西南高山亚高山区植被水分利用效率时空特征及其与气候因子的关系

水分利用效率(WUE)是深入理解生态系统水碳循环及其耦合关系的重要指标。为了揭示气候变化背景下区域尺度不同植被类型的响应和适应特征, 对中国西南高山亚高山地区2000-2014年的9种植被类型的WUE时空特征及其影响因素进行探究。该研究基于MODIS总初级生产力(GPP)、蒸散发(ET)数据和气象数据, 估算西南高山亚高山区植被WUE, 采用趋势分析及相关分析等方法, 分析了研究区植被WUE与气温、降水及海拔的关系。主要结果: (1)西南高山亚高山区2000-2014年植被WUE多年均值为0.95 g·m^-2·mm^-1, 整体呈显著增加趋势, 增速为0.011 g·m^-2·mm^-1·a^-1; 空间上WUE呈东南高西北低的分布, 85.84%区域的WUE呈增加趋势。(2)西南高山亚高山区各植被类型WUE多年均值表现为常绿针叶林>稀树草原>常绿阔叶林>有林草原>农田>落叶阔叶林>混交林>郁闭灌丛>草地; 时间上, 各植被类型WUE均呈上升趋势。(3)西南高山亚高山区89.56%区域的WUE与气温正相关, 92.54%区域的WUE与降水量负相关; 各植被类型中, 草地WUE与气温的相关性最高, 有林草原WUE与降水量的相关性最高。(4)西南高山亚高山区典型的地带性顶极植被常绿针叶林的WUE具有较强的海拔适应性及应对气候变化的能力。     

2000-2017年新疆天山植被水分利用效率时空特征及其与气候因子关系分析

水分利用效率(WUE)是衡量生态系统碳水循环耦合程度的重要指标, 估算新疆天山及南北主要绿洲的植被WUE并分析其时空变化规律, 探索其影响因素, 对该区域生态系统保护、农业水资源的合理利用与开发等方面具有重要的意义。基于MODIS遥感数据、气象数据和土地利用类型数据, 分析新疆天山近18年植被WUE时空变化特征以及与气候因子的关系。结果表明: (1) 2000-2017年新疆天山植被WUE变化范围为0.84-1.34 g·mm ^-1·m ^-2, 多年均值为1.11 g·mm ^-1·m ^-2, 整体呈减少趋势, 变化率为-0.014 1 g·mm ^-1·m ^-2·a ^-1; 空间分布具有较强的垂直地带性规律, 1 000 m以上的区域随着海拔的升高而减少。(2)植被WUE年内变化呈单峰型变化格局, 具有明显的季节性差异, 表现为: 夏季>春季>秋季>冬季。(3)相关分析和统计结果表明, 新疆天山植被WUE时空变化受到气温影响的区域占33.23%, 受降水影响的区域占8.57%, 受气温和降水综合强影响的区域占5.63%, 气温和降水综合弱影响的区域占13.13%; 因此气候因素中气温在新疆天山植被WUE的变化中起到主导作用。(4)水田与旱地水分利用效率随着时间变化呈持续减少趋势, 并且这些区域基本上受到非气候因子的影响, 说明当地人类活动存在不合理性。     

Temporal and spatial variation characteristics of China shrubland net primary production and its response to climate change from 2001 to 2013

Aims Net primary production (NPP) is the input to terrestrial ecosystem carbon pool. Climate and land use change affect NPP significantly. Shrublands occupy more than 20% of the terrestrial area of China, and their NPP is comparable to those of the forests. Our objective was to estimate China shrubland NPP from 2001 to 2013, and to analyze its variation and response to climate change.Methods We used a Carnegie-Ames-Stanford Approach (CASA) model to estimate the NPP of six shrubland types in China from 2001 to 2013. Furthermore, we used Theil-Sen slope combined with Mann-kendall test to analyze its spatial variation and a linear regression of one-variable model to analyze its inter- and intra-annual variation. Finally, a multi-factor linear regression model was used to analyze its response to climate change.Important findings We found the annual mean NPP of China shrubland was 281.82 g•m^-2•a^-1. The subtropical evergreen shrubland has the maximum NPP of 420.47 g•m^-2•a^-1, while the high cold desert shrubland has the minimum NPP of 52.65 g•m^-2•a^-1. The countrywide shrublands NPP increased at the rate of 1.23 g•m^-2•a^-1, the relative change rate was 5.99%. The temperate deciduous shrubland NPP increased the fastest with a speed of 3.05 g•m^-2•a^-1 and subalpine evergreen shrubland had a decreasing trend with a speed of -0.73 g•m^-2•a^-1. Moreover, the other four shrublands NPP had a growing trend, only subalpine deciduous shrubland NPP did not change significantly. The response of NPP to climate change of different seasons varies to different shrubland types. In general, the NPP variation was mainly affected by precipitation, and the spring warming also contributed to it. The increase of countrywide shrubland NPP may promote its contribution to the regional ecosystem function.     

