Application and comparison of remote sensing GPP models with multi-site data in China北大核心CSCD

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.     

Coupling between carbon cycling and climate in a high-elevation,subalpine forest: a model-data fusion analysis

Fundamental questions exist about the effects of climate on terrestrial net ecosystem CO₂ exchange (NEE), despite a rapidly growing body of flux observations. One strategy to clarify ecosystem climate–carbon interactions is to partition NEE into its component fluxes, gross ecosystem CO₂ exchange (GEE) and ecosystem respiration (R _E), and evaluate the responses to climate of each component flux. We separated observed NEE into optimized estimates of GEE and R _E using an ecosystem process model combined with 6 years of continuous flux data from the Niwot Ridge AmeriFlux site. In order to gain further insight into the processes underlying NEE, we partitioned R _E into its components: heterotrophic (R _H) and autotrophic (R _A) respiration. We were successful in separating GEE and R _E, but less successful in accurately partitioning R _E into R _A and R _H. Our failure in the latter was due to a lack of adequate contrasts in the assimilated data set to distinguish between R _A and R _H. We performed most model runs at a twice-daily time step. Optimizing on daily-aggregated data severely degraded the model’s ability to separate GEE and R _E. However, we gained little benefit from using a half-hourly time step. The model-data fusion showed that most of the interannual variability in NEE was due to variability in GEE, and not R _E. In contrast to several previous studies in other ecosystems, we found that longer growing seasons at Niwot Ridge were correlated with less net CO₂ uptake, due to a decrease of available snow-melt water during the late springtime photosynthetic period. Warmer springtime temperatures resulted in increased net CO₂ uptake only if adequate moisture was available; when warmer springtime conditions led into mid-summer drought, the annual net uptake declined.     

北京永定河沿河沙地杨树人工林光能利用效率

光能利用效率(LUE)是影响生态系统生产力大小和质量的主要因素。以位于北京市大兴区永定河沿河沙地的杨树(欧美107/108,Populus euramericana cv.)人工林生态系统作为研究对象,依托涡度相关观测系统,对该生态系统的LUE进行研究,从而确定LUE在不同时间尺度上的影响因子,并确定最大光能利用利用效率(LUEmax)。结果表明:LUE存在明显的季节变化趋势,4月份生长季开始后LUE迅速升高,到7—8月达到最大,而后逐渐降低;在生长季不同阶段,LUE日动态的影响因子不同:4月份气温(Ta)、蒸散比(EF)和饱和水汽压差(VPD)是影响LUE日动态的主要因子,7、8月份光合有效辐射(PAR)和冠层导度(gc)是主要影响因子,5—6月与9—10月LUE日动态则与土壤水分(VWC)有较大关系;而LUE月动态则与月蒸散比(EFm)和月平均土壤温度(Tsm)有关。由于该人工林各月光能利用最适宜环境条件不同,各月LUEmax也各有差异,该生态系统年LUEmax为0.44 g C/MJ PAR,7、8月LUEmax最大,分别为0.66和0.69 g C/MJ PAR。研究结果表明,在利用光能利用模型进行区域乃至全球初级生产力估算时需要根据研究的不同时间尺度确定LUEmax。     

生物生产力的“4P”概念、估算及其相互关系

生物生产力是指从个体、群体到生态系统、区域乃至生物圈等不同生命层次的物质生产能力,它决定着系统的物质循环和能量流动,也是指示系统健康状况的重要指标。表示生物生产力的概念有总初级生产力（GP P）、净初级生产力（NPP）、净态生态系统生产力（NEP）和净生物群区生产力（NBP）,本文简称“4P”。主要探讨了“4P”概念的内涵和估算以及全球变化对它们的影响;通过生态系统的碳循环,建立“4P” 之间的相互联系,并对若干衍生概念进行定义。尽管生态系统的最终产物（NBP或现存量）占光合总产量的很少一部分,但它是决定物质再生物的资本,维持和决定生态系统的物质再生产。     

Measurement of net ecosystem exchange,productivity and respiration in three spruce forests in Sweden shows unexpectedly large soil carbon losses

