2000-2011年广西植被净初级生产力时空分布特征及其驱动因素

受人类活动及自然环境影响,广西土壤酸化、水土流失及石漠化等问题比较严重,生态环境面临巨大压力。NPP能有效反映植物群落在自然环境中的生产能力,是评价生态服务功能的重要指标。利用2000—2011年MODIS归一化植被指数(NDVI)数据,基于光能利用率模型对广西植被净初级生产力(NPP)进行估算,分析其时空变化规律,探讨气象因子、植被类型、土壤类型、海拔高度及人类活动的影响。研究表明:近12年广西全区NPP总体呈增加趋势,在西南部地区上升较为明显,而在桂林、柳州等地区呈缓慢下降趋势。广西NPP与降水呈显著正相关关系,与温度相关性不显著;NPP值随海拔高度升高而增加;NPP时空变化特征随植被类型和土壤类型的不同而不同,其中栽培植被NPP不断上升,显示人类活动逐渐成为影响NPP变化的主要因素。     

2009-2011年我国西南地区旱灾程度及其对植被净初级生产力的影响

2009—2011年,我国西南地区遭受了极端干旱气候影响。利用1980—2011年气象站点观测数据和基于光能利用率的植被净初级生产力估算模型Glo PEM,研究了2009—2011年西南地区干旱灾害过程和程度及其对植被净初级生产力的影响,结果显示:2009—2011年西南地区年均降水量和湿润指数明显低于1980—2008年均值。受干旱气候影响,研究区植被净初级生产力比2001—2011年均值低12.55 g C m-2a-1,总计低0.017 Pg C/a,造成的碳损失约占我国总碳汇的7.91%。2001—2011年西南地区植被净初级生产力与蒸散量变化显著相关(R2=0.44,P0.05),而降水量和湿润指数变化过程与植被净初级生产力和蒸散量不同步,可能是由于该地区森林覆盖率较高,具有较强的涵养水源功能,导致土壤湿度变化滞后于降水量和湿润指数变化,从而使降水量变化过程与植被净初级生产力变化不同步。     

膜下滴灌对新疆棉田生态系统净初级生产力、土壤异氧呼吸和CO2净交换通量的影响

2009年4-10月,通过田间试验,以传统无膜漫灌为对照,研究了膜下滴灌对我国新疆棉田生态系统净初级生产力、土壤异氧呼吸和CO2净交换通量的影响.结果表明:膜下滴灌和无膜漫灌处理下,棉田生态系统净初级生产力、土壤异氧呼吸通量和CO2净交换通量均呈先增大后减小的变化趋势.与无膜漫灌相比,膜下滴灌显著提高了棉花地上、地下生物量和净初级生产力,降低了土壤异氧呼吸通量.在整个生长季节,膜下滴灌处理的年土壤异氧呼吸通量为214 g C·m-2,低于无膜漫灌处理的317 g C·m-2;膜下滴灌处理的棉花年净初级生产力为1030 g C·m-2,显著高于无膜漫灌处理的649 g C·m-2;膜下滴灌处理比无膜漫灌处理多固定大气CO2479 g C·m-2.膜下滴灌栽培措施既提高了作物生产力,又降低了土壤CO2排放,是干旱地区一种重要的农业固碳减排措施.     

2000—2015年秦巴山区植被净初级生产力时空变化及其趋动因子

基于2000—2015年MOD17A3数据及各驱动因素数据,辅以地统计学理论,利用趋势分析、Hurst指数及相关分析等方法,剖析秦巴山区近16年植被净初级生产力(NPP)时空变化特征,研究气候变化、土壤类型、地形因子、植被类型及人类活动等对植被NPP的影响.结果表明: 秦巴山区植被NPP空间上呈西南高、东北低的分布格局;时间上,近16年呈西北增、东北减的变化特征,在未来呈北部持续性、南部反持续性的发展态势.秦巴山区植被NPP与降雨量和气温呈正相关;暗棕壤、黄壤、紫色土和水稻土4种土壤类型的NPP均值明显高于其他土壤类型;不同植被类型的NPP存在空间分布和变化趋势的差异;NPP的高值主要分布在坡度25°～50°、海拔500～1000 m 以及大于2500 m的区域内;人类活动对NPP具有双重扰动性,表现为正向促进,反向抑制.     

