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Keywords = change pattern of desertification

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22 pages, 3382 KiB  
Article
Communities of Arbuscular Mycorrhizal Fungi and Their Effects on Plant Biomass Allocation Patterns in Degraded Karst Grasslands of Southwest China
by Wangjun Li, Xiaolong Bai, Dongpeng Lv and Yurong Yang
J. Fungi 2025, 11(7), 525; https://doi.org/10.3390/jof11070525 - 16 Jul 2025
Viewed by 274
Abstract
The biomass allocation patterns between aboveground and belowground are an essential functional trait for plant survival under a changing environment. The effects of arbuscular mycorrhizal fungi (AMF) communities on plant biomass allocation, particularly in degraded Festuca ovina grasslands in ecologically fragile karst areas, [...] Read more.
The biomass allocation patterns between aboveground and belowground are an essential functional trait for plant survival under a changing environment. The effects of arbuscular mycorrhizal fungi (AMF) communities on plant biomass allocation, particularly in degraded Festuca ovina grasslands in ecologically fragile karst areas, remain unclear. Therefore, we conducted a field investigation combined with a greenhouse experiment to explore the importance of AMF compared to bacteria and fungi for plant biomass allocation. The results showed that plant biomass in degraded grasslands exhibited allometric biomass allocation, contrasting with isometric partitioning in non-degraded grasslands. AMF, not bacteria or fungi, were the primary microbial mediators of grassland degradation effects on plant biomass allocation based on structural equation modeling. The greenhouse experiment demonstrated that the selected AMF keystone species from the field study performed according to ecological network analysis, particularly multi-species combinations, enhanced the belowground biomass allocation of F. ovina under rocky desertification stress compared to single-species inoculations, through decreasing soil pH, enhancing alkaline phosphatase (ALP) activity, and increasing the expression level of AMF-inducible phosphate transporter (PT4). This study highlights the critical role of the AMF community, rather than individual species, in mediating plant survival strategies under rocky desertification stress. Full article
(This article belongs to the Section Environmental and Ecological Interactions of Fungi)
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17 pages, 4669 KiB  
Article
Effect of Caragana korshinskii Plantation Succession on Community Stability in Alpine Sandy Regions
by Zhengchen Shi, Li Ma, Zhonghua Zhang, Honglin Li, Dengxian Wei, Xuebin Zhao, Ruimin Qin, Hongye Su, Shan Li, Xue Hu, Haze Ade and Huakun Zhou
Agriculture 2025, 15(11), 1143; https://doi.org/10.3390/agriculture15111143 - 26 May 2025
Viewed by 311
Abstract
Climate change and intensified human activities have led to plant degradation and land desertification in desert areas, which seriously threaten ecological security. The establishment of the Caragana korshinskii plantation is considered to be one of the important means to improve the ecological environment [...] Read more.
Climate change and intensified human activities have led to plant degradation and land desertification in desert areas, which seriously threaten ecological security. The establishment of the Caragana korshinskii plantation is considered to be one of the important means to improve the ecological environment in thealpine sandy region. This study focuses on Caragana korshinskii plantation in the alpine sandy region of the Qinghai–Tibet Plateau. Adopting a space-for-time substitution approach, six restoration chrono sequences were selected: 0 years, 5 years, 15 years, 25 years, 35 years, and 50 years. By investigating the variations in vegetation community composition and soil properties, we aim to elucidate the plant and soil system interactions under different restoration durations. The findings will clarify the stability evolution patterns of Caragana korshinskii plantation during desertification control and contribute to promoting green development strategies. The main conclusions of this study are as follows: With the passage of planting time, the plant biomass and species diversity of the Caragana korshinskii plantation community showed a trend of first increasing and then decreasing, reaching their peak in 25~35 years. Soil water content exhibited fluctuating trends, while soil organic matter showed progressive accumulation, demonstrating that Caragana korshinskii plantations effectively improved soil fertility. Community stability reaches its maximum (4.98) at 25 years. In summary, the Caragana korshinskii plantation are in an early stage of ecological secondary succession, with plant communities developing from simple to complex structures and gradually approaching, though not yet achieving a stable state. Full article
(This article belongs to the Special Issue Research on Soil Carbon Dynamics at Different Scales on Agriculture)
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17 pages, 6051 KiB  
Article
Construction and Analysis of the Ecological Security Pattern in Territorial Space in Shaanxi of the Yellow River Basin, China
by Zhengyao Liu, Jing Huang, Xiaokang Liu, Yonghong Li and Yiping He
Atmosphere 2025, 16(2), 217; https://doi.org/10.3390/atmos16020217 - 14 Feb 2025
Cited by 2 | Viewed by 603
Abstract
In the context of rapid urbanization and extreme climate change globally, balancing ecological resources and economic development for land spatial planning has become one of the pressing issues that need to be addressed. This study proposes a composite model to construct a spatial [...] Read more.
