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20 pages, 8101 KiB  
Article
An Analysis of Spatial Variation in Human Impact on Forest Ecological Functions
by Qingjun Wu, Liyong Fu, Ram P. Sharma, Yaquan Dou and Xiaodi Zhao
Appl. Sci. 2025, 15(9), 4854; https://doi.org/10.3390/app15094854 - 27 Apr 2025
Viewed by 130
Abstract
As the cornerstone of terrestrial ecosystems, forests have faced mounting challenges due to escalating human activities, jeopardizing their vital ecological functions and even their existence. It has become an important issue to explore how to promote harmonious coexistence of man and nature, or [...] Read more.
As the cornerstone of terrestrial ecosystems, forests have faced mounting challenges due to escalating human activities, jeopardizing their vital ecological functions and even their existence. It has become an important issue to explore how to promote harmonious coexistence of man and nature, or even to improve the forest ecological function (FEF) through human activities. Thus, in this study, we select the Yellow River Basin (YRB) in China as a typical region. Firstly, we assess the FEF at the county level and reveal their spatial distribution and agglomeration characteristics on the basis of the data from the Ninth National Forest Inventory of China. Then, using multiple linear regression (MLR) and geographically weighted regression (GWR) modeling, we further explore the overall impacts of different human activities on FEF and their spatial differences, respectively. Our findings underscored a moderate deficiency in the county-level FEF in the YRB, with pronounced positive spatial agglomerations. The high–high areas are primarily clustered in the southern and central mountainous areas, whereas low–low areas are distributed in the upstream warm temperate steppe and desert-grassland regions. Human activities exert substantial impacts on FEF, with distinct spatial heterogeneity in the coefficient and significance levels. The trend analysis indicates that FEF is more sensitive to the increase in living land, population density and forest protection in the east–west direction. And in the north–south direction, FEF is more easily affected by agricultural development, population growth and urbanization. This study verifies that natural factors dominate FEF in those regions where human activities are quite scarce, and also reveals that due to the inter-constraint or counteract effects among different human activities, FEF may still ultimately depend on the natural endowments in some populated regions. We point out the core human activity factors affecting FEF after excluding the interference from natural conditions. And we recommend that policymakers prioritize sustainable development strategies that mitigate the adverse impacts of human activities on forest ecosystems while promoting conservation efforts tailored to the unique characteristics of each region. Full article
(This article belongs to the Special Issue Application of Machine Learning in Land Use and Land Cover)
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22 pages, 7740 KiB  
Article
A Future Scenario Prediction for the Arid Inland River Basins in China Under Climate Change: A Case Study of the Manas River Basin
by Fuchu Zhang, Xinlin He, Guang Yang and Xiaolong Li
Sustainability 2025, 17(8), 3658; https://doi.org/10.3390/su17083658 - 18 Apr 2025
Viewed by 160
Abstract
Global warming poses significant threats to agriculture, ecosystems, and human survival. This study focuses on the arid inland Manas River Basin in northwestern China, utilizing nine CMIP6 climate models and five multi-model ensemble methods (including machine learning algorithms such as random forest and [...] Read more.
Global warming poses significant threats to agriculture, ecosystems, and human survival. This study focuses on the arid inland Manas River Basin in northwestern China, utilizing nine CMIP6 climate models and five multi-model ensemble methods (including machine learning algorithms such as random forest and support vector machines) to evaluate historical temperature and precipitation simulations (1979–2014) after bias correction via Quantile Mapping (QM). Future climate trends (2015–2100) under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) are projected and analyzed for spatiotemporal evolution. The results indicate that the weighted set method (WSM) significantly improves simulation accuracy after excluding poorly performing models. Under SSP1-2.6, the long-term average increases in maximum temperature, minimum temperature, and precipitation are 1.654 °C, 1.657 °C, and 34.137 mm, respectively, with minimal climate variability. In contrast, SSP5-8.5 exhibits the most pronounced warming, with increases reaching 4.485 °C, 4.728 °C, and 60.035 mm, respectively. Notably, the minimum temperature rise gradually surpasses the maximum temperature, indicating a shift toward warmer and more humid conditions in the basin. Spatially, high warming rates are concentrated in low-altitude desert areas, while the precipitation increases correlate with elevation. These findings provide critical insights for climate adaptation strategies, sustainable water resource management, and ecological conservation in China’s arid inland river basins under future climate change. Full article
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18 pages, 6835 KiB  
Article
Response of Gross Primary Productivity (GPP) of the Desert Steppe Ecosystem in the Northern Foothills of Yinshan Mountain to Extreme Climate
by Shuixia Zhao, Mengmeng Zhang, Yingjie Wu, Enliang Guo, Yongfang Wang, Shengjie Cui and Tomasz Kolerski
Land 2025, 14(4), 884; https://doi.org/10.3390/land14040884 - 16 Apr 2025
Viewed by 279
Abstract
The desert steppe ecosystem at the Northern Foothills of the Yinshan Mountains (NFYS) is characterized by its fragility and heightened sensitivity to global climate change. Understanding the response and lag effects of Gross Primary Productivity (GPP) to climate change is imperative for advancing [...] Read more.
