Modeling seasonal course of carbon fluxes and evapotranspiration in response to low temperature and moisture in a boreal Scots pine ecosystem

Environmental conditions act above and below ground, and regulate carbon fluxes and evapotranspiration. The productivity of boreal forest ecosystems is strongly governed by low temperature and moisture conditions, but the understanding of various feedbacks between vegetation and environmental conditions is still unclear. In order to quantify the seasonal responses of vegetation to environmental factors, the seasonality of carbon and heat fluxes and the corresponding responses for temperature and moisture in air and soil were simulated by merging a process-based model (CoupModel) with detailed measurements representing various components of a forest ecosystem in Hyytiälä, southern Finland. The uncertainties in parameters, model assumptions, and measurements were identified by generalized likelihood uncertainty estimation (GLUE). Seasonal and diurnal courses of sensible and latent heat fluxes and net ecosystem exchange (NEE) of CO₂ were successfully simulated for two contrasting years. Moreover, systematic increases in efficiency of photosynthesis, water uptake, and decomposition occurred from spring to summer, demonstrating the strong coupling between processes. Evapotranspiration and NEE flux both showed a strong response to soil temperature conditions via different direct and indirect ecosystem mechanisms. The rate of photosynthesis was strongly correlated with the corresponding water uptake response and the light use efficiency. With the present data and model assumptions, it was not possible to precisely distinguish the various regulating ecosystem mechanisms. Our approach proved robust for modeling the seasonal course of carbon fluxes and evapotranspiration by combining different independent measurements. It will be highly interesting to continue using long-term series data and to make additional tests of optional stomatal conductance models in order to improve our understanding of the boreal forest ecosystem in response to climate variability and environmental conditions.     

Identification of important factors for water vapor flux and CO2 exchange in a cropland

Water vapor flux and carbon dioxide (CO₂) exchange in croplands are crucial to water and carbon cycle research as well as to global warming evaluation. In this study, a standard three-layer feed-forward back propagation neural network technique associated with the Bayesian technique of automatic relevance determination (ARD) was employed to investigate water vapor and CO₂ exchange between the canopy of summer maize and atmosphere in responses to variations of environmental and physiological factors. These factors, namely the photosynthetically active radiation (PAR), air temperature (T), vapor pressure deficient (VPD), leaf-area index (LAI), soil water content in root zone (W), and friction velocity (U*), were used as inputs in neural network analysis. Results showed that PAR, VPD, T and LAI were the primary factors regulating both water vapor and CO₂ fluxes with VPD and W more critical to water vapor flux and PAR and T more crucial to CO₂ exchange. Furthermore, two time variables “day of the year (DOY)” and “time of the day (TOD)” could also improve the simulation results of neural network analysis. The important factors identified by the neural network technique used in this study were in the order of PAR > T > VPD > LAI > U* > TOD for water vapor flux and in the order of VPD > W > LAI > T > PAR > DOY for CO₂ exchange. This study suggests that neural network technique associated with ARD could be a useful tool for identifying important factors regulating water vapor and CO₂ fluxes in terrestrial ecosystem.     

Mass conservation above slopes in the Regional Atmospheric Modelling System (RAMS)

This paper examines the mass balance in calculations with the Regional Atmospheric Modelling System (RAMS). An error is pointed out that concerns the calculation of the surface fluxes on slopes. This error affects all the prognostic variables in RAMS when sloping terrain is involved. Here we explain how the error can be corrected. To study the impact of the error, we compared simulations with the uncorrected and corrected model. The model contains CO₂ transport, and online mass balance calculations were performed for this tracer. Without correction, effective surface CO₂-fluxes on mountain slopes were found to be enhanced under certain common conditions to several times the parameterized fluxes. Neglecting this error may cause substantial deviations in both forward and inverse model calculations. After the correction a very good closure of the mass balance is obtained. The correction also modifies the meteorological parameters, although the consequences were limited compared to the CO₂-fluxes.     

