Carbon Fluxes In Terrestrial Ecosystems Research Articles

Invert global and China's terrestrial carbon fluxes over 2019–2021 based on assimilating richer atmospheric CO2 observations

With China's commitment to reach carbon peak by 2030 and achieve carbon neutrality by 2060, it is particularly important to obtain terrestrial ecosystem carbon fluxes with low uncertainty both globally and in China. The use of more observation data may help reduce the uncertainty of inverting carbon fluxes. This study uses the observation data from global stations, background stations and provincial stations in China, as well as the OCO-2 satellite, and uses the China Carbon Monitoring, Verification and Supporting System for Global (CCMVS-G) to estimate the carbon fluxes of global and Chinese terrestrial ecosystems from 2019 to 2021. The results revealed that the global terrestrial ecosystem carbon sink was approximately −3.40 Pg C/yr from 2019 to 2021. The carbon sinks in the Northern Hemisphere are large, especially in Asia, North America, and Europe. From 2019 to 2021, the carbon sink of China's terrestrial ecosystem was approximately −0.44 Pg C/yr. Carbon sinks exhibit significant seasonal and interannual variations in China. After assimilating the observation data, the uncertainty of the posterior flux is smaller than that of the prior flux, a more reasonable distribution of carbon sources and sinks can be obtained, and more accurate boundary conditions can be provided for the China Carbon Monitoring, Verification and Supporting System for Regional (CCMVS-R). In the future, it is important to establish a well-designed CO2 ground-based observation network.

Acid rain reduced soil carbon emissions and increased the temperature sensitivity of soil respiration: A comprehensive meta-analysis

Soil respiration the second-largest carbon flux in terrestrial ecosystems, has been extensively studied across a wide range of biomes. Surprisingly, no consensus exist on how acid rain (AR) impacts the spatiotemporal pattern of soil respiration. Therefore, we conducted a meta-analysis using 318 soil respiration and 263 soil respiration temperature sensitivity (Q10) data points obtained from 48 studies to assess the impact of AR on soil respiration components and their Q10. The results showed that AR reduced soil total respiration (Rt) and soil autotrophic respiration (Ra) by 7.41 % and 20.75 %, respectively. As the H+ input increased, the response rates of Ra to AR (RR-Ra) and soil heterotrophic respiration (Rh) to AR (RR-Rh) decreased and increased, respectively. With increased AR duration, the RR-Ra increased, whereas the RR-Rh did not change. AR increased the Q10 of Rt (Rt-Q10) and Rh (Rh-Q10) by 1.92 % and 9.47 %, respectively, and decreased the Q10 of Ra (Ra-Q10) by 2.77 %. Increased mean annual temperature, mean annual precipitation, and initial soil organic carbon increased the response rate of Ra-Q10 to AR (RR-Ra-Q10) and decreased the response rate of Rh-Q10 to AR (RR-Rh-Q10). However, as the AR frequency and initial soil pH increased, both RR-Ra-Q10 and RR-Rh-Q10 also increased. In summary, AR decreased Rt but increased Q10, likely due to soil acidification (soil pH decreased by 7.84 %), reducing plant root biomass (decreased by 5.67 %) and soil microbial biomass (decreased by 5.67 %), changing microbial communities (increased fungi to bacteria ratio of 15.91 %), and regulated by climate, vegetation, soil and AR regimes. To the best of our knowledge, this is the first study to reveal the large-scale, varied response patterns of soil respiration components and their Q10 to AR. It highlights the importance of applying the reductionism theory in soil respiration research to enhance our understanding of soil carbon cycling processes with in the context of global climate change.

The extreme wet and large precipitation size increase carbon uptake in Eurasian meadow steppes: Evidence from natural and manipulated precipitation experiments

