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运用IBIS模型估测东北东部森林生态系统碳动态的模拟

Carbon Dynamics Simulation in the Eastern Part of Northeast Forest Ecosystems in China Using Ibis

【作者】 刘曦

【导师】 国庆喜;

【作者基本信息】 东北林业大学 , 生态学, 2011, 博士

【摘要】 集成生物圈模型(Integrated Biosphere Simulator, IBIS)属于陆面生物圈-动态植被耦合模型。集成了大范围的生物物理、生理以及生态学过程,并且与大气环流模式(AGCMs)进行耦合,能够模拟变化复杂的、时间跨度从秒到数百年的生物圈过程,属于新一代全球生物圈模型DGVMs (Dynamic Global Vegetation Models),代表着全球碳循环模拟的研究方向。本文在IBIS原有模型的基础上,对帽儿山生态站不同植被类型净第一性生产力(NPP)、土壤呼吸(Rs)和气象条件(温度temperature和降水precipitation),进行IBIS的初步运行和调试,应用生态站多年的研究成果为模型提供参数,进行修改和验证。继而从点到面,针对东北东部地区研究现状,利用修正后的IBIS模型对当地气候条件和碳动态进行模拟,分析该研究地区森林生态系统碳动态的时间和空间规律。并根据政府间气候变化专门委员会(IPCC)第3次评估报告的权威预测,确定本研究未来气候情景,分析碳通量对气候变化和植被参数(LAI)的敏感性。通过研究,所得主要结论如下:1.模型修正方面:结合我国东北地区情况,保留了原模型中12种植物功能型其中的8种,15种植物群落类型其中的7种。不考虑土壤加速程序,凋落物碳库直接赋值,使模型得以简化,并更加符合土壤达到平衡状态时的实际情况。2.模型验证方面:IBIS模型能够较好的模拟生长季温度和降水,但对非生长季尤其是初春和冬季温度和降雨(雪)模拟不足。对不同植被类型年均NPP、GPP和土壤呼吸季节动态变化的模拟误差均小于众文献。因此,IBIS模型的模拟结果总体上反映了东北东部森林生态系统的NPP、GPP和土壤呼吸的实际情况,表明了该模型在本区域内的适用性。3.Rs模拟方面:受大气温度和降水的共同影响,土壤呼吸表现出比较明显的季节变化特征。夏季是土壤呼吸最为强烈的时期也是全年土壤呼吸变异率最大的季节,平均占全年Rs52-57%,是冬季土壤呼吸值的十几倍-几十倍。随着季节的变化,根系呼吸贡献率也呈现出季节动态,变化曲线趋向于复合函数,最小值出现在4月和5月间,最大值出现在10月份。本研究的根系自养呼吸贡献率高于Raich分析假定的30%贡献率。根系自养呼吸是土壤呼吸的主要部分,高于异养呼吸。自养呼吸模拟值均处于大部分温带森林研究结果0.122-0.663kg Cm-2a-1之内,异养呼吸的模拟值低于大部分温带森林Rh研究结果0.31-0.692kg Cm-2a-1,这可能是造成土壤呼吸低估的主要原因。