In the context of rapid urbanization and extreme climate change globally, balancing ecological resources and economic development for land spatial planning has become one of the pressing issues that need to be addressed. This study proposes a composite model to construct a spatial ecological security pattern. It identifies restoration areas with different risk levels based on the spatial distribution of land use, offering suggestions for optimizing spatial configuration. Focusing on the central Shaanxi region of the Yellow River Basin in China, ecological sources are identified by integrating ecological factors, and ecological corridors and restoration zones are extracted using the minimum cumulative resistance difference and circuit theory. The results indicate significant improvements in ecological quality and desertification in the study area from 2000 to 2020. Currently, the core area covers 51,649.71 km2, accounting for 62.18% of all landscape types; the total ecological source area covers 31,304.88 km2, representing 18.84% of the entire area. These ecological source areas are mainly distributed in the northern Loess Plateau and the southern mountainous regions. The area has 26 important ecological corridors, identifying 16 ecological pinch points and 12 ecological barriers, presenting an ecological security pattern characterized by a grid-like structure in the northern region and a dispersed pattern in the southern region. Additionally, 273.72 km2 of ecological restoration priority areas and 197.98 square kilometers of ecological restoration encouragement areas are proposed as key planning regions for ecological environmental protection. This study provides references for optimizing spatial configuration to promote the sustainable development of urban and rural living environments in the Yellow River Basin. Full article
(This article belongs to the Special Issue Desert Climate and Environmental Change: From Past to Present)
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21 pages, 7834 KiB  
Article
Modeling and Nonlinear Analysis of Plant–Soil Moisture Interactions for Sustainable Land Management: Insights for Desertification Mitigation
by Ge Kai, Yongquan Han, Necdet Sinan Özbek, Wensai Ma, Yaze Liu, Gengyun He, Xinyu Zhao and Yangquan Chen
Sustainability 2025, 17(3), 1327; https://doi.org/10.3390/su17031327 - 6 Feb 2025
Viewed by 871
Abstract
This research explores the dynamics of vegetation patterns under changing environmental conditions, considering the United Nations Sustainable Development Goal 15: “Protect, restore, and promote the sustainable use of terrestrial ecosystems; combat desertification; halt and reverse land degradation; and prevent biodiversity loss”. In this [...] Read more.
