青海湖北岸草甸草原CO2通量年际动态及其驱动机制

青藏高原草甸草原是生态系统中重要的植被类型,准确评估高寒草甸草原生态系统碳源汇状况及碳储量变化尤为重要。基于涡度相关系统观测,分析了2009年至2016年8年期间青海湖北岸草甸草原环境因子以及碳通量的变化特征,运用结构方程模型(SEM)分析环境因子对总初级生产力(GPP)、净生态系统CO₂交换量(NEE)、生态系统呼吸(Re)的调控机制。结果表明：2009—2016年8年NEE日均值在-2.02—0.88 gC m^-2 d^-1之间,5—9月NEE为负值,表现为碳吸收,雨热同期的6、7、8月是CO₂净吸收最强的时期,平均每月吸收CO₂ 39.85 gC m^-2 month^-1,NEE负值日数约占全年的48%,10月—翌年4月为正值,表现为碳释放,初春3月和秋末11月是CO₂净释放最强的时期;Re日均值为1.69 gC m^-2 d^-1,受季节温度的影响,呈夏季强,冬季弱的态...     

不同高寒生态系统甲烷通量时空差异及影响因素的量化

使用便携式温室气体分析仪对位于玉树藏族自治州和玛多县的高寒沼泽、高寒草甸、高寒草原和高寒荒漠生态系统的CH₄通量进行原位观测，同时分析生物量、微生物、营养元素、土壤水分和温度等因子，旨在明确不同生态系统CH₄通量时空差异及其主要影响因素。结果表明：在生长季节高寒沼泽和高寒草甸是CH₄源，8月通量达到最大值，高寒草原和高寒荒漠是CH₄的汇，8月达到最小值，4种生态系统之间的CH₄通量差异显著(P<0.05);高寒沼泽的mcrA基因丰度最大，高寒草甸次之，而pmoA丰度则是高寒草甸最大高寒沼泽次之，高寒荒漠的mcrA和pmoA基因丰度均最小，4种生态系统之间差异显著(P<0.05);Pearson相关分析显示，生长季节高寒沼泽和高寒草甸的CH₄通量与土壤温度和mcrA显著正相关(P<0.05),高寒草原和高寒荒漠的CH₄通量与土壤温度和与pmoA显著负相关(P<0.05),不同生态系统之间CH₄     

CO2 flux dynamics and its limiting factors in the alpine shrub-meadow and steppe-meadow on the Qinghai-Xizang Plateau

高寒灌丛草甸和草甸均是青藏高原广泛分布的植被类型, 在生态系统碳通量和区域碳循环中具有极其重要的作用。然而迄今为止, 对其碳通量动态的时空变异还缺乏比较分析, 对碳通量的季节和年际变异的主导影响因子认识还不够清晰, 不利于深入理解生态系统碳通量格局及其形成机制。该研究选取位于青藏高原东部海北站高寒灌丛草甸和高原腹地当雄站高寒草原化草甸年降水量相近的5年(2004-2008年)的涡度相关CO₂通量连续观测数据, 对生态系统净初级生产力(NEP)及其组分, 包括总初级生产力(GPP)和生态系统呼吸的季节、年际动态及其影响因子进行了对比分析。结果表明: 灌丛草甸的CO₂通量无论是季节还是年际累积量均高于草原化草甸, 并且连续5年表现为“碳汇”, 平均每年NEP为70 g C·m ^-2·a ^-1, 高寒草原化草甸平均每年NEP为-5 g C·m ^-2·a ^-1, 几乎处于碳平衡状态, 但其源/汇动态极不稳定, 在2006年-88 g C·m ^-2·a ^-1的“碳源”至2008年54 g C·m ^-2·a ^-1的“碳汇”之间转换, 具有较大的变异性。这两种高寒生态系统源/汇动态的差异主要源于归一化植被指数(NDVI)的差异, 因为NDVI无论在年际水平还是季节水平都是NEP最直接的影响因子; 其次, 灌丛草甸还具有较高的碳利用效率(CUE, CUE = NEP/GPP), 而年降水量和NDVI是决定两生态系统CUE大小的关键因子。两地区除了CO₂通量大小的差异外, 其环境影响因子也有所不同。采用结构方程模型进行的通径分析表明, 灌丛草甸生长季节CO₂通量的主要限制因子是温度, NEP和GPP主要受气温控制, 随着气温升高而增加; 而草原化草甸的CO₂通量多以季节性干旱导致的水分限制为主, 其次才是气温的影响, 受二者的共同限制。此外, 两生态系统生长季节生态系统呼吸主要受GPP和5 cm土壤温度的直接影响, 其中GPP起主导作用, 非生长季节生态系统呼吸主要受5 cm土壤温度影响。该研究还表明, 水热因子的协调度是决定青藏高原高寒草地GPP和NEP的关键要素。     

