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林业科学 ›› 2019, Vol. 55 ›› Issue (3): 13-21.doi: 10.11707/j.1001-7488.20190302

• 论文与研究报告 • 上一篇    下一篇

气候变化情景下河北省3个优势树种适宜分布区预测

吕振刚, 李文博, 黄选瑞, 张志东   

  1. 河北农业大学林学院 河北省林木种质资源与森林保护重点实验室 保定 071000
  • 收稿日期:2018-04-24 修回日期:2019-01-03 出版日期:2019-03-25 发布日期:2019-04-17
  • 基金资助:
    林业公益性行业科研专项(20150430304);国家自然科学基金项目(31370636)。

Predicting Suitable Distribution Area of Three Dominant Tree Species under Climate Change Scenarios in Hebei Province

Lü Zhengang, Li Wenbo, Huang Xuanrui, Zhang Zhidong   

  1. Hebei Province Key Laboratory of Forest Trees Germplasm Resources and Forest Protection College of Forestry, Agricultural University of Hebei Baoding 071000
  • Received:2018-04-24 Revised:2019-01-03 Online:2019-03-25 Published:2019-04-17

摘要: [目的]探究河北省3个优势树种分布与气候因子的关系,并进行适宜分布区预测,以期为评估气候变化的影响及制定适宜未来气候变化的森林经营策略提供理论依据。[方法]依据河北省森林资源调查数据,选取华北落叶松、蒙古栎和油松这3个主要树种,采用ClimateAP气候模型生成当前及未来(2040—2069年和2070—2099年)与降水和温度相关的10个气候因子,利用MaxEnt生态位模型和基于3个气候变化情景(温室气体最低排放,RCP2.6;中度稳定排放,RCP4.5;高度排放,RCP8.5)的一致性预测,模拟3个树种当前和未来的潜在适宜分布区,并采取响应曲线分析主要气候因子对3个树种适宜分布区的影响。[结果] 3个树种MaxEnt模型的受试者工作特征曲线下面积(AUC值)都大于0.85,具有较好的预测能力;当前3个树种主要适宜分布在燕山和太行山地区;影响3个树种分布的主导气候因子存在差异,华北落叶松主要受小于0℃年积温和湿季降水量的影响,蒙古栎则主要受最热月平均气温、Hargreaves水分亏缺和湿季降水量的影响,而最热月平均气温、湿季降水量、大于5℃年积温和年均气温是影响油松分布的主要气候因子;一致性预测表明,在2040—2069年,河北省华北落叶松分布面积明显扩大,蒙古栎分布面积变化较小,而油松分布面积显著缩小;在2070—2099年,3个树种的适宜分布面积都显著缩小,幅度均超过3%。[结论]随着气候变化,3个树种均有向高海拔地区迁移的趋势,但在经纬度方向上的分布变化不大。在未来3个树种的适宜分布区,采取人工手段(如造林)辅助树种扩散以适应气候变化,有利于提高森林生产力,构建健康稳定的森林生态系统。

关键词: 气候变化, 生态位模型, 华北落叶松, 油松, 蒙古栎

Abstract: [Objective] Exploring the relationship between geographical distributions of tree species and climatic factors, and predicting their suitable distribution area are essential steps for assessing the impact of climate change on forests and for providing a theoretical basis for developing adaptive forest management strategies.[Method]Based on the forest inventory data of Hebei Province, three tree species including Larix principis-rupprechtii, Quercus mongolica and Pinus tabulaeformis were selected. Ten climatic factors related to precipitation and temperature for current and two future periods (2040-2069 and 2070-2099) were achieved using a high-resolution climate model, i.e., ClimateAP. Moreover, the ecological niche model (MaxEnt) and three climate change scenarios (the lowest, moderate, and highest greenhouse gas emission scenarios:RCP2.6, RCP4.5, and RCP8.5) were applied to predict the consensual suitable distribution area of the three tree species in current and two future periods. Response curves method was used to analyze the influence of major climatic factors on the suitable distribution area of the three tree species.[Result]Results showed that the area under the receiver operating characteristics curves (AUC) for all the studied three tree species were more than 0.85, indicating MaxEnt model had a highly predictive performance. Currently these tree species were mainly distributed in the regions of Yanshan and Taihang Mountains in Hebei Province. The main climatic factors affecting the potential distribution of the three tree species were different. Larix principis-rupprechtii was mainly affected by the accumulative temperature below 0℃ and the mean precipitation of wet quarter; while Quercus mongolica was mainly influenced by the mean temperature of the warmest month. Hargreaves climatic moisture deficit and mean precipitation of wet quarter; and Pinus tabulaeformis was mainly affected by the mean temperature of the warmest month, the mean precipitation of wet quarter, the accumulative temperature above 5℃ and the mean annual temperature. Consensus projections for 2040-2069 indicated suitable areas for Larix principis-rupprechtii and Pinus tabulaeformis would substantially expand and decrease, respectively; while Quercus mongolica would remain relatively stable. Consensus projections for 2070-2099 indicated that suitable climate habitats for all these tree species would reduce significantly and the reduction range would exceed 3% in Hebei Province.[Conclusion]The results confirmed that the geographical distribution of these tree species might change under changing climate in the future. All these tree species showed an upward shift in elevation of the projected distribution, whilst no clear shift in latitude and longitude in the two future periods. Reforestation and afforestation could be an option in adaptive forest resource management to assist these species in expanding their migration to new suitable areas in the future. The above-mentioned adaptive strategy might be useful for improving forest productivity and maintaining a healthy forest ecosystem.

Key words: climate change, niche model, Larixprincipis-rupprechtii, Pinus tabulaeformis, Quercus mongolica

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