The distribution of seasonal precipitation would profoundly affect the dynamics of carbon fluxes in terrestrial ecosystems. However, little is known about the impacts of extreme precipitation and size events on ecosystem carbon cycle when compared to the effects of average precipitation amount. The study involved an analysis of carbon fluxes and water exchange using the eddy covariance and chamber based techniques during the growing seasons of 2015–2017 in Bayan, Mongolia and 2019–2021 in Hulunbuir, Inner Mongolia, respectively. The components of carbon fluxes and water exchange at each site were normalized to evaluate of relative response among carbon fluxes and water exchange. The investigation delved into the relationship between carbon fluxes and extreme precipitation over five gradients (control, dry spring, dry summer, wet spring and wet summer) in Hulunbuir meadow steppe and distinct four precipitation sizes (0.1–2, 2–5, 5–10, and 10–25 mm d−1) in Bayan meadow steppe. The wet spring and summer showed the greatest ecosystem respiration (ER) relative response values, 76.2% and 73.5%, respectively, while the dry spring (−16.7%) and dry summer (14.2%) showed the lowest values. Gross primary production (GPP) relative response improved with wet precipitation gradients, and declined with dry precipitation gradients in Hulunbuir meadow steppe. The least value in net ecosystem CO2 exchange (NEE) was found at 10–25 mm d−1 precipitation size in Bayan meadow steppe. Similarly, the ER and GPP increased with size of precipitation events. The structural equation models (SEM) satisfactorily fitted the data (χ2 = 43.03, d.f. = 11, p = 0.215), with interactive linkages among soil microclimate, water exchange and carbon fluxes components regulating NEE. Overall, this study highlighted the importance of extreme precipitation and event size in influencing ecosystem carbon exchange, which is decisive to further understand the carbon cycle in meadow steppes.

Understanding aerosol–climate–ecosystem interactions and the implications for terrestrial carbon sink using the Community Earth System Model

Anthropogenic aerosols exert significant effects on the terrestrial ecosystem carbon cycle by causing climate change and altering surface hydrological conditions through radiation and cloud interaction, but such aerosol–climate–ecosystem interactions are difficult to quantify using currently available observations. Here, we used the Community Earth System Model (CESM, version 2.1.3) to quantify the effects of anthropogenic aerosols on terrestrial ecosystem carbon fluxes during the period from 1980 to 2014. The results found that the response of temperature and radiation to anthropogenic aerosols in different regions shows considerable variability in the CESM. Anthropogenic aerosols caused a 0.26 Pg C (0.43%) reduction in cumulative net biome production (NBP) during the period 1980-2014. In Southeast China (SEC) and East United States (EUS), anthropogenic aerosols caused a net reduction in NBP of 0.27 and 0.09 Pg C, respectively. In India (IND) and Europe (EUR), anthropogenic aerosols caused an increase of NBP by 0.07 and 0.14 Pg C, respectively. In addition, the decrease of the carbon sink was mainly dominated by changes in TER and others (40.6%), and the increase of the carbon sink was mainly dominated by changes in gross primary production (GPP) (38.9%). We also found that temperature is the dominant climate variable controlling the carbon cycle with a relative contribution of about 38%. Finally, the carbon flux response at the global scale is significantly lower than at the regional scale, which in turn highlights the importance of the assessment of the regional carbon cycle.

