Understanding the degree to which the species diversity-productivity relationship (SDPR) is applicable to natural ecosystems-beyond modeling and experimental contexts - is of vital importance for comprehending the consequences of global biodiversity loss on terrestrial ecosystems. Two essential features of natural forests that have not received adequate attention in the SDPR are seasonality and species evenness. Here, we monitor the intraand inter-annual growths of 6,515 trees in a subtropical seasonal (temperature- and rainfall-seasonal) forest over a six-year period. We investigate whether evenness affects forest productivity independently or interacting with richness and how the underlying mechanisms shift with seasonality and soil properties, employing structural equation modeling. Our findings reveal a consistent decline in species diversity, functional diversity and forest productivity from the wet-warm season to the dry-cold season, with community traits shifting from acquisition to conservative strategies. Species richness increases but evenness decreases forest productivity-uneven communities are more productive, and the attenuation effect of evenness on productivity varies slightly across different seasons. Species richness and evenness jointly affect productivity through community-weighted means (CWM) of functional traits in the wet-warm season and through both functional diversity and CWM of functional traits in the dry-cold season, indicating that the mass ratio effect is predominant during the wet-warm season, whereas both niche complementarity and mass ratio effects jointly drive productivity in the dry-cold season. Soil water availability directly affects forest productivity in the wet-warm season and indirectly through CWM of functional traits in the dry-cold season. Our study, the first to elucidate the seasonal dynamics of the SDPR in subtropical forests. Our results highlight species evenness as a key component of species diversity regulating seasonal productivity dynamics in heterogeneous, species-rich natural forests. To enhance forest resilience under climate change (e.g., drought), management should prioritize maintaining moderate evenness, while strategically planting drought-tolerant species and acquisitive species of subtropical forest ecosystems.

Studying spatial distribution patterns and intraspecific and interspecific associations of tree species is crucial for understanding the maintenance of biodiversity and offering insights into community dynamics and stability. The Shennongjia National Park, located in the transition zone between the (sub)tropics and the temperate climate, holds great significance for understanding how species interact with each other and coexist within forest communities. We used data from a fully mapped 25 ha montane deciduous broad-leaved forest dynamic plot at Shennongjia (SNJ) National Park, central China, to conduct a community-level evaluation of spatial distribution patterns and intraspecific and interspecific associations. We analyzed the spatial distribution patterns of 20 dominant species with univariate and bivariate g(r) functions, as well as intraspecific and interspecific associations across different life-history stages. We assessed the relative contributions of underlying processes in community assembly with three models: complete spatial randomness (CSR), heterogeneous Poisson (HP), and antecedent condition (AC). The results showed that all 20 tree species exhibited aggregated distribution patterns within a 100 m scale. After excluding the influence of environmental heterogeneity, the degree of aggregation decreased, and with the increasing spatial scale from 0 to 100 m, the distribution gradually shifted from aggregated to random or uniform appearance. Positive associations were common in different life-history stages. Negative associations were common across different species, while most of the intraspecific and interspecific associations turned out to be irrelevant when environmental heterogeneity was excluded. We concluded that habitat heterogeneity and dispersal limitation may primarily determine the spatial distribution of species in subtropical montane deciduous broad-leaved forests. This indicates that species distribution may align with environmental patterns, and interspecific correlations may exist. However, the exact responses of these species to environmental changes remain uncertain. Upcoming management approaches ought to concentrate on ongoing observation, which is crucial for mitigating how climate change might affect species distribution and community interactions, thus guaranteeing enduring stability and the conservation of biodiversity.