Parameter uncertainties in the modelling of vegetation dynamics—Effects on tree community structure and ecosystem functioning in European forest biomes

Dynamic vegetation models are useful tools for analysing terrestrial ecosystem processes and their interactions with climate through variations in carbon and water exchange. Long-term changes in structure and composition (vegetation dynamics) caused by altered competitive strength between plant functional types (PFTs) are attracting increasing attention as controls on ecosystem functioning and potential feedbacks to climate. Imperfect process knowledge and limited observational data restrict the possibility to parameterise these processes adequately and potentially contribute to uncertainty in model results. This study addresses uncertainty among parameters scaling vegetation dynamic processes in a process-based ecosystem model, LPJ-GUESS, designed for regional-scale studies, with the objective to assess the extent to which this uncertainty propagates to additional uncertainty in the tree community structure (in terms of the tree functional types present and their relative abundance) and thus to ecosystem functioning (carbon storage and fluxes). The results clearly indicate that the uncertainties in parameterisation can lead to a shift in competitive balance, most strikingly among deciduous tree PFTs, with dominance of either shade-tolerant or shade-intolerant PFTs being possible, depending on the choice of plausible parameter values. Despite this uncertainty, our results indicate that the resulting effect on ecosystem functioning is low. Since the vegetation dynamics in LPJ-GUESS are representative for the more complex Earth system models now being applied within ecosystem and climate research, we assume that our findings will be of general relevance. We suggest that, in terms of carbon storage and fluxes, the heavier parameterisation requirement of the processes involved does not widen the overall uncertainty in model predictions.     

ANAFORE: A stand-scale process-based forest model that includes wood tissue development and labile carbon storage in trees

A stand-scale forest model has been developed that dynamically simulates, besides carbon (C) and water (H₂O) fluxes, wood tissue development from physiological principles. The forest stand is described as consisting of trees of different size cohorts (for example, dominant, co-dominant and suppressed trees), either of the same or of different species (deciduous or coniferous). Half-hourly C and H₂O fluxes are modeled at the leaf, tree and stand level. In addition to total growth and yield, the model simulates the daily evolution of tracheid or vessel biomass and radius, parenchyma and branch development. From these data early and latewood biomass, wood tissue composition and density are calculated. Simulation of the labile C stored in the living tissues allows for simulation of trans-seasonal and trans-yearly effects, and improved simulations of long-term effects of environmental stresses on growth. A sensitivity analysis was performed to indicate the main parameters influencing simulated stem growth and wood quality at the tree and stand level. Case studies were performed for a temperate pine forest to illustrate the main model functioning and, more in particular, the simulation of the wood quality. The results indicate that the ANAFORE model is a useful tool for simultaneous analyses of wood quality development and forest ecosystem functioning.     

Influences of canopy structure and physiological traits on flux partitioning between understory and overstory in an eastern Siberian boreal larch forest

Boreal forests play an important role in the global balance of energy and CO₂. Our previous study of elaborate eddy covariance observations in a Siberian boreal larch forest, conducted both above the forest canopy and at the forest floor, revealed a significant contribution of latent heat flux (LE) from the cowberry understory to the whole ecosystem LE. Thus, in the present study, we examined what factors control the partitioning of whole ecosystem LE and CO₂ flux into the understory and overstory vegetation, using detailed leaf-level physiology (for both understory and overstory vegetation) and soil respiration property measurements as well as a multilayer soil-vegetation-atmosphere transfer (SVAT) model. The modeling results showed that the larch overstory's leaf area index (LAI) and vertical profile of leaf photosynthetic capacity were major factors determining the flux partitioning in this boreal forest ecosystem. This is unlike other forest ecosystems that tend to have dense LAI. We concluded that control of the larch overstory's LAI had a relationship with both the coexistence of the larch with the cowberry understory and with the water resources available to the total forest ecosystem.     

Coupling biochemical and biophysical processes at the leaf level: an equilibrium photosynthesis model for leaves of C3 plants

The paper presents a generic computer model for estimating short-term steady-state fluxes of CO₂, water vapor, and heat from broad leaves and needle-leaved coniferous shoots of C₃ plant species. The model explicitly couples all major processes and feedbacks known to impact leaf biochemistry and biophysics including biochemical reactions, stomatal function, and leaf-boundary layer heat- and mass-transport mechanisms. The ability of the model to successfully predict measured photosynthesis and stomatal-conductance data as well as to simulate a variety of observed leaf responses is demonstrated. A model application investigating physiological and environmental regulation of leaf water-use efficiency (WUE) under steady-state conditions is discussed. Simulation results suggest that leaf physiology has a significant control over the environmental sensitivity of leaf WUE. The implementation of a highly efficient solution technique allows the model to be directly incorporated into plant-canopy and terrestrial ecosystem models.     

