Dynamic change of net primary productivity and fractional vegetation cover in the Yellow River Basin using multi-temporal AVHRR NDVI Data

An exponential relationship between net primary productivity (NPP) and integrated NDVI has been found in this paper. Based on the relationship and using multi-temporal 8 km resolution NOAA AVHRR-NDVI data, the spatial distribution and dynamic change of NPP and fractional vegetation cover in the Yellow River Basin from 1982 to 1999 are analyzed. Finally, the effect of rainfall on NDVI is examined. Results show that mean NPP and fractional vegetation cover have an inclining trend for the whole basin, and rainfall in flood season influences vegetation cover most.

Influence of vapor pressure deficit on vegetation growth in China

Vapor pressure deficit(VPD)plays a crucial role in determining plant physiological functions and exerts a substantial influence on vegetation,second only to carbon dioxide(CO_(2)).As a robust indicator of atmospheric water demand,VPD has implications for global water resources,and its significance extends to the structure and functioning of ecosystems.However,the influence of VPD on vegetation growth under climate change remains unclear in China.This study employed empirical equations to estimate the VPD in China from 2000 to 2020 based on meteorological reanalysis data of the Climatic Research Unit(CRU)Time-Series version 4.06(TS4.06)and European Centre for Medium-Range Weather Forecasts(ECMWF)Reanalysis 5(ERA-5).Vegetation growth status was characterized using three vegetation indices,namely gross primary productivity(GPP),leaf area index(LAI),and near-infrared reflectance of vegetation(NIRv).The spatiotemporal dynamics of VPD and vegetation indices were analyzed using the Theil-Sen median trend analysis and Mann-Kendall test.Furthermore,the influence of VPD on vegetation growth and its relative contribution were assessed using a multiple linear regression model.The results indicated an overall negative correlation between VPD and vegetation indices.Three VPD intervals for the correlations between VPD and vegetation indices were identified:a significant positive correlation at VPD below 4.820 hPa,a significant negative correlation at VPD within 4.820–9.000 hPa,and a notable weakening of negative correlation at VPD above 9.000 hPa.VPD exhibited a pronounced negative impact on vegetation growth,surpassing those of temperature,precipitation,and solar radiation in absolute magnitude.CO_(2) contributed most positively to vegetation growth,with VPD offsetting approximately 30.00%of the positive effect of CO_(2).As the rise of VPD decelerated,its relative contribution to vegetation growth diminished.Additionally,the intensification of spatial variations in temperature and precipitation accentuated the spatial heterogeneity in the impact of VPD on vegetation growth in China.This research provides a theoretical foundation for addressing climate change in China,especially regarding the challenges posed by increasing VPD.

Seasonal Responses of Net Primary Productivity of Vegetation to Phenological Dynamics in the Loess Plateau, China

With global warming, the great changes in the patterns of plant growth have occurred. The conditions in early spring and late autumn have changed the process of vegetation photosynthesis, which are expected to have a significant impact on net primary productivity(NPP) and affect the global carbon cycle. Currently, the seasonal response characteristics of NPP to phenological changes in dryland ecosystems are still not well defined. This article calibrated and analyzed the normalized difference vegetation index(NDVI)time series of Advanced Very-High-Resolution Radiometer(AVHRR) data from 1982 to 2015 in the Loess Plateau, China. The spatial and temporal distributions of vegetation phenology and NPP in the Loess Plateau under semihumid and semiarid conditions were investigated. The seasonal variation in the NPP response to vegetation phenology under the climate change was also analyzed. The results showed that, different from the northern forest, there was distinct spatial heterogeneity in the effect of climate change on the dynamic change in vegetation growth in the Loess Plateau: 1) an advance of the start of the growing season(SOS) and a delay of the end of the growing season(EOS) significantly increased the NPP in spring and autumn, respectively, in the humid southeast;2) in the arid northwest, the NPP did not significantly increase in spring and autumn but significantly decreased in summer.