Understanding the mechanisms of species diversity maintenance is crucial for appreciating community assembly and predicting responses to global climate change. Niche differentiation is one of the most important mechanisms underlying biodiversity maintenance across ecosystems. However, direct evidence for niche differentiation remains scarce in subtropical speciose forests. In this study, a 25-ha (500 m × 500 m) subtropical montane deciduous broadleaved forest dynamics plot in Shennongjia national park was developed to assess species-habitat associations across life history stages. Five habitat types were identified using multivariate regression trees and mapped to 625 20 m × 20 m quadrats. Torus-translation randomization tests identified species-habitat associations across life forms and life stages. Out of 105 species, 81 were significantly associated with at least one habitat type and 65 associated with elevation or convexity (49 species with elevation and 36 with convexity). Across all life stages, saplings were most strongly related to low elevation habitats, while juveniles and mature trees most often correlated with the “low convex slope” habitat type. Canopy and shrub species were positively correlated with the “high convex slope” and “low convex slope” habitat types, respectively. In conclusion, niche differentiation during regeneration (based on topographic heterogeneity) is essential for stable multi-species coexistence and the maintenance of biodiversity in subtropical speciose forests. Future studies are needed to examine how demographic rates shift along environmental gradients of convexity and elevation, providing a more in-depth understanding of niche differentiation in forest ecosystems.

涡度相关技术连续观测的碳水通量是准确评估生态系统固碳持水等生态功能的重要基础数据,由于通量观测数据的缺失十分常见且比例较高,引入现代机器学习算法以发展缺失数据的插补方法对降低研究结果不确定性具有重要意义。该研究利用青藏高原东北隅高寒金露梅（Potentillafruticosa）灌丛已发布的2003–2005年水、热、CO 2 通量数据集,结合气温、大气水汽压、风速、太阳短波辐射、表层土壤温度和表层土壤含水量等主要环境因子构建了增强回归树模型（BRT）以插补缺失通量数据,并与中国通量观测研究联盟（China FLUX）的数据序列进行了比对,以评估BRT在通量数据集成分析中的应用。BRT对大样本（N＞ 10 000）通量数据具有较好的模拟效果,观测值与模拟值的回归斜率为1.01–1.05 （R2＞ 0.80）。BRT表明植被生长季（5–10月）白天30min净CO 2 交换量（NEE）主要受控于太阳短波辐射和大气水汽压,二者对NEE变异的相对贡献之和为74.7%。表层土壤温度是生长季夜间及非生长季全天30minNEE的主要驱动因子,其相对贡献为68.5%。30min显热通量（H）和潜热通量（LE）均主要受控于太阳短波辐射（相对贡献大于58.6%）。BRT插补的30 min缺失通量数据均显著小于China FLUX的插补结果。除逐日NEE无显著差异外（p=0.14）, BRT的逐日生态系统总交换（GEE）、生态系统呼吸（RES）、H和LE极显著小于ChinaFLUX的数据序列分别约17.5%、21.0%、2.7%和2.2%,但由于量级差异较小,二者具有较高的一致性（数据序列的回归斜率在0.95–1.17）。除逐月GEE和RES外,BRT的逐月NEE、H和LE与ChinaFLUX的数据序列无显著（p＞0.09）差异。相对于ChinaFLUX数据插补方法,BRT不需要复杂的数学表达就可模拟主要环境因子的非线性作用特征,从而进行缺失通量数据的插补,是通量数据集成分析的一种可行方法。

为探讨暖季休牧恢复过程中退化高寒草甸植被和土壤恢复特性,本研究对泽库县退化高山嵩草草甸暖季休牧样地不同恢复阶段植被和土壤特性进行调查,结果显示植被高度、地上生物量、土壤含水量、土壤有机碳含量等生态功能属性随自然恢复时间的延长不断得到改善(P<0.05),在恢复末期(9—10年)恢复最好;植被盖度、地下生物量、多样性、土壤容重等恢复效果逐渐增强,并在恢复后期、恢复末期趋于稳定;随着休牧时间的延长,垂穗披碱草(Elymus nutans)生存状态指数逐渐增大,在恢复末期达到了10.27,而植被退化的指示物种黄帚橐吾(Ligu-laria virgaurea)和瑞苓草(Saussurea nigrescens)生存状态指数逐渐减小,从较高的优势物种逐渐被垂穗披碱草等物种所替代.对草地质量进行综合评价发现,暖季休牧样地草地质量在恢复末期的草地质量评分最好.本研究为推广实施暖季休牧来恢复退化高寒草甸提供了理论基础.

