Spatiotemporal changes of gross primary productivity and its response to drought in the Mongolian Plateau under climate change

Gross primary productivity(GPP)of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought.Understanding the impact of droughts on different types of vegetation GPP provides insight into the spatiotemporal variation of terrestrial carbon sinks,aiding efforts to mitigate the detrimental effects of climate change.In this study,we utilized the precipitation and temperature data from the Climatic Research Unit,the standardized precipitation evapotranspiration index(SPEI),the standardized precipitation index(SPI),and the simulated vegetation GPP using the eddy covariance-light use efficiency(EC-LUE)model to analyze the spatiotemporal change of GPP and its response to different drought indices in the Mongolian Plateau during 1982-2018.The main findings indicated that vegetation GPP decreased in 50.53% of the plateau,mainly in its northern and northeastern parts,while it increased in the remaining 49.47%area.Specifically,meadow steppe(78.92%)and deciduous forest(79.46%)witnessed a significant decrease in vegetation GPP,while alpine steppe(75.08%),cropland(76.27%),and sandy vegetation(87.88%)recovered well.Warming aridification areas accounted for 71.39% of the affected areas,while 28.53% of the areas underwent severe aridification,mainly located in the south and central regions.Notably,the warming aridification areas of desert steppe(92.68%)and sandy vegetation(90.24%)were significant.Climate warming was found to amplify the sensitivity of coniferous forest,deciduous forest,meadow steppe,and alpine steppe GPP to drought.Additionally,the drought sensitivity of vegetation GPP in the Mongolian Plateau gradually decreased as altitude increased.The cumulative effect of drought on vegetation GPP persisted for 3.00-8.00 months.The findings of this study will improve the understanding of how drought influences vegetation in arid and semi-arid areas.

Responses of gross primary productivity to different sizes of precipitation events in a temperate grassland ecosystem in Inner Mongolia, China

Changes in the sizes of precipitation events in the context of global climate change may have profound impacts on ecosystem productivity in arid and semiarid grasslands. However, we still have little knowledge about to what extent grassland productivity will respond to an individual precipitation event. In this study, we quantified the duration, the maximum, and the time-integrated amount of the response of daily gross primary productivity (GPP) to an individual precipitation event and their variations with different sizes of precipitation events in a typical temperate steppe in Inner Mongolia, China. Results showed that the duration of GPP-response (τR) and the maximum absolute GPP-response (GPPmax) increased linearly with the sizes of precipitation events (Pes), driving a corresponding increase in time-integrated amount of the GPP-response (GPPtotal) because variations of GPPtotal were largely explained by τR and GPPmax. The relative contributions of these two parameters to GPPtotal were strongly Pes-dependent. The GPPmax contributed more to the variations of GPPtotal when Pes was relatively small (<20 mm), whereas τR was the main driver to the variations of GPPtotal when Pes was relatively large. In addition, a threshold size of at least 5 mm of precipitation was required to induce a GPP-response for the temperate steppe in this study. Our work has important implications for the modeling community to obtain an advanced understanding of productivity-response of grassland ecosystems to altered precipitation regimes.

Sensitivity of Near Real-time MODIS Gross Primary Productivity in Terrestrial Forests Based on Eddy Covariance Measurements

As an important product of Moderate Resolution Imaging Spectroradiometer(MODIS), MOD17A2 provides dramatic improvements in our ability to accurately and continuously monitor global terrestrial primary production, which is also significant in effort to advance scientific research and eco-environmental management. Over the past decades, forests have moderated climate change by sequestrating about one-quarter of the carbon emitted by human activities through fossil fuels burning and land use/land cover change. Thus, the carbon uptake by forests reduces the rate at which carbon accumulates in the atmosphere. However, the sensitivity of near real-time MODIS gross primary productivity(GPP) product is directly constrained by uncertainties in the modeling process, especially in complicated forest ecosystems. Although there have been plenty of studies to verify MODIS GPP with ground-based measurements using the eddy covariance(EC) technique, few have comprehensively validated the performance of MODIS estimates(Collection 5) across diverse forest types. Therefore, the present study examined the degree of correspondence between MODIS-derived GPP and EC-measured GPP at seasonal and interannual time scales for the main forest ecosystems, including evergreen broadleaf forest(EBF), evergreen needleleaf forest(ENF), deciduous broadleaf forest(DBF), and mixed forest(MF) relying on 16 flux towers with a total of 68 site-year datasets. Overall, site-specific evaluation of multi-year mean annual GPP estimates indicates that the current MOD17A2 product works highly effectively for MF and DBF, moderately effectively for ENF, and ineffectively for EBF. Except for tropical forest, MODIS estimates could capture the broad trends of GPP at 8-day time scale for all other sites surveyed. On the annual time scale, the best performance was observed in MF, followed by ENF, DBF, and EBF. Trend analyses also revealed the poor performance of MODIS GPP product in EBF and DBF. Thus, improvements in the sensitivity of MOD17A2 to forest productivity require continued efforts.

