Systematic Hydrological Evaluation of the Noah-MP Land Surface Model over China

We evaluate water budget components—namely, soil moisture, runoff, evapotranspiration, and terrestrial water storage (TWS)—simulated by the Noah land surface model with multi-parameterization options (Noah-MP) in China, a large geographic domain challenging for hydrological modeling due to poor observational data and a lack of one single parameterization that can fit for complex hydrological processes. By comparing the model simulations with multi-source reference data, we show that Noah-MP can generally reproduce the overall spatiotemporal patterns of runoff and evapotranspiration over six major river basins, with the annual correlation coefficients generally greater than 0.8 and the Nash–Sutcliffe model efficiency coefficient exceeding 0.5. Among the six basins evaluated, the best model performance is seen over the Huaihe River basin. The temporal trend of the modeled TWS anomalies agrees well with GRACE (Gravity Recovery and Climate Experiment) observations, capturing major flood and drought events in different basins. Experiments with 12 selected physical parameterization options show that the runoff parameterization has a stronger impact on the simulated soil moisture–runoff–evapotranspiration relationships than the soil moisture factor for stomatal resistance schemes, a result consistent with previous studies. Overall, Noah-MP driven by GLDAS forcing simulates the hydrological variables well, except for the Songliao basin in northeastern China, likely because this is a transitional region with extensive freeze–thaw activity, while representations of human activities may also help improve the model performance.     

Description and Application of a Model for Simulating Regional Nitrogen Cycling and Calculating Nitrogen Flux

A regional nitrogen cycle model, named IAP-N, was designed for simulating regional nitrogen （N） cycling and calculating N fluxes flowing among cultivated soils, crops, and livestock, as well as human, atmospheric and other systems. The conceptual structure and calculation methods and procedures of this model are described in detail. All equations of the model are presented. In addition, definitions of all the involved variables and parameters are given. An application of the model in China at the national scale is presented. In this example, annual surpluses of consumed synthetic N fertilizer; emissions of nitrous oxide （N2O）, ammonia （NH3） and nitrogen oxide （NOx）; N loss from agricultural lands due to leaching and runoff; and sources and sinks of anthropogenic reactive N （Nr） were estimated for the period 1961-2004. The model estimates show that surpluses of N fertilizer started to occur in the mid 1990s and amounted to 5.7 Tg N yr^-1 in the early 2000s. N20 emissions related to agriculture were estimated as 0.69 Tg N yr^-1 in 2004, of which 58% was released directly from N added to agricultural soils. Total NH3 and NOx emissions in 2004 amounted to 4.7 and 4.9 Tg N yr^-1, respectively. About 3.9 Tg N yr^-1 of N was estimated to have flowed out of the cultivated soil layer in 2004, which accounted for 33% of applied synthetic N fertilizer. Anthropogenic Nr sources changed from 2.8 （1961） to 28.1 Tg N yr^-1 （2004）, while removal （sinks） changed from to 2.1 to 8.4 Tg N yr^-1. The ratio of anthropogenic Nr sources to sinks was only 1.4 in 1961 but 3.3 in 2004. Further development of the IAP-N model is suggested to focus upon： Ca） inter-comparison with other regional N models; （b） overcoming the limitations of the current model version, such as adaptation to other regions, high-resolution database, and so on; and （c） developing the capacity to estimate the safe threshold of anthropogenic Nr source to sink ratios.     

A review on vegetation models and applicability to climate simulations at regional scale

The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson’s rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.     

Incorporation of a dynamic root distribution into CLM4.5: Evaluation of carbon and water fluxes over the Amazon

Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon–nitrogen(CN) interactions(CLM4.5-CN) to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83(BRSa3) site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production(GPP) and latent heat flux(LE) for the dry season, and improved the carbon(C) and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m~(-2)d~(-1), net ecosystem exchange by 1.96 g C m~(-2)d~(-1), LE by 5.0 W m~(-2), and soil moisture by 0.03 m~3m~(-3), at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses(including GPP and LE) to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.     