2000-2020年华北地区植被固碳能力时空变化特征及其气象影响分析

PDF HTML阅读 XML下载 导出引用 引用提醒 2000-2020年华北地区植被固碳能力时空变化特征及其气象影响分析 DOI: 10.5846/stxb202110072771 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 以清洁能源淡化海水促进生态修复和应对气候变化的可行路径及综合效益研究(SGGEIG00JYJS2000053);国家重点研发计划项目(2019YFC1510204);国家气象中心预报员专项(Y202116) Spatial and temporal patterns of carbon sequestration and their responses to climatic factors in North China from 2000 to 2020 Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:净生态系统生产力(NEP)是估算植被生态系统碳源／汇的重要指标,开展区域NEP时空变化特征分析,对科学评估植被生态系统固碳能力及其气候变化应对措施具有重要意义。研究基于土壤呼吸模型和TEC模型,利用2000-2020年气象数据和遥感数据,采用线性趋势分析、Hurst指数和相关分析等统计方法,对华北地区固碳能力时空变化特征、影响因素及其未来变化趋势进行分析。结果表明:2000-2020年,华北地区年均NEP为228.8 gC/m2,在空间分布上呈现从西北向东南逐步递增的趋势,总体上表现为净固碳。从变化趋势来看,华北地区生态系统的固碳能力总体呈增加趋势,分布面积占比达到88.8%,达到显著增加趋势的面积比例为54.5%(P<0.05),其中河北北部、北京北部、山西西北部、山东西部等地NEP每年每平方米增加9.0 gC以上。华北大部地区NEP年际波动较小,有79.6%的区域多处于较高稳定、高稳定的等级。从变化趋势来看,华北地区有84.9%区域NEP具有强持续性,且NEP未来仍将持续增加的区域面积占比达到51.4%。华北地区NEP的空间分布和年际变化主要受降水的影响,达到显著相关的区域面积占总面积的44.7%,但与气温、日照呈弱正相关,而且不同区域相关性差异明显。其中降水影响空间格局差异极为明显,华北中北部NEP与降水呈显著正相关,南部呈负相关。 Abstract:Net ecosystem productivity (NEP) is an important index for estimating carbon source/sink of regional vegetation system. Analyzing the distribution characteristics and changing trend of net ecosystem productivity spatially is of great significance to scientifically assess carbon sequestration capacity of ecosystems and formulate policies and measures to cope with climate change. Using the soil respiration model and terrestrial ecosystem carbon flux model (TEC model), combined with MODIS and meteorological data, this paper estimated the NEP in North China from 2000 to 2020. And its spatial distribution characteristics and changing trend were analyzed, using methods of linear regression, the Hurst index, coefficient of variation and other methods. Results showed that: from 2000 to 2020, the annual average NEP in North China was about 228.8 gC/m2. In spatial distribution, the NEP showed an increasing trend from northwest to southeast, representing carbon sink as a whole. From spatial distribution of change trend, the carbon sequestration capacity of North China ecosystems was increasing, especially in the north of Hebei, the north of Beijing, the northwestern Shanxi, the western Shandong with increase of NEP over 9.0 gC/m2. The area of increasing trend with the NEP accounted for 88.8% of the research area, of which 54.5% showed a significantly increasing trend (P<0.05). As for the coefficient of variation (CV), the NEP status in North China presented slight fluctuations with 79.6%% of the area in higher stability and the highest stability. From the NEP change trend analysis, 84.9% of the area in North China was persistent in the future. The NEP in 51.4% of the regions will continue to increase in the future. The spatial distribution and interannual variation of the NEP values were mainly influenced by the values of precipitation, of which 44.7% showed a positive correlation with precipitation. The changes of NEP were slightly positively associated with temperature and sunshine. The responses of NEP in North China to the meteorological factors were diverse in spatial difference of the North China, especially differences by the influence of precipitation. There is a significantly positive correlation between NEP and precipitation in the northern part of North China, and a negative correlation in the south. 参考文献 相似文献 引证文献

A high spatial resolution land surface phenology dataset for AmeriFlux and NEON sites

Vegetation phenology is a key control on water, energy, and carbon fluxes in terrestrial ecosystems. Because vegetation canopies are heterogeneous, spatially explicit information related to seasonality in vegetation activity provides valuable information for studies that use eddy covariance measurements to study ecosystem function and land-atmosphere interactions. Here we present a land surface phenology (LSP) dataset derived at 3 m spatial resolution from PlanetScope imagery across a range of plant functional types and climates in North America. The dataset provides spatially explicit information related to the timing of phenophase changes such as the start, peak, and end of vegetation activity, along with vegetation index metrics and associated quality assurance flags for the growing seasons of 2017–2021 for 10 × 10 km windows centred over 104 eddy covariance towers at AmeriFlux and National Ecological Observatory Network (NEON) sites. These LSP data can be used to analyse processes controlling the seasonality of ecosystem-scale carbon, water, and energy fluxes, to evaluate predictions from land surface models, and to assess satellite-based LSP products.

Soil enzymes in response to climate warming: Mechanisms and feedbacks

Abstract Soil enzymes are central to ecosystem processes because they mediate numerous reactions that are essential in biogeochemical cycles. However, how soil enzyme activities will respond to global warming is uncertain. We reviewed the literature on mechanisms linking temperature effects on soil enzymes and microbial communities, and outlined a conceptual overview on how these changes may influence soil carbon fluxes in terrestrial ecosystems. At the enzyme scale, although temperature can have a positive effect on enzymatic catalytic power in the short term (i.e. via the instantaneous response of activity), this effect can be countered over time by enzyme inactivation and reduced substrate affinity. At the microbial scale, short‐term warming can increase enzymatic catalytic power via accelerated synthesis and microbial turnover, but shifts in microbial community composition and growth efficiency may mediate the effect of warming in the long term. Although increasing enzyme activities may accelerate labile carbon decomposition over months to years, our literature review highlights that this initial stage can be followed by the following phases: (a) a reduction in soil carbon loss, due to changing carbon use efficiency among communities or substrate depletion, which together can decrease microbial biomass and enzyme activity and (b) an acceleration of soil carbon loss, due to shifts in microbial community structure and greater allocation to oxidative enzymes for recalcitrant carbon degradation. Studies that bridge scales in time and space are required to assess whether there will be an attenuation or acceleration of soil carbon loss through changes in enzyme activities in the very long term. We conclude that soil enzymes determine the sensitivity of soil carbon to warming, but that the microbial community and enzymatic traits that mediate this effect change over time. Improving representation of enzymes in soil carbon models requires long‐term studies that characterize the response of wide‐ranging hydrolytic and oxidative enzymatic traits—catalytic power, kinetics, inactivation—and the microbial community responses that govern enzyme synthesis. Read the free Plain Language Summary for this article on the Journal blog.