Spatiotemporal variation in vegetation net primary productivity and its relationship with meteorological factors in the Tarim River Basin of China from 2001 to 2020 based on the Google Earth Engine

Vegetation growth status is an important indicator of ecological security.The Tarim River Basin is located in the inland arid region of Northwest China and has a highly fragile ecological environment.Assessing the vegetation net primary productivity(NPP)of the Tarim River Basin can provide insights into the vegetation growth variations in the region.Therefore,based on the Google Earth Engine(GEE)cloud platform,we studied the spatiotemporal variation of vegetation NPP in the Tarim River Basin(except for the eastern Gobi and Kumutag deserts)from 2001 to 2020 and analyzed the correlations between vegetation NPP and meteorological factors(air temperature and precipitation)using the Sen slope estimation method,coefficient of variation,and rescaled range analysis method.In terms of temporal characteristics,vegetation NPP in the Tarim River Basin showed an overall fluctuating upward trend from 2001 to 2020,with the smallest value of 118.99 g C/(m2•a)in 2001 and the largest value of 155.07 g C/(m2•a)in 2017.Regarding the spatial characteristics,vegetation NPP in the Tarim River Basin showed a downward trend from northwest to southeast along the outer edge of the study area.The annual average value of vegetation NPP was 133.35 g C/(m2•a),and the area with annual average vegetation NPP values greater than 100.00 g C/(m2•a)was 82,638.75 km2,accounting for 57.76%of the basin.The future trend of vegetation NPP was dominated by anti-continuity characteristic;the percentage of the area with anti-continuity characteristic was 63.57%.The area with a significant positive correlation between vegetation NPP and air temperature accounted for 53.74%of the regions that passed the significance test,while the area with a significant positive correlation between vegetation NPP and precipitation occupied 98.68%of the regions that passed the significance test.Hence,the effect of precipitation on vegetation NPP was greater than that of air temperature.The results of this study improve the understanding on the spatiotemporal variation of vegetation NPP in the Tarim River Basin and the impact of meteorological factors on vegetation NPP.

Response of vegetation net primary productivity to climate change scenarios in the Loess Plateau of China--A case study of the Yangou watershed

Vegetation net primary productivity(NPP)is a sensitive indicator to characterize the response of terrestrial ecosystems to the climate change.Projections of the NPP changes of the Loess Plateau under future climate scenarios have great significances in revealing the interactions among terrestrial ecosystems and climatic systems,as well as instructing future vegetation construction of this region.Here,we carried out a case study on the Yangou watershed in the Loess Plateau.Using the vegetation-producing process model(VPP)established for such small watersheds,we simulated the NPP of the Yangou watershed under different scenarios of climate changes.The results showed that the NPP significandy increased with the precipitation increasing and evidently decreased with the temperature increasing where the climate change occurred in the whole year or in the summer half year.However,where the climate change occurred in the winter half year,the increased precipitation had little effect on the NPP,and the increased temperature significantly reduced the NPP.There were clear differences among the response sensitivities of different vegetation types with trees and shrubs were more sensitive to the changes in temperature and precipitation than crops and grasses.Currently,the most favourable climate change scenario to the NPP in the Yangou watershed was T0P15 under which the precipitation increased by 15%and the temperature did not changed,in the whole year;in the meantime,the most unfavourable climate change scenarios was T2P-15 under which the precipitation declined by 15%and the temperature increased by 2℃,in the whole year.