This research explores the dynamics of vegetation patterns under changing environmental conditions, considering the United Nations Sustainable Development Goal 15: “Protect, restore, and promote the sustainable use of terrestrial ecosystems; combat desertification; halt and reverse land degradation; and prevent biodiversity loss”. In this context, this study presents a modeling and nonlinear analysis framework for plant–soil-moisture interactions, including Holling-II functional response and hyperbolic mortality models. The primary goal is to explore how nonlinear soil–water interactions influence vegetation patterns in semi-arid ecosystems. Moreover, the influence of nonlinear soil–water interaction on the establishment of population patterns is investigated. The formation and evolution of these patterns are explored using theoretical analysis and numerical simulations, as well as important factors and critical thresholds. These insights are crucial for addressing desertification, a key challenge in semi-arid regions that threatens biodiversity, ecosystem services, and sustainable land management. The model, which includes environmental parameters such as rainfall, plant growth rates, and soil moisture, was tested using both theoretical analysis and numerical simulations. These characteristics are carefully adjusted to find important thresholds influencing the danger of desertification. Simulation scenarios, run under set initial conditions and varying parameters, yield useful insights into the pattern of patch development under dynamically changing environmental conditions. The findings revealed that changes in environmental conditions, such as rainfall and plant growth rates, prompted Hopf bifurcation, resulting in the production of three distinct patterns: a dotted pattern, a striped pattern, and a combination of both. The creation of these patterns provides essential information about the sustainability of environmental equilibrium. The variation curve of the average plant biomass reveals that the biomass fluctuates around a constant period, with the amplitude initially increasing, then decreasing, and gradually stabilizing. This research provides a solid foundation for addressing desertification risks, using water resources responsibly, and contributing to a better understanding of ecosystem stability. Full article
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32 pages, 10860 KiB  
Article
Combining the SHAP Method and Machine Learning Algorithm for Desert Type Extraction and Change Analysis on the Qinghai–Tibetan Plateau
by Ruijie Lu, Shulin Liu, Hanchen Duan, Wenping Kang and Ying Zhi
Remote Sens. 2024, 16(23), 4414; https://doi.org/10.3390/rs16234414 - 25 Nov 2024
Cited by 2 | Viewed by 1380
Abstract
For regional desertification control and sustainable development, it is critical to quickly and accurately understand the distribution pattern and spatial and temporal changes of deserts. In this work, five different machine learning algorithms are used to classify different desert types on the Qinghai–Tibetan [...] Read more.
For regional desertification control and sustainable development, it is critical to quickly and accurately understand the distribution pattern and spatial and temporal changes of deserts. In this work, five different machine learning algorithms are used to classify different desert types on the Qinghai–Tibetan Plateau (QTP), and their classification performance is evaluated on the basis of their classification results and classification accuracy. Then, on the basis of the best classification model, the Shapely Additive Explanations (SHAP) method is used to clarify the contribution of each classification feature to the identification of desert types during the machine learning classification process, both globally and locally. Finally, the independent and interactive effects of each factor on desert change on the Qinghai-Tibetan Plateau during the study period are quantitatively analyzed via geodetector. The main results are as follows: (1) Compared with other classification algorithms (GTB, CART, KNN, and SVM), the RF classifier achieves the best performance in classifying QTP desert types, with an overall accuracy (OA) of 87.11% and a kappa coefficient of 0.83. (2) From the perspective of the overall classification of deserts, the five features, namely, elevation, slope, VV, VH, and GLCM, contribute most significantly to the features. In terms of the influence of each classification feature on the extraction of different types of deserts, the radar backscattering coefficient VV serves the most important role in distinguishing sandy deserts; the VH is helpful in distinguishing the four types of deserts: rocky desert, alpine cold desert, sandy deserts, and loamy desert; slope is more effective in distinguishing between the two desert types (rocky desert and alpine cold desert) and other types of deserts; and elevation has a significant role in the identification of alpine cold deserts; and the short-wave infrared band SR_B7 has an important role in the identification of salt crusts and saline deserts. (3) During the study period, the QTP deserts exhibited a reversing trend, and the proportion of desert area decreased from 28.62% to 26.20%. (4) Compared with other factors, slope, precipitation, elevation, vegetation type, and the human footprint have greater effects on changes in the QTP desert area, and the interactions among the factors affecting changes in the desert area all show bidirectional enhancement or nonlinear enhancement effects. Full article
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17 pages, 5372 KiB  
Article
Ecological Importance Evaluation and Ecological Function Zoning of Yanshan-Taihang Mountain Area of Hebei Province
by Pengtao Zhang, Qixuan Duan, Jie Dong, Lichao Piao and Zhaoyang Cui
Sustainability 2024, 16(23), 10233; https://doi.org/10.3390/su162310233 - 22 Nov 2024
Cited by 1 | Viewed by 950
Abstract
Ecological importance evaluation can clearly identify the ecological service functions and ecological values of a region. This paper takes the Yanshan-Taihang Mountain area in Hebei Province as the research area, utilizing 2020 land use data. With the help of various analytical models and [...] Read more.
