机构地区:[1]中国林业科学研究院高原林业研究所,昆明650233 [2]中国科学院西双版纳热带植物园、热带森林生态学重点实验室,勐腊666303 [3]国家林业和草原局云南普洱森林生态系统国家定位观测研究站,普洱665000 [4]普洱森林生态系统云南省野外科学观测研究站,普洱665000 [5]西南林业大学,昆明650233 [6]云南云龙天池国家级自然保护区管护局,云龙672700 [7]威远江省级自然保护区管护局,景谷666400
出 处:《林业科学》2024年第11期48-62,共15页Scientia Silvae Sinicae
基 金:国家自然科学基金项目(32201523);科技部科技基础资源调查专项课题(2022FY100201);中国林业科学研究院中央级公益性科研院所基本科研业务费专项(CAFYBB2022SY036);云南省基础研究专项(202301AU070017)。
摘 要:【目的】探究云南高原高山松、云南松和思茅松3种松树径向生长对区域气候因子的响应和适应性特征,为预测气候变化背景下西南林区树木生长动态及各树种地理分布区变化提供指导,为区域森林保护和管理提供理论依据。【方法】根据树木年轮学方法,采集各树种分布区内树轮样本,构建树轮宽度年表,结合各采样点1958—2018年的气温、降水、帕尔默干旱指数等气象资料,利用响应分析、多元回归分析和滑动相关分析等方法,确定影响3种松树径向生长的关键气候因子及其对气候变化的响应差异。【结果】3种松树采样点的气候均呈暖干化特征。限制松树径向生长的关键因子对高山松为当年5月降水量和1月平均气温,其对回归模型方差解释率的贡献分别达59.8%和27.5%;对云南松为上一年10月、12月和当年1月降水量,其对回归模型方差解释率的贡献分别达38.8%、15.4%和25.4%;对思茅松为当年生长季(7月)、上一年和当年生长季后期(9月)降水量,其对回归模型方差解释率的贡献分别达53.8%、30.9%和15.3%。云南松径向生长对干旱的敏感性高于高山松和思茅松。气候暖干化使高山松对生长季初期(5月)气温和降水量的敏感性增强;使云南松对生长季初期(5月)降水量的敏感性减弱,对生长季(8月)气温的敏感性增强;使思茅松对7月平均气温、平均最高温度的敏感性减弱,对上一年生长季后期(9月)降水量的敏感性增强。气候变暖使3种松树径向生长与气候因子的响应关系变得不稳定,主要发生在各采样点气候突变时间段,与区域气候波动同步,且不同树种具有一致性。【结论】高山松和思茅松对干旱的适应性强于云南松。气候变暖使气温对高海拔区高山松径向生长的促进效应减弱,使云南松对生长季初期低降水敏感转变为对生长季低温敏感;气候变暖抑制思茅松生长季充足水分条件�【Objective】This study aims to investigate the response characteristics and adaptability of three main pine species(Pinus densata,Pinus yunnanensis,and Pinus kesiya var.langbianensis)to regional climate change in Yunnan,for guiding the prediction of forest growth dynamics in southwest China in the context of climate change,and providing a theoretical basis for forest protection and management in this area.【Method】According to the standardized dendrochronological methods,tree ring samples were collected in the distribution areas of various tree species to construct tree-ring chronologies.Combined with climate data including temperature,precipitation,and Palmer drought index at each sampling point from 1958 to 2018,response analysis,multiple regression analysis,and moving correlation analysis were used to determine the critical climate factors affecting the radial growth of the three pine species and their differences in response to climate change.【Result】The climate at the sampling sites of the three pine species was warming and drying.The key factors limiting radial growth of P.densata were the precipitation in May and the mean temperature in January,which contributed 59.8%and 27.5%to the variance interpretation rate of the regression model.The critical factors limiting radial growth of P.yunnanensis were the precipitation in October,December of the previous year and January,which contributed 38.8%,15.4%and 25.4%respectively to the variance interpretation rate of the regression model.The critical factors limiting radial growth of P.kesiya var.langbianensis were the precipitation in the current growing season(July),and precipitation in late growing season(September)of the previous year and current year,and their contribution to the variance interpretation rate of the regression model reached 53.8%,30.9%and 15.3%,respectively.The radial growth of P.yunnanensis trees was more sensitive to drought than that of P.densata and P.kesiya var.langbianensis trees.Warming and drying enhanced the sensitivity of P.d
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