The desert steppe ecosystem at the Northern Foothills of the Yinshan Mountains (NFYS) is characterized by its fragility and heightened sensitivity to global climate change. Understanding the response and lag effects of Gross Primary Productivity (GPP) to climate change is imperative for advancing ecological management and fostering sustainable development. The spatiotemporal dynamics of chlorophyll fluorescence-based GPP data and its responses to precipitation, temperature, and extreme climate from 2001 to 2023 were analyzed. The random forest model and the partial least squares regression model were employed to further elucidate the response mechanisms of GPP to extreme climate, with a specific focus on the lag effect. The findings revealed that the GPP in the NFYS exhibited distinct regional characteristics, demonstrating a predominantly increasing trend over the past 23 years. The region has experienced a warming and drying trend, marked by a decrease in the intensity and frequency of extreme precipitation events, and an increase in extremely high temperatures and consecutive hot days, except a slight, albeit insignificant, increase in precipitation in the northeastern part. GPP exhibits varying degrees of lag, ranging from one to three months, in response to both normal and extreme climatic conditions, with a more immediate response to extreme temperatures than to precipitation. The influence of different climatic conditions on the lag effects of GPP can amplify the negative effects of extreme temperatures and the positive impact of extreme precipitation. The anticipated trend towards a warmer and more humid climate is projected to foster an increase in GPP. This research is of great theoretical and practical significance for deeply understanding the adaptation mechanisms of ecosystems under the context of climate change, optimizing desertification control strategies, and enhancing regional ecological resilience. Full article
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14 pages, 3183 KiB  
Article
Impacts of Cereal and Legume Cultivation on Soil Properties and Microbial Communities in the Mu Us Desert
by Lirong He, Lei Shi, Yang Wu, Guoliang Wang and Guobin Liu
Agronomy 2025, 15(4), 968; https://doi.org/10.3390/agronomy15040968 - 16 Apr 2025
Viewed by 156
Abstract
This study aimed to evaluate the effects of different crop cultivation practices on soil chemical properties and microbial communities in the Mu Us Desert, with the goal of optimizing land management and promoting ecological restoration. A one-way randomized block design was used to [...] Read more.
This study aimed to evaluate the effects of different crop cultivation practices on soil chemical properties and microbial communities in the Mu Us Desert, with the goal of optimizing land management and promoting ecological restoration. A one-way randomized block design was used to establish experimental plots for a cereal (Setaria italica, SI), a legume (Glycine max, GM), and a control group with no crops (CK) in the central Mu Us Desert. Soil samples were collected to assess physicochemical properties and to analyze microbial community structures via high-throughput 16S rRNA gene sequencing. Results showed that crop cultivation decreased soil pH while increasing soil organic carbon (SOC), total nitrogen (TN), and available phosphorus (AP), indicating improved soil fertility and reduced soil alkalinity. The composition of soil bacterial communities varied significantly among treatments. Both SI and GM treatments increased the number of operational taxonomic units (OTUs), enhancing bacterial richness and diversity. Proteobacteria and Actinobacteria increased with crop cultivation, whereas Chloroflexi declined. These shifts were largely attributed to changes in pH and nutrient availability. Notably, SI treatment had a stronger positive effect on bacterial richness. Correlation analyses between soil chemical properties and microbial community composition highlighted the potential of crop cultivation to influence soil ecosystem services. These findings provide a scientific basis for sustainable agricultural practices and ecological restoration in arid regions such as the Mu Us Desert. Further studies are warranted to investigate the functional roles of microbial communities under different cropping patterns. Full article
(This article belongs to the Special Issue Soil Health and Properties in a Changing Environment)
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33 pages, 33351 KiB  
Article
A Deep Learning Method for Land Use Classification Based on Feature Augmentation
by Yue Wang, Wanshun Zhang, Xin Liu, Hong Peng, Minbo Lin, Ao Li, Anna Jiang, Ning Ma and Lu Wang
Remote Sens. 2025, 17(8), 1398; https://doi.org/10.3390/rs17081398 - 14 Apr 2025
Viewed by 281
Abstract
Land use monitoring by satellite remote sensing can improve the capacity of ecosystem resources management. The satellite source, bandwidth, computing speed, data storage and cost constrain the development and application in the field. A novel deep learning classification method based on feature augmentation [...] Read more.