Ecological importance evaluation can clearly identify the ecological service functions and ecological values of a region. This paper takes the Yanshan-Taihang Mountain area in Hebei Province as the research area, utilizing 2020 land use data. With the help of various analytical models and GIS spatial analysis methods, this paper selects water conservation, soil and water conservation, biodiversity, carbon sequestration and oxygen release to evaluate the importance of ecosystem services, and selects soil and water loss sensitivity and land desertification sensitivity to evaluate the ecological sensitivity, so as to identify the important areas of ecological protection in the study area, analyze their spatial change characteristics and divide the leading ecological functions according to the results. The results show that the moderately important and highly important areas in the Yanshan-Taihang region of Hebei Province account for more than 70% of the total study area. Based on the importance evaluation results, three types of dominant ecological function zones were obtained using self-organized feature mapping neural network analysis in the R language, and control measures were proposed. The research results can provide strategic support for local ecological protection and regional ecological restoration, as well as serving as a reference for the optimization of land spatial development patterns. Full article
(This article belongs to the Section Soil Conservation and Sustainability)
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16 pages, 9480 KiB  
Article
Assessing Climate and Land-Use Change Scenarios on Future Desertification in Northeast Iran: A Data Mining and Google Earth Engine-Based Approach
by Weibo Yin, Qingfeng Hu, Jinping Liu, Peipei He, Dantong Zhu and Abdolhossein Boali
Land 2024, 13(11), 1802; https://doi.org/10.3390/land13111802 - 31 Oct 2024
Viewed by 1254
Abstract
Desertification poses a significant threat to dry and semi-arid regions worldwide, including Northeast Iran. This study investigates the impact of future climate and land-use changes on desertification in this region. Six remote sensing indices were selected to model desertification using four machine learning [...] Read more.
Desertification poses a significant threat to dry and semi-arid regions worldwide, including Northeast Iran. This study investigates the impact of future climate and land-use changes on desertification in this region. Six remote sensing indices were selected to model desertification using four machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), and Generalized Linear Models (GLM). To enhance the model’s reliability, an ensemble model was employed. Future climate and land-use scenarios were projected using the CNRM-CM6 model and Markov chain analysis, respectively. Results indicate that the RF and SVM models performed best in mapping current desertification patterns. The ensemble model highlights a 2% increase in decertified areas by 2040, primarily in the northwestern regions. The study underscores the importance of land-use change and climate change in driving desertification and emphasizes the need for sustainable land management practices and climate change adaptation strategies to mitigate future impacts. Full article
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18 pages, 6419 KiB  
Article
Quantifying the Contributions of Vegetation Dynamics and Climate Factors to the Enhancement of Vegetation Productivity in Northern China (2001–2020)
by Kaixuan Liu, Xufeng Wang and Haibo Wang
Remote Sens. 2024, 16(20), 3813; https://doi.org/10.3390/rs16203813 - 14 Oct 2024
Cited by 2 | Viewed by 1483
Abstract
Vegetation dynamics are critical to the terrestrial carbon and water cycle, with China recognized as one of the largest contributors to global greening due to significant variations in forest coverage. However, distinguishing the effects of vegetation changes from those of climate factors on [...] Read more.
