Systematic assessment of terrestrial biogeochemistry in coupled climate–carbon models

With representation of the global carbon cycle becoming increasingly complex in climate models, it is important to develop ways to quantitatively evaluate model performance against in situ and remote sensing observations. Here we present a systematic framework, the Carbon‐LAnd Model Intercomparison Project (C‐LAMP), for assessing terrestrial biogeochemistry models coupled to climate models using observations that span a wide range of temporal and spatial scales. As an example of the value of such comparisons, we used this framework to evaluate two biogeochemistry models that are integrated within the Community Climate System Model (CCSM) – Carnegie‐Ames‐Stanford Approach′ (CASA′) and carbon–nitrogen (CN). Both models underestimated the magnitude of net carbon uptake during the growing season in temperate and boreal forest ecosystems, based on comparison with atmospheric CO₂ measurements and eddy covariance measurements of net ecosystem exchange. Comparison with MODerate Resolution Imaging Spectroradiometer (MODIS) measurements show that this low bias in model fluxes was caused, at least in part, by 1–3 month delays in the timing of maximum leaf area. In the tropics, the models overestimated carbon storage in woody biomass based on comparison with datasets from the Amazon. Reducing this model bias will probably weaken the sensitivity of terrestrial carbon fluxes to both atmospheric CO₂ and climate. Global carbon sinks during the 1990s differed by a factor of two (2.4 Pg C yr^?1 for CASA′ vs. 1.2 Pg C yr^?1 for CN), with fluxes from both models compatible with the atmospheric budget given uncertainties in other terms. The models captured some of the timing of interannual global terrestrial carbon exchange during 1988–2004 based on comparison with atmospheric inversion results from TRANSCOM (r=0.66 for CASA′ and r=0.73 for CN). Adding (CASA′) or improving (CN) the representation of deforestation fires may further increase agreement with the atmospheric record. Information from C‐LAMP has enhanced model performance within CCSM and serves as a benchmark for future development. We propose that an open source, community‐wide platform for model‐data intercomparison is needed to speed model development and to strengthen ties between modeling and measurement communities. Important next steps include the design and analysis of land use change simulations (in both uncoupled and coupled modes), and the entrainment of additional ecological and earth system observations. Model results from C‐LAMP are publicly available on the Earth System Grid.     

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.     

Model–data synthesis in terrestrial carbon observation: methods, data requirements and data uncertainty specifications

Systematic, operational, long‐term observations of the terrestrial carbon cycle (including its interactions with water, energy and nutrient cycles and ecosystem dynamics) are important for the prediction and management of climate, water resources, food resources, biodiversity and desertification. To contribute to these goals, a terrestrial carbon observing system requires the synthesis of several kinds of observation into terrestrial biosphere models encompassing the coupled cycles of carbon, water, energy and nutrients. Relevant observations include atmospheric composition (concentrations of CO₂ and other gases); remote sensing; flux and process measurements from intensive study sites; in situ vegetation and soil monitoring; weather, climate and hydrological data; and contemporary and historical data on land use, land use change and disturbance (grazing, harvest, clearing, fire). A review of model–data synthesis tools for terrestrial carbon observation identifies ‘nonsequential’ and ‘sequential’ approaches as major categories, differing according to whether data are treated all at once or sequentially. The structure underlying both approaches is reviewed, highlighting several basic commonalities in formalism and data requirements. An essential commonality is that for all model–data synthesis problems, both nonsequential and sequential, data uncertainties are as important as data values themselves and have a comparable role in determining the outcome. Given the importance of data uncertainties, there is an urgent need for soundly based uncertainty characterizations for the main kinds of data used in terrestrial carbon observation. The first requirement is a specification of the main properties of the error covariance matrix. As a step towards this goal, semi‐quantitative estimates are made of the main properties of the error covariance matrix for four kinds of data essential for terrestrial carbon observation: remote sensing of land surface properties, atmospheric composition measurements, direct flux measurements, and measurements of carbon stores.     