水热条件对不同坡位兴安落叶松林土壤CH4通量的影响

兴安落叶松林是我国北方最大的针叶林,在我国具有重要的碳汇地位,对我国以及全球的气候变化具有重要影响。由于独特的高寒高湿和多年冻土的特殊生态环境,兴安落叶松林土壤中 CH4的吸收与释放的规律与众不同。因此,开展对土壤 CH4动态及其与环境关系的研究,对揭示兴安落叶松林碳汇能力的形成、碳释放动态以及兴安落叶松林对气候变化的作用具有重要的理论和实践意义。作者于2011年5月到9月间在内蒙古根河国家生态站,在不同坡位的4种典型兴安落叶松林群落中布设样地,采用静态箱-红外气体分析仪收集气体并分析CH4通量的变化,同时测定不同深度的土壤温度,测定土壤含水率。借助SAS方差分析、相关性分析等统计方法,对兴安落叶松林土壤CH4通量的季节变化进行研究,同时分析土壤温度及含水率对 CH4通量的影响。结果表明,CH4的季节动态变化规律：坡顶 CH4通量为春季释放,夏季吸收,秋季释放,吸收大于释放,通量的平均值为-68.12μg·m^-2·h^-1;坡上部CH4通量为春夏秋3季均吸收,通量的平均值为-342.49μg·m^-2·h^-1;坡下部CH4通量为春季释放,夏季吸收,秋季释放,释放大于吸收,通量的平均值为67.8μg·m^-2·h^-1;坡脚CH4通量为春夏秋3季均释放,通量的平均值为263μg·m^-2·h^-1。总的来说,在生长季兴安落叶松林土壤甲烷通量吸收大于释放,说明地处寒温带的大兴安岭是CH4的汇。观测期间CH4通量与温度及土壤含水率均有一定的相关性,二者从不同角度影响CH4通量的变化,而随着坡位的变化土壤水热条件也随之改变,这同样是影响CH4通量的一个重要因素。     

Acknowledging the spatial heterogeneity in modelling/reconstructing carbon dioxide exchange in a northern aapa mire

Chamber method is commonly used to measure the CO₂ exchange from plant communities. Due to low time resolution, actual measurements reflect only momentary CO₂ exchange rates. Therefore, a common way to derive seasonal or annual estimates is to establish models describing the response of CO₂ exchange to environmental variables, and then to reconstruct the CO₂ exchange over the desired time period. There are several alternative ways to obtain the CO₂ balance for the entire mire: models can be parameterized by individual sample plots, plant communities or the entire site. Similarly, the CO₂ balance can be reconstructed by plots, plant communities or the entire site. We tested how the choice of the modelling and reconstruction approach influences the CO₂ exchange estimates for the entire mire and for individual sample plots and plant communities. We measured the CO₂ exchange in a spatially heterogeneous sedge-dominated northern aapa mire for two growing seasons. We observed high spatial variation in CO₂ balance between the plant communities. We noticed that when the CO₂ balances of individual sample plots or plant communities are of interest, using a model appropriate for the entire site may result in biased estimates. In worst case the different modelling approaches may turn the CO₂ balance of an individual sample plot from positive to negative. Further, while using the whole ecosystem approach in modelling, the superior ability of chamber method in acknowledging spatial variation is lost. While the modelled growing season CO₂ balance of the mire ranged from 232 to 625 g CO₂ m⁻² depending on the chosen modelling and reconstruction approach, the average estimates still remained within the uncertainty range of one another. Acknowledgement of the spatial variation in plant community level makes the areal estimate more robust to varying weather conditions. Further, the reliability of estimates is improved by explicit formulation of the choices behind the modelling and reconstruction units reflecting the study objectives.     