Drought Impacts on Vegetation Indices and Productivity of Terrestrial Ecosystems in Southwestern China During 2001–2012

Drought, as a recurring extreme climate event, affects the structure, function, and process of terrestrial ecosystems. Despite the increasing occurrence and intensity of the drought in the past decade in Southwestern China, the impacts of continuous drought events on vegetation in this region remain unclear. During 2001–2012, Southwestern China experienced the severe drought events from 2009 to 2011. Our aim is to characterize drought conditions in the Southwestern China and explore the impacts on the vegetation condition and terrestrial ecosystem productivity. The Standardized Precipitation Index(SPI) was used to characterize drought area and intensity and a light-use efficiency model was used to explore the effect of drought on the terrestrial ecosystem productivity with Moderate Resolution Imaging Spectrometer(MODIS) data. The SPI captured the major drought events in Southwestern China during the study period, indicated that the 12-year period of this study included both ‘normal' precipitation years and two severe drought events in 2009–2010 and 2011. Results showed that vegetation greenness(Normalized Difference Vegetation Index, NDVI and Enhanced Vegetation Index, EVI) both declined in 2009/2010 drought, but the 2011 drought resulted in less declines of vegetation greenness and productivity due to shorten drought duration and rising temperature. Meanwhile, it was about 5 months lapse between drought events and maximum declines in vegetation greenness for 2009/2010 drought events. In addition, forest, grassland and cropland revealed significant different ecosystem responses to drought. It indicated that grassland showed an early sensitivity to drought, while cropland was the most sensitive to water deficit and forest was more resilient to drought. This study suggests that it is necessary to detect the difference responses of ecosystem to drought in a regional area with satellite data and ecosystem model.

Estimation of net primary productivity in China using remote sensing data

It is significant to estimate terrestrial net primary productivity (NPP) accurately not only for global change research, but also for natural resources management to achieve sustainable development. Remote sensing data can describe spatial distribution of plant resources better. So, in this paper an NPP model based on remote sensing data and climate data is developed. And 1km resolution AVHRR NDVI data are used to estimate the spatial distribution and seasonal change of NPP in China. The results show that NPP estimated using remote sensing data are more close to truth. Total annual NPP in China is 2.645X109 tC. The spatial distribution of NPP in China is mainly affected by precipitation and has the trend of decreasing from southeast to northwest.

Estimation of net primary productivity and its driving factors in the Ili River Valley,China

Net primary productivity（NPP）, as an important variable and ecological indicator in grassland ecosystems, can reflect environmental change and the carbon budget level. The Ili River Valley is a wetland nestled in the hinterland of the Eurasian continent, which responds sensitively to the global climate change. Understanding carbon budget and their responses to climate change in the ecosystem of Ili River Valley has a significant effect on the adaptability of future climate change and sustainable development. In this study, we calculated the NPP and analyzed its spatio-temporal pattern of the Ili River Valley during the period 2000–2014 using the normalized difference vegetation index（NDVI） and an improved Carnegie-Ames-Stanford（CASA） model. Results indicate that validation showed a good performance of CASA over the study region, with an overall coefficient of determination（R2） of 0.65 and root mean square error（RMSE） of 20.86 g C/（m^2·a）. Temporally, annual NPP of the Ili River Valley was 599.19 g C/（m^2·a） and showed a decreasing trend from 2000 to 2014, with an annual decrease rate of –3.51 g C/（m^2·a）. However, the spatial variation was not consistent, in which 55.69% of the areas showed a decreasing tendency, 12.60% of the areas remained relatively stable and 31.71% appeared an increasing tendency. In addition, the decreasing trends in NPP were not continuous throughout the 15-year period, which was likely being caused by a shift in climate conditions. Precipitation was found to be the dominant climatic factor that controlled the inter-annual variability in NPP. Furthermore, the correlations between NPP and climate factors differed along the vertical zonal. In the medium-high altitudes of the Ili River Valley, the NPP was positively correlated to precipitation and negatively correlated to temperature and net radiation. In the low-altitude valley and high-altitude mountain areas, the NPP showed a negative correlation with precipitation and a weakly positive correlation with temperature and net radiation. The results suggested that the vegetation of the Ili River Valley degraded in recent years, and there was a more complex mechanism of local hydrothermal redistribution that controlled the growth of vegetation in this valley ecosystem.