Enhanced regional terrestrial carbon uptake over Korea revealed by atmospheric CO2 measurements from 1999 to 2017

Understanding changes in terrestrial carbon balance is important to improve our knowledge of the regional carbon cycle and climate change. However, evaluating regional changes in the terrestrial carbon balance is challenging due to the lack of surface flux measurements. This study reveals that the terrestrial carbon uptake over the Republic of Korea has been enhanced from 1999 to 2017 by analyzing long‐term atmospheric CO₂ concentration measurements at the Anmyeondo Station (36.53°N, 126.32°E) located in the western coast. The influence of terrestrial carbon flux on atmospheric CO₂ concentrations (ΔCO₂) is estimated from the difference of CO₂ concentrations that were influenced by the land sector (through easterly winds) and the Yellow Sea sector (through westerly winds). We find a significant trend in ΔCO₂ of ?4.75 ppm per decade (p < .05) during the vegetation growing season (May through October), suggesting that the regional terrestrial carbon uptake has increased relative to the surrounding ocean areas. Combined analysis with satellite measured normalized difference vegetation index and gross primary production shows that the enhanced carbon uptake is associated with significant nationwide increases in vegetation and its production. Process‐based terrestrial model and inverse model simulations estimate that regional terrestrial carbon uptake increases by up to 18.9 and 8.0 Tg C for the study period, accounting for 13.4% and 5.7% of the average annual domestic carbon emissions, respectively. Atmospheric chemical transport model simulations indicate that the enhanced terrestrial carbon sink is the primary reason for the observed ΔCO₂ trend rather than anthropogenic emissions and atmospheric circulation changes. Our results highlight the fact that atmospheric CO₂ measurements could open up the possibility of detecting regional changes in the terrestrial carbon cycle even where anthropogenic emissions are not negligible.     

Using model‐data fusion to interpret past trends,and quantify uncertainties in future projections,of terrestrial ecosystem carbon cycling

Uncertainties in model projections of carbon cycling in terrestrial ecosystems stem from inaccurate parameterization of incorporated processes (endogenous uncertainties) and processes or drivers that are not accounted for by the model (exogenous uncertainties). Here, we assess endogenous and exogenous uncertainties using a model‐data fusion framework benchmarked with an artificial neural network (ANN). We used 18 years of eddy‐covariance carbon flux data from the Harvard forest, where ecosystem carbon uptake has doubled over the measurement period, along with 15 ancillary ecological data sets relative to the carbon cycle. We test the ability of combinations of diverse data to constrain projections of a process‐based carbon cycle model, both against the measured decadal trend and under future long‐term climate change. The use of high‐frequency eddy‐covariance data alone is shown to be insufficient to constrain model projections at the annual or longer time step. Future projections of carbon cycling under climate change in particular are shown to be highly dependent on the data used to constrain the model. Endogenous uncertainties in long‐term model projections of future carbon stocks and fluxes were greatly reduced by the use of aggregated flux budgets in conjunction with ancillary data sets. The data‐informed model, however, poorly reproduced interannual variability in net ecosystem carbon exchange and biomass increments and did not reproduce the long‐term trend. Furthermore, we use the model‐data fusion framework, and the ANN, to show that the long‐term doubling of the rate of carbon uptake at Harvard forest cannot be explained by meteorological drivers, and is driven by changes during the growing season. By integrating all available data with the model‐data fusion framework, we show that the observed trend can only be reproduced with temporal changes in model parameters. Together, the results show that exogenous uncertainty dominates uncertainty in future projections from a data‐informed process‐based model.     

Organic carbon cycling in Taylor Valley, Antarctica: quantifying soil reservoirs and soil respiration

