Sensitivity of carbon budget to historical climate variability and atmospheric CO2 concentration in temperate grassland ecosystems in China

Chinese temperate grasslands play an important role in the terrestrial carbon cycle. Based on the parameterization and validation of Terrestrial Ecosystem Model (TEM, Version 5.0), we analyzed the carbon budgets of Chinese temperate grasslands and their responses to historical atmospheric CO₂ concentration and climate variability during 1951–2007. The results indicated that Chinese temperate grassland acted as a slight carbon sink with annual mean value of 7.3 T?g C, ranging from -80.5 to 79.6 T?g C yr^-1. Our sensitivity experiments further revealed that precipitation variability was the primary factor for decreasing carbon storage. CO₂ fertilization may increase the carbon storage (1.4 %) but cannot offset the proportion caused by climate variability (-15.3 %). Impacts of CO₂ concentration, temperature and precipitation variability on Chinese temperate grassland cannot be simply explained by the sum of the individual effects. Interactions among them increased total carbon storage of 56.6 T?g C which 14.2 T?g C was stored in vegetation and 42.4 T?g C was stored in soil. Besides, different grassland types had different responses to climate change and CO₂ concentration. NPP and R_H of the desert and forest steppes were more sensitive to precipitation variability than temperature variability while the typical steppe responded to temperature variability more sensitively than the desert and forest steppes.     

Multiple temporal scale variability during the twentieth century in global carbon dynamics simulated by a coupled climate–terrestrial carbon cycle model

A coupled climate–carbon cycle model composed of a process-based terrestrial carbon cycle model, Sim-CYCLE, and the CCSR/NIES/FRCGC atmospheric general circulation model was developed. We examined the multiple temporal scale functions of terrestrial ecosystem carbon dynamics induced by human activities and natural processes and evaluated their contribution to fluctuations in the global carbon budget during the twentieth century. Global annual net primary production (NPP) and heterotrophic respiration (HR) increased gradually by 6.7 and 4.7%, respectively, from the 1900s to the 1990s. The difference between NPP and HR was the net carbon uptake by natural ecosystems, which was 0.6 Pg C year^?1 in the 1980s, whereas the carbon emission induced by human land-use changes was 0.5 Pg C year^?1, largely offsetting the natural terrestrial carbon sequestration. Our results indicate that monthly to interannual variation in atmospheric CO₂ growth rate anomalies show 2- and 6-month time lags behind anomalies in temperature and the NiNO₃ index, respectively. The simulated anomaly amplitude in monthly net carbon flux from terrestrial ecosystems to the atmosphere was much larger than in the prescribed air-to-sea carbon flux. Fluctuations in the global atmospheric CO₂ time series were dominated by the activity of terrestrial vegetation. These results suggest that terrestrial ecosystems have acted as a net neutral reservoir for atmospheric CO₂ concentrations during the twentieth century on an interdecadal timescale, but as the dominant driver for atmospheric CO₂ fluctuations on a monthly to interannual timescale.     

Carbon Storage of Forest Vegetation in China and its Relationship with Climatic Factors

Estimates of forest vegetation carbon storage in China varied due to different methods used in the assessments. In this paper, we estimated the forest vegetation carbon storage from the Fourth Forest Inventory Data (FFID) in China using a modified volume-derived method. Results showed that total carbon storage and mean carbon density of forest vegetation in China were 3.8 Pg C (about 1.1% of the global vegetation carbon stock) and 41.32 Mg/ha, respectively. In addition, based on linear multiple regression equation and factor analysis method, we analyzed contributions of biotic and abiotic factors (including mean forest age, mean annual temperature, annual precipitation, and altitude) to forest carbon storage. Our results indicated that forest vegetation carbon storage was more sensitive to changes of mean annual temperature than other factors, suggesting that global warming would seriously affect the forest carbon storage.     