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.

Effects of climate change on phenology and primary productivity in the desert steppe of Inner Mongolia

Variations in temperature and precipitation affect local ecosystems. Considerable spatial and temporal heterogeneity exists in arid ecosystems such as desert steppes. In this study, we analyzed the spatiotemporal dy- namics of climate and vegetation phenology in the desert steppe of Inner Mongolia, China using meteorological data （1961-2010） from 11 stations and phenology data （2004-2012） from 6 ecological observation stations. We also estimated the gross primary production for the period of 1982-2009 and found that the annual mean tem- perature increased at a rate of 0.47~C/decade during 1961-2010, with the last 10 years being consistently warmer than the 50 years as an average. The most significant warming occurred in winters. Annual precipitation slightly decreased during the 50-year period, with summer precipitation experiencing the highest drop in the last 10 years, and spring precipitation, a rise. Spatially, annual precipitation increased significantly in the northeastern and eastern central areas next to the typical steppe. From 2004 to 2012, vegetation green-up and senescence date advanced in the study area, shortening the growing season. Consequently, the primary productivity of the desert steppe de- creased along the precipitation gradient from southeast to northwest. Temporally, productivity increased during the period of 1982-1999 and significantly decreased after 2000. Overall, the Last decade witnessed the most dramatic climatic changes that were likely to negatively affect the desert steppe ecosystem. The decreased primary produc- tivity, in particular, decreases ecosystem resilience and impairs the livelihood of local farmers and herdsmen.

Response of Growing Season Gross Primary Production to El Nino in Different Phases of the Pacific Decadal Oscillation over Eastern China Based on Bayesian Model Averaging

Gross primary production(GPP) plays a crucial part in the carbon cycle of terrestrial ecosystems.A set of validated monthly GPP data from 1957 to 2010 in 0.5°× 0.5° grids of China was weighted from the Multi-scale Terrestrial Model Intercomparison Project using Bayesian model averaging(BMA).The spatial anomalies of detrended BMA GPP during the growing seasons of typical El Nino years indicated that GPP response to El Nino varies with Pacific Decadal Oscillation(PDO) phases: when the PDO was in the cool phase,it was likely that GPP was greater in northern China(32°–38°N,111°–122°E) and less in the Yangtze River valley(28°–32°N,111°–122°E);in contrast,when PDO was in the warm phase,the GPP anomalies were usually reversed in these two regions.The consistent spatiotemporal pattern and high partial correlation revealed that rainfall dominated this phenomenon.The previously published findings on how El Nino during different phases of PDO affecting rainfall in eastern China make the statistical relationship between GPP and El Nino in this study theoretically credible.This paper not only introduces an effective way to use BMA in grids that have mixed plant function types,but also makes it possible to evaluate the carbon cycle in eastern China based on the prediction of El Nino and PDO.

Responses in gross primary production of Stipa krylovii and Allium polyrhizum to a temporal rainfall in a temperate grassland of Inner Mongolia, China