The Divergent Estimates of Diffuse Radiation Effects on Gross Primary Production of Forest Ecosystems Using Light‐Use Efficiency Models

AbstractDiffuse radiation can promote the vegetation photosynthesis. Radiation use efficiency (RUE = GPP/PAR) simulated by Terrestrial Ecosystem Carbon Flux GPP Model (TEC), Vegetation Photosynthesis Model (VPM), Eddy Covariance Light Use Efficiency Model (EC‐LUE), and Diffuse Fraction‐Based Two‐Leaf Terrestrial Ecosystem Carbon Flux Model (DTEC) models were against the measured radiation‐use efficiency (RUE) from FLUXNET under different bins of diffuse photosynthetically active radiation fraction (FDIFFPAR) in this study. Our results showed that the observed RUE increased linearly with FDIFFPAR. The differences of RUE between the first bin and other bin (RUEbin) from two big‐leaf models were underestimated when the FDIFFPAR is higher than 0.5 except in evergreen broadleaf forests and RUEbin from the DTEC model was overestimated when the FDIFFPAR is higher than 0.7. The role of temperature and vapor pressure deficit in the diffuse radiation effects on vegetation photosynthesis was underestimated in EC‐LUE, TEC, VPM. Although many studies applied LUE models to assess the effects of diffuse radiation on vegetation photosynthesis, our results suggested that these models were needed to be improved.

Effect of atmospheric nitrogen deposition and its components on carbon flux in terrestrial ecosystems in China

Long-term atmospheric nitrogen (N) deposition increases bioavailable N in terrestrial ecosystems, thereby influencing ecosystem productivity. However, how N deposition and its components (i.e., NO3−–N and NH4+–N) influence the spatial pattern of productivity in terrestrial ecosystems in China remains unknown. Here, we utilize published data including carbon (C) fluxes from eddy flux tower (gross ecosystem productivity, ecosystem respiration, and net ecosystem productivity) and the corresponding climate and N deposition data for 60 typical ecosystems in China. The objective was to investigate the effect of N deposition on ecosystem productivity and explore the variations of N use efficiency (NUE). Our results reveal that atmospheric total N deposition is significantly correlated with C fluxes of terrestrial ecosystems in China. Ecosystems respond variably to different components of N deposition. In detail, forest ecosystem marginally correlated with NO3−–N and wet deposition, while grassland ecosystem significantly correlated with NH4+–N and dry deposition. NUE of productivity induced by N deposition in Chinese terrestrial ecosystems was 53.95 ± 40.30 g C g−1 N, and it was influenced by precipitation and aridity index. This study quantifies the contribution of total N deposition and its associated components to productivity in terrestrial ecosystems in China, offering vital information for regional C and N management.

Including leaf trait information helps empirical estimation of jmax from vcmax in cool-temperate deciduous forests

Understanding the uncertainty in the parameterization of the two photosynthetic capacity parameters, leaf maximum carboxylation rate (Vcmax), and maximum electron transport rate (Jmax), is crucial for modeling and predicting carbon fluxes in terrestrial ecosystems. In gas exchange models, to date, Jmax is typically estimated from Vcmax based on a linear regression. However, recent studies have revealed that this relationship varies, dependent upon species, leaf groups, and time, so it is doubtful that the regression applies universally. Furthermore, far less is known regarding how other leaf traits affect the regression. In this study we analyzed the two key photosynthetic parameters and popularly measurable leaf traits, leaf chlorophyll concentration and leaf mass per area (LMA), of cool-temperate forest stands in Japan, aiming to construct a simple regression applicable to temperate deciduous forests, at least. The analysis was based on a long-term field dataset covering years of data for both sunlit and shaded leaves at different altitudes. Results showed that the best-fitted slope of the regression differed markedly from those previously reported, which were typically acquired from sunlit leaves. LMA had a significant effect on the regression, producing the lowest root mean square errors and the highest ratio of performance to deviation values (RPD = 2.017). Although more data are needed to validate in other ecosystems, our approach at least provides a promising way to substantially improve photosynthesis model predictions, by introducing leaf traits into the popular empirical regression of Jmax against Vcmax, and ultimately to better understand the functioning of the photosynthetic machinery.