温度和水分对科尔沁草甸湿地净生态系统碳交换量的影响

基于涡度相关和波文比气象土壤监测系统,研究了2016年科尔沁草甸湿地生态系统生长季5—9月CO₂通量的动态变化特征,分析了温度、水分等环境因子与其的响应关系.结果表明:生长季累计净生态系统碳交换量(NEE)为-766.18 g CO₂·m^-2,总初级生产力(GPP)和生态系统呼吸量(R_e)分别为3379.89和2613.71 g CO₂·m^-2,R_e/GPP为77.3%,表现为明显的碳汇.NEE各月平均日变化呈单峰“U”型曲线,其中5—7月和8月中旬表现为吸收CO₂,8月后半月和9月表现为释放CO₂.日间NEE与光合有效辐射(PAR)呈显著的直角双曲线关系,同时受饱和水汽压差(VPD)、土壤含水量(SWC)和气温(T_a)等环境要素调控.回归关系表明,日间NEE达到最大时,VPD和SWC值分别为1.75 kPa和35.5%,而NEE随T_a增加逐渐增大,当T_a达到最大时,并未对NEE产生抑制作用;夜间NEE随土壤温度(T_s)呈指数趋势上升.在整个生长季,生态系统呼吸的温度敏感性指数(Q₁₀)为2.4,且SWC越高,Q₁₀越小,夜间NEE受T_s和SWC共同调控.     

青藏高原高寒草甸生态系统净二氧化碳交换量特征

高寒草甸是青藏高原广泛分布的植被类型之一,面积约120万km2,地处青藏高原腹地的当雄草原站即位于该类植被的典型分布区。以2003年8~10月中旬在该站用涡度相关法连续观测的CO2通量数据资料为基础,分析了高寒草甸生态系统8~10月份净二氧化碳交换量(NEE)的日变化规律,及其与光合有效辐射、降水、温度等环境因子之间的关系。结果表明,8~10月份的日均NEE有明显的日变化,表现为单峰型,通常在地方时11:00~12:00左右达到碳吸收的最大值,平均为-0.2680mgCO2/(m2·s)(-6.0800μmolCO2/(m2·s))。白天的NEE与光合有效辐射之间符合很好的直角双曲线关系,表观量子产额平均为0.0203μmolCO2/μmolPAR,表观最大光合速率平均为9.7411μmolCO2/(m2·s)。夜晚的NEE与5cm地温有很好的指数函数关系。     

温度对盐土和碱土土壤无机CO2通量的影响

干旱区盐碱土的土壤无机CO₂通量是一个崭新、独特的科学现象,打破了土壤CO₂通量完全来自于生物源的假设。为研究温度对土壤无机CO₂通量的影响,2009年8—10月在阜康荒漠生态系统实验站,以盐土和碱土为研究对象,通过灭菌处理（121℃,24h）,将土壤CO₂通量拆分为土壤无机CO₂通量和土壤有机CO₂通量,分析三者的日动态特征及其与温度的相关关系。结果表明,土壤CO₂通量、土壤无机CO₂通量和土壤有机CO₂通量均存在明显的日动态;除碱土的土壤有机CO₂通量日动态呈弱双峰曲线外,盐土和碱土的土壤CO₂通量、土壤有机CO₂通量和土壤无机CO₂通量日过程均呈单峰曲线,表现为日间CO₂通量随温度升高而增加,峰值出现在12:00—14:00,随后随温度降低而减小,谷值出现在3:00—4:00。盐土和碱土的土壤无机CO₂通量作用超过土壤有机CO₂通量,主导土壤CO₂通量的日变化。土壤CO₂通量和土壤无机CO₂通量主要受温度调控,呈直线方程关系。忽略土壤无机CO₂通量对土壤CO₂通量的贡献,将严重低估土壤有机CO₂通量,是造成干旱区碳循环评估不准确的重要因素之一。     