In the arid and semi-arid areas of China, rainfall and drought affect the growth and photosynthetic activities of plants.Gross primary productivity(GPP) is one of the most important indices that measure the photosynthetic ability of plants.This paper focused on the GPP of two representative grassland species(Stipa krylovii Roshev.and Allium polyrhizum Turcz.ex Regel) to demonstrate the effect of a temporal rainfall on the two species.Our research was conducted in a temperate grassland in New Barag Right Banner, Hulun Buir City, Inner Mongolia Autonomous Region of China, in a dry year 2015.We measured net ecosystem productivity(NEP) and ecosystem respiration flux(ER) using a transparent chamber system and monitored the photosynthetically active radiation(PAR), air and soil temperature and humidity simultaneously.Based on the measured values of NEP and ER, we calculated the GPP of the two species before and after the rainfall.The saturated GPP per aboveground biomass(GPPAGB) of A.polyrhizum remarkably increased from 0.033(±0.018) to 0.185(±0.055) μmol CO2/(gdw·s) by 5.6-fold and that of S.krylovii decreased from 0.068(±0.021) to 0.034(±0.011) μmol CO2/(gdw·s) by 0.5-fold on the 1st and 2nd d after a 9.1 mm rainfall event compared to the values before the rainfall at low temperatures below 35℃.However, on the 1st and 2nd d after the rainfall, both of the saturated GPPAGB values of S.krylovii and A.polyrhizum were significantly lower at high temperatures above 35℃(0.018(±0.007) and 0.110(±0.061) μmol CO2/(gdw·s), respectively) than at low temperatures below 35℃(0.034(±0.011) and 0.185(±0.055) μmol CO2/(gdw·s), respectively).The results showed that the GPP responses to the temporal rainfall differed between S.krylovii and A.polyrhizum and strongly negative influenced by temperature.The temporal rainfall seems to be more effective on the GPP of A.polyrhizum than S.krylovii.These differences might be related to the different physiological and structural features, the coexistence of the species and their species-specific survival strategies.

Ocean-atmosphere Teleconnections Play a Key Role in the Interannual Variability of Seasonal Gross Primary Production in China

Since the 1950s,the terrestrial carbon uptake has been characterized by interannual variations,which are mainly determined by interannual variations in gross primary production(GPP).Using an ensemble of seven-member TRENDY(Trends in Net Land-Atmosphere Carbon Exchanges)simulations during 1951-2010,the relationships of the interannual variability of seasonal GPP in China with the sea surface temperature(SST)and atmospheric circulations were investigated.The GPP signals that mostly relate to the climate forcing in terms of Residual Principal Component analysis(hereafter,R-PC)were identified by separating out the significant impact from the linear trend and the GPP memory.Results showed that the seasonal GPP over China associated with the first R-PC1(the second R-PC2)during spring to autumn show a monopole(dipole or tripole)spatial structure,with a clear seasonal evolution for their maximum centers from springtime to summertime.The dominant two GPP R-PC are significantly related to Sea Surface Temperature(SST)variability in the eastern tropical Pacific Ocean and the North Pacific Ocean during spring to autumn,implying influences from the El Niño-Southern Oscillation(ENSO)and the Pacific Decadal Oscillation(PDO).The identified SST and circulation factors explain 13%,23%and 19%of the total variance for seasonal GPP in spring,summer and autumn,respectively.A clearer understanding of the relationships of China’s GPP with ocean-atmosphere teleconnections over the Pacific and Atlantic Ocean should provide scientific support for achieving carbon neutrality targets.

Modeling Gross Primary Production by Integrating Satellite Data and Coordinated Flux Measurements in Arid and Semi-Arid China

Assessing large-scale patterns of gross primary production (GPP) in arid and semi-arid (ASA) areas is important for both scientific and practical purposes.Remote sensing-based models,which integrate satellite data with input from ground-based meteorological measurements and vegetation characteristics,improve spatially extended estimates of vegetation productivity with high accuracy.In this study,the authors simulated GPP in ASA areas by integrating moderate resolution imaging spectral radiometer (MODIS) data with eddy covariance and meteorological measurements at the flux tower sites using the Vegetation Photosynthesis Model (VPM),which is a remote sensing-based model for analyzing the spatial pattern of GPP in different land cover types.The field data were collected by coordinating observations at nine stations in 2008.The results indicate that in the region during the growing season GPP was highest in cropland sites,second highest in woodland sites,and lowest in grassland sites.VPM captured the temporal and spatial characteristics of GPP for different land covers in ASA areas.Further,Enhanced Vegetation Index (EVI) had a strong liner relationship with GPP in densely vegetated areas,while the Normalized Difference Vegetation Index (NDVI) had a strong liner relationship with GPP over less dense vegetation.This study demonstrates the potential of satellite-driven models for scaling-up GPP,which is a key component for studying the carbon cycle at regional and global scales.

