Impulse response functions of terrestrial carbon cycle models: method and application

To provide a common currency for model comparison, validation and manipulation, we suggest and describe the use of impulse response functions, a concept well-developed in other fields, but only partially developed for use in terrestrial carbon cycle modelling. In this paper, we describe the derivation of impulse response functions, and then examine (i) the dynamics of a simple five-box biosphere carbon model; (ii) the dynamics of the CASA biosphere model, a spatially explicit NPP and soil carbon biogeochemistry model; and (iii) various diagnostics of the two models, including the latitudinal distribution of mean age, mean residence time and turnover time. We also (i) deconvolve the past history of terrestrial NPP from an estimate of past carbon sequestration using a derived impulse response function to test the performance of impulse response functions during periods of historical climate change; (ii) convolve impulse response functions from both the simple five-box model and the CASA model against a historical record of atmospheric δ¹³C to estimate the size of the terrestrial ¹³C isotopic disequilibrium; and (iii) convolve the same impulse response functions against a historical record of atmospheric ¹⁴C to estimate the ¹⁴C content and isotopic disequilibrium of the terrestrial biosphere at the 1° × 1° scale. Given their utility in model comparison, and the fact that they facilitate a number of numerical calculations that are difficult to perform with the complex carbon turnover models from which they are derived, we strongly urge the inclusion of impulse response functions as a diagnostic of the perturbation response of terrestrial carbon cycle models.     

The contributions of land-use change, CO2 fertilization, and climate variability to the Eastern US carbon sink

Atmospheric measurements and land‐based inventories imply that terrestrial ecosystems in the northern hemisphere are taking up significant amounts of anthropogenic cabon dioxide (CO₂) emissions; however, there is considerable disagreement about the causes of this uptake, and its expected future trajectory. In this paper, we use the ecosystem demography (ED) model to quantify the contributions of disturbance history, CO₂ fertilization and climate variability to the past, current, and future terrestrial carbon fluxes in the Eastern United States. The simulations indicate that forest regrowth following agricultural abandonment accounts for uptake of 0.11 Pg C yr^?1 in the 1980s and 0.15 Pg C yr^?1 in the 1990s, and regrowth following forest harvesting accounts for an additional 0.1 Pg C yr^?1 of uptake during both these decades. The addition of CO₂ fertilization into the model simulations increases carbon uptake rates to 0.38 Pg C yr^?1 in the 1980s and 0.47 Pg C yr^?1 in the 1990s. Comparisons of predicted aboveground carbon uptake to regional‐scale forest inventory measurements indicate that the model's predictions in the absence of CO₂ fertilization are 14% lower than observed, while in the presence of CO₂ fertilization, predicted uptake rates are 28% larger than observed. Comparable results are obtained from comparisons of predicted total Net Ecosystem Productivity to the carbon fluxes observed at the Harvard Forest flux tower site and in model simulations free‐air CO₂ enrichment (FACE) experiments. These results imply that disturbance history is the principal mechanism responsible for current carbon uptake in the Eastern United States, and that conventional biogeochemical formulations of plant growth overestimate the response of plants to rising CO₂ levels. Model projections out to 2100 imply that the carbon uptake arising from forest regrowth will increasingly be dominated by forest regrowth following harvesting. Consequently, actual carbon storage declines to near zero by the end of the 21st century as the forest regrowth that has occurred since agricultural abandonment comes into equilibrium with the landscape's new disturbance regime. Incorporating interannual climate variability into the model simulations gives rise to large interannual variation in regional carbon fluxes, indicating that long‐term measurements are necessary to detect the signature of processes that give rise to long‐term uptake and storage.     