Measurement of net ecosystem exchange was made using the eddy covariance method above three forests along a north-south climatic gradient in Sweden: Flakaliden in the north, Knottåsen in central and Asa in south Sweden. Data were obtained for 2 years at Flakaliden and Knottåsen and for one year at Asa. The net fluxes (N_ep) were separated into their main components, total ecosystem respiration (R_t) and gross primary productivity (P_g). The maximum half-hourly net uptake during the heart of the growing season was highest in the southernmost site with ?0.787 mg CO₂ m^?2 s^?1 followed by Knottåsen with ?0.631 mg CO₂ m^?2 s^?1 and Flakaliden with ?0.429 mg CO₂ m^?2 s^?1. The maximum respiration rates during the summer were highest in Knottåsen with 0.245 mg CO₂ m^?2 s^?1 while it was similar at the two other sites with 0.183 mg CO₂ m^?2 s^?1. The annual N_ep ranged between uptake of ?304 g C m^?2 year^?1 (Asa) and emission of 84 g C m^?2 year^?1 (Knottåsen). The annual R_t and P_g ranged between 793 to 1253 g C m^?2 year^?1 and ?875 to ?1317 g C m^?2 year^?1, respectively. Biomass increment measurements in the footprint area of the towers in combination with the measured net ecosystem productivity were used to estimate the changes in soil carbon and it was found that the soils were losing on average 96–125 g C m^?2 year^?1. The most plausible explanation for these losses was that the studied years were much warmer than normal causing larger respiratory losses. The comparison of net primary productivity and P_g showed that ca 60% of P_g was utilized for autotrophic respiration.     

Coral reef benthic productivity based on optical absorptance and light-use efficiency

In the interest of determining productivity across a range of spatial scales (meters to many kilometers) and in different reef environments, this paper proposes a technique for measuring productivity based on remote sensing of optical absorptance and light-use efficiency. The concept is straightforward: gross primary production equals plant-incident irradiance multiplied by plant absorptance multiplied by the plant’s light-use efficiency (GPP = E _d Aε). Both E _d and A are derivable from various remote sensing data sources, thus the approach is feasible. This paper presents a demonstration of the application for Kaneohe Bay, Oahu, HI based on Quickbird satellite imagery and SHOALS LIDAR data. E _d is modeled at every point in the image, and the image itself is inverted to provide A. Organismal-scale ε reported in the literature is taken as a surrogate for community-scale ε. The resulting GPP image compares well with the range of GPP values for reef-flats in general, as well as the distribution and range of GPP for Kaneohe Bay in particular. Though results likely can be improved by using spectral imagery and more accurate values for ε, this concept study demonstrates the tractability of this approach for measuring coral reef GPP.     

鼎湖山森林群落的光能利用效率

本文研究了鼎湖山自然保护区,亚热带季风常绿阔叶林和针叶阔叶混交林的光能利用效率。根据群落的垂直结构和成层现象,应用红外线CO_2气体分析法,分层测定了主要植物22种58株的光合速率.计算了群落的生产力;用量子传感器分层测定了两个群落的光合有效辐射,并计算其光能利用效率。结果表明:阔叶林总生产力的光能利用效率为14.28%,混交林为12.01%,说明了不同森林类型对光能资源的利用效率。     

Estimating crop yield using a satellite-based light use efficiency model

Satellite-based techniques that provide temporally and spatially continuous information over vegetated surfaces have become increasingly important in monitoring the global agriculture yield. In this study, we examine the performance of a light use efficiency model (EC-LUE) for simulating the gross primary production (GPP) and yield of crops. The EC-LUE model can explain on average approximately 90% of the variability in GPP for 36 FLUXNET sites globally. The results indicate that a universal set of parameters, independent of crop species (except for C4 crops), can be adopted in the EC-LUE model for simulating crops’ GPP. At both irrigated and rainfed sites, the EC-LUE model exhibits a similar level of performance. However, large errors are found when simulating yield based on crop harvest index. This analysis highlights the need to improve the representation of the harvest index and carbon allocation for improving crop yield estimations from satellite-based methods.     