中国旱区GPP时空演变特征及影响因素研究

为明晰中国旱区生态系统的固碳能力及其变化机制,本研究根据AI指数划分了中国旱区范围,并基于MODIS植被总初级生产力(GPP)数据集,结合气温、降水、饱和水气压差(VPD)、土壤含水量等气象数据和土地利用等人类活动,探究了中国旱区2001—2020年植被固碳能力的时空演变特征及影响因素。结果表明:(1)中国旱区GPP 20 a间呈增长趋势,其中,64.72%的区域GPP呈显著增长趋势;(2)温度对GPP的影响最低,相对贡献率为21.70%,降水和土壤含水量是GPP增长的主导因子,二者贡献率总和超过55%。随干旱程度加剧,水分胁迫作用逐渐增强。不同植被类型下,除混交林和高山植被外,降水是影响其他植被类型GPP变化最重要的气候因子;(3)土壤类型及地貌类型的差异是影响GPP空间分异的主导因子,水分、土地利用类型因素也有重要作用,任意两要素间的交互作用解释力均大于单一要素的解释力,以土壤类型与其他各因子的交互作用最为显著。研究结果对深入理解我国旱区生态系统碳汇演变特征及其对外界环境因子响应机制具有重要理论意义。

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.

海南岛近20年GPP变化格局及驱动因素分析

为探究气象因素与人类活动对近20年海南岛总初级生产力(Gross Primary Production,GPP)变化的相对贡献,首先利用Theil-Sen及Mann-Kendall方法获取海南岛GPP整体时空分布特征,在此基础上,分别以土地利用及覆被变化(Land Use and Cover Change,LUCC)指示人类活动,以气温(Air Temperature,Ta)、饱和水汽压差(Vapor Pressure Deficit,VPD)以及光合有效辐射(Photosynthetically Active Radiation,PAR)作为气象要素指标,通过空间统计与机器学习手段,构建海南岛GPP变化格局归因模型,量化驱动因素的相对贡献。结果表明:研究期间内,时间上,海南岛GPP呈现0.44 Tg·a^(-1)的显著增加趋势(P=0.024);空间上,海南岛87.8%面积的GPP表现增加趋势,海口及三亚周边等小部分区域(约9%)则表现为下降;海南岛土地利用共计转移15528.40 km^(2),主要发生于林地地区,林地净增加642.88 km^(2),草地地区转移面积为4759.28 km^(2),耕地地区转移的面积为4051.23 km^(2);相较于人类活动,研究期年际间气象条件的差异是海南岛GPP变化的主导因素,但特殊年份中LUCC对海南省市县的影响则有所凸显。

Analysis of the Spatiotemporal Variation Characteristics and Driving Factors of Land Vegetation GPP in a Certain Region of Asia

Gross primary productivity (GPP) of vegetation is a critical indicator of ecosystem growth and carbon sequestration. The spatiotemporal variation characteristics of land vegetation GPP trends in a specific region of Asia from 2001 to 2020 were analyzed by Sen and MK trend analysis methods in this study .Moreover , a GPP change attribution model was established to explore the driving influences of factors such as Leaf Area Index (LAI), Land Surface Temperature (LST), Vapor Pressure Deficit (VPD), Soil Moisture, Solar Radiation and Wind Speed on GPP. The results indicate that summer GPP values are significantly higher than those in other months, accounting for 60.8% of the annual total GPP;spring and autumn contribute 18.91% and 13.04%, respectively. In winter, due to vegetation being nearly dormant, the contribution is minimal at 7.19%. Spatially, GPP shows a decreasing trend from southeast to northwest. LAI primarily drives the spatial and seasonal variations of regional GPP, while VPD, surface temperature, solar radiation, and soil moisture have varying impacts on GPP across different dimensions. Additionally, wind speed exhibits a minor contribution to GPP across different dimensions.

中国亚热带地区植被GPP时空变化及其对GPP_(max)和物候的响应

亚热带地区植被具有很强的固碳能力,其动态变化对区域乃至全球尺度碳循环都具有重要影响。基于植被总初级生产力(GPP)和日光诱导叶绿素荧光(SIF)数据,本文采用曲率求导和样条插值提取我国亚热带植被春秋季物候和GPP峰值(GPP_(max)),结合MK趋势检验和偏相关分析,定量分析2001—2018年我国亚热带植被年GPP时空变化特征及其对物候和GPP_(max)的响应。结果表明,研究期间,亚热带地区植被年GPP和GPP_(max)均表现为显著增加的趋势,春季物候和秋季物候则分别表现出不显著提前和显著推迟。偏相关分析结果表明,GPP_(max)和春季物候与年GPP在整个研究区分别为正相关和负相关;除研究区东南部以外,秋季物候与年GPP也表现为正相关。整体而言,研究区内植被年GPP变化主要受到GPP_(max)的控制,其次为春季物候和秋季物候。