Sensitivity of the Carbon Storage of Potential Vegetation to Historical Climate Variability and CO2 in Continental China

The interest in the national levels of the terrestrial carbon sink and its spatial and temporal variability with the climate and CO2 concentrations has been increasing. How the climate and the increasing atmospheric CO2 concentrations in the last century affect the carbon storage in continental China was investigated in this study by using the Modified Sheffield Dynamic Global Vegetation Model (M-SDGVM). The estimates of the M-SDGVM indicated that during the past 100 years a combination of increasing CO2 with historical temperature and precipitation variability in continental China have caused the total vegetation carbon storage to increase by 2.04 Pg C, with 2.07 Pg C gained in the vegetation biomass but 0.03 Pg C lost from the organic soil carbon matter. The increasing CO2 concentration in the 20th century is primarily responsible for the increase of the total potential vegetation carbon. These factorial experiments show that temperature variability alone decreases the total carbon storage by 1.36 Pg C and precipitation variability alone causes a loss of 1.99 Pg C. The effect of the increasing CO2 concentration alone increased the total carbon storage in the potential vegetation of China by 3.22 Pg C over the past 100 years. With the changing of the climate, the CO2 fertilization on China's ecosystems is the result of the enhanced net biome production (NBP), which is caused by a greater stimulation of the gross primary production (GPP) than the total soil-vegetation respiration. Our study also shows notable interannual and decadal variations in the net carbon exchange between the atmosphere and terrestrial ecosystems in China due to the historical climate variability.     

Responses of Grassland and Forest to Temperature and Precipitation Changes in Northeast China

Using the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation growth, we explored the characteristics and differences in the response to drought of five vegetation biomes in Northeast China, including typical steppe, desert steppe, meadow steppe, deciduous coniferous forest and deciduous broad-leaved forest during the period 1982-2009. The results indicate that growing season precipitation may be the primary vegetation growth-limiting factor in grasslands. More than 70% of the temporal variations in NDVI can be explained by the amount of precipitation during the growing season in typical and desert steppes. During the same period, the mean temperature in the growing season could explain nearly 43% of the variations in the mean growing season NDVI and is therefore a dominant growth-limiting factor for forest ecosystems. Therefore, the NDVI trends differ largely due to differences in the vegetation growth-limiting factors of the different vegetation biomes. The NDVI responses to droughts vary in magnitude and direction and depend on the drought-affected areas of the five vegetation types. Specifically, the changes in NDVI are consistent with the variations in precipitation for grassland ecosystems. A lack of precipitation resulted in decreases in NDVI, thereby reducing vegetation growth in these regions. Conversely, increasing precipitation decreased the NDVI of forest ecosystems. The results also suggest that grasslands under arid and semi-arid environments may be more sensitive to drought than forests under humid environments. Among grassland ecosystems, desert steppe was most sensitive to drought, followed by typical steppe; meadow steppe was the least sensitive.     

An estimate of equilibrium sensitivity of global terrestrial carbon cycle using NCAR CCSM4

Increasing concentrations of atmospheric CO₂ influence climate, terrestrial biosphere productivity and ecosystem carbon storage through its radiative, physiological and fertilization effects. In this paper, we quantify these effects for a doubling of CO₂ using a low resolution configuration of the coupled model NCAR CCSM4. In contrast to previous coupled climate-carbon modeling studies, we focus on the near-equilibrium response of the terrestrial carbon cycle. For a doubling of CO₂, the radiative effect on the physical climate system causes global mean surface air temperature to increase by 2.14 K, whereas the physiological and fertilization on the land biosphere effects cause a warming of 0.22 K, suggesting that these later effects increase global warming by about 10 % as found in many recent studies. The CO₂-fertilization leads to total ecosystem carbon gain of 371 Gt-C (28 %) while the radiative effect causes a loss of 131 Gt-C (~10 %) indicating that climate warming damps the fertilization-induced carbon uptake over land. Our model-based estimate for the maximum potential terrestrial carbon uptake resulting from a doubling of atmospheric CO₂ concentration (285–570 ppm) is only 242 Gt-C. This highlights the limited storage capacity of the terrestrial carbon reservoir. We also find that the terrestrial carbon storage sensitivity to changes in CO₂ and temperature have been estimated to be lower in previous transient simulations because of lags in the climate-carbon system. Our model simulations indicate that the time scale of terrestrial carbon cycle response is greater than 500 years for CO₂-fertilization and about 200 years for temperature perturbations. We also find that dynamic changes in vegetation amplify the terrestrial carbon storage sensitivity relative to a static vegetation case: because of changes in tree cover, changes in total ecosystem carbon for CO₂-direct and climate effects are amplified by 88 and 72 %, respectively, in simulations with dynamic vegetation when compared to static vegetation simulations.     

