基于随机森林模型的毛竹林CO_2通量模拟及其影响因子

【目的】探究环境因子对毛竹林CO_2通量的影响,为亚热带典型森林碳循环模拟提供技术和理论支撑。【方法】基于浙江省安吉县山川乡2011—2014年毛竹林通量塔观测数据,采用随机森林模型对毛竹林CO_2通量进行模拟,以均方根误差(RMSE)、决定系数(R~2)和林氏调和系数(LCCC)3个指标评价模型精度,并通过计算环境因子重要性得分来分析环境因子对毛竹林CO_2通量的影响。【结果】随机森林模型能以较高精度模拟毛竹林CO_2通量,但由于2013年7和8月发生极端高温干旱,模型难以刻画这种短时、剧烈的干扰,最终导致测试阶段模型精度(R~2=0.845 5,RMSE=0.437 7 mg·m~(-2)s~(-1),LCCC=0.914 1)低于训练阶段模型精度(R~2=0.961 5,RMSE=0.005 4 mg·m~(-2)s~(-1),LCCC=0.980 1);十折交叉验证表明,随机森林模型拟合效果稳定,且模型内部参数设置合理,模型误差主要来自于输入数据;在月尺度上,环境因子对毛竹林CO_2通量影响的重要性得分表现为光合有效辐射PAR(63.332)土壤5 cm深处温度T_S(29.932)空气相对湿度R_H(25.839)大气温度T_A(25.581)空气CO_2浓度C_(CO_2)(25.095)饱和水汽压差VPD(24.123)风速W_S(23.504)生态系统有效能量A_E(19.323)土壤热通量Q_S(18.502),PAR对毛竹林CO_2通量变化影响最大,PAR、T_S和VPD对毛竹林CO_2通量的影响较显著(P0.05),这3个因子是影响月尺度上毛竹林CO_2通量变化的主导因子。【结论】随机森林模型能以较高精度拟合毛竹林CO_2通量;在相关环境因子中,光合有效辐射、土壤5 cm深处温度和饱合水汽压差对毛竹林CO_2通量影响的贡献最显著,这3个因子对毛竹林CO_2通量月尺度上的变化具有控制作用。     

石漠化区蚬木天然林土壤呼吸动态变化及其影响因素

蚬木(Excentrodendron hsienmu)林是桂西南石灰岩季节性雨林最具代表性的顶极演替群落,但对该群落类型碳循环过程的研究相对较少。本研究通过对石漠化区蚬木林土壤呼吸动态及其影响因子的测定和分析,研究蚬木林土壤呼吸的动态变化规律及驱动机制。结果表明:蚬木林土壤呼吸日变化与土壤温度呈正相关性,在非生长季的11月两者相关性达到显著水平。土壤呼吸季节动态与土壤温度、日最低气温呈显著正相关性,呈现夏季高、冬季低的特征,与土壤呼吸呈微弱正相关。基于日最低气温和土壤湿度的双因子模型对土壤呼吸拥有最佳拟合效果,可解释土壤呼吸季节变异的71.0%。采用基于日最低气温的单因子模型计算得到土壤呼吸CO_2通量为54.61 t/(hm~2·a);扣除地表裸露岩石后,土壤呼吸CO_2通量为12.95 t/(hm~2·a)。蚬木林土壤呼吸的动态变化与同气候带森林相似;仅考虑土壤覆盖时,土壤呼吸碳通量处于相对较高水平。     

