气候变化情景下基于最大熵模型的青海云杉潜在分布格局模拟

Abstract

PDF HTML阅读 XML下载 导出引用 引用提醒 气候变化情景下基于最大熵模型的青海云杉潜在分布格局模拟 DOI: 10.5846/stxb201809151999 作者: 作者单位: 甘肃农业大学林学院,兰州大学生命科学学院,甘肃农业大学林学院,甘肃农业大学林学院 作者简介: 通讯作者: 中图分类号: 基金项目: 甘肃农业大学科技创新基金-公招博士科研启动基金项目（GSAU-RCZX01707）；学科建设专项基金项目（GAU-XKJS-2018-099）；国家自然基金项目（31860197） Simulation of the potential distribution patterns of Picea crassifolia in climate change scenarios based on the maximum entropy (Maxent) model Author: Affiliation: Gansu Agricultural University, Lanzhou 730070 Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:青海云杉（Picea crassifolia）是我国青藏高原东北缘特有树种，在维系我国西北地区生态平衡、水土保持、水源涵养和生物多样性等方面发挥着重要作用。基于其分布范围内的69个地理分布样点，利用最大熵（Maxent）模型对现实气候条件下青海云杉的潜在分布及其分布的主导气候因子进行分析，同时结合3种大气环流模型模拟青海云杉在3种气候变化情景（温室气候排放量不同）下未来2050s和2080s潜在分布区的变化。结果表明：Maxent模型对青海云杉潜在分布区的预测具有极高的准确度，所有模型的平均受试者工作特征曲线下面积（AUC测试值）均高于0.99；Jackknife检验和气候因子响应曲线表明年最低降雨量是限制青海云杉分布的主导因子；当前青海云杉的潜在分布区主要集中于青海东部、甘肃东南部、宁夏大部分地区、西藏东部、四川西部山区以及陕西、新疆和内蒙古部分地区。在未来3种增温情景下，青海云杉在2050s和2080s的潜在分布总面积与当前相比变化不明显，但不同适生等级的潜在分布面积变化较大，其中，中度适生区和低度适生区受气候增温影响显著，中度增温下这些区域在2080s的面积明显增大，而高度适生区（核心分布）则在所有增温情景下均呈缩小趋势。同时，在未来3种增温情景下，青海云杉在2050s和2080s的潜在分布区有向北移动趋势，但其心分布区域（高度适生区）仍然以青海东部、甘肃北部为主，无明显变迁趋势。从气候因素角度考虑，本研究表明未来气候变化情景下，青海云杉依然在西部高山地区，特别是作为我国重要生态屏障的祁连山、贺兰山等山区具有重要的经济价值并将持续其生态服务功能。 Abstract:Qinghai spruce (Picea crassifolia) is the endemic tree species in the northeastern margin of the Qinghai-Tibet Plateau (QTP) in China. It plays an important role in maintaining ecological balance, biodiversity, and soil and water conservation in northwestern China. In this study, the current potential distribution of Qinghai spruce and its dominant climatic factors were analyzed firstly based on 69 distributional records via the maximum entropy model (Maxent). Then the distribution patterns of Qinghai spruce under three climate change scenarios (i.e., the lowest, a moderate, and the highest greenhouse gas emission scenarios; RCP2.6, RCP4.5 and RCP8.5) with three general atmospheric circulation models were predicted by Maxent for two future decades:the 2050s and 2080s. The results showed that the accuracy of the Maxent model was pretty high for modeling potential distribution regions of Qinghai spruce, and the average values of the area under the receiver operator characteristic curve (AUC) were higher than 0.99. The results from the Jackknife test and climate factor response curves revealed that the annual lowest precipitation is the key factor that limited the distribution of Qinghai spruce; the current potential distribution regions of Qinghai spruce are mainly concentrated in eastern Qinghai, southeastern Gansu, most of Ningxia, eastern Tibet, mountainous areas of western Sichuan, and parts of Shaanxi, Xinjiang, and Inner Mongolia. The total potential distribution area of Qinghai spruce in the 2050s and 2080s was changed little compared to the current distribution in all three scenarios, but its potential distribution area at different levels of fitness was changed a lot. Among them, the regions with fitness of less than 0.1 and in the range of 0.1-0.3 were significantly affected by the climate changes, and their area was largely increased in the medium emission scenario. In contrast, the regions with fitness in the range of 0.5-0.8 were shrunk in all scenarios. At the same time, the distribution patterns of Qinghai spruce in the 2050s and 2080s had a tendency to move northward in all scenarios, whereas its central distributional regions (more suitable regions) were still kept in eastern Qinghai and northern Gansu, with no obvious trend to change. From the perspective of climatic factors, this study showed that Qinghai spruce would continue to have important economic values and ecological service functions in the western mountains, especially in the Qilian Mountains and Helan Mountains, which are the important ecological barriers in China. 参考文献 相似文献 引证文献