摘要
植物分布与气候之间的关系是预估未来气候变化对生态系统影响的实现基础。以往的物种分布模型通常以物种的分布区或者分布点的物种存在数据作为物种分布的响应变量。相较于物种存在数据,多度反映了一个物种占用资源并把资源分配给个体的能力,更能衡量物种对区域生态系统的影响。该研究通过野外调查获取了华北及周边地区1045个样方的栎属树木多度,利用广义线性模型、广义加性模型和随机森林模型模拟栓皮栎(Quercus variabilis)、麻栎(Q.acutissima)、槲栎(Q.aliena)、锐齿槲栎(Q.aliena var.acuteserrata)和蒙古栎(Q.mongolica)5个树种多度的地理分布及未来2个不同时期(2050年和2070年)的潜在分布。结果表明:随机森林模型对5个栎属树种的多度的拟合结果要优于广义线性模型和广义加性模型;典型浓度路径(RCP)8.5下的5个栎属树种在未来两个时期的多度变化幅度都要大于RCP2.6下的变化,在超过一半面积的区域中麻栎、槲栎、锐齿槲栎和蒙古栎的多度减少,其中内蒙古东北部和黑龙江北部地区是5种栎属植物多度减少的集中分布地区。未来气候变化背景下,需要加强对这几个区域的监测与物种保护。
Aims To develop a statistically appropriate species distribution model for the abundance of five species from Quercus in the northern China,and to predict the change of abundance under climate change.Methods We surveyed abundance data of five Quercus species from 1045 plots in the northern China,and then fit the abundance with climatic variables using random forest model(RF).We then predict the abundance of these five Quercus species in 2050 and 2070 under Representation Concentration Pathways(RCP)2.6 and 8.5.Important findings The change magnitudes of abundance for all 5 species under RCP 8.5 were larger than under RCP 2.6.Except for Quercus variabilis,abundances of other four species declined under climate change to 2050 and 2070 in more than half of the current distribution areas.Moreover,the northeastern part of Nei Mongol and the northern part of Heilongjiang will be the hotspots of decrease of abundance.Therefore,it is necessary to strengthen the monitoring and species protection in the areas mentioned above with the increasing threaten of climate change.
作者
张雪皎
高贤明
吉成均
康慕谊
王仁卿
岳明
张峰
唐志尧
ZHANG Xue-Jiao;GAO Xian-Ming;JI Cheng-Jun;KANG Mu-Yi;WANG Ren-Qing;YUE Ming;ZHANG Feng;TANG Zhi-Yao(Institute of Ecology,College of Urban and Environmental Sciences,Laboratory for Earth Surface Processes of the Ministry of Education,Peking University,Beijing 100871,China;State Key Laboratory of Vegetation and Environmental Change,Institute of Botany,Chinese Academy of Sciences,Beijing 100093,China;State Key Laboratory of Earth Surface Processes and Resource Ecology,Beijing Normal University,Beijing 100875,China;College of Resources Science&Technology,Faculty of Geographical Science,Beijing Normal University,Beijing 100875,China;School of Life Sciences,Shandong University,Jinan 250100,China;Key Laboratory of Resource Biology and Biotechnology in Western China,Ministry of Education,Northwest University,Xi’an 710069,China;Institute of Loess Plateau,Shanxi University,Taiyuan 030006,China)
出处
《植物生态学报》
CAS
CSCD
北大核心
2019年第9期774-782,共9页
Chinese Journal of Plant Ecology
基金
国家科技基础性工作专项(2011FY110300和2015FY210200)~~
关键词
广义线性模型
广义加性模型
随机森林模型
物种分布模型
generalized linear model
generalized additive model
random forest model
species distribution model