2000—2015年秦巴山区植被净初级生产力时空变化及其驱动因子

基于2000—2015年MOD17A3数据及各驱动因素数据,辅以地统计学理论,利用趋势分析、Hurst指数及相关分析等方法,剖析秦巴山区近16年植被净初级生产力(NPP)时空变化特征,研究气候变化、土壤类型、地形因子、植被类型及人类活动等对植被NPP的影响.结果表明: 秦巴山区植被NPP空间上呈西南高、东北低的分布格局;时间上,近16年呈西北增、东北减的变化特征,在未来呈北部持续性、南部反持续性的发展态势.秦巴山区植被NPP与降雨量和气温呈正相关;暗棕壤、黄壤、紫色土和水稻土4种土壤类型的NPP均值明显高于其他土壤类型;不同植被类型的NPP存在空间分布和变化趋势的差异;NPP的高值主要分布在坡度25°～50°、海拔500～1000 m 以及大于2500 m的区域内;人类活动对NPP具有双重扰动性,表现为正向促进,反向抑制.     

Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data‐based evaluations of emergent ecosystem responses to climate and CO₂ at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO₂ in ten ecosystem models with the sensitivities found in tree‐ring reconstructions of NPP and raw ring‐width series at six temperate forest sites. These model‐data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO₂ in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree‐ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm‐growing season temperatures, while tree‐ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO₂ drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO₂ sensitivity. Fire in model simulations reduced model sensitivity to climate and CO₂, but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO₂ in individual models.     

Soil property,CO2 emission and aridity index as agroecological indicators to assess the mineralization of cover crop green manure in a Mediterranean environment

In this study soil chemical and biochemical properties, cover crop biomass production and quality, and climatic factors (AI) have been taken into account in order to identify sensitive agroecological indicators suitable for an early assessment of green manuring outcomes, measured in terms of soil CO₂ emission and soil mineralization dynamics in a short term experiment in a Mediterranean environment. The field experiment was conducted over two cropping rotations during 2004–2005 in central Italy. A winter cover crop/sweet pepper sequence with the cover crop used as green manure was adopted. The cover crop treatments were common vetch (CV), rye grass (RG), and fallow soil as the control (Control). Soil enzyme activities (acid phosphatase. protease and β-glucosidase), CO₂ emission, and inorganic nitrogen concentrations were monitored from cover crop green manure incorporation to pepper harvesting in order to evaluate soil mineralization dynamics. The climatic conditions were summarized by the monthly aridity index (AI) calculated as the precipitation/temperature ratio. A group of mineralization indexes, calculated using values of available nitrogen and enzyme activities, was used to describe the soil process during crop cycle after green manure. The mineralization process dynamic results as a combined effect of climatic conditions and soil organic matter quality produced by different cover crop green manures. The common vetch green manuring was effective in lowering the soil C/N with respect to the control soil (5.7 vs. 8.3 and 8.5 vs. 12.1 in 2004 and 2005, respectively), promoting CO₂ emission (8.95 vs. 5.19 and 6.75 vs. 4.28 Mg CO₂-C ha⁻¹ in 2004 and 2005, respectively), enzyme activity, nitrogen release, and crop aboveground biomass (8.59 vs. 7.05 Mg ha⁻¹ dry matter). Among the selected agroecological indicators, the relationships between enzyme activities and the monthly aridity index may suggest a new approach for agronomists and soil scientists to understand the combined effect of temperature and precipitation on soil mineralization dynamic. The high aridity index at the time of green manuring may have caused a priming effect of SOM and promoted soil mineralization during the vegetable crop growing season in a Mediterranean environment. Finally, no evidence was found between soil CO₂ emission and the aridity index; soil respiration was mainly affected by cover crop biomass and the soil C/N ratio.     

