长江口北支涌潮的形成条件及其初生地探讨

根据 2 0 0 1年 4月青龙港出现涌潮时的实测流速和水深 ,采用水跃原理 ,简明地揭示了涨潮流速大于潮波传速是北支涌潮的成因。通过影响流速和波速的因素分析 ,并经实例计算认为 :北支的喇叭形河势和水下沙坎是涌潮形成的必要条件 ;青龙港一潮的进潮量达到 1 5亿m3,或北支口门一潮进潮量达到 18亿m3是涌潮形成的充分条件。进而据沿程水深和潮汐等有关资料 ,经对比、试算 ,建立了沿程变化的进潮量、潮差等计算公式 ,并计算得到 :在口门最大进潮量 2 0 7亿m3的条件下 ,也只有当潮波上溯到距离口门约 5 0km的灵甸港时 ,才出现流速大于波速 ,初生涌潮。由此表明 。

Quantifying the impacts of fire aerosols on global terrestrial ecosystem productivity with the fully-coupled Earth system model CESM

Fire is a global phenomenon and a major source of aerosols from the terrestrial biosphere to the atmosphere.Most previous studies quantified the effect of fire aerosols on climate and atmospheric circulation,or on the regional and site-scale terrestrial ecosystem productivity.So far,only one work has quantified their global impacts on terrestrial ecosystem productivity based on offline simulations,which,however,did not consider the impacts of aerosol–cloud interactions and aerosol–climate feedbacks.This study quantitatively assesses the influence of fire aerosols on the global annual gross primary productivity(GPP)of terrestrial ecosystems using simulations with the fully coupled global Earth system model CESM1.2.Results show that fire aerosols generally decrease GPP in vegetated areas,with a global total of−1.6 Pg C yr^−1,mainly because fire aerosols cool and dry the land surface and weaken the direct photosynthetically active radiation(PAR).The exception to this is the Amazon region,which is mainly due to a fire-aerosol-induced wetter land surface and increased diffuse PAR.This study emphasizes the importance of the influence of fire aerosols on climate in quantifying global-scale fire aerosols’impacts on terrestrial ecosystem productivity.

Contributions of climate change, land use change and CO2 to changes in the gross primary productivity of the Tibetan Plateau

The ecosystems on the Tibetan Plateau(TP) are highly vulnerable to climate change, rising CO2 concentration, and land-use and land-cover change(LULCC), but their contributions to changes in the gross primary productivity(GPP) of the TP are not clearly understood. In this study, the role of these three factors on the interannual variations(IAVs) and trends of the TP’s GPP were investigated using 12 terrestrial biosphere models. The ensemble simulations showed that climate change can explain most of the changes in the GPP, while the direct effect of LULCC and rising CO2(mainly fertilization effect) contributed 10% and-14% to the mean GPP values, 37% and -20% to the IAV, and 52% and -24% to the GPP’s trend, respectively. The LULCC showed higher contributions to the significant positive trend in the annual GPP of the TP. However, the results from different model simulations showed that considerable uncertainties were associated with the effects of LULCC on the GPP of the TP.

Improving Simulation of the Terrestrial Carbon Cycle of China in Version 4.5 of the Community Land Model Using a Revised V_(cmax) Scheme

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

River Flow Control on the Phytoplankton Dynamics of Chesapeake Bay

Recent observations support an emerging paradigm that climate variability dominates nutrient enrichment in costal eco-systems, which can explain seasonal and inter-annual variability of phytoplankton community composition, biomass (Chl-a), and primary production (PP). In this paper, we combined observation and modeling to investigate the regulation of phytoplankton dynamics in Chesapeake Bay. The year we chose is 1996 that has high river runoff and is usually called a 'wet year'. A 3-D physical-biogeochemical model based on ROMS was developed to simulate the seasonal cycle and the regional distributions of phytoplankton biomass and primary production in Chesapeake Bay. Based on the model results, NO3 presents a strong contrast to the river nitrate load during spring and the highest concentration in the bay reaches around 80 mmol Nm-3 . Compared with the normal year, phytoplankton bloom in spring of 1996 appears in lower latitudes with a higher concentration. Quantitative comparison between the modeled and observed seasonal averaged dissolved inorganic nitrogen concentrations shows that the model produces reliable results. The correlation coefficient r2 for all quantities exceeds 0.95, and the skill parameter for the four seasons is all above 0.95.