科学评估三江源区草地的气候资源利用率及载畜能力,是有效开展草地资源利用和实施生态保护的基础和前提,对促进草地畜牧业可持续发展和区域生态文明建设具有重要意义.三江源国家公园位于青藏高原高寒生态脆弱区和敏感区,其核心区是重要生物多样性保护区,国家公园以外的传统利用区是当地牧民维持生计的重要支撑区.本研究基于GLOPEM-CEVSA模型,模拟了1981–2018年三江源区草地现实产草量和气候产草量,分析了草地的气候资源利用率及载畜能力.结果表明,近40年三江源区平均现实产草量和气候产草量分别为852.56和1357.14?kg·hm?2,草地的平均气候资源利用率为62.82％,且呈西北部较高东南部较低的分布特点,国家公园3个园区草地气候资源利用率在61.92％～66.42％.除国家公园所在县域及气候资源利用率较高的唐古拉山乡外,东、南部各县仍有约35％的气候潜力,即505.53?kg·hm?2的草料潜力和每公顷0.44标准羊单位(SU·hm?2)的载畜潜力.因此,建议在东、南部水热条件较好地区,合理开展退化草地修复工作,提高草地气候资源利用率及草地生产力,承接分担国家公园区域畜牧生产压力,进而在保护国家公园脆弱生态系统和生物多样性基础上,促进整个区域牧民生计、畜牧生产和生态系统稳定的协调可持续发展.

以祁连山东段嵩草草甸(矮嵩草草甸)、灌丛草甸(金露梅灌丛草甸)、沼泽草甸(帕米尔苔草沼泽草甸)和草甸草原(西北针茅草甸草原)4类重要草地为对象,基于2011年植被生长季(6～9月)涡度相关观测系统连续监测的CO2通量和遥感反演的叶面积指数(LAI),比较研究CO2通量及群落光合特征参数与LAI的关系.结果表明,生长季中嵩草草甸的LAI和碳汇强度分别为2.76m2/m2和694.13gCO2/m2,显著高于其他3类草地类型.灌丛草甸碳汇强度居中(662.98gCO2/m2),但LAI最小(1.66m2/m2),草甸草原碳汇强度次之(524.40gCO2/m2),沼泽草甸碳汇强度最小(460.77gCO2/m2).4类草地的逐日生态系统CO2净交换(Net ecosystem CO2 exchange,NEE)均主要受控于生态系统总初级生产力(Gross primary productivity,GPP).逐日NEE、GPP、生态系统总呼吸(Ecosys-tem respiration,RES)均与LAI呈显著线性相关(P＜0.05).沼泽草甸和灌丛草甸的逐日GPP及NEE对LAI的敏感度极显著高于嵩草草甸和草甸草原(P＜0.001),但不同草地类型间逐日RES对LAI的敏感度无显著差异.嵩草草甸的饱和光合速率和生态系统暗呼吸速率相对最大,平均分别为0.89和0.22mgCO2/(m2·s),但与其他3类草地无显著差异.草地类型间群落光合特征参数的季节变异主要受控于LAI(P＜0.01),与草地类型和生长阶段关系较小.因此,LAI和草地类型通过影响总初级生产力、呼吸强度和群落光合特征,共同调控着高寒草地的碳收支.研究结果可为祁连山东部区域碳汇功能评估提供理论依据和数据支撑.

草地退化显著削弱了三江源高寒草甸的土壤肥力及生态承载功能,但空间尺度上的驱动强度和环境调控尚不清晰.在2020年7-8月,基于三江源国家公园高寒草甸典型分布区原生植被和退化植被的60个配对采样,研究表层(0-30 cm)土壤有机碳(SOC)、全氮(TN)和全磷(TP)含量对草地退化的空间响应特征.三江源国家公园高寒草甸原生植被SOC和TN含量分别为(2.45±2.05)％(平均值±标准差,下同)和(0.25±0.20)％,配对样本t-检验的结果表明草地退化导致SOC和TN分别极显著(P＜0.001)下降了 44.0％和35.6％.TP对草地退化无显著响应(P=0.22).原生植被的土壤C ∶N ∶P平均为59.6∶6.2∶1.0,草地退化导致化学计量值平均下降28.3％.一般线性模型的结果表明草地退化对SOC和TN及土壤生态化学计量特征的空间降低强度主要取决于纬度和海拔(P＜0.01),与经度和土壤深度关系较弱(P＞0.30),即低纬度高海拔的高寒草甸响应相对强烈.草地退化导致三江源国家公园高寒草甸土壤碳氮损失严重,降低了土壤生态化学计量.研究结果可为三江源退化高寒草甸土壤营养功能的治理和恢复提供理论支撑.

