How uncertainties in future climate change predictions translate into future terrestrial carbon fluxes

We forced a global terrestrial carbon cycle model by climate fields of 14 ocean and atmosphere general circulation models (OAGCMs) to simulate the response of terrestrial carbon pools and fluxes to climate change over the next century. These models participated in the second phase of the Coupled Model Intercomparison Project (CMIP2), where a 1% per year increase of atmospheric CO₂ was prescribed. We obtain a reduction in net land uptake because of climate change ranging between 1.4 and 5.7 Gt C yr^?1 at the time of atmospheric CO₂ doubling. Such a reduction in terrestrial carbon sinks is largely dominated by the response of tropical ecosystems, where soil water stress occurs. The uncertainty in the simulated land carbon cycle response is the consequence of discrepancies in land temperature and precipitation changes simulated by the OAGCMs. We use a statistical approach to assess the coherence of the land carbon fluxes response to climate change. The biospheric carbon fluxes and pools changes have a coherent response in the tropics, in the Mediterranean region and in high latitudes of the Northern Hemisphere. This is because of a good coherence of soil water content change in the first two regions and of temperature change in the high latitudes of the Northern Hemisphere. Then we evaluate the carbon uptake uncertainties to the assumptions on plant productivity sensitivity to atmospheric CO₂ and on decomposition rate sensitivity to temperature. We show that these uncertainties are on the same order of magnitude than the uncertainty because of climate change. Finally, we find that the OAGCMs having the largest climate sensitivities to CO₂ are the ones with the largest soil drying in the tropics, and therefore with the largest reduction of carbon uptake.     

Feedback of carbon and nitrogen cycles enhances carbon sequestration in the terrestrial biosphere

The efforts to explain the ‘missing sink’ for anthropogenic carbon dioxide (CO₂) have included in recent years the role of nitrogen as an important constraint for biospheric carbon fluxes. We used the Nitrogen Carbon Interaction Model (NCIM) to investigate patterns of carbon and nitrogen storage in different compartments of the terrestrial biosphere as a consequence of a rising atmospheric CO₂ concentration, in combination with varying levels of nitrogen availability. This model has separate but closely coupled carbon and nitrogen cycles with a focus on soil processes and soil–plant interactions, including an active compartment of soil microorganisms decomposing litter residues and competing with plants for available nitrogen. Biological nitrogen fixation is represented as a function of vegetation nitrogen demand. The model was validated against several global datasets of soil and vegetation carbon and nitrogen pools. Five model experiments were carried out for the modeling periods 1860–2002 and 2002–2100. In these experiments we varied the nitrogen availability using different combinations of biological nitrogen fixation, denitrification, leaching of soluble nitrogen compounds with constant or rising atmospheric CO₂ concentrations. Oversupply with nitrogen, in an experiment with nitrogen fixation, but no nitrogen losses, together with constant atmospheric CO₂, led to some carbon sequestration in organismic pools, which was nearly compensated by losses of C from soil organic carbon pools. Rising atmospheric CO₂ always led to carbon sequestration in the biosphere. Considering an open nitrogen cycle including dynamic nitrogen fixation, and nitrogen losses from denitrification and leaching, the carbon sequestration in the biosphere is of a magnitude comparable to current observation based estimates of the ‘missing sink.’ A fertilization feedback between the carbon and nitrogen cycles occurred in this experiment, which was much stronger than the sum of separate influences of high nitrogen supply and rising atmospheric CO₂. The demand‐driven biological nitrogen fixation was mainly responsible for this result. For the modeling period 2002–2100, NCIM predicts continued carbon sequestration in the low range of previously published estimates, combined with a plausible rate of CO₂‐driven biological nitrogen fixation and substantial redistribution of nitrogen from soil to plant pools.     