Impacts of Climate Change on Net Primary Productivity in Arid and Semiarid Regions of China

In recent years, with the constant change in the global climate, the effect of climate factors on net primary productivity(NPP) has become a hot research topic. However, two opposing views have been presented in this research area: global NPP increases with global warming, and global NPP decreases with global warming. The main reasons for these two opposite results are the tremendous differences among seasonal and annual climate variables, and the growth of plants in accordance with these climate variables. Therefore, it will fail to fully clarify the relation between vegetation growth and climate changes by research that relies solely on annual data. With seasonal climate variables, we may clarify the relation between vegetation growth and climate changes more accurately. Our research examined the arid and semiarid areas in China(ASAC), which account for one quarter of the total area of China. The ecological environment of these areas is fragile and easily affected by human activities. We analyzed the influence of climate changes, especially the changes in seasonal climate variables, on NPP, with Climatic Research Unit(CRU) climatic data and Moderate Resolution Imaging Spectroradiometer(MODIS) satellite remote data, for the years 2000–2010. The results indicate that: for annual climatic data, the percentage of the ASAC in which NPP is positively correlated with temperature is 66.11%, and 91.47% of the ASAC demonstrates a positive correlation between NPP and precipitation. Precipitation is more positively correlated with NPP than temperature in the ASAC. For seasonal climatic data, the correlation between NPP and spring temperature shows significant regional differences. Positive correlation areas are concentrated in the eastern portion of the ASAC, while the western section of the ASAC generally shows a negative correlation. However, in summer, most areas in the ASAC show a negative correlation between NPP and temperature. In autumn, precipitation is less important in the west, as opposed to the east, in which it is critically important. Temperatures in winter are a limiting factor for NPP throughout the region. The findings of this research not only underline the importance of seasonal climate variables for vegetation growth, but also suggest that the effects of seasonal climate variables on NPP should be explored further in related research in the future.

The Impacts of Permafrost Change on NPP and Implications:A Case of the Source Regions of Yangtze and Yellow Rivers

This paper studies the relationship between net primary productivity (NPP) and annual average air temperature (GT) at 0cm above ground in permafrost regions by using revised Chikugo NPP model,cubic spline interpolating functions,and non-linear regression methods.The source regions of the Yangtze and Yellow Rivers were selected as the research areas.Results illustrate that:(1) There is significant non-linear relationship between NPP and GT in various typical years;(2) The maximum value of NPP is 6.17,5.87,7.73,and 5.41 DM·t·hm-2 ·a-1 respectively,and the corresponding GT is 7.1,10.0,21.2,and 8.9 o C respectively in 1980,1990,2000 and 2007;(3) In 1980,the sensitivity of NPP to GT is higher than in 1990,2000 and 2007.This tendency shows that the NPP presents change from fluctuation to an adaptation process over time;(4) During 1980～2007,the accumulated NPP was reduced to 8.05,and the corresponding carrying capacity of theoretical livestock reduced by 11%;(5) The shape of the demonstration region of ecological compensation system,livelihood support system,and science appraisal system in the source regions of Yangtze and Yellow Rivers are an important research for increasing the adaptation capacity and balancing protection and development.

Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982–2010

Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.

A Population Morphologically Structured Model for Microscopic Growth of Filamentous Microorganism

The growth of filamentous microorganism is contributed by tip extension and branching. The microscopic growth of filamentous microorganism means the growth process from one or a few spores. In order to describe the microscopic process, a population morphologically structured model is proposed, in which three morphological compartment and their interactions were considered, and the heterogeneity of hyphal growth was included. The model was applied to describe the microscopic growth of Streptomyces tendae and Geotrichum candidum with good agreement. From model prediction, it is concluded that if the number of hyphae is large enough (macroscopic growth), the specific growth rate of filamentous microorganism and the ratio of morphological forms in hyphae will become constant.