Dynamic compartment approach for modelling regimes of carbon cycle functioning in bog ecosystems

Svirezhev's method of dynamic model design by a given “storage-flow” diagram [Svirezhev Y.M., 1997. On some general properties of trophic networks. Ecol. Model. 99, 7–17] is developed and used for investigating dynamic regimes of carbon cycle functioning in a typical boreal transitional bog ecosystem. Ecosystems are often represented by static “storage-flow” diagrams reflecting their structure and matter or energy transfer between components at fixed time moments. Using the data of such diagrams aggregated in ecological field studies one can construct a dynamic model of the ecosystem to predict its future behaviour and to estimate a response to external perturbations—natural and human. Stability of both current equilibrium and possible alternative steady states and more complicated attractors are studied under two types of parameter perturbation: CO₂ atmospheric concentration increase initiated by greenhouse effect, and change in the rate of carbon output from dead organic matter and litter which depends on the water table level and possible peat excavation. Calculation of bifurcation curves gives areas in the parameter space where stable functioning of carbon cycle is provided. Steady states can be interpreted as raised bog, meadow, forest and fen. CO₂ concentration increase leads the current state of transitional bog to loose stability with appearance of oscillatory dynamics and further evolution to the chaotic attractor. The model is rich by chaotic solutions serving as transition regimes between regular steady and periodic attractors. Another chaotic regime is formed from forest equilibrium and exists in the same area of phase space where current equilibrium is stable.     

Modeling the carbon dynamics of the La Grande hydroelectric complex in northern Quebec

A mechanistic semi-empirical carbon cycle model of the La Grande reservoir complex in northern Quebec, Canada was conceived in order to investigate the climate impact of such a large alteration of the continental water cycle. The model includes inputs from the drainage basin, organic matter release from flooded soils, CO₂ emissions across the water-atmosphere interface and sedimentation. Most input data stems from previous research by our group on those ecosystems. The model includes the seven reservoirs of the La Grande complex and was run for periods of 50 and 100 years. Terrigeneous dissolved, particulate and suspended soil carbon fluxes and concentrations were computed. Over 100 years, 31.3 × 10¹² g C are released from flooded soils, equivalent to 28-29% of inputs from the drainage basin. 40-74% of dissolved organic carbon is mineralized. CO₂ fluxes over 100 years are 50.5-79.8 × 10¹² g C, 46.4-67.9 × 10¹² g C more than in the absence of reservoirs. The increase in mineralization of organic matter and in CO₂ emissions is a result of the increase in cumulated water residence time due to the creation of the reservoirs. Changes in other carbon sinks and sources likely offset a part of this additional carbon flux to the atmosphere. In the first years following flooding of the reservoir, organic carbon release from flooded soils exceeds CO₂ emissions, implying the downstream export of large quantities of eroded soil organic carbon. After this initial period, CO₂ emissions are fuelled by organic carbon originating from the drainage basin.     

鼎湖山南亚热带森林生态系统服务价值动态

以鼎湖山3个南亚热带森林演替典型阶段生态系统为对象,采用我国《森林生态系统服务功能评估规范》（LY/T 1721—2008）标准化计算公式与服务价格,量化揭示南亚热带森林生态系统演替过程中生态系统服务功能价值动态。结果表明：随着演替的进行,南亚热带森林生态系统服务功能总价值不断增大;但各分项服务功能价值则表现出不同的动态规律与变化幅度,从而使得森林生态系统服务结构呈现非线性演化特征。在南亚热带森林生态系统演替的早期阶段,生态系统服务价值的最大组分是涵养水源的功能价值,而中、后期则是保育土壤。人工林营造可以有效增强区域生态系统的水源涵养能力,而保育演替中、后期森林则对于大气CO2收和土壤保育而言尤为重要。     

Modelling forest management within a global vegetation model—Part 1: Model structure and general behaviour