1981—2019年全球陆地生态系统碳通量变化特征及其驱动因子

陆地生态系统碳汇显著降低大气CO₂浓度上升和全球变暖的速率,受人类活动和气候变化的影响,陆地生态系统碳通量具有强烈的时空变化,其估算结果仍存在较大的不确定性,不同因子的贡献尚不清晰。为此,利用遥感驱动的陆地生态系统过程模型BEPS模拟分析了1981—2019年全球陆地生态系统碳通量的时空变化特征,评价了大气CO₂浓度、叶面积指数（Leaf Area Index,LAI）、氮沉降、气候变化对全球陆地生态系统碳收支变化的贡献。1981—2019年全球陆地生态系统总初级生产力（Gross Primary Productivity,GPP）、净初级生产力（Net Primary Productivity,NPP）和净生态系统生产力（Net Ecosystem Productivity,NEP）的平均值分别为115.3、51.3和2.7 Pg·a^-1（以碳质量计,下同）,上升速率分别为0.47、0.21和0.06 Pg·a^-1。全球大部分区域GPP和NPP显著增加,NEP显著上升（p<0.05）的区域明显少于GPP和NPP。1981—2019年,全球NEP累积为105.2 Pg,森林、稀树草原及灌木、农田和草地的贡献分别为76.4、15.8、9.4和3.6 Pg。CO₂浓度、LAI、氮沉降和气候变化各自对NEP的累积贡献分别为58.4、20.6、0.7和-43.6 Pg,全部4个因子变化对NEP的累积贡献为39.8 Pg,其中CO₂浓度上升是近40 a全球陆地生态系统NEP上升的主要贡献因子,其次为LAI。     

Uncertainty of Climate Response to Natural and Anthropogenic Forcings Due to Different Land Use Scenarios

The A.M.Obukhov Institute of Atmospheric Physics,Russian Academy of Sciences (IAP RAS) climate model (CM) of intermediate complexity is extended by a spatially explicit terrestrial carbon cycle module.Numerical experiments with the IAP RAS CM are performed forced by the reconstructions of anthropogenic and natural forcings for the 16th to the 20th centuries and by combined SRES (Special Report on Emission Scenarios) A2-LUH (Land Use Harmonization) anthropogenic scenarios for the 21st century.Hereby,the impact of uncertainty in land-use scenarios on results of simulations with a coupled climate-carbon cycle model is tested.The simulations of the model realistically reproduced historical changes in carbon cycle characteristics.In the IAP RAS CM,climate warming reproduced in the 20th and 21st centuries enhanced terrestrial net primary production but terrestrial carbon uptake was suppressed due to an overcompensating increase in soil respiration.Around year 2100,the simulations the model forced by different land use scenarios diverged markedly,by about 70 Pg (C) in terms of biomass and soil carbon stock but they differed only by about 10 ppmv in terms of atmospheric carbon dioxide content.     

Coupling a Terrestrial Biogeochemical Model to the Common Land Model

A terrestrial biogeochemical model (CASACNP) was coupled to a land surface model (the Common Land Model,CoLM) to simulate the dynamics of carbon substrate in soil and its limitation on soil respiration.The combined model,CoLM CASACNP,was able to predict long-term carbon sources and sinks that CoLM alone could not.The coupled model was tested using measurements of belowground respiration and surface fluxes from two forest ecosystems.The combined model simulated reasonably well the diurnal and seasonal variations of net ecosystem carbon exchange,as well as seasonal variation in the soil respiration rate of both the forest sites chosen for this study.However,the agreement between model simulations and actual measurements was poorer under dry conditions.The model should be tested against more measurements before being applied globally to investigate the feedbacks between the carbon cycle and climate change.     

