Future changes of the terrestrial ecosystem based on a dynamic vegetation model driven with RCP8.5 climate projections from 19 GCMs

Future changes of terrestrial ecosystems due to changes in atmospheric CO₂ concentration and climate are subject to a large degree of uncertainty, especially for vegetation in the Tropics. Here, we evaluate the natural vegetation response to projected future changes using an improved version of a dynamic vegetation model (CLM-CN-DV) driven with climate change projections from 19 global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The simulated equilibrium vegetation distribution under historical climate (1981–2000) has been compared with that under the projected future climate (2081–2100) scenario for Representative Concentration Pathway 8.5 (RCP8.5) to qualitatively assess how natural potential vegetation might change in the future. With one outlier excluded, the ensemble average of vegetation changes corresponding to climates of 18 GCMs shows a poleward shift of forests in northern Eurasia and North America, which is consistent with findings from previous studies. It also shows a general “upgrade” of vegetation type in the Tropics and most of the temperate zones, in the form of deciduous trees and shrubs taking over C3 grass in Europe and broadleaf deciduous trees taking over C4 grasses in Central Africa and the Amazon. LAI and NPP are projected to increase in the high latitudes, southeastern Asia, southeastern North America, and Central Africa. This results from CO₂ fertilization, enhanced water use efficiency, and in the extra-tropics warming. However, both LAI and NPP are projected to decrease in the Amazon due to drought. The competing impacts of climate change and CO₂ fertilization lead to large uncertainties in the projection of future vegetation changes in the Tropics.     

Influence of dynamic vegetation on climate change arising from increasing CO<Subscript>2</Subscript>

A dynamic global vegetation model (DGVM) is coupled to an atmospheric general circulation model (AGCM) to investigate the influence of vegetation dynamics on climate change under conditions of global warming. The model results are largely in agreement with observations and the results of previous studies in terms of the present climate, present potential vegetation, present net primary productivity (NPP), and pre-industrial carbon budgets. The equilibrium state of climate properties are compared among pre-industrial, doubled, and quadrupled atmospheric CO₂ values using DGVM–AGCM and current AGCM with fixed vegetation to evaluate the influence of dynamic vegetation change. We also separated the contributions of temperature, precipitation and CO₂ fertilization on vegetation change. The results reveal an amplification of global warming climate sensitivity by 10% due to the inclusion of dynamic vegetation. The total effects of elevated CO₂ and climate change also lead to an increase in NPP and vegetation coverage globally. The reduction of albedo associated with this greening results in enhanced global warming. Our separation analysis indicates that temperature alters vegetation at high latitudes such as Siberia or Alaska, where there is a switch from tundra to forest. On the other hand, CO₂ fertilization provides the largest contribution to greening in arid/semi-arid region. Precipitation change did not cause any drastic vegetation shift.     

The Potential Response of Terrestrial Carbon Storage to Changes in Climate and Atmospheric CO2

We use a georeferenced model of ecosystem carbon dynamics to explore the sensitivity of global terrestrial carbon storage to changes in atmospheric CO₂ and climate. We model changes in ecosystem carbon density, but we do not model shifts in vegetation type. A model of annual NPP is coupled with a model of carbon allocation in vegetation and a model of decomposition and soil carbon dynamics. NPP is a function of climate and atmospheric CO₂ concentration. The CO₂ response is derived from a biochemical model of photosynthesis. With no change in climate, a doubling of atmospheric CO₂ from 280 ppm to 560 ppm enhances equilibrium global NPP by 16.9%; equilibrium global terrestrial ecosystem carbon (TEC) increases by 14.9%. Simulations with no change in atmospheric CO₂ concentration but changes in climate from five atmospheric general circulation models yield increases in global NPP of 10.0–14.8%. The changes in NPP are very nearly balanced by changes in decomposition, and the resulting changes in TEC range from an increase of 1.1% to a decrease of 1.1%. These results are similar to those from analyses using bioclimatic biome models that simulate shifts in ecosystem distribution but do not model changes in carbon density within vegetation types. With changes in both climate and a doubling of atmospheric CO₂, our model generates increases in NPP of 30.2–36.5%. The increases in NPP and litter inputs to the soil more than compensate for any climate stimulation of decomposition and lead to increases in global TEC of 15.4–18.2%.     