细根对竹林-阔叶林界面两侧土壤养分异质性形成的贡献

土壤养分异质性是竹林-阔叶林界面(bamboo and broad-leaved forest interface, 以下简称竹阔界面)的重要特征, 细根生长、周转和分解影响土壤养分供应能力, 但其在竹阔界面养分异质性形成中的贡献尚不清楚。该文选取竹阔界面两侧的毛竹(Phyllostachys pubescens)林和常绿阔叶林为研究对象, 开展土壤养分(C、N、P)含量、细根生物量及周转、细根分解及养分回归等指标的对比研究。结果表明: (1)竹阔界面两侧毛竹林和常绿阔叶林土壤养分差异明显, 毛竹林0-60 cm土壤有机碳(SOC)和土壤总氮(STN)含量分别为20.51和0.53 g·kg^-1, 常绿阔叶林0-60 cm土壤有机碳(SOC)和土壤总氮(STN)含量分别为13.42和0.26 g·kg^-1, 前者比后者分别高出34.53%和50.35%, 但毛竹林土壤全磷(STP)含量低于常绿阔叶林25.54%; (2)竹阔界面两侧细根生物量、养分密度及养分回归量差异明显, 毛竹林细根生物量高达1201.60 g·m^-2, 是常绿阔叶林的5.86倍; 养分密度分别为591.42 g C·m^-2、5.44 g N·m^-2、0.25 g P·m^-2, 分别是常绿阔叶林的6.12倍、3.77倍和3.11倍; 年均养分回归量分别为278.54 g C·m^-2·a^-1、2.36 g N·m^-2·a^-1、0.11 g P·m^-2·a^-1, 是常绿阔叶林的6.93倍、4.29倍和3.67倍; (3)细根对界面两侧土壤SOC、STN异质性形成的年均潜在贡献分别为76.79%和28.33%, 但对STP异质性形成起减缓作用, 贡献率为6.17%。这些结果说明毛竹扩张可以改变常绿阔叶林土壤的养分状况, 且细根对不同养分的异质性形成贡献不一致, 是土壤SOC、STN异质性形成的重要原因。     

Greenhouse gas fluxes of typical northern subtropical forest soils: Impacts of land use change and reduced precipitation

Aims It is important to study the effects of land use change and reduced precipitation on greenhouse gas fluxes (CO₂, CH₄ and N₂O) of forest soils. Methods The fluxes of CO₂, CH₄ and N₂O and their responses to environmental factors of primary forest soil, secondary forest soil and artificial forest soil under a reduced precipitation regime were explored using the static chamber and gas chromatography methods during the period from January to December in 2014. Important findings Results indicate that CH₄ uptake of primary forest soil ((-44.43 ± 8.73) μg C·m^-2·h^-1) was significantly higher than that of the secondary forest soil ((-21.64 ± 4.86) μg C·m^-2·h^-1) and the artificial forest soil ((-10.52 ± 2.11) μg C·m^-2·h^-1). CH₄ uptake of the secondary forest soil ((-21.64 ± 4.86) μg C·m^-2·h^-1) was significantly higher than that of the artificial forest ((-10.52 ± 2.11) μg C·m^-2·h^-1). CO₂ emissions of the artificial forest soil ((106.53 ± 19.33) μg C·m^-2·h^-1) were significantly higher than that of the primary forest soil ((49.50 ± 8.16) μg C·m^-2·h^-1) and the secondary forest soil ((63.50 ± 5.35) μg C·m^-2·h^-1) (p < 0.01). N₂O emissions of the secondary forest soil ((1.91 ± 1.22) μg N·m^-2·h^-1) were higher than that of the primary forest soil ((1.40 ± 0.28) μg N·m^-2·h^-1) and the artificial forest soil ((1.01 ± 0.86) μg N·m^-2·h^-1). Reduced precipitation (-50%) had a significant inhibitory effect on CH₄ uptake of the artificial forest soil, while it enhanced CO₂ emissions of the primary forest soil and the secondary forest soil. Reduced precipitation had a significant inhibitory effect on CO₂ emissions of the artificial forest soil and N₂O emissions of the secondary forest (p < 0.01). Reduced precipitation promotes N₂O emissions of the primary forest soil and the artificial forest soil. CH₄ uptake of the primary forest and the secondary forest soil increased significantly with the increase of soil temperature under natural and reduced precipitation. CO₂ and N₂O emission fluxes of the primary forest soil, secondary forest soil and artificial forest soil were positively correlated with soil temperature (p < 0.05). Soil moisture inhibited CH₄ uptake of the secondary forest soil and the artificial forest soil (p < 0.05). CO₂ emissions of the primary forest soil were significantly positively correlated with soil moisture (p < 0.05). N₂O emissions of primary forest soil and secondary forest soil were significantly correlated with the nitrate nitrogen content (p < 0.05). It was implied that reduced precipitation and land use change would have significant effects on greenhouse gas emissions of subtropical forest soils.     