This article describes a new forest management module (FMM) that explicitly simulates forest stand growth and management within a process-based global vegetation model (GVM) called ORCHIDEE. The net primary productivity simulated by ORCHIDEE is used as an input to the FMM. The FMM then calculates stand and management characteristics such as stand density, tree size distribution, tree growth, the timing and intensity of thinnings and clear-cuts, wood extraction and litter generated after thinning. Some of these variables are then fed back to ORCHIDEE. These computations are made possible with a distribution-based modelling of individual tree size. The model derives natural mortality from the relative density index (rdi), a competition index based on tree size and stand density. Based on the common forestry management principle of avoiding natural mortality, a set of rules is defined to calculate the recurrent intensity and frequency of forestry operations during the stand lifetime. The new-coupled model is called ORCHIDEE-FM (forest management).The general behaviour of ORCHIDEE-FM is analysed for a broadleaf forest in north-eastern France. Flux simulation throughout a forest rotation compare well with the literature values, both in absolute values and dynamics.Results from ORCHIDEE-FM highlight the impact of forest management on ecosystem C-cycling, both in terms of carbon fluxes and stocks. In particular, the average net ecosystem productivity (NEP) of 225 gC m⁻² year⁻¹ is close to the biome average of 311 gC m⁻² year⁻¹. The NEP of the “unmanaged” case is 40% lower, leading us to conclude that management explains 40% of the cumulated carbon sink over 150 years. A sensitivity analysis reveals 4 major avenues for improvement: a better determination of initial conditions, an improved allocation scheme to explain age-related decline in productivity, and an increased specificity of both the self-thinning curve and the biomass-diameter allometry.     

鼎湖山森林演替序列水文过程中总有机碳(TOC)变化规律及其对土壤碳平衡的贡献

森林水文过程中的总有机碳转运对土壤有机碳平衡起着重要的作用,但我们对于水文过程对碳平衡的贡献机理所知甚少.本研究针对鼎湖山季风常绿阔叶林演替序列不同森林生态系统(马尾松林、针阔混交林和季风常绿阔叶林(简称季风林))的大气降水、穿透水、树干流、凋落物淋洗水以及地表径流中的总有机碳(TOC)进行了三年(2002年4月-2005年5月)观测,以此来分析水文学过程中TOC的变化规律和水文学过程对不同成熟度森林生态系统土壤有机碳积累的贡献.每场雨后进行水样的采集,采集的水样装入棕色玻璃瓶中,加硫酸至pH值小于2,放置于实验室冰箱冷藏待测.TOC用日本岛津公司生产的5000A型TOC-V分析仪测定.研究结果及推论如下:鼎湖山森林水文学过程中TOC浓度和总量变化呈现规律性的变化.大气降水中的TOC浓度和总量分别为(3.65±0.59)mg·L~(-1)和51.8104 kg·hm~(-2)·a~(-1),大气降水是鼎湖山森林生态系统水文循环过程中TOC的主要来源.穿透水(DTF)中TOC浓度和总量均为:松林>混交林>季风林,其中季风林TOC浓度显著低于其他两种林型.松林树干流的TOC浓度显著高于混交林和季风林.凋落物淋洗水TOC浓度和总量大小依次均为:松林>混交林>季风林,且三林型间存在显著差异(p<0.05).径流中TOC浓度和总量均较小,且无明显差异.在湿季5月份,穿透水、树干流、凋落物淋洗水的TOC浓度呈现下降趋势.干季(10月)开始以后,穿透水、树干流、凋落物淋洗水中的TOC浓度又逐步回升.地表径流中TOC浓度干湿季变化趋势不明显.干季中各水文学分量TOC浓度大于湿季,但TOC总量呈现相反趋势.在森林水文学过程中,凋落物淋洗水所携带的有机碳量是土壤有机碳输入的最大项,季风林、混交林、松林中TOC总量分别为246.983 kg·hm~(-2)·a~(-1),255.187kg·hm~(-2)·a~(-1)和261.876kg·hm~(-2)·a~(-1);其次是直接到达土壤表面的穿透水,季风林、混交林、松林中TOC总量分别为28.152kg·hm~(-2)·a~(-1),37.410kg·hm~(-2)·a~(-1)和43.176kg·hm~(-2)·a~(-1);树干流中有机碳浓度虽高,但总量很微小,季风林、混交林、松林中TOC总量分别为4.663kg·hm~(-2)·a~(-1),5.910kg·hm~(-2)·a~(-1)和4.566kg·hm~(-2)·a~(-1),所以对土壤有机碳收入贡献不大.径流所携带的TOC总量很小,季风林、混交林、松林中分别为8.707kg·hm~(-2)·a~(-1),9.318kg·hm~(-2)·a~(-1),7.220kg·hm~(-2)·a~(-1).由此可知,水文过程输入土壤的TOC总量远大于径流所带走的TOC总量,导致了水文过程中的TOC存留在土壤中,对土壤有机碳(SOC)的积累起着重要作用.季风林、混交林和马尾松林土壤每年通过水文学过程净输入的有机碳量分别为(27.1+1.65)g·m~(-2),(28.9±2.79)g·m~(-2)和(30.2±2.65)g·m~(-2).水文学过程中的这部分有机碳由于占总有机碳比例较小往往被忽视,但是正是由于水分在土壤中的下渗使得有机碳的分布趋于均匀,这将更加利于SOC的积累和保存.     

