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Ge X, Ding J, Amantai N, Xiong J, Wang J. Responses of vegetation cover to hydro-climatic variations in Bosten Lake Watershed, NW China. FRONTIERS IN PLANT SCIENCE 2024; 15:1323445. [PMID: 38689846 PMCID: PMC11058830 DOI: 10.3389/fpls.2024.1323445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 03/26/2024] [Indexed: 05/02/2024]
Abstract
Amidst the backdrop of global climate change, it is imperative to comprehend the intricate connections among surface water, vegetation, and climatic shifts within watersheds, especially in fragile, arid ecosystems. However, these relationships across various timescales remain unclear. We employed the Ensemble Empirical Mode Decomposition (EEMD) method to analyze the multifaceted dynamics of surface water and vegetation in the Bosten Lake Watershed across multiple temporal scales. This analysis has shed light on how these elements interact with climate change, revealing significant insights. From March to October, approximately 14.9-16.8% of the areas with permanent water were susceptible to receding and drying up. Both the annual and monthly values of Bosten Lake's level and area exhibited a trend of initial decline followed by an increase, reaching their lowest point in 2013 (1,045.0 m and 906.6 km2, respectively). Approximately 7.7% of vegetated areas showed a significant increase in the Normalized Difference Vegetation Index (NDVI). NDVI volatility was observed in 23.4% of vegetated areas, primarily concentrated in the southern part of the study area and near Lake Bosten. Regarding the annual components (6 < T < 24 months), temperature, 3-month cumulative NDVI, and 3-month-leading precipitation exhibited the strongest correlation with changes in water level and surface area. For the interannual components (T≥ 24 months), NDVI, 3-month cumulative precipitation, and 3-month-leading temperature displayed the most robust correlation with alterations in water level and surface area. In both components, NDVI had a negative impact on Bosten Lake's water level and surface area, while temperature and precipitation exerted positive effects. Through comparative analysis, this study reveals the importance of temporal periodicity in developing adaptive strategies for achieving Sustainable Development Goals in dryland watersheds. This study introduces a robust methodology for dissecting trends within scale components of lake level and surface area and links these trends to climate variations and NDVI changes across different temporal scales. The inherent correlations uncovered in this research can serve as valuable guidance for future investigations into surface water dynamics in arid regions.
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Affiliation(s)
- Xiangyu Ge
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, China
- Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China
- Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi, China
| | - Jianli Ding
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, China
- Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China
- Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi, China
| | - Nigenare Amantai
- Institute of Ecology, College of Urban and Environmental Sciences, Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing, China
| | - Ju Xiong
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, China
- Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China
- Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi, China
| | - Jingzhe Wang
- Institute of Applied Artificial Intelligence of the Guangdong-Hong Kong-Macao Greater Bay Area, Shenzhen Polytechnic University, Shenzhen, China
- School of Artificial Intelligence, Shenzhen Polytechnic University, Shenzhen, China
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Yan C, Hao H, Wang Z, Sha S, Zhang Y, Wang Q, Kang Z, Huang L, Wang L, Feng H. Prediction of Suitable Habitat Distribution of Cryptosphaeria pullmanensis in the World and China under Climate Change. J Fungi (Basel) 2023; 9:739. [PMID: 37504728 PMCID: PMC10381404 DOI: 10.3390/jof9070739] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 07/04/2023] [Accepted: 07/07/2023] [Indexed: 07/29/2023] Open
Abstract
Years of outbreaks of woody canker (Cryptosphaeria pullmanensis) in the United States, Iran, and China have resulted in massive economic losses to biological forests and fruit trees. However, only limited information is available on their distribution, and their habitat requirements have not been well evaluated due to a lack of research. In recent years, scientists have utilized the MaxEnt model to estimate the effect of global temperature and specific environmental conditions on species distribution. Using occurrence and high resolution ecological data, we predicted the spatiotemporal distribution of C. pullmanensis under twelve climate change scenarios by applying the MaxEnt model. We identified climatic factors, geography, soil, and land cover that shape their distribution range and determined shifts in their habitat range. Then, we measured the suitable habitat area, the ratio of change in the area of suitable habitat, the expansion and shrinkage of maps under climate change, the direction and distance of range changes from the present to the end of the twenty-first century, and the effect of environmental variables. C. pullmanensis is mostly widespread in high-suitability regions in northwestern China, the majority of Iran, Afghanistan, and Turkey, northern Chile, southwestern Argentina, and the west coast of California in the United States. Under future climatic conditions, climate changes of varied intensities favored the expansion of suitable habitats for C. pullmanensis in China. However, appropriate land areas are diminishing globally. The trend in migration is toward latitudes and elevations that are higher. The estimated area of possible suitability shifted eastward in China. The results of the present study are valuable not only for countries such as Morocco, Spain, Chile, Turkey, Kazakhstan, etc., where the infection has not yet fully spread or been established, but also for nations where the species has been discovered. Authorities should take steps to reduce greenhouse gas emissions in order to restrict the spread of C. pullmanensis. Countries with highly appropriate locations should increase their surveillance, risk assessment, and response capabilities.
