喀斯特常绿与落叶阔叶混交林过去50年来的碳循环模拟

通过对Forest-DNDC模型的植被和土壤参数本地化校准,以气象插值数据为输入,模拟了贵州省普定县高原型喀斯特次生常绿与落叶阔叶混交林1965~2014年的土壤、植被和生态系统碳循环特征。结果表明,与冷模拟和实测值相比,参数本地化校准后的模型能更准确地模拟春、秋、冬3个季节的土壤呼吸动态,而模拟的夏季土壤呼吸偏小;但统计检验指出,参数修订后的Forest-DNDC模型能够较好地模拟喀斯特森林土壤呼吸,降低了模拟误差,可用于喀斯特常绿与落叶阔叶混交林碳动态的模拟。进一步分析发现,1965~2014年喀斯特森林的碳通量除模拟早期的前3~4年急剧增加之外,随后总初级生产力(GPP)保持相对稳定,植物呼吸(Rplant)和生态系统呼吸(R_(ecosystem))随着森林发育而增加,土壤呼吸(R_(soil))减少,植被净初级生产力(NPP)呈迅速减小趋势;净生态系统碳交换量(NEE)亦较迅速下降,在2013年达到最低值-0.17 t C/ha,喀斯特森林由碳汇变为弱碳源。相关分析表明,年均温度和年降水对喀斯特常绿与落叶阔叶混交林的GPP和R_(soil)没有显著影响,但却显著影响NPP、R_(plant)、R_(ecosystem)和NEE。     

四川桤柏混交林土壤N2O排放的实测与模拟

采用静态箱-气相色谱法对川中丘陵区桤柏混交林土壤N2O排放进行了连续两年的测定.通过与Forest-DNDC模型模拟进行对比分析,结果表明,模型能够较好地模拟林地土壤N2O排放.2005和2006年模型模拟的土壤N2O年平均排放速率为15.02,14.03mg/(m2×h),分别为实际观测值的85.7%和87.5%.2005和2006年的实际观测值与模型模拟值之间差异均不显著(P>0.05),模拟有效系数分别为0.56和0.51.以2005年降雨量和气温为基准利用模型进行情景分析,结果表明,本地区降雨量在±30%范围内变化时,林地土壤N2O排放量的变化幅度不超过25%;气温在±3℃范围内变化时,林地土壤N2O排放量的变化幅度不超过10%.     

Modeling effects of temperature and precipitation on carbon characteristics and GHGs emissions in Abies fabric forest of subalpine

Abies fabric forest in the eastern slope of Gongga mountain is one type of subalpine dark coniferous forests of southwestern China. It is located on the southeastern edge of the Qinghai-Tibet plateau and is sensitive to climatic changes. A process-oriented biogeochemical model, Forest-DNDC, was applied to simulate the e ects of climatic factors, temperature and precipitation changes on carbon characteristics, and greenhouse gases (GHGs) emissions in A. fabric forest. Validation indicated that the Forest-DNDC could be used to predict carbon characteristics and GHGs emissions with reasonable accuracy. The model simulated carbon fluxes, soil carbon dynamics, soil CO2, N2O, and NO emissions with the changes of temperature and precipitation conditions. The results showed that with variation in the baseline temperature from –2℃ to +2℃, the gross primary production (GPP) and soil organic carbon (SOC) increased, and the net primary production (NPP) and net ecosystem production (NEP) decreased because of higher respiration rate. With increasing baseline precipitation the GPP and NPP increased slightly, and the NEP and SOC showed decreasing trend. Soil CO2 emissions increased with the increase of temperature, and CO2 emissions changed little with increased baseline precipitation. With increased temperature and decreased baseline temperature, the total annual soil N2O emissions increased.With the variation of baseline temperature from –2℃ to +2℃, the total annual soil NO emissions increased. The total annual N2O and NO emissions showed increasing trends with the increase of precipitation. The biogeochemical simulation of the typical forest indicated that temperature changes strongly a ected carbon fluxes, soil carbon dynamics, and soil GHGs emissions. The precipitation was not a principal factor a ecting carbon fluxes, soil carbon dynamics, and soil CO2 emissions, but changes in precipitation could exert strong e ect on soil N2O and NO emissions.     