Vegetation dynamics are critical to the terrestrial carbon and water cycle, with China recognized as one of the largest contributors to global greening due to significant variations in forest coverage. However, distinguishing the effects of vegetation changes from those of climate factors on vegetation productivity remains challenging. This study conducted a comprehensive analysis of vegetation productivity in Northwest China over the past two decades, focusing on the spatiotemporal patterns and drivers of gross primary production (GPP) within ecological restoration areas. Using trend analysis and ridge regression models, we assessed the relative contributions of climate factors and vegetation coverage changes to GPP dynamics. The results revealed a significant increase in both the GPP and vegetation coverage in Northern China from 2001 to 2020, with GPP rising by 6.7 g C m−2 yr−1 and forest coverage increasing by 0.08% per year. A strong positive correlation (r = 0.9) was observed between vegetation coverage changes and GPP. The increase in GPP was driven by both climate factors and changes in forest coverage, with climate factors contributing 61.0% and vegetation coverage changes contributing 39.0%. Among the climate factors, radiation, temperature, and precipitation contributed 15.4%, 6.4%, and 39.2%, respectively. The study highlights the critical role of ecological restoration efforts, particular in regions like the Less Plateau and Inner Mongolian Plateau, in enhancing vegetation productivity. These findings provide valuable insights for addressing desertification and inform strategies for ecological restoration and sustainable development in Northern China. Full article
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21 pages, 14551 KiB  
Article
Detection of the Evolution Process of Desertification in Gulang County Based on Long Series and Similar Time Images
by Panpan Liu, Bing Guo and Rui Zhang
Land 2024, 13(10), 1652; https://doi.org/10.3390/land13101652 - 10 Oct 2024
Cited by 1 | Viewed by 966
Abstract
Previous studies are mostly conducted based on sparse time series and often ignore the dramatic changes in desertification during the year. Utilizing the Landsat and MODIS data sets from 2000 to 2020, this study applied the spatio-temporal fusion algorithm to obtain the images [...] Read more.
Previous studies are mostly conducted based on sparse time series and often ignore the dramatic changes in desertification during the year. Utilizing the Landsat and MODIS data sets from 2000 to 2020, this study applied the spatio-temporal fusion algorithm to obtain the images of the study area taken at similar times in August over the past 20 years. The optimal desertification remote sensing monitoring index of Gulang County was constructed based on the feature space model, and then the spatial and temporal evolution patterns and the driving mechanism of desertification in Gulang County were revealed by using a geographic detector. The research results were as follows: (1) The ESTARFM algorithm had better applicability in constructing long time series and similar time images with the correlation coefficient R2 = 0.83 between the results of the ESTARFM fusion model and the original image; (2) the SWCI-MSAVI feature space desertification monitoring index model based on point-to-point mode had the best applicability with an overall accuracy of 95.39% and a Kappa coefficient of 0.94; (3) from 2000 to 2020, the desertification showed an increasing trend, and the degree of desertification gradually intensified from south to north in Gulang County; (4) the dominant factors in various historical periods were different, which were mainly composed of precipitation, temperature and population density. The dominant interactive factors changed from alternating dominance of natural factors and human activity factors to the co-dominance of natural factors and human activity factors. The research results could provide decision-making support for precise prevention and control of desertification in arid–semi-arid regions. Full article
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24 pages, 45018 KiB  
Article
Change Patterns of Desertification and Its Dominant Influencing Factors in China–Mongolia–Russia Economic Corridor Based on MODIS and Feature Space Model
by Longhao Wang, Bing Guo and Rui Zhang
Land 2024, 13(9), 1431; https://doi.org/10.3390/land13091431 - 4 Sep 2024
Viewed by 1202
Abstract
The desertification of the China–Mongolia–Russia Economic Corridor (CMREC), one of the six major economic corridors in the Belt and Road Initiative, has posed a great challenge to the ecological environment protection and sustainable economic development of the region. In this work, two categories [...] Read more.
