to hydrological drought at a rate of 36.11% to 94.25%. Drought probability is significantly influenced by climate through precipitation and temperature changes, while land use primarily mitigates hydrological drought by impacting the three runoff components. It is predicted that over the next 40 years, total runoff will decrease by 2.08% to 60.16%, along with hydrological droughts that are more frequent, longer in average duration, and more intense; however, the Maximum Drought Duration is anticipated to shorten. In the east and northeast, hydrological drought presents a trend of intensification, with central and western regions exhibiting weaker or declining changes. Full article
(This article belongs to the Special Issue The Response of Plateau Vegetation to Climatic and Anthropogenic Drivers)
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24 pages, 9802 KB  
Article
Threshold Dynamics of Vegetation Carbon Sink Loss Under Multiscale Droughts in the Mongolian Plateau
by Hongguang Chen, Mulan Wang, Fanhao Meng, Chula Sa, Min Luo, Wenfeng Chi and Sonomdagva Chonokhuu
Atmosphere 2025, 16(8), 964; https://doi.org/10.3390/atmos16080964 - 14 Aug 2025
Viewed by 1259
Abstract
Gross primary productivity (GPP) is a key carbon flux in the global carbon cycle, and understanding the inhibitory effects of drought on GPP and its underlying mechanisms is crucial for understanding carbon–climate feedback. However, current research has not sufficiently addressed the threshold dynamics [...] Read more.
Gross primary productivity (GPP) is a key carbon flux in the global carbon cycle, and understanding the inhibitory effects of drought on GPP and its underlying mechanisms is crucial for understanding carbon–climate feedback. However, current research has not sufficiently addressed the threshold dynamics and regional differentiation of GPP responses to the synergistic effects of meteorological drought (MD) and soil moisture drought (SD), particularly in the drought-sensitive Mongolian Plateau. This study focuses on the Mongolian Plateau from 1982 to 2021, using the standardized precipitation index (SPI) and standardized soil moisture index (SSI) to characterize MD and SD, respectively. The study combines the three-threshold run theory, cross-wavelet analysis, Spearman correlation analysis, and copula models to systematically investigate the variation characteristics, propagation patterns, and the probability and thresholds for triggering GPP loss under different time scales (monthly, seasonal, semi-annual, and annual). The results show that (1) both types of droughts exhibited significant intensification trends, with SD intensifying at a faster rate (annual scale SSI12 trend: −0.34/10a). The intensification trend strengthened with increasing time scales. MD exhibited high frequency, short duration, and low intensity, while SD showed the opposite characteristics. The most significant aridification occurred in the central region. (2) The average propagation time from MD to SD was 11.22 months. The average response time of GPP to MD was 10.46 months, while the response time to SD was significantly shorter (approximately 2 months on average); the correlation between SSI and GPP was significantly higher than that between SPI and GPP. (3) The conditional probability of triggering mild GPP loss (e.g., <40th percentile) was relatively high for both drought types, and the probability of loss increased as the time scales extended. Compared to MD, SD was more likely to induce severe GPP loss. Additionally, the drought intensity threshold for triggering mild loss was lower (i.e., mild drought could trigger it), while higher drought intensity was required to trigger severe and extreme losses. Therefore, this study provides practical guidance for regional drought early-warning systems and ecosystem adaptive management, while laying an important theoretical foundation for a deeper understanding of drought response mechanisms. Full article
(This article belongs to the Special Issue The Response of Plateau Vegetation to Climatic and Anthropogenic Drivers)
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