不同植被类型2年间的土壤呼吸平均取值及变化范围存在较大差异,除常绿针叶林2005年土壤呼吸低于2004年3.1%外,其余土壤呼吸值均高于前一年。不同生态系统之间的Rs存在显著性差异,针阔叶混交林土壤呼吸是所有植被类型中呼吸值最高的,约为最低值兴安落叶松林的2倍多。土壤Rs空间分布随降水量与温度分布呈现区域异质性。降雨量低于465mm或年平均气温低于-3℃成为生态系统呼吸的限制性因子。4.NPP模拟方面:在本研究中,运用IBIS模拟了2004和2005年2年间的NPP变化情况,结果表明NPP具有比较明显的季节变化特征。夏季NPP是全年最高的季节,平均占全年NPP的53%-70%,最低值出现在冬季,春季NPP变化最剧烈。2005年NPP较2004年有不同程度的升高,变化幅度因植被类型而有所差异,2年间NPP的平均水平来看,以针阔叶混交林NPP最高,达0.89kg Cm-2a-1,杂木林最低,为0.68kg C m-2a-1。2年间针叶林NPP与GPP比值介于0.36-0.56,阔叶林0.25-0.56,介于Waring et al.1998数据之内。NPP空间分布随降水量与温度分布呈现区域异质性。总体上研究区域中部植被NPP较高,南北差异较大。年均温度低于-3℃或降水量低于465mm成为该地区植被生长的限制性因子。不同森林植被由于NPP以及异养呼吸差异,NEP也存在很大变化,以针阔叶混交林为之最,NEP平均值介于0.72-0.74kg Cm-2a-1,硬阔叶林最小,平均值为0.47-0.53kg Cm-2a-1。5.敏感性研究方面:1)LAI。不同植被类型,不论LAI如何增减变化,NPP均降低,Rs及其分量Ra、Rh反之。所有植被类型NPP、Rs、Ra和Rh对LAI变化5%最敏感,敏感性指数均高于0.2;2)温度。升温促进NPP增长,但不是无限制的增长,存在升温阈值,本研究的阈值温度为3℃,NPP对温度升高并不敏感,敏感性指数低于0.1,土壤呼吸和根系呼吸对温度变化中度敏感,敏感性指数介于0.1-0.2,并随温度升高幅度加大,敏感性增强,对升温3℃最为敏感。异养呼吸对温度变化很敏感,敏感性指数先降低,后升高,介于2.07-2.61。3)降水量。与NPP成正相关,对比降水量增加和降低的不同情况,NPP对降水量降低更为敏感(常绿针叶林和落叶松林除外),敏感性指数大多在0.2以上。不同植被类型土壤呼吸都对降雨增加10%和降低5%反应更为敏感,其中针叶林对降雨量变化敏感性高于阔叶混交林。自养呼吸对降水变化的敏感指数不如异养呼吸高,但也大多超过0.1,甚至在0.2以上达到中度敏感或极敏感程度,自养呼吸与异养呼吸随降雨量的不同变化,说明两种呼吸方式对水分要求的差异,这也为土壤呼吸大区域范围内的估算提出了难题。6.未来气候情景下森林碳通量的模拟研究:1)升温降水量减少。NPP值均降低。2)升温降水量增加,大部分绿色植被NPP升高(常绿针叶,针阔叶混交林和兴安落叶松林除外)。土壤呼吸在各个气候情境下均表现出升高的趋势,气候变化对土壤呼吸作用更明显,这与Griffis等研究结果相同。