葡萄园土壤呼吸特征及CO_2排放监测方法比较

基于开路式土壤碳通量测量系统和静态箱法对酿酒葡萄园和鲜食葡萄园的碳通量进行全年观测,观测结果表明:开路式土壤碳通量测量系统和静态箱法均能观测到施肥、翻耕或降水后引起CO_2的剧烈排放,施肥后高水平排放通常持续7 d左右,峰值一般在第3到5天时出现;在对葡萄园的土壤CO_2通量观测中,2种方法测得结果一致性较好,开路式土壤碳通量测量系统测得结果普遍高于静态箱法结果,不同季节存在8.30%到387.41%的差异,差值大小随通量降低而增高;在全年观测中,春季累计排放通量最大,随季节更替逐渐降低。葡萄园CO_2排放主要集中于春、夏2季,其土壤CO_2排放量占全年总排放量额75%以上。开路式土壤碳通量测量系统观测结果与静态箱法观测结果趋势一致性较好,2种方法在对葡萄园土壤CO_2通量观测中均取得良好的效果。因此,开路式土壤碳通量测量系统的观测结果具有可信性,而开路式土壤碳通量测量系统具有操作简便,自动化程度高,可直接获得观测数据的优点,较静态箱法有一定改进和提高。     

城市湿地毛竹林土壤二氧化碳通量研究

为了解城市湿地典型基塘系统的土壤二氧化碳(CO_2)通量特征,以杭州西溪国家湿地公园毛竹林为主要研究对象,通过静态箱式法进行土壤CO_2的通量观测。结果表明:西溪湿地毛竹林土壤是CO_2的排放源,为单峰型,CO_2通量最小值出现在冬季1月,为(127.41±24.06)mg·m~(-2)·h~(-1),最大值出现在夏季的9月,为(537.21±41.12)mg·m~(-2)·h~(-1),是1月最小通量的4倍多,全年毛竹林土壤CO_2的累积排放量为3 366.29 g·m~(-2)·a~(-1)。西溪湿地毛竹林土壤CO_2通量与10 cm土壤温度、0~20 cm土壤含水量有显著相关性,与土壤有机碳质量分数呈负相关。     

植被类型和管理方式对4种经济林土壤活性碳氮及碳通量的影响

土壤活性碳氮含量与CO_2,CH_4通量对研究经济林土壤养分状况和碳氮循环有重要意义。以贵阳黄壤上4种经济林——松林(马尾松Pinus massoniana林)、茶('福鼎大白茶'Camellia sinensis 'Fuding-dabaicha')园、油桃(Prunus persica var. nectarina)林和女贞('金森女贞' Ligustrum japonicum 'Howardii'阔叶人工混交)林0～20 cm的表层土壤为研究对象,比较了植被类型和管理方式对土壤溶解性碳氮养分、微生物量碳氮和CO_2,CH_4通量的影响。结果表明:(1)4种经济林土壤溶解性有机碳含量在5.7～77.5 mg·kg~(-1),溶解性全氮含量在2.2～71.9mg·kg~(-1),各经济林间均没有显著性差异,但植被类型和树龄对其碳氮比有重要影响;(2)土壤NH_4~+-N含量在1.4～15.8 mg·kg~(-1),NO_3~--N含量在0.2～4.2 mg·kg~(-1),无机氮含量变化趋势与pH值相同,与树龄相反;(3)微生物量碳、微生物量氮分别介于221.1～601.4 mg·kg~(-1),41.1～110.2 mg·kg~(-1)之间,其比值受土壤碳氮比和含水量显著影响,且自然生长的经济林显著高于人工管理的经济林(P0.05);(4)研究区表现为CO_2的源和CH_4的汇,其通量分别为~(-1)31.6～605.5 mg·m~(-2)·h~(-1),-583.1～0 mg·m~(-2)·h~(-1),植被类型对CO_2通量没有显著性影响,施硝态氮肥、长期连作等人工管理方式都会导致CH_4通量增加。试验结果表明,调节土壤水分条件和pH值,改进管理方式有助于减少经济林土壤温室气体的释放。     