Land use monitoring by satellite remote sensing can improve the capacity of ecosystem resources management. The satellite source, bandwidth, computing speed, data storage and cost constrain the development and application in the field. A novel deep learning classification method based on feature augmentation (CNNs-FA) is developed in this paper, which offers a robust avenue to realize regional low-cost and high-precision land use monitoring. Twenty-two spectral indices are integrated to augment vegetation, soil and water features, which are used for convolutional neural networks (CNNs) learning to effectively differentiate seven land use types, including cropland, forest, grass, built-up, bare, wetland and water. Results indicated that multiple spectral indices can effectively distinguish land uses with a similar reflectance, achieving an overall accuracy of 99.70%, 94.81% and 90.07%, respectively, and a kappa coefficient of 99.96%, 98.62% and 99.76%, respectively, for Bayannur, Ordos and the Hong Lake Basin (HLB). The overall accuracy of 98.18% for the field investigation demonstrated that the accuracy of the classification in wet areas and ecologically sensitive areas was characterized by significant desert–grassland interspersion. Full article
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21 pages, 10754 KiB  
Article
Accounting of Grassland Ecosystem Assets and Assessment of Sustainable Development Potential in the Bosten Lake Basin
by Zhichao Zhang, Zhoukang Li, Zhen Zhu and Yang Wang
Sustainability 2025, 17(8), 3460; https://doi.org/10.3390/su17083460 - 13 Apr 2025
Viewed by 242
Abstract
Assessing the ecosystem service value (ESV) of grasslands is crucial for sustainable resource management and environmental conservation. This study evaluates the spatiotemporal changes in grassland ecosystem services in the Bosten Lake Basin using long-term land use data (2000–2022). Employing the Patch-generating Land Use [...] Read more.
Assessing the ecosystem service value (ESV) of grasslands is crucial for sustainable resource management and environmental conservation. This study evaluates the spatiotemporal changes in grassland ecosystem services in the Bosten Lake Basin using long-term land use data (2000–2022). Employing the Patch-generating Land Use Simulation (PLUS) model, we develop three future scenarios—natural development, ecological protection, and economic priority—to predict grassland utilization trends. The findings reveal a continuous decline in grassland area and ecosystem service values, driven by climate change and human activities. Compared with 2022, all three scenarios indicate further degradation, but ecological protection measures significantly mitigate ESV loss. This study provides scientific insights for sustainable land management and policy-making, contributing to ecological restoration strategies under climate change impacts. The findings reveal the following: (1) Over the 22-year period, the grassland area in the Bosten Lake Basin has experienced an overall decline. Notably, the area of plain desert steppe grassland expanded from 626,179.41 ha to 1,223,506.62 ha, whereas plain meadow grassland reduced from 556,784.64 ha to 118,948.23 ha. (2) The total ecosystem service value of grasslands in the basin exhibited a marginally insignificant decrease, amounting to a reduction of 5.73422 billion CNY. The values for mountain desert, mountain desert steppe, mountain typical steppe, and mountain meadow grasslands were relatively low and showed minimal change. (3) In comparison to 2022, the projected areas of grassland under the three scenarios for 2000 show a substantial reduction, particularly in plain desert and hilly desert grasslands. The ecosystem service values across all scenarios are expected to decline in tandem with varying degrees of grassland degradation. This research underscores the impact of global warming and human activities on the shrinking grassland area and the diminishing ecosystem service values in the Bosten Lake Basin. The current state of grassland resources in the study area is under threat, highlighting the urgent need for strategic planning and conservation efforts to ensure sustainable development and ecological integrity. Full article
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17 pages, 1761 KiB  
Article
Species and Functional Diversity of Bird Communities in Different Habitats in Shiquan River National Wetland Park, Tibet
by Yang Wei, Jingshan Wang, Yi Guo, Chen Huang and Xu Li
Diversity 2025, 17(4), 271; https://doi.org/10.3390/d17040271 - 11 Apr 2025
Viewed by 168
Abstract
The Shiquan River National Wetland Park in Tibet is an integrated high-elevation wetland ecosystem. This wetland park also serves as a demonstration site for international river conservation and the ‘conservation–utilization–sustainable enhancement’ of wetland resources in alpine desert zones. This study supplements the research [...] Read more.