Influence of changed vegetations fields on regional climate simulations in the Barents Sea Region

In the context of the EU-Project BALANCE () the regional climate model REMO was used for extensive calculations of the Barents Sea climate to investigate the vulnerability of this region to climate change. The regional climate model REMO simulated the climate change of the Barents Sea Region between 1961 and 2100 (Control and Climate Change run, CCC-Run). REMO on ~50 km horizontal resolution was driven by the transient ECHAM4/OPYC3 IPCC SRES B2 scenario. The output of the CCC-Run was applied to drive the dynamic vegetation model LPJ-GUESS. The results of the vegetation model were used to repeat the CCC-Run with dynamic vegetation fields. The feedback effect of the modified vegetation on the climate change signal is investigated and discussed with focus on precipitation, temperature and snow cover. The effect of the offline coupled vegetation feedback run is much lower than the greenhouse gas effect.     

Benchmarking Climate-Carbon Model Simulations against Forest FACE Data

Terrestrial carbon fluxes are an important factor in regulating concentrations of atmospheric carbon dioxide (CO₂). In this study, we use a coupled climate model with interactive biogeochemistry to benchmark the simulation of net primary productivity (NPP) and its response to elevated atmospheric CO₂. Short-term field experiments such as Free-Air Carbon Dioxide Enrichment (FACE) studies have examined this phenomenon but it is difficult to infer trends from only a few years of field data. Here, we employ the University of Victoria's Earth System Climate Model (UVic ESCM) version 2.8 to compare simulated changes in NPP due to an elevated atmospheric CO₂ concentration of 550 ppm to observed increases in NPP of 23% ±2% from four temperate forest FACE studies between 1997 and 2002. We further compare two scenarios: elevated CO₂ with climate change, and elevated CO₂ without climate change, the latter being consistent with FACE methodology. In the climate change scenario global terrestrial and forest-only NPP increased by 24.5% and 27.9%, respectively, while these increases were 21.0% and 17.2%, respectively, in the latitude band most representative of the location of the FACE studies. In the scenario without climate change, terrestrial and forest-only NPP increased instead by 28.3% and 30.6%, respectively, while these increases were 24.3% and 14.4%, respectively, in the FACE latitudes. This suggests that the model may underestimate temperate forest NPP increases when compared to results from temperate forest FACE studies and highlights the need for both increased experimental study of other forest biomes and further model development.     

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.     

Regional hydrologic and carbon balance responses of forests resulting from potential climate change

The projected response of coniferous forests to a climatic change scenario of doubled atmospheric CO₂, air temperature of +4 °C, and +10% precipitation was studied using a computer simulation model of forest ecosystem processes. A topographically complex forested region of Montana was simulated to study regional climate change induced forest responses. In general, increases of 10–20% in LAI, and 20–30% in evapotranspiration (ET) and photosynthesis (PSN) were projected. Snowpack duration decreased by 19–69 days depending on location, and growing season length increased proportionally. However, hydrologic outflow, primarily fed by snowmelt in this region, was projected to decrease by as much as 30%, which could virtually dry up rivers and irrigation water in the future.To understand the simulated forest responses, and explore the extent to which these results might apply continentally, seasonal hydrologic partitioning between outflow and ET, PSN, respiration, and net primary production (NPP) were simulated for two contrasting climates of Jacksonville, Florida (hot, wet) and Missoula, Montana (cold, dry). Three forest responses were studied sequentially from; climate change alone, addition of CO₂ induced tree physiological responses of-30% stomatal conductance and +30% photosynthetic rates, and finally with a reequilibration of forest leaf area index (LAI), derived by a hydrologic equilibrium theory. NPP was projected to increase 88%, and ET 10%, in Missoula, MT, yet dcrease 5% and 16% respectively for Jacksonville, FL, emphasizing the contrasting forest responses possible with future climatic change.     