Net biome production of the Amazon Basin in the 21st century

Global change includes multiple stressors to natural ecosystems ranging from direct climate and land‐use impacts to indirect degradation processes resulting from fire. Humid tropical forests are vulnerable to projected climate change and possible synergistic interactions with deforestation and fire, which may initiate a positive feedback to rising atmospheric CO₂. Here, we present results from a multifactorial impact analysis that combined an ensemble of climate change models with feedbacks from deforestation and accidental fires to quantify changes in Amazon Basin carbon cycling. Using the LPJmL Dynamic Global Vegetation Model, we modelled spatio‐temporal changes in net biome production (NBP); the difference between carbon fluxes from fire, deforestation, soil respiration and net primary production. By 2050, deforestation and fire (with no CO₂ increase or climate change) resulted in carbon losses of 7.4–20.3 Pg C with the range of uncertainty depending on socio‐economic storyline. During the same time period, interactions between climate and land use either compensated for carbon losses due to wetter climate and CO₂ fertilization or exacerbated carbon losses from drought‐induced forest mortality (?20.1 to +4.3 Pg C). By the end of the 21st century, depending on climate projection and the rate of deforestation (including its interaction with fire), carbon stocks either increased (+12.6 Pg C) or decreased (?40.6 Pg C). The synergistic effect of deforestation and fire with climate change contributed up to 26–36 Pg C of the overall decrease in carbon stocks. Agreement between climate projections (n=9), not accounting for deforestation and fire, in 2050 and 2098 was relatively low for the directional change in basin‐wide NBP (19–37%) and aboveground live biomass (13–24%). The largest uncertainty resulted from climate projections, followed by implementation of ecosystem dynamics and deforestation. Our analysis partitions the drivers of tropical ecosystem change and is relevant for guiding mitigation and adaptation policy related to global change.     

中国东北样带植被净初级生产力时空动态遥感模拟

 中国东北样带(Northeast China Transect, NECT)是中纬度半干旱区的国际地圈-生物圈计划(IGBP)陆地样带之一, 是全球变化研究的 重要手段与热点。该研究应用生态系统碳循环过程CASA(Carnegie-Ames-Stanford Approach)模型分析了NECT从1982~1999年植被净初级生产力 (Net primary productivity, NPP)的时空变异及其影响因子。结果表明, 1) 1982~1999年NECT植被NPP为58 ~ 811 g C·m^–2·a^–1, 平均为426 g C·m^–2·a^–1, 大体上呈现由东向西逐渐递减的趋势; 2)研究时段内NECT的总NPP变异范围是0.218 ~ 0.325 Pg C, 平均为0.270 Pg C (1 Pg = 10¹⁵ g); 3) NECT的总NPP在过去18年内整体呈显著性增加趋势, 其中从1982~1990年样带NPP呈显著性增加趋势, 而后期1991~1999样带NPP没 有显著性变化趋势; 4)沿NECT不同植被类型对气候变化的响应特征是不同的, 在研究时段内, 农田、典型草原和草甸草原表现出最大的NPP增加 量, 而典型草原、荒漠草原对气候变化表现出高的敏感性; 5) NECT植被NPP的空间分布格局是由年降水量的分布格局所决定, 而NPP的时间变异 则由年降水量、年太阳总辐射的变化所影响驱动。     

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.     

Combining meteorology, eddy fluxes, isotope measurements, and modeling to understand environmental controls of carbon isotope discrimination at the canopy scale

Estimates of terrestrial carbon isotope discrimination are useful to quantify the terrestrial carbon sink. Carbon isotope discrimination by terrestrial ecosystems may vary on seasonal and interannual time frames, because it is affected by processes (e.g. photosynthesis, stomatal conductance, and respiration) that respond to variable environmental conditions (e.g. air humidity, temperature, light). In this study, we report simulations of the temporal variability of canopy‐scale C₃ photosynthetic carbon isotope discrimination obtained with an ecophysiologically based model (ISOLSM) designed for inclusion in global models. ISOLSM was driven by half‐hourly meteorology, and parameterized with eddy covariance measurements of carbon and energy fluxes and foliar carbon isotope ratios from a pine forest in Metolius (OR). Comparing simulated carbon and energy fluxes with observations provided a range of parameter values that optimized the simulated fluxes. We found that the sensitivity of photosynthetic carbon isotope discrimination to the slope of the stomatal conductance equation (m, Ball–Berry constant) provided an additional constraint to the model, reducing the wide parameter space obtained from the fluxes alone. We selected values of m that resulted in similar simulated long‐term discrimination as foliar isotope ratios measured at the site. The model was tested with ¹³C measurements of ecosystem (δ_R) and foliar (δ_f) respiration. The daily variability of simulated ¹³C values of assimilated carbon (δ_A) was similar to that of observed δ_f, and higher than that of observed and simulated δ_R. We also found similar relationships between environmental factors (i.e. vapor pressure deficit) and simulated δ_R as measured in ecosystem surveys of δ_R. Therefore, ISOLSM reasonably simulated the short‐term variability of δ_A controlled by atmospheric conditions at the canopy scale, which can be useful to estimate the variability of terrestrial isotope discrimination. Our study also shows that including the capacity to simulate carbon isotope discrimination, together with simple ecosystem isotope measurements, can provide a useful constraint to land surface and carbon balance models.     

Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models

The possible responses of ecosystem processes to rising atmospheric CO₂ concentration and climate change are illustrated using six dynamic global vegetation models that explicitly represent the interactions of ecosystem carbon and water exchanges with vegetation dynamics. The models are driven by the IPCC IS92a scenario of rising CO₂ ( Wigley et al. 1991 ), and by climate changes resulting from effective CO₂ concentrations corresponding to IS92a, simulated by the coupled ocean atmosphere model HadCM2‐SUL. Simulations with changing CO₂ alone show a widely distributed terrestrial carbon sink of 1.4–3.8 Pg C y^?1 during the 1990s, rising to 3.7–8.6 Pg C y^?1 a century later. Simulations including climate change show a reduced sink both today (0.6–3.0 Pg C y^?1) and a century later (0.3–6.6 Pg C y^?1) as a result of the impacts of climate change on NEP of tropical and southern hemisphere ecosystems. In all models, the rate of increase of NEP begins to level off around 2030 as a consequence of the ‘diminishing return’ of physiological CO₂ effects at high CO₂ concentrations. Four out of the six models show a further, climate‐induced decline in NEP resulting from increased heterotrophic respiration and declining tropical NPP after 2050. Changes in vegetation structure influence the magnitude and spatial pattern of the carbon sink and, in combination with changing climate, also freshwater availability (runoff). It is shown that these changes, once set in motion, would continue to evolve for at least a century even if atmospheric CO₂ concentration and climate could be instantaneously stabilized. The results should be considered illustrative in the sense that the choice of CO₂ concentration scenario was arbitrary and only one climate model scenario was used. However, the results serve to indicate a range of possible biospheric responses to CO₂ and climate change. They reveal major uncertainties about the response of NEP to climate change resulting, primarily, from differences in the way that modelled global NPP responds to a changing climate. The simulations illustrate, however, that the magnitude of possible biospheric influences on the carbon balance requires that this factor is taken into account for future scenarios of atmospheric CO₂ and climate change.     

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.     

Diagnosing and assessing uncertainties of terrestrial ecosystem models in a multimodel ensemble experiment: 2. Carbon balance

This paper examines carbon stocks and their relative balance in terrestrial ecosystems simulated by Biome‐BGC, LPJ, and CASA in an ensemble model experiment conducted using the Terrestrial Observation and Prediction System. We developed the Hierarchical Framework for Diagnosing Ecosystem Models to separate the simulated biogeochemistry into a cascade of functional tiers and examine their characteristics sequentially. The analyses indicate that the simulated biomass is usually two to three times higher in Biome‐BGC than LPJ or CASA. Such a discrepancy is mainly induced by differences in model parameters and algorithms that regulate the rates of biomass turnover. The mean residence time of biomass in Biome‐BGC is estimated to be 40–80 years in temperate/moist climate regions, while it mostly varies between 5 and 30 years in CASA and LPJ. A large range of values is also found in the simulated soil carbon. The mean residence time of soil carbon in Biome‐BGC and LPJ is ～200 years in cold regions, which decreases rapidly with increases of temperature at a rate of ～10 yr °C^?1. Because long‐term soil carbon pool is not simulated in CASA, its corresponding mean residence time is only about 10–20 years and less sensitive to temperature. Another key factor that influences the carbon balance of the simulated ecosystem is disturbance caused by wildfire, for which the algorithms vary among the models. Because fire emissions are balanced by net ecosystem production (NEP) at steady states, magnitudes, and spatial patterns of NEP vary significantly as well. Slight carbon imbalance may be left by the spin‐up algorithm of the models, which adds uncertainty to the estimated carbon sources or sinks. Although these results are only drawn on the tested model versions, the developed methodology has potential for other model exercises.     