The desertification of the China–Mongolia–Russia Economic Corridor (CMREC), one of the six major economic corridors in the Belt and Road Initiative, has posed a great challenge to the ecological environment protection and sustainable economic development of the region. In this work, two categories of feature space models based on point–point mode and point–line mode were constructed. The optimal feature space model was used to establish the spatial–temporal change patterns of desertification in the CMREC from 2001 to 2020, and then the dominant driving factors were quantitatively determined. The conclusions demonstrated the following: (1) the monitoring accuracy of the Albedo–MSAVI desertification model based on point–point mode was the highest, at 86.47%, followed by that of the TGSI–MSAVI model based on point–line mode, at 85.71%; (2) from 2001 to 2020, the spatial distribution of desertification in the China–Mongolia–Russia Economic Corridor region showed a decreasing trend radiating outwards from the Inner Mongolia Plateau and Gobi Desert; (3) the gravity center of desertification in Chinese parts in the CMREC migrated toward the northeast, while the Mongolia and Russia parts migrated toward the southwest and southeast, respectively; and (4) from 2001 to 2020, precipitation and land use change had the greatest impacts on the evolution patterns of desertification in China and Mongolia, while topography and land use contributed greatly to the change process of desertification in Russia. The research results could provide data support for desertification control in the CMREC. Full article
(This article belongs to the Section Land – Observation and Monitoring)
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29 pages, 16629 KiB  
Article
Response of Surface Runoff Evolution to Landscape Patterns in Karst Areas: A Case Study of Yun–Gui Plateau
by Hui Xu, Cunyou Chen, Luyun Liu, Qizhen Li, Baojing Wei and Xijun Hu
Sustainability 2024, 16(17), 7338; https://doi.org/10.3390/su16177338 - 26 Aug 2024
Cited by 1 | Viewed by 1186
Abstract
To control and improve the phenomena of rocky desertification and soil erosion in karst landform areas, which are caused by a series of human factors that include social and economic development and human activities, China has successively introduced many policies, resulting in spatial [...] Read more.
To control and improve the phenomena of rocky desertification and soil erosion in karst landform areas, which are caused by a series of human factors that include social and economic development and human activities, China has successively introduced many policies, resulting in spatial and temporal changes in the landscape pattern of the southern karst area. In this study, land use transfer intensity maps, the grid method, the sample line method, the semivariogram method, and the Spearman analysis method are used to explore the spatial and temporal evolutions in surface runoff as responses to landscape pattern and policy factors in karst landform area. Therefore, this study provides theoretical and policy support for improving the regional landscape structure, optimizing the landscape layout, introducing regional policies, reducing surface runoff, and alleviating soil erosion. The results show that the best scale for the study of landscape patterns in the southern karst area is 3000 m. Forests are the land type that make up the highest proportion in the southern karst area, and they have the strongest interception capacity for surface runoff. The spatial and temporal distributions of the surface runoff are significantly different, and urban expansion has led to an increase in impervious runoff year over year. Runoff is positively correlated with the Shannon diversity index (SHDI), patch density (PD), and landscape shape index (LSI). The stronger the landscape heterogeneity, the more runoff. DIVISION is positively correlated with forest runoff and negatively correlated with other land types. The higher is the degree of aggregation of impervious patches, the higher the regional runoff rate. The more dispersed the forest patches are, the smaller the area proportion, and the greater the runoff. In addition, policy factors have a significant impact on surface runoff. Full article
(This article belongs to the Section Environmental Sustainability and Applications)
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29 pages, 4624 KiB  
Review
Understanding Tree Mortality Patterns: A Comprehensive Review of Remote Sensing and Meteorological Ground-Based Studies
by Filippos Eliades, Dimitrios Sarris, Felix Bachofer, Silas Michaelides and Diofantos Hadjimitsis
Forests 2024, 15(8), 1357; https://doi.org/10.3390/f15081357 - 3 Aug 2024
Cited by 7 | Viewed by 2913
Abstract
Land degradation, desertification and tree mortality related to global climate change have been in the spotlight of remote sensing research in recent decades since extreme climatic events could affect the composition, structure, and biogeography of forests. However, the complexity of tree mortality processes [...] Read more.
Land degradation, desertification and tree mortality related to global climate change have been in the spotlight of remote sensing research in recent decades since extreme climatic events could affect the composition, structure, and biogeography of forests. However, the complexity of tree mortality processes requires a holistic approach. Herein, we present the first global assessment and a historical perspective of forest tree mortality by reviewing both remote sensing and meteorological ground-based studies. We compiled 254 papers on tree mortality that make use of remotely sensed products, meteorological ground-based monitoring, and climatic drivers, focusing on their spatial and temporal patterns and the methods applied while highlighting research gaps. Our core results indicate that international publications on tree mortality are on the increase, with the main hotspots being North America (39%) and Europe (26%). Wetness indicators appear as the barometer in explaining tree mortality at a local scale, while vegetation indicators derived from multispectral optical sensors are promising for large-scale assessments. We observed that almost all of the studies we reviewed were based on less than 25 years of data and were at the local scale. Longer timeframes and regional scale investigations that will include multiple tree species analysis could have a significant impact on future research. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
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27 pages, 21745 KiB  
Article
Semi-Arid to Arid Scenario Shift: Is the Cabrobó Desertification Nucleus Becoming Arid?