Spatio-temporal characteristics of evapotranspiration and water use efficiency in grasslands of Xinjiang

Aims Xinjiang is located in the hinterland of the Eurasian arid areas, with grasslands widely distributed. Grasslands in Xinjiang provide significant economic and ecological benefits. However, research on evapotranspiration (ET) and water use efficiency (WUE) of the grasslands is still relatively weak. This study aimed to explore the spatio-temporal characteristics on ET and WUE in the grasslands of Xinjiang in the context of climate change.Methods The Biome-BGC model was used to determine the spatio-temporal characteristics of ET and WUE of the grasslands over the period 1979-2012 across different seasons, areas and grassland types in Xinjiang.Important findings The average annual ET in the grasslands of Xinjiang was estimated at 245.7 mm, with interannual variations generally consistent with that of precipitation. Overall, the value of ET was lower than that of precipitation. The higher values of ET mainly distributed in the Tianshan Mountains, Altai Mountains, Altun Mountains and the low mountain areas on the northern slope of Kunlun Mountains. The lower values of ET mainly distributed in the highland areas of Kunlun Mountains and the desert plains. Over the period 1979-2012, average annual ET was 183.2 mm in the grasslands of southern Xinjiang, 357.9 mm in the grasslands of the Tianshan Mountains, and 221.3 mm in grasslands of northern Xinjiang. In winter, ET in grasslands of northern Xinjiang was slightly higher than that of Tianshan Mountains. Average annual ET ranked among grassland types as: mid-mountain meadow > swamp meadow > typical grassland > desert grassland > alpine meadow > saline meadow. The highest ET value occurred in summer, and the lowest ET value occurred in winter, with ET in spring being slightly higher than that in autumn. The higher WUE values mainly distributed in the areas of Tianshan Mountains and Altai Mountains. The lower WUE values mainly distributed in the highland areas of Kunlun Mountains and part of the desert plains. The average annual WUE in the grasslands of Xinjiang was 0.56 g·kg^-1, with the seasonal values of 0.43 g·kg^-1 in spring, 0.60 g·kg^-1 in summer, and 0.48 g·kg^-1 in autumn, respectively. Over the period 1979-2012, the values of WUE displayed significant regional differences: the average values were 0.73 g·kg^-1 in northern Xinjiang, 0.26 g·kg^-1 in southern Xinjiang, and 0.69 g·kg^-1 in Tianshan Mountains. There were also significant differences in WUE among grassland types. The values of WUE ranked in the order of mid-mountain meadow > typical grassland > swamp meadow > saline meadow > alpine meadow > desert grassland.     

近20年内蒙古鄂托克旗草地降水利用效率时空演变的驱动力量化

降水利用效率(PUE)是评价干旱半干旱地区草地生产力与降水关系的有效指标。为进一步探究气候变化和人类活动对草地PUE的驱动机理,本研究采用改进的CASA模型估算了2001—2020年鄂托克旗草地净初级生产力(NPP),结合同期降水量的空间插值数据获取了研究区草地PUE,利用简单线性回归和分段线性回归分析了PUE的时空演变特征及其空间格局对6类气候因子的响应,并引入基于偏导数的量化分析方法定量评估了气候变化和人类活动对PUE动态的相对贡献。结果表明: 鄂托克旗草地PUE多年均值为0.748 g C·m^-2·mm^-1,年际波动呈显著下降趋势,下降速率为0.014 g C·m^-2·mm^-1·a^-1;PUE在空间上西低东高,沿气温、降水、相对湿度、日照时数和ET₀的增长梯度呈显著的单峰分段线性模式,而沿风速梯度表现为先快后慢的持续显著增长模式;研究区94.3%的草地表现为PUE衰减态势,且有43.6%为严重衰减,这一突出问题是气候变化和人类活动共同作用导致的,二者的贡献分别为-1.162×10^-2和-0.240×10^-2 g C·m^-2·mm^-1·a^-1,而气候变化是首要驱动力,其中降水是关键气候驱动因子。     

