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.

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。

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.

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.

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。

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.

Clipping Alters the Response of Biomass Production to Experimental Warming: A Case Study in an Alpine Meadow on the Tibetan Plateau, China

Predicting how human activity will influence the response of alpine grasslands to future warming has many uncertainties.In this study, a field experiment with controlled warming and clipping was conducted in an alpine meadow at three elevations（4313 m, 4513 m and 4693 m） in Northern Tibet to test the hypothesis that clipping would alter warming effect on biomass production.Open top chambers（OTCs） were used to increase temperature since July,2008 and the OTCs increased air temperature by approximately 0.9o C ~ 1.8o C during the growing in2012.Clipping was conducted three times one year during growing season and the aboveground parts of all live plants were clipped to approximately 0.01 m in height using scissors since 2009.Gross primary production（GPP） was calculated from the Moderate-Resolution Imaging Spectroradiometer GPP algorithm and aboveground plant production was estimated using the surface-measured normalized difference vegetation index in 2012.Warming decreased the GPP, aboveground biomass（AGB） and aboveground net primary production（ANPP） at all three elevations when clipping was not applied.In contrast, warming increased AGB at all three elevations, GPP at the two lower elevations and ANPP at the two higher elevations when clipping was applied.These findings show that clipping reduced the negative effect of warming on GPP, AGB and ANPP, suggesting that clipping may reduce the effect of climate warming on GPP, AGB and ANPP in alpine meadows on the Tibetan Plateau, and therefore, may be a viable strategy for mitigating the effects of climate change on grazing and animal husbandry on the Tibetan Plateau.

1982—2017年典型干旱年的中国GPP变化

干旱导致的总初级生产力(GPP)的减少会对陆地碳汇产生重大影响。基于全国618个站点的月气象数据计算的标准降水蒸散指数(SPEI)和2套公开的GPP数据集(EC-LUE GPP和GLASS GPP),系统分析了中国1982—2017年典型干旱年的GPP在不同时间尺度下受不同程度干旱影响的变化。结果表明:(1)基于SPEI的5个选取指标,选出1982—2017年典型干旱的年份为2001年和2011年。(2)在年和季节尺度上,2001年的GPP受干旱影响严重区域主要在华北、东北和中东部地区的北部,2011年主要集中在西南地区的东南部和中东部地区。月尺度上,2001年5月的GPP受干旱影响最严重,主要集中在华北和东北的大部分区域。2011年1月GPP受干旱影响最为严重,主要集中在中东部地区的大部分区域。(3)无论是年、季节还是月尺度,随着干旱程度的加重,导致GPP的下降率越大,极端干旱的影响最大。从季节尺度看,2001年夏季极端干旱造成GPP下降率分别为19.96%(EC-LUE GPP)和15.57%(GLASS GPP);2011年春季极端干旱造成GPP下降率分别为14.32%(EC-LUE GPP)和8.75%(GLASS GPP)。研究结果可进一步加深不同时间尺度下不同等级干旱对GPP影响的认识,对了解干旱条件下陆地与大气之间的碳交换具有重要意义。

Spatial and temporal variations of gross primary production simulated by land surface model BCC_AVIM2.0

Gross primary production(GPP)is the largest flux and a crucial player in the terrestrial carbon cycle and has been studied extensively,yet large uncertainties remain in the spatiotemporal patterns of GPP in both observations and simulations.This study evaluates the performance of the second version of the Beijing Climate Center Atmosphere−Vegetation Interaction Model(BCC_AVIM2.0)in simulating GPP on multiple spatial and temporal scales in the Coupled Model Intercomparison Project Phase 6(CMIP6)experiments.Model simulations driven by two meteorological datasets were compared with two observation-based GPP products covering 1982–2008.Spatial patterns of annual GPP show a significant latitudinal gradient in each dataset,increasing from cold(tundra)and dry(desert)biomes to warm(temperate)and humid(tropical rainforest)biomes.BCC_AVIM2.0 overestimates GPP in most parts of the globe,especially in boreal forest regions and Southeast China,while underestimating GPP in subhumid regions in eastern South America and tropical Africa.The four datasets broadly agree on the GPP seasonal cycle,but BCC_AVIM2.0 predicts an earlier beginning of spring growth and a larger amplitude of seasonal variations than those in the observations.The observation-based datasets exhibit slight interannual variability(IAV)and weak GPP linear trends,while the BCC_AVIM2.0 simulations demonstrate relatively large year-to-year variability and significant trends in the low-latitudes and temperate monsoon regions in North America and East Asia.Regarding the possible relationships between annual means of GPP and climate factors,BCC_AVIM2.0 predicts more extensive regions of the globe where the IAV of annual GPP is dominated by precipitation,especially in mid-to-high latitudes of the Northern Hemisphere and tropical Africa,while the observed GPP in the above regions is temperature-or radiation-dominant.The positive GPP biases due to earlier spring growth in boreal forest regions and negative GPP biases in off-equator tropical areas in the BCC_AVIM2.0 simulations imply that cold stress on biomes in boreal mid-to-high latitudes should be strengthened to restrain plant growth,while drought stress in low-latitude regions might be eased to enhance plant production in the future version of BCC_AVIM.