Aerosol-induced direct radiative forcing effects on terrestrial ecosystem carbon fluxes over China

Atmospheric aerosols can change vegetation photosynthesis through the effects of aerosols on radiation, which will affect the peak carbon dioxide emissions and carbon neutrality at global scales. In this study, we quantify the aerosol-induced direct radiation forcing (ADRF) in China from 2001 to 2014 based on the radiation flux simulation used by the Fu-Liou radiation transfer model under with-aerosols and no-aerosols scenarios. Using the radiation simulation results, we modify the atmospheric forcing datasets to drive Community Land Model 4.5 (CLM4.5) to gain the changes in carbon fluxes in China caused by ADRF. The results show that these two models are accurate in estimating radiation (R2 = 0.78–0.88) and carbon fluxes (R2 = 0.73–0.75) in China. High levels of ADRFs were captured in China, especially with increasing diffuse fraction, resulting in the diffusing fertilization effect occurring in most areas of China. The ADRF can increase cumulative gross primary productivity (GPP) and total ecosystem respiration (ER) by 3.20 gC m−2 and 5.13 gC m−2 per year, respectively. From 2001 to 2014, the diffusing fertilization effects experienced trends of increasing first and then decreasing. However, ADRFs in some regions of China show negative effects on carbon fluxes due to vulnerable vegetation functional types and high aerosol loading. The ADRF will also enable soil temperature decreases and volumetric soil water increases, which is closely related to changes in carbon fluxes. Meanwhile, due to changes in soil water and heat conditions, N2O and CH4 production will also be disturbed, and ADRF increases the global warming potential (GWP) for both greenhouse gases. This phenomenon indicated that atmospheric aerosol pollution control is far-reaching significance for peaking carbon dioxide emissions before 2030.

Does the Removal of Non-Photosynthetic Sections Lead to a Down-Regulation of Photosynthesis in Mosses? A First Experiment

When measuring photosynthesis in mosses, the non-photosynthetic (brown) sections are usually removed and only the green sections are measured. However, how this pretreatment affects photosynthesis rates is unclear. Therefore, we studied the effect of removing the non-photosynthetic sections in three moss species with distinct morphological and stem-anatomical structures, comparing net CO2 assimilation rates (AN) of detached green and brown sections to those of intact shoots. Right after separation, the summed AN of the separated sections was significantly lower than those of the intact shoots for Pogonatum nudiusculum Mitt. and Pleuroziopsis ruthenica (Weinm.) Kindb. ex E. Britton, while no significant difference was found for Actinothuidium hookeri (Mitt.) Broth. However, AN recovered within a day, and the progressive reduction of AN expected if carbon-sink removal was an important mechanism was not observed. Our study indicates that removal of non-photosynthetic sections results in an underestimation of the photosynthetic capacity of the green moss sections, but only for the species with relatively complex internal transport structures, and only immediately after the separation. The fast and transient response suggests a mechanism via an electrical signal induced by wounding or reduced hydraulic integrity, rather than through a reduced carbon-sink strength. More comprehensive investigations on signaling and other mechanisms regulating moss photosynthesis will contribute to more accurate measurement methods as well as a deeper understanding of moss ecophysiology and the contribution of mosses to carbon fluxes in terrestrial ecosystems.

How will forecasted warming and drought affect soil respiration in savannah ecosystems? The role of tree canopy and grazing legacy