Terrestrial nitrogen–carbon cycle interactions at the global scale

Interactions between the terrestrial nitrogen (N) and carbon (C) cycles shape the response of ecosystems to global change. However, the global distribution of nitrogen availability and its importance in global biogeochemistry and biogeochemical interactions with the climate system remain uncertain. Based on projections of a terrestrial biosphere model scaling ecological understanding of nitrogen–carbon cycle interactions to global scales, anthropogenic nitrogen additions since 1860 are estimated to have enriched the terrestrial biosphere by 1.3 Pg N, supporting the sequestration of 11.2 Pg C. Over the same time period, CO₂ fertilization has increased terrestrial carbon storage by 134.0 Pg C, increasing the terrestrial nitrogen stock by 1.2 Pg N. In 2001–2010, terrestrial ecosystems sequestered an estimated total of 27 Tg N yr⁻¹ (1.9 Pg C yr⁻¹), of which 10 Tg N yr⁻¹ (0.2 Pg C yr⁻¹) are due to anthropogenic nitrogen deposition. Nitrogen availability already limits terrestrial carbon sequestration in the boreal and temperate zone, and will constrain future carbon sequestration in response to CO₂ fertilization (regionally by up to 70% compared with an estimate without considering nitrogen–carbon interactions). This reduced terrestrial carbon uptake will probably dominate the role of the terrestrial nitrogen cycle in the climate system, as it accelerates the accumulation of anthropogenic CO₂ in the atmosphere. However, increases of N₂O emissions owing to anthropogenic nitrogen and climate change (at a rate of approx. 0.5 Tg N yr⁻¹ per 1°C degree climate warming) will add an important long-term climate forcing.     

Carbon cost of plant nitrogen acquisition: global carbon cycle impact from an improved plant nitrogen cycle in the Community Land Model

Plants typically expend a significant portion of their available carbon (C) on nutrient acquisition – C that could otherwise support growth. However, given that most global terrestrial biosphere models (TBMs) do not include the C cost of nutrient acquisition, these models fail to represent current and future constraints to the land C sink. Here, we integrated a plant productivity‐optimized nutrient acquisition model – the Fixation and Uptake of Nitrogen Model – into one of the most widely used TBMs, the Community Land Model. Global plant nitrogen (N) uptake is dynamically simulated in the coupled model based on the C costs of N acquisition from mycorrhizal roots, nonmycorrhizal roots, N‐fixing microbes, and retranslocation (from senescing leaves). We find that at the global scale, plants spend 2.4 Pg C yr^?1 to acquire 1.0 Pg N yr^?1, and that the C cost of N acquisition leads to a downregulation of global net primary production (NPP) by 13%. Mycorrhizal uptake represented the dominant pathway by which N is acquired, accounting for ~66% of the N uptake by plants. Notably, roots associating with arbuscular mycorrhizal (AM) fungi – generally considered for their role in phosphorus (P) acquisition – are estimated to be the primary source of global plant N uptake owing to the dominance of AM‐associated plants in mid‐ and low‐latitude biomes. Overall, our coupled model improves the representations of NPP downregulation globally and generates spatially explicit patterns of belowground C allocation, soil N uptake, and N retranslocation at the global scale. Such model improvements are critical for predicting how plant responses to altered N availability (owing to N deposition, rising atmospheric CO₂, and warming temperatures) may impact the land C sink.     

Climatic role of terrestrial ecosystem under elevated CO2: a bottom‐up greenhouse gases budget