Application and comparison of remote sensing GPP models with multi-site data in China

Aims Estimation of gross primary productivity (GPP) of vegetation at the global and regional scales is important for understanding the carbon cycle of terrestrial ecosystems. Due to the heterogeneous nature of land surface, measurements at the site level cannot be directly up-scaled to the regional scale. Remote sensing has been widely used as a tool for up-saling GPP by integrating the land surface observations with spatial vegetation patterns. Although there have been many models based on light use efficiency and remote sensing data for simulating terrestrial ecosystem GPP, those models depend much on meteorological data; use of different sources of meteorological datasets often results in divergent outputs, leading to uncertainties in the simulation results. In this study, we examines the feasibility of using two GPP models driven by remote sensing data for estimating regional GPP across different vegetation types. Methods Two GPP models were tested in this study, including the Temperature and Greenness Model (TG) and the Vegetation Index Model (VI), based on remote sensing data and flux data from the China flux network (ChinaFLUX) for different vegatation types for the period 2003-2005. The study sites consist of eight ecological stations located in Xilingol (grassland), Changbaishan (mixed broadleaf-conifer forest), Haibei (shrubland), Yucheng (cropland), Damxung (alpine meadow), Qianyanzhou (evergreen needle-leaved forest), Dinghushan (evergreen broad-leaved forest), and Xishuangbanna (evergreen broad-leaved forest), respectively. Important findings All the remote sensing parameters employed by the TG and VI models had good relationships with the observed GPP, with the values of coefficient of determination, R², exceeding 0.67 for majority of the study sites. However, the root mean square errors (RMSEs) varied greatly among the study sites: the RMSE of TG ranged from 0.29 to 6.40 g·m^-2·d^-1, and that of VI ranged from 0.31 to 7.09 g·m^-2·d^-1, respectively. The photosynthetic conversion coefficients m and a can be up-scaled to a regional scale based on their relationships with the annual average nighttime land surface temperature (LST), with 79% variations in m and 58% of variations in a being explainable in the up-scaling. The correlations between the simulated outputs of both TG and VI and the measured values were mostly high, with the values of correlation coefficient, r, ranging from 0.06 in the TG model and 0.13 in the VI model at the Xishuangbanna site, to 0.94 in the TG model and 0.89 in the VI model at the Haibei site. In general, the TG model performed better than the VI model, especially at sites with high elevation and that are mainly limited by temperature. Both models had potential to be applied at a regional scale in China.     

Remote sensing estimation of gross primary productivity and its response to climate change in the upstream of Heihe River Basin

AimsQuantifying the gross primary productivity (GPP) of vegetation is of primary interest in studies of global carbon cycle. This study aims to optimize the MODIS GPP model for specific environments of a fragile waterhead ecosystem, by performing simulations of long-term (from 2001 to 2012) GPP with optimized MOD_17 model, and to analyze the response of GPP to the local climatic variations.Methods The original MODIS GPP products that underestimate GPP were validated against two years (2010-2011) of eddy covariance (EC) data at two sites (i.e. an alpine pasture site and a forest site, respectively) in the upstream of Heihe River Basin. Three comparative experiments were then conducted to analyze the effects of input parameters derived from three sources (i.e. meteorological, biome-specific, and fraction of absorbed photosynthetically active radiation (fPAR) parameters) on the model behavior. After refining the model-driven parameters, long-term GPPs of the study area were estimated using the optimized MOD_17 model, and the Least Absolute Deviation method was applied to analyze the partial correlations between interannual GPPs and climatic variables (temperature, precipitation and vapor pressure deficit (VPD)). Important findings The uncertainties in the original MODIS GPP products are attributable to biome-specific parameters, input data (e.g. meteorological and radiometry data) and vegetation maps. At the pasture site, the light use efficiency had the strongest impact on the GPP simulations. The refined fPAR calculated from the leaf area index (LAI) products of Global Land Surface Satellite (GLASS) greatly improved the GPP estimates, especially at the forest site. The GPPs from the optimized MOD_17 model well matched the EC data (R² = 0.90, root mean squared error (RMSE) = 1.114 g C·m^-2·d^-1 at the alpine pasture site; R² = 0.91, RMSE = 0.649 g C·m^-2·d^-1 at the forest site). The time series of GPPs displayed an up trend at an average rate of 9.58 g C·m^-2·a^-1 from 2001 to 2012. Examination of the partial correlations between interannual GPPs and climatic variables showed that the annual mean temperature and VPD generally had significant positive impacts on GPP, and the annual precipitation had a negative impact on GPP.     