放牧草地生态系统中氮素的损失和管理

对于大多数放牧草地,Ｎ素都是限制生产力的最重要因素之一,而生态系统中Ｎ素的损失量又很大,Ｎ素以ＮＯ－３、ＮＨ３、Ｎ２Ｏ等形态进入水圈和大气圈,不仅造成了生产上的资源浪费,而且对全球环境和人类健康都产生了深远的影响。本文将对草地生态系统中Ｎ素损失的主要过程（如氮挥发、反硝化和ＮＯ－３淋溶等）及影响因素研究的进展情况进行简要地综述,然后对ＩＭＧＡＲＳＳ项目研究中关于Ｎ素损失研究部分提出一些建议。草地生态系统中Ｎ素损失的主要途径包括：土壤、植物、动物排泄物和肥料的氨挥发;生物和化学反硝化;淋溶;动物体和动物产品对Ｎ素的固持;动植物残体和动物排泄物的燃烧;动物以排泄物形式将Ｎ素从生产区转移到非生产区;通过土壤侵蚀而损失等。放牧加速了草地生态系统中Ｎ素的损失速率。从全球角度分析ＮＨ３的来源后认为,生物残体燃烧是最大的ＮＨ３源,其次是自然土地。对欧洲ＮＨ３来源的研究表明,与人类活动有关的ＮＨ３挥发总量的大部分来源于牲畜排泄物的氨挥发。由于方法的限制,对田间条件下的反硝化测定较少,动物排泄物对Ｎ２Ｏ的贡献及对全球变化影响的研究数据较少。但研究表明,草地尿、粪斑处Ｎ２Ｏ释放速率很高,动物排泄物可能是最重要的Ｎ２Ｏ源。在半干     

Modeling Dynamic Vegetation Response to Rapid Climate Change Using Bioclimatic Classification

Modeling potential global redistribution of terrestrial vegetation frequently is based on bioclimatic classifications which relate static regional vegetation zones (biomes) to a set of static climate parameters. The equilibrium character of the relationships limits our confidence in their application to scenarios of rapidly changing climate. Such assessments could be improved if vegetation migration and succession would be incorporated as response variables in model simulations. We developed the model MOVE (Migration Of VEgetation), to simulate the geographical implications of different rates of plant extirpation and in-migration. We used the model to study the potential impact on terrestrial carbon stocks of climate shifts hypothesized from a doubling of atmospheric greenhouse gas concentration. The model indicates that the terrestrial vegetation and soil could release carbon; the amount of this carbon pulse depends on the rate of migration relative to the rate of climate change. New temperate and boreal biomes, not found on the landscape today, increase rapidly in area during the first 100 years of simulated response to climate change. Their presence for several centuries and their gradual disappearance after the climate ceases to change adds uncertainty in calculating future terrestrial carbon fluxes.     

东亚季风区夏季陆地生态系统碳循环对东亚夏季风的响应

东亚地区陆地生态系统的时空变率表现出明显的对季风气候的响应特征。使用EOF（经验正交分解）方法分析了AVIM2动态植被陆面模式离线模拟试验模拟的1953～2004年东亚季风区夏季陆地生态系统总初级生产力（GPP）、生态系统净初级生产力（NPP）、净生态系统初级生产力（NEP）、植被呼吸以及土壤呼吸的时空分布特点,探讨了东亚夏季风对陆地生态系统碳循环影响机制。研究发现,在强季风年,江淮地区高温少雨的特点限制了光合作用,造成GPP偏低;而华南地区在强季风年气候温暖湿润,利于植被生长,GPP偏高。季风对于植被呼吸和土壤呼吸影响不明显,使得GPP和植被呼吸之差NPP的变化及NPP和土壤呼吸之差NEP的变化与GPP的变化保持一致。在强季风年江淮流域地区干热的气候条件使得NPP和NEP降低;但是在华南地区温度升高的同时降水增多使得在NPP偏高的基础上NEP也偏高。     

Does the integration of the dynamic nitrogen cycle in a terrestrial biosphere model improve the long-term trend of the leaf area index?