Patterns and mechanisms of belowground carbon responses to changes in precipitation

It is well known that aboveground productivity usually increases with precipitation.However,how belowground carbon(C)processes respond to changes in precipitation remains elusive,although belowground net primary productivity(BNPP)represents more than one-half of NPP and soil stores the largest terrestrial C in the biosphere.This paper reviews the patterns of belowground C processes(BNPP and soil C)in response to changes in precipitation from transect studies,manipulative experiments,modeling and data integration and synthesis.The results suggest the possible existence of nonlinear patterns of BNPP and soil C in response to changes in precipitation,which is largely different from linear response for aboveground productivity.C allocation,root turnover time and species composition may be three key processes underlying mechanisms of the nonlinear responses to changes in precipitation for belowground C processes.In addition,microbial community structure and long-term ecosystem processes(e.g.mineral assemblage,soil texture,aggregate stability)may also affect patterns of belowground C processes in response to changes in precipitation.At last,we discuss implications and future perspectives for potential nonlinear responses of belowground C processes to changes in precipitation.

Cropland Dynamics and Their Influence on the Productivity in Northern Shaanxi,China,for the Past 20 Years:Based on Remotely Sensed Data

In this paper,we mainly focused our research on northern Shaanxi district,which is a pilot area of the Grain for Green Project.We compared the spatial distribution patterns of croplands and their productivity for the past 20 years（from the end of the 1980 s to 2010）.Cropland dynamics for the past 20 years were interpreted from medium- and high-resolution remote sensing images（Landsat TM/ETM＋）.In addition,using the GLO-PEM and AGRO-VPM models with a medium resolution and long time series remote sensing dataset（AVHRR/MODIS）,net primary productivity（NPP） and its relationship with cropland were estimated.Finally,the effect of cropland change on productivity was analyzed.The results show that during the first decade of the research period,cropland area and productivity in northern Shaanxi experienced a small boost,while in the latter decade,both cropland area and NPP were significantly reduced.The main cause of the increase in cropland was the reclamation of large area of grassland and unutilized land to meet the food demands of the local population as well as to compensate for the occupation of urban constructions.While the main cause of the decrease in cropland was the implementation of the Grain for Green Project.In addition,urbanization was also a key factor.Overall,during the past 20 years,the total area of cropland in northern Shaanxi decreased by 42.56%,and cropland NPP dropped by 41.90%.This study is of great importance for the assessment of regional cropland security,food security and scientific planning of regional land use.

Responses of Grassland Net Primary Productivity to Environmental Variables in Northern China

Various environmental factors affect net primary productivity （NPP） of grassland ecosystem. Extensive reports on the effects of environmental variables on NPP can be found in literature. However, the agreement on the relative importance of various factors in shaping the spatial pattern of grassland NPP has not yet been reached. Here a grassland in situ NPP database comprising 602 samples in northern China for 1980-1999 was developed based on a literature review of published biomass and forage yield field measurements. Correlation analyses and dominance analysis were used to quantify the separate and combined effects of environmental variables （climate topography and soil） on spatial variation in NPP separately. Grassland NPP ranged from 4.76 g C m-2a-1 to 975.94gCm-2a-1, showing significant variations in space. NPP increased with annual precipitation and declined with annual mean temperature significantly. Specifically, precipitation had the greatest impact on deserts, followed by steppes and meadows. Grassland NPP decreased with increasing altitude because of water limitation, and positively correlated with slope, but weakly correlated with aspect. Soil quality showed positive effects on NPP. Annual precipitation was the dominant factor affecting the spatial variability of net primary productivity, followed by elevation.