磷影响陆地生态系统碳循环过程及模型表达方法

全球气候变暖已大大改变了陆地植物碳吸收能力, 提高了全球植被净初级生产力。随着气候变暖的加剧, 磷对植物生长的限制作用逐渐显现且不断增强, 磷影响陆地生态系统碳循环的机理和模型研究已成为研究热点。该文系统分析了磷影响陆地生态系统碳循环的相关机理以及模型对相关过程的定量化表达方法。综合对比分析了国际上的Carnegie- Ames-Stanford Approach-CNP (CASA-CNP)、Community Land Model-CNP (CLM-CNP)和Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg-CNP (JSBACH-CNP)等碳、氮、磷耦合模型中磷影响植物光合作用与同化物分配过程、植物对磷的吸收过程、土壤中磷的转化过程以及生态系统磷输入与输出等过程的相关数学表达方法, 指出了模型算法的局限与不确定性以及未来模型发展与改进的方向。同时综合对比分析了CASA-CNP、CLM-CNP、JSBACH-CNP模型的基本特征, 总结了磷循环模型的建模方法, 为未来开展磷影响陆地生态系统碳循环的模型模拟研究提供了借鉴方法与参考思路。     

Predictability of the terrestrial carbon cycle

Terrestrial ecosystems sequester roughly 30% of anthropogenic carbon emission. However this estimate has not been directly deduced from studies of terrestrial ecosystems themselves, but inferred from atmospheric and oceanic data. This raises a question: to what extent is the terrestrial carbon cycle intrinsically predictable? In this paper, we investigated fundamental properties of the terrestrial carbon cycle, examined its intrinsic predictability, and proposed a suite of future research directions to improve empirical understanding and model predictive ability. Specifically, we isolated endogenous internal processes of the terrestrial carbon cycle from exogenous forcing variables. The internal processes share five fundamental properties (i.e., compartmentalization, carbon input through photosynthesis, partitioning among pools, donor pool‐dominant transfers, and the first‐order decay) among all types of ecosystems on the Earth. The five properties together result in an emergent constraint on predictability of various carbon cycle components in response to five classes of exogenous forcing. Future observational and experimental research should be focused on those less predictive components while modeling research needs to improve model predictive ability for those highly predictive components. We argue that an understanding of predictability should provide guidance on future observational, experimental and modeling research.     

Implications of CO2 fertilization for future climate change in a coupled climate–carbon model

The terrestrial carbon cycle plays a critical role in determining levels of atmospheric CO₂ that result from anthropogenic carbon emissions. Elevated atmospheric CO₂ is thought to stimulate terrestrial carbon uptake, through the process of CO₂ fertilization of vegetation productivity. This negative carbon cycle feedback results in reduced atmospheric CO₂ growth, and has likely accounted for a substantial portion of the historical terrestrial carbon sink. However, the future strength of CO₂ fertilization in response to continued carbon emissions and atmospheric CO₂ rise is highly uncertain. In this paper, the ramifications of CO₂ fertilization in simulations of future climate change are explored, using an intermediate complexity coupled climate–carbon model. It is shown that the absence of future CO₂ fertilization results in substantially higher future CO₂ levels in the atmosphere, as this removes the dominant contributor to future terrestrial carbon uptake in the model. As a result, climate changes are larger, though the radiative effect of higher CO₂ on surface temperatures in the model is offset by about 30% due to reduced positive dynamic vegetation feedbacks; that is, the removal of CO₂ fertilization results in less vegetation expansion in the model, which would otherwise constitute an important positive surface albedo‐temperature feedback. However, the effect of larger climate changes has other important implications for the carbon cycle – notably to further weaken remaining carbon sinks in the model. As a result, positive climate–carbon cycle feedbacks are larger when CO₂ fertilization is absent. This creates an interesting synergism of terrestrial carbon cycle feedbacks, whereby positive (climate–carbon cycle) feedbacks are amplified when a negative (CO₂ fertilization) feedback is removed.     

