A process-based model designed for filling of large data gaps in tower-based measurements of net ecosystem productivity

In this paper we present a simple hybrid gap-filling model (GFM) designed with a minimum number of parameters necessary to capture the ecological processes important for filling medium-to-large gaps in Flux data. As the model is process-based, the model has potential to be used in filling large gaps exhibiting a broad range of micro-meteorological and site conditions. The GFM performance was evaluated using “Punch hole” and extrapolation experiments based on data collected in west-central New Brunswick. These experiments indicated that the GFM is able to provide acceptable results (r² > 0.80) when >500 data points are used in model parameterization. The GFM was shown to address daytime evolution of NEP reasonably well for a wide range of weather and site conditions. An analysis of residuals indicated that for the most part no obvious trends were evident; although a slight bias was detected in NEP with soil temperature. To explore the portability of the GFM across ecosystem types, a transcontinental validation was conducted using NEP and ancillary data from seven ecosystems along a north-south transect (i.e., temperature–moisture gradient) from northern Europe (Finland) to the Middle East (Israel). The GFM was shown to explain over 75% of the variability in NEP measured at most ecosystems, which strongly suggests that the GFM maybe successfully applied to forest ecosystems outside Canada.     

A sensitivity analysis of an ecosystem model of estuarine carbon flow

The North Inlet Marsh-Estuarine System Model (NIMES) is a 19-compartment real-time deterministic ecosystem simulation model of intrasystem carbon flow and exchange between an estuary and adjacent coastal water. A complete sensitivity analysis of this model with regard to POM, DOM and nekton annual exchange and annual system net productivity was completed and the functional relationship between these system behaviors and the perturbed parameters were determined by regression techniques. Simulated POM annual exchange between the estuary and the sea was largely controlled by offshore POM concentration, water column respiration and the gross productivity of the marsh and water column flora. Simulated DOM annual estuarine-oceanic exchange was most sensitive to perturbations in the gross productivity and biomass changes in marsh flora and water column microbial DOM uptake. Simulated nekton exchange reflected a sensitivity to migratory behavior and subtidal benthic biomass changes. System annual net productivity as simulated by the model showed a high sensitivity to all model processes which affected component primary production and respiration. From this sensitivity analysis, a scheme is developed to evaluate research needs for further model development for the North Inlet ecosystem.     

Marine-derived nutrients, bioturbation, and ecosystem metabolism: reconsidering the role of salmon in streams

In coastal areas of the North Pacific Ocean, annual returns of spawning salmon provide a substantial influx of nutrients and organic matter to streams and are generally believed to enhance the productivity of recipient ecosystems. Loss of this subsidy from areas with diminished salmon runs has been hypothesized to limit ecosystem productivity in juvenile salmon rearing habitats (lakes and streams), thereby reinforcing population declines. Using five to seven years of data from an Alaskan stream supporting moderate salmon densities, we show that salmon predictably increased stream water nutrient concentrations, which were on average 190% (nitrogen) and 390% (phosphorus) pre-salmon values, and that primary producers incorporated some of these nutrients into tissues. However, benthic algal biomass declined by an order of magnitude despite increased nutrients. We also measured changes in stream ecosystem metabolic properties, including gross primary productivity (GPP) and ecosystem respiration (ER), from three salmon streams by analyzing diel measurements of oxygen concentrations and stable isotopic ratios (delta O-O2) within a Bayesian statistical model of oxygen dynamics. Our results do not support a shift toward higher primary productivity with the return of salmon, as is expected from a nutrient fertilization mechanism. Rather, net ecosystem metabolism switched from approximately net autotrophic (GPP > or = ER) to a strongly net heterotrophic state (GPP < ER) in response to bioturbation of benthic habitats by salmon. Following the seasonal arrival of salmon, GPP declined to <12% of pre-salmon rates, while ER increased by over threefold. Metabolism by live salmon could not account for the observed increase in ER early in the salmon run, suggesting salmon nutrients and disturbance enhanced in situ heterotrophic respiration. Salmon also changed the physical properties of the stream, increasing air-water gas exchange by nearly 10-fold during peak spawning. We suggest that management efforts to restore salmon ecosystems should consider effects on ecosystem metabolic properties and how salmon disturbance affects the incorporation of marine-derived nutrients into food webs.     