Climatic Changes Dominant Interannual Trend in Net Primary Productivity of Alpine Vulnerable Ecosystems

The Three-River Headwaters(TRH), which is the source area of Yangtze River, Yellow River and Lancang River, is vulnerable and sensitive, and its alpine ecosystem is considered an important barrier for China’s ecological security. Understanding the impact of climate changes is essential for determining suitable measures for ecological environmental protection and restoration against the background of global climatic changes. However, different explanations of the interannual trends in complex alpine ecosystems have been proposed due to limited availability of reliable data and the uncertainty of the model itself. In this study, the remote sensing-process coupled model(GLOPEM-CEVSA) was used to estimate the net primary productivity(NPP) of vegetation in the TRH region from 2000 to 2012. The estimated NPP significantly and linearly correlated with the above-ground biomass sampled in the field(the multiple correlative coefficient R2 = 0.45, significant level P < 0.01) and showed better performance than the MODIS productivity product, i.e. MOD17 A3,(R2 = 0.21). The climate of TRH became warmer and wetter during 1990-2012, and the years 2000 to 2012 were warmer and wetter than the years1990–2000. Responding to the warmer and wetter climate, the NPP had an increasing trend of 13.7 g m^–2(10 yr)^–1 with a statistical confidence of 86%(P = 0.14). Among the three basins, the NPP of the Yellow River basin increased at the fastest rate of 17.44 g m^–2(10 yr)^–1(P = 0.158), followed by the Yangtze River basin, and the Lancang River, which was the slowest with a rate of 12.2 g m^–2(10 yr)^–1 and a statistical confidence level of only 67%. A multivariate linear regression with temperature and precipitation as the independent variables and NPP as the dependent variable at the pixel level was used to analyze the impacts of climatic changes on the trend of NPP. Both temperature and precipitation can explain the interannual variability of 83% in grassland NPP in the whole region, and can explain high, medium and low coverage of 78%, 84% and 83%, respectively, for grassland in the whole region. The results indicate that climate changes play a dominant role in the interannual trend of vegetation productivity in the alpine ecosystems on Qinghai-Tibetan Plateau. This has important implications for the formulation of ecological protection and restoration policies for vulnerable ecosystems against the background of global climate changes.

Effect of Land Use and Land Cover Change on the Changes in Net Primary Productivity in Karst Areas of Southwest China:A Case Study of Huanjiang Maonan Autonomous County

Karst areas in southwest China have experienced significant land cover and land use change(LUCC)due to utilization for human activity and a comprehensive rocky desertification control project(RDCP)since 2008.It is important to quantify the effect of LUCC on ecosystem productivity in this region for assessing the overall benefit of this ecological restoration project.In this study,we used using MODIS land cover and NPP products to investigate the relative contribution of LUCC to the change in net primary productivity(NPP)during 2008–2013 in Huanjiang County,one of first one hundred pilot counties to implement RDCP.Our results show that NPP increased in 95.53%of the county,and the average growth of NPP in non-rocky desertification area was higher than in rocky desertification or potential rocky desertification areas.LUCC has an important contribution(25.23%)to the NPP increase in the county,especially in the LUCC area(70.97%),which increased the average NPP by 3.9%and 10.5%,respectively.Across the six RDCP regions in the county,the average increase in NPP for the vegetation restoration measure of governed karst area is significantly greater than in the ungoverned karst area,and the positive change in NPP increased with the increasing implementation area of the vegetation restoration measure.

The Effect of Higher Warming on Vegetation Indices and Biomass Production is Dampened by Greater Drying in an Alpine Meadow on the Northern Tibetan Plateau