尖峰岭热带山地雨林林窗土壤甲烷通量研究

以海南岛尖峰岭热带山地雨林因2012年左右台风干扰形成的林窗样地为研究对象,开展土壤甲烷通量的原位观测试验,测定林窗和林下凋落物质量、土壤温度、土壤含水量、酶活性及其他土壤理化指标,运用最佳结构模型研究土壤甲烷通量与环境因子的关系,分析林窗土壤甲烷通量变化特征、影响因素及其与林下的差异。结果表明:海南岛尖峰岭热带山地雨林表现为甲烷吸收,林窗和林下的年平均甲烷通量分别为(-0.37±0.26)和(-0.36±0.24)nmol·m^-2·s^-1,林窗和林下的土壤甲烷通量月变化特征无显著差异(P>0.05),呈现旱季高雨季低的特征。土壤甲烷通量的最佳结构模型表明,全年和旱季的林窗与林下土壤甲烷的主要调控因子均为土壤含水量,但雨季土壤甲烷调控作用最强的因子是土壤温度。结果表明,因台风形成的6个林窗短期对土壤甲烷通量没有显著影响,但林窗和林下的土壤甲烷通量具有旱季大于雨季的季节变化特征。     

亚高山暗针叶林的土壤呼吸

以贡嘎山国家级自然保护区中峨眉冷杉(Abies fabri)林为研究对象,采用LI-6400-09便携式土壤呼吸室对其土壤呼吸速率进行了连续定位观测。结果表明:(1)峨眉冷杉成熟林和中龄林的土壤呼吸速率和土壤温度在各个月份存在差异;(2)两种林分的土壤呼吸速率具有明显的季节变化特征,表现为夏季>秋季>春季>冬季;成熟林的月平均土壤呼吸速率在0.82μmol·s^-1·m^-2～5.88μmol·s^-1·m^-2之间,季节变差系数为50.6%,中龄林的月平均土壤呼吸速率在0.52μmol·s^-1·m^-2～3.52μmol·s^-1·m^-2之间,季节变差系数为48.5%;(3)两种林分的土壤呼吸速率季节变化与土壤5 cm温度呈显著性正相关;(4)峨眉冷杉成熟林和中龄林土壤CO_2释放率的Q₁₀值分别为3.2和2.6,峨眉冷杉成熟林土壤呼吸对温度的敏感性指数要大于中龄林。     

4种寒温带兴安落叶松林土壤CO_2,CH_4和N_2O排放通量特征

利用静态箱-气相色谱法,研究大兴安岭4种典型落叶松林(藓类-兴安落叶松林、杜香-兴安落叶松林、草类-兴安落叶松林和杜鹃-兴安落叶松林)在生长季主要温室气体(CO_2、CH_4和N_2O)排放通量特征及与土壤理化性质的关系。结果表明:4种落叶松林均为CO_2的排放源,平均排放通量分别为45.88(藓类-兴安落叶松林)、38.68(杜香-兴安落叶松林)、54.54(草类-兴安落叶松林)和62.98(杜鹃-兴安落叶松林) mg·m~(-2)h~(-1)。其中杜鹃-兴安落叶松林排放通量最高,4种林型土壤CO_2排放通量均与土壤温度呈显著正相关。CH_4平均排放通量依次为0.089(藓类-兴安落叶松林)、-0.037(杜香-兴安落叶松林)、0.004(草类-兴安落叶松林)和-0.03(杜鹃-兴安落叶松林)mg·m~(-2)h~(-1),藓类-兴安落叶松林和草类-兴安落叶松林为CH_4的源,另2种林型表现为CH_4的汇。其中藓类-兴安落叶松林贡献了该地区95%以上的CH_4排放量。草类-兴安落叶松林和杜鹃-兴安落叶松林与土壤温度存在显著相关性。藓类-兴安落叶松林和杜香-兴安落叶松林与土壤有机碳呈显著负相关。4种林型中仅杜鹃-兴安落叶松林土壤CH_4排放通量与5 cm深土壤含水量存在显著相关性。N_2O平均排放通量依次为0.007 3(藓类-兴安落叶松林)、0.012(杜香-兴安落叶松林)、0.009 3(草类-兴安落叶松林)和-0.0003(杜鹃-兴安落叶松林)mg·m~(-2)h~(-1),表现为N_2O的源(杜鹃除外)。不同月份N_2O排放通量研究结果显示,该地区4种林型N_2O的排放主要集中在夏末和秋季。影响N_2O排放通量的环境因子因林型而异,其中草类-兴安落叶松林与10 cm土壤温度呈显著正相关,与全氮、碱解氮和有机碳呈显著负相关;杜鹃-兴安落叶松林与土壤温度和土壤含水量均呈显著正相关性;藓类-兴安落叶松林和杜香-兴安落叶松林分别与土壤全氮和有机碳存在显著相关性,与土壤温度、含水量、pH值无显著相关性。     