Reconciling estimates of the contemporary North American carbon balance among terrestrial biosphere models,atmospheric inversions,and a new approach for estimating net ecosystem exchange from inventory‐based data

We develop an approach for estimating net ecosystem exchange (NEE) using inventory‐based information over North America (NA) for a recent 7‐year period (ca. 2000–2006). The approach notably retains information on the spatial distribution of NEE, or the vertical exchange between land and atmosphere of all non‐fossil fuel sources and sinks of CO₂, while accounting for lateral transfers of forest and crop products as well as their eventual emissions. The total NEE estimate of a ?327 ± 252 TgC yr^?1 sink for NA was driven primarily by CO₂ uptake in the Forest Lands sector (?248 TgC yr^?1), largely in the Northwest and Southeast regions of the US, and in the Crop Lands sector (?297 TgC yr^?1), predominantly in the Midwest US states. These sinks are counteracted by the carbon source estimated for the Other Lands sector (+218 TgC yr^?1), where much of the forest and crop products are assumed to be returned to the atmosphere (through livestock and human consumption). The ecosystems of Mexico are estimated to be a small net source (+18 TgC yr^?1) due to land use change between 1993 and 2002. We compare these inventory‐based estimates with results from a suite of terrestrial biosphere and atmospheric inversion models, where the mean continental‐scale NEE estimate for each ensemble is ?511 TgC yr^?1 and ?931 TgC yr^?1, respectively. In the modeling approaches, all sectors, including Other Lands, were generally estimated to be a carbon sink, driven in part by assumed CO₂ fertilization and/or lack of consideration of carbon sources from disturbances and product emissions. Additional fluxes not measured by the inventories, although highly uncertain, could add an additional ?239 TgC yr^?1 to the inventory‐based NA sink estimate, thus suggesting some convergence with the modeling approaches.     

陆地碳循环的动态非平衡假说

生态系统维持物质与能量的动态平衡是地球系统孕育与维持生物多样性的重要基础。自工业革命以来, 人类活动导致陆地生态系统的碳循环转变为动态非平衡,进而使陆地生态系统的结构与功能出现许多难以预测的变化动态。本文阐释了陆地生态系统碳循环的动态非平衡假说。该假说构建于陆地碳循环内部过程的四点基本特征和五类外部驱动因素。基于这些内部特征与外部因素, 本文归纳了陆地生态系统碳循环动态非平衡在不同时间与空间尺度的表达现象, 并从观测、实验与模型的角度讨论了其检测方法。陆地生态系统碳循环的动态非平衡假说不仅有助于我们理解复杂的陆地碳循环现象, 也为预测未来陆地碳汇动态提供了新的理论框架。     

Simulation of terrestrial carbon equilibrium state by using a detachable carbon cycle scheme

Determining the equilibrium state of terrestrial carbon is a prerequisite for scientific analysis on the carbon cycle. However, the mechanism through which the carbon cycle reaches the equilibrium state remains unclear. Moreover, the carbon cycle in most of the short–term field experiments rarely reaches the equilibrium state. In this study, a detachable carbon cycle (DCC) model was proposed to simulate the equilibrium state of each carbon pool. The model was established based on a pool–and–flux scheme and contained 14 carbon pools, or carbon flow processes, each process could be detached from the main model and evaluated as an independent component. The environmental scalar algorithms of the Integrated Terrestrial Ecosystem Carbon budget model (InTEC) and Community Atmosphere Biosphere Land Exchange (CABLE) were incorporated in the DCC model. Four situations were compared using the two environmental scalar algorithms and model structure (9 vs. 14 carbon pools). Furthermore, the size and turnover time of each carbon pool were analyzed at the equilibrium state. A sensitivity analysis was then conducted to investigate the responses of carbon density and equilibrium time to 12 key parameters of the model. Results indicated that the combination of the CABLE environmental scalar algorithm and 14 pools exhibited improved performance on carbon storage simulation than that of the other combinations, and the effect of the environmental scalar algorithm was considerably larger than that of the carbon pool number. Sensitivity analysis indicated that the carbon density of grassland and cropland was more vulnerable and sensitive to key parameters of the model than that of the other biomes. This study elucidates influencing factors and underlying control mechanisms in the carbon accumulation, and provides a framework for quantitative analysis of each component of the carbon cycle.     