In order to understand whether or not the response of vegetation indices and biomass production to warming varies with warming magnitude,an experiment of field warming at two magnitudes was conducted in an alpine meadow on the northern Tibetan Plateau beginning in late June,2013.The normalized difference vegetation index（NDVI）,green normalized difference vegetation index（GNDVI） and soil adjusted vegetation index（SAVI） data were obtained using a Tetracam Agricultural Digital Camera in 2013–2014.The gross primary production（GPP） and aboveground plant biomass（AGB） were modeled using the surface measured NDVI and climatic data during the growing seasons（i.e.June–September） in 2013–2014.Both low and high warming significantly increased air temperature by 1.54 and 4.00°C,respectively,and significantly increased vapor pressure deficit by 0.13 and 0.31 kP a,respectively,in 2013-2014.There were no significant differences of GNDVI,AGB and ANPP among the three warming treatments.The high warming significantly reduced average NDVI by 23.3%（-0.06）,while the low warming did not affect average NDVI.The low and high warming significantly decreased average SAVI by 19.0%（-0.04） and 27.4%（-0.05）,respectively,and average GPP by 24.2%（i.e.0.21 g C m^（-2） d^（-1）） and 44.0%（i.e.0.39 g C m^（–2） d^（-1））,respectively.However,the differences of the average NDVI,SAVI,and GPP between low and high warming were negligible.Our findings suggest that a greater drying may dampen the effect of a higher warming on vegetation indices and biomass production in alpine meadow on the northern Tibetan Plateau.

Greater soil microbial biomass loss at low frequency of N addition in an Inner Mongolia grassland

Soil microbial biomass is critical for biogeochemical cycling and serves as precursor for carbon(C)sequestration.The anthropogenic nitrogen(N)input has profoundly changed the pool of soil microbial biomass.However,traditional N deposition simulation experiments have been exclusively conducted through infrequent N addition,which may have caused biased effects on soil microbial biomass compared with those under the natural and continuous N deposition.Convincing data are still scarce about how the different N addition frequencies affect soil microbial biomass.By independently manipulating the frequencies(2 times vs.12 times N addition yr^(–1))and the rates(0–50 g N m^(−2) yr^(−1))of N addition,our study aimed to examine the response of soil microbial biomass C(MBC)to different N addition frequencies with increasing N addition rates.Soil MBC gradually decreased with increasing N addition rates under both N addition frequencies,while the soil MBC decreased more at low frequency of N addition,suggesting that traditional studies have possibly overestimated the effects of N deposition on soil microbial biomass.The greater soil microbial biomass loss with low N frequency resulted from the intensifed soil acidifcation,higher soil inorganic N,stronger soil C and N imbalance,less net primary production allocated to belowground and lower fungi to bacteria ratio.To reliably predict the effects of atmospheric N deposition on soil microbial functioning and C cycling of grassland ecosystems in future studies,it is necessary to employ both the dosage and the frequency of N addition.

Quantitative Assessment of the Effects of Climate Change and Human Activities on Grassland NPP in Altay Prefecture

Grassland degradation in Altay Prefecture is of considerable concern as it is a threat that hinders the sustainable development of the local economy and the stable operation of the livestock industry.Quantitative assessment of the relative contributions of climate change and human activities,which are considered as the dominant triggers of grassland degradation,to grassland variation is crucial for understanding the grassland degradation mechanism and mitigating the degraded grassland in Altay Prefecture.In this paper,the Carnegie-Ames-Stanford Approach model and the Thornthwaite memorial model were adopted to simulate the actual net primary productivity(NPP_(A))and potential net primary productivity(NPP_(P))in the Altay Prefecture from 2000 to 2019.Meanwhile,the difference between potential NPP and actual NPP was employed to reflect the effects of human activities(NPP_(H))on the grassland.On this basis,we validated the viability of the simulated NPP using the Pearson correlation coefficient,investigated the spatiotemporal variability of grassland productivity,and established comprehensive scenarios to quantitatively assess the relative roles of climate change and human activities on grassland in Altay prefecture.The results indicate three main points.(1)The simulated NPP_(A) was highly consistent with the MOD17 A3 dataset in spatial distribution.(2)Regions with an increased NPP_(A) accounted for 70.53% of the total grassland,whereas 29.47% of the total grassland area experienced a decrease.At the temporal scale,the NPP_(A) presented a slightly increasing trend(0.83 g C m^(-2) yr^(-1))over the study period,while the trends of NPP_(P) and NPP_(H) were reduced(-1.31 and-2.15 g C m^(-2) yr^(-1)).(3)Compared with climate change,human activities played a key role in the process of grassland restoration,as 66.98% of restored grassland resulted from it.In contrast,inter-annual climate change is the primary cause of grassland degradation,as it influenced 55.70% of degraded grassland.These results could shed light on the mechanisms of grassland variation caused by climate change and human activities,and they can be applied to further develop efficient measures to combat desertification in Altay Prefecture.