氮沉降对中国森林土壤CO_2通量的影响

氮沉降可能改变森林土壤CO_2通量,已有研究结果对氮沉降作用的方向和强度上具有很大的不确定性。通过整合已有模拟氮沉降的野外监测数据,评估了氮沉降对中国森林土壤CO_2通量的影响。结果表明,氮沉降平均降低了中国土壤CO_2通量的8.7%,且这种影响对次生林和人工林影响较大,而对原始林影响较小。同时,氮沉降对土壤CO_2通量的影响对阔叶林、针叶林和针阔混交林均无显著影响,但显著降低了竹林土壤CO_2通量的36%。施加100 kg N·hm~(-2)·a~(-1)时才会对森林土壤CO_2通量造成显著降低,且施加硝酸铵的降低大于尿素。氮沉降的这种影响主要是由于过多的氮抑制了土壤微生物活性造成的。     

长白山森林生态系统土壤氮矿化时空动态特征

通过对土壤温度的定位观测(土壤深度5cm处)及分析,长白山北坡3种不同林型土壤氮矿化速率表现为季节动态变化,与土壤温度季节动态变化比较相似。在不同月份氮矿化速率存在较大差异。在7、8月份时,氮矿化速率最大且红松云冷杉林土壤氮矿化速率明显高于阔叶红松林和岳桦云冷杉林。而在11、12、1～3月份之间氮矿化速率比较低且变化比较平稳。主要是因为温度对氮矿化速率起限制作用。就不同林型而言,阔叶红松林土壤年氮矿化量是44.13kg/hm2.a为最高,其次是红松云冷杉林31.3kg/hm2.a和岳桦云冷杉林25.73kg/hm2.a。因此阔叶红松林土壤供氮潜力更大。     

An alternative modelling approach to predict emissions of N<Subscript>2</Subscript>O and NO from forest soils

Emissions of N₂O from forest soils in Europe are an important source of global greenhouse gas emissions. However, influencing the emission rates by forest management is difficult because the relations and feedbacks between forest and soils are complex. Process-based models covering both vegetation and soil biogeochemical processes are frequently used to analyse emission patterns. Particularly, the simulation of soil C and N turnover processes driving N₂O production, consumption and emission from forest soils requires highly specific input data which renders their regional application difficult since at this scale, soil conditions are often not well understood. Therefore, a soil C and N model (DecoNit) has been developed which describes biogeochemical processes with a simplified structure compared to existing carbon/nitrogen models that nevertheless follows the basic physical and chemical laws involved and which allows to simulate N trace gas emissions. The DecoNit model was previously calibrated using an extensive dataset on decomposition rates of incubated plant materials, microbial dynamics and nitrification. The DecoNit model has now been embedded in a modular simulation environment (MoBiLE) where it is combined with soil water balance and forest process sub-modules. Here, we present the evaluation of MoBiLE-DecoNit with emission data of N₂O and NO from forest soils of 15 European sites and compare simulation results with a previous study in which a more complex model (PnET-N-DNDC) was used. Evaluation criteria were as follows: (1) precision of modelled annual average emission rates; (2) coherence of modelled and measured annual average and daily emissions; (3) a dynamic representation of emission rates that correspond with the observed variance of fluxes. The results show that MoBiLE-DecoNit captures average annual emission rates more precisely than the more complex model PnET-N-DNDC. Also the structural underestimation of N trace gas fluxes from forest soils was resolved. Moreover, we present evidence that the new modelling approach is also somewhat more adequate for describing inter-daily emission dynamics. The combined MoBiLE-DecoNit is therefore thought to be a promising approach to simulate forest development and greenhouse gas balances on site and regional scales.     

