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中国东部森林最大总初级生产力的时空分布特征及其影响因子

石旭霞1,宋沼鹏1,侯继华1*,张雷明2,牛书丽2,王安志3,项文化4,王辉民2   

  1. (1北京林业大学林学院, 北京 100083;  2中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室, 北京 100101;3中国科学院沈阳应用生态研究所, 沈阳 110016; 4中南林业科技大学生命科学与技术学院, 长沙 410004)
  • 出版日期:2019-07-10 发布日期:2019-07-10

Spatiotemporal patterns of the maximum primary productivity and driving factors in the eastern China’s forests.

SHI Xu-xia1, SONG Zhao-peng1, HOU Jihua1*, ZHANG Lei-ming2, NIU Shu-li2, WANG An-zhi3, XIANG Wen-hua4, WANG Hui-min2   

  1. (1College of Forestry, Beijing Forestry University, Beijing 100083, China; 2Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; 3Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; 4Faculty of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China).
  • Online:2019-07-10 Published:2019-07-10

摘要: 生态系统碳循环对温度的响应是全球变化生态学的重要研究内容之一。总初级生产力(GPP)随着温度的升高而升高,在最适温下达到最大值(GPPmax),之后随温度的升高而保持不变甚至下降,因此GPPmax代表着最适温度下的植被光合潜力。然而,关于森林生态系统GPPmax的时空分布和影响因子仍不清楚。本文以中国东部南北森林样带(NSTEC)上的长白山温带针阔混交林、会同亚热带杉木人工林、千烟洲亚热带常绿针叶人工林、鼎湖山亚热带常绿针阔混交林和西双版纳热带季雨林等5种典型生态系统为对象,利用涡度相关技术分析森林GPPmax的时空规律及其主要影响因素。结果表明:在所有森林生态系统中,GPP对温度的响应模式均为单峰曲线,最适温下的GPPmax表现为长白山温带针阔混交林>千烟洲亚热带常绿针叶人工林>西双版纳热带季雨林>会同亚热带杉木人工林>鼎湖山亚热带常绿针阔混交林。在所有的站点中,温度是引起GPPmax空间变异的最主要因素,GPPmax随温度的增加而减少。此外,太阳辐射、降水和饱和蒸汽压差也显著影响GPPmax。在时间尺度上,对每个森林生态系统GPPmax年际变异的对比分析发现,温度是长白山温带针阔混交林GPPmax年际变化的主要控制因子,5 cm土壤含水量是影响会同、千烟洲和鼎湖山通量观测系统GPPmax年际变异的主要因子,未发现影响西双版纳热季雨林年际变异的主要因子。本研究有助于理解未来气候变暖背景下GPP的变化趋势,并为中国碳循环的准确模拟提供实验证据和参数依据。

关键词: 连作, 马铃薯, 根系分泌物, 棕榈酸, 邻苯二甲酸二丁酯, 立枯丝核菌

Abstract: The response of ecosystem carbon cycle to temperature is one of the major topics in the research field of global change ecology. The general pattern of the response of gross primary productivity (GPP) to temperature usually shows that GPP increases with temperature at the lower temperature range to reach a maximum value (GPPmax), and then declines as temperature increases further. Thus,GPPmax represents the photosynthetic potential of vegetation at the optimum temperature. However, our understanding on the spatial and temporal patterns and main driving factors of GPPmax in forest ecosystems are still limited. In this study, we analyzed the temporal and spatial distribution of GPPmax and main influencing factors in five typical forest ecosystems based on flux data (temperate coniferous and broad-leaved mixed forest of Changbaishan, subtropical Chinese fir (Cunninghamia lanceolata) plantation of Huitong, subtropical evergreen coniferous forest of Qianyanzhou, subtropical evergreen broadleaf and coniferous mixed forest of Dinghushan, and tropical monsoon forest of Xishuangbanna) along the NorthSouth Transect of Eastern China (NSTEC), which covered tropical, subtropical, and temperate climate zones. The results showed that the temperature response of GPP showed a unimodal pattern, with GPPmax occurring at the optimum temperature in each year for all ecosystems. GPPmax at the optimum temperature in forests were ranked following the order: Changbaishan > Qianyanzhou > Xishuangbanna > Huitong > Dinghushan. Temperature played the most important role in driving the spatial variation of GPPmax across sites, with GPPmax decreasing with the increases of temperatur. Solar radiation, precipitation and VPD affected GPPmax. For the interannual variation of GPPmax in each site, GPPmax in Changbaishan was mainly controlled by air temperature and by soil water content in Huitong, Qianyanzhou, and Dinghushan forests. We failed to find the main factors affecting interannual variation of tropical rainforest in Xishuangbanna. Our results benefit the understanding of GPP variation under climate change and provide evidence and parameter for accurate simulation of carbon cycle.

Key words: continuous cropping, potato, root exudates, palmitic acid, dibutyl phthalate, Rhizoctonia solani.