Effects of climate extremes on the terrestrial carbon cycle: concepts,processes and potential future impacts

Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance‐induced mechanisms and processes to also operate in an extreme context. The paucity of well‐defined studies currently renders a quantitative meta‐analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land‐cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground‐based observational case studies reveals that many regions in the (sub‐)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon–climate feedbacks.     

Urban ecosystems and the North American carbon cycle

Approximately 75–80% of the population of North America currently lives in urban areas as defined by national census bureaus, and urbanization is continuing to increase. Future trajectories of fossil fuel emissions are associated with a high degree of uncertainty; however, if the activities of urban residents and the rate of urban land conversion can be captured in urban systems models, plausible emissions scenarios from major cities may be generated. Integrated land use and transportation models that simulate energy use and traffic‐related emissions are already in place in many North American cities. To these can be added a growing dataset of carbon gains and losses in vegetation and soils following urbanization, and a number of methods of validating urban carbon balance modeling, including top down atmospheric monitoring and urban ‘metabolic’ studies of whole ecosystem mass and energy flow. Here, we review the state of our understanding of urban areas as whole ecosystems with regard to carbon balance, including both drivers of fossil fuel emissions and carbon cycling in urban plants and soils. Interdisciplinary, whole‐ecosystem studies of the socioeconomic and biophysical factors that influence urban carbon cycles in a range of cities may greatly contribute to improving scenarios of future carbon balance at both continental and global scales.     

Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends

The purpose of this study was to evaluate 10 process‐based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux‐tower‐based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO₂ trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO₂ sensitivity of NPP is compared to the results from four Free‐Air CO₂ Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr^?1) than JU11 (118 ± 6 Pg C yr^?1). In response to rising atmospheric CO₂ concentration, modeled NPP increases on average by 16% (5–20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO₂ than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr^?1 is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr^?1). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980–2009. Both model‐to‐model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is ?3.0 ± 1.5 Pg C yr^?1 °C^?1, within the uncertainty of what derived from RLS (?3.9 ± 1.1 Pg C yr^?1 °C^?1). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO₂ and climate, the agreement between modeled and observation‐based GPP and NBP can be fortuitous. Carbon–nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO₂ concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.     

Modelling the vegetation of China using the process-based equilibrium terrestrial biosphere model BIOME3

1 We model the potential vegetation and annual net primary production (NPP) of China on a 10′ grid under the present climate using the processed‐based equilibrium terrestrial biosphere model BIOME3. The simulated distribution of the vegetation was in general in good agreement with the potential natural vegetation based on a numerical comparison between the two maps using the ΔV statistic (ΔV = 0.23). Predicted and measured NPP were also similar, especially in terms of biome‐averages. 2 A coupled ocean–atmosphere general circulation model including sulphate aerosols was used to drive a double greenhouse gas scenario for 2070–2099. Simulated vegetation maps from two different CO₂ scenarios (340 and 500 p.p.m.v.) were compared to the baseline biome map using ΔV. Climate change alone produced a large reduction in desert, alpine tundra and ice/polar desert, and a general pole‐ward shift of the boreal, temperate deciduous, warm–temperate evergreen and tropical forest belts, a decline in boreal deciduous forest and the appearance of tropical deciduous forest. The inclusion of CO₂ physiological effects led to a marked decrease in moist savannas and desert, a general decrease for grasslands and steppe, and disappearance of xeric woodland/scrub. Temperate deciduous broadleaved forest, however, shifted north to occupy nearly half the area of previously temperate mixed forest. 3 The impact of climate change and increasing CO₂ is not only on biogeography, but also on potential NPP. The NPP values for most of the biomes in the scenarios with CO₂ set at 340 p.p.m.v. and 500 p.p.m.v. are greater than those under the current climate, except for the temperate deciduous forest, temperate evergreen broadleaved forest, tropical rain forest, tropical seasonal forest, and xeric woodland/scrub biomes. Total vegetation and total carbon is simulated to increase significantly in the future climate scenario, both with and without the CO₂ direct physiological effect. 4 Our results show that the global process‐based equilibrium terrestrial biosphere model BIOME3 can be used successfully at a regional scale.     