Soil respiration (RS) is one of the most important carbon fluxes in terrestrial ecosystems, and it is considered as a keystone in predicting ecosystem functioning. Changes in climate and land use may alter RS, triggering feedbacks between RS and other ecosystem components. Different factors might simultaneously alter RS, but the consequences of the interactive effects for ecosystems functioning remain poorly understood. Here, the impact of the expected changes in climate were analysed in a factorial field study over two consecutive years in a Mediterranean savannah ecosystem. We assessed how the interaction of changes in climate with grazing legacy and habitat structure influences RS. We simulated different climate scenarios (ambient, drier, warmer, and drier and warmer conditions) forecasted for the study area at three adjacent sites with different grazing legacies (high, medium, and low) and for the two most important habitat types (open grasslands and under tree canopy). We also considered other factors that could affect RS, such as soil organic C, microbial biomass or net primary productivity, unravelling the direct and indirect effects of the factors controlling RS over time by using structural-equation models (SEMs). Overall, RS was higher under tree canopy than in open grasslands, and high grazing intensity tended to alter RS differently through seasons. Warming scenario consistently increased RS, while drought reduced it (especially in moist seasons), with a moderate increase of RS resulting from the combination of warming and drought. Tree canopy modulated the impact of climate on RS. The SEM analyses identified soil moisture, temperature, grazing legacy and canopy as the main factors controlling RS, although they presented seasonal variations in the size and direction of their effects. Thus, the projected changes in climate can deeply alter ecosystem functioning of carbon sequestration, although their impact can be modulated by canopy cover and management activities.

Temporal dynamics of litter quality, soil properties and microbial strategies as main drivers of the priming effect

The priming effect describes the change in the rate of soil organic matter (SOM) mineralisation due to the addition of fresh organic matter (FOM), and is thus central to the evaluation of carbon fluxes in terrestrial ecosystems. However, little is known about how litter quality interact with soil properties and microbial communities to explain the priming effect. Here, we provide new empirical evidence showing how litter, soil and microbial parameters control FOM and SOM decomposition. We monitored the kinetics of carbon fluxes over 202 days and at 23 dates after additions of two 13C-labelled plant litters of contrasted quality (nutrient-rich and labile litter [i.e., high quality] vs nutrient-poor and recalcitrant litter [i.e., low quality]) using four soil types originating from different ecosystems (forest, grassland, cropland and plantation). We found that the priming effect varied over time with: (i) an ‘immediate’ priming effect after the addition of high quality litter, which rapidly decreases when nitrogen is available; and (ii) a ‘delayed’ priming effect after the addition of low quality litter, which increases continuously when nitrogen is depleted. The ‘immediate’ priming was mainly related to the decomposition of accessible carbon compounds, whereas the ‘delayed priming’ was mainly related to the decomposition of recalcitrant carbon compounds. These results were linked to changes in microbial resource acquisition strategies as indicated by shifts in enzyme activities from hydrolytic to oxidative and nitrogen-related enzymes, therefore suggesting that two series of mechanisms act in succession at different time scales in relation to litter quality and nitrogen availability. Furthermore, our data demonstrate that incorporating carbon in the soil via the increase in soil microbial biomass can counterbalance carbon losses via priming effect. This highlights the importance to assess the balance between the carbon outputs and inputs to determine whether terrestrial ecosystems act as a sink or a source of carbon. We conclude that shifts in litter quality, nutrient availability and microbial resource acquisition strategies need to be taken into consideration for accurate assessment of the variability of the priming effect from the short to the long term.

Soil CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; efflux errors are lognormally distributed – implications and guidance

Abstract. Soil CO2 efflux is the second-largest carbon flux in terrestrial ecosystems. Its feedback to climate determines model predictions of the land carbon sink, which is crucial to understanding the future of the earth system. For understanding and quantification, however, observations by the most widely applied chamber measurement method need to be aggregated to larger temporal and spatial scales. The aggregation is hampered by random error that is characterized by occasionally large fluxes and variance heterogeneity that is not properly accounted for under the typical assumption of normally distributed fluxes. Therefore, we explored the effect of different distributional assumptions on the aggregated fluxes. We tested the alternative assumption of lognormally distributed random error in observed fluxes by aggregating 1 year of data of four neighboring automatic chambers at a Mediterranean savanna-type site. With the lognormal assumption, problems with error structure diminished, and more reasonable prediction intervals were obtained. While the differences between distributional assumptions diminished when aggregating data of single chambers to an annual value, differences were important on short timescales and were especially pronounced when aggregating across chambers to plot level. Hence we recommend as a good practice that researchers report plot-level fluxes with uncertainties based on the lognormal assumption. Model data integration studies should compare predictions and observations of soil CO2 efflux on a log scale. This study provides methodology and guidance that will improve the analysis of soil CO2 efflux observations and hence improve understanding of soil carbon cycling and climate feedbacks.