Inter-annual variability of ecosystem production in boreal jack pine forests (1975-2004) estimated from tree-ring data using CBM-CFS3

We describe and apply a method of using tree-ring data and an ecosystem model to reconstruct past annual rates of ecosystem production. Annual data on merchantable wood volume increment and mortality obtained by dendrochronological stand reconstruction were used as input to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate net ecosystem production (NEP), net primary production (NPP), and heterotrophic respiration (Rh) annually from 1975 to 2004 at 10 boreal jack pine (Pinus banksiana Lamb.) stands in Saskatchewan and Manitoba, Canada. From 1975 (when sites aged 41-60 years) to 2004 (when they aged 70-89 years), all sites were moderate C sinks except during some warmer than average years where estimated Rh increased. Across all sites and years, estimated annual NEP averaged 57 g Cm⁻² yr⁻¹ (range −31 to 176 g Cm⁻² yr⁻¹), NPP 244 g Cm⁻² yr⁻¹ (147-376 g Cm⁻² yr⁻¹), and Rh 187 g Cm⁻² yr⁻¹ (124-270 g Cm⁻² yr⁻¹). Across all sites, NPP was related to stand age and density, which are proxies for successional changes in leaf area. Regionally, warm spring temperature increased NPP and defoliation by jack pine budworm 1 year previously reduced NPP. Our estimates of NPP, Rh, and NEP were plausible when compared to regional eddy covariance and carbon stock measurements. Inter-annual variability in ecosystem productivity contributes uncertainty to inventory-based assessments of regional forest C budgets that use yield curves predicting averaged growth over time. Our method could expand the spatial and temporal coverage of annual forest productivity estimates, providing additional data for the development of empirical models accounting for factors not presently considered by these models.     

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.     

不同海拔高寒放牧草甸的生态系统呼吸与环境因子的关系

在全球变化的背景下,为了研究藏北高寒放牧草甸的生态系统呼吸和土壤呼吸特征,沿着3个海拔高度（4 300、4 500和4 700 m）观测了2010年7-9月白天的呼吸通量。同时,观测了同期的土壤温度、土壤水分含量、空气温度和相对湿度,在定性分析土壤水分含量和呼吸通量关系的基础上,将其分成低、中和高3个水平,在此基础上,分析生态系统呼吸、土壤呼吸与土壤温度、土壤水分含量、空气温度以及相对湿度的关系。结果表明,空气温度是决定生态系统呼吸和土壤呼吸变异的主导因子;生态系统呼吸、土壤呼吸以及裸地的土壤呼吸的Q10值分别为1.83～3.07、1.54～4.13和1.29～2.89;总体而言,生态系统呼吸和土壤呼吸Q10值随着海拔的升高和土壤水分含量的增加而增大。     

深圳福田秋茄红树林生态系统碳循环的初步研究

滨海红树林的生产力极高,在全球碳循环中占有重要地位,但是其碳循环的系统测定却鲜见报道。以深圳福田秋茄林为研究对象,2011年4月-2012年4月对内滩天然林、中滩和外滩人工林的植被、凋落物、粗木质残体、土壤的碳密度和净增量,以及植被和土壤呼吸进行了实际观测,并探讨了土壤有机碳来源,初步构建了秋茄林沿不同滩位的生态系统碳循环模式。结果表明,深圳福田秋茄林的碳密度在234.58～694.46 t.hm^-2之间,其中植被碳密度为44.54～239.51 t.hm^-2,凋落物和粗木质残体碳密度为2.02～24.56 t.hm^-2,土壤碳密度（深度为50 cm）为188.02～430.39 t.hm^-2,生态系统碳密度整体上表现为自内滩向外滩降低的趋势。在研究时段内,3个滩位的植被碳密度净增量为4.31～13.28 t.hm^-2.a^-1,凋落物和土壤碳密度没有显著变化。红树林的凋落物生成量为2.17～10.55 t.hm^-2.a^-1,约有49.94～94.01%通过食草动物、冲入海洋和腐烂分解等途径消耗。植被呼吸量为2.20～12.08 t.hm^-2.a^-1,土壤微生物的异氧呼吸量为0.25～1.61 t.hm^-2.a^-1,甲烷排放为0.09～0.31 t.hm^-2.a^-1,土壤有机碳输入约18.99%～44.43%来自植被内源输入,其余来源于海洋碳输入。生态系统的总初级生产力介于8.68～35.91t.hm^-2.a^-1之间,约有47.38%～74.08%转变为净初级生产力（6.48～23.84 t.hm^-2.a^-1）。碳平衡分析表明,在研究时段内,内滩的天然林是个很大的碳汇,约20.08 t.hm^-2.a^-1,中滩和外滩的人工林碳汇量分别为9.98 t.hm^-2.a^-1和4.03 t.hm^-2.a^-1。相对于陆地森林,秋茄红树林有着显著的碳汇效益,在全球碳循环中起着不可忽视的作用。     