Leaf expansion,net CO2 uptake,Rubisco activity,and efficiency of long-term biomass gain for the common desert subshrub Encelia farinosa

Encelia farinosa is one of the most abundant and highly studied species of the Sonoran Desert, yet characteristics of its leaf development and long-term photosynthetic capacity are relatively unknown. The net CO₂ uptake rate and the Rubisco activity per unit leaf area for E. farinosa in a glasshouse increased in parallel for about 18 days after leaf emergence (leaf area was then 5 cm²), after which both were constant, suggesting that Rubisco levels controlled net CO₂ uptake. Instantaneous net CO₂ uptake rates at noon for well-watered E. farinosa in the glasshouse at different temperatures and light levels correctly predicted differences in daily net CO₂ uptake at four seasonally diverse times for transplanted plants under irrigated conditions in the field but overpredicted the daily means by 13%. After this correction, seasonally adjusted net CO₂ uptake per unit leaf area multiplied by the estimated monthly leaf area predicted that 42% of the net carbon gain was incorporated into plant dry weight over a 17-month period. The ecological success of E. farinosa apparently reflects an inherently high daily net CO₂ uptake and retention of a substantial fraction of its leaf carbon gain.     

Gross primary productivity and transpiration flux of the Australian vegetation from 1788 to 1988 AD: effects of CO2 and land use change

We present a novel approach to estimating the transpiration flux and gross primary productivity (GPP) from Normalized Difference Vegetation Index, leaf functional types, and readily available climate data. We use this approach to explore the impact of variations in the concentration of carbon dioxide in the atmosphere ([CO₂]) and consequent predicted changes in vegetation cover, on the transpiration flux and GPP. There was a near 1 : 1 relationship between GPP estimated with this transpiration flux approach and that estimated using a radiation‐use efficiency (RUE) approach. Model estimates are presented for the Australian continent under three vegetation–[CO₂] scenarios: the present vegetation and hypothetical ‘natural’ vegetation cover with atmospheric CO₂ concentration ([CO₂]) of 350 μmol mol^?1 (pveg₃₅₀ and nveg₃₅₀), and for the ‘natural’ vegetation with [CO₂] 280 μmol mol^?1 (nveg₂₈₀). Estimated continental GPP is 6.5, 6.3 and 4.3 Gt C yr^?1 for pveg₃₅₀, nveg₃₅₀ and nveg₂₈₀, respectively_. The corresponding transpiration fluxes are 232, 224 and 190 mm H₂O yr^?1. The contribution of the raingreen and evergreen components of the canopy to these fluxes are also estimated.     

Impact of CO2 enrichment on the regional evapotranspiration of agro-ecosystems,a theoretical and numerical modelling study

This paper gives a brief overview of factors determining evapotranspiration of vegetated surfaces. It indicates which of these factors are sensitive to CO₂ enrichment. A qualitative analysis is presented of the impact of large scale climate changes.Data in literature indicate that the surface resistance of vegetated areas may change within the range –25% and +50% if the atmospheric CO₂-concentration doubles. The impact of such changes on regional scale transpiration is evaluated using a numerical model in which the interaction between the evapotranspiration and the Planetary Boundary Layer is accounted for. It is concluded that the impact of CO₂ enrichment on the transpiration at the regional scale is relatively small for aerodynamically smooth surfaces (between +7% and –11%). For aerodynamically rough surfaces the effects are somewhat larger (between +15% and –21%).     

三江源地区人工草地的生态系统CO2净交换、总初级生产力及其影响因子

为了揭示三江源区垂穗披碱草(Elymus nutans)人工草地生态系统(100°26′-100°41′ E, 34°17′-34°25′ N, 海拔3 980 m)的净生态系统CO₂交换(NEE), 该研究利用2006年涡度相关系统观测的数据分析了该人工草地的NEE, 总初级生产力(GPP)、生态系统呼吸(R_eco)以及R_eco/GPP的变化特征及其影响因子。CO₂日最大吸收值为6.56 g CO₂·m^-2·d^-1, 最大排放值为4.87 g CO₂·m^-2·d^-1。GPP年总量为1 761 g CO₂·m^-2, 其中约90%以上被生态系统呼吸所消耗, CO₂的年吸收量为111 g CO₂·m^-2。5月的R_eco/GPP略高于生长季的其他月份, 为90%; 6月R_eco/GPP比值最低, 为79%。生态系统的呼吸商(Q₁₀)为4.81, 显著高于其他生态系统。该研究表明: 生长季的NEE主要受光量子通量密度(PPFD)、温度和饱和水汽压差(VPD)的影响, 生态系统呼吸则主要受土壤温度的控制。     