中国干旱半干旱区植被降水利用效率时空变化特征及影响因素分析

植被的降水利用效率（Precipitation use efficiency,PUE）是表征植被生产力对降水量时空动态变化响应特征的重要指示器,对了解干旱环境下植被生产力的变化尤为关键。基于中国干旱半干旱区2000-2020年的植被净初级生产力、降水量、气温、土地利用类型和地形等数据,分析了中国干旱半干旱区植被降水利用效率的时空特征及其变化趋势,探究了植被PUE与气候因子的关联以及气候变化下土地利用和地形对植被PUE的影响。研究结果表明：（1）2000-2020年中国干旱半干旱区植被平均PUE为0.41 g C m^-2 mm^-1,不同土地利用类型下植被PUE的大小顺序为：草地<湿地<灌木<耕地<林地。（2）植被PUE年际变化整体呈现波动上升趋势,上升速率为0.004 g C m^-2 mm^-1,其中呈现显著改善趋势的面积占总面积的12.24%。（3）气温升高在不同程度上对大多数植被PUE起到促进作用,而降水增多则会抑制绝大多数区域的植被PUE。植被较少的区域,植被降水利用效率与气温、降水两气候因子基本无关。（4）随着海拔的升高,植被PUE呈现出先减后增再减的趋势。随着海拔的变化,气温依然与植被PUE呈正相关,降水依然与植被PUE呈负相关。研究结果可为中国干旱半干旱区生态系统保护、恢复以及可持续利用提供科学参考。     

CO2 balance of boreal, temperate, and tropical forests derived from a global database

Terrestrial ecosystems sequester 2.1 Pg of atmospheric carbon annually. A large amount of the terrestrial sink is realized by forests. However, considerable uncertainties remain regarding the fate of this carbon over both short and long timescales. Relevant data to address these uncertainties are being collected at many sites around the world, but syntheses of these data are still sparse. To facilitate future synthesis activities, we have assembled a comprehensive global database for forest ecosystems, which includes carbon budget variables (fluxes and stocks), ecosystem traits (e.g. leaf area index, age), as well as ancillary site information such as management regime, climate, and soil characteristics. This publicly available database can be used to quantify global, regional or biome‐specific carbon budgets; to re‐examine established relationships; to test emerging hypotheses about ecosystem functioning [e.g. a constant net ecosystem production (NEP) to gross primary production (GPP) ratio]; and as benchmarks for model evaluations. In this paper, we present the first analysis of this database. We discuss the climatic influences on GPP, net primary production (NPP) and NEP and present the CO₂ balances for boreal, temperate, and tropical forest biomes based on micrometeorological, ecophysiological, and biometric flux and inventory estimates. Globally, GPP of forests benefited from higher temperatures and precipitation whereas NPP saturated above either a threshold of 1500 mm precipitation or a mean annual temperature of 10 °C. The global pattern in NEP was insensitive to climate and is hypothesized to be mainly determined by nonclimatic conditions such as successional stage, management, site history, and site disturbance. In all biomes, closing the CO₂ balance required the introduction of substantial biome‐specific closure terms. Nonclosure was taken as an indication that respiratory processes, advection, and non‐CO₂ carbon fluxes are not presently being adequately accounted for.     

任豆林的生物量和光能利用率

 本文研究了粤北石灰岩地区以任豆(Zenia insignis)为主的自然林(萌生34年)的生产能力,并与任豆人工林(6年生)作对照。结果表明,在1992年7月调查时,自然林和人工林的现存生物量分别是125.38和10.34t·hm-2;平均增长量为3.69和1.72t·hm-2·a-1;木材蓄积量为86.35和9.93m3·hm-2;其乔木层总生产力为84284和21510kJ·m-2·a-1;对光合有效辐射能的利用效率为5.43％和1.39％。反映了任豆自然林现存生物量和生产力比鼎湖山南亚热带常绿阔叶林(同龄萌生林,在1991年11月调查)现存生物量196t·hm-2低,而比热带和亚热带半干早区森林植物量分别107和98.7t·hm-2高。任豆人工林因盖度和叶面积指数比自然林低,故总生产力和光能利用率也比较低,说明任豆人工林尚有较高的生产潜力。     