Organic carbon reservoirs and respiration rates in soils have been calculated for most major biomes on Earth revealing patterns related to temperature, precipitation, and location. Yet data from one of the Earth's coldest, driest, and most southerly soil ecosystems, that of the McMurdo Dry Valleys of Antarctica, are currently not a part of this global database. In this paper, we present the first regional calculations of the soil organic carbon reservoirs in a dry valley ecosystem (Taylor Valley) and report measurements of CO₂ efflux from Antarctic soils. Our analyses indicate that, despite the absence of visible accumulations of organic matter in most of Taylor Valley's arid soils, this soil environment contained a significant percentage (up to 72%) of the seasonally unfrozen organic carbon reservoir in the terrestrial ecosystem. Field measurements of soil CO₂‐efflux in Taylor Valley soils were used to evaluate biotic respiration and averaged 0.10 ± 0.08 μmol CO₂ m^?2 s^?1. Laboratory soil microcosms suggested that this respiration rate was sensitive to increases in temperature, moisture, and carbon addition. Finally, a steady‐state calculation of the mean residence time for organic carbon in Taylor Valley soils was 23 years. Because this value contradicts all that is currently known about carbon cycling rates in the dry valleys, we suggest that the dry valley soil carbon dynamics is not steady state. Instead, we suggest that the dynamic is complex, with at least two (short‐ and long‐term) organic carbon reservoirs. We also suggest that organic carbon in the dry valley soil environment may be more important, and play a more active role in long‐term ecosystem processes, than previously believed.     

Effects of 21st‐century climate,land use,and disturbances on ecosystem carbon balance in California

Terrestrial ecosystems are an important sink for atmospheric carbon dioxide (CO₂), sequestering ~30% of annual anthropogenic emissions and slowing the rise of atmospheric CO₂. However, the future direction and magnitude of the land sink is highly uncertain. We examined how historical and projected changes in climate, land use, and ecosystem disturbances affect the carbon balance of terrestrial ecosystems in California over the period 2001–2100. We modeled 32 unique scenarios, spanning 4 land use and 2 radiative forcing scenarios as simulated by four global climate models. Between 2001 and 2015, carbon storage in California's terrestrial ecosystems declined by ?188.4 Tg C, with a mean annual flux ranging from a source of ?89.8 Tg C/year to a sink of 60.1 Tg C/year. The large variability in the magnitude of the state's carbon source/sink was primarily attributable to interannual variability in weather and climate, which affected the rate of carbon uptake in vegetation and the rate of ecosystem respiration. Under nearly all future scenarios, carbon storage in terrestrial ecosystems was projected to decline, with an average loss of ?9.4% (?432.3 Tg C) by the year 2100 from current stocks. However, uncertainty in the magnitude of carbon loss was high, with individual scenario projections ranging from ?916.2 to 121.2 Tg C and was largely driven by differences in future climate conditions projected by climate models. Moving from a high to a low radiative forcing scenario reduced net ecosystem carbon loss by 21% and when combined with reductions in land‐use change (i.e., moving from a high to a low land‐use scenario), net carbon losses were reduced by 55% on average. However, reconciling large uncertainties associated with the effect of increasing atmospheric CO₂ is needed to better constrain models used to establish baseline conditions from which ecosystem‐based climate mitigation strategies can be evaluated.     

The production of phytolith‐occluded carbon in China's forests: implications to biogeochemical carbon sequestration

The persistent terrestrial carbon sink regulates long‐term climate change, but its size, location, and mechanisms remain uncertain. One of the most promising terrestrial biogeochemical carbon sequestration mechanisms is the occlusion of carbon within phytoliths, the silicified features that deposit within plant tissues. Using phytolith content–biogenic silica content transfer function obtained from our investigation, in combination with published silica content and aboveground net primary productivity (ANPP) data of leaf litter and herb layer in China's forests, we estimated the production of phytolith‐occluded carbon (PhytOC) in China's forests. The present annual phytolith carbon sink in China's forests is 1.7 ± 0.4 Tg CO₂ yr ^{? 1}, 30% of which is contributed by bamboo because the production flux of PhytOC through tree leaf litter for bamboo is 3–80 times higher than that of other forest types. As a result of national and international bamboo afforestation and reforestation, the potential of phytolith carbon sink for China's forests and world's bamboo can reach 6.8 ± 1.5 and 27.0 ± 6.1 Tg CO₂ yr^?1, respectively. Forest management practices such as bamboo afforestation and reforestation may significantly enhance the long‐term terrestrial carbon sink and contribute to mitigation of global climate warming.     