陆地生态系统与全球变化相互作用的研究进展

全球变化及其对生态系统特别是陆地生态系统的影响已经严重地影响到人类生存环境与社会经济的可持续发展 ,引起了各国政府、科学家及公众的高度关注。文中从CO2 浓度倍增、温度变化、水分变化、水热与CO2 协同作用、辐射变化、臭氧变化以及人为干扰等气候环境变化对植物光合生理、生长发育、物质分配、水分利用、碳氮代谢等的影响方面阐述了全球变化影响生态系统的过程与机理 ;从地理分布范围、物候、结构与功能、生态系统的稳定性等方面分析了中国植被、森林生态系统、草原生态系统与农田生态系统对全球变化的响应 ;从植被变化引起的动力条件与热力条件的变化及植被固碳潜力的变化探讨了植被对于气候的反馈作用。在此基础上 ,基于当前全球变化研究前沿 ,提出了未来关于陆地生态系统与全球变化相互作用研究需要重视的方面 ,尤其是关于生态系统对全球变化响应的阈值研究应引起高度重视。     

Terrestrial biosphere carbon storage under alternative climate projections

This study investigates commonalities and differences in projected land biosphere carbon storage among climate change projections derived from one emission scenario by five different general circulation models (GCMs). Carbon storage is studied using a global biogeochemical process model of vegetation and soil that includes dynamic treatment of changes in vegetation composition, a recently enhanced version of the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM). Uncertainty in future terrestrial carbon storage due to differences in the climate projections is large. Changes by the end of the century range from −106 to +201 PgC, thus, even the sign of the response whether source or sink, is uncertain. Three out of five climate projections produce a land carbon source by the year 2100, one is approximately neutral and one a sink. A regional breakdown shows some robust qualitative features. Large areas of the boreal forest are shown as a future CO₂ source, while a sink appears in the arctic. The sign of the response in tropical and sub-tropical ecosystems differs among models, due to the large variations in simulated precipitation patterns. The largest uncertainty is in the response of tropical rainforests of South America and Central Africa.     

陆地生态系统固碳速率立体监测方法:进展与挑战

全球CO₂浓度增加造成的全球变暖已成为人类亟需解决的问题,陆地生态系统在过去几十年一直扮演着重要的碳汇角色,吸收了30％左右的人类活动排放CO₂。本文调研分析了陆地生态系统固碳速率空间估算方法,包括样地调查、通量监测、模型模拟、遥感估算等,梳理了各种估算方法的研究现状与进展。样地调查、通量观测等方法可以提供点尺度的固碳速率直接测量信息,但存在观测样本有限、空间代表性不足等问题。模型模拟方法可以从机理的角度描述陆地碳、水、能量循环,模拟预测陆地生态系统固碳速率的状态和变化。然而,在模型建立过程中,抽象和简化会引入结构与假设的不确定性,以及模型驱动数据引入的不确定性等问题是碳循环模型模拟方法面临的重大挑战。卫星遥感具有全球覆盖、分辨率精细、时间序列观测等优点,结合机器学习方法,为地球大数据驱动的全球碳源汇估算提供了新的研究范式。但是,当前各种固碳速率的监测方法还没有满足高度时空异质性的陆地生态系统固碳量监测需求,未来需要整合地面观测、模型模拟和卫星遥感等多种技术手段,提供区域和全球尺度的陆地生态系统碳汇精确估算方法体系和科学数据产品。     