The net balance of greenhouse gas (GHG) exchanges between terrestrial ecosystems and the atmosphere under elevated atmospheric carbon dioxide (CO₂) remains poorly understood. Here, we synthesise 1655 measurements from 169 published studies to assess GHGs budget of terrestrial ecosystems under elevated CO₂. We show that elevated CO₂ significantly stimulates plant C pool (NPP) by 20%, soil CO₂ fluxes by 24%, and methane (CH₄) fluxes by 34% from rice paddies and by 12% from natural wetlands, while it slightly decreases CH₄ uptake of upland soils by 3.8%. Elevated CO₂ causes insignificant increases in soil nitrous oxide (N₂O) fluxes (4.6%), soil organic C (4.3%) and N (3.6%) pools. The elevated CO₂‐induced increase in GHG emissions may decline with CO₂ enrichment levels. An elevated CO₂‐induced rise in soil CH₄ and N₂O emissions (2.76 Pg CO₂‐equivalent year^?1) could negate soil C enrichment (2.42 Pg CO₂ year^?1) or reduce mitigation potential of terrestrial net ecosystem production by as much as 69% (NEP, 3.99 Pg CO₂ year^?1) under elevated CO₂. Our analysis highlights that the capacity of terrestrial ecosystems to act as a sink to slow climate warming under elevated CO₂ might have been largely offset by its induced increases in soil GHGs source strength.     

Modeling the effects of snowpack on heterotrophic respiration across northern temperate and high latitude regions: Comparison with measurements of atmospheric carbon dioxide in high latitudes

Simulations by global terrestrial biogeochemical models (TBMs) consistently underestimate the concentration of atmospheric carbon dioxide (CO₂ at high latitude monitoring stations during the non-growing season. We hypothesized that heterotrophic respiration is underestimated during the nongrowing season primarily because TBMs do not generally consider the insulative effects of snowpack on soil temperature. To evaluate this hypothesis, we compared the performance of baseline and modified versions of three TBMs in simulating the seasonal cycle of atmospheric CO₂ at high latitude CO₂ monitoring stations; the modified version maintained soil temperature at 0 °C when modeled snowpack was present. The three TBMs include the Carnegie-Ames-Stanford Approach (CASA), Century, and the Terrestrial Ecosystem Model (TEM). In comparison with the baseline simulation of each model, the snowpack simulations caused higher releases of CO₂ between November and March and greater uptake of CO₂ between June and August for latitudes north of 30° N. We coupled the monthly estimates of CO₂ exchange, the seasonal carbon dioxide flux fields generated by the HAMOCC3 seasonal ocean carbon cycle model, and fossil fuel source fields derived from standard sources to the three-dimensional atmospheric transport model TM2 forced by observed winds to simulate the seasonal cycle of atmospheric CO₂ at each of seven high latitude monitoring stations. In comparison to the CO₂ concentrations simulated with the baseline fluxes of each TBM, concentrations simulated using the snowpack fluxes are generally in better agreement with observed concentrations between August and March at each of the monitoring stations. Thus, representation of the insulative effects of snowpack in TBMs generally improves simulation of atmospheric CO₂ concentrations in high latitudes during both the late growing season and nongrowing season. These simulations highlight the global importance of biogeochemical processes during the nongrowing season in estimating carbon balance of ecosystems in northern high and temperate latitudes.     

Terrestrial carbon sinks in China and around the world and their contribution to carbon neutrality

Enhancing the terrestrial ecosystem carbon sink (referred to as terrestrial C sink) is an important way to slow down the continuous increase in atmospheric carbon dioxide (CO₂) concentration and to achieve carbon neutrality target. To better understand the characteristics of terrestrial C sinks and their contribution to carbon neutrality, this review summarizes major progress in terrestrial C budget researches during the past decades, clarifies spatial patterns and drivers of terrestrial C sources and sinks in China and around the world, and examines the role of terrestrial C sinks in achieving carbon neutrality target. According to recent studies, the global terrestrial C sink has been increasing from a source of (?0.2±0.9) Pg C yr^?1 (1 Pg=10¹⁵ g) in the 1960s to a sink of (1.9±1.1) Pg C yr^?1 in the 2010s. By synthesizing the published data, we estimate terrestrial C sink of 0.20–0.25 Pg C yr^?1 in China during the past decades, and predict it to be 0.15–0.52 Pg C yr^?1 by 2060. The terrestrial C sinks are mainly located in the mid- and high latitudes of the Northern Hemisphere, while tropical regions act as a weak C sink or source. The C balance differs much among ecosystem types: forest is the major C sink; shrubland, wetland and farmland soil act as C sinks; and whether the grassland functions as C sink or source remains unclear. Desert might be a C sink, but the magnitude and the associated mechanisms are still controversial. Elevated atmospheric CO₂ concentration, nitrogen deposition, climate change, and land cover change are the main drivers of terrestrial C sinks, while other factors such as fires and aerosols would also affect ecosystem C balance. The driving factors of terrestrial C sink differ among regions. Elevated CO₂ concentration and climate change are major drivers of the C sinks in North America and Europe, while afforestation and ecological restoration are additionally important forcing factors of terrestrial C sinks in China. For future studies, we recommend the necessity for intensive and long term ecosystem C monitoring over broad geographic scale to improve terrestrial biosphere models for accurately evaluating terrestrial C budget and its dynamics under various climate change and policy scenarios.