Growth enhancement due to global atmospheric change as predicted by terrestrial ecosystem models: consistent with US forest inventory data

Small reported growth enhancement factors based on analyses of forest inventory data from the eastern USA ( Caspersen et al. 2000 , Science, 290, 1148–1151) have been interpreted as evidence against CO₂ fertilization in natural forests. We show to the contrary that growth enhancement in response to rising CO₂, as found in ecosystems with experimental CO₂ enrichment and implemented in terrestrial ecosystem models, is consistent with the data that have been presented within their uncertainties. Comparing forest inventory data with results of an empirical model of age‐dependent biomass accumulation, we find that growth enhancement of plausible magnitude could not be detected in these data, even if it were present. Although forest regrowth due to land‐use change is recognized as an important cause of carbon uptake by eastern US forests, forest inventory data do not provide a basis for eliminating environmentally induced growth enhancement as a substantial contribution to the global terrestrial carbon sink.     

Abrupt changes in Great Britain vegetation carbon projected under climate change

Past abrupt ‘regime shifts’ have been observed in a range of ecosystems due to various forcing factors. Large‐scale abrupt shifts are projected for some terrestrial ecosystems under climate change, particularly in tropical and high‐latitude regions. However, there is very little high‐resolution modelling of smaller‐scale future projected abrupt shifts in ecosystems, and relatively less focus on the potential for abrupt shifts in temperate terrestrial ecosystems. Here, we show that numerous climate‐driven abrupt shifts in vegetation carbon are projected in a high‐resolution model of Great Britain's land surface driven by two different climate change scenarios. In each scenario, the effects of climate and CO₂ combined are isolated from the effects of climate change alone. We use a new algorithm to detect and classify abrupt shifts in model time series, assessing the sign and strength of the non‐linear responses. The abrupt ecosystem changes projected are non‐linear responses to climate change, not simply driven by abrupt shifts in climate. Depending on the scenario, 374–1,144 grid cells of 1.5 km × 1.5 km each, comprising 0.5%–1.5% of Great Britain's land area show abrupt shifts in vegetation carbon. We find that abrupt ecosystem shifts associated with increases (rather than decreases) in vegetation carbon, show the greatest potential for early warning signals (rising autocorrelation and variance beforehand). In one scenario, 89% of abrupt increases in vegetation carbon show increasing autocorrelation and variance beforehand. Across the scenarios, 81% of abrupt increases in vegetation carbon have increasing autocorrelation and 74% increasing variance beforehand, whereas for decreases in vegetation carbon these figures are 56% and 47% respectively. Our results should not be taken as specific spatial or temporal predictions of abrupt ecosystem change. However, they serve to illustrate that numerous abrupt shifts in temperate terrestrial ecosystems could occur in a changing climate, with some early warning signals detectable beforehand.     

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.     

Towards physiologically meaningful water‐use efficiency estimates from eddy covariance data

Intrinsic water‐use efficiency (iWUE) characterizes the physiological control on the simultaneous exchange of water and carbon dioxide in terrestrial ecosystems. Knowledge of iWUE is commonly gained from leaf‐level gas exchange measurements, which are inevitably restricted in their spatial and temporal coverage. Flux measurements based on the eddy covariance (EC) technique can overcome these limitations, as they provide continuous and long‐term records of carbon and water fluxes at the ecosystem scale. However, vegetation gas exchange parameters derived from EC data are subject to scale‐dependent and method‐specific uncertainties that compromise their ecophysiological interpretation as well as their comparability among ecosystems and across spatial scales. Here, we use estimates of canopy conductance and gross primary productivity (GPP) derived from EC data to calculate a measure of iWUE (G₁, “stomatal slope”) at the ecosystem level at six sites comprising tropical, Mediterranean, temperate, and boreal forests. We assess the following six mechanisms potentially causing discrepancies between leaf and ecosystem‐level estimates of G₁: (i) non‐transpirational water fluxes; (ii) aerodynamic conductance; (iii) meteorological deviations between measurement height and canopy surface; (iv) energy balance non‐closure; (v) uncertainties in net ecosystem exchange partitioning; and (vi) physiological within‐canopy gradients. Our results demonstrate that an unclosed energy balance caused the largest uncertainties, in particular if it was associated with erroneous latent heat flux estimates. The effect of aerodynamic conductance on G₁ was sufficiently captured with a simple representation. G₁ was found to be less sensitive to meteorological deviations between canopy surface and measurement height and, given that data are appropriately filtered, to non‐transpirational water fluxes. Uncertainties in the derived GPP and physiological within‐canopy gradients and their implications for parameter estimates at leaf and ecosystem level are discussed. Our results highlight the importance of adequately considering the sources of uncertainty outlined here when EC‐derived water‐use efficiency is interpreted in an ecophysiological context.     

