土地利用约束下中国东部南北样带生产力和植被分布对全球变化的响应

对现有的区域植被动态模拟模型进行了改进,使之包含了土地利用分布格局对植被和生态系统相关过程的影响。改进后的模型被用地研究中国东部南北样带(NSTEC)植被和净第一性生产力对未来气候变化的响应。模拟结果显示土地利用格局对未来气候条件下植被分布的变迁和生产力形成过程有非常显著的影响。与没有土地利用约束的情形相比较,土地利用作为限制条件缓减了植被类型之间的竞争,从而减少了模拟的样带区域内常绿阔叶林,但增加了模拟灌木和草地的分布。土地利用约束使得模拟得到的当前条件下的净第一性生产力更为接近实际情况,且未来气候条件下的生产力改变量更为可信。对未来CO2倍增条件下7个大气环流模型预测的气候情景的模拟结果表明：落叶阔叶林将显著增加,但针叶林、灌木和草原的分布将下降。未来气候条件下NSTEC样带的净第一性生产力总量将增加。预测样带北部的净第一性生产力的变化范围大于样带南部。温度变化比降水变化对样带的生产力具有更强的控制。     

土地利用约束下中国东部南北样带生产力和植被分布对全球变化的响应

对现有的区域植被动态模拟模型进行了改进,使之包含了土地利用分布格局对植被和生态系统相关过程的影响.改进后的模型被用于研究中国东部南北样带(NSTEC)植被和净第一性生产力对未来气候变化的响应.模拟结果显示土地利用格局对未来气候条件下植被分布的变迁和生产力形成过程有非常显著的影响.与没有土地利用约束的情形相比较,土地利用作为限制条件缓减了植被类型之间的竞争,从而减少了模拟的样带区域内常绿阔叶林,但增加了模拟灌木和草地的分布.土地利用约束使得模拟得到的当前条件下的净第一性生产力更为接近实际情况,且未来气候条件下的生产力改变量更为可信.对未来CO2倍增条件下7个大气环流模型预测的气候情景的模拟结果表明:落叶阔叶林将显著增加,但针叶林、灌木和草原的分布将下降.未来气候条件下NSTEC样带的净第一性生产力总量将增加.预测样带北部的净第一性生产力的变化范围大于样带南部.温度变化比降水变化对样带的生产力具有更强的控制.     

Simulating effects of climate change on boreal ecosystem carbon pools in central Canada

Aim Possible effects of current and future climates on boreal vegetation dynamics and carbon (C) cycling were investigated using the CENTURY 4.0 soil process model and a modified version of the FORSKA2 forest patch model. Location Eleven climate station locations distributed along a transect across the boreal zone of central Canada. Methods Both models were driven by detrended long-term monthly climate data. Using a climate change signal derived from the GISS general circulation model (GCM) 2×CO₂ equilibrium climate scenario, the output from the two models was then used to compare simulated current and possible future total ecosystem C storage at the climate station locations. Results After allowing for their different underlying structures, comparison of output from both models showed good agreement with local field data under current climate conditions. CENTURY 4.0 was able to reproduce spatial variation in soil and litter C densities satisfactorily but tended to overestimate biomass productivity. FORSKA2 reproduced aboveground biomass productivity and spatially averaged biomass densities relatively well. Under the GISS 2×CO₂ scenario, both models generally predicted small increases in aboveground biomass C density for forest and tundra locations, but CENTURY 4.0 predicted greater decreases in soil and litter pools, for overall decreases in ecosystem C storage in the range 16–19%. Main conclusions With some caveats, results imply that effects of increased precipitation (as simulated by the GISS GCM) would more than compensate for any negative effects of increased temperature on forest growth. Increased temperature would also increase decomposition rates of soil and litter organic matter, however, for a net overall decrease in total ecosystem C storage.     