The Shiquan River National Wetland Park in Tibet is an integrated high-elevation wetland ecosystem. This wetland park also serves as a demonstration site for international river conservation and the ‘conservation–utilization–sustainable enhancement’ of wetland resources in alpine desert zones. This study supplements the research on bird community structure and ecological function to fill the gap in basic data on birds in the Shiquan River National Wetland Park. From May 2023 to October 2024, a sampling point method was used to conduct four systematic surveys during the breeding and non-breeding periods of birds in four habitats—grass land, marsh land, bare land, and water bodies—in the Shiquan River National Wetland Park to explore the effects of different habitat types on bird communities from the perspective of species and functional diversity. A total of 56 bird species, representing 23 families and 11 orders, were documented in this survey. Species diversity was highest in the marsh habitat during the breeding season, followed sequentially by grassland, bare land, and water bodies, with consistent results in the non-breeding period. The functional richness (FRic) results revealed a pattern of marsh land > grass land > bare land > water bodies, indicating that birds utilized the ecological space within the marsh habitat to the greatest extent. The functional differentiation (FDiv) results followed a pattern of bare land > water bodies > grass land > marsh land, suggesting stronger niche complementarity and weaker competition in bare ground habitats. Finally, the functional dispersion (FDis) results demonstrated a pattern of grass land > marsh land > bare land > water bodies, indicating a greater number of species with similar functional traits in grass habitats. This study addresses the research gap concerning bird communities in the Shiquan River National Wetland Park through the lens of both species and functional diversity, thereby providing a scientific foundation and critical support for the conservation of avian biodiversity in the Shiquan River Basin and high-elevation regions. Full article
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22 pages, 21780 KiB  
Article
Spatio-Temporal Variation Characteristics of Grassland Water Use Efficiency and Its Response to Drought in China
by Mengxiang Xing, Liang Liu, Jianghua Zheng, Xinwei Wang and Wei Li
Water 2025, 17(8), 1134; https://doi.org/10.3390/w17081134 - 10 Apr 2025
Viewed by 248
Abstract
Understanding the impact of drought on the water use efficiency (WUE) of grasslands is essential for comprehending the mechanisms of the carbon–water cycle in the context of global warming. Nevertheless, the cumulative and lagged effects of drought on WUE across different grassland types [...] Read more.
Understanding the impact of drought on the water use efficiency (WUE) of grasslands is essential for comprehending the mechanisms of the carbon–water cycle in the context of global warming. Nevertheless, the cumulative and lagged effects of drought on WUE across different grassland types in China remain unclear. This study investigates the cumulative and lagged effects of drought on WUE across different grassland types in China from 1982 to 2018. We employed the Sen-MK trend test and correlation analysis to identify the primary factors influencing the temporal effects of drought on WUE. The results indicated that WUE in Chinese grasslands, across various grassland types, exhibited an upward trend over time, with the most rapid increase observed in meadow. Drought had both cumulative and lagged effects on WUE, with cumulative effects lasting an average of 5.2 months and lagged effects lasting 6.1 months. Specifically, the cumulative effects of drought on WUE lasted for 5.6 months for alpine and subalpine meadow, slope, and desert grassland, whereas the lagged effects lasted 9 months for alpine and subalpine plain grassland. Furthermore, the influence of drought on WUE in grasslands varied across different grassland types and intensified with increasing altitude. The trends observed in the cumulative and lagged impacts of drought on WUE across various aridity index (AI) zones were consistent with those for grasslands as a whole. Our findings underscore that the response of WUE to drought in grasslands and their distinct types is primarily characterized by lagged effects. This research provides an important reference value for enhancing the stability of grassland ecosystems. Full article
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30 pages, 31096 KiB  
Article
Decadal Trends and Drivers of Dust Emissions in East Asia: Integrating Statistical and SHAP-Based Interpretability Approaches
by Ziwei Yi, Yaqiang Wang, Zhaoliang Zeng, Weijie Li, Huizheng Che and Xiaoye Zhang
Remote Sens. 2025, 17(7), 1313; https://doi.org/10.3390/rs17071313 - 7 Apr 2025
Viewed by 412
Abstract
Dust emissions significantly impact the radiation balance, ecosystems, human health, and global climate change through long-range transport. However, their spatiotemporal characteristics and driving mechanisms in East Asia remain poorly understood. This study integrates multi-source reanalysis and remote sensing data (1980–2023) to analyze dust [...] Read more.