Investigating Temperature and Nutrients as Drivers of Primary Productivity in Aquatic Environment

An investigation into the relationship between temperature and the nutrients (,, and ) in pelagial primary productivity of the middle reaches of Otamiri River in Owerri, Southeastern Nigeria was carried out between October and November, 2018 at ten sampling points (OTP 1-OTP 10). The estimation of productivity was made with the light and dark bottle technique. Maximum yields in Gross Primary Productivity (GPP) (0.8738 mgCL-1d-1), Net Primary Productivity (NPP) (0.8513 mgCL-1d-1), as well as Community Respiration (CR) (0.1613 mgCL-1d-1) were recorded at OTP 3, OTP 3 and OTP 8 respectively that had more vegetation covers than in segments without cover. GPP is correlated withions (r = 0.400),ions (r = 0.418), and water temperature (r = 0.379) (p 0.05), while CR is correlated with ions (r = 0.500) (p 0.01). The variability of GPP increased mildly with increasing temperature and the nutrients;with predicted regression model productivities of 0.1388, 0.5621, and 0.6066 mgCL-1d-1, corresponding with mean values of 28.41℃, 0.33 mg/L, 1.04 mg/L and 10.25 mg/L recorded for temperature,,, and ions concentrations. Mean GPP was estimated to result in a comparatively low annual productivity of 188.75 mgCL-1yr-1. Conservation and restoration of riparian vegetation covers in watershed corridors of the river for optimal driver roles were recommended.

Research Advances in Net Primary Productivity of Terrestrial Ecosystem

The net primary productivity of vegetation reflects the total amount of carbon fixed by plants through photosynthesis each year. The study of vegetation net primary productivity is one of the core contents of global change and terrestrial ecosystems. This article reviews the current research status of net primary productivity of terrestrial vegetation, and comprehensively analyzes the advantages and disadvantages of three types of productivity estimation models, climate relative models, biogeochemical models, and light energy utilization models. The light energy utilization models have become the mainstream method for estimating vegetation net primary productivity because they can directly use remote sensing data. However, there are still many deficiencies in the estimation of vegetation net primary productivity, which need to be further improved and tested.

Cultivation Systems Using Vegetation Cover Improves Sustainable Production and Nutritional Quality of New Rice for Africa in the Tropics

Little is known about the impact of direct sowing under vegetation cover on the production and quality of New Rice for Africa （NERICA） on poor oxisol. In this study, two NERICA varieties （NERICA 3 and NERICA 8） were grown under tropical oxisol soil with very low nutrient contents. Four cultivation systems were used in completely randomized block design, including plowing （control）, unplowed soil with dead vegetation cover （DVC）, unplowed soil with live vegetation cover （LVC） and unplowed soil with mixed vegetation cover （MVC）. DVC significantly improved the exponential growth of NERICAs. NERICA 3 was the more productive （2.16–3.05 t/hm2） compared with NERICA 8 （0.71–1.21 t/hm2）. Cultivation systems improved the nutritional quality of NERICAs. The total protein content of NERICA 3 under DVC and MVC was 84.8% and 75.0% higher than control, respectively. The total soluble carbohydrate contents of NERICA 8 under LVC and MVC was 73.2% and 57.3% higher than control, respectively. These results suggested that conservative approach like direct sowing on unplowed soil with vegetation cover systems can improve the nutritional quality of rainfed NERICAs and their sustainable production under poor oxisol soil in sub-Saharan Africa.