基于日光诱导叶绿素荧光的陆地生态系统GPP估算研究

为了更加精确全面地掌握全球陆地生态系统固碳情况,基于GUANTER提出的简单线性模型,利用FLUXNET2015通量数据、GOME-2叶绿素荧光数据、MODIS植被指数产品以及土地覆盖数据,将温度胁迫因子和饱和水汽压胁迫因子加入模型中,估算结果与传统简单线性模型的估算结果相比,13个通量站点中有10个通量站点的估算精度得到了提升。此外,本研究还在考虑环境影响因素模型的基础上,利用植被指数来模拟叶绿素荧光的冠层逃逸率fesc,进一步提升模型的估算精度。结果显示,与传统简单线性模型和只加入环境影响因子的模型估算结果相比,13个通量站点的估算精度都有所提升。

How the enhanced East Asian summer monsoon regulates total gross primary production in eastern China

Recognizing the relationship between gross primary production(GPP)and precipitation in eastern China,the East Asian Summer Monsoon(EASM)plays a crucial role in shaping GPP.Despite confirmation of the strong link between EASM and GPP,there remains a notable research gap in understanding the specific impact of the EASM on GPP in different regions of eastern China.Here we used simulations from Trends in Net Land-Atmosphere Carbon Exchanges(TRENDY)models from 1951 to 2010 and divided eastern China into five subregions for the study.We also used the New East Asian Summer Monsoon Index(NEWI)as a quantitative metric to distinguish between periods of strong and weak EASM.Building on this,this study aims to investigate the response of GPP in different subregions of eastern China.Regionally,under strengthened EASM years(1954,1957,1965,1969,1977,1980,1983,1987,1993 and 1998),East China experienced the most pronounced increase in GPP at 12±21(mean±1 sigma)gC m^(-2) mon^(-1) compared to the weak EASM years(1958,1961,1972,1973,1978,1981,1985,1994,1997 and 2004).In contrast,Southwest China showed a decline in GPP at-4±10 gC m^(-2) mon^(-1).Moreover,GPP also increased in Northeast and North China when EASM strengthened,while South China showed a decline in GPP.This indicated that GPP changed with monsoon intensity.According to the mechanism analysis,during strong EASM,there was intense moisture convergence through alterations in the atmospheric circulation field over East China and abundant precipitation,which further contributed to the increase in GPP.Downward solar radiation in Southwest China decreased with EASM enhancement,which suppressed GPP and hindered vegetation growth.Overall,the results highlight the importance of accurately predicting the impact of different EASM intensities of regional carbon fluxes.

基于多源GPP和ET产品的秦岭生态系统水分利用效率研究

通过评价多种生态系统总初级生产力(gross primary productivity,GPP)和蒸散(evapotranspiration,ET)遥感数据产品,构建了适用于我国秦岭区域的GPP和ET组合数据集,并计算分析了秦岭区域生态系统水分利用效率(water use efficiency,WUE)的时空变化规律。结果表明:不同产品对于不同植被类型GPP和ET的估算效果差异较大,其中VPM GPP和RF GPP这2种GPP产品,China ET和PML-V2 ET这2种ET产品的总体表现较好。秦岭区域的多年平均GPP_(year)为1489.95 g C/m^(2),ET_(year)为588.49 mm,WUE_(year)为2.56 g C/kg H_(2)O,多年平均WUE_(year)的变化率为0.156 g C/(kg H_(2)O·10 a)。秦岭区域WUE_(year)总体呈现出不显著的上升趋势(p>0.05);秦岭区域不同植被覆盖下的多年平均WUE_(year)数值差异不大,但WUE_(year)的变化趋势略有不同,部分植被类型呈现上升趋势,而其他植被类型呈现下降趋势;多年平均逐月WUE_(month)变化多呈现较为明显的“双峰”模式。研究结果为不同类型生态系统水碳关系研究中获取和选择数据提供了依据和途径,加深了对秦岭区域生态系统WUE时空变化规律的认识,从而为研究气候变化对秦岭地区生态系统的影响提供了数据支持和科学参考。