植物与微生物碳利用效率及影响因子研究进展

陆地生态系统碳循环是生物地球化学循环的关键过程之一。碳利用效率（carbon use efficiency,CUE）是描述生物用于形成生物量的碳占其所吸收总碳比例的一个定量指标,反映了生物的碳同化能力和固碳潜力,是研究生态系统碳循环中碳通量和碳分配模式的重要参数,能有效预测生物与周围环境之间的碳流通和碳反馈。目前,关于CUE的研究还不充分,尤其是对CUE及其影响因子的系统性综合论述还较少。为此,本文综述了国内外有关碳利用效率（植物碳利用效率（CUE_a）和微生物碳利用效率（CUE_h））的研究方法和研究进展,分析了CUE_a和CUE_h的异同、内在联系及作用机理。基于分析对今后的研究提出几点展望：（1）优化测量手段和计算方法,适当地调整参数,将模型方法与实测数据结合,使CUE的定量描述结果更准确;（2）结合不同尺度的研究结果,探究个体、种群、群落、生态系统等不同空间尺度和时间尺度上CUE的联系及变化规律,为碳循环和碳流通的时空变化规律提供新证据;（3）研究CUE对全球变化（如高温、干旱、CO₂浓度增加等）的响应,探讨CUE对未来气候情景的响应和适应机制;（4）开展有关物种丰富度或生物多样性的梯度变化对CUE的影响研究,阐释物种多样性减少或物种灭绝等现象对碳循环过程的影响,将生态系统物种多样性与生态系统功能相联系;（5）加强对CUE_h的研究,定量探究其与CUE_a的异同,并将二者结合起来,更全面地解释地上-地下生态系统碳的分配特征。同时适当开展动物CUE的研究,目前该类研究还缺乏系统性。     

Water and energy footprints of bioenergy crop production on marginal lands

Water and energy demands associated with bioenergy crop production on marginal lands are inextricably linked with land quality and land use history. To illustrate the effect of land marginality on bioenergy crop yield and associated water and energy footprints, we analyzed seven large‐scale sites (9–21 ha) converted from either Conservation Reserve Program (CRP) or conventional agricultural land use to no‐till soybean for biofuel production. Unmanaged CRP grassland at the same location was used as a reference site. Sites were rated using a land marginality index (LMI) based on land capability classes, slope, soil erodibility, soil hydraulic conductivity, and soil tolerance factors extracted from a soil survey (SSURGO) database. Principal components analysis was used to develop a soil quality index (SQI) for the study sites based on 12 soil physical and chemical properties. The water and energy footprints on these sites were estimated using eddy‐covariance flux techniques. Aboveground net primary productivity was inversely related to LMI and positively related to SQI. Water and energy footprints increased with LMI and decreased with SQI. The water footprints for grain, biomass and energy production were higher on lands converted from agricultural land use compared with those converted from the CRP land. The sites which were previously in the CRP had higher SQI than those under agricultural land use, showing that land management affects water footprints through soil quality effects. The analysis of biophysical characteristics of the sites in relation to water and energy use suggests that crops and management systems similar to CRP grasslands may provide a potential strategy to grow biofuels that would minimize environmental degradation while improving the productivity of marginal lands.     

遥感GPP模型在中亚干旱区4个典型生态系统的适用性评价

总初级生产力(GPP)是全球生态系统碳循环的重要组成部分,对全球气候变化有重要影响。目前有多种遥感模型可以模拟总初级生产力,比较不同遥感模型在中亚干旱区上的适用性对推进全球干旱区碳收支估算具有重要意义。基于涡度协相关技术观测的四个地面站数据验证MOD17、VODCA2、VPM、TG、SANIRv五种模型的模拟精度。结果表明：(1)基于光能利用率理论的MOD17、VPM模型模拟咸海荒漠植被和阜康荒漠植被GPP的精度最高(R²分别为0.52和0.80),但在模拟草地、农田生态系统生产力时存在较明显的低估(RE>20%);基于植被指数的遥感模型TG模型、SANIRv模型模拟巴尔喀什湖草地生态系统和乌兰乌苏农田生态系统GPP的精度最高(R²分别为0.91和0.81),同时模拟值与实测值的相对误差也较低;基于微波的VODCA2模型模拟各生态系统生产力的效果最差。(2)水分亏缺是限制植被GPP的主要因素,因此是否合理考虑水分胁迫是影响GPP模型在中亚干旱区适用性的重要因素。研究揭示了遥感GPP模型在中亚干旱区的应用潜力,为推进全球植被碳通量的准确估...