气候变暖背景下森林土壤碳循环研究进展

由人类活动引起的温室效应以及由此造成的气候变暖对森林牛态系统的影响已引起人们的普遍关注.森林土壤碳循环作为全球碳循环的重要组成部分,是决定未来陆地牛物嘲表现为碳源/碳汇的关键环节,揭示这一作用对于准确理解全球变化背景下陆地生态系统碳循环过程具有重要的指导意义.本文主要通过论述影响土壤碳循环过程的5个方面(土壤呼吸、土壤微生物、土壤酶活性、凋落物输入与分解、土壤碳库),综述了近10 a来全球气候变暖对土壤碳循环过程的影响.近年来,尽管已开展了大量有关土壤碳循环对气候变暖的响应及反馈机制的研究,并取得了一定的成果,但研究结果仍然存在很大的不确定性.整合各种密切关联的全球变化现象,完善研究方法和实验手段,加强根际微生态系统碳循环过程与机理研究将是下一步研究的方向和重点.参70     

Carbon sequestration in Taiwan harvested wood products

This study, with FAOSTAT and Taiwan data sources, estimates Taiwan carbon dioxide (CO₂) emissions in harvested wood products (HWP) by applying the three accounting methods suggested by the 2006 IPCC Guidelines. The investigation also explores impulse responses of CO₂ emissions to economic factors. Results from FAOSTAT and Taiwan data demonstrate an inconsistent production approach (PA) in the signs of the estimated CO₂ emissions. Average contributions of HWP from 1990 to 2008 for the stock change approach (SCA), PA and atmospheric flow approach (AFA) in Taiwan are ?3.195 Tg, 0.412 Tg and 10.632 Tg CO₂ emissions, respectively. SCA has determined the Taiwan HWP as a carbon reservoir; in contrast, PA and AFA have determined Taiwan HWP as a CO₂ emission. The net forest products imports into Taiwan induce the inconsistent signs of HWP carbon sequestration among SCA, PA and AFA. The vector autoregressive model (VAR) results also indicate that real GDP per capita is crucial for SCA CO₂ emissions, followed by exchange rate.     

Response of tree growth to a changing climate in boreal central Canada: A comparison of empirical,process-based,and hybrid modelling approaches