Spatial variation and controlling factors of temperature sensitivity of soil respiration in forest ecosystems across China

土壤呼吸的温度敏感性(Q₁₀)是陆地碳循环与气候系统间相互作用的关键参数。尽管已有大量关于不同类型森林Q₁₀季节和年际变化规律的研究, 但是对Q₁₀在区域尺度的空间变异特征及其影响因素仍认识不足, 已有结果缺乏一致结论。该研究通过整合已发表论文, 构建了中国森林生态系统年尺度Q₁₀数据集, 共包含399条记录、5种森林类型(落叶阔叶林(DBF)、落叶针叶林(DNF)、常绿阔叶林(EBF)、常绿针叶林(ENF)、混交林(MF))。分析了不同森林类型Q₁₀的空间变异特征及其与地理、气候和土壤因素的关系。结果显示, 1) Q₁₀介于1.09到6.24之间, 平均值(±标准误差)为2.37 (± 0.04), 且在不同森林类型之间无显著差异; 2)当考虑所有森林类型时, Q₁₀随纬度、海拔、土壤有机碳含量(SOC)和土壤全氮含量(TN)的增加而增大, 随经度、年平均气温(MAT)、平均年降水量(MAP)的增加而减小。气候(MAT、MAP)和土壤(SOC、TN)因素间存在相互作用, 共同解释了33%的Q₁₀空间变异, 其中MAT和SOC是Q₁₀空间变异的主要驱动因素; 3)不同类型森林Q₁₀对气候和土壤因素的响应存在差异。在DNF中Q₁₀随MAP的增加而减小, 而其他类型森林中Q₁₀与MAP无显著相关性; 在EBF、DBF、ENF中Q₁₀随TN的增加而增大, 但Q₁₀对TN的敏感性在EBF中最高, 在ENF中最低。这些结果表明, 尽管Q₁₀有一定的集中分布趋势, 但仍有较大范围的空间变异, 在进行碳收支估算时应注意尺度问题。Q₁₀的主要驱动因素和Q₁₀对环境因素的响应随森林类型而变化, 在气候变化情景下, 不同森林类型间Q₁₀可能发生分异。因此, 未来的碳循环-气候模型还应考虑不同类型森林碳循环关键参数对气候变化的响应差异。     

荒漠短命植物地上和地下生产力对极端干旱和降水的响应

在古尔班通古特沙漠南缘沙垄4个坡位和坡向,设置减少65%和增加65%生长季降水量以模拟极端干旱和极端降水事件,研究极端干旱和极端降水事件对沙垄不同坡位和坡向短命植物层片生产力的影响。结果表明: 极端干旱使地上净初级生产力和地下净初级生产力分别显著降低48.8%和13.7%,极端降水使地上净初级生产力和地下净初级生产力分别显著增加37.9%和23.2%。地上净初级生产力对极端干旱和极端降水的敏感性(0.26和0.21 g·m^-2·mm^-1)显著强于地下净初级生产力的敏感性(0.02和0.03 g·m^-2·mm^-1)。沙垄东坡地上净初级生产力(24.22 g·m^-2)和地下净初级生产力(5.77 g·m^-2)与西坡相比显著增大29.7%和71.7%,而地上净初级生产力和地下净初级生产力对降水变化的敏感性在不同坡位和坡向之间差异不显著。     

Plant species change and water budget in restored grasslands in Taibus Banner,Inner Mongolia,China

2008年和2009年(均为枯水年), 在半干旱区内蒙古太仆寺旗农田-草地生态系统国家野外站开展观测实验, 通过观测蒸散发(波文比系统)、土壤水分(烘干称重法)、降水量, 以及植被土壤特征调查, 基于水量平衡理论, 对比研究了3块天然草地、3块不同退耕时间草地共6个样地的水分收支, 旨在定量地评估退耕草地的水分收支, 为采取科学措施促进退耕草地尽快向天然草地过渡提供依据。结果表明: 1)随着退耕时间增加, 植被盖度逐渐增加, 但是群落中科、属、种的数量趋于减少, 且优势种从一年生的中旱生草本植物逐渐转变成多年生的旱生草本植物; 2)植被蒸腾是草原植被主要的耗水途径, 随着退耕时间增加, 退耕草地的蒸散发量呈增加趋势, 其最大值在4.5-5.8 mm·d^-1之间; 3)退耕草地土壤含水量平均值为0.09 m³·m^-3, 其水分剧烈变化主要发生在距地 表60 cm内, 且随退耕时间增加土壤含水量减少, 而天然草地土壤含水量平均值为0.06 m³·m^-3, 其水分剧烈变化发生在距地 表20 cm内; 4)随退耕时间增加, 退耕草地与天然草地的土壤水分与蒸散发在数值上差距逐渐缩小; 5)退耕草地水分收支基本平衡, 但在极枯年份(降水量174 mm)的生长季, 降水不能满足蒸散发需求, 呈现水分亏损。退耕草地逐步向天然草地过渡, 但是退耕草地的土壤水分在逐渐减少, 呈现“生境干旱化现象”。今后应加强对草地的封育与监测, 促进植物群落向水分利用效率更高、更适应半干旱环境的方向演替。     