三江源国家公园是青藏高原生态屏障的核心单元,准确评估其土壤碳氮特征是区域生态功能认知和分区管理的重要基础.基于54个样点调查数据,结合高程、坡度、坡向及2000-2018年的年均气温、降水、归一化植被指数等生态因子,采用增强回归树模型研究了三江源国家公园表层(0-30 cm)土壤有机碳(SOC)、全氮(TN)密度的空间格局和等级区划及储量特征.结果表明三江源国家公园SOC密度和TN密度分别为(5.41±3.12)kg/m2(平均值±标准差,下同)和(0.57±0.27)kg/m2,其空间变异均主要受降水和归一化植被指数影响.澜沧江源园区和黄河源园区SOC和TN密度分别为(9.39±0.89)kg/m2和(0.92±0.09)kg/m2、(8.26±2.33)kg/m2和(0.80±0.20)kg/m2,约为长江源园区的2倍.SOC和TN密度等级在澜沧江源园区呈现出中心高周围低的特征,在黄河源园区和长江源园区分别表现出从北到南和从东南到西北逐渐降低的格局.三江源国家公园SOC储量和TN储量分别为0.60 Pg和0.06 Pg,其中澜沧江源园区、黄河源园区、长江源园区的储量占比分别约为20％、20％和60％.三江源国家公园SOC储量和TN储量均主要集中在高寒草甸和高寒草原,二者累计占比约为90％,是区域生态功能的主要载体和管理规划的重点对象.研究结果可为三江源国家公园的功能评估和分区管理提供参考依据.

The carbon process of the alpine ecosystem is complex and sensitive in the face of continuous global warming. However, the long-term dynamics of carbon budget and its driving mechanism of alpine ecosystem remain unclear. Using the eddy covariance (EC) technique—a fast and direct method of measuring carbon dioxide (CO 2 ) fluxes, we analyzed the dynamics of CO 2 fluxes and their driving mechanism in an alpine wetland in the northeastern Qinghai–Tibet Plateau (QTP) during the growing season (May–September) from 2004–2016. The results show that the monthly gross primary productivity (GPP) and ecosystem respiration (Re) showed a unimodal pattern, and the monthly net ecosystem CO 2 exchange (NEE) showed a V-shaped trend. With the alpine wetland ecosystem being a carbon sink during the growing season, that is, a reservoir that absorbs more atmospheric carbon than it releases, the annual NEE, GPP, and Re reached −67.5 ± 10.2, 473.4 ± 19.1, and 405.9 ± 8.9 gCm -2 , respectively. At the monthly scale, the classification and regression tree (CART) analysis revealed air temperature (Ta) to be the main determinant of variations in the monthly NEE and GPP. Soil temperature (Ts) largely determined the changes in the monthly Re. The linear regression analysis confirmed that thermal conditions (Ta, Ts) were crucial determinants of the dynamics of monthly CO 2 fluxes during the growing season. At the interannual scale, the variations of CO 2 fluxes were affected mainly by precipitation and thermal conditions. The annual GPP and Re were positively correlated with Ta and Ts, and were negatively correlated with precipitation. However, hydrothermal conditions (Ta, Ts, and precipitation) had no significant effect on annual NEE. Our results indicated that climate warming would be beneficial to the improvement of GPP and Re in the alpine wetland, while the increase of precipitation can weaken this effect.