Forage Yield-Based Carbon Storage in Grasslands of China

Forage yield-based carbon storage in 18 grasslands of China was estimated according to the detailed investigation of grassland area and forage yield (standing crop), which were derived from a 10-year national grassland survey. The total forage yield carbon in Chinese grasslands is 134.09 Tg C for ca. 299 × 10⁶ ha of grassland area and 1232 kg/ha of mean forage yield. The carbon storage is different depending on grassland types and climatic regions. Meadow, steppe and tussock occupy 93.3% (125.14 Tg C), and desert and swamp only accounts for 6.7% (8.95 Tg C) of total forage yield carbon. Forage yield carbon is stored largely in temperate (38.4%, 51.54 Tg C) and alpine regions (30.4%, 40.78 Tg C), and to less extent in tropical regions (22.1%, 29.66 Tg C). These three regions take 91% of the forage yield carbon in grasslands of China. The warm-temperate region accounts for only 9% (12.1 Tg C) of forage yields carbon. The forage yield-based carbon in grasslands of China is more accurate than the site biomass-based carbon estimate and the carbon density-based estimate. Although, forage yield carbon storage is small compared with the total carbon storage in China, carbon budgets of grasslands are often a dominant component in many regions and provide an important management opportunity to enhance terrestrial carbon sinks in vast areas of China.     

A statistical power analysis of woody carbon flux from forest inventory data

At a national scale, the carbon (C) balance of numerous forest ecosystem C pools can be monitored using a stock change approach based on national forest inventory data. Given the potential influence of disturbance events and/or climate change processes, the statistical detection of changes in forest C stocks is paramount to maintaining the net sequestration status of these stocks. To inform the monitoring of forest C balances across large areas, a power analysis of a forest inventory of live/dead standing trees and downed dead wood C stocks (and components thereof) was performed in states of the Great Lakes region, U.S. Using data from the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, it was found that a decrease in downed wood C stocks (?1.87 Mg/ha) was nearly offset by an increase in standing C stocks (1.77 Mg/ha) across the study region over a 5-year period. Carbon stock change estimates for downed dead wood and standing pools were statistically different from zero (α?=?0.10), while the net change in total woody C (?0.10 Mg/ha) was not statistically different from zero. To obtain a statistical power to detect change of 0.80 (α?=?0.10), standing live C stocks must change by at least 0.7 %. Similarly, standing dead C stocks would need to change by 3.8 %; while downed dead C stocks require a change of 6.9 %. While the U.S.’s current forest inventory design and sample intensity may not be able to statistically detect slight changes (<1 %) in forest woody C stocks at sub-national scales, large disturbance events (>3 % stock change) would almost surely be detected. Understanding these relationships among change detection thresholds, sampling effort, and Type I (α) error rates allows analysts to evaluate the efficacy of forest inventory data for C pool change detection at various spatial scales and levels of risk for drawing erroneous conclusions.     

Boreal forest and tundra ecosystems as components of the climate system

The effects of terrestrial ecosystems on the climate system have received most attention in the tropics, where extensive deforestation and burning has altered atmospheric chemistry and land surface climatology. In this paper we examine the biophysical and biogeochemical effects of boreal forest and tundra ecosystems on atmospheric processes. Boreal forests and tundra have an important role in the global budgets of atmospheric CO₂ and CH₄. However, these biogeochemical interactions are climatically important only at long temporal scales, when terrestrial vegetation undergoes large geographic redistribution in response to climate change. In contrast, by masking the high albedo of snow and through the partitioning of net radiation into sensible and latent heat, boreal forests have a significant impact on the seasonal and annual climatology of much of the Northern Hemisphere. Experiments with the LSX land surface model and the GENESIS climate model show that the boreal forest decreases land surface albedo in the winter, warms surface air temperatures at all times of the year, and increases latent heat flux and atmospheric moisture at all times of the year compared to simulations in which the boreal forest is replaced with bare ground or tundra. These effects are greatest in arctic and sub-arctic regions, but extend to the tropics. This paper shows that land-atmosphere interactions are especially important in arctic and sub-arctic regions, resulting in a coupled system in which the geographic distribution of vegetation affects climate and vice versa. This coupling is most important over long time periods, when changes in the abundance and distribution of boreal forest and tundra ecosystems in response to climatic change influence climate through their carbon storage, albedo, and hydrologic feedbacks.     

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.     