Estimating California ecosystem carbon change using process model and land cover disturbance data: 1951-2000

Land use change, natural disturbance, and climate change directly alter ecosystem productivity and carbon stock level. The estimation of ecosystem carbon dynamics depends on the quality of land cover change data and the effectiveness of the ecosystem models that represent the vegetation growth processes and disturbance effects. We used the Integrated Biosphere Simulator (IBIS) and a set of 30- to 60-m resolution fire and land cover change data to examine the carbon changes of California's forests, shrublands, and grasslands. Simulation results indicate that during 1951-2000, the net primary productivity (NPP) increased by 7%, from 72.2 to 77.1 Tg C yr⁻¹ (1 teragram = 10¹² g), mainly due to CO₂ fertilization, since the climate hardly changed during this period. Similarly, heterotrophic respiration increased by 5%, from 69.4 to 73.1 Tg C yr⁻¹, mainly due to increased forest soil carbon and temperature. Net ecosystem production (NEP) was highly variable in the 50-year period but on average equalled 3.0 Tg C yr⁻¹ (total of 149 Tg C). As with NEP, the net biome production (NBP) was also highly variable but averaged −0.55 Tg C yr⁻¹ (total of -27.3 Tg C) because NBP in the 1980s was very low (-5.34 Tg C yr⁻¹). During the study period, a total of 126 Tg carbon were removed by logging and land use change, and 50 Tg carbon were directly removed by wildland fires. For carbon pools, the estimated total living upper canopy (tree) biomass decreased from 928 to 834 Tg C, and the understory (including shrub and grass) biomass increased from 59 to 63 Tg C. Soil carbon and dead biomass carbon increased from 1136 to 1197 Tg C.Our analyses suggest that both natural and human processes have significant influence on the carbon change in California. During 1951-2000, climate interannual variability was the key driving force for the large interannual changes of ecosystem carbon source and sink at the state level, while logging and fire were the dominant driving forces for carbon balances in several specific ecoregions. From a long-term perspective, CO₂ fertilization plays a key role in maintaining higher NPP. However, our study shows that the increase in C sequestration by CO₂ fertilization is largely offset by logging/land use change and wildland fires.     

森林生态系统中土壤呼吸研究进展

土壤呼吸是土壤微生物活性和土壤肥力的一个重要指标，是土壤碳流通的一个重要过程，也是陆地生态系统碳循环的一个关键部分，对研究全球变化有非常重要影响。文章综述了森林生态系统土壤呼吸的各种测量方法，比较了静态气室法和动态气室法的优缺点，认为动态红外气体分析法是最可靠的方法之一；探讨了影响土壤呼吸速率的各种因素，指出在各生物和非生物因素中，温度对土壤呼吸的影响最大；最后提出了土壤呼吸研究过程中存在的一些问题及今后的发展方向。     

Nitrogen controls on ecosystem carbon sequestration: a model implementation and application to Saskatchewan,Canada

A plant–soil nitrogen (N) cycling model was developed and incorporated into the Integrated BIosphere Simulator (IBIS) of Foley et al. [Foley, J.A., Prentice, I.C., Ramankutty, N., Levis, S., Pollard, D., Sitch, S., Haxeltine, A., 1996. An integrated biosphere model of land surface process, terrestrial carbon balance and vegetation dynamics. Global Biogeochem. Cycles 10, 603–628]. In the N-model, soil mineral N regulates ecosystem carbon (C) fluxes and ecosystem C:N ratios. Net primary productivity (NPP) is controlled by feedbacks from both leaf C:N and soil mineral N. Leaf C:N determines the foliar and canopy photosynthesis rates, while soil mineral N determines the N availability for plant growth and the efficiency of biomass construction. Nitrogen controls on the decomposition of soil organic matter (SOM) are implemented through N immobilization and mineralization separately. The model allows greater SOM mineralization at lower mineral N, and conversely, allows greater N immobilization at higher mineral N. The model's seasonal and inter-annual behaviours are demonstrated. A regional simulation for Saskatchewan, Canada, was performed for the period 1851–2000 at a 10 km × 10 km resolution. Simulated NPP was compared with high-resolution (1 km × 1 km) NPP estimated from remote sensing data using the boreal ecosystem productivity simulator (BEPS) [Liu, J., Chen, J.M., Cihlar, J., Park, W.M., 1997. A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sens. Environ. 44, 81–87]. The agreement between IBIS and BEPS, particularly in NPP spatial variation, was considerably improved when the N controls were introduced into IBIS.     

Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.     

Modeling patterns of nonlinearity in ecosystem responses to temperature, CO2, and precipitation changes.

It is commonly acknowledged that ecosystem responses to global climate change are nonlinear. However, patterns of the nonlinearity have not been well characterized on ecosystem carbon and water processes. We used a terrestrial ecosystem (TECO) model to examine nonlinear patterns of ecosystem responses to changes in temperature, CO2, and precipitation individually or in combination. The TECO model was calibrated against experimental data obtained from a grassland ecosystem in the central United States and ran for 100 years with gradual change at 252 different scenarios. We primarily used the 100th-year results to explore nonlinearity of ecosystem responses. Variables examined in this study are net primary production (NPP), heterotrophic respiration (R(h)), net ecosystem carbon exchange (NEE), runoff, and evapotranspiration (ET). Our modeling results show that nonlinear patterns were parabolic, asymptotic, and threshold-like in response to temperature, CO2, and precipitation anomalies, respectively, for NPP, NEE, and R(h). Runoff and ET exhibited threshold-like pattern in response to both temperature and precipitation anomalies but were less sensitive to CO2 changes. Ecosystem responses to combined temperature, CO2, and precipitation anomalies differed considerably from the responses to individual factors in terms of response patterns and/or critical points of nonlinearity. Our results suggest that nonlinear patterns in response to multiple global-change factors were diverse and were considerably affected by combined climate anomalies on ecosystem carbon and water processes. The diverse response patterns in nonlinearity have profound implications for both experimental design and theoretical development.     

青海湖高寒湿地生态系统夏季CO2通量日变化及其影响因子研究

利用涡度相关技术对青海湖高寒湿地生态系统夏季CO２通量日变化特征进行分析,并且结合气象观测数据对CO２通量日变化的影响因子进行探讨。结果表明,青海湖高寒湿地生态系统夏季CO２通量日变化呈“U”字型,白天8：00—20：00 CO２通量值为负,其他时间为正,最低值出现在12：30,为-15.34 μmol·m-2·s-1。CO２通量日平均值为-3.65 μmol·m-2·s-1（约-13.87 g·m-2·d-1）,表现为明显的CO２吸收,是重要的碳汇。CO２通量与净辐射、气温和表层土壤温度的相关性分析表明,净辐射是影响青海湖高寒湿地生态系统夏季CO２通量日变化的主要因子,气温次之,表层土壤温度对CO２通量的影响最小。采用多元回归分析得出CO２通量与各个影响因子之间的关系符合三元一次线性回归方程,R2=0.689,且达到极显著水平（P〈0.01）。     

Dealing with microtopography of an ombrotrophic bog for simulating ecosystem-level CO2 exchanges

Peatlands contain approximately 25% of the global soil carbon (C), despite covering only 3% of the earth's land surface. In order to evaluate the role of peatlands in global C cycling, models of ecosystem biogeochemistry are required, but peatland ecosystems present a number of unique challenges, particularly how to deal with the large variability that occurs at scales of one to several metres. In models, spatial variability is considered either explicitly for each individual unit and the outputs averaged, referred to as flux upscaling, or implicitly by weighting model parameters by the fractional occurrence of the individual units, referred to as parameter upscaling. The advantage of parameter upscaling is that it is much more computationally efficient: a requirement for hemispheric scale simulations. In this study we determined the differences between modelling a raised bog peatland with hummock-hollow microtopography using flux and parameter upscaling. We used the McGill Wetland Model (MWM), a process-based ecosystem C model for peatlands, configured for hummocks and hollows separately and then a weighted mixture of both. The simulated output based on flux and parameter upscaling was compared with eddy-covariance tower measurements. We found that net ecosystem production (NEP) for hollows was much larger than that for hummocks because total ecosystem respiration (TER) for hummocks was greater while gross primary production (GPP) did not differ significantly between the two topographic features. However, despite differences in components of NEP between hummocks and hollows, there was no statistically significant difference between the NEP based on flux and parameter upscaling using the MWM. Both flux and parameter upscaling show equivalent capability to capture the magnitude, direction, seasonality and inter-annual variability. The root-mean-square-errors (RMSE) are 0.66, 0.45, and 0.49 g C m⁻² day⁻¹, respectively for GPP, TER and NEP based on the flux upscaling, while 0.67, 0.44, and 0.48 g C m⁻² day⁻¹, respectively based on the parameter upscaling. The degree of agreement (d*) is 0.96, 0.97, and 0.88, respectively for GPP, TER and NEP based on the flux upscaling, while 0.96, 0.97, and 0.89, respectively based on the parameter upscaling. This result suggests that differences in processes caused by peatland microtopography scale linearly, which means an ecosystem-level model set-up (i.e. parameter upscaling scheme), is sufficient to simulate the C cycling.     