Monitoring the impact of climate change and human activities on grassland vegetation dynamics in the northeastern Qinghai-Tibet Plateau of China during 2000–2015

Climate change and human activities can influence vegetation net primary productivity(NPP), a key component of natural ecosystems. The Qinghai-Tibet Plateau of China, in spite of its significant natural and cultural values, is one of the most susceptible regions to climate change and human disturbances in the world. To assess the impact of climate change and human activities on vegetation dynamics in the grassland ecosystems of the northeastern Qinghai-Tibet Plateau, we applied a time-series trend analysis to normalized difference vegetation index(NDVI) datasets from 2000 to 2015 and compared these spatiotemporal variations with trends in climatic variables over the same time period. The constrained ordination approach(redundancy analysis) was used to determine which climatic variables or human-related factors mostly influenced the variation of NDVI. Furthermore, in order to determine whether current conservation measures and programs are effective in ecological protection and reconstruction, we divided the northeastern Qinghai-Tibet Plateau into two parts: the Three-River Headwater conservation area(TRH zone) in the south and the non-conservation area(NTRH zone) in the north. The results indicated an overall(73.32%) increasing trend of vegetation NPP in grasslands throughout the study area. During the period 2000–2015, NDVI in the TRH and NTRH zones increased at the rates of 0.0015/a and 0.0020/a, respectively. Specifically, precipitation accounted for 9.2% of the total variation in NDVI, while temperature accounted for 13.4%. In addition, variation in vegetation NPP of grasslands responded not only to long-and short-term changes in climate, as conceptualized in non-equilibrium theory, but also to the impact of human activities and their associated perturbations. The redundancy analysis successfully separated the relative contributions of climate change and human activities, of which village population and agricultural gross domestic product were the two most important contributors to the NDVI changes, explaining 17.8% and 17.1% of the total variation of NDVI(with the total contribution >30.0%), respectively. The total contribution percentages of climate change and human activities to the NDVI variation were 27.5% and 34.9%, respectively, in the northeastern Qinghai-Tibet Plateau. Finally, our study shows that the grassland restoration in the study area was enhanced by protection measures and programs in the TRH zone, which explained 7.6% of the total variation in NDVI.

Climate and Vegetation Drivers of Terrestrial Carbon Fluxes:A Global Data Synthesis

The terrestrial carbon(C) cycle plays an important role in global climate change, but the vegetation and environmental drivers of C fluxes are poorly understood. We established a global dataset with 1194 available data across site-years including gross primary productivity(GPP), ecosystem respiration(ER), net ecosystem productivity(NEP), and relevant environmental factors to investigate the variability in GPP, ER and NEP, as well as their covariability with climate and vegetation drivers.The results indicated that both GPP and ER increased exponentially with the increase in mean annual temperature(MAT)for all biomes. Besides MAT, annual precipitation(AP) had a strong correlation with GPP(or ER) for non-wetland biomes.Maximum leaf area index(LAI) was an important factor determining C fluxes for all biomes. The variations in both GPP and ER were also associated with variations in vegetation characteristics. The model including MAT, AP and LAI explained 53%of the annual GPP variations and 48% of the annual ER variations across all biomes. The model based on MAT and LAI explained 91% of the annual GPP variations and 92.9% of the annual ER variations for the wetland sites. The effects of LAI on GPP, ER or NEP highlighted that canopy-level measurement is critical for accurately estimating ecosystem–atmosphere exchange of carbon dioxide. The present study suggests a significance of the combined effects of climate and vegetation(e.g.,LAI) drivers on C fluxes and shows that climate and LAI might influence C flux components differently in different climate regions.

Simulating the vegetation-producing process in small watersheds in the Loess Plateau of China

Small watersheds are the basic composition unit of the Loess Plateau in China. An accurate estimation of vegetation net primary productivity （NPP） is of great significance for eco-benefit evaluation in small watershed management in this region. Here we describe the development and testing of a vegetation-producing process model （VPP） of a small watershed in the Loess Plateau. The model couples three modules： radiation adjustment; soil hydrological processes; and vegetation carbon assimilation. Model validation indicates that the VPP model can be used to estimate the NPP of small watersheds in the region. With the VPP model, we estimated the spatial NPP distributions in the Yangou watershed for 2007. The results show that in the Yangou watershed the NPP is relatively low, averaging 168 g C/（m^2.a）. Trees and shrubs have a higher NPP than crops and grasses. The NPP is larger on the partly shaded and shaded slopes than on the partly sunny and sunny slopes. The NPP on the slopes increases gradually on 0-20° slopes and decreases slightly on slopes steeper than 20°. Our simulation indicates that the vegetation type is the most important factor in determining the NPP distribution in small watersheds in the Loess Plateau.