     

China's crop productivity and soil carbon storage as influenced by multifactor global change

Much concern has been raised about how multifactor global change has affected food security and carbon sequestration capacity in China. By using a process‐based ecosystem model, the Dynamic Land Ecosystem Model (DLEM), in conjunction with the newly developed driving information on multiple environmental factors (climate, atmospheric CO₂, tropospheric ozone, nitrogen deposition, and land cover/land use change), we quantified spatial and temporal patterns of net primary production (NPP) and soil organic carbon storage (SOC) across China's croplands during 1980–2005 and investigated the underlying mechanisms. Simulated results showed that both crop NPP and SOC increased from 1980 to 2005, and the highest annual NPP occurred in the Southeast (SE) region (0.32 Pg C yr^?1, 35.4% of the total NPP) whereas the largest annual SOC (2.29 Pg C yr^?1, 35.4% of the total SOC) was found in the Northeast (NE) region. Land management practices, particularly nitrogen fertilizer application, appear to be the most important factor in stimulating increase in NPP and SOC. However, tropospheric ozone pollution and climate change led to NPP reduction and SOC loss. Our results suggest that China's crop productivity and soil carbon storage could be enhanced through minimizing tropospheric ozone pollution and improving nitrogen fertilizer use efficiency.     

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.     

Interannual Variability in Terrestrial Net Primary Production: Exploration of Trends and Controls on Regional to Global Scales

Climate and biophysical regulation of terrestrial plant production and interannual responses to anomalous events were investigated using the NASA Ames model version of CASA (Carnegie–Ames–Stanford Approach) in a transient simulation mode. This ecosystem model has been calibrated for simulations driven by satellite vegetation index data from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) over the mid-1980s. Relatively large net source fluxes of carbon were estimated from terrestrial vegetation about 6 months to 1 year following El Niño events of 1983 and 1987, whereas the years 1984 and 1988 showed a drop in net primary production (NPP) of 1–2 Pg (10¹⁵ g) C from their respective previous years. Zonal discrimination of model results implies that the northern hemisphere low latitudes could account for almost the entire 2 Pg C decrease in global terrestrial NPP predicted from 1983 to 1984. Model estimates further suggest that from 1985 to 1988, the northern middle-latitude zone (between 30° and 60°N) was the principal region driving progressive increases in NPP, mainly by an expanded growing season moving toward the zonal latitude extremes. Comparative regional analysis of model controls on NPP reveals that although Normalized Difference Vegetation Index “greenness” can alone account for 30%–90% of the variation in NPP interannual anomalies, temperature or radiation loading can have a fairly significant 1-year lag effect on annual NPP at middle- to high-latitude zones, whereas rainfall amount and temperature drying effects may carry over with at least a 2-year lag time to influence NPP in semiarid tropical zones.     

土地利用/覆盖变化对陆地生态系统碳循环的影响

土地利用/覆盖变化是学术界最为关注的环境变化问题之一,它能够影响陆地生态系统的生物多样性、水、碳和养分循环、能量平衡,引起温室气体释放增加等其它环境问题。不同类型的土地利用/覆盖变化对生态系统碳循环的作用不同,由高生物量的森林转化为低生物量的草地、农田或城市后,大量的CO₂将释放到大气中。全球土地利用/覆盖变化具有很强的空间变异性,对生态系统碳循环的影响同样具有明显的空间差异:热带地区的土地利用/覆盖变化造成大量的碳释放,而中高纬度地区土地利用/覆盖变化则表现为碳汇。目前,土地利用/覆盖变化引起的生态系统碳循环变化主要是通过模型模拟来估算的。尽管土地利用/覆盖变化及其相关过程与生态系统碳循环的关系已经比较清楚,但是,由于土地利用/覆盖变化过程复杂且影响广泛,对于如何量化两者之间的关系还存在很多不确定性。目前的量化过程主要是利用经验数据来实现的,机理性不强,使得对土地利用/覆盖变化造成的陆地生态系统CO₂释放量的估测差异很大。除了进一步加强长期定位研究以获得土地利用/覆盖变化与生态系统碳循环过程的定量关系外,土地利用/覆盖变化模型与植被动态模型、生态系统过程模型的耦合也是今后模型发展的主要方向之一。采用合理的管理措施能够大量增加土地利用/覆盖变化过程中的碳储存量,降低碳释放量,因此在模型中耦合管理措施来研究土地利用/覆盖变化过程对生态系统碳循环的影响是未来几年的工作重点。     