Modelling Regional Climate Change Effects On Potential Natural Ecosystems in Sweden

This study aims to demonstrate the potential of a process-based regional ecosystem model, LPJ-GUESS, driven by climate scenarios generated by a regional climate model system (RCM) to generate predictions useful for assessing effects of climatic and CO₂ change on the key ecosystem services of carbon uptake and storage. Scenarios compatible with the A2 and B2 greenhouse gas emission scenarios of the Special Report on Emission Scenarios (SRES) and with boundary conditions from two general circulation models (GCMs) – HadAM3H and ECHAM4/OPYC3 – were used in simulations to explore changes in tree species distributions, vegetation structure, productivity and ecosystem carbon stocks for the late 21st Century, thus accommodating a proportion of the GCM-based and emissions-based uncertainty in future climate development. The simulations represented in this study were of the potential natural vegetation ignoring direct anthropogenic effects. Results suggest that shifts in climatic zones may lead to changes in species distribution and community composition among seven major tree species of natural Swedish forests. All four climate scenarios were associated with an extension of the boreal forest treeline with respect to altitude and latitude. In the boreal and boreo-nemoral zones, the dominance of Norway spruce and to a lesser extent Scots pine was reduced in favour of deciduous broadleaved tree species. The model also predicted substantial increases in vegetation net primary productivity (NPP), especially in central Sweden. Expansion of forest cover and increased local biomass enhanced the net carbon sink over central and northern Sweden, despite increased carbon release through decomposition processes in the soil. In southern Sweden, reduced growing season soil moisture levels counterbalanced the positive effects of a longer growing season and increased carbon supply on NPP, with the result that many areas were converted from a sink to a source of carbon by the late 21st century. The economy-oriented A2 emission scenario would lead to higher NPP and stronger carbon sinks according to the simulations than the environment-oriented B2 scenario.     

Productivity response of climax temperate forests to elevated temperature and carbon dioxide: a north american comparison between two global models

We assess the appropriateness of using regression- and process-based approaches for predicting biogeochemical responses of ecosystems to global change. We applied a regression-based model, the Osnabruck Model (OBM), and a process-based model, the Terrestrial Ecosystem Model (TEM), to the historical range of temperate forests in North America in a factorial experiment with three levels of temperature (+0 °C, +2 °C, and +5 °C) and two levels of CO₂ (350 ppmv and 700 ppmv) at a spatial resolution of 0.5° latitude by 0.5° longitude. For contemporary climate (+0 °C, 350 ppmv), OBM and TEM estimate the total net primary productivity (NPP) for temperate forests in North America to be 2.250 and 2.602 × 10¹⁵ g C ? yr^?1, respectively. Although the continental predictions for contemporary climate are similar, the responses of NPP to altered climates qualitatively differ; at +0 °C and 700 ppmv CO₂, OBM and TEM predict median increases in NPP of 12.5% and 2.5%, respectively. The response of NPP to elevated temperature agrees most between the models in northern areas of moist temperate forest, but disagrees in southern areas and in regions of dry temperate forest. In all regions, the response to CO₂ is qualitatively different between the models. These differences occur, in part, because TEM includes known feedbacks between temperature and ecosystem processes that affect N availability, photosynthesis, respiration, and soil moisture. Also, it may not be appropriate to extrapolate regression-based models for climatic conditions that are not now experienced by ecosystems. The results of this study suggest that the process-based approach is able to progress beyond the limitations of the regression-based approach for predicting biogeochemical responses to global change.     

Projections of climate change impacts on central America tropical rainforest

Tropical rainforest plays an important role in the global carbon cycle, accounting for a large part of global net primary productivity and contributing to CO₂ sequestration. The objective of this work is to simulate potential changes in the rainforest biome in Central America subject to anthropogenic climate change under two emissions scenarios, RCP4.5 and RCP8.5. The use of a dynamic vegetation model and climate change scenarios is an approach to investigate, assess or anticipate how biomes respond to climate change. In this work, the Inland dynamic vegetation model was driven by the Eta regional climate model simulations. These simulations accept boundary conditions from HadGEM2-ES runs in the two emissions scenarios. The possible consequences of regional climate change on vegetation properties, such as biomass, net primary production and changes in forest extent and distribution, were investigated. The Inland model projections show reductions in tropical forest cover in both scenarios. The reduction of tropical forest cover is greater in RCP8.5. The Inland model projects biomass increases where tropical forest remains due to the CO₂ fertilization effect. The future distribution of predominant vegetation shows that some areas of tropical rainforest in Central America are replaced by savannah and grassland in RCP4.5. Inland projections under both RCP4.5 and RCP8.5 show a net primary productivity reduction trend due to significant tropical forest reduction, temperature increase, precipitation reduction and dry spell increments, despite the biomass increases in some areas of Costa Rica and Panama. This study may provide guidance to adaptation studies of climate change impacts on the tropical rainforests in Central America.     