Are regional precipitation-productivity relationships robust to decadal-scale dry period?

Precipitation(PPT)is the primary climatic determinant of plant growth and aboveground net primary productivity(ANPP)for many of the world’s major terrestrial ecosystems.Thus,relationships between PPT and productivity can provide insight into how changes in climate may alter ecosystem functions globally.Spatial PPT–ANPP relationships for grasslands are found remarkably similar around the world,but whether and how they change during periods of extended climatic anomalies remain unknown.Here,we quantifed how regional-scale PPTANPP relationships vary between an extended wet and a dry period by taking advantage of a 35-year record of PPT and NDVI(as a surrogate for ANPP)at 1700 sites in the temperate grasslands of northern China.We found a sharp decrease in the strength of the spatial PPT–ANPP relationship during an 11-year period of below average PPT.We attributed the collapse of this relationship to asynchrony in the responses of different grassland types to this decadal period of increased aridity.Our results challenge the robustness of regional PPT–productivity if aridity in grasslands is increased globally by climate change.

Nitrogen addition amplified water effects on species composition shift and productivity increase

Aims Water and nitrogen(N)are two key resources in dryland ecosystems,but they may have complex interactive effects on the community structure and ecosystem functions.How future precipitation(rainfall vs snowfall)change will impact aboveground net primary production(ANPP)is far from clear,especially when combined with increasing N availability.Methods In this study,we investigated changes in community productivity,abundance and aboveground biomass of two dominant plant functional groups(PFGs),i.e.perennial rhizome grasses(PR)and perennial bunchgrasses(PB)under the impacts of increased precipitation(rainfall vs snowfall)combined with N addition in a semiarid temperate steppe.Important Findings Summer rainfall augmentation marginally increased community ANPP,whereas it significantly increased the abundance and aboveground biomass of PR,but not those of PB.Summer rainfall addition increased the fraction of PR biomass(fPR)while decreased that of PB(fPB).Spring snow addition had no effect on aboveground biomass of either compositional PFG although it marginally increased community ANPP.Nitrogen addition significantly increased community ANPP with greater increase in PR under summer rainfall addition,indicating strong interactive effects on community ANPP largely by enhancing PR biomass.We also found a nonlinear increase in the positive effect of nitrogen addition on productivity with the increased precipitation amount.These findings indicate an amplified impact of precipitation increase on grassland productivity under the accelerated atmospheric N deposition in the future.

Explaining variation in productivity requires intraspecific variability in plant height among communities

While recent studies have shown the importance of intraspecific trait variation in the processes of community assembly,we still know little about the contributions of intraspecific trait variability to ecosystem functions.Here,we conducted a functional group removal experiment in an alpine meadow in Qinghai-Tibetan Plateau over 4 years to investigate the relative importance of inter-and intraspecific variability in plant height for productivity.We split total variability in plant height within each of 75 manipulated communities into interspecific variability(TV_(inter))and intraspecific variability within a community(ITV_(within)).Community-weighted mean height among communities was decomposed into fixed community-weighted mean(CWM_(fixed))and intraspecific variability among communities(ITV_(among)).We constructed a series of generalized additive mixed models and piecewise structural equation modeling to determine how trait variability(i.e.TV_(inter),ITV_(within),CWM_(fixed) and ITV_(among))indirectly mediated the changes in productivity in response to functional group removal.Community productivity was not only affected directly by treatment manipulations,but also increased with both inter-and intraspecific variability(i.e.CWM_(fixed) and ITV_(among))in plant height indirectly.This suggests that both the‘selection effect’and a‘shade-avoidance syndrome’can incur higher CWM_(fixed) and ITV_(among),and may simultaneously operate to regulate productivity.Our findings provide new evidence that,besides interspecific variability,intraspecific trait variability in plant height also plays a role in maintaining net primary productivity.