三江并流核心区亚高山森林非生长季净生态系统CO2交换量及其影响因素

采用开路式涡度相关系统,针对三江并流核心区西藏红拉山滇金丝猴国家自然保护区,通过测量和分析非生长季亚高山常绿针叶林净生态系统碳交换量(NEE),探讨了亚高山森林非生长季CO₂通量特征及其主要影响因子。保护区常绿针叶林NEE值在非生长季具有明显“U”型变化曲线,白天表现为碳吸收,夜间表现为碳释放,日间CO₂吸收高峰介于12:00到15:00之间,平均每天碳汇时间在10 h左右。非生长季各月NEE大小依次为：4月> 3月>2月>11月>1月>12月。研究期内气温(T)、相对湿度(RH)、饱和水汽压差(VPD)和光合有效辐射(PAR)等气象因子对净生态系统CO₂交换量影响显著。此外,森林碳吸收对温度响应敏感,光合作用在整个非生长季较为明显。各影响因子中光合有效辐射对碳交换影响最大;夜间NEE与5 cm土壤温度呈极显著相关性(P<0.01)且NEE随着土壤温度升高而增大;整个非生长季NEE、生态系统呼吸量(Re)和总生态系统CO₂交换量(GEE)分别为-596.759 g...     

锡林浩特草原净生态系统碳交换量特征及源区分布

为探究草原生态系统固碳能力,利用锡林浩特国家气候观象台2018—2021年的涡动相关资料分析了锡林浩特草原生态系统CO₂通量的变化特征以及环境因子对CO₂通量的影响,并对通量源区分布进行了探讨。结果表明：研究区全年盛行西南风,生长季的源区面积大于非生长季,大气稳定条件下的源区面积大于不稳定条件;90%贡献率的源区最大长度接近400 m,与经典法则估算的长度一致。锡林浩特草原净生态系统碳交换量(NEE)具有明显的日变化和季节变化,生长季白天为碳汇,夜间为碳源,非生长季白天和夜间均为弱碳源。2018—2021年,年总NEE分别为-15.59、-46.28、-41.94和-78.14 g C·m^-2·a^-1,平均值为-45.49 g C·m^-2·a^-1,表明锡林浩特草原有较强的固碳能力。饱和水汽压差和光合有效辐射有助于草原生态系统吸收大气中CO₂;夜间,当温度高于0℃时,气温和土壤温度升高会促进植被呼吸作用释放CO₂。     

长江源区高寒草原和高寒草甸土壤粒径分布特征

为探究长江源区主要下垫面土壤空间异质性与粒径分布(PSD)非均匀性,运用分形理论描述高寒草原和高寒草甸2种下垫面土壤粒径分布特征,分析了2种下垫面土壤的分形维数特征差异及其与土壤颗粒组成的关系。结果表明: 研究区土壤颗粒粒径主要分布于100～800 μm,高寒草原土壤单重分形维数(D_V)为2.429～2.508,高寒草甸土壤D_V为2.697～2.743,高寒草原土壤质地偏粗,高寒草甸土壤质地偏细。土壤在20～30 cm深度质地最细,在0～10 cm层质地最粗糙;多重分形维数(容量维数D₀、信息熵维数D₁、关联维数D₂)均以高寒草原(0.896～0.961、0.828～0.887、0.725～0.819)高于高寒草甸(0.890～0.914、0.693～0.744、0.540～0.603),与高寒草甸相比,高寒草原土壤粒径分布范围更宽,土壤整体构造更复杂,土壤整体非均匀性更高。D_V与土壤黏粒、粉粒含量呈显著正相关,与砂粒含量呈显著负相关;D₁、D₂与黏粒、粉粒含量呈显著负相关,与砂粒含量呈显著正相关。土壤砂粒含量是土壤PSD非均匀分布及分形维数大小变化的主要因素。     

青藏高原高寒灌丛非生长季节CO2通量特征

利用2003年和2004年涡度相关系统通量观测资料,对青藏高原高寒灌丛非生长季节CO2通量特征及其主要影响因子进行了分析。(1)从净生态系统CO2交换(NEE)日变化特征看,除13:00~19:00时有较小的CO2净释放以外,其余时段NEE均很小;(2)高寒灌丛非生长季月份间NEE差异明显,4月和10月是CO2净释放量较大,1月和12月CO2净释放量较小;(3)相对温带草原(高杆草大草原)草地类型,低温抑制下的青藏高原高寒灌丛生态系统非生长季节日平均CO2释放率较低;(4)高寒灌丛非生长季NEE日变化模式与5 cm土壤温度变化呈显著正相关,土壤温度是影响非生长季节青藏高原高寒灌丛NEE变化的主导气候因子,同时NEE变化还受降水的影响。     

Effects of plateau pika (Ochotona curzoniae) on net ecosystem carbon exchange of grassland in the Three Rivers Headwaters region, Qinghai-Tibet, China

Background and aim

Because the indigenous burrowing lagomorph plateau pika (Ochotona curzoniae) is considered to have negative ecological impacts on alpine meadow steppe grasslands of the Headwaters Region of the Yellow, Yangtze and Mekong Rivers we investigated its effects on ecosystem productivity and soil properties, and especially net ecosystem carbon flux.