人工陆桥岛屿系统土壤呼吸速率及其影响因子

研究片段化森林中土壤呼吸速率的格局对进一步揭示陆地生态系统碳循环具有重要意义。本研究以千岛湖人工陆桥岛屿系统不同生境(岛屿与大陆,岛屿边缘与岛屿内部)为对象,分析了土壤呼吸速率的季节动态变化规律及其与土壤理化因子的关系。结果表明: 1)土壤呼吸速率在不同季节差异显著。夏季(3.74 μmol·m^-2·s^-1)>秋季(2.30 μmol·m^-2·s^-1)>春季(1.82 μmol·m^-2·s^-1)>冬季(1.40 μmol·m^-2·s^-1)。2)森林片段化对土壤呼吸速率产生显著影响,岛屿土壤呼吸速率(2.37 μmol·m^-2·s^-1)显著高于大陆(2.08 μmol·m^-2·s^-1);岛屿边缘土壤呼吸速率(2.46 μmol·m^-2·s^-1)显著高于岛屿内部(2.03 μmol·m^-2·s^-1)。3)土壤温度显著促进了土壤呼吸速率,并作为主要因子解释了56.1%的变化。4)土壤呼吸速率与土壤全碳、铵态氮含量和地表植被覆盖率呈显著正相关。土壤全碳和铵态氮含量在岛屿边缘显著高于岛屿内部。综上,森林片段化促进了土壤呼吸速率,而土壤理化因子的变化是其主要原因。     

Effects of climate change on net primary productivity in Larix olgensis plantations based on process modeling

Aims Climate change has significant effects on net primary productivity (NPP) in forests, but there is a large uncertainty in the direction and magnitude of the effects. Process-based models are important tools for understanding the responses of forests to climate change. The objective of the study is to simulate changes in NPP of Larix olgensis plantations under future climate scenarios using 3-PG model in order to guide the management of L. olgensis plantations in the context of global climate change.Methods Data were obtained for 30 permanent plots of L. olgensis plantations in Siping, Linjiang, Baishan, etc. of Jilin Province, and a process model, 3-PG model, was applied to simulate changes in NPP over a rotation period of 40 years under different climate scenarios. Parameter sensitivity was also determined. Important findings The locally parameterized 3-PG model well simulates the changes in NPP against the measured NPP data, with values between 272.79-844.80 g·m^-2·a^-1 and both mean relative error and relative root mean square error within 12%. The NPP in L. olgensis plantations would increase significantly with increases in atmospheric CO₂ concentration, temperature and precipitation collectively. However, an increase in temperature alone would lead to a decrease in NPP, but increases in precipitation and atmospheric CO₂ concentration would increase NPP; the positive effect of increasing precipitation appears to be weaker than the negative effect of increasing temperature. Sensitivity analysis shows that the model performance is sensitive to the optimum temperature, stand age at which specific leaf area equals to half of the sum of specific leaf area at age 0 (SLA₀) and that for mature leaves (SLA₁), and days of production loss due to frost.     

Alpine grassland water use efficiency based on annual precipitation,growing season precipitation and growing season evapotranspiration