Modeling Productivity in Mangrove Forests as Impacted by Effective Soil Water Availability and Its Sensitivity to Climate Change Using Biome-BGC

Ecosystem dynamics and the responses to climate change in mangrove forests are poorly understood. We applied the biogeochemical process model Biome-BGC to simulate the dynamics of net primary productivity (NPP) and leaf area index (LAI) under the present and future climate conditions in mangrove forests in Shenzhen, Zhanjiang, and Qiongshan across the southern coast of China, and in three monocultural mangrove stands of two native species, Avicennia marina and Kandelia obovata, and one exotic species, Sonneratia apetala, in Shenzhen. The soil hydrological process of the model was modified by incorporating a soil water (SW) stress index to account for the impact of the effective SW availability in the coastal wetland. Our modified Biome-BGC well predicted the dynamics of NPP and LAI in the mangrove forests at the study sites. We found that the six mangrove systems differed in sensitivity to variations in the effective SW availability. At the ecosystem level, however, soil salinity alone could not entirely explain the limitation of the effective SW availability on the productivity of mangrove forests. Increasing atmospheric CO₂ concentration differentially affected growth of different mangrove species but only had a small impact on NPP (<7%); whereas a doubling of atmospheric CO₂ concentration associated with a 2°C temperature rise would increase NPP by 14–19% across the three geographically separate mangrove forests and by 12% to as much as 68% across the three monocultural mangrove stands. Our simulation analysis indicates that temperature change is more important than increasing CO₂ concentration in affecting productivity of mangroves at the ecosystem level, and that different mangrove species differ in sensitivity to increases in temperature and CO₂ concentration.     

Probable effects of CO2-induced climatic changes on net primary productivity of terrestrial vegetation in East Asia

Changes in the net primary productivity (NPP) of natural vegetation of monsoon East Asia were simulated under three, doubled CO₂-climate scenarios (GISS, GFDL and UKMO). These three scenarios and baseline climate data were converted to grids of 1^o×1^o meshes. The gridded climatic data were used together with the Chikugo model to assess NPP under baseline and CO₂-doubling climates. The potential total net production (TNP₀) of East Asia was climatically evaluated to be 154×10⁸ t dry matter year⁻¹. The climatic changes induced by a doubled CO₂ concentration are predicted to increase the TNP₀ by approximately 9–15%, depending on the climatic scenario. The estimated increase in TNP₀ would be limited by the difference between the rate of shift of climatic zones and the rate of migration of vegetation formations.     

Modelling the recent historical impacts of atmospheric CO2 and climate change on Mediterranean vegetation

During the past century, annual mean temperature has increased by 0.75°C and precipitation has shown marked variation throughout the Mediterranean basin. These historical climate changes may have had significant, but presently undefined, impacts on the productivity and structure of sclerophyllous shrubland, an important vegetation type in the region. We used a vegetation model for this functional type to examine climate change impacts, and their interaction with the concurrent historical rise in atmospheric CO₂. Using only climate and soil texture as data inputs, model predictions showed good agreement with observations of seasonal and regional variation in leaf and canopy physiology, net primary productivity (NPP), leaf area index (LAI) and soil water. Model simulations for shrubland sites indicated that potential NPP has risen by 25% and LAI by 7% during the past century, although the absolute increase in LAI was small. Sensitivity analysis suggested that the increase in atmospheric CO₂ since 1900 was the primary cause of these changes, and that simulated climate change alone had negative impacts on both NPP and LAI. Effects of rising CO₂ were mediated by significant increases in the efficiency of water‐use in NPP throughout the region, as a consequence of the direct effect of CO₂ on leaf gas exchange. This increase in efficiency compensated for limitation of NPP by drought, except in areas where drought was most severe. However, while water was used more efficiently, total canopy water loss rose slightly or remained unaffected in model simulations, because increases in LAI with CO₂ counteracted the effects of reduced stomatal conductance on transpiration. Model simulations for the Mediterranean region indicate that the recent rise in atmospheric CO₂ may already have had significant impacts on productivity, structure and water relations of sclerophyllous shrub vegetation, which tended to offset the detrimental effects of climate change in the region.     