The impact of 2 × CO₂ driven climate change on radial growth of boreal tree species Pinus banksiana Lamb., Populus tremuloides Michx. and Picea mariana (Mill.) BSP growing in the Duck Mountain Provincial Forest of Manitoba (DMPF), Canada, is simulated using empirical and process-based model approaches. First, empirical relationships between growth and climate are developed. Stepwise multiple-regression models are conducted between tree-ring growth increments (TRGI) and monthly drought, precipitation and temperature series. Predictive skills are tested using a calibration–verification scheme. The established relationships are then transferred to climates driven by 1× and 2 × CO₂ scenarios using outputs from the Canadian second-generation coupled global climate model. Second, empirical results are contrasted with process-based projections of net primary productivity allocated to stem development (NPP_s). At the finest scale, a leaf-level model of photosynthesis is used to simulate canopy properties per species and their interaction with the variability in radiation, temperature and vapour pressure deficit. Then, a top-down plot-level model of forest productivity is used to simulate landscape-level productivity by capturing the between-stand variability in forest cover. Results show that the predicted TRGI from the empirical models account for up to 56.3% of the variance in the observed TRGI over the period 1912–1999. Under a 2 × CO₂ scenario, the predicted impact of climate change is a radial growth decline for all three species under study. However, projections obtained from the process-based model suggest that an increasing growing season length in a changing climate could counteract and potentially overwhelm the negative influence of increased drought stress. The divergence between TRGI and NPP_s simulations likely resulted, among others, from assumptions about soil water holding capacity and from calibration of variables affecting gross primary productivity. An attempt was therefore made to bridge the gap between the two modelling approaches by using physiological variables as TRGI predictors. Results obtained in this manner are similar to those obtained using climate variables, and suggest that the positive effect of increasing growing season length would be counteracted by increasing summer temperatures. Notwithstanding uncertainties in these simulations (CO₂ fertilization effect, feedback from disturbance regimes, phenology of species, and uncertainties in future CO₂ emissions), a decrease in forest productivity with climate change should be considered as a plausible scenario in sustainable forest management planning of the DMPF.     

Spatially distributed modeling of the long-term carbon balance of a boreal landscape

Spatially and temporally distributed information on the sizes of biomass carbon (C) pools (BCPs) and soil C pools (SCPs) is vital for improving our understanding of biosphere-atmosphere C fluxes. Because the sizes of C pools result from the integrated effects of primary production, age-effects, changes in climate, atmospheric CO₂ concentration, N deposition, and disturbances, a modeling scheme that interactively considers these processes is important. We used the InTEC model, driven by various spatio-temporal datasets to simulate the long-term C-balance in a boreal landscape in eastern Canada. Our results suggested that in this boreal landscape, mature coniferous stands had stabilized their productivity and fluctuated as a weak C-sink or C-source depending on the interannual variations in hydrometeorological factors. Disturbed deciduous stands were larger C-sinks (NEP₂₀₀₄ = 150 gC m⁻² yr⁻¹) than undisturbed coniferous stands (e.g. NEP₂₀₀₄ = 8 gC m⁻² yr⁻¹). Wetlands had lower NPP but showed temporally consistent C accumulation patterns. The simulated spatio-temporal patterns of BCPs and SCPs were unique and reflected the integrated effects of climate, plant growth and atmospheric chemistry besides the inherent properties of the C pool themselves. The simulated BCPs and SCPs generally compared well with the biometric estimates (BCPs: r = 0.86, SCPs: r = 0.84). The largest BCP biases were found in recently disturbed stands and the largest SCP biases were seen in locations where moss necro-masses were abundant. Reconstructing C pools and C fluxes in the ecosystem in such a spatio-temporal manner could help reduce the uncertainties in our understanding of terrestrial C-cycle.     

Effects of boreal forest management practices on the climate impact of CO2 emissions from bioenergy

In Life Cycle Assessment (LCA), carbon dioxide (CO₂) emissions from biomass combustion are traditionally assumed climate neutral if the bioenergy system is CO₂ flux neutral, i.e. the quantity of CO₂ released approximately equals the amount of CO₂ sequestered in biomass. This convention is a plausible assumption for fast growing biomass species, but is inappropriate for slower growing biomass, like forests. In this case, the climate impact from biomass combustion can be potentially underestimated if CO₂ emissions are ignored, or overestimated, if biogenic CO₂ is considered equal to anthropogenic CO₂. The estimation of the effective climate impact should take into account how the CO₂ fluxes are distributed over time: the emission of CO₂ from bioenergy approximately occurs at a single point in time, while the absorption by the new trees is spread over several decades. Our research target is to include this dynamic time dimension in unit-based impact analysis, using a boreal forest stand as case study. The boreal forest growth is modelled with an appropriate function, and is investigated under different forestry regimes (affecting the growth rate and the year of harvest). Specific atmospheric decay functions for biomass-derived CO₂ are then elaborated for selected combinations of forest management options. The contribution to global warming is finally quantified using the GWP_bio index as climate metric. Results estimates the effects of these practices on the characterization factor used for the global warming potential of CO₂ from bioenergy, and point out the key role played by the selected time horizon.