基于NIR-PLS的土壤碳含量预测模型研究

以东北小兴安岭林区带岭林业局东方红林场的土壤为研究对象,对120个土壤样品近红外光谱做去噪、Savitzky-Golay平滑和多元散射校正预处理,利用偏最小二乘（PLS）法建立关于土壤碳含量和吸光度之间的定量分析模型,并进行模型校、验证及部分预测集样品碳含量预测.结果表明：主成分数为4时,模型最优.校正模型的决定系数R2和均方根误差（RMSE）分别为0.784和5.752;验证模型的决定系数R2和均方根误差（RMSE）分别为0.621和7.521,预测集样品的实测值和预测值的决定系数R2达到0.735,均方根误差RMSE为7.202,预测标准差SEP为10.356.应用近红外技术可以实现对小兴安岭次生林土壤碳含量的有效预测,为大面积快速测定土壤碳含量提供理论依据与技术支撑,进而为林分土壤碳循环的相关研究提供新的思路.     

Modeling annual production and carbon fluxes of a large managed temperate forest using forest inventories, satellite data and field measurements

We evaluated annual productivity and carbon fluxes over the Fontainebleau forest, a large heterogeneous forest region of 17,000 ha, in terms of species composition, canopy structure, stand age, soil type and water and mineral resources. The model is a physiological process-based forest ecosystem model coupled with an allocation model and a soil model. The simulations were done stand by stand, i.e., 2992 forest management units of simulation. Some input parameters that are spatially variable and to which the model is sensitive were calculated for each stand from forest inventory attributes, a network of 8800 soil pits, satellite data and field measurements. These parameters are: (1) vegetation attributes: species, age, height, maximal leaf area index of the year, aboveground biomass and foliar nitrogen content; and (2) soil attributes: available soil water capacity, soil depth and soil carbon content. Main outputs of the simulations are wood production and carbon fluxes on a daily to yearly basis. Results showed that the forest is a carbon sink, with a net ecosystem exchange of 371 g C m(-2) year(-1). Net primary productivity is estimated at 630 g C m(-2) year(-1) over the entire forest. Reasonably good agreement was found between simulated trunk relative growth rate (2.74%) and regional production estimated from the National Forest Inventory (IFN) (2.52%), as well as between simulated and measured annual wood production at the forest scale (about 71,000 and 68,000 m(3) year(-1), respectively). Results are discussed species by species.     

Stem radial CO_2 conductance affects stem respiratory CO_2 fluxes in ash and birch trees

The CO_2 released from respiring cells in woody tissues of trees can contribute to one of three fluxes:efflux to the atmosphere(E_A),internal xylem sap transport flux(F_T),and storage flux(DS).Adding those fluxes together provides an estimate of actual stem respiration(R_S).We know that the relative proportion of CO_2 in those fluxes varies greatly among tree species,but we do not yet have a clear understanding of the causes for this variation.One possible explanation is that species differ in stem radial CO_2 conductance(g_c).A high g_c would favor the E_A pathway and a low g_cwould favor the F_Tpathway.However,g_chas only been measured once in situ and only in a single tree species.We measured g_cusing two methods in stems of Fraxinus mandshurica Rupr.(ash)and Betula platyphylla Suk.(birch)trees in situ,along with R_S,E_A,F_T and DS.Stem radial CO_2 conductance was substantially greater in ash trees than in birch trees.Corresponding to that finding,in ash trees over 24 h,E_Aconstituted the entire flux of respired CO_2 ,and F_Twas negative,indicating that additional CO_2 ,probably transported from the root system via the xylem,was also diffusing into the atmosphere.In ash trees,F_T was negative over the entire 24 h,and this study represents the first time that has been reported.The addition of xylem-transported CO_2 to E_A caused E_Ato be 9% higher than the actual R_Sover the diel measurement period.Birch trees,which had lower g_c,also had a more commonly seen pattern,with E_A accounting for about 80% of the CO_2 released from local cell respiration and F_T accounting for the remainder.The inorganic carbon concentration in xylem sap was also lower in ash trees than in birch trees:2.7 versus 5.3 mmol L^-1,respectively.Our results indicate that stem CO_2 conductance could be a very useful measurement to help explain differences among species in the proportion of respired CO_2 that remains in the xylem or diffuses into the atmosphere.     

