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DOI:10.12357/cjea.20230665
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基于MaxEnt模型分析青藏高原青稞适生区对气候变化的响应
赵佳丽1, 兰措卓玛1, 王伟1, 王寒冬2, 王稳3, 沈纪萍1
1.青海大学;2.中国科学院西北高原生物研究所;3.青海大学省部共建三江源生态与高原农牧业国家重点实验室
摘要:  青藏高原对气候变化的响应十分敏感,研究长时间序列气候变化对青藏高原青稞适生区的影响可以为高原农业应对气候变化和优化青稞种植空间格局提供参考。本文以163份青藏高原青稞样点为研究对象,运用ArcGIS软件和最大熵模型(MaxEnt)对其进行模拟预测,得到影响青藏高原青稞分布的主要环境因子和在气候变化下古气候时期(末次间冰期、末次冰盛期、全新世中期)、当代(1970年-2000年)、未来100年ssp126和ssp585两种情景下青稞在青藏高原的分布范围以及空间格局变化。结果表明:(1)影响青稞分布最关键的环境因子是年降水量、年平均气温、最干季度平均温度和海拔,当气候处于不稳定和极端干冷化情况下,海拔控制青稞适生区面积。(2)从末次间冰期到全新世中期再到当代,青稞适生区面积增大,逐渐扩张到青藏高原东北部的河湟谷地、东南缘的川西地区和藏南谷地的一江两河流域,到未来,青稞适生区向高原中部和北部扩张,东南部面积在缩减。(3)在气候变化条件下,青稞适生区质心点向高纬度、高海拔地区移动,并且在未来青稞适生区海拔上限增加207m。结合其他研究可得出,从末次冰期到全新世,青稞种植区发生扩张受制于气候暖湿化和人类在高原定居并进行农牧业传播的双重影响;从当代到未来100年,青稞潜在适生区发生扩张可能是由于气候变暖使得种植青稞的海拔上限提高,青稞潜在适生区缩减可能是由于一些气候突变事件导致气温变化幅度超过了青稞发育的最适温度。
关键词:  气候变化  青藏高原  青稞适生区  最大熵模型
中图分类号:S512;S162
基金项目:国家自然科学基金项目(42261030)
Response of Qinghai Tibet Plateau Highland Barley adaptation area to climate change based on Maximum Entropy Model analysis
Zhao Jiali1, Lancuo Zhuoma1, Wangwei1, Wang Handong2, Wangwen3, Shen Jiping1
1.Qinghai University;2.Northwest Plateau Biology Institute, Chinese Academy of Sciences;3.State Key Laboratory of Sanjiangyuan Ecology and Plateau Agriculture and Animal Husbandry jointly built by Qinghai University
Abstract:  The response of the Qinghai Tibet Plateau to climate change is very sensitive. Studying the impact of long-term climate change on the suitable areas for highland barley cultivation in the Qinghai Tibet Plateau can provide a reference for plateau agriculture to respond to climate change and optimize the spatial pattern of highland barley cultivation. This article takes 205 highland barley samples from the Qinghai Tibet Plateau as the research object and uses ArcGIS software and the Maximum Entropy Model to simulate and predict them. The main environmental factors that affect the distribution of highland barley on the Qinghai Tibet Plateau, as well as the paleo climatic periods (Last Interglacial, Last Glacial Maximum, Mid Holocene), contemporary (1970-2000) The distribution range and spatial pattern changes of highland barley in the Qinghai Tibet Plateau under two scenarios of ssp126 and ssp585 in the next 100 years. The results indicate that: (1) The most critical environmental factors affecting the distribution of highland barley are annual precipitation, annual average temperature, average temperature in the driest quarter, and altitude. When the climate is unstable and extremely dry and cold, altitude controls the suitable area for highland barley growth. (2) From the last interglacial period to the mid-Holocene and then to the present era, the area of suitable areas for highland barley has increased, gradually expanding to the Hehuang Valley in the northeast of the Qinghai Tibet Plateau, the western Sichuan region in the southeast margin, and the one river and two river basins in the southern Tibetan Valley. In the future, the suitable areas for highland barley will expand towards the central and northern parts of the plateau, while the area in the southeast will decrease. (3) Under the conditions of climate change, the centroid of the suitable growth area for barley is moving towards high latitude and altitude areas, and the upper limit of altitude in the future suitable growth area for barley will increase by 207m.. Combined with other studies, it can be concluded that from the last glacial period to the Holocene, the expansion of barley planting areas was constrained by the dual effects of climate warming and humidification, as well as human settlement on the plateau and the spread of agriculture and animal husbandry; From the present to the next 100 years, the expansion of potential suitable areas for barley cultivation may be due to the increase in altitude limit caused by climate warming, while the reduction of potential suitable areas for barley cultivation may be due to some climate change events causing temperature changes to exceed the optimal temperature for barley development.
Keyword:  Climate change  Qinghai-Tibet Plateau  Suitable growth area for highland barley  MaxEnt model
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