On temperature and water limitation of net ecosystem productivity: Implementation in the C-Fix model

Monitoring, understanding and modelling carbon emission and fixation fluxes are key actions to guide climate change stakeholders in the application of mitigation strategies. In this study, we use the remote sensing model C-Fix at the local stand scale to improve the integration of algorithms for water and temperature limitation. These new algorithms are applied to estimate net ecosystem productivity in a fully water limited mode.     

Using nocturnal cold air drainage flow to monitor ecosystem processes in complex terrain.

This paper presents initial investigations of a new approach to monitor ecosystem processes in complex terrain on large scales. Metabolic processes in mountainous ecosystems are poorly represented in current ecosystem monitoring campaigns because the methods used for monitoring metabolism at the ecosystem scale (e.g., eddy covariance) require flat study sites. Our goal was to investigate the potential for using nocturnal down-valley winds (cold air drainage) for monitoring ecosystem processes in mountainous terrain from two perspectives: measurements of the isotopic composition of ecosystem-respired CO2 (delta13C(ER)) and estimates of fluxes of CO2 transported in the drainage flow. To test if this approach is plausible, we monitored the wind patterns, CO2 concentrations, and the carbon isotopic composition of the air as it exited the base of a young (approximately 40 yr-old) and an old (>450 yr-old) steeply sided Douglas-fir watershed. Nocturnal cold air drainage within these watersheds was strong, deep, and occurred on more than 80% of summer nights. The depth of cold air drainage rapidly increased to tower height or greater when the net radiation at the top of the tower approached zero. The carbon isotope composition of CO2 in the drainage system holds promise as an indicator of variation in basin-scale physiological processes. Although there was little vertical variation in CO2 concentration at any point in time, we found that the range of CO2 concentration over a single evening was sufficient to estimate delta 13C(ER) from Keeling plot analyses. The seasonal variation in delta 13C(ER) followed expected trends: during the summer dry season delta 13C(ER) became less negative (more enriched in 13C), but once rain returned in the fall, delta 13C(ER) decreased. However, we found no correlation between recent weather (e.g., vapor pressure deficit) and delta 13C(ER) either concurrently or with up to a one-week lag. Preliminary estimates suggest that the nocturnal CO2 flux advecting past the 28-m tower is a rather small fraction (<20%) of the watershed-scale respiration. This study demonstrates that monitoring the isotopic composition and CO2 concentration of cold air drainage at the base of a watershed provides a new tool for quantifying ecosystem metabolism in mountainous ecosystems on the basin scale.     

区域能源碳足迹计算模型比较研究——以湖北省为例

能源消费排放是最主要的碳排放来源,研究能源碳足迹重要理论和现实意义。如何准确计算和表征能源碳足迹的大小成为该研究领域的重要问题。在文献回顾的基础上,文章总结了3种目前应用较广泛的计算区域能源消费碳足迹的方法和模型,它们分别是碳汇法、净初级生产力改进模型和净生态系统生产力改进模型。分别介绍了其计算公式、输入参数和计算过程。以湖北省1998-2009年能源消费碳足迹的计算为例,分别用这几种方法计算了能源消费碳足迹的总量和人均碳足迹。得到的主要结论有：研究区域能源消费碳排放量增长较快,3种方法和模型计算得到的碳足迹总量和人均量从时间序列上看,整体变化趋势一致,碳足迹亦呈现快速增长。但3种模型计算出的碳足迹大小差异较大,碳汇法模型足迹最大,净生态系统生产力改进模型次之,净初级生产力改进模型结果最小,并且碳汇法的计算结果明显大于其他两种模型。计算结果差异的原因在于,传统碳汇法模型只考虑林地的碳吸收能力,忽略了区域其他用地类型的碳吸收能力。净初级生产力改进模型考虑了各种用地类型的吸收能力,但从生态系统来说忽略了异氧呼吸的碳释放,高估了区域的碳吸收能力。几种模型都运用了固定值或者平均统计量,未能考虑地域差异,同时未考虑各统计量随时间和气候等变化而变化的可能,存在一定的不合理性,这也是今后研究值得深人研究的方向。     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.     

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.