Potential knowledge gain in large-scale simulations of forest carbon fluxes from remotely sensed biomass and height

Global vegetation models (GVMs) simulate CO₂, water and energy fluxes at large scales, typically no smaller than 10 × 10 km. GVM simulations are thus expected to simulate the average functioning, but not the local variability. The two main limiting factors in refining this scale are (1) the scale at which the pedo-climatic inputs - temperature, precipitation, soil water reserve, etc. - are available to drive models and (2) the lack of geospatial information on the vegetation type and the age of forest stands. This study assesses how remotely sensed biomass or stand height could help the new generation of GVMs, which explicitly represent forest age structure and management, to better simulate this local variability. For the ORCHIDEE-FM model, we find that a simple assimilation of biomass or height brings down the root mean square error (RMSE) of some simulated carbon fluxes by 30-50%. Current error levels of remote sensing estimates do not impact this improvement for large gross fluxes (e.g. terrestrial ecosystem respiration), but they reduce the improvement of simulated net ecosystem productivity, adding 13.5-21% of RMSE to assimilations using the in situ estimates. The data assimilation under study is more effective to improve the simulation of respiration than the simulation of photosynthesis. The assimilation of height or biomass in ORCHIDEE-FM enables the correct retrieval of variables that are more difficult to measure over large areas, such as stand age. A combined assimilation of biomass and net ecosystem productivity could possibly enable the new generation of GVMs to retrieve other variables that are seldom measured, such as soil carbon content.     

阔叶红松林土壤CO2,N2O排放和CH4吸收的研究

为研究凋落物对CO2,N2O排放和CH4吸收的影响,从2002年9月3日到2003年10月30日,采用静态密闭箱技术对长白山阔叶红松林两种类型土壤生态系统的CO2,N2O和CH4的通量进行测定。两种土壤类型分别为表层有凋落物覆盖和没有凋落物覆盖。研究结果表明,凋落物对CO2,N2O和CH4通量有显著性影响(P<0.05)。有凋落物样地的CO2,N2O和CH4通量的日变化趋势和无凋落物样地中三种气体的日变化趋势相似,且CO2,N2O和CH4的日通量峰值都出现在18:00。有凋落物样地的CO2,N2O和CH4通量的季节变化趋势和无凋落物样地中三种气体的季节变化趋势也相似,但在一年之中,CO2和CH4的峰值出现在六月,N2O的峰值却出现在八月。研究结果还表明有凋落物样地CO2,N2O的日排放通量和年均排放通量明显大于无凋落物样地中两种气体的排放通量,但有凋落物样地的CH4日吸收通量和年均排放通量却小于无凋落物样地的CH4吸收通量。     

亚热带典型丘陵坡地马尾松林土壤N2O的年通量特征

由人类活动所造成的大气中温室气体浓度急剧增加而引起的全球气候变暖和环境变化已引起全世界的广泛关注。氧化亚氮(N2O)是仅次于二氧化碳(CO2)和甲烷(CH4)的一种温室气体,在大气中含量较低却十分稳定,具有较大的增温潜能(其单分子的增温潜能是CO2的310倍)和较快的浓度增加速率(以每年0.25%的速率增加)(IPCC,2007)。N2O可吸收红外线,减少地球表面通过大气向外层空间的热辐射,导致地球表面温度增加。N2O能参与大气中许多光化学反应,破坏臭氧层(Crutzen,1970),导致到达地球表面的紫外线明显增加,给人类健康和生态环境带来多方面的危害。     