中国八大经济区GPP变化及影响因子协同机制

以中国和八大综合经济区为研究区,全面分析人文因子、土地利用类型、气候因子和地形因子对植被总初级生产力(GPP)空间分异的影响差异.利用MODIS GPP数据、气象数据、土地利用类型、DEM数据、夜间灯光和人口密度数据等,基于Theil-Sen Median趋势分析、Mann-Kendall显著性检验和地理探测器模型,在全国和经济区尺度上分析2000~2020年植被GPP时空变化特征,探测植被空间分异的影响因子及影响因子间的协同机制.结果表明,2000~2020年中国及八大经济区植被GPP整体呈波动上升趋势,呈上升趋势的区域占总面积的84.46%,其中,呈极显著上升区域占19.86%,主要分布在黄河中游综合经济区中部和大西北综合经济区东部.影响因子探测结果表明,湿度、日照时数、降水和土地利用类型是中国植被GPP空间分异的主要影响因子,其中,湿度的影响力最高,q值为0.64.经济区尺度上,湿度、日照时数、降水是影响东北、黄河中游、大西南和大西北综合经济区植被GPP空间分异的主导因子,而人文因子对东部和南部沿海综合经济区植被空间分异的影响较大.交互作用探测结果表明,中国植被GPP空间分异主要受土地利用类型∩湿度的协同影响,q值为0.75.经济区尺度上,除黄河中游和大西南综合经济区植被GPP空间分异主要受降水∩其他因子协同影响外,其他经济区植被GPP空间分异主要受土地利用类型∩其他因子或湿度∩其他因子的协同影响.

Using triple oxygen isotopes and oxygen-argon ratio to quantify ecosystem production in the mixed layer of northern South China Sea slope region

Quantifying the gross and net production is an essential component of carbon cycling and marine ecosystem studies.Triple oxygen isotope measurements and the O_(2)/Ar ratio are powerful indices in quantifying the gross primary production and net community production of the mixed layer zone,respectively.Although there is a substantial advantage in refining the gas exchange term and water column vertical mixing calibration,application of mixed layer depth history to the gas exchange term and its contribution to reducing indices error are unclear.Therefore,two cruises were conducted in the slope regions of the northern South China Sea in October 2014(autumn)and June 2015(spring).Discrete water samples at Station L07 in the upper 150 m depth were collected for the determination ofδ^(17)0,δ^(18)O,and the O_(2)/Ar ratio of dissolved gases.Gross oxygen production(GOP)was estimated using the triple oxygen isotopes of the dissolved O_(2),and net oxygen production(NOP)was calculated using O_(2)/Ar ratio and O_(2)concentration.The vertical mixing effect in NOP was calibrated via a N_(2)O based approach.GOP for autumn and spring was(169±23)mmol/(m^(2)·d)(by O_(2))and(189±26)mmol/(m^(2)·d)(by O_(2)),respectively.While NOP was 1.5 mmol/(m^(2)·d)(by O_(2))in autumn and 8.2 mmol/(m^(2)·d)(by O_(2))in spring.Application of mixed layer depth history in the gas flux parametrization reduced up to 9.5%error in the GOP and NOP estimations.A comparison with an independent O_(2)budget calculation in the diel observation indicated a26%overestimation in the current GOP,likely due to the vertical mixing effect.Both GOP and NOP in June were higher than those in October.Potential explanations for this include the occurrence of an eddy process in June,which may have exerted a submesoscale upwelling at the sampling station,and also the markedly higher terrestrial impact in June.

中国生态系统GPP变化热点区域检测与归因分析

结合趋势分析与热点分析检测中国GPP变化的热点区域,从热点区和像元2个尺度探讨了自然和人类活动对热点区域GPP变化的影响.结果表明:1982−2017年中国GPP总体呈增加趋势,变化均值为1.92 g·m^(−2)·a^(−1);GPP正向变化的热点区域位于川西高原、黄土高原、华北平原及云贵高原;GPP负向变化的热点区域位于藏南、长江三角洲和东南沿海地区;研究考虑的3个自然因子中,气温与GPP相关程度最高;以气温和人类活动为主导因素的像元比例最高,达43.86%.气温和人类活动在各热点区域的影响方向不同,总体上在GPP显著增加的4个热点区域都起到了促进作用,在GPP显著减少的3个热点区域都起到了负面影响.