The carbon cycle strongly interacts with the nitrogen cycle. Several observations show that the effects of global change on primary production and carbon storage in plant biomass and soils are partially controlled by N availability. Nevertheless, only a small number of terrestrial biosphere models represent explicitly the nitrogen cycle, despite its importance on the carbon cycle and on climate. These models are difficult to evaluate at large spatiotemporal scales because of the scarcity of data at the global scale over a long time period. In this study, we benchmark the capacity of the O–CN global terrestrial biosphere model to reproduce temporal changes in leaf area index (LAI) at the global scale observed by NOAA_AVHRR satellites over the period 1982–2002. Using a satellite LAI product based on the normalized difference vegetation index of global inventory monitoring and modelling studies dataset, we estimate the long-term trend of LAI and we compare it with the results from the terrestrial biosphere models, either with (O–CN) or without (O–C) a dynamic nitrogen cycle coupled to the carbon–water-energy cycles. In boreal and temperate regions, including a dynamic N cycle (O–CN) improved the fit between observed and modeled temporal changes in LAI. In contrast, in the tropics, simulated LAI from the model without the dynamic N cycle (O–C) better matched observed changes in LAI over time. Despite differential regional trends, the satellite estimate suggests an increase in the global average LAI during 1982–2002 by 0.0020 m² m^?2 y^?1. Both versions of the model substantially overestimated the rate of change in LAI over time (0.0065 m² m^?2 y^?1 for O–C and 0.0057 m² m^?2 y^?1 for O–CN), suggesting that some additional limitation mechanisms are missing in the model. We also estimated the relative importance of climate, CO₂ and N deposition as potential drivers of the temporal changes in LAI. We found that recent climate change better explained temporal changes in LAI when the dynamic N cycle was included in the model (higher ranked fit for O–CN vs. O–C). Using the O–C configuration to estimate the direct effect of climate on LAI, we quantified the importance of climate-N cycle feedbacks in explaining the LAI response. We found that the warming-induced release of N from soil organic matter decomposition explains 17.5 % of the global trend in LAI over time, however, reaching up to 40.9 % explained variance in the boreal zone, which is a more important contribution than increasing anthropogenic nitrogen deposition. Our analysis supports a strong connection between warming, N cycling, and vegetation productivity. These findings underscore the importance of including N cycling in global-scale models of vegetation response to environmental change.     

典型温带针阔叶混交林碳收支对温度的响应特征

森林生态系统是一个庞大的碳储备系统,在当前气候变暖条件下,温度变化会对森林生态系统的碳收支过程产生重要影响。该文选择长白山温带针阔混交林森林生态系统（CBS）作为研究对象,利用多年通量及小气候观测资料分析该生态系统碳收支过程对温度的响应特征,结果显示该温带森林碳交换的季节变化特征十分明显。生态系统总初级生产力GPP、生态系统呼吸R_e和净生态系统碳交换NEE在2003—2008年的月平均变化显示,碳收支3个组分最大值均出现在夏季,GPP最大值出现在7月,R_e最大值主要出现在8月,NEE负方向的最大值主要出现在6月或7月,表现为碳吸收。在日尺度和月尺度对温度的响应上,GPP和R_e都是随温度（气温和5 cm土壤温度）呈显著的指数升高形式。在日尺度上和月尺度上, NEE对气温的响应皆是分段线性形式,先是随气温的上升而正向增大,表现为碳排放;当超过临界温度,随气温的继续上升而负值增大,表现为碳吸收。根据温度、GPP、R_e以及NEE的季节的变化,每年达到最大的GPP、R_e以及NEE的最适温度均不同,这表明了在气温变化的背景下,生态系统的最适温度也在随之改变,也表明了不考虑其它因素的影响,在气候变暖的背景下,长白山针阔混交林森林生态系统的GPP、R_e随气温的升高增大,而NEE随气温的升高而减小。     

Earth System Model FGOALS-s2: Coupling a dynamic global vegetation and terrestrial carbon model with the physical climate system model

Earth System Models （ESMs） are fundamental tools for understanding climate-carbon feedback. An ESM version of the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） was recently developed within the IPCC AR5 Coupled Model Intercomparison Project Phase 5 （CMIP5） modeling framework, and we describe the development of this model through the coupling of a dynamic global vegetation and terrestrial carbon model with FGOALS-s2. The performance of the coupled model is evaluated as follows. The simulated global total terrestrial gross primary production （GPP） is 124.4 PgC yr-I and net pri- mary production （NPP） is 50.9 PgC yr-1. The entire terrestrial carbon pools contain about 2009.9 PgC, comprising 628.2 PgC and 1381.6 PgC in vegetation and soil pools, respectively. Spatially, in the tropics, the seasonal cycle of NPP and net ecosystem production （NEP） exhibits a dipole mode across the equator due to migration of the monsoon rainbelt, while the seasonal cycle is not so significant in Leaf Area Index （LAI）. In the subtropics, especially in the East Asian monsoon region, the seasonal cycle is obvious due to changes in temperature and precipitation from boreal winter to summer. Vegetation productivity in the northern mid-high latitudes is too low, possibly due to low soil moisture there. On the interannual timescale, the terrestrial ecosystem shows a strong response to ENSO. The model- simulated Nifio3.4 index and total terrestrial NEP are both characterized by a broad spectral peak in the range of 2-7 years. Further analysis indicates their correlation coefficient reaches -0.7 when NEP lags the Nifio3.4 index for about 1-2 months.     