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.     

Why are estimates of the terrestrial carbon balance so different?

The carbon balance of the world's terrestrial ecosystems is uncertain. Both top‐down (atmospheric) and bottom‐up (forest inventory and land‐use change) approaches have been used to calculate the sign and magnitude of a net terrestrial flux. Different methods often include different processes, however, and comparisons can be misleading. Differences are not necessarily the result of uncertainties or errors, but often result from incomplete accounting inherent in some of the methods. Recent estimates are reviewed here. Overall, a northern mid‐latitude carbon sink of approximately 2 Pg C yr^?1 appears robust, although the mechanisms responsible are uncertain. Several lines of evidence point to environmentally enhanced rates of carbon accumulation. Other lines suggest that recovery from past disturbances is largely responsible for the sink. The tropics appear to be a small net source of carbon or nearly neutral, and the same uncertainties of mechanism exist. In addition, studies in the tropics do not permit an unequivocal choice between two alternatives: large emissions of carbon from deforestation offset by large sinks in undisturbed forests, or moderate emissions from land‐use change with essentially no change in the carbon balance in undisturbed forests. Resolution of these uncertainties is most likely to result from spatially detailed historical reconstructions of land‐use change and disturbance in selected northern mid‐latitude regions where such data are available, and from systematic monitoring of changes in the area of tropical forests with satellite data of high spatial resolution collected over the last decades and into the future.     

基于模型数据融合的长白山阔叶红松林碳循环模拟

 充分、有效地利用各种陆地生态系统碳观测数据改善陆地生态系统模型, 是当前我国陆地生态系统碳循环研究领域亟待解决的重要问题之一。该研究以2003~2005年长白山阔叶红松林的6组生物计量观测数据和涡度相关技术测定的碳通量数据为基础, 利用马尔可夫链-蒙特卡罗方法对陆地生态系统模型的关键参数(即碳滞留时间)进行了反演, 进而预测了长白山阔叶红松林生态系统碳库、碳通量及其不确定性。反演结果表明, 长白山阔叶红松林叶凋落物和微生物碳的平均滞留时间最短, 为2~6个月; 其次是叶和细根生物量碳, 二者的平均滞留时间为1~2 a; 慢性土壤有机碳的平均滞留时间为8~16 a; 碳在木质生物量和惰性土壤有机质库中的滞留时间最长, 平均滞留时间分别为77~109 a和409~1 879 a。模拟结果显示, 碳库和累积碳通量模拟值的不确定性将随着模拟时间的延长而增大。当气温升高10%和20%时, 长白山阔叶红松林总初级生产力年总量将分别增加6.5%和9.9%, 净生态系统生产力(NEP)年总量的变化取决于土壤温度的变化。若土壤温度保持不变, NEP年总量将分别增加11.4%~21.9%和17.6%~33.1%; 若土壤温度也相应升高10%和20%, NEP年总量的增幅反而下降甚至低于原来的水平。假设气候和植被保持在2003~2005年的状态, 2020年长白山阔叶红松林NEP年总量为(163±12) g C·m^–2·a^–1, 土壤呼吸年总量为(721±14) g C·m^–2·a^–1。马尔可夫链-蒙特卡罗方法是反演模型参数、优化模拟结果和评估模拟结果不确定性的有效方法, 但今后仍需在惰性土壤碳滞留时间的估计、驱动数据和模型结构的不确定性分析、模型数据融合方法方面进行深入研究, 以进一步提高碳循环模拟的准确性。     

The impacts of rising CO2 concentrations on Australian terrestrial species and ecosystems