CO2 Concentration, A Critical Factor Influencing the Relationship between Solar-induced Chlorophyll Fluorescence and Gross Primary Productivity

The uncertainty of carbon fluxes of the terrestrial ecosystem is the highest among all flux components, calling for more accurate and efficient means to monitor land sinks. Gross primary productivity (GPP) is a key index to estimate the terrestrial ecosystem carbon flux, which describes the total amount of organic carbon fixed by green plants through photosynthesis. In recent years, the solar-induced chlorophyll fluorescence (SIF), which is a probe for vegetation photosynthesis and can quickly reflect the state of vegetation growth, emerges as a novel and promising proxy to estimate GPP. The launch of Orbiting Carbon Observatory 2 (OCO-2) further makes it possible to estimate GPP at a finer spatial resolution compared with Greenhouse Gases Observing Satellite (GOSAT), Global Ozone Monitoring Experiment-2 (GOME-2) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). However, whether the relationship between GPP and SIF is linear or non-linear has always been controversial. In this research, we proposed a new model to estimate GPP using SIF and the atmospheric CO2 concentration from OCO-2 as critical driven factors simultaneously (SIF-CO2-GPP model). Evidences from all sites show that the introduction of the atmospheric CO2 concentration improves accuracies of estimated GPP. Compared with the SIF-CO2-GPP linear model, we found the SIF-GPP model overestimated GPP in summer and autumn but underestimated it in spring and winter. A series of simulation experiments based on SCOPE (Soil-Canopy Observation of Photosynthesis and Energy) was carried out to figure out the possible mechanism of improved estimates of GPP due to the introduction of atmospheric CO2 concentrations. These experiments also demonstrate that there could be a non-linear relationship between SIF and GPP at half an hour timescale. Moreover, such relationships vary with CO2 concentration. As OCO-2 is capable of providing SIF and XCO2 products with identical spatial and temporal scales, the SIF-CO2-GPP linear model would be implemented conveniently to monitor GPP using remotely sensed data. With the help of OCO-3 and its successors, the proposed SIF-CO2-GPP linear model would play a significant role in monitoring GPP accurately in large geographical extents.

Biotic and Abiotic Contribution to Diurnal Soil CO2 Fluxes from Saline/Alkaline Soils

As the second largest carbon flux in terrestrial ecosystems, the soil CO2 flux is closely related to the atmospheric CO2 concentration. The soil CO2 flux is the sum of biotic respiration and abiotic geochemical CO2 exchange; however, little is known about abiotic CO2 fluxes in arid areas. To investigate the relative contribution of abiotic and biotic soil CO2 fluxes over a diurnal course, the abiotic CO2 flux was distinguished by autoclaving sterilization in both saline and alkaline soils at an arid site in northwestern China. The results demonstrated that: (1) Over the diurnal course, the abiotic CO2 was a significant component of the soil CO2 flux in both saline and alkaline soil, which accounted for more than 56% of the diurnal soil CO2 flux. (2) There was a dramatic difference in the temperature response between biotic and abiotic CO2 fluxes: the response curves of biotic respiration were exponential in the saline soil and quadratic in the alkaline soil, while the abiotic CO2 flux was linearly correlated with soil temperature. They were of similar magnitude but with opposite signs: resulting in almost neutral carbon emissions on daily average. (3) Due to this covering up effect of the abiotic CO2 flux, biotic respiration was severely underestimated (directly measured soil CO2 flux was only one-seventh of the biotic CO2 flux in saline soil, and even an order of magnitude lower in alkaline soil). In addition, the soil CO2 flux masked the temperature-inhibition of biotic respiration in the alkaline soil, and veiled the differences in soil biological respiration between the saline and alkaline soils. Hence, the soil CO2 flux may not be an ideal representative of soil respiration in arid soil. Our study calls for a reappraisal of the definition of the soil CO2 flux and its temperature dependence in arid or saline/alkaline land. Further investigations of abiotic CO2 fluxes are needed to improve our understanding of arid land responses to global warming and to assist in identifying the underlying abiotic mechanisms.