The interactive climate and vegetation along the Pole-Equator belts simulated by a global coupled model

The interaction between climate and vegetation along four Pole-Equator-Pole （PEP） belts were explored using a global two-way coupled model, AVIM-GOALS, which links the ecophysiological processes at the land surface with the general circulation model （GCM）. The PEP belts are important in linking the climate change with the variation of sea and land, including terrestrial ecosystems. Previous PEP belts studies have mainly focused on the paleoclimate variation and its reconstruction. This study analyzes and discusses the interaction between modern climate and vegetation represented by leaf area index （LAI） and net primary production （NPP）. The results show that the simulated LAI variation, corresponding to the observed LAI variation, agrees with the peak-valley variation of precipitation in these belts. The annual mean NPP simulated by the coupled model is also consistent with PIK NPP data in its overall variation trend along the four belts, which is a good example to promote global ecological studies by coupling the climate and vegetation models. A large discrepancy between the simulated and estimated LAI emerges to the south of 15°N along PEP 3 and to the south of 18°S in PEP 1S, and the discrepancy for the simulated NPP and PIK data in the two regions is relatively smaller in contrast to the LAI difference. Precipitation is a key factor affecting vegetation variation, and the overall trend of LAI and NPP corresponds more obviously to precipitation variation than temperature change along most parts of these PEP belts.     

Detecting a Terrestrial Biosphere Sink for Carbon Dioxide: Interannual Ecosystem Modeling for the Mid-1980s

There is considerable uncertainty as to whether interannual variability in climate and terrestrial ecosystem production is sufficient to explain observed variation in atmospheric carbon content over the past 20–30 years. In this paper, we investigated the response of net CO₂ exchange in terrestrial ecosystems to interannual climate variability (1983 to 1988) using global satellite observations as drivers for the NASA-CASA (Carnegie-Ames-Stanford Approach) simulation model. This computer model of net ecosystem production (NEP) is calibrated for interannual simulations driven by monthly satellite vegetation index data (NDVI) from the NOAA Advanced Very High Resolution Radiometer (AVHRR) at 1 degree spatial resolution. Major results from NASA-CASA simulations suggest that from 1985 to 1988, the northern middle-latitude zone (between 30 and 60°N) was the principal region driving progressive annual increases in global net primary production (NPP; i.e., the terrestrial biosphere sink for carbon). The average annual increase in NPP over this predominantly northern forest zone was on the order of +0.4 Pg (10¹⁵ g) C per year. This increase resulted mainly from notable expansion of the growing season for plant carbon fixation toward the zonal latitude extremes, a pattern uniquely demonstrated in our regional visualization results. A net biosphere source flux of CO₂ in 1983–1984, coinciding with an El Niño event, was followed by a major recovery of global NEP in 1985 which lasted through 1987 as a net carbon sink of between 0.4 and 2.6 Pg C per year. Analysis of model controls on NPP and soil heterotrophic CO₂ fluxes (R_h) suggests that regional warming in northern forests can enhance ecosystem production significantly. In seasonally dry tropical zones, periodic drought and temperature drying effects may carry over with at least a two-year lag time to adversely impact ecosystem production. These yearly patterns in our model-predicted NEP are consistent in magnitude with the estimated exchange of CO₂ by the terrestrial biosphere with the atmosphere, as determined by previous isotopic (¹³C) deconvolution analysis. Ecosystem simulation results can help further target locations where net carbon sink fluxes have occurred in the past or may be verified in subsequent field studies.     