Summary of Recent Climate Change Studies on the Carbon and Nitrogen Cycles in the Terrestrial Ecosystem and Ocean in China

This article reviews recent advances over the past 4 years in the study of the carbon-nitrogen cycling and their relationship to climate change in China. The net carbon sink in the Chinese terrestrial ecosystem was 0.19-0.26 Pg C yr-1 for the 1980s and 1990s. Both natural wetlands and the rice-paddy regions emitted 1.76 Tg and 6.62 Tg of CH 4 per year for the periods 1995-2004 and 2005-2009, respectively. China emitted～1.1 Tg N 2 O-N yr-1 to the atmosphere in 2004. Land soil contained～8.3 Pg N. The excess nitrogen stored in farmland of the Yangtze River basin reached 1.51 Tg N and 2.67 Tg N in 1980 and 1990, respectively. The outer Yangtze Estuary served as a moderate or significant sink of atmospheric CO 2 except in autumn. Phytoplankton could take up carbon at a rate of 6.4 ×10 11 kg yr-1 in the China Sea. The global ocean absorbed anthropogenic CO 2 at the rates of 1.64 and 1.73 Pg C yr-1 for two simulations in the 1990s. Land net ecosystem production in China would increase until the mid-21st century then would decrease gradually under future climate change scenarios. This research should be strengthened in the future, including collection of more observation data, measurement of the soil organic carbon (SOC) loss and sequestration, evaluation of changes in SOC in deep soil layers, and the impacts of grassland management, carbon-nitrogen coupled effects, and development and improvement of various component models and of the coupled carbon cycle-climate model.     

Improving Simulation of the Terrestrial Carbon Cycle of China in Version 4.5 of the Community Land Model Using a Revised Vcmax Scheme

The maximum rate of carboxylation(Vcmax) is a key photosynthetic parameter for gross primary production(GPP) estimation in terrestrial biosphere models. A set of observation-based Vcmax values, which take the nitrogen limitation on photosynthetic rates into consideration, are used in version 4.5 of the Community Land Model(CLM4.5). However, CLM4.5 with carbon-nitrogen(CN) biogeochemistry(CLM4.5-CN) still uses an independent decay coefficient for nitrogen after the photosynthesis calculation. This means that the nitrogen limitation on the carbon cycle is accounted for twice when CN biogeochemistry is active. Therefore, to avoid this double nitrogen down-regulation in CLM4.5-CN, the original Vcmax scheme is revised with a new one that only accounts for the transition between Vcmax and its potential value(without nitrogen limitation). Compared to flux towerbased observations, the new Vcmax scheme reduces the root-mean-square error(RMSE) in GPP for mainland China by 13.7 g C m-2 yr-1, with a larger decrease over humid areas(39.2 g C m-2 yr-1). Moreover, net primary production and leaf area index are also improved, with reductions in RMSE by 0.8% and 11.5%, respectively.     

Modeling soil thermal and hydrological dynamics and changes of growing season in Alaskan terrestrial ecosystems

Abundant evidence indicates the growing season has been changed in the Alaskan terrestrial ecosystems in the last century as climate warms. Reasonable simulations of growing season length, onset, and ending are critical to a better understanding of carbon dynamics in these ecosystems. Recent ecosystem modeling studies have been slow to consider the interactive effects of soil thermal and hydrological dynamics on growing season changes in northern high latitudes. Here, we develop a coupled framework to model these dynamics and their effects on plant growing season at a daily time step. In this framework, we (1) incorporate a daily time step snow model into our existing hydrological and soil thermal models and (2) explicitly model the moisture effects on soil thermal conductivity and heat capacity and the effects of active layer depth and soil temperature on hydrological dynamics. The new framework is able to well simulate snow depth and soil temperature profiles for both boreal forest and tundra ecosystems at the site level. The framework is then applied to Alaskan boreal forest and tundra ecosystems for the period 1923–2099. Regional simulations show that (1) for the historical period, the growing season length, onset, and ending, estimated based on the mean soil temperature of the top 20 cm soils, and the annual cycle of snow dynamics, agree well with estimates based on satellite data and other approaches and (2) for the projected period, the plant growing season length shows an increasing trend in both tundra and boreal forest ecosystems. In response to the projected warming, by year 2099, (1) the snow-free days will be increased by 41.0 and 27.5 days, respectively, in boreal forest and tundra ecosystems and (2) the growing season lengths will be more than 28 and 13 days longer in boreal forest and tundra ecosystems, respectively, compared to 2010. Comparing two sets of simulations with and without considering feedbacks between soil thermal and hydrological dynamics, our analyses suggest coupling hydrological and soil thermal dynamics in Alaskan terrestrial ecosystems is important to model ecosystem dynamics, including growing season changes.     