Science Needs and New Technology for Increasing Soil Carbon Sequestration

Fossil fuel use and land use change that began over 200 years ago are driving the rapid increase in atmospheric content of CO₂ and other greenhouse gases that may be impacting climatic change (Houghton et al., 1996). Enhanced terrestrial uptake of CO₂ over the next 50 to 100 years has been suggested as a way to reclaim the 150 or more Pg carbon (C) lost to the atmosphere from vegetation and soil since 1850 as a consequence of land use change (Batjes, 1999; Lal et al., 1998a; Houghton, 1995), thus effectively `buying time' for the development and implementation of new longer term technical solutions, such as C-free fuels. The ultimate potential for terrestrial C sequestration is not known, however, because we lack adequate understanding of (1) the biogeochemical mechanisms responsible for C fluxes and storage potential on the molecular, landscape, regional, and global scales, and (2) the complex genetic and physiological processes controlling key biological and ecological phenomena. Specifically, the structure and dynamics of the belowground component of terrestrial carbon pools, which accounts for two-thirds of global terrestrial organic C stocks, is poorly understood. Focusing primarily on forests, croplands and grasslands, the purpose of this chapter is to consider innovative technology for enhancing C sequestration in terrestrial ecosystems and address the scientific issues related to better understanding of soil C sequestration potential through appropriate and effective approaches to ecosystem management.     

Carbon Storage in Terrestrial Ecosystems of China: Estimates at Different Spatial Resolutions and Their Responses to Climate Change

The carbon storage of terrestrial ecosystems in China was estimated using acommon carbon density method for vegetation and soils relating to thevegetation types. Usingmedian density estimates, carbon storage of 35.23 Gt (1 Gt = 10¹⁵g) in biomass and119.76 Gt in soils with total of 154.99 Gt were calculated based on thebaseline distribution of37 vegetation types. Total carbon storage of the median estimates at differentspatial resolutionswas 153.43, 158.08 and 158.54 Gt, respectively, for the fine (10),median (20) and coarse (30)latitude × longitude grids. There were differences of –1.56, +3.09and +3.55 Gt carbon storagebetween baseline vegetation and those at different spatial resolutions. Changein mappingresolution would change area estimates and hence carbon storage estimates. Thefiner the spatialresolution in mapping vegetation, the closer the carbon storage to thebaseline estimation. Carbonstorage in vegetation and soils for baseline vegetation is quite similar tothat of biomes predictedby BIOME3 for the present climate and CO₂ concentration of 340ppmv. Climate changealone as well as climate change with elevated CO₂ concentrationwill produce an increasein carbon stored by vegetation and soils, especially a larger increase in thesoils. Total mediancarbon storage of terrestrial ecosystems in China will increase by 5.09 Gt and15.91 Gt for theclimate scenario at CO₂ concentration of 340 ppmv and 500 ppmv,respectively. This ismainly due to changes in vegetation areas and the effects of changes inclimate and CO₂concentration.     

中国森林乔木林碳储量及其固碳潜力预测

加强对我国森林碳储量和固碳潜力的研究,是制定中国增汇减排政策的重要依据,对我国国际气候谈判和全面了解森林碳汇潜力具有重要作用。利用我国第七次和第八次森林资源清查中各优势树种的面积和蓄积量数据,采用IPCC材积源生物量法（volume-biomass method),估算了我国森林（乔木林）碳储量和碳密度及其分布,分析我国不同省份天然乔木林和人工乔木林碳储量龄组结构特征;建立分区域、分起源主要优势树种的单位面积蓄积-林龄Logistic生长方程,结合我国森林2020年和2030年面积蓄积增长目标,预测我国乔木林2010—2050年间碳汇潜力。结果表明：第八次清查期间中国乔木林总碳储量为6135.68 Tg,碳密度为37.28 Mg/hm ²;天然乔木林和人工乔木林的碳储量分别为5246.07 Tg和889.61 Tg,分别占总碳储量的85.50%和14.50%。到2050年,中国乔木林和新造林的总碳储量和平均碳密度将分别达到11125.76 Tg和52.52 Mg/hm ²,与2010年相比分别增加81%和41%。分析结果表明中国乔木林有很大的碳汇潜力,将在应对和减缓全球气候变化中发挥重要作用。     

Modeling responses of the meadow steppe dominated by Leymus chinensis to climate change