Methods

We measured net ecosystem CO₂ exchange (NEE) and its components gross ecosystem productivity (GEP) and ecosystem respiration (ER) at peak aboveground biomass by the chamber method with reference to plant and soil characteristics of areas of alpine meadow steppe with different densities of pika burrows.

Results

Higher burrow density decreased NEE, GEP and ER. Above-ground biomass, species number, plant cover and leaf area index decreased with increasing pika density. Higher burrow density was associated with lower soil moisture and higher soil temperature. Responses of NEE were related to changes of abiotic and biotic factors affecting its two components. NEE was positively related to soil moisture, soil ammonium nitrogen, plant cover, leaf area index and above-ground biomass but was negatively correlated with higher soil nitrate nitrogen.

Conclusion

Decrease of NEE by plateau pika may reduce the carbon sink balance of Qinghai-Tibet plateau grassland. Such effects may be influenced by grazing pressure from domestic livestock, population levels of natural predators, and climate change.     

Different responses of ecosystem carbon exchange to warming in three types of alpine grassland on the central Qinghai–Tibetan Plateau

Climate is a driver of terrestrial ecosystem carbon exchange, which is an important product of ecosystem function. The Qinghai–Tibetan Plateau has recently been subjected to a marked increase in temperature as a consequence of global warming. To explore the effects of warming on carbon exchange in grassland ecosystems, we conducted a whole‐year warming experiment between 2012 and 2014 using open‐top chambers placed in an alpine meadow, an alpine steppe, and a cultivated grassland on the central Qinghai–Tibetan Plateau. We measured the gross primary productivity, net ecosystem CO₂ exchange (NEE), ecosystem respiration, and soil respiration using a chamber‐based method during the growing season. The results show that after 3 years of warming, there was significant stimulation of carbon assimilation and emission in the alpine meadow, but both these processes declined in the alpine steppe and the cultivated grassland. Under warming conditions, the soil water content was more important in stimulating ecosystem carbon exchange in the meadow and cultivated grassland than was soil temperature. In the steppe, the soil temperature was negatively correlated with ecosystem carbon exchange. We found that the ambient soil water content was significantly correlated with the magnitude of warming‐induced change in NEE. Under high soil moisture condition, warming has a significant positive effect on NEE, while it has a negative effect under low soil moisture condition. Our results highlight that the NEE in steppe and cultivated grassland have negative responses to warming; after reclamation, the natural meadow would subject to loose more C in warmer condition. Therefore, under future warmer condition, the overextension of cultivated grassland should be avoided and scientific planning of cultivated grassland should be achieved.     

A growing season climatic index to simulate gross primary productivity and carbon budget in a Tibetan alpine meadow

Accurate estimation of gross primary production (GPP) of ecosystem is needed to evaluate terrestrial carbon cycle at various spatial and temporal scales. Eddy covariance (EC) technique provides continuous measurements of net ecosystem CO₂ exchange (NEE) and can be used to separate GPP from NEE in real time series. However, seasonal and inter-annual variation and consequently ecosystem carbon budget is still very difficult to simulate from climatic and environment. To address this limitation, we develop a growing season indicator (GSI) based on low temperature and soil water stress to model and predict intra and inter-annual dynamic of gross primary productivity (GPP). Validation of this new index was conducted using continuous six-year consective EC measurement from 2004 to 2009 at a Tibetan alpine meadow. Simulated GPP agreed well with the observed GPP in terms of seasonal and inter-annual variation. The six-year correlation coefficients on seasonal scale between GSI and scalar GPP derived from EC reached more than 0.85 no matter in dry years or wet years. In addition, the temporal GPP estimation derived from GSI model was quite similar to those from observed values by EC measurement. Moreover, accumulated GSI values can predict annual variability of net ecosystem production (NEP). Higher yearly accumulated GSI corresponded to more annual NEP. When cumulative GSI arrived up to 92, the target ecosystem was a carbon sink. This is probably a threshold which Tibetan alpine meadow changes from carbon source to carbon sink. It is indicated that the GSI model is a simple, alternative approach to estimating GPP and has the potential to simulate spatial GPP in a larger scale. However, the performance of GSI model in other vegetation types or regions still needs a further verification.     