中国陆地土壤有机碳蓄积量估算误差分析

简要介绍了土壤碳蓄积量的计算方法,包括土壤类型法、植被类型法、生命地带法、相关关系法和模型方法,以及土壤有机碳蓄积量的误差分析方法．根据中国策二次土壤普查2473个典型土种剖面数据,采用土壤类型法和两种碳密度方法计算,估算的中国陆地土壤有机碳蓄积量处于615.19×10^14-1211.37×10^14g之间,平均碳密度为10．49-10．53kg·m^-2(土壤厚度为100cm)或11．52-12．04kg·m^-3(土壤平均厚度为88cm),土壤平均碳蓄积量为913．28±298．09×10^14g,估算的不确定性在20％～50％之间．其中,土壤碳计算和采样数量的差异是导致土壤碳蓄积量估算不确定性的重要因素。     

The high-latitude terrestrial carbon sink: a model analysis

A dynamic, global vegetation model, hybrid v4.1 ( Friend et al. 1997 ), was driven by transient climate output from the UK Hadley Centre GCM (HadCM2) with the IS92a scenario of increasing atmospheric CO₂ equivalent, sulphate aerosols and predicted patterns of atmospheric N deposition. Changes in areas of vegetation types and carbon storage in biomass and soils were predicted for areas north of 50°N from 1860 to 2100. Hybrid is a combined biogeochemical, biophysical and biogeographical model of natural, potential ecosystems. The effect of periodic boreal forest fires was assessed by adding a simple stochastic fire model. Hybrid represents plant physiological and soil processes regulating the carbon, water and N cycles and competition between individuals of parameterized generalized plant types. The latter were combined to represent tundra, temperate grassland, temperate/mixed forest and coniferous forest. The model simulated the current areas and estimated carbon stocks in the four vegetation types. It was predicted that land areas above 50°N (about 23% of the vegetated global land area) are currently accumulating about 0.4 PgC y^?1 (about 30% of the estimated global terrestrial sink) and that this sink could grow to 0.8–1.0 PgC y^?1 by the second half of the next century and persist undiminished until 2100. This sink was due mainly to an increase in forest productivity and biomass in response to increasing atmospheric CO₂, temperature and N deposition, and includes an estimate of the effect of boreal forest fire, which was estimated to diminish the sink approximately by the amount of carbon emitted to the atmosphere during fires. Averaged over the region, N deposition contributed about 18% to the sink by the 2080 s. As expected, climate change (temperature, precipitation, solar radiation and saturation pressure deficit) and N deposition without increasing atmospheric CO₂ produced a carbon source. Forest areas expanded both south and north, halving the current tundra area by 2100. This expansion contributed about 30% to the sink by the 2090 s. Tundra areas which were not invaded by forest fluctuated from sink to source. It was concluded that a high latitude carbon sink exists at present and, even assuming little effect of N deposition, no forest expansion and continued boreal forest fires, the sink is likely to persist at its current level for a century.     