【Abstract】 Integrated Biosphere Simulator (IBIS) is designed to integrate a variety of terrestrial ecosystem phenomena within a single, physically consistent model that can be directly incorporated within AGCMs. It belongs to a new generation of dynamic global vegetation models (DGVMs), which can simulate complexity and long time biosphere processes. Also IBIS represents the future trends of carbon model development.Based on original IBIS framework, we simulated net primary production (NPP), soil respiration (Rs) and climate conditions (temperature and precipitation) in Maoer Mountain Natural Reservoir Station and compared these simulations with observed data set, thus parameters and biogeochemical processes in IBIS were modified. Scaling-up from point scale to regional scale, forest ecosystem carbon dynamics and climate conditions were simulated in Northeast China by the modified IBIS, also temporal and spatial distribution variations were evaluated. Under model sensitivity analysis, climate scenarios were set here to evaluate effect of climate change and vegetation cover (LAI) on carbon balance according to the third authority report of IPCC. Main results are listed as below:1. Model modification. Eight plant functional types were derived form the original twelve, as well as seven vegetation types from fifteen according to the vegetation characteristics of our study area. Soil spin-up procedure in belowground carbon&nitrogen cycling module is not considered in this modified IBIS. Litter carbon pools were evaluated directly to make a model simplification and totally accorded with the real conditions of soil balance.2. Model validation. IBIS simulated well with the precipitation and temperature in growing season, but little agreement with climate variety in late spring and winter. Modeled errors of NPP, GPP and soil respiration in seasonal dynamics were smaller than these reported literatures. Overall, modified IBIS can represent the real dynamics of NPP, GPP and soil respiration in Northeast China and applied carbon simulation in the study area.3. Rs. Two years of Rs variation in2004and2005were simulated, results showed that:Rs had a great seasonal pattern since the highest Rs in summer, persisting52-57%of the total yearly Rs value, the lowest in winter. Contribution ratio (RC) of autotrophic respiration (Ra) showed a clear seasonal patterns also, which can be expressed by a compound function. RCmin occured in April and May, while RCmax in October. RC was much higher than30%reported by Raich. Compared to heterotrophic respiration (Rh), Ra persisted a higher value. Simulated Ra falls in0.122-0.663kg Cm-2a-1conducted by a lot of temperate forests, Rh, was much lower compared to0.31-0.692kg Cm-2a-1, which maybe the reason for low soil respiration simulation. Rs in different ecosystems showed a great variation, broadleaf-conifer mixed forest persisted the highest value of Rs, while larch forest the lowest. Rs spatial pattern was dependent on the spatial variations in T and P. When P was less than465mm, and T was less than-3℃, ecosystem respiration was restricted.4.NPP. Two years of NPP variation in2004and2005were simulated, results showed that: NPP had a great seasonal pattern since the highest NPP in summer, persisting53-70%of the total yearly NPP, the lowest in winter and the most obvious change in spring. NPP values in2005were much higher than that in2004, with different changing expend in various vegetation types. Broadleaf-conifer mixed forest had the highest NPP,0.89kg C m-2a-1, mixed forest the lowest,0.68kg C m-a-1. NPP to GPP ratio for evergreen coniferous forest fell in0.36-0.56, broadleaf in0.25-0.56, which accorded well with Waring et al.1998. NPP spatial pattern was dependent on the spatial variations in T and P. When P was less than460mm, and T was less than-3℃, vegetation growth was restricted. Broadneadle leaf mixed forest maintained the biggest NEP, with the avegrage ranging from0.72to0.74kg C m-2a-1, while hardleaf forest the least, ranging from0.47-0.53kg C m-2a-15. Sensitivity analysis.1) LAI. Responses of NPP, Rs, Ra, Rh, to the variations of LAI input showed that NPP decreased with LAI increasing or decreasing, as Rs, Ra, and Rh, on the contrary.2) Temperature. Vegetation growth can be accelerated by temperature increasing, but exhibit a threshold (+3℃observed in our research). NPP was not sensitive to temperature various, with sensitivity index (SI) less than0.1. Responses of Rs, and Ra to temperature were mediate with SI between0.1and0.2. Rh was very sensitive to temperature variations with SI increasing first and then decreasing, SI were between2.07-2.61.3) Precipitation. NPP was more sensitivity to precipitation decreasing than to increasing, with SI more than0.2. Rs in different species was more sensitive to precipitation various with+10%and-5%, with higher SI in coniferous forest than in broadleaf forest. Response of Ra to precipitation variations was less than Rh, but SI degree reached media or maximum. The different responses of Ra and Rh to precipitation, explained a diverse requirement of Ra and Rh to precipitation, which gives a big challenge in regional soil respiration simulation.6. Carbon dynamic simulating under the future climate scenarios.1) Temperature increased with precipitation decreased. NPP decreased under this climate scenario.2) Both temperature and precipitation increased, NPP for most vegetation types were increased, with evergreen conifer, broadleaf-conifer and larch forest except. Rs increased under both of the above climate scenarios. Climate change had more effect on Rs than on NPP, this agreed well with the result of Griffis et al.

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