The role of shrub (Potentilla fruticosa) on ecosystem CO2 fluxes in an alpine shrub meadow

Aims Recent studies have shown that alpine meadows on the Qinghai-Tibetan plateau act as significant CO₂ sinks. On the plateau, alpine shrub meadow is one of typical grassland ecosystems. The major alpine shrub on the plateau is Potentilla fruticosa L. (Rosaceae), which is distributed widely from 3 200 to 4 000 m. Shrub species play an important role on carbon sequestration in grassland ecosystems. In addition, alpine shrubs are sensitive to climate change such as global warming. Considering global warming, the biomass and productivity of P. fruticosa will increase on Qinghai-Tibetan Plateau. Thus, understanding the carbon dynamics in alpine shrub meadow and the role of shrubs around the upper distribution limit at present is essential to predict the change in carbon sequestration on the plateau. However, the role of shrubs on the carbon dynamics in alpine shrub meadow remains unclear. The objectives of the present study were to evaluate the magnitude of CO₂ exchange of P. fruticosa shrub patches around the upper distribution limit and to elucidate the role of P. fruticosa on ecosystem CO₂ fluxes in an alpine meadow.Methods We used the static acrylic chamber technique to measure and estimate the net ecosystem productivity (NEP), ecosystem respiration (R e), and gross primary productivity (GPP) of P. fruticosa shrub patches at three elevations around the species' upper distribution limit. Ecosystem CO₂ fluxes and environmental factors were measured from 17 to 20 July 2008 at 3 400, 3 600, and 3 800 m a.s.l. We examined the maximum GPP at infinite light (GPP max) and maximum R e (R emax) during the experimental time at each elevation in relation to aboveground biomass and environmental factors, including air and soil temperature, and soil water content.Important findings Patches of P. fruticosa around the species' upper distribution limit absorbed CO₂, at least during the daytime. Maximum NEP at infinite light (NEP max) and GPP max of shrub patches in the alpine meadow varied among the three elevations, with the highest values at 3 400 m and the lowest at 3 800 m. GPP max was positively correlated with the green biomass of P. fruticosa more strongly than with total green biomass, suggesting that P. fruticosa is the major contributor to CO₂ uptake in the alpine shrub meadow. Air temperature influenced the potential GPP at the shrub-patch scale. R emax was correlated with aboveground biomass and R emax normalized by aboveground biomass was influenced by soil water content. Potentilla fruticosa height (biomass) and frequency increased clearly as elevation decreased, which promotes the large-scale spatial variation of carbon uptake and the strength of the carbon sink at lower elevations.     

青海湖北岸高寒草甸草原生态系统CO2通量特征及其驱动因子

 草甸草原是青藏高原的重要植被类型, 与其他植被类型相比, 其碳交换过程和驱动机理的研究仍较薄弱。利用青海湖东北岸草甸草原的涡度相关系统观测的连续数据(2010年7月1日–2011年6月30日), 分析了草甸草原CO₂通量特征及其驱动因子。结果表明: 草甸草原净生态系统CO₂交换量(NEE)在植物生长季的5–9月, 其日变化主要受控于光合光量子通量密度(PPFD); 而非生长季(10月21日–4月19日)和生长季初(4月下旬)、末期(10月中上旬) NEE的日变化主要受气温(T_a)的影响。CO₂
日最大吸收值和释放值分别出现在7月1日(11.37 g CO₂·m^–2·d^–1)和10月21日(4.04 g CO₂·m^–2·d^–1)。逐日NEE主要受控于T_a, 两者关系可用指数线性(explinear)方程表示(R² = 0.54, p < 0.01)。叶面积指数(LAI)和增强型植被指数(EVI)对逐日NEE的影响表现为渐近饱和型, LAI和T_a交互作用明显(p < 0.05), EVI的主效应强烈(p < 0.001)。生态系统的呼吸熵(Q₁₀)为2.42, 总呼吸(R_eco)约占总初级生产力(GPP)的74%。生长季适度的昼夜温差(<14.8 ℃)有利于系统的碳蓄积。研究时段该草甸草原作为碳汇从大气吸收271.31 g CO₂· m^–2。     