Contrasting Climatic Controls on the Estimated Productivity of Global Terrestrial Biomes

Net primary productivity (NPP) represents the greatest annual carbon flux from the atmosphere to the biosphere, is an important component of seasonal fluctuations in atmospheric CO₂ concentrations, and is the most critical biotic component of the global carbon cycle. NPP measures products of major economic and social importance, such as crop yield and forest production. Given that global NPP can not be measured directly, model simulations must provide understanding of its global spatial and temporal dynamics. In this study, we used the biogeochemical model BIOME-BGC to simulate global terrestrial NPP and assessed relative importance of climatic controls (temperature, water availability, and radiation) in limiting NPP in the array of climatic combinations found globally. The degree of limitation on NPP by climatic controls was defined by using an empirical membership function. Results showed that temperature or water availability limited NPP over larger land areas (31% and 52%, respectively) than did radiation limitation (5%). Climatic controls appeared to be important in limiting productivity in most vegetation biomes, except for evergreen broadleaf forests. Nevertheless, there were areas of the globe (12%) where none of the climatic factors appeared to limit NPP. Our research has suggested that other environmental controls, such as nutrient availability or biological constraints, should then be considered. The wide distribution of NPP between zero and the upper boundary values in the correlation plots indicated that multivariate environmental balances, not single limiting factors, controlled biospheric productivity. Received 27 August 1997; accepted 19 November 1997.     

我国西南喀斯特地区2001—2018年植被净初级生产力时空演变

植被净初级生产力（Net primary productivity,NPP）是陆地生态系统碳循环的重要指标,定量评价NPP的变化规律是碳循环机理的主要研究内容之一。以我国西南地区为研究区域,基于土地覆盖和NPP产品分析了2001-2018年西南地区NPP的时空变化特征,利用土地转移矩阵和统计分析方法,定量描述了土地覆盖类型变化导致的NPP变化量,对NPP变化的主要原因进行分析。结果表明：（1）2001-2018年,西南地区NPP均值呈波动上升趋势。（2） NPP变化趋势在空间分布上呈南高北低,NPP呈增长趋势主要集中在四川的中东部、重庆、贵州西部和云南东部;NPP呈减少趋势出现在云南、四川中西部和贵州东部。（3）森林、草地和耕地转灌丛以及灌丛转森林是对NPP变化量影响较大的土地覆盖类型转变,土地类型转变导致的NPP净增量为20.643 TgC。（4）降水与NPP相关性低,气温与NPP有一定相关性,植被叶面积指数与NPP有显著相关关系,表明气候因子对NPP的影响较小,植被生长密度对NPP有显著影响。退耕还林还草等生态工程实施,导致耕地面积减少和森林面积大量增加,是西南地区NPP上升的主导因素,因此生态工程的实施是西南地区NPP增加的重要影响因素。研究可为生态工程实施背景下NPP的变化机理研究提供参考。     

Dynamic Modelling of Northeast China Transect Responses to Global Change-A Regional Vegetation Model Driven by Remote Sensing Information

A remote sensing driven dynamic simulation model was developed for terrestrial ecosystems. The model was encoded in C language under the environment of SPAMOD, a spatial simulation tool developed under MS Windows. The model was applied to Northeast China Transect to simulate the dynamics of green and non-green biomass of 12 vegetation categories as well as soil water of 3 layers. The green biomass was converted to normalized difference vegetation index (NDVI) of AVHRR remote sensing, and compared with the observed NDVI from 1986 to 1990. The model was also compared with ground measurements of biomass and productivity along the transect. Ambient CO2 concentration, monthly mean air temperature and monthly precipitation were regarded as the three basic driving variables for global change study. The model also included the effects of temperature and precipitation on sunshine fracti6n, relative humidity, radiation, soil water and eventually plant growth. For each CO2 and climatic scenario, the model was run for an equilibrium solution. The results indicated that the natural vegetation of the transect was very sensitive to variation of temperature and CO2 concentration. With CO2 remained unchanged and temperature increased by 4 CE, the induced increase in evapotranspiration could reduce the average biomass and net primary productivity (NPP) over the whole transect by 32.1% and 41.9 % respectively. In contrast, a 20 % increase in precipitation alone could lead to an increase of the average biomass and NPP by 8.1% and 13.4% respectively. Under the present climatic conditions, CO2 doubling could increase the average biomass and NPP by 12.2% and 17.1% respectively. Because of compensation between the positive effects of CO2 and precipitation increase and the negative effect of temperature increase, a comprehensive interaction among CO2 doubling, a 20% increase of precipitation and a 4 ℃ increase of temperature altogether can lead to approximately a 2% reduction in the biomass and NPP of the natural vegetation over the whole transect.     