Grassland is one of the most widespread vegetation types worldwide and plays a significant role in regional climate and global carbon cycling. Understanding the sensitivity of Chinese grassland ecosystems to climate change and elevated atmospheric CO₂ and the effect of these changes on the grassland ecosystems is a key issue in global carbon cycling. China encompasses vast grassland areas of 354 million ha of 17 major grassland types, according to a national grassland survey. In this study, a process-based terrestrial model the CENTURY model was used to simulate potential changes in net primary productivity (NPP) and soil organic carbon (SOC) of the Leymus chinensis meadow steppe (LCMS) under different scenarios of climatic change and elevated atmospheric CO₂. The LCMS sensitivities, its potential responses to climate change, and the change in capacity of carbon stock and sequestration in the future are evaluated. The results showed that the LCMS NPP and SOC are sensitive to climatic change and elevated CO₂. In the next 100 years, with doubled CO₂ concentration, if temperature increases from 2.7-3.9˚C and precipitation increases by 10% NPP and SOC will increase by 7-21% and 5-6% respectively. However, if temperature increases by 7.5-7.8˚C and precipitation increases by only 10% NPP and SOC would decrease by 24% and 8% respectively. Therefore, changes in the NPP and SOC of the meadow steppe are attributed mainly to the amount of temperature and precipitation change and the atmospheric CO₂ concentration in the future.     

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.     

The Potential Effects of Elevated Co2 and Climate Change on Tropical Forest Soils and Biogeochemical Cycling

Tropical forests are responsible for a large proportion of the global terrestrial C flux annually for natural ecosystems. Increased atmospheric CO₂ and changes in climate are likely to affect the distribution of C pools in the tropics and the rate of cycling through vegetation and soils. In this paper, I review the literature on the pools and fluxes of carbon in tropical forests, and the relationship of these to nutrient cycling and climate. Tropical moist and humid forests have the highest rates of annual net primary productivity and the greatest carbon flux from soil respiration globally. Tropical dry forests have lower rates of carbon circulation, but may have greater soil organic carbon storage, especially at depths below 1 meter. Data from tropical elevation gradients were used to examine the sensitivity of biogeochemical cycling to incremental changes in temperature and rainfall. These data show significant positive correlations of litterfall N concentrations with temperature and decomposition rates. Increased atmospheric CO₂ and changes in climate are expected to alter carbon and nutrient allocation patterns and storage in tropical forest. Modeling and experimental studies suggest that even a small increase in temperature and CO₂ concentrations results in more rapid decomposition rates, and a large initial CO₂ efflux from moist tropical soils. Soil P limitation or reductions in C:N and C:P ratios of litterfall could eventually limit the size of this flux. Increased frequency of fires in dry forest and hurricanes in moist and humid forests are expected to reduce the ecosystem carbon storage capacity over longer time periods.     

基于森林资源清查的江西省森林贮碳功能研究

利用江西省1999--2003年森林资源二类清查资料,结合大岗山森林生态站的实测数据以及已公布的调查资料,运用材积源生物量法对江西省森林的碳储量和碳密度进行了估算和评价。结果表明,江西省不同类型森林乔木层碳密度,由大到小依次为硬阔林、针阔混交林、毛竹林、国外松林、杉木林、软阔林、灌木林、马尾松林和经济林,且碳密度随着林龄的增大而增大,随人口密度的增大而减小。森林碳密度土壤层最大,植被层次之,枯落物层最小。不同森林类型乔木层碳储量,由大到小依次为杉木林、硬阔林、马尾松林、毛竹林、灌木林、国外松林、经济林、针阔混交林、软阔林。从森林类型分布看,除杉木和国外松林外,其他森林类型天然林乔木层碳储量远大于人工林;从地理分布看,除南昌、萍乡、新余三市外,其余各市均是天然林乔木层碳储量远大于人工林。不同年龄森林乔木层碳储量,由大到小依次为中龄林、幼龄林、近熟林、成熟林、过熟林。不同森林碳储量由大到小依次为杉木林、马尾松林、硬阔林、灌木林、经济林、毛竹林、针阔混交林、国外松林和软阔林,南部和中西部要高于中东部和北部。江西省森林总碳储量为1．5Gt,占全国森林总碳储量的5．33％。