The increasing atmospheric concentration of carbon dioxide ([CO₂]) contributes to global warming and the accompanying shifts in climate. However, [CO₂] itself has the potential to impact on Australia's terrestrial biodiversity, due to its importance in the photosynthetic process, which underlies all terrestrial food webs. Here, we review our knowledge regarding the impacts of elevated [CO₂] on native terrestrial species and ecosystems, and suggest key areas in which we have little information on this topic. Experimental information exists for 70 (or less than 0.05%) of Australia's native terrestrial plant and animal species. Of these, 68 are vascular plants. The growth of Australian woody species is more reliably increased by elevated [CO₂] than it is in grasses. At the species level, the most overwhelming responses to increased [CO₂] are a reduction in plant nitrogen concentration and an increase in the production of secondary metabolites. This is of particular concern for Australia's unique herbivorous and granivorous marsupials, for which no information is available. While many plant species also displayed increased growth rates at higher [CO₂], this was far from universal, indicating that changes in community structure and function are likely, leading to alterations of habitat quality. Future research should be directed to key knowledge gaps including the relationship between [CO₂], fire frequency and fire tolerance and the impacts of increasing [CO₂] for Australia's iconic browsing mammals. We also know virtually nothing of the impacts of the increasing [CO₂] on Australia's unique shrublands and semi‐arid/arid rangelands. In conclusion, there is sufficient information available to be certain that the increasing [CO₂] will affect Australia's native biodiversity. However, the information required to formulate predictions concerning the long‐term future of almost all organisms is far in excess of that currently available.     

Influences of error distributions of net ecosystem exchange on parameter estimation of a process-based terrestrial model: A case of broad-leaved Korean pine mixed forest in Changbaishan, China

Model predictions can be improved by parameter estimation from measurements. It was assumed that measurement errors of net ecosystem exchange (NEE) of CO₂ follow a normal distribution. However, recent studies have shown that errors in eddy covariance measurements closely follow a double exponential distribution. In this paper, we compared effects of different distributions of measurement errors of NEE data on parameter estimation. NEE measurements in the Changbaishan forest were assimilated into a process-based terrestrial ecosystem model. We used the Markov chain Monte Carlo method to derive probability density functions of estimated parameters. Our results showed that modeled annual total gross primary production (GPP) and ecosystem respiration (Re) using the normal error distribution were higher than those using the double exponential distribution by 61–86 gC m^?2 a^?1 and 107–116 gC m^?2 a^?1, respectively. As a result, modeled annual sum of NEE using the normal error distribution was lower by 29–47 gC m^?2 a^?1 than that using the double exponential error distribution. Especially, modeled daily NEE based on the normal distribution underestimated the strong carbon sink in the Changbaishan forest in the growing season. We concluded that types of measurement error distributions and corresponding cost functions can substantially influence the estimation of parameters and carbon fluxes.     

The production of phytoliths in China's grasslands: implications to the biogeochemical sequestration of atmospheric CO2

Among the most promising approaches of long‐term atmospheric CO₂ sequestration is terrestrial biogeochemical carbon sequestration. One of the most promising terrestrial biogeochemical carbon sequestration mechanisms is the occlusion of carbon within phytoliths, the silicified features that deposit within plant tissues. Using phytolith content‐biogenic silica content transfer function obtained from our investigation, in combination with published silica content and above‐ground net primary productivity (ANPP) data of China's grasslands, we estimated the production of phytoliths and phytolith‐occluded carbon (PhytOC) in grasslands. The results show that the average above‐ground phytolith production rates of China's grasslands (10.9 10⁶ t yr^?1 or 1.45% of world grasslands) are much lower than those of other grasslands (e.g. North American nonwoody grasslands) mainly because of much lower ANPP. Assuming a median content of PhytOC of 1.5%, the average above‐ground PhytOC production rates of China's grasslands and world grasslands are estimated to be 0.6 10⁶ t CO₂ yr^?1 and 41.4 10⁶ t CO₂ yr^?1, respectively. The management of grasslands to maximize ANPP has the potential to result in considerable quantities of phytoliths and securely bio‐sequestered carbon.     

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.