Water use efficiency (WUE) is an important parameter to understand the coupling between the water, and carbon cycles of terrestrial ecosystems. Previous studies on the grassland ecosystem WUE on the Qinghai-Xizang Plateau mainly based on annual precipitation (AP). However, vegetation water use mainly occurs in growing season. Therefore, we aimed to explore the differences of ecosystem WUE between alpine meadow and alpine steppe, and the relationships between ecosystem WUE and environmental factors from 2000 to 2010, using annual precipitation use efficiency (PUE_a), growing season precipitation use efficiency (PUE_gs), growing season water use efficiency (WUE_gs) based on AP, growing season precipitation (GSP) and growing season evapotranspiration (ET_gs ) respectively. Combining satellite-derived above-ground net primary productivity (ANPP), satellite-derived evapotranspiration and meteorological data from 2000 to 2010, we calculated PUE_a (ANPP / AP), PUE_gs (ANPP / GSP) and WUE_gs (ANPP / ET_gs) to find the differences of PUE_a, PUE_gs and WUE_gs between alpine meadow and alpine steppe. Moreover, we explored the relationships between PUE_a, PUE_gs or WUE_gs and precipitation (or evapotranspiration) or air temperature. We found that (1) the PUE_a and PUE_gs of alpine meadow were higher than that of alpine steppe, but there were no significant difference between WUE_gs of the two grassland types, indicating that there may be similar intrinsic water use efficiencies of the two grassland types. (2) The inter-annual variation of PUE_a and PUE_gs were similar while WUE_gs showed a larger fluctuation, implying that ET-based WUE_gs was more sensitive than precipitation-based PUE_a and PUE_gs, therefore WUE_gs is a better indicator of ecosystem water use efficiency than PUE_a or PUE_gs. (3) The PUE_a, PUE_gs and WUE_gs were negatively correlated with AP, GSP and ET_gs respectively, reflecting a consistency of the three water use efficiency measurements. In the alpine steppe, only WUE_gs was observed positively correlated with air temperature among the three measurements, but in the alpine meadow, no significant relationships between water use efficiency and air temperature was detected, suggesting that the WUE_gs of alpine steppe was more sensitive to air temperature than that of alpine meadow.     

1999—2015年若尔盖草原湿地净初级生产力时空变化

植被净初级生产力(NPP)是草原湿地生态系统碳收支平衡和气候变化的核心内容之一。本研究基于植被指数、气象数据(降水和气温)、植被类型数据,利用CASA模型对若尔盖草原湿地1999—2015年NPP进行估算,分析了若尔盖草原湿地NPP时空格局特征及其与气候因子的关系。结果表明: NPP实测值与模拟值之间显著相关,R²为0.78,均方根误差为120.3 g C·m^-2·a^-1;研究区年均和生长季(4—9月)NPP分别为329.0、229.4 g C·m^-2·a^-1,年际间波动明显,以2.3、1.6 g C·m^-2·a^-1的微弱趋势下降,不同植被类型的年均及生长季NPP的年际波动与整个研究区的波动趋势基本一致;年均和生长季NPP的变化斜率分别为-21.3～18.7、-31.5～23.1 g C·m^-2·a^-1,显著增加的面积分别占研究区总面积的0.3%和0.7%,主要分布于森林覆盖区和湿地生态补偿区;显著下降的面积分别占研究区总面积的1.4%和6.4%,主要分布于人类活动集中的地区;研究区不同植被的固碳能力存在差异,其中,森林最强,草地次之,湿地最弱;降水是影响草原湿地植被NPP的主导气候因子。     

氮肥和种植密度对达乌里胡枝子的生长与生物固氮的影响

氮供给和种植密度是影响植物生长的两个重要因素。豆科植物因其生物固氮能力而在受到氮限制的生态系统中具有重要作用, 氮含量增加促进植物生长的同时也会抑制豆科植物的生物固氮能力, 种植密度会通过种内竞争影响豆科植物的生长和生物固氮能力, 然而少有研究关注氮肥添加和种植密度对豆科植物生长和生物固氮能力的影响。该研究以达乌里胡枝子(Lespedeza davurica)为研究对象, 通过温室盆栽实验, 探究氮肥和种植密度对其生长和生物固氮的影响。实验设置4个氮添加水平(0、5、10、20 g·m^-2·a^-1)和3种种植密度(1、3、6 Ind.·pot^-1, 约32、96、192 Ind.·m^-2)。结果发现: 1)施肥和密度增加均影响了达乌里胡枝子的生长。叶片碳(C)、氮(N)含量、净光合速率随施氮量增加而增加, 氮添加也促进了植物的生长, 当施氮量为10 g·m^-2·a^-1时植物产量达到最大。叶片C、N含量、净光合速率随种植密度增加而下降, 密度增加可以促进每盆的总生物量, 但对单个植株的生长有负效应。2)氮肥对根瘤形成有抑制作用, 但种植密度增加会缓解氮肥对生物固氮能力带来的“氮阻遏”。该实验条件下, 当施氮量为10 g·m^-2·a^-1, 种植密度为3 Ind.·pot^-1, 或施氮量为5 g·m^-2·a^-1, 种植密度为6 Ind.·pot^-1时, 能最大程度发挥“施氮增产”和种植密度缓解“氮阻遏”的作用。氮添加降低了达乌里胡枝子的根瘤生物量和对根瘤形成的投资(根瘤生物量占总生物量的比例), 从而抑制达乌里胡枝子的生物固氮。种植密度增加导致达乌里胡枝子因种内竞争增加而使资源获取受限, 从而增加对根瘤的投资和根瘤生物量来获得更多来自大气中的氮。3)结构方程结果显示, 氮肥和种植密度通过直接或间接作用, 解释了64%的达乌里胡枝子生物量变化和42%的根瘤生物量变化。上述结果表明合理优化豆科植物的施肥量和种植密度可能对人工草地种植以及退化草地恢复管理具有重要意义。     