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Affiliation(s)
- Chengcai Yan
- Key Laboratory of Integrated Pest Management (IPM) of Xinjiang Production and Construction Corps in Southern Xinjiang, College of Agronomy, Tarim University, Alar 843300, China
- Scientific Observing and Experimental Station of Crop Pests in Alar, Ministry of Agriculture, College of Agronomy, Tarim University, Alar 843300, China
- The National and Local Joint Engineering Laboratory of High Efficiency and Superior-Quality Cultivation and Fruit Deep Processing Technology of Characteristic Fruit Trees in Southern Xinjiang, Alar 843300, China
| | - Haiting Hao
- Key Laboratory of Integrated Pest Management (IPM) of Xinjiang Production and Construction Corps in Southern Xinjiang, College of Agronomy, Tarim University, Alar 843300, China
- Scientific Observing and Experimental Station of Crop Pests in Alar, Ministry of Agriculture, College of Agronomy, Tarim University, Alar 843300, China
- The National and Local Joint Engineering Laboratory of High Efficiency and Superior-Quality Cultivation and Fruit Deep Processing Technology of Characteristic Fruit Trees in Southern Xinjiang, Alar 843300, China
| | - Zhe Wang
- Key Laboratory of Integrated Pest Management (IPM) of Xinjiang Production and Construction Corps in Southern Xinjiang, College of Agronomy, Tarim University, Alar 843300, China
- Scientific Observing and Experimental Station of Crop Pests in Alar, Ministry of Agriculture, College of Agronomy, Tarim University, Alar 843300, China
- The National and Local Joint Engineering Laboratory of High Efficiency and Superior-Quality Cultivation and Fruit Deep Processing Technology of Characteristic Fruit Trees in Southern Xinjiang, Alar 843300, China
| | - Shuaishuai Sha
- Key Laboratory of Integrated Pest Management (IPM) of Xinjiang Production and Construction Corps in Southern Xinjiang, College of Agronomy, Tarim University, Alar 843300, China
- Scientific Observing and Experimental Station of Crop Pests in Alar, Ministry of Agriculture, College of Agronomy, Tarim University, Alar 843300, China
- The National and Local Joint Engineering Laboratory of High Efficiency and Superior-Quality Cultivation and Fruit Deep Processing Technology of Characteristic Fruit Trees in Southern Xinjiang, Alar 843300, China
| | - Yiwen Zhang
- Key Laboratory of Integrated Pest Management (IPM) of Xinjiang Production and Construction Corps in Southern Xinjiang, College of Agronomy, Tarim University, Alar 843300, China
- Scientific Observing and Experimental Station of Crop Pests in Alar, Ministry of Agriculture, College of Agronomy, Tarim University, Alar 843300, China
- The National and Local Joint Engineering Laboratory of High Efficiency and Superior-Quality Cultivation and Fruit Deep Processing Technology of Characteristic Fruit Trees in Southern Xinjiang, Alar 843300, China
| | - Qingpeng Wang
- Key Laboratory of Integrated Pest Management (IPM) of Xinjiang Production and Construction Corps in Southern Xinjiang, College of Agronomy, Tarim University, Alar 843300, China
- Scientific Observing and Experimental Station of Crop Pests in Alar, Ministry of Agriculture, College of Agronomy, Tarim University, Alar 843300, China
| | - Zhensheng Kang
- Key Laboratory of Integrated Pest Management (IPM) of Xinjiang Production and Construction Corps in Southern Xinjiang, College of Agronomy, Tarim University, Alar 843300, China
- State Key Laboratory of Crop Stress Biology for Arid Areas, Northwest A&F University, Yangling 712100, China
- Yangling Seed Industry Innovation Center, Northwest A&F University, Yangling 712100, China
| | - Lili Huang
- Key Laboratory of Integrated Pest Management (IPM) of Xinjiang Production and Construction Corps in Southern Xinjiang, College of Agronomy, Tarim University, Alar 843300, China
- State Key Laboratory of Crop Stress Biology for Arid Areas, Northwest A&F University, Yangling 712100, China
- Yangling Seed Industry Innovation Center, Northwest A&F University, Yangling 712100, China
| | - Lan Wang
- Key Laboratory of Integrated Pest Management (IPM) of Xinjiang Production and Construction Corps in Southern Xinjiang, College of Agronomy, Tarim University, Alar 843300, China
- Scientific Observing and Experimental Station of Crop Pests in Alar, Ministry of Agriculture, College of Agronomy, Tarim University, Alar 843300, China
- The National and Local Joint Engineering Laboratory of High Efficiency and Superior-Quality Cultivation and Fruit Deep Processing Technology of Characteristic Fruit Trees in Southern Xinjiang, Alar 843300, China
| | - Hongzu Feng
- Key Laboratory of Integrated Pest Management (IPM) of Xinjiang Production and Construction Corps in Southern Xinjiang, College of Agronomy, Tarim University, Alar 843300, China
- Scientific Observing and Experimental Station of Crop Pests in Alar, Ministry of Agriculture, College of Agronomy, Tarim University, Alar 843300, China
- The National and Local Joint Engineering Laboratory of High Efficiency and Superior-Quality Cultivation and Fruit Deep Processing Technology of Characteristic Fruit Trees in Southern Xinjiang, Alar 843300, China
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