紫金山不同海拔高度土壤的碳氮分布特征

有机碳氮是影响陆地生态系统的重要因子,保持并提高土壤碳氮储量,是稳定生态系统生产力的关键.以南京紫金山土壤为研究对象,依照海拔高度进行采样,对比分析了土壤有机碳氮的变化规律.研究结果表明:紫金山土壤有机碳氮受地表植被的影响比较大,混交林>林地>草地,土壤有机碳氮总量随海拔的升高呈现上升趋势,土壤碳氮比高达34~45,且随海拔升高呈下降趋势.相关分析表明,紫金山土壤有机碳与全氮质量分数呈显著正相关关系,由此说明氮素主要以有机氮的形式存在于有机质中.     

Adaptive management to climate change for Norway spruce forests along a regional gradient in Finland

We hypothesized that the responses of boreal Norway spruce (Picea abies) forests to climate change would be region-specific due to regional differences in temperature and water availability. In this context, we analyzed the adaptive effects of varied thinning intensities on the gross primary production (GPP), total stem wood growth, and timber yield over a 100-year period using a process-based ecosystem model. Our simulations represented Norway spruce forests for five different bioclimatic zones spanning southern to northern Finland (61–67^oN). Ten thinning regimes with thinning intensities ranging from 5 to 50 %, as well as an unthinned regime, were included in the calculations. The results showed that at the southern sites without thinning, the cumulative GPP and total stem wood growth were lower under the changing climate than in the current climate over the simulation period due to greater water depletion via evapotranspiration and reduced soil water availability. At the central and the northern sites, the climate changes increasingly enhanced the GPP and total stem wood growth due to the mitigation of low-temperature limitation and the improved soil water availability. Thinning generally mitigated the soil water deficit by reducing water evaporation and led to a reduction of the natural mortality. At the southern sites, light and moderate thinning intensities increased the GPP and total stem wood growth relative to sites with a changing climate that experienced no thinning. Moreover, moderate thinning resulted in the greatest timber yield. Heavy thinning, in which a large proportion of standing trees were removed, reduced the GPP and total stem wood growth despite allowing increased soil water availability. At the northern sites, all levels of thinning, including light thinning, decreased the GPP and stem wood growth, indicating that soil water availability was not a limiting factor for growth prior to thinning.     

Climate and Vegetation Drivers of Terrestrial Carbon Fluxes:A Global Data Synthesis

The terrestrial carbon(C) cycle plays an important role in global climate change, but the vegetation and environmental drivers of C fluxes are poorly understood. We established a global dataset with 1194 available data across site-years including gross primary productivity(GPP), ecosystem respiration(ER), net ecosystem productivity(NEP), and relevant environmental factors to investigate the variability in GPP, ER and NEP, as well as their covariability with climate and vegetation drivers.The results indicated that both GPP and ER increased exponentially with the increase in mean annual temperature(MAT)for all biomes. Besides MAT, annual precipitation(AP) had a strong correlation with GPP(or ER) for non-wetland biomes.Maximum leaf area index(LAI) was an important factor determining C fluxes for all biomes. The variations in both GPP and ER were also associated with variations in vegetation characteristics. The model including MAT, AP and LAI explained 53%of the annual GPP variations and 48% of the annual ER variations across all biomes. The model based on MAT and LAI explained 91% of the annual GPP variations and 92.9% of the annual ER variations for the wetland sites. The effects of LAI on GPP, ER or NEP highlighted that canopy-level measurement is critical for accurately estimating ecosystem–atmosphere exchange of carbon dioxide. The present study suggests a significance of the combined effects of climate and vegetation(e.g.,LAI) drivers on C fluxes and shows that climate and LAI might influence C flux components differently in different climate regions.