北半球近地层典型区CO_2体积分数时空分布及成因

利用GEOS-Chem全球三维大气化学传输模式,分析了北半球近地层CO2体积分数的时空变化特征及其成因。2006—2010年的5 a的模拟结果表明:北半球中纬度近地层CO2体积分数存在着两个高值中心,即亚洲东部和北美东北部。在季节尺度上,亚洲东部CO2体积分数最大值出现在春季,而北美东北区域CO2体积分数最大值出现在冬季;而两个地区的CO2体积分数最低值都出现在夏季。在年际尺度上,两个区域CO2体积分数的年际变率增幅明显高于北半球其它区域,且CO2体积分数高值出现时间的年际差异较大。另外,模拟分析发现北半球森林、农田、草原典型区域,所对应的CO2体积分数具有不同的季节变化特点,它们的CO2季节内变幅依次减小。进一步分析发现3种不同典型区域的CO2体积分数与叶面积指数(LAI)季节变化,具有很好的负相关性。可见陆地生态系统作为碳汇,对近地层CO2体积分数的季节变化具有重要的作用。而温度和降水是影响LAI的最重要的两个气象因子,它们与CO2体积分数季节变化存在内在联系,模拟结果表明北半球大部分陆地近地层CO2体积分数与温度、降水呈现显著的负相关。     

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)...     

基于CMIP5模式安徽省植被净初级生产力预估

利用耦合模式比较计划第5阶段（CMIP5）中5个全球气候模式3种典型浓度路径（RCPs）预估结果,基于植被净初级生产力模型,估算安徽省21世纪近期（2018—2030年)、中期（2031—2050年）和远期（2051—2099年）植被净初级生产力及其对气候变化的响应。结果表明：对不同模式在安徽省模拟能力的评估可知,气温以多模式集合模拟效果优于单个模式,MIROC-ESM-CHEM对降水的模拟能力较好。未来安徽省将持续变暖,北部变暖幅度高于南部,其中RCP8.5情景下变暖趋势更显著;全省降水量将增加,南部增加多于北部。随着气候趋于暖湿化,植被净初级生产力总体增加;与基准年相比,21世纪近期增加不明显,中后期显著增加,空间上南部增加总体高于北部。从气候变化响应来看,安徽省植被净初级生产力与降水量和平均气温均显著相关,并且对降水量的响应程度更高。     

Climate change impacts on ecosystems and the terrestrial carbon sink: a new assessment

Climate output from the UK Hadley Centre's HadCM2 and HadCM3 experiments for the period 1860 to 2100, with IS92a greenhouse gas forcing, together with predicted patterns of N deposition and increasing CO₂, were input (offline) to the dynamic vegetation model, Hybrid v4.1 (Friend et al., 1997; Friend and White, 1999). This model represents biogeochemical, biophysical and biogeographical processes, coupling the carbon, nitrogen and water cycles on a sub-daily timestep, simulating potential vegetation and transient changes in annual growth and competition between eight generalized plant types in response to climate.Global vegetation carbon was predicted to rise from about 600 to 800 PgC (or to 650 PgC for HadCM3) while the soil carbon pool of about 1100 PgC decreased by about 8%. By the 2080s, climate change caused a partial loss of Amazonian rainforest, C₄ grasslands and temperate forest in areas of southern Europe and eastern USA, but an expansion in the boreal forest area. These changes were accompanied by a decrease in net primary productivity (NPP) of vegetation in many tropical areas, southern Europe and eastern USA (in response to warming and a decrease in rainfall), but an increase in NPP of boreal forests. Global NPP increased from 45 to 50 PgC y⁻¹ in the 1990s to about 65 PgC y⁻¹ in the 2080s (about 58 PgC y⁻¹ for HadCM3). Global net ecosystem productivity (NEP) increased from about 1.3 PgC y⁻¹ in the 1990s to about 3.6 PgC y⁻¹ in the 2030s and then declined to zero by 2100 owing to a loss of carbon from declining forests in the tropics and at warm temperate latitudes — despite strengthening of the carbon sink at northern high latitudes. HadCM3 gave a more erratic temporal evolution of NEP than HadCM2, with a dramatic collapse in NEP in the 2050s.     