由于青藏高原高海拔、低温的特殊环境，使得生态系统呼吸（RE）对气候变化的响应极其敏感，然而对高寒湿地生态系统长时间尺度上的RE动态特征及驱动机制的研究相对薄弱。以青藏高原东北部高寒湿地为研究对象，分析了基于涡度相关系统观测的高寒湿地2004—2016年的CO 2 通量排放动态及影响机制，对预测高寒湿地碳平衡对未来气候变化的响应具有重要意义。结果表明：高寒湿地在2004—2016年的月平均RE表现为单峰变化趋势，在8月达到峰值；年RE表现为逐年升高的趋势（P＜0.05）,年RE均值为（608.9±65.6） g C m -2 a -1 ;生长季RE约是非生长季RE的2.7倍，线性回归分析表明生长季RE（r~2=0.66,P=0.001）、非生长季RE（r~2=0.47,P=0.01）与全年RE呈极显著正相关。在月尺度上，分类回归树分析和线性回归分析表明土壤温度是月RE的最主要控制因素，暗示高寒湿地的土壤呼吸对整个生态系统的碳排放至关重要。在年际尺度上，生长季积温与生长季RE呈显著正相关（P＜0.05）,而生长季降水（PPT）与生长季RE呈显著负相关（P＜0.05）,非生长季气温（P＜0.05）、PPT（P＜0.05）与非生长季RE呈显著正相关，暗示未来温度的升高将会促进高寒湿地的CO 2 排放，而生长季、非生长季碳排放对PPT的差异化响应，暗示在分析高寒生态系统CO 2 排放对未来水热条件响应时需更加谨慎。

Abstract Biomass temporal stability plays a key role in maintaining sustainable ecosystem functions and services of grasslands, and climate change has exerted a profound impact on plant biomass. However, it remains unclear how the community biomass stability in alpine meadows responds to changes in some climate factors (e.g., temperature and precipitation). Long‐term field aboveground biomass monitoring was conducted in four alpine meadows (Haiyan [HY], Henan [HN], Gande [GD], and Qumalai [QML]) on the Qinghai‐Tibet Plateau. We found that climate factors and ecological factors together affected the community biomass stability and only the stability of HY had a significant decrease over the study period. The community biomass stability at each site was positively correlated with both the stability of the dominant functional group and functional groups asynchrony. The effect of dominant functional groups on community stability decreased with the increase of the effect of functional groups asynchrony on community stability and there may be a ‘trade‐off’ relationship between the effects of these two factors on community stability. Climatic factors directly or indirectly affect community biomass stability by influencing the stability of the dominant functional group or functional groups asynchrony. Air temperature and precipitation indirectly affected the community stability of HY and HN, but air temperature in the growing season and nongrowing season had direct negative and direct positive effects on the community stability of GD and QML, respectively. The underlying mechanisms varied between community composition and local climate conditions. Our findings highlighted the role of dominant functional group and functional groups asynchrony in maintaining community biomass stability in alpine meadows and we highlighted the importance of the environmental context when exploring the stability influence mechanism. Studies of community stability in alpine meadows along with different precipitation and temperature gradients are needed to improve our comprehensive understanding of the mechanisms controlling alpine meadow stability.