Model evaluation of different mechanisms driving freeze–thaw N2O emissions

N₂O emissions from soil contribute significantly to global warming. Pulse emissions of N₂O from soils during freeze-thawing were recently recognized as important atmospheric sources. In this modelling study we explore three different hypotheses for explaining freeze–thaw related N₂O emissions: (1) soil frost or snow cover may reduce gas diffusion and create anaerobic conditions that stimulate N₂O production via denitrification, (2) microbes that die of frost deliver easy decomposable organic carbon and nitrogen to the soil, which stimulates microbial growth and vigorous N₂O production during freeze–thaw, and (3) the enzyme nitrous oxide reductase, which is responsible for the reduction of N₂O to N₂ during denitrification, is more sensitive to low temperatures than other enzymes, so that N₂O becomes the dominating end-product of denitrification at low temperatures. These hypotheses were tested with a biogeochemical model that combines hydrology and physics calculations with a newly developed, parameter-poor biochemistry module. The model was first calibrated with field datasets on soil–atmosphere fluxes of N₂O, NO and CO₂ and soil NO₃ and NH₄ concentrations that were measured in a spruce forest in Southeast Germany in the years 1994–1997. Subsequently, additional model mechanisms were implemented that allow the model to describe the outlined mechanisms potentially driving freeze–thaw N₂O fluxes. After each implementation the model was recalibrated. We were able to mimic dimension and timing of high N₂O emissions when either one of the first two hypotheses were assumed, but found no confirmation for the third. The best model fit was achieved by combining hypothesis one and two, indicating that freeze–thaw N₂O emissions are not mono-causal.     

气候变化对亚高山暗针叶林土壤温室气体排放的影响

利用生物地球化学模犁Forest-DNDC模拟气候变化对贡嘎山亚高山暗针叶林土壤温室气体的释放的影响.以位于贡嘎山东坡海拔3 000 m的峨眉冷杉(Abies fabri)中龄林为研究对象,以1999-2006年8年的日气候数据进行平均得到的日平均最高温度、日平均最低温度和日平均降水总最作为基线(Base)气候情景,另外设置了温度+2℃(升)、温度.2℃(T-)、降水量+20%(P+)、降水量-20%(P-)、温度十2℃同时降水量+20%(T+P+)、温度-2℃同时降水量-20%(T-P-)、温度+2℃同时降水量-20%(T+P-)、温度-2℃同时降水量+20%(T-P+)8种气候变化情景.结果显示:贡嘎山峨眉冷杉林土壤CO_2释放随着温度增加而增加,土壤N_2O释放对降水量改变敏感,而土壤NO的释放对温度和降水的改变均比较敏感,二者表现为协同作用.温度+2℃同时降水量+20%(升P+)情景下土壤CO_2释放最高,高于基线情景的36.08%;温度-2℃同时降水量+20%(T-P+)情景下土壤CO_2释放最低,低于基线情景的36.89%.土壤N_2O释放随着降水量的增加而升高,随着降水量减少而降低;温度和降水最同时增加时土壤NO释放均高于单一增加温度或降水量情景,而温度和降水量同时降低时土壤NO释放均低于单一降低温度或降水量情景.     

Modeling effects of temperature and precipitation on carbon characteristics and GHGs emissions in Abies fabric forest of subaipine

Abies fabric forest in the eastern slope of Gongga mountain is one type of subalpine dark coniferous forests of southwestern China. It is located on the southeastern edge of the Qinghai-Tibet plateau and is sensitive to climatic changes. A process-oriented biogeochemical model, Forest-DNDC, was applied to simulate the effects of climatic factors, temperature and precipitation changes on carbon characteristics, and greenhouse gases （GHGs） emissions in A. fabric forest. Validation indicated that the Forest-DNDC could be used to predict carbon characteristics and GHGs emissions with reasonable accuracy. The model simulated carbon fluxes, soil carbon dynamics, soil CO2, N2O, and NO emissions with the changes of temperature and precipitation conditions. The results showed that with variation in the baseline temperature from -2℃ to ＋2℃, the gross primary production （GPP） and soil organic carbon （SOC） increased, and the net primary production （NPP） and net ecosystem production （NEP） decreased because of higher respiration rate. With increasing baseline precipitation the GPP and NPP increased slightly, and the NEP and SOC showed decreasing trend. Soil CO2 emissions increased with the increase of temperature, and CO2 emissions changed little with increased baseline precipitation. With increased temperature and decreased baseline temperature, the total annual soil N2O emissions increased. With the variation of baseline temperature from -2℃ to ＋2℃, the total annual soil NO emissions increased. The total annual N2O and NO emissions showed increasing trends with the increase of precipitation. The biogeochemical simulation of the typical forest indicated that temperature changes strongly affected carbon fluxes, soil carbon dynamics, and soil GHGs emissions. The precipitation was not a principal factor affecting carbon fluxes, soil carbon dynamics, and soil CO2 emissions, but changes in precipitation could exert strong effect on soil N2O and NO emissions.     

A comparison of four process-based models and a statistical regression model to predict growth of Eucalyptus globulus plantations

In forest management and ecological research, consideration of the impacts and risks of climate change or management optimisation is complex. Computer models have long been applied as tools for these tasks. Process-based forest growth models claim to overcome the limitations of empirical statistical models, but the capacity of different process-based models and modelling approaches have rarely been compared directly. This study evaluates stepwise multiple regression models in comparison to four process-based modelling approaches (3-PG, 3-PG+, CABALA and Forest-DNDC) for greenfield predictions of Eucalyptus globulus plantation growth from 2 to 8 years after planting throughout southern Australia.