Dust emissions significantly impact the radiation balance, ecosystems, human health, and global climate change through long-range transport. However, their spatiotemporal characteristics and driving mechanisms in East Asia remain poorly understood. This study integrates multi-source reanalysis and remote sensing data (1980–2023) to analyze dust emissions across East Asian source regions using statistical methods and SHapley Additive exPlanations (SHAP) interpretability. The results show significant spatial and seasonal variations, with peak emissions occurring in spring (March–May). The Taklamakan Desert (S4) accounts for 38.1% of total emissions and is the largest source region. Meteorological factors are the main drivers (49.4–68.8% contribution), while climate indices contribute the least (2.9–8.0%). Wind speed is the most critical factor driving dust emissions, showing a significant positive correlation and interacting with 850 hPa geopotential height and boundary layer height. The driving factors of dust emissions vary across regions. In Mongolia (S1), dust emissions are mainly influenced by wind speed and atmospheric circulation, while in S4, near-surface meteorological conditions play a dominant role. In the Tsaidam Basin and Kumutage Desert (S5), as well as the Badain Jaran, Tengger, and Ulan Buh Deserts (S6), dust emissions are primarily driven by wind speed and boundary layer height, with atmospheric circulation also playing a certain role. Relative humidity shows a significant negative correlation with dust emissions in S5 and S6, while snowmelt and soil temperature have significant impacts on S4 and S5. The negative phases of the Arctic Oscillation and North Atlantic Oscillation enhance cold air activity and wind speed, significantly promoting dust emissions in S1 and S6. This study quantifies the mechanisms of dust emissions in East Asia and offers scientific support for improving climate models and developing disaster mitigation strategies. Full article
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22 pages, 40986 KiB  
Article
Modeling Short-Term Drought for SPEI in Mainland China Using the XGBoost Model
by Fanchao Zeng, Qing Gao, Lifeng Wu, Zhilong Rao, Zihan Wang, Xinjian Zhang, Fuqi Yao and Jinwei Sun
Atmosphere 2025, 16(4), 419; https://doi.org/10.3390/atmos16040419 - 4 Apr 2025
Viewed by 315
Abstract
Accurate drought prediction is crucial for optimizing water resource allocation, safeguarding agricultural productivity, and maintaining ecosystem stability. This study develops a methodological framework for short-term drought forecasting using SPEI time series (1979–2020) and evaluates three predictive models: (1) a baseline XGBoost model (XGBoost1), [...] Read more.