Known as the "Third Pole" and "Early-warning region" of the world, the Qinghai-Tibetan Plateau (QTP) had an intense increase in surface temperature and marked change in the amplitude of diurnal temperature (ADT), which could have significant influences on the ecosystem carbon cycle. The increasing rate of the mean daily minimum temperature (MinTa) was about two times higher than that of maximum temperature (MaxTa) in the last five decades, and this asymmetric pattern has resulted in a smaller ADT, which substantially affected the plant phenology and vegetation productivity. The reduction in the ADT caused by global climate change would have a profound impact on the carbon balance of alpine ecosystems. However, the response of carbon budgets to the ADT over the QTP remained unclear. Here. we analyzed the 15-a growing seasonal (June-September) carbon fluxes (measured by the eddy covariance [EC] technique) in alpine meadow at the southern foot of Qilian Mountains, which is one of the most extensive vegetation types on the QTP. This study aimed to clarify how carbon fluxes respond to ADT at different temporal (daily, monthly and annual) scales in alpine meadow and to understand their potential response to future climate change. The results indicated that both the MaxTa and MinTa showed bell-shaped seasonal patterns, whereas the ADT failed to show an obvious trend during the growing season from 2002 to 2016. Besides, there was a non-significant increase in annual MaxTa. MinTa and ADT (P>0.05). Meanwhile, daily gross primary productivity (GPP) and ecosystem respiration (Re) exhibited a single-peaked trend that increased and then decreased. whereas daily net ecosystem CO2 exchange (NEE) showed a v-shaped trend. The alpine meadow ecosystem is a carbon sink during the growing season. and the annual NEE, GPP. and Re were -230.4 +/- 17.3.668.8 +/- 25.5, 438.3 +/- 27.5 g C m(-2) respectively. Moreover, the annual GPP and Re of alpine meadow in the growing season showed a significant increase trend (P<0.05), but the annual NEE showed no significant inter-annual change trend (P>0.05). Annual CO, fluxes were not related annual ADT. Only annual MaxTa exerted significant influence on variations in annual GPP and Re. Interestingly, the slopes of GPP and Re with respect to MaxTa were similar, also indicating the little impact of MaxTa on annual NEE. On a monthly scale, ADT exerted a negligible influence on CO2 fluxes (P>0.05), but there were significant correlations between MinTa and MaxTa with CO2 fluxes. On a daily scale, there was a significant quadratic relationship between daily NEE and ADT during the whole growing season (P<0.001), with a threshold of 19.8 degrees C. However. linear regression analysis showed that there was a significant negative correlation (P<0.001) between daily NEE and daily ADT in June, July, August and September, respectively. On the whole, the increase in ADT is beneficial to carbon sequestration of the alpine meadow ecosystem. Therefore, the results suggest that the decrease in ADT in the future will cripple the carbon sink of the alpine meadow ecosystem on the Qinghai-Tibetan Plateau.

Alpine wetlands sequester large amounts of soil carbon, so it is vital to gain a full understanding of their land-atmospheric CO2 exchanges and how they contribute to regional carbon neutrality; such an understanding is currently lacking for the Qinghai—Tibet Plateau (QTP), which is undergoing unprecedented climate warming. We analyzed two-year (2018–2019) continuous CO2 flux data, measured by eddy covariance techniques, to quantify the carbon budgets of two alpine wetlands (Luanhaizi peatland (LHZ) and Xiaobohu swamp (XBH)) on the northeastern QTP. At an 8-day scale, boosted regression tree model-based analysis showed that variations in growing season CO2 fluxes were predominantly determined by atmospheric water vapor, having a relative contribution of more than 65%. Variations in nongrowing season CO2 fluxes were mainly controlled by site (categorical variable) and topsoil temperature (Ts), with cumulative relative contributions of 81.8%. At a monthly scale, structural equation models revealed that net ecosystem CO2 exchange (NEE) at both sites was regulated more by gross primary productivity (GPP), than by ecosystem respiration (RES), which were both in turn directly controlled by atmospheric water vapor. The general linear model showed that variations in nongrowing season CO2 fluxes were significantly (p < 0.001) driven by the main effect of site and Ts. Annually, LHZ acted as a net carbon source, and NEE, GPP, and RES were 41.5 ± 17.8, 631.5 ± 19.4, and 673.0 ± 37.2 g C/(m2 year), respectively. XBH behaved as a net carbon sink, and NEE, GPP, and RES were –40.9 ± 7.5, 595.1 ± 15.4, and 554.2 ± 7.9 g C/(m2 year), respectively. These distinctly different carbon budgets were primarily caused by the nongrowing season RES being approximately twice as large at LHZ (p < 0.001), rather than by other equivalent growing season CO2 fluxes (p > 0.10). Overall, variations in growing season CO2 fluxes were mainly controlled by atmospheric water vapor, while those of the nongrowing season were jointly determined by site attributes and soil temperatures. Our results highlight the different carbon functions of alpine peatland and alpine swampland, and show that nongrowing season CO2 emissions should be taken into full consideration when upscaling regional carbon budgets. Current and predicted marked winter warming will directly stimulate increased CO2 emissions from alpine wetlands, which will positively feedback to climate change.