Net primary production, carbon storage and climate change in Chinese biomes

Net primary production (NPP) and leaf area index (LAI) of Chinese biomes were simulated by BIOME3 under the present climate, and their responses to climate change and doubled CO₂ under a future climatic scenario using output from Hadley Center coupled ocean‐atmosphere general circulation model with CO₂ modelled at 340 and 500 ppmv. The model estimated annual mean NPP of the biomes in China to be between 0 and 1270.7 gC m^‐2 yr^‐1 at present. The highest productivity was found in tropical seasonal and rain forests while temperate forests had an intermediate NPP, which is higher than a lower NPP of temperate savannas, grasslands and steppes. The lowest NPP occurred in desert, alpine tundra and ice/polar desert in cold or arid regions, especially on the Tibetan Plateau. The lowest monthly NPP of each biome occurred generally in February and the highest monthly NPP occurred during the summer (June to August). The annual mean NPP and LAI of most of biomes at changed climate with CO₂ at 340 and 500 ppmv (direct effects on physiology) would be greater than present. The direct effects of carbon dioxide on plant physiology result in significant increase of LAI and NPP. The carbon storage of Chinese biomes at present and changed climates was calculated by the carbon density and vegetation area method. The present estimates of carbon storage are totally 175.83 × 10¹² gC (57.57 × 10¹² gC in vegetation and 118.28 × 10¹² gC in soils). Changed climate without and with the CO₂ direct physiological effects will result in an increase of carbon storage of 5.1 and 16.33 × 10¹², gC compared to present, respectively. The interaction between elevated CO₂ and climate change plays an important role in the overall responses of NPP and carbon to climate change.     

Leaf area index and net primary productivity along subtropical to alpine gradients in the Tibetan Plateau

Aim Our aims were to quantify climatic and soil controls on net primary productivity (NPP) and leaf area index (LAI) along subtropical to alpine gradients where the vegetation remains relatively undisturbed, and investigate whether NPP and LAI converge towards threshold‐like logistic patterns associated with climatic and soil variables that would help us to verify and parameterize process models for predicting future ecosystem behaviour under global environmental change. Location Field data were collected from 22 sites along the Tibetan Alpine Vegetation Transects (TAVT) during 1999–2000. The TAVT included the altitudinal transect on the eastern slope of the Gongga Mountains in the Eastern Tibetan Plateau, with altitudes from 1900 m to 3700 m, and the longitudinal‐latitudinal transect in the Central Tibetan Plateau, of approximately 1000 km length and 40 km width. Methods LAI was measured as the product of foliage biomass multiplied by the ratio of specific leaf area. NPP in forests and shrub communities was estimated as the sum of increases in standing crops of live vegetation using recent stem growth rate and leaf lifespan. NPP in grasslands was estimated from the above‐ground maximum live biomass. We measured the soil organic carbon (C) and total and available nitrogen (N) contents and their pool sizes by conventional methods. Mean temperatures for the year, January and July and annual precipitation were estimated from available meteorological stations by interpolation or simulation. The threshold‐like logistic function was used to model the relationships of LAI and NPP with climatic and soil variables. Results Geographically, NPP and LAI both significantly decreased with increasing latitude (P < 0.02), but increased with increasing longitude (P < 0.01). Altitudinal trends in NPP and LAI showed different patterns. NPP generally decreased with increasing altitude in a linear relationship (r² = 0.73, P < 0.001), whereas LAI showed a negative quadratic relationship with altitude (r² = 0.58, P < 0.001). Temperature and precipitation, singly or in combination, explained 60–68% of the NPP variation with logistic relationships, while the soil organic C and total N variables explained only 21–46% of the variation with simple linear regressions of log‐transformed data. LAI showed significant logistic relationships with both climatic and soil variables, but the data from alpine spruce‐fir sites diverged greatly from the modelled patterns associated with temperature and precipitation. Soil organic C storage had the strongest correlation with LAI (r² = 0.68, P < 0.001). Main conclusions In response to climatic gradients along the TAVT, LAI and NPP across diverse vegetation types converged towards threshold‐like logistic patterns consistent with the general distribution patterns of live biomass both above‐ground and below‐ground found in our earlier studies. Our analysis further revealed that climatic factors strongly limited the NPP variations along the TAVT because the precipitation gradient characterized not only the vegetation distribution but also the soil N conditions of the natural ecosystems. LAI generally increased with increasing precipitation and was well correlated with soil organic C and total N variables. The interaction between LAI growth and soil N availability would appear to have important implications for ecosystem structure and function of alpine spruce‐fir forests. Convergence towards logistic patterns in dry matter production of plants in the TAVT suggests that alpine plant growth would increase in a nonlinear response to global warming.     