by José Lucas Pereira da Silva, Francisco Bento da Silva Junior, João Pedro Alves de Souza Santos, Alexsandro Claudio dos Santos Almeida, Thieres George Freire da Silva, José Francisco de Oliveira-Júnior, George do Nascimento Araújo Júnior, Christopher Horvath Scheibel, Jhon Lennon Bezerra da Silva, João Luís Mendes Pedroso de Lima and Marcos Vinícius da Silva
Remote Sens. 2024, 16(15), 2834; https://doi.org/10.3390/rs16152834 - 2 Aug 2024
Cited by 3 | Viewed by 2256
Abstract
Monitoring areas susceptible to desertification contributes to the strategic development of regions located in environments of extreme hydric and social vulnerability. Therefore, the objective of this study is to evaluate the process of soil degradation in the Desertification Nucleus of Cabrobó (DNC) over [...] Read more.
Monitoring areas susceptible to desertification contributes to the strategic development of regions located in environments of extreme hydric and social vulnerability. Therefore, the objective of this study is to evaluate the process of soil degradation in the Desertification Nucleus of Cabrobó (DNC) over the past three decades using remote sensing techniques. This study used primary climatic data from TerraClimate, geospatial data of land use and land cover (LULC), and vegetation indices (SAVI and LAI) via Google Earth Engine (GEE) from Landsat 5/TM and 8/OLI satellites, and established the aridity index (AI) from 1992 to 2022. The results indicated 10 predominant LULC classes with native vegetation suppression, particularly in agriculture and urbanization. SAVI ranged from −0.84 to 0.90, with high values influenced by La Niña episodes and increased rainfall; conversely, El Niño episodes worsened the rainfall regime in the DNC region. Based on the Standardized Precipitation Index (SPI), it was possible to correlate normal and severe drought events in the DNC with years under the influence of El Niño and La Niña phases. In summary, the AI images indicated that the DNC remained semi-arid and that the transition to an arid region is a cyclical and low-frequency phenomenon, occurring in specific periods and directly influenced by El Niño and La Niña phenomena. The Mann–Kendall analysis showed no increasing trend in AI, with a Tau of −0.01 and a p-value of 0.97. During the analyzed period, there was an increase in Non-Vegetated Areas, which showed a growing trend with a Tau of 0.42 in the Mann–Kendall analysis, representing exposed soil areas. Annual meteorological conditions remained within the climatic pattern of the region, with annual averages of precipitation and actual evapotranspiration (ETa) close to 450 mm and an average temperature of 24 °C, showing changes only during El Niño and La Niña events, and did not show significant increasing or decreasing trends in the Mann–Kendall analysis. Full article
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22 pages, 6697 KiB  
Article
Analysis of Landscape Pattern Evolution and Impact Factors in the Mainstream Basin of the Tarim River from 1980 to 2020
by Lili Jiang and Yating Li
Hydrology 2024, 11(7), 93; https://doi.org/10.3390/hydrology11070093 - 27 Jun 2024
Cited by 3 | Viewed by 1221
Abstract
The mainstream basin of the Tarim River serves as a vital ecological security barrier that prevents the merging and expansion of deserts and an important strategic corridor directly linking Qinghai and Xinjiang. With society’s development and climate change, ecological issues such as river [...] Read more.