Accurate drought prediction is crucial for optimizing water resource allocation, safeguarding agricultural productivity, and maintaining ecosystem stability. This study develops a methodological framework for short-term drought forecasting using SPEI time series (1979–2020) and evaluates three predictive models: (1) a baseline XGBoost model (XGBoost1), (2) a feature-optimized XGBoost variant incorporating Pearson correlation analysis (XGBoost2), and (3) an enhanced CPSO-XGBoost model integrating hybrid particle swarm optimization with dual mechanisms of binary feature selection and parameter tuning. Key findings reveal spatiotemporal prediction patterns: temporal-scale dependencies show all models exhibit limited capability at SPEI-1 (R2: 0.32–0.41, RMSE: 0.68–0.79) but achieve progressive accuracy improvement, peaking at SPEI-12 where CPSO-XGBoost attains optimal performance (R2: 0.85–0.90, RMSE: 0.33–0.43) with 18.7–23.4% error reduction versus baselines. Regionally, humid zones (South China/Central-Southern) demonstrate peak accuracy at SPEI-12 (R2 ≈ 0.90, RMSE < 0.35), while arid regions (Northwest Desert/Qinghai-Tibet Plateau) show dramatic improvement from SPEI-1 (R2 < 0.35, RMSE > 1.0) to SPEI-12 (R2 > 0.85, RMSE reduction > 52%). Multivariate probability density analysis confirms the model’s robustness through enhanced capture of nonlinear atmospheric-land interactions and reduced parameterization uncertainties via swarm intelligence optimization. The CPSO-XGBoost’s superiority stems from synergistic optimization: binary particle swarm feature selection enhances input relevance while adaptive parameter tuning improves computational efficiency, collectively addressing climate variability challenges across diverse terrains. These findings establish an advanced computational framework for drought early warning systems, providing critical support for climate-resilient water management and agricultural risk mitigation through spatiotemporally adaptive predictions. Full article
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13 pages, 1674 KiB  
Article
Urban Environmental Predictors of Group Size in Cliff Swallows (Petrochelidon pyrrhonota): A Test Using Community-Science Data
by Cassie Rueda and Kevin J. McGraw
Birds 2025, 6(2), 17; https://doi.org/10.3390/birds6020017 - 3 Apr 2025
Viewed by 235
Abstract
Due to continuing worldwide urban expansion, research into how urban environments affect local flora/fauna has grown significantly. Studies on the impacts of urbanization on birds have explored a wide variety of behaviors (e.g., foraging, breeding, migratory), but there is little research on the [...] Read more.
Due to continuing worldwide urban expansion, research into how urban environments affect local flora/fauna has grown significantly. Studies on the impacts of urbanization on birds have explored a wide variety of behaviors (e.g., foraging, breeding, migratory), but there is little research on the impacts of cities on avian coloniality. Various urban-environmental factors may impact colonial birds. The predominance of impervious surfaces in cities, for example, has been associated with the decline of several bird species due to negative effects on availability and quality of habitat. The urban heat island effect and shifts in resource availability (e.g., food, water) may also affect colonial birds. Here, we used five years of community-science data available in eBird to investigate urban impacts on group size in Cliff Swallows (Petrochelidon pyrrhonota), an abundant colonial bird species that now breeds readily under bridges and other built structures over or near water in Phoenix, Arizona, USA. We hypothesized that, based on the colonial breeding habits of these neotropical migratory birds in this desert environment, swallows in Phoenix would form larger groups in areas with more food and water sources and with more built structures. In fact, we found that proximity to water sources and cropland, but not impervious surface density, was positively and significantly related to group size. These results suggest that, in this desert ecosystem, an abundance of food/water resources provided by humans permits Cliff Swallows to form larger social groups during breeding. Although many studies show harmful impacts of cities on local wildlife, our findings highlight how urban and/or agricultural ‘oases’ may relieve some native species from natural resource limitations and permit them to thrive and increase in group size in human-impacted environments. Full article
(This article belongs to the Special Issue Resilience of Birds in Changing Environments)
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20 pages, 3381 KiB  
Article
From Ordinary to Extraordinary: The Crucial Role of Common Species in Desert Plant Community Stability with Arbuscular Mycorrhizal (AM) Fungi Under Increased Precipitation
by Zhanquan Ji, Qianqian Dong, Rong Yang, Wenhao Qin, Yi Peng and Yangyang Jia
Plants 2025, 14(7), 1099; https://doi.org/10.3390/plants14071099 - 2 Apr 2025
Viewed by 384
Abstract
Climate change is altering precipitation patterns in Central Asia’s arid zones, destabilizing desert ecosystems. Arbuscular mycorrhizal (AM) fungi, key soil microorganisms forming symbiosis with most plants, critically maintain ecosystem stability, yet their mechanisms in regulating individual plant species to sustain community stability remain [...] Read more.