降水量和温度对植被覆盖指数影响的空间非平稳性特征——以新疆伊犁河谷地区为例

多变量空间相关分析多基于时间序列数据,对数据时长与统计要求严格,空间非平稳性特征分析可以利用单期数据分析多变量之间的相关性。通过空间变系数回归模型分析了2006年和2011年的新疆伊犁地区降水量和温度对植被覆盖度指数影响的空间变化特征,利用局部线性地理加权回归(GWR)方法估计得到了回归系数曲面,揭示出变量间相互影响的空间异质性,同时利用线性回归最小二乘估计进行了对比。结果表明:(1)空间变系数回归模型可以用于变量间的空间相关分析;(2)局部线性GWR估计方法明显优于线性回归最小二乘估计;(3)拟合结果表明,伊犁地区降水量和温度对植被覆盖指数的影响具有显著的空间非平稳性特征;(4)模型估计误差是降水、气温之外的地形、地貌及人类活动等多种因素造成的,需进一步研究。方法可为具有空间非平稳性特征变量间空间相关性分析以及植被覆盖指数的空间模拟分布提供思路和方法。     

Integration of CO2 flux and remotely-sensed data for primary production and ecosystem respiration analyses in the Northern Great Plains: potential for quantitative spatial extrapolation

Aim Extrapolation of tower CO₂ fluxes will be greatly facilitated if robust relationships between flux components and remotely sensed factors are established. Long‐term measurements at five Northern Great Plains locations were used to obtain relationships between CO₂ fluxes and photosynthetically active radiation (Q), other on‐site factors, and Normalized Difference Vegetation Index (NDVI) from the SPOT VEGETATION data set. Location CO₂ flux data from the following stations and years were analysed: Lethbridge, Alberta 1998–2001; Fort Peck, MT 2000, 2002; Miles City, MT 2000–01; Mandan, ND 1999–2001; and Cheyenne, WY 1997–98. Results Analyses based on light‐response functions allowed partitioning net CO₂ flux (F) into gross primary productivity (P_g) and ecosystem respiration (R_e). Weekly averages of daytime respiration, γ_day, estimated from light responses were closely correlated with weekly averages of measured night‐time respiration, γ_night (R² 0.64 to 0.95). Daytime respiration tended to be higher than night‐time respiration, and regressions of γ_day on γ_night for all sites were different from 1 : 1 relationships. Over 13 site‐years, gross primary production varied from 459 to 2491 g CO₂ m^?2 year^?1, ecosystem respiration from 996 to 1881 g CO₂ m^?2 year^?1, and net ecosystem exchange from ?537 (source) to +610 g CO₂ m^?2 year^?1 (sink). Maximum daily ecological light‐use efficiencies, ?_d,max = P_g/Q, were in the range 0.014 to 0.032 mol CO₂ (mol incident quanta)^?1. Main conclusions Ten‐day average P_g was significantly more highly correlated with NDVI than 10‐day average daytime flux, P_d (R² = 0.46 to 0.77 for P_g‐NDVI and 0.05 to 0.58 for P_d‐NDVI relationships). Ten‐day average R_e was also positively correlated with NDVI, with R² values from 0.57 to 0.77. Patterns of the relationships of P_g and R_e with NDVI and other factors indicate possibilities for establishing multivariate functions allowing scaling‐up local fluxes to larger areas using GIS data, temporal NDVI, and other factors.     