1981-2008年中国陆地植被NPP对气候变化响应的敏感性试验

在验证CENTURY模型对中国陆地植被净初级生产力(Net Primary Productivity,NPP)模拟能力的基础上,利用该模型探讨了1981-2008年中国陆地植被NPP的年际变异和变化趋势对CO₂浓度、温度和降水变化的响应。结果表明,中国陆地植被NPP对不同气候因子的响应程度存在明显不同。其中,CO₂浓度变化对植被NPP年际变异的影响不显著,但能够引起中国大部分地区植被NPP趋势系数增大;温度对中国中高纬度地区植被NPP的年际变化影响显著,但就全国范围而言,植被NPP年际变异对温度变化的响应程度总体低于对降水变化的响应程度;降水变化是对中国植被NPP变化趋势起主导作用的气候因子。此外,综合考虑温度和降水变化的影响发现,植被NPP变化趋势的响应特征类似于降水单独变化时植被NPP变化趋势的响应特征。     

Global vegetation change predicted by the modified Budyko model

A modified Budyko global vegetation model is used to predict changes in global vegetation patterns resulting from climate change (CO₂ doubling). Vegetation patterns are predicted using a model based on a dryness index and potential evaporation determined by solving radiation balance equations. Climate change scenarios are derived from predictions from four General Circulation Models (GCM's) of the atmosphere (GFDL, GISS, OSU, and UKMO). Global vegetation maps after climate change are compared to the current climate vegetation map using the kappa statistic for judging agreement, as well as by calculating area statistics. All four GCM scenarios show similar trends in vegetation shifts and in areas that remain stable, although the UKMO scenario predicts greater warming than the others. Climate change maps produced by all four GCM scenarios show good agreement with the current climate vegetation map for the globe as a whole, although over half of the vegetation classes show only poor to fair agreement. The most stable areas are Desert and Ice/Polar Desert. Because most of the predicted warming is concentrated in the Boreal and Temperate zones, vegetation there is predicted to undergo the greatest change. Specifically, all Boreal vegetation classes are predicted to shrink. The interrelated classes of Tundra, Taiga, and Temperate Forest are predicted to replace much of their poleward (mostly northern) neighbors. Most vegetation classes in the Subtropics and Tropics are predicted to expand. Any shift in the Tropics favoring either Forest over Savanna, or vice versa, will be determined by the magnitude of the increased precipitation accompanying global warming. Although the model predicts equilibrium conditions to which many plant species cannot adjust (through migration or microevolution) in the 50–100 y needed for CO₂ doubling, it is nevertheless not clear if projected global warming will result in drastic or benign vegetation change.     

Effects of Climate Change on Carbon Storage in Boreal Forests of China: A Local Perspective

The BIOME3 model was used to simulate the distribution patterns and carbon storage of the horizontal, zonal boreal forests in northeast and northwest China using a mapping system for vegetation patterns combined with carbon density estimates from vegetation and soils. The BIOME3 prediction is in reasonable good agreement with the potential distribution of Chinese boreal forests. The effects of changing atmospheric CO₂ concentration had a nonlinear effect on boreal forest distribution, with 3.5–10.8% reduced areas for both increasing and decreasing CO₂. In contrast, the increased climate together with and without changing CO₂ concentration showed dramatic changes in geographic patterns, with 70% reduction in area and disappearance of almost boreal forests in northeast China. The baseline carbon storage in boreal forests of China is 4.60 PgC (median estimate) based on the vegetation area of actual boreal forest distribution. If taking the large area of agricultural crops into account, the median value of potential carbon storage is 6.92 PgC. The increasing (340–500 ppmv) and decreasing CO₂ concentration (340–200 ppmv) led to decrease of carbon storage, 0.33 PgC and 1.01 PgC respectively compared to BIOME3 potential prediction under present climate and CO₂ conditions. Both climate change alone and climate change with CO₂ enrichment (340–500 ppmv) reduced largely the carbon stored in vegetation and soils by ca. 6.5 PgC. The effect of climate change is more significant than the direct physiological effect of CO₂ concentration on the boreal forests of China, showing a large reduction in both distribution area and carbon storage.