Climate change is altering precipitation patterns in Central Asia’s arid zones, destabilizing desert ecosystems. Arbuscular mycorrhizal (AM) fungi, key soil microorganisms forming symbiosis with most plants, critically maintain ecosystem stability, yet their mechanisms in regulating individual plant species to sustain community stability remain unclear. We conducted a 5-year in situ experiment in the Gurbantunggut Desert, testing how AM fungi influence desert plant community stability under increased precipitation. Using a randomized block design with three treatments—control (CK), increased precipitation (W), and precipitation with Benomyl fungicide (BW)—we monitored plant community dynamics. We discovered that both increased precipitation and AM fungi altered plant community structure without affecting diversity. Precipitation boosted aboveground net primary productivity (ANPP) and density, enhancing community stability via dominant species (e.g., Meniocus linifolius), supporting the mass ratio hypothesis. AM fungi further stabilized the community by increasing ANPP and enhancing the common species stability under increased precipitation, while the contribution of rare species was also non-negligible, aligning with the subordinate insurance hypothesis. Overall, our study elucidates how increased precipitation and AM fungi regulate plant community stability at the species level. Specifically, it overcomes key gaps by revealing AM fungi’s pivotal role in stabilizing communities through sustaining common species stability. Full article
(This article belongs to the Section Plant Ecology)
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20 pages, 7508 KiB  
Article
Spatiotemporal Pattern of Soil Moisture and Its Association with Vegetation in the Yellow River Basin
by Jiahui Xia, Junliang Jin, Shanshui Yuan, Liliang Ren, Fang Ji, Shanhu Jiang, Yi Liu and Xiaoli Yang
Water 2025, 17(7), 1028; https://doi.org/10.3390/w17071028 - 31 Mar 2025
Viewed by 176
Abstract
Soil moisture (SM) plays a crucial role in the hydrological and ecological processes of the Yellow River Basin (YRB), with its spatiotemporal distribution and variability serving as key factors for understanding ecosystem responses to environmental changes. However, previous research has often overlooked the [...] Read more.
Soil moisture (SM) plays a crucial role in the hydrological and ecological processes of the Yellow River Basin (YRB), with its spatiotemporal distribution and variability serving as key factors for understanding ecosystem responses to environmental changes. However, previous research has often overlooked the spatiotemporal variation of SM across different soil layers and the complex bidirectional interactions between SM and vegetation, particularly as indicated by the Normalized Difference Vegetation Index (NDVI), within different vegetation zones and soil layers. Widely used in fields such as agriculture and water cycle research, the GLDAS dataset has been applied to analyze the spatiotemporal patterns of SM at four different depths (0–10 cm, 10–40 cm, 40–100 cm, and 100–200 cm) in the YRB from 1948 to 2022, revealing a continuous increase in SM over time, with more pronounced changes after identified breakpoints (1985 for the 10–40 cm layer, and 1986 for the other layers). Granger causality tests show that the bidirectional interaction between NDVI and SM dominates across all soil layers and regions, far surpassing the unidirectional effects of SM on NDVI or vice versa. Regardless of whether SM or NDVI is the primary variable, the Temperate Evergreen Broadleaf Forest (TEBF) region consistently exhibits the strongest lag effects across all layers, followed by the Qinghai-Tibet Plateau Alpine Vegetation (QTPAV) and the Temperate Desert Region (TDR). The Subtropical Warm Temperate Deciduous Forest (SWTDF) and Temperate Grassland Region (TGR) show the weakest lag effects. This research offers new insights into the mutual feedback between vegetation and hydrology in the YRB and provides a scientific basis for more effective water resource management. Full article
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20 pages, 4073 KiB  
Article
Effects of Relative Precipitation Changes on Soil Microbial Community Structure in Two Alpine Grassland Ecosystems
by Jianyu Xiao, Zhishu Wang, Fusong Han, Shaolin Huang, Chengqun Yu and Gang Fu
Agronomy 2025, 15(4), 851; https://doi.org/10.3390/agronomy15040851 - 29 Mar 2025
Viewed by 318
Abstract
Precipitation variability profoundly influences soil microbial diversity, community assembly processes, and co-occurrence networks. However, the responses of soil microbial structure to relative precipitation changes in alpine regions remain uncertain. To address this, we conducted a two-year field precipitation manipulation experiment in alpine steppe [...] Read more.