Partitioning of the net CO2 exchange using an automated chamber system reveals plant phenology as key control of production and respiration fluxes in a boreal peatland

The net ecosystem CO₂ exchange (NEE) drives the carbon (C) sink–source strength of northern peatlands. Since NEE represents a balance between various production and respiration fluxes, accurate predictions of its response to global changes require an in depth understanding of these underlying processes. Currently, however, detailed information of the temporal dynamics as well as the separate biotic and abiotic controls of the NEE component fluxes is lacking in peatland ecosystems. In this study, we address this knowledge gap by using an automated chamber system established across natural and trenching/vegetation removal plots to partition NEE into its production (i.e., gross and net primary production; GPP and NPP) and respiration (i.e., ecosystem, heterotrophic and autotrophic respiration; ER, Rh and Ra) fluxes in a boreal peatland in northern Sweden. Our results showed that daily NEE patterns were driven by GPP while variations in ER were governed by Ra rather than Rh. Moreover, we observed pronounced seasonal shifts in the Ra/Rh and above/belowground NPP ratios throughout the main phenological phases. Generalized linear model analysis revealed that the greenness index derived from digital images (as a proxy for plant phenology) was the strongest control of NEE, GPP and NPP while explaining considerable fractions also in the variations of ER and Ra. In addition, our data exposed greater temperature sensitivity of NPP compared to Rh resulting in enhanced C sequestration with increasing temperature. Overall, our study suggests that the temporal patterns in NEE and its component fluxes are tightly coupled to vegetation dynamics in boreal peatlands and thus challenges previous studies that commonly identify abiotic factors as key drivers. These findings further emphasize the need for integrating detailed information on plant phenology into process‐based models to improve predictions of global change impacts on the peatland C cycle.     

Gross primary production responses to warming,elevated CO2, and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland

Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO₂ (eCO₂) and warming requires accurate quantification of gross primary production (GPP), the largest flux of C in the global C cycle. We evaluated 6 years (2007–2012) of flux‐derived GPP data from the Prairie Heating and CO₂ Enrichment (PHACE) experiment, situated in a grassland in Wyoming, USA. The GPP data were used to calibrate a light response model whose basic formulation has been successfully used in a variety of ecosystems. The model was extended by modeling maximum photosynthetic rate (A_max) and light‐use efficiency (Q) as functions of soil water, air temperature, vapor pressure deficit, vegetation greenness, and nitrogen at current and antecedent (past) timescales. The model fits the observed GPP well (R² = 0.79), which was confirmed by other model performance checks that compared different variants of the model (e.g. with and without antecedent effects). Stimulation of cumulative 6‐year GPP by warming (29%, P = 0.02) and eCO₂ (26%, P = 0.07) was primarily driven by enhanced C uptake during spring (129%, P = 0.001) and fall (124%, P = 0.001), respectively, which was consistent across years. Antecedent air temperature (Tair_ant) and vapor pressure deficit (VPD_ant) effects on A_max (over the past 3–4 days and 1–3 days, respectively) were the most significant predictors of temporal variability in GPP among most treatments. The importance of VPD_ant suggests that atmospheric drought is important for predicting GPP under current and future climate; we highlight the need for experimental studies to identify the mechanisms underlying such antecedent effects. Finally, posterior estimates of cumulative GPP under control and eCO₂ treatments were tested as a benchmark against 12 terrestrial biosphere models (TBMs). The narrow uncertainties of these data‐driven GPP estimates suggest that they could be useful semi‐independent data streams for validating TBMs.     

潮汐作用下干湿交替对黄河三角洲盐沼湿地净生态系统CO2交换的影响

潮汐作用作为盐沼湿地独特的水文特征能在短时间内强烈影响盐沼湿地的碳平衡.利用涡度相关和微气象监测技术,对黄河三角洲盐沼湿地净生态系统CO₂交换(NEE)和环境因子进行监测,并同步监测潮汐变化,探究潮汐过程及潮汐作用下干湿交替对NEE的影响.结果表明: 潮汐过程促进了白天生态系统CO₂的吸收但未对夜晚CO₂的释放产生显著影响,潮汐淹水成为影响白天NEE的主要因子.干旱阶段和湿润阶段NEE的日平均动态均呈“U”型曲线,但干旱阶段NEE的变幅较小.干湿交替增强了白天生态系统CO₂的吸收,干旱阶段最大光合速率(A_max)、表观量子产量(α)和生态系统呼吸(R_eco)的均值均高于湿润阶段.此外,干湿交替减少了盐沼湿地夜晚NEE释放的同时增强了其温度敏感性.