Temperature Sensitivity in Individual Components of Ecosystem Respiration Increases along the Vertical Gradient of Leaf–Stem–Soil in Three Subtropical Forests

Temperature sensitivity (Q10) of ecosystem respiration (ER) is a crucial parameter for predicting the fate of CO2 in terrestrial e cosystems under global warming. Most studies focus their attention in the variation of Q10 in one or two components of ER, but not in the integration or comparison among Q10 in major components of ER. Vertical and seasonal variations in individual components, including leaf respiration, stem respiration and soil respiration, of ER were observed synchronously along the gradient of leaf–stem–soil over a 2 year period in three forest stands dominated by masson pine, loblolly pine and oak, respectively, in a subtropical forest ecosystem of central China. We found that Q10 in individual components of ER increased along the vertical gradient of leaf–stem–soil. The vertical pattern of Q10 in individual components of ER was ascribed to variations of diurnal temperature range (DTR) and activation energy (ΔHa). These results suggest that a vertical pattern of Q10 in individual components of ER along the gradient of leaf–stem–soil should be taken into consideration in process-based models that simulate respiratory carbon flux in terrestrial ecosystems.

Terrestrial ecosystem carbon flux estimated using GOSAT and OCO-2 XCO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; retrievals

Abstract. In this study, both the Greenhouse Gases Observing Satellite (GOSAT) and the Orbiting Carbon Observatory 2 (OCO-2) XCO2 retrievals produced by the NASA Atmospheric CO2 Observations from Space (ACOS) project (version b7.3) are assimilated within the GEOS-Chem 4D-Var assimilation framework to constrain the terrestrial ecosystem carbon flux during 1 October 2014 to 31 December 2015. One inversion for the comparison, using in situ CO2 observations, and another inversion as a benchmark for the simulated atmospheric CO2 distributions of the real inversions, using global atmospheric CO2 trends and referred to as the poor-man inversion, are also conducted. The estimated global and regional carbon fluxes for 2015 are shown and discussed. CO2 observations from surface flask sites and XCO2 retrievals from Total Carbon Column Observing Network (TCCON) sites are used to evaluate the simulated concentrations with the posterior carbon fluxes. Globally, the terrestrial ecosystem carbon sink (excluding biomass burning emissions) estimated from GOSAT data is stronger than that inferred from OCO-2 data, weaker than the in situ inversion and matches the poor-man inversion the best. Regionally, in most regions, the land sinks inferred from GOSAT data are also stronger than those from OCO-2 data, and in North America, Asia and Europe, the carbon sinks inferred from GOSAT inversion are comparable to those from in situ inversion. For the latitudinal distribution of land sinks, the satellite-based inversions suggest a smaller boreal and tropical sink but larger temperate sinks in both the Northern and Southern Hemisphere than the in situ inversion. However, OCO-2 and GOSAT generally do not agree on which continent contains the smaller or larger sinks. Evaluations using flask and TCCON observations and the comparisons with in situ and poor-man inversions suggest that only GOSAT and the in situ inversions perform better than a poor-man solution. GOSAT data can effectively improve the carbon flux estimates in the Northern Hemisphere, while OCO-2 data, with the specific version used in this study, show only slight improvement. The differences of inferred land fluxes between GOSAT and OCO-2 inversions in different regions are mainly related to the spatial coverage, the data amount and the biases of these two satellite XCO2 retrievals.

Multi‐model analysis of climate impacts on plant photosynthesis in China during 2000–2015

AbstractDifferences, arising from differences in gross primary production (GPP) model structures and driving forces, have fuelled arguments concerning interannual changes of GPP in China since 2000. To better investigate the interannual variability of GPP and its covariance with climate factors in China, this study adopted a multi‐model analysis based on three GPP models (i.e., Terrestrial Ecosystem Carbon flux model [TEC], Breathing Earth System Simulator model [BESS], and MOD17 GPP model). The results show that annual GPP in China increased by 0.021–0.057 Pg C year−1 from 2000 to 2015 attributable to atmospheric‐CO2 fertilization effects and favourable climate change, that is, increasing precipitation (Pr) and temperature (Ta). However, northern China and southern China had a large difference in the amplitude of these GPP changes; annual GPP increased by 0.017–0.039 Pg C year−1 in northern China but only 0.001–0.018 Pg C year−1 in southern China. Northern China and southern China occupy contrasting climate zones and this contrast produced different interannual variability of GPP through different mechanisms. Northern China has a dry climate with GPP changes sensitive to Pr. As a result, more Pr along with higher Ta in northern China produced the strong uptrend of GPP from 2000 to 2015. In contrast, southern China has a wet climate with its GPP sensitive to solar radiation and Ta. For the interval of 2000–2015, decreasing radiation plus drought exerted a negative influence on GPP in southern China. This study highlights the diverse mechanisms in which climate change affects GPP in dry and wet climate zones. A robust multi‐model analysis is preferred to reduce uncertainties arising from a single GPP model and its driving data.