Precipitation variability profoundly influences soil microbial diversity, community assembly processes, and co-occurrence networks. However, the responses of soil microbial structure to relative precipitation changes in alpine regions remain uncertain. To address this, we conducted a two-year field precipitation manipulation experiment in alpine steppe and alpine desert steppe ecosystems at the source of the Yarlung Zangbo River on the Tibetan Plateau. The experiment simulated 25%, 50%, and 75% increases and decreases in precipitation to examine how soil microbial communities respond to altered precipitation regimes. Our results reveal that microbial responses varied with precipitation magnitude, grassland type, and microbial kingdom. In the alpine steppe, bacterial α-diversity exhibited a negative asymmetric response to altered precipitation at both species and phylogenetic levels. Both bacterial and fungal species α-diversity tended to respond more strongly to changes in precipitation at high gradients in the alpine steppe than in the alpine desert steppe. Microbial co-occurrence networks in the alpine steppe were generally more responsive to altered precipitation than those in the alpine desert steppe. Furthermore, fungal α-diversity at both species and phylogenetic levels, as well as β-diversity, responded more strongly to altered precipitation than bacterial communities. These findings suggest that precipitation-driven shifts in microbial community composition and network structure vary across alpine grassland ecosystems, with fungal communities exhibiting greater sensitivity than bacterial communities. As warming intensifies precipitation variability, these microbial shifts may have cascading effects on soil biogeochemical processes and ecosystem stability, underscoring the necessity for ecosystem-specific conservation frameworks and adaptive management strategies tailored to alpine grasslands. Full article
(This article belongs to the Section Grassland and Pasture Science)
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17 pages, 4170 KiB  
Article
The Effects of Inoculation with Rhizosphere Phosphate-Solubilizing Bacteria on the Growth and Physiology of Reaumuria soongorica Seedlings Under NaCl Stress
by Xueying Wang, Peifang Chong, Xinguang Bao and Feng Zhang
Forests 2025, 16(4), 591; https://doi.org/10.3390/f16040591 - 28 Mar 2025
Viewed by 207
Abstract
Soil salinization significantly exacerbates the deficiency in plant-available phosphorus in the soil, thereby adversely affecting plant growth and development. Through various processes, phosphate-solubilizing bacteria in the rhizosphere significantly increase soil-soluble phosphorus content, boosting plant development and stress resistance. This study focused on annual [...] Read more.
Soil salinization significantly exacerbates the deficiency in plant-available phosphorus in the soil, thereby adversely affecting plant growth and development. Through various processes, phosphate-solubilizing bacteria in the rhizosphere significantly increase soil-soluble phosphorus content, boosting plant development and stress resistance. This study focused on annual R. soongorica seedlings to examine how rhizosphere phosphate-solubilizing bacteria enhance growth under NaCl-induced stress conditions. This study isolated and characterized rhizosphere phosphate-solubilizing bacteria, evaluating their phosphate solubilization capacity and effects on R. soongorica seedling growth and physiology under NaCl stress through pot experiments, with potential applications in saline soil improvement and desert ecosystem restoration. This study used four treatment groups (control group, NaCl treatment group, bacterial inoculation treatment group, and bacterial and NaCl mixed-treatment group) with twelve treatments and four replicates per treatment. The experimental results demonstrated that five phosphate-solubilizing bacterial strains exhibited a significant phosphate solubilization capacity, accompanied by a notable reduction in pH within the inorganic phosphorus medium. Compared to the NaCl treatment, the net growth of the plant height of R. soongorica seedlings inoculated with strains J23, J24, and M1 under NaCl stress increased significantly (p < 0.05), and all of them more than doubled, and the net growth of the stem diameter of R. soongorica seedlings inoculated with strain J24 increased significantly by 144.17%. The physiological characteristics of R. soongorica seedlings demonstrated significant alterations following inoculation with the five phosphate-solubilizing bacterial strains. The inoculation of R. soongorica seedlings with the five phosphate-solubilizing bacterial resulted in a statistically significant increase in both foliar total phosphorus content and available phosphorus levels within the rhizosphere soil (p < 0.05). Additionally, under NaCl stress conditions, R. soongorica seedlings inoculated with the five phosphate-solubilizing bacterial strains exhibited varying degrees of salt tolerance, with the following descending order of effectiveness: J24 > P2 > J23 > P3 > M1. In conclusion, the rhizosphere phosphate-solubilizing bacteria J24 represents a potentially valuable microbial resource for saline soil amelioration, demonstrating the most pronounced enhancement in both the growth parameters and salt tolerance of R. soongorica seedlings under 300 mmol·L−1 NaCl stress. Full article
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