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
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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(GPP_(max)),之后随温度的升高而保持不变甚至下降,因此GPP_(max)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GPP_(max)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GPP_(max)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GPP_(max)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GPP_(max)空间变异的最主要因素,GPP_(max)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GPP_(max)。在时间尺度上,对每个森林生态系统GPP_(max)年际变异的对比分析发现,温度是长白山温带针阔混交林GPP_(max)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GPP_(max)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。
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 _(max)imum value( GPP_(max)),and then declines as temperature increases further. Thus,GPP_(max)represents the photosynthetic potential of vegetation at the optimum temperature. However,our understanding on the spatial and temporal patterns and main driving factors of GPP_(max)in forest ecosystems are still limited. In this study,we analyzed the temporal and spatial distribution of GPP_(max)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 GPP_(max) occurring at the optimum temperature in each year for all ecosystems. GPP_(max)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 GPP_(max)across sites,with GPP_(max)decreasing with the increases of temperatur. Solar radiation,precipitation and VPD affected GPP_(max). For the interannual variation of GPP_(max)in each site,GPP_(max)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.
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 _(max)imum value( GPP_(max)),and then declines as temperature increases further. Thus,GPP_(max)represents the photosynthetic potential of vegetation at the optimum temperature. However,our understanding on the spatial and temporal patterns and main driving factors of GPP_(max)in forest ecosystems are still limited. In this study,we analyzed the temporal and spatial distribution of GPP_(max)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 GPP_(max) occurring at the optimum temperature in each year for all ecosystems. GPP_(max)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 GPP_(max)across sites,with GPP_(max)decreasing with the increases of temperatur. Solar radiation,precipitation and VPD affected GPP_(max). For the interannual variation of GPP_(max)in each site,GPP_(max)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.
引文
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于贵瑞,张雷明,孙晓敏.2014.中国陆地生态系统通量观测研究网络(China FLUX)的主要进展及发展展望.地理科学进展.33(7):903-917.
张雷明,曹沛雨,朱亚平,等.2015.长白山阔叶红松林生态系统光能利用率的动态变化及其主控因子.植物生态学报,39(12):1156-1165.
张雷明,于贵瑞,孙晓敏,等.2006.中国东部森林样带典型生态系统碳收支的季节变化.中国科学:地球科学,36(s1):45-59.
张雷明.2006.中国东部南北森林样带典型生态系统碳收支特征及其生理生态学机制(博士学位论文).北京:中国科学院地理科学与资源研究所.
张利平,赵仲辉.2010.会同杉木人工林土壤热通量特征.中南林业科技大学学报,30(5):12-17.
张一平,赵双菊,于贵瑞,等.2005.西双版纳热带季节雨林干热季林冠上小气候特征及CO2通量的观测.生态学报,25(10):2540-2549.
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Baldocchi D,Falge E,Gu LH,et al.2001.FLUXNET:A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide,water vapor,and energy flux densities.Bulletin of the American Meteorological Society,82:2415-2434.
Baldocchi D.2014.Measuring fluxes of trace gases and energy between ecosystems and the atmosphere:The state and future of the eddy covariance method.Global Change Biology,20:3600-3609.
Beer C,Reichstein M,Tomelleri E,et al.2010.Terrestrial gross carbon dioxide uptake:Global distribution and covariation with climate.Science,329:834-838.
Bernacchi CJ,Pimentel C,Long SP.2003.In vivo temperature response functions of parameters required to model Ru BP-limited photosynthesis.Plant,Cell&Environment,26:1419-1430.
Bernacchi CJ,Singsaas EL,Pimentel C,et al.2001.Improved temperature response functions for models of Rubisco-limited photosynthesis.Plant,Cell&Environment,24:253-259.
Booth BBB,Jones CD,Collins M,et al.2012.High sensitivity of future global warming to land carbon cycle processes.Environmental Research Letters,7:24002.
Chu HS,Baldocchi DD,John R,et al.2017.Fluxes all of the time?A primer on the temporal representativeness of FLUXNET.Journal of Geophysical Research:Biogeosciences,122:289-307.
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