CO2 stabilization,climate change and the terrestrial carbon sink

A nonequilibrium, dynamic, global vegetation model, Hybrid v4.1, with a subdaily timestep, was driven by increasing CO₂ and transient climate output from the UK Hadley Centre GCM (HadCM2) with simulated daily and interannual variability. Three IPCC emission scenarios were used: (i) IS92a, giving 790 ppm CO₂ by 2100, (ii) CO₂ stabilization at 750 ppm by 2225, and (iii) CO₂ stabilization at 550 ppm by 2150. Land use and future N deposition were not included. In the IS92a scenario, boreal and tropical lands warmed 4.5 °C by 2100 with rainfall decreased in parts of the tropics, where temperatures increased over 6 °C in some years and vapour pressure deficits (VPD) doubled. Stabilization at 750 ppm CO₂ delayed these changes by about 100 years while stabilization at 550 ppm limited the rise in global land surface temperature to 2.5 °C and lessened the appearance of relatively hot, dry areas in the tropics. Present‐day global predictions were 645 PgC in vegetation, 1190 PgC in soils, a mean carbon residence time of 40 years, NPP 47 PgC y^?1 and NEP (the terrestrial sink) about 1 PgC y^?1, distributed at both high and tropical latitudes. With IS92a emissions, the high latitude sink increased to the year 2100, as forest NPP accelerated and forest vegetation carbon stocks increased. The tropics became a source of CO₂ as forest dieback occurred in relatively hot, dry areas in 2060–2080. High VPDs and temperatures reduced NPP in tropical forests, primarily by reducing stomatal conductance and increasing maintenance respiration. Global NEP peaked at 3–4 PgC y^?1 in 2020–2050 and then decreased abruptly to near zero by 2100 as the tropical source offset the high‐latitude sink. The pattern of change in NEP was similar with CO₂ stabilization at 750 ppm, but was delayed by about 100 years and with a less abrupt collapse in global NEP. CO₂ stabilization at 550 ppm prevented sustained tropical forest dieback and enabled recovery to occur in favourable years, while maintaining a similar time course of global NEP as occurred with 750 ppm stabilization. By lessening dieback, stabilization increased the fraction of carbon emissions taken up by the land. Comparable studies and other evidence are discussed: climate‐induced tropical forest dieback is considered a plausible risk of following an unmitigated emissions scenario.     

The role of amoeboid protists and the microbial community in moss-rich terrestrial ecosystems: biogeochemical implications for the carbon budget and carbon cycle, especially at higher latitudes

Moss-rich terrestrial communities are widely distributed in low- and high-latitude environments, covering vast surface areas in the boreal forests and tundra. The microbial biota in these organic-rich communities may contribute substantially to the carbon budget of terrestrial communities and the carbon cycle on a global scale. Recent research is reported on the carbon content of microbial communities in some temperate and high-latitude moss communities. The total carbon content and potential respiratory carbon dioxide (CO(2)) efflux is reported for bacteria, microflagellates, naked amoebae, and testate amoebae within sampling sites at a northeastern forest and the tundra at Toolik, Alaska. Quantitative models of the predicted total CO(2) efflux from the microbes, based on microscopic observations and enumeration of the microbiota in samples from the research sites, are described and predictions are compared with published field-based data of CO(2) efflux. The significance of the predictions for climate change and global warming are discussed.     

Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model

The Lund–Potsdam–Jena Dynamic Global Vegetation Model (LPJ) combines process‐based, large‐scale representations of terrestrial vegetation dynamics and land‐atmosphere carbon and water exchanges in a modular framework. Features include feedback through canopy conductance between photosynthesis and transpiration and interactive coupling between these ‘fast’ processes and other ecosystem processes including resource competition, tissue turnover, population dynamics, soil organic matter and litter dynamics and fire disturbance. Ten plants functional types (PFTs) are differentiated by physiological, morphological, phenological, bioclimatic and fire‐response attributes. Resource competition and differential responses to fire between PFTs influence their relative fractional cover from year to year. Photosynthesis, evapotranspiration and soil water dynamics are modelled on a daily time step, while vegetation structure and PFT population densities are updated annually. Simulations have been made over the industrial period both for specific sites where field measurements were available for model evaluation, and globally on a 0.5°° × 0.5°° grid. Modelled vegetation patterns are consistent with observations, including remotely sensed vegetation structure and phenology. Seasonal cycles of net ecosystem exchange and soil moisture compare well with local measurements. Global carbon exchange fields used as input to an atmospheric tracer transport model (TM2) provided a good fit to observed seasonal cycles of CO₂ concentration at all latitudes. Simulated inter‐annual variability of the global terrestrial carbon balance is in phase with and comparable in amplitude to observed variability in the growth rate of atmospheric CO₂. Global terrestrial carbon and water cycle parameters (pool sizes and fluxes) lie within their accepted ranges. The model is being used to study past, present and future terrestrial ecosystem dynamics, biochemical and biophysical interactions between ecosystems and the atmosphere, and as a component of coupled Earth system models.     