黄河三角洲芦苇湿地生长季净生态系统CO2交换及其环境调控机制

采用涡度相关法,对2011年生长季的黄河三角洲芦苇湿地净生态系统CO₂交换(NEE)进行了观测,研究湿地NEE的变化规律及其影响因子.结果表明: 不同月份芦苇湿地的NEE日变化均呈“U”形曲线,CO₂最大净吸收率和释放率的日均值分别为(0.44±0.03)和(0.16±0.01) mg CO₂·m^-2·s^-1;芦苇湿地NEE、生态系统呼吸(R_eco)、总初级生产力(GPP)的季节变化均呈现生长旺季(7-9月)较高、生长初期(5-6月)和生长末期(10-11月)较低的趋势;R_eco和NEE在8月达到峰值,GPP在7月达到峰值.芦苇湿地生态系统的CO₂交换受到光合有效辐射(PAR)、土壤温度(T_s)和土壤体积含水量(SWC)的共同影响.白天NEE与PAR呈直角双曲线关系;5 cm深处T_s与夜间生态系统呼吸(R_eco,n)呈指数关系,生态系统呼吸的温度敏感性(Q₁₀)为2.30,SWC和T_s是影响芦苇湿地R_eco,n的主要因子.在整个生长季,黄河三角洲芦苇湿地生态系统是一个明显的CO₂的汇,总净固碳量为780.95 g CO₂·m^-2.     

藏北高寒草地土壤有机质化学组成对土壤蛋白酶和脲酶活性的影响

土壤酶作为生态系统的生物催化剂, 是土壤有机体的代谢驱动力, 在土壤物质循环和能量转化过程中起着重要作用。该研究以藏北5种不同类型高寒草地(高寒草甸、高寒草原、高寒草甸草原、高寒荒漠草原和高寒荒漠)为研究对象, 利用热裂解气质联用技术(Py-GC/MS)分析不同类型草地土壤有机质化学组成, 并建立其与土壤蛋白酶和脲酶活性之间的相互关系。结果表明, 5种高寒草地土壤(0-15 cm)的酶活性表现出一定差异性, 高寒荒漠草原土壤的脲酶活性显著高于蛋白酶活性, 而其余类型高寒草地的脲酶和蛋白酶活性之间的差异未达到显著水平; 蛋白酶活性在5种高寒草地土壤之间的差异显著, 而脲酶活性在5种草地土壤之间的差异未达到显著水平。相关分析发现, 土壤蛋白酶活性与土壤有机质烷烃、烯烃和芳香烃的相对丰度和糠醛:吡咯的值密切相关, 土壤脲酶活性与土壤有机质化学组成之间相关性未达到显著水平。综上所述, 高寒草地类型和土壤有机质化学组成是影响高寒草地土壤蛋白酶活性的重要因素, 而对土壤脲酶活性的影响均未达到显著水平, 其影响因素有待进一步深入的研究。     

增温对青藏高原高寒草甸生态系统固碳通量影响的模拟研究

低温被广泛认为是高寒草甸生态系统首要限制性因子,因此增温可能会在某种程度上促进初级生产力,但是也可能由于土壤水分、N素营养状况的改变形成新胁迫而抑制生产力提高。此外,生态系统呼吸由于增温而提高的幅度也可能高于初级生产力提高的幅度,造成总碳库平衡的改变。利用青藏高原海北高寒草甸实测数据对生态系统过程模型Biome-BGC(V.4.2)进行了参数化,并利用研究区实测土壤水分(0-40 cm)和其它观测数据对模型进行了检验,证明模型模拟结果较为可靠。模型使用2005-2008年的海北气象站实测气象数据包括气温、降水等作为驱动数据,模拟了增温1.2-1.7℃下青藏高原海北定位站高寒草甸生态系统碳通量的变化,并整合分析增温试验平台上已发表的试验,与模拟结果进行对比,探讨增温对海北高寒草甸生态系统碳收支的可能影响。结果表明:2005-2008年青藏高原高寒草甸生态系统为弱的碳汇,短期增温导致系统净碳固定增加。增温直接影响系统碳通量,也通过土壤水分和土壤矿化氮变化间接影响碳通量,相比土壤水分和氮素,增温对影响碳通量变化过程中的效应更大;研究也揭示,在增温条件下,植物对土壤矿化氮的吸收量小于有机质分解产生的土壤矿化氮量,土壤矿化氮含量增加。