植物群落特征和生存状态变化能够反映植物群落内种间关系和演替进程.本研究以青海海北地区高寒草甸的冷季放牧场为研究对象,分析比较了禁牧封育(CK,禁牧)、轻度放牧(LG,4.5只羊·hm?2)、中度放牧(MG,7.5只羊·hm?2)和重度放牧(HG,15只羊·hm?2)?4种放牧压力对植物群落特征及各功能群代表性植物生存状态指数的影响.结果表明:1)禾本科的重要值在轻度放牧时最大,莎草科的重要值在禁牧样地中最大,杂草类植物的重要值在重度放牧样地中最大.2)?Shannon-Wiener多样性指数、Simpson优势度指数、Patrick丰富度指数随着放牧强度的增加均呈增加趋势.3)轻度放牧样地中垂穗披碱草(Elymus nutans)和山地早熟禾(Poa orinosa)的生存状态指数最高,禁牧样地中矮生嵩草(Kobresia humilis)和钝苞雪莲(Saussurea nigrescens)的生存状态指数最高,但随着放牧强度的增加,钝苞雪莲(Saussurea nigrescens)的生存状态指数也随之增加.研究结果表明放牧强度增加能提高高寒草甸群落多样性,禾草类生存状态和在群落中的优势地位下降,杂草类生存状态和在群落中的优势地位上升,草地质量下降.

全球气候变化背景下气温逐渐升高,将会对陆地生态系统碳循环产生重要影响.研究利用2003-2016年的涡度相关系统观测资料,研究了祁连山南麓高寒灌丛生长季(5月-9月)总初级生产力(gross primary productivity,GPP)在不同时间尺度上对生长季有效积温(growing season degree days,GDD)的响应,对于研究气候变暖对高寒生态系统碳循环的影响有重要意义.结果表明:高寒灌丛生态系统在生长季的月GPP、GDD都表现为先增大后减小的单峰变化趋势,都在7月或8月达到峰值,在5月达到最小值.在整个生长季尺度上,GPP与GDD具有较高变异性,但整体上表现为逐渐增加的趋势(P ＜0.05).2003-2016年整个生长季GPP与GDD的均值分别为507.11 g·m-2和975.93 ℃.在月尺度和生长季尺度上,GPP与GDD都呈显著正相关关系(P＜0.05).但是,通过比较生长季每个月GPP与GDD的关系发现,5、9月的GPP与GDD没有显著相关性(P ＞0.05),而在7月相关性最为显著(P ＜ 0.01).整体上看,高寒灌丛生态系统植被的总初级生产力与热量条件表现为正相关关系,由此说明在全球气候变暖的背景下,青藏高原高寒灌丛生态系统植被的光合生产能力将会提高.

全球气候变化引起的气温日较差(ADT)减小,将会对高寒生态系统的碳平衡造成深刻影响.基于涡度相关系统,利用2003-2016年的涡度相关系统观测资料,做了青藏高原高寒灌丛在生长季(6-9月)不同月份的ADT对CO2通量影响的研究.结果表明:2003-2016年的生长季中,最高气温(MaxTa)和最低气温(MinTa)呈先升高后降低的单峰变化趋势,ADT没有呈现明显的变化趋势.逐日总初级生产力(GPP)和生态系统呼吸(Re)呈先增加后降低的单峰趋势,逐日净生态系统CO2交换(NEE)呈先下降后上升的"V"型变化趋势.高寒灌丛在生长季为碳汇,整个生长季总NEE、GPP和Re平均值分别为(-161.2±30.1)、(501.9±60.2)、(340.7±54.4) gCm-2.在高寒灌丛生长季(6-9月)的每个月份,MaxTa、MinTa和ADT分别是GPP(P＜0.001)、Re(P＜0.001)和NEE(P＜0.01)变化的主要控制因子.高寒灌丛的ADT的增大有利于生态系统的碳固持,暗示在未来气候变化背景下ADT的减小将会削弱高寒灌丛生态系统的碳汇能力.