FLUXNET and modelling the global carbon cycle

Measurements of the net CO₂ flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO₂ source–sink patterns, CO₂ flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO₂ (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model‐data comparison. Flux measurements made over four vegetation types were used to calibrate the land‐surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land‐surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO₂ uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). This model is forced by satellite‐measured absorbed radiation and suggests that global net primary production (NPP) increased 6.2% over 1982–1999. Good agreement is found between global trends in NPP estimated by the PEM and a dynamic global vegetation model (DGVM), and between the DGVM and estimates of global NEE derived from a global inversion of atmospheric CO₂ measurements. Combining the PEM, DGVM, and inversion results suggests that CO₂ fertilization is playing a major role in current increases in NPP, with lesser impacts from increasing N deposition and growing season length. Both the PEM and the inversion identify the Amazon basin as a key region for the current net terrestrial CO₂ uptake (i.e. 33% of global NEE), as well as its interannual variability. The inversion's global NEE estimate of −1.2 Pg [C] yr⁻¹ for 1982–1995 is compatible with the PEM‐ and DGVM‐predicted trends in NPP. There is, thus, a convergence in understanding derived from process‐based models, remote‐sensing‐based observations, and inversion of atmospheric data. Future advances in field measurement techniques, including eddy covariance (particularly concerning the problem of night‐time fluxes in dense canopies and of advection or flow distortion over complex terrain), will result in improved constraints on land‐atmosphere CO₂ fluxes and the rigorous attribution of mechanisms to the current terrestrial net CO₂ uptake and its spatial and temporal heterogeneity. Global ecosystem models play a fundamental role in linking information derived from FLUXNET measurements to atmospheric CO₂ variability. A number of recommendations concerning FLUXNET data are made, including a request for more comprehensive site data (particularly historical information), more measurements in undisturbed ecosystems, and the systematic provision of error estimates. The greatest value of current FLUXNET data for global carbon cycle modelling is in evaluating process representations, rather than in providing an unbiased estimate of net CO₂ exchange.     

Observing terrestrial ecosystems and the carbon cycle from space

Terrestrial ecosystem and carbon cycle feedbacks will significantly impact future climate, but their responses are highly uncertain. Models and tipping point analyses suggest the tropics and arctic/boreal zone carbon–climate feedbacks could be disproportionately large. In situ observations in those regions are sparse, resulting in high uncertainties in carbon fluxes and fluxes. Key parameters controlling ecosystem carbon responses, such as plant traits, are also sparsely observed in the tropics, with the most diverse biome on the planet treated as a single type in models. We analyzed the spatial distribution of in situ data for carbon fluxes, stocks and plant traits globally and also evaluated the potential of remote sensing to observe these quantities. New satellite data products go beyond indices of greenness and can address spatial sampling gaps for specific ecosystem properties and parameters. Because environmental conditions and access limit in situ observations in tropical and arctic/boreal environments, use of space‐based techniques can reduce sampling bias and uncertainty about tipping point feedbacks to climate. To reliably detect change and develop the understanding of ecosystems needed for prediction, significantly, more data are required in critical regions. This need can best be met with a strategic combination of remote and in situ data, with satellite observations providing the dense sampling in space and time required to characterize the heterogeneity of ecosystem structure and function.