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Ma Q, Li Y, Li X, Liu J, Keyimu M, Zeng F, Liu Y. Modeling future changes in potential habitats of five alpine vegetation types on the Tibetan Plateau by incorporating snow depth and snow phenology. Sci Total Environ 2024; 918:170399. [PMID: 38296095 DOI: 10.1016/j.scitotenv.2024.170399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/27/2023] [Accepted: 01/22/2024] [Indexed: 02/13/2024]
Abstract
Although snow cover is a major factor affecting vegetation in alpine regions, it is rarely introduced into ecological niche models in alpine regions. Snow phenology over the Tibetan Plateau (TP) was estimated using a daily passive microwave snow depth dataset, and future datasets of snow depth and snow phenology were projected based on their sensitivity to temperature and precipitation. Furthermore, the potential habitats of five alpine vegetation types on the TP were predicted under two future climate scenarios (SSP245 and SSP585) by using a model with incorporated snow variables, and the driving factors of habitat change were analyzed. The results showed that the inclusion of snow variables improved the prediction accuracy of MaxEnt model, particularly in alpine meadow habitats. By the end of the 21st century, the potential habitats of steppes, meadows, shrubs, deserts, and coniferous forests on the TP will migrate to higher latitudes and altitudes, in which the potential habitats of alpine desert will recede (replaced by alpine steppe), and the potential habitats of other four vegetation types will expand. The random forest importance analysis showed that the recession of potential habitat was mainly driven by the increase in average annual temperature, and the expansion of potential habitat was mainly driven by the increase in precipitation. With the gradual increase in temperature and precipitation in the future, the snow depth and snow cover duration days will decrease, which may further lead to the transition of vegetation types from cold-adapted to warm-adapted on the TP. Our study highlights both that the prediction accuracy of alpine vegetation was improved by incorporating snow variables into the species distribution model, and that a changing climate will likely have a powerful influence on the distribution of alpine vegetation across the TP.
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Affiliation(s)
- Qianqian Ma
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Cele National Station of Observation and Research for Desert Grassland Ecosystems, Cele 848300, Xinjiang, China; Xinjiang Key Laboratory of Desert Plant Roots Ecology and Vegetation Restoration, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanyan Li
- University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Agro-Ecological Processes in Subtropical Region, Changsha Research Station for Agricultural and Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China.
| | - Xiangyi Li
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Cele National Station of Observation and Research for Desert Grassland Ecosystems, Cele 848300, Xinjiang, China; Xinjiang Key Laboratory of Desert Plant Roots Ecology and Vegetation Restoration, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Ji Liu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, Central China Normal University, Wuhan 430079, China
| | - Maierdang Keyimu
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Cele National Station of Observation and Research for Desert Grassland Ecosystems, Cele 848300, Xinjiang, China; Xinjiang Key Laboratory of Desert Plant Roots Ecology and Vegetation Restoration, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fanjiang Zeng
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Cele National Station of Observation and Research for Desert Grassland Ecosystems, Cele 848300, Xinjiang, China; Xinjiang Key Laboratory of Desert Plant Roots Ecology and Vegetation Restoration, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yalan Liu
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Cele National Station of Observation and Research for Desert Grassland Ecosystems, Cele 848300, Xinjiang, China; Xinjiang Key Laboratory of Desert Plant Roots Ecology and Vegetation Restoration, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China
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