模拟氮沉降对华西雨屏区天然常绿阔叶林土壤微生物生物量碳和氮的影响

为理解模拟氮沉降对华西雨屏区天然常绿阔叶林土壤微生物生物量碳(MBC)和氮(MBN)的影响,通过一年野外模拟氮(NH₄NO₃)沉降试验,氮沉降水平分别为对照(CK, 0 g N·m^-2·a^-1)、低氮沉降(L, 5 g N·m^-2·a^-1)、中氮沉降(M, 15 g N·m^-2·a^-1)和高氮沉降(H, 30 g N·m^-2·a^-1),研究了氮沉降对天然常绿阔叶林土壤MBC和MBN的影响.结果表明: 氮沉降显著降低了0～10 cm土层MBC和MBN,且随氮沉降量的增加,下降幅度增大;L和M处理对10～20 cm土层MBC和MBN无显著影响,H处理显著降低了10～20 cm土层土壤MBC和MBN;氮沉降对MBC和MBN的影响随土壤深度的增加而减弱.MBC和MBN具有明显的季节变化,在0～10和10～20 cm土层均表现为秋季最高,夏季最低.0～10和10～20 cm土层土壤微生物生物量C/N分别介于10.58～11.19和9.62～12.20,表明在华西雨屏区天然常绿阔叶林土壤微生物群落中真菌占据优势.     

油蒿资源利用效率在生长季的相对变化及对环境因子的响应

为了探明西北半干旱区典型沙生植物油蒿(Artemisia ordosica)叶水平资源利用效率的相对变化及对环境因子的响应机制, 该研究于2018年5-10月, 使用LI-6400XT便携式光合仪测定了毛乌素沙地油蒿叶片的净光合速率(P_n)、蒸腾速率(E)、叶表面光合有效辐射(PAR_l)、叶表面温度(T_l)、叶表面相对湿度(RH_l), 在实验室计算叶片单位面积氮含量(N_area), 分析了叶片氮利用效率(NUE)、水分利用效率(WUE)、光利用效率(LUE)与环境因子之间的关系及NUE、WUE、LUE之间的相对变化。研究结果表明, 在充足且稳定光强下油蒿的P_n主要受温度的影响, NUE、WUE与VPD_l、T_l之间具有显著负相关关系, NUE、WUE与LUE间为正相关关系, NUE、WUE和LUE最大值分别发生在5、7和9月, 分别为9.43 μmol CO₂·g^-1·s^-1、3.86 mmol·mol^-1、0.04 mol·mol^-1, 资源利用效率的变化主要受P_n的影响。温度通过影响植物N分配来改变P_n, 进而影响着资源利用效率, WUE与LUE显著正相关, 对构建荒漠区生态系统能量交换过程模型有重要意义。     

黄土丘陵区表层土壤有机碳沿降水梯度的分布

沿368～591 mm降水量梯度选取7个调查地点、共63个调查样点,在每个样点选择恢复年限相近的林地、草地和农地,调查表层（0～30 cm）土壤有机碳的分布特征,分析气候、土层深度和土地利用类型等因素对土壤有机碳分布的影响.结果表明： 在黄土丘陵区368～591 mm的降水量范围内,表层土壤有机碳含量表现为草地（8.70 g·kg^-1）>林地（7.88 g·kg^-1）>农地（7.73 g·kg^-1）,土壤有机碳密度表现为草地（20.28 kg·m^-2）>农地（19.34 kg·m^-2）>林地（17.14 kg·m^-2）.林地、草地、农地的土壤有机碳含量无显著差异,综合3种土地利用类型的数据分析表明,不同降雨梯度下土壤有机碳含量差异显著（P<0.001）,土壤有机碳含量（r=0.838,P<0.001）与年均降水量间存在显著线性正相关关系;由北向南（以最北端鄂尔多斯为起点）,土壤有机碳含量沿着368～591 mm的年均降水量梯度的递增速率为0.04 g·kg^-1·mm^-1,土壤有机碳密度的递增速率为0.08 kg·m^-2·mm^-1.年均降水量、土壤黏粒含量、林下枯落物蓄积量和农作物根系密度可较好地模拟表层土壤有机碳分布.