基于地面涡度数据的中国草原区GPP遥感产品验证

草地生产力的准确评估对于合理利用草地资源,提高草地产量以及增加陆地碳汇、适应气候变化和保障生态安全都具有重要指导意义。本研究基于FLUXNET和ChinaFlux数据,开展了中分辨率成像光谱仪(moderate resolution imaging spectroradiometer,MODIS)总初级生产力(GPP)、植物光合模型(vegetation photosynthesis model,VPM)GPP和地球系统呼吸模拟器(Breathing earth system simulator,BESS)GPP遥感产品在中国草原区的验证,并分析了产品输入参数及干旱条件对GPP产品精度的影响来解释产品误差来源。结果表明,3个产品的总体精度表现为BESS GPP>MODIS GPP>VPM GPP,作为产品模型输入的吸收光合有效辐射比例(fraction of absorbed photosynthetically active radiation,FPAR)和饱和水汽压差(vapor pressure deficit,VPD)较剧烈的季节变化导致了MODIS GPP产品相对于另两个产品表现出较剧烈的季节波动;MODIS EVI产品误差引起了VPM GPP产品在部分站点监测到生长季中期GPP发展与涡度GPP不一致现象。3个产品都高估了位于半干旱区的典型草原GPP,在干旱年份高估更加严重,主要是由于干旱条件下模型输入参数对干旱的敏感性不如GPP所导致。该研究对遥感产品在中国草原区的深度应用及GPP精准估算有重要指导意义。

两叶光能利用率模拟结果与全球GPP产品的时空一致性

利用MODIS遥感数据、站点实测气象数据和通量观测数据,基于两叶光能利用率模型(TL-LUE),模拟2000—2011年500m分辨率的中国总初级生产力(GPP_TL),分别比较GPP_TL与全球GPP产品FluxcomGPP(GPP_MPI)在站点和区域的一致性。结果表明:GPP_TL和GPP_MPI均与站点实测GPP具有较好的一致性,GPP_TL相较于GPP_MPI提高了GPP模拟精度(R2提高了0.155,ERMS减小了0.650gC/(m2·d);2000—2011年全国GPP的空间分布东南沿海最高,依次向西北内陆递减;年际波动在西北内陆较大,在东北与华南地区较小;在一年的范围内,全国GPP总量呈现明显夏高冬低的规律;2000—2011年全国GPP_TL与GPP_MPI的月总量呈显著正相关(R2=0.990,ERMS=0.097PgC/month);GPP_TL与GPP_MPI在73.0%的植被区域年均值差值在±400gC/(m2·a)以内,在94.4%的植被区域月均值(全年)呈显著正相关(R2=0.692)。

泾河流域粮食产量与生产潜力时空分布特征及其与MODIS-GPP的关系

以黄土高原泾河流域为例,利用2001—2012年的MOD17A2H GPP数据、流域范围28个站点气象及辐射数据,以及农业统计年鉴数据,采用MK趋势检验和回归分析等方法,对流域尺度GPP、生产潜力与粮食产量的时空分布特征及相互关系进行了分析。结果表明:(1)研究时段内,泾河流域单位面积年GPP随时间呈增加趋势,流域平均GPP为519.6 g·m^-2·a-1。GPP空间格局总体上与降雨分布特征一致,自西北向东南逐渐增加,北部为GPP低值区,两侧山地林区和河川区为GPP高值区,南部的长武、正宁、旬邑、彬县一带是GPP次高值区。(2)泾河流域光温生产潜力在空间上整体自西向东呈增加趋势,南北向呈“马鞍形”分布,范围为16462~21786 kg·hm^-2;气候生产潜力在空间上自西北向东南呈增加趋势,其变化范围为4945~12412 kg·hm^-2;研究时段内,二者的年际变化趋势都不显著。(3)泾河流域粮食产量在空间上自西北向东南增加,2001—2012年间单位面积粮食产量逐年增加,流域内大部分县区的作物气候生产潜力与粮食产量差值在6000 kg·hm^-2以上。(4)对各站点数据的统计分析表明,空间分布上泾河流域单位面积粮食产量、作物气候生产潜力及GPP两两之间的相关性分别达到了极显著水平;时间过程上单位面积粮食产量与GPP之间显著相关。单位面积粮食产量与MODIS-GPP时空间的极显著相关性展示了通过遥感数据估算粮食产量的有效性,有助于推进区域粮食产量的预测预报。