Net primary and ecosystem production and carbon stocks of terrestrial ecosystems and their responses to climate change

Evaluating the role of terrestrial ecosystems in the global carbon cycle requires a detailed understanding of carbon exchange between vegetation, soil, and the atmosphere. Global climatic change may modify the net carbon balance of terrestrial ecosystems, causing feedbacks on atmospheric CO₂ and climate. We describe a model for investigating terrestrial carbon exchange and its response to climatic variation based on the processes of plant photosynthesis, carbon allocation, litter production, and soil organic carbon decomposition. The model is used to produce geographical patterns of net primary production (NPP), carbon stocks in vegetation and soils, and the seasonal variations in net ecosystem production (NEP) under both contemporary and future climates. For contemporary climate, the estimated global NPP is 57.0 Gt C y^–1, carbon stocks in vegetation and soils are 640 Gt C and 1358 Gt C, respectively, and NEP varies from –0.5 Gt C in October to 1.6 Gt C in July. For a doubled atmospheric CO₂ concentration and the corresponding climate, we predict that global NPP will rise to 69.6 Gt C y^–1, carbon stocks in vegetation and soils will increase by, respectively, 133 Gt C and 160 Gt C, and the seasonal amplitude of NEP will increase by 76%. A doubling of atmospheric CO₂ without climate change may enhance NPP by 25% and result in a substantial increase in carbon stocks in vegetation and soils. Climate change without CO₂ elevation will reduce the global NPP and soil carbon stocks, but leads to an increase in vegetation carbon because of a forest extension and NPP enhancement in the north. By combining the effects of CO₂ doubling, climate change, and the consequent redistribution of vegetation, we predict a strong enhancement in NPP and carbon stocks of terrestrial ecosystems. This study simulates the possible variation in the carbon exchange at equilibrium state. We anticipate to investigate the dynamic responses in the carbon exchange to atmospheric CO₂ elevation and climate change in the past and future.     

Modeling the effects of Hurricane Hugo on spatial and temporal variation in primary productivity and soil carbon and nitrogen in the Luquillo Experimental Forest, Puerto Rico

Hurricanes account for much of the spatial and temporal variation in forest productivity and soil organic matter pools in many forest ecosystems. In this study, we used an ecosystem level model, TOPOECO, to simulate the effects of Hurricane Hugo (18 September 1989) on spatial and temporal patterns of gross primary productivity (GPP), net primary productivity (NPP), soil organic carbon (SOC) and nitrogen over the entire Luquillo Experimental Forest (LEF), Puerto Rico, a tropical rainforest. Our simulation results indicated that simulated annual GPP increased by an average of 30% five years after Hugo in the Tabonuco forest at low elevations where there was a fast recovery of the canopy, whereas simulated GPP decreased by an average of 20% in the Palm and Dwarf forests at high elevations as a result of the slow recovery of the canopy. Simulated annual NPP in the Palm and Dwarf forests also did not recover to pre-Hugo levels within 5 years. Simulated storages of SOC, CO₂ emission from decomposition of SOC and total soil nitrogen increased slightly but N mineralization rate increased significantly in all four vegetation types due to the massive input of plant materials from Hugo at low elevations and the slow decomposition at high elevations.     