Dissolved Organic Carbon in Terrestrial Ecosystems: Synthesis and a Model

The movement of dissolved organic carbon (DOC) through soils is an important process for the transport of carbon within ecosystems and the formation of soil organic matter. In some cases, DOC fluxes may also contribute to the carbon balance of terrestrial ecosystems; in most ecosystems, they are an important source of energy, carbon, and nutrient transfers from terrestrial to aquatic ecosystems. Despite their importance for terrestrial and aquatic biogeochemistry, these fluxes are rarely represented in conceptual or numerical models of terrestrial biogeochemistry. In part, this is due to the lack of a comprehensive understanding of the suite of processes that control DOC dynamics in soils. In this article, we synthesize information on the geochemical and biological factors that control DOC fluxes through soils. We focus on conceptual issues and quantitative evaluations of key process rates to present a general numerical model of DOC dynamics. We then test the sensitivity of the model to variation in the controlling parameters to highlight both the significance of DOC fluxes to terrestrial carbon processes and the key uncertainties that require additional experiments and data. Simulation model results indicate the importance of representing both root carbon inputs and soluble carbon fluxes to predict the quantity and distribution of soil carbon in soil layers. For a test case in a temperate forest, DOC contributed 25% of the total soil profile carbon, whereas roots provided the remainder. The analysis also shows that physical factors—most notably, sorption dynamics and hydrology—play the dominant role in regulating DOC losses from terrestrial ecosystems but that interactions between hydrology and microbial–DOC relationships are important in regulating the fluxes of DOC in the litter and surface soil horizons. The model also indicates that DOC fluxes to deeper soil layers can support a large fraction (up to 30%) of microbial activity below 40 cm. Received 14 January 2000; accepted 6 September 2000     

Interannual variability in global soil respiration, 1980–94

We used a climate‐driven regression model to develop spatially resolved estimates of soil‐CO₂ emissions from the terrestrial land surface for each month from January 1980 to December 1994, to evaluate the effects of interannual variations in climate on global soil‐to‐atmosphere CO₂ fluxes. The mean annual global soil‐CO₂ flux over this 15‐y period was estimated to be 80.4 (range 79.3–81.8) Pg C. Monthly variations in global soil‐CO₂ emissions followed closely the mean temperature cycle of the Northern Hemisphere. Globally, soil‐CO₂ emissions reached their minima in February and peaked in July and August. Tropical and subtropical evergreen broad‐leaved forests contributed more soil‐derived CO₂ to the atmosphere than did any other vegetation type (～30% of the total) and exhibited a biannual cycle in their emissions. Soil‐CO₂ emissions in other biomes exhibited a single annual cycle that paralleled the seasonal temperature cycle. Interannual variability in estimated global soil‐CO₂ production is substantially less than is variability in net carbon uptake by plants (i.e., net primary productivity). Thus, soils appear to buffer atmospheric CO₂ concentrations against far more dramatic seasonal and interannual differences in plant growth. Within seasonally dry biomes (savannas, bushlands and deserts), interannual variability in soil‐CO₂ emissions correlated significantly with interannual differences in precipitation. At the global scale, however, annual soil‐CO₂ fluxes correlated with mean annual temperature, with a slope of 3.3 Pg C y^?1 per °C. Although the distribution of precipitation influences seasonal and spatial patterns of soil‐CO₂ emissions, global warming is likely to stimulate CO₂ emissions from soils.