采伐强度对小兴安岭低质林分土壤碳通量的影响

针对择伐后的小兴安岭低质林分,采用LI-8100碳通量自动监测系统在春、夏、秋、冬4个季节对低质林分土壤碳通量进行观测,运用统计分析方法,分析采伐强度对土壤碳通量、土壤温度与湿度的影响。结果表明:采伐区的土壤碳通量高于对照区,随采伐强度的增加土壤碳通量呈现波动性,从采伐强度22%～47%,碳通量逐渐减小,之后趋于平稳,春、夏、秋、冬4个季节土壤碳通量的最大值出现在低度和中度采伐强度林分条件下;随采伐强度增加土壤温度增加,土壤湿度减少,土壤碳通量与距地表10cm处的土壤温度的关系符合指数模型,土壤碳通量与土壤湿度的关系符合一元二次模型;从标准化回归方程看出,土壤碳通量主要由土壤温度与湿度共同影响,且土壤湿度对碳通量的影响大于土壤温度的影响。采伐强度与土壤碳通量具有负相关性,二者的关系为双曲线。     

Factors controlling N_2O and CH_4 fluxes in mixed broad-leaved/Korean pine forest of Changbai Mountain, China

IntroductionTheincreasinggreenhousegasconcentrationshavereceivedmuchattention.TwoofthesegasesthatscientistsareveryconcernedaboutareN2oandCH`,becauseoftheirrapidincreaseandtheirim-portantchemistryintheatmosphere(Bouwman199o).ThemoIecuIegIobalwarmingpotentialofN2OandCH4areabout58and2o6timesthanthatofCO2.Inaddition,atmosphericconcentrationsofN2OandCH`areincreasingatahnualratesofo.25%ando.9%respectively(HoughtonetaI1992).Forestecosystemhasbeenknownasanimportantterres-trialecosystemattheasp…     

High-frequency analysis of the complex linkage between soil CO(2) fluxes, photosynthesis and environmental variables

High-frequency soil CO(2) flux data are valuable for providing new insights into the processes of soil CO(2) production. A record of hourly soil CO(2) fluxes from a semi-arid ponderosa pine stand was spatially and temporally deconstructed in attempts to determine if variation could be explained by logical drivers using (i) CO(2) production depths, (ii) relationships and lags between fluxes and soil temperatures, or (iii) the role of canopy assimilation in soil CO(2) flux variation. Relationships between temperature and soil fluxes were difficult to establish at the hourly scale because diel cycles of soil fluxes varied seasonally, with the peak of flux rates occurring later in the day as soil water content decreased. Using a simple heat transport/gas diffusion model to estimate the time and depth of CO(2) flux production, we determined that the variation in diel soil CO(2) flux patterns could not be explained by changes in diffusion rates or production from deeper soil profiles. We tested for the effect of gross ecosystem productivity (GEP) by minimizing soil flux covariance with temperature and moisture using only data from discrete bins of environmental conditions (±1 °C soil temperature at multiple depths, precipitation-free periods and stable soil moisture). Gross ecosystem productivity was identified as a possible driver of variability at the hourly scale during the growing season, with multiple lags between ~5, 15 and 23 days. Additionally, the chamber-specific lags between GEP and soil CO(2) fluxes appeared to relate to combined path length for carbon flow (top of tree to chamber center). In this sparse and heterogeneous forested system, the potential link between CO(2) assimilation and soil CO(2) flux may be quite variable both temporally and spatially. For model applications, it is important to note that soil CO(2) fluxes are influenced by many biophysical factors, which may confound or obscure relationships with logical environmental drivers and act at multiple temporal and spatial scales; therefore, caution is needed when attributing soil CO(2) fluxes to covariates like temperature, moisture and GEP.