Potentially complex biosphere responses to transient global warming

Feedback interactions between terrestrial vegetation and climate could alter predictions of the responses of both systems to a doubling of atmospheric CO₂. Most previous analyses of biosphere responses to global warming have used output from equilibrium simulations of current and future climate, as compared to more recently available transient GCM simulations. We compared the vegetation responses to these two different classes of GCM simulation (equilibrium and transient) using an equilibrium vegetation distribution model, MAPSS. Average climatologies were extracted from the transient GCM simulations for current and doubled (2×) CO₂ concentrations (taken to be 2070–2099) for use by the equilibrium vegetation model. However, the 2 × CO₂ climates extracted from the transient GCM simulations were not in equilibrium, having attained only about 65% of their eventual 2 × CO₂ equilibrium temperature change. Most of the differences in global vegetation response appeared to be related to a very different simulated change in the pole to tropic temperature gradient. Also, the transient scenarios produced much larger increases of precipitation in temperate latitudes, commensurate with a minimum in the latitudinal temperature change. Thus, the (equilibrium) global vegetation response, under the transient scenarios, tends more to a greening than a decline in vegetation density, as often previously simulated. It may be that much of the world could become greener during the early phases of global warming, only to reverse in later, more equilibrial stages. However, whether or not the world's vegetation experiences large drought-induced declines or perhaps large vegetation expansions in early stages could be determined by the degree to which elevated CO₂ will actually benefit natural vegetation, an issue still under debate. There may occur oscillations, perhaps on long timescales, between greener and drier phases, due to different frequency responses of the coupled ocean–atmosphere–biosphere interactions. Such oscillations would likely, of themselves, impart further reverberations to the coupled Earth System.     

青藏高原两种植被类型净初级生产力与气候因素的关系及周转值分析

基于2008—2016年青海海北站9年净初级生产力及气候因子监测数据,分析了青藏高原高寒小嵩草草甸和高寒金露梅灌丛两种植被净初级生产力年际动态,并探讨了气候因子对其影响及其不同土层深度根系周转值特征。结果表明:(1)年际尺度上,小嵩草草甸地上净初级生产力表现为显著增加趋势,增幅为7.02 g m~(-2) a~(-1),而金露梅灌丛地上净初级生产力相对较为稳定;对于其地下净初级生产力和总生产力,小嵩草草甸和金露梅灌丛均表现为增加趋势(P0.05),9年间小嵩草草甸地上、地下和总净初级生产力平均值分别为(217.55±9.95)、(1882.75±161.33) g m~(-2) a~(-1)和(2100.30±163.38) g m~(-2) a~(-1),金露梅灌丛地上、地下和总净初级生产力9年间平均值分别为(256.27±11.4)、(1614.31±173.03) g m~(-2) a~(-1)和(1870.58±177.93) g m~(-2) a~(-1)。(2)不同植被类型地上净初级生产力对气候因素响应不同,金露梅灌丛地上净初级生产力主要受温度影响,而温度对小嵩草草甸地上净初级生产力无显著影响。此外,降水不是限制高寒生态系统草地地上净初级生产力主要因子,相比于降水影响,高寒生态系统地上净初级生产力更受温度调控。(3)年均温和年降水对金露梅灌丛和小嵩草草甸地下净初级生产力均无显著影响(P0.05),表明高寒生态系统,其地下生产力受外界气候条件变化影响微弱,是一个稳定的碳库。(4)两种植被类型其根系周转值均随着土壤深度的增加呈逐渐增加趋势,且高寒灌丛根系周转值明显高于高寒草甸根系周转值。研究表明,在全球气候变暖背景下将会增加金露梅灌丛地上净初级生产力,而对小嵩草草甸地上净初级生产力无显著影响。     

Converging Climate Sensitivities of European Forests Between Observed Radial Tree Growth and Vegetation Models