The amplitude of the diurnal temperature (ADT) has been decreasing under climate change, with substantial anticipated effects on alpine grassland carbon budgets. Here, we quantified the temporal response of the growing seasonal CO(2)fluxes to ADT over alpine shrubland on Qinghai-Tibetan Plateau (QTP) from 2003 to 2016. At a daily scale, net ecosystem exchange (NEE) and gross primary production (GPP) quadratically responded to ADT with optimum values of 15.4 and 13.4 degrees C, respectively. Ecosystem respiration (RES) negatively linearly correlated with ADT. Partial correlation, and classification and regression trees (CART) analysis, both showed that the maximal (MaxTa) or minimal air temperature (MinTa), rather than ADT, played much more important role in daily variations of CO(2)fluxes. At a monthly scale, GPP and NEE were both positively and negatively controlled by MaxTa while RES was negatively determined by MinTa, respectively. Monthly ADT exerted a negligible influence on monthly CO(2)fluxes. At an annual scale, only MaxTa played a significant role in variations of GPP and RES. NEE did not significantly respond to ADT, MaxTa or MinTa. The little direct correlations between NEE and ADT at daily, monthly or annual scales contradicts a previous hypothesis that a larger ADT would enhance carbon sequestration capacity over alpine ecosystems. Given the positive impact of MaxTa on GPP and MinTa on RES, our study would suggest that a decreasing ADT could indirectly stimulate more carbon loss and weaken the carbon sequestration capacity of alpine shrublands under the scenario of further increases in MinTa over QTP.

基于涡度相关系统,利用2004-2016年的涡度相关系统观测资料,做了青藏高原高寒湿地生长季总初级生产力(GPP)在不同时间尺度上对生长季有效积温(GDD)响应的研究.结果表明:高寒湿地生态系统在生长季的日GPP、GDD与月际GPP、GDD都表现为先增大后减小的单峰变化趋势,都在7月或8月达到峰值,在5月达到最小值.在整个生长季尺度上,GPP与GDD变异性较大,没有明显的变化趋势.2004-2016年整个生长季GPP与GDD的均值分别为(458.82±25.78)gCm-2季-1和(1060.89±84.07)℃.在日尺度、月尺度、生长季尺度上,GPP与GDD都呈极显著正相关关系(P＜0.01).但是,通过比较生长季分别每个月GPP与GDD的关系发现,5、9月的GPP与GDD没有显著相关性(P＞0.05),而在7月相关性最为显著(P＜0.01).整体上看,高寒湿地生态系统植被的总初级生产力与热量条件表现为正相关关系,由此说明在全球气候变暖的背景下,将会提高青藏高原高寒湿地生态系统植被的光合生产能力.

通过监测三江源玛沁县高寒草甸2017年度植被特征及土壤呼吸通量,探讨了不同退化阶段植被群落、土壤呼吸特征及其协同关系,并分析了土壤呼吸的温度敏感性.结果表明:随着高寒草甸退化程度加剧,禾本科植物重要值降低,毒杂草显著增加(P<0.05);植被盖度、物种数、多样性指数显著下降(P<0.05),重度退化阶段的地上生物量比轻度、中度退化阶段降低了25.36％、22.37％(P<0.05);在中度退化条件下,均匀度指数和地下生物量显著增多(P<0.05).在各退化阶段,土壤呼吸年内均呈单峰式变化过程,表现出生长季高、非生长季低的特征,植物生长旺季(7-8月)最高,且与5 cm深度处土壤温度之间呈显著指数关系(P<0.05);2017年轻度退化、中度退化和重度退化阶段的土壤呼吸碳排放总量分别为626.89 gC·m-2、386.66 gC·m-2、393.81 gC·m-2;同时,土壤呼吸与植被群落演替具有显著的协同性,随着退化程度加剧土壤呼吸速率下降.轻度退化、中度退化、重度退化阶段土壤呼吸的温度敏感性系数(Q10)分别为2.82、3.54和2.35,表明中度退化条件下的温度敏感性最强,重度退化条件下最弱.