The mainstream basin of the Tarim River serves as a vital ecological security barrier that prevents the merging and expansion of deserts and an important strategic corridor directly linking Qinghai and Xinjiang. With society’s development and climate change, ecological issues such as river interruption, vegetation degradation, and land desertification in the basin have notably intensified, and the ecological security is facing a critical test. Exploring the characteristics of landscape changes and their driving factors within the basin is crucial in improving the ecological environment system’s management. Based on land use data from 1980 to 2020, this study analyzed the characteristics of the spatiotemporal changes and pattern evolution of the landscape through a landscape transfer matrix and landscape pattern indices. It further revealed the impact factors of the landscape pattern through canonical correspondence analysis. The results showed that (1) in 1980–2020, the areas of desert, forest, farmland, and settlement landscapes increased, while the area of grassland landscape decreased, and the water landscape showed an “increasing–decreasing–recovery” pattern. The landscape transition types mainly included the transition from grassland to desert; mutual transitions among farmland, grassland, and forests; mutual transitions between water and grassland; and the transition from farmland to settlements. (2) The overall landscape pattern demonstrated increased fragmentation, shape complexity, and evenness with decreased aggregation. Furthermore, different landscapes exhibited distinct characteristics of landscape pattern changes; for instance, grassland landscape showed severe fragmentation, while desert landscape displayed the strongest dominance. (3) The landscape pattern was a result of the combined impact of natural and human factors, with the soil thickness (SOT), road density (ROD), annual actual evapotranspiration (AAE), population density (POD), and mean annual temperature (MAT) exhibiting significant influences. Specifically, the settlement and farmland landscapes were mainly influenced by the mean annual relative humidity (MAH), POD, GDP density (GDP), and distance to artificial water (DAW); the forest, grassland, and water landscapes were mainly influenced by the SOT, soil organic matter content (SOM), AAE, ROD, elevation (ELE), MAT, slope (SLP), and distance to natural water (DNW); and the desert landscape was mainly influenced by the DAW, DNW, SLP, AAE, SOT, SOM, and ROD. These findings can provide a scientific reference for landscape management and restoration, as well as sustainable social and economic development, in the mainstream basin of the Tarim River. Full article
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18 pages, 6909 KiB  
Article
Effects of the Implementation Intensity of Ecological Engineering on Ecosystem Service Tradeoffs in Qinghai Province, China
by Ke Yan, Bingting Zhao, Yuanhui Li, Xiangfu Wang, Jiaxin Jin, Jiang Jiang, Wenting Dong, Rongnv Wang, Hongqiang Yang, Tongli Wang and Weifeng Wang
Land 2024, 13(6), 848; https://doi.org/10.3390/land13060848 - 14 Jun 2024
Cited by 2 | Viewed by 1238
Abstract
Ecological engineering (EE) has a profound impact on land-use dynamics, leading to alterations in ecosystem services (ESs). However, an appropriate EE implementation intensity that can balance the tradeoffs associated with altered ESs well has always been a concern for researchers and policymakers. In [...] Read more.
Ecological engineering (EE) has a profound impact on land-use dynamics, leading to alterations in ecosystem services (ESs). However, an appropriate EE implementation intensity that can balance the tradeoffs associated with altered ESs well has always been a concern for researchers and policymakers. In this study, we set the transition probability of farmland, bare land, and desertification land to forest and natural shrub, with 2010–2020 as the natural implementation scenario, as 10% for the low-intensity implementation scenario (LIS), 30% for the medium-intensity scenario, and 50% for the high-intensity scenario. The patch-generating land-use simulation (PLUS) model was used to project land-use patterns and the Integrated Valuation of Ecosystem Service and Tradeoffs (InVEST) model was used to simulate changes in the quality of ESs under four EE implementation intensities in 2030. We then performed a quantitative tradeoff analysis on the dominant ESs under four scenarios and used the production possibility frontier (PPF) curve to identify the optimal EE implementation intensity scenario. Our results indicated that an increase in EE implementation intensity would lead to an increase in soil retention, water purification, habitat quality, and carbon storage, but also to a decrease in water yield, aggravating the tradeoffs between water yield and other ESs. In all EE implementation intensity scenarios, the LIS had the lowest tradeoff intensity index and balanced ESs well, and thus was the optimal EE implementation scenario in Qinghai province. Our results provide knowledge to help decision makers select the appropriate EE intensity to maintain sustainable development. The integrated methodology can also be applied in other conservation regions to carry out practical land management. Full article
(This article belongs to the Section Land Use, Impact Assessment and Sustainability)
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