The impacts of climate variability and trends on European forests are unevenly distributed across different bioclimatic zones and species. Extreme climate events are also becoming more frequent and it is unknown how they will affect feedbacks of CO₂ between forest ecosystems and the atmosphere. An improved understanding of species differences at the regional scale of the response of forest productivity to climate variation and extremes is thus important for forecasting forest dynamics. In this study, we evaluate the climate sensitivity of aboveground net primary production (NPP) simulated by two dynamic global vegetation models (DGVM; ORCHIDEE and LPJ-wsl) against tree ring width (TRW) observations from about 1000 sites distributed across Europe. In both the model simulations and the TRW observations, forests in northern Europe and the Alps respond positively to warmer spring and summer temperature, and their overall temperature sensitivity is larger than that of the soil-moisture-limited forests in central Europe and Mediterranean regions. Compared with TRW observations, simulated NPP from ORCHIDEE and LPJ-wsl appear to be overly-sensitive to climatic factors. Our results indicate that the models lack biological processes that control time lags, such as carbohydrate storage and remobilization, that delay the effects of radial growth dynamics to climate. Our study highlights the need for re-evaluating the physiological controls on the climate sensitivity of NPP simulated by DGVMs. In particular, DGVMs could be further enhanced by a more detailed representation of carbon reserves and allocation that control year-to-year variation in plant growth.     

Circumpolar arctic tundra biomass and productivity dynamics in response to projected climate change and herbivory

Satellite remote sensing data have indicated a general ‘greening’ trend in the arctic tundra biome. However, the observed changes based on remote sensing are the result of multiple environmental drivers, and the effects of individual controls such as warming, herbivory, and other disturbances on changes in vegetation biomass, community structure, and ecosystem function remain unclear. We apply ArcVeg, an arctic tundra vegetation dynamics model, to estimate potential changes in vegetation biomass and net primary production (NPP) at the plant community and functional type levels. ArcVeg is driven by soil nitrogen output from the Terrestrial Ecosystem Model, existing densities of Rangifer populations, and projected summer temperature changes by the NCAR CCSM4.0 general circulation model across the Arctic. We quantified the changes in aboveground biomass and NPP resulting from (i) observed herbivory only; (ii) projected climate change only; and (iii) coupled effects of projected climate change and herbivory. We evaluated model outputs of the absolute and relative differences in biomass and NPP by country, bioclimate subzone, and floristic province. Estimated potential biomass increases resulting from temperature increase only are approximately 5% greater than the biomass modeled due to coupled warming and herbivory. Such potential increases are greater in areas currently occupied by large or dense Rangifer herds such as the Nenets‐occupied regions in Russia (27% greater vegetation increase without herbivores). In addition, herbivory modulates shifts in plant community structure caused by warming. Plant functional types such as shrubs and mosses were affected to a greater degree than other functional types by either warming or herbivory or coupled effects of the two.     

Impacts of tropospheric ozone and climate change on net primary productivity and net carbon exchange of China's forest ecosystems

Aim We investigated how ozone pollution and climate change/variability have interactively affected net primary productivity (NPP) and net carbon exchange (NCE) across China's forest ecosystem in the past half century. Location Continental China. Methods Using the dynamic land ecosystem model (DLEM) in conjunction with 10‐km‐resolution gridded historical data sets (tropospheric O₃ concentrations, climate variability/change, and other environmental factors such as land‐cover/land‐use change (LCLUC), increasing CO₂ and nitrogen deposition), we conducted nine simulation experiments to: (1) investigate the temporo‐spatial patterns of NPP and NCE in China's forest ecosystems from 1961–2005; and (2) quantify the effects of tropospheric O₃ pollution alone or in combination with climate variability and other environmental stresses on forests' NPP and NCE. Results China's forests acted as a carbon sink during 1961–2005 as a result of the combined effects of O₃, climate, CO₂, nitrogen deposition and LCLUC. However, simulated results indicated that elevated O₃ caused a 7.7% decrease in national carbon storage, with O₃‐induced reductions in NCE (Pg C year^?1) ranging from 0.4–43.1% among different forest types. Sensitivity experiments showed that climate change was the dominant factor in controlling changes in temporo‐spatial patterns of annual NPP. The combined negative effects of O₃ pollution and climate change on NPP and NCE could be largely offset by the positive fertilization effects of nitrogen deposition and CO₂. Main conclusions In the future, tropospheric O₃ should be taken into account in order to fully understand the variations of carbon sequestration capacity of forests and assess the vulnerability of forest ecosystems to climate change and air pollution. Reducing air pollution in China is likely to increase the resilience of forests to climate change. This paper offers the first estimate of how prevention of air pollution can help to increase forest productivity and carbon sequestration in China's forested ecosystems.     

Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models

The possible responses of ecosystem processes to rising atmospheric CO₂ concentration and climate change are illustrated using six dynamic global vegetation models that explicitly represent the interactions of ecosystem carbon and water exchanges with vegetation dynamics. The models are driven by the IPCC IS92a scenario of rising CO₂ ( Wigley et al. 1991 ), and by climate changes resulting from effective CO₂ concentrations corresponding to IS92a, simulated by the coupled ocean atmosphere model HadCM2‐SUL. Simulations with changing CO₂ alone show a widely distributed terrestrial carbon sink of 1.4–3.8 Pg C y^?1 during the 1990s, rising to 3.7–8.6 Pg C y^?1 a century later. Simulations including climate change show a reduced sink both today (0.6–3.0 Pg C y^?1) and a century later (0.3–6.6 Pg C y^?1) as a result of the impacts of climate change on NEP of tropical and southern hemisphere ecosystems. In all models, the rate of increase of NEP begins to level off around 2030 as a consequence of the ‘diminishing return’ of physiological CO₂ effects at high CO₂ concentrations. Four out of the six models show a further, climate‐induced decline in NEP resulting from increased heterotrophic respiration and declining tropical NPP after 2050. Changes in vegetation structure influence the magnitude and spatial pattern of the carbon sink and, in combination with changing climate, also freshwater availability (runoff). It is shown that these changes, once set in motion, would continue to evolve for at least a century even if atmospheric CO₂ concentration and climate could be instantaneously stabilized. The results should be considered illustrative in the sense that the choice of CO₂ concentration scenario was arbitrary and only one climate model scenario was used. However, the results serve to indicate a range of possible biospheric responses to CO₂ and climate change. They reveal major uncertainties about the response of NEP to climate change resulting, primarily, from differences in the way that modelled global NPP responds to a changing climate. The simulations illustrate, however, that the magnitude of possible biospheric influences on the carbon balance requires that this factor is taken into account for future scenarios of atmospheric CO₂ and climate change.     

Assessing forest growth across southwestern Oregon under a range of current and future global change scenarios using a process model, 3‐PG

With improvements in mapping regional distributions of vegetation using satellite‐derived information, there is an increasing interest in the assessment of current limitations on forest growth and in making projections of how productivity may be altered in response to changing climatic conditions and management policies. We utilised a simplified physiologically based process model (3‐PG) across a 54 000 km² mountainous region of southwestern Oregon, USA, to evaluate the degree to which maximum periodic mean annual increment (PAI) of forests could be predicted at a set of 448 forest inventory plots. The survey data were pooled into six broad forest types (coastal rain forest, interior coast range forest, mixed conifer, dry‐site Douglas‐fir, subalpine forest, and pine forest) and compared to the 3‐PG predictions at a spatial resolution of 1 km². We found good agreement (r² = 0.84) between mean PAI values of forest productivity for the six forest types with those obtained from field surveys. With confidence at this broader level of integration, we then ran model simulations to evaluate the constraints imposed by (i) soil fertility under current climatic conditions, (ii) the effect of doubling monthly precipitation across the region, and (iii) a widely used climatic change scenario that involves modifications in monthly mean temperatures and precipitation, as well as a doubling in atmospheric CO₂ concentrations. These analyses showed that optimum soil fertility would more than double growth, with the greatest response in the subalpine type and the least increase in the coastal rain forests. Doubling the precipitation increased productivity in the pine type (> 50%) with reduced responses elsewhere. The climate change scenario with doubled atmospheric CO₂ increased growth by 50% on average across all forest types, primarily as a result of a projected 33% increase in photosynthetic capacity. This modelling exercise indicates that, at a regional scale, a general relationship exists between simulated maximum leaf area index and maximum aboveground growth, supporting the contention that satellite‐derived estimates of leaf area index may be good measures of the potential productivity of temperate evergreen forests.