IMPACT OF ROAD CONSTRUCTION ON VEGETATION ALONGSIDE QINGHAI-XIZANG HIGHWAY AND RAILWAY

Based on the field investigation in August 2001 and August 2002,digital China Vegetation Map in 2001 and Qinghai-Xizang(Tibet) Plateau Vegetation Regionalization Map in 1996,vegetation characteristics along two sides of Qinghai-Xizang highway and railway are studied in this paper. Meanwhile,the impact of Qinghai-Xizang highway and railway constructions on the vegetation types are analyzed using ARCVIEW,ARC/INFO and PATCH ANALYSIS. It was found that: 1) Qinghai-Xizang highway and railway span 9 latitudes,12 longitudes and 6 physical geographic regions (East Qinghai and Qilian mountain steppe region,Qaidam mountain desert region,South Qinghai-Xizang alpine meadow steppe region,Qiangtang alpine steppe region,Golog-Nagqu alpine shrub meadow region and South Xizang mountain shrub steppe region); 2) the construction of Qinghai-Xizang highway and railway destroyed natural vegetation and landscape,especially in 50m-wide buffer regions along both sides of the roads,it was estimated that the net primary productivity deceased by about 30 504.62t/a and the gross biomass deceased by 432 919.25-1 436 104.3t. The losing primary productivity accounted for 5.70% of the annual primary productivity within 1km-wide buffer regions (535 005.07-535 740.11t/a),and only 0.80%-0.89% of that within 10km-wide buffer regions (3 408 950.45-3 810 480.92t/a). The losing gross biomass was about 9.47%-17.06% of the gross biomass within 1km-wide buffer regions (7 502 971.85-25 488 342.71t),and only 1.47%-2.94% of that within 10km-wide buffer regions (43 615 065.35-164 150 665.37t).

基于BEPS模型的塞罕坝植被净初级生产力时空变化分析研究

叶面积指数(leaf area index,LAI)是北部生态系统生产力模拟模型(boreal ecosystem productivity simulator,BEPS)的关键驱动数据,获取高精度LAI对区域森林生态系统碳循环十分重要,然而当前大多研究采用的MODIS LAI产品缺乏可信度。为此,基于LAI动态模型、PROSAIL辐射传输模型和层状贝叶斯网络(Hierarchical Bayesian Network,HBN)构建数据同化系统,获得空间分辨率为20 m的LAI数据,驱动BEPS模型,模拟塞罕坝机械林场2011—2021年的植被净初级生产力(Net Primary Productivity,NPP),并对NPP时空变化特征及影响因子进行分析。结果表明,基于贝叶斯同化方法获得的高分辨率LAI数据极大提高了MODIS LAI产品的精度;基于同化后的LAI数据驱动BEPS模型获取模拟森林NPP,与样地实测数据计算NPP间相关性较高(R^(2)=0.77);2011—2021年塞罕坝机械林场植被NPP平均值为307.4 g/(m^(2)·a),森林NPP呈现平稳增长趋势;不同植被类型模拟NPP存在较大差异,针叶林、落叶林及混交林模拟NPP分别为484.9、402.4、287.9 g/(m^(2)·a);植被NPP与温度因子相关性较高,偏相关系数为0.2~0.8,而植被NPP与降水量的相关性总体而言相对较低,其偏相关系数为-0.3~0.4,在该地区降水量对植被NPP的影响较低,温度为该地区NPP变化的主导因子。研究结果可获取高空间分辨率的LAI数据,为森林生态系统碳循环的精准时空模拟提供依据。

Climate-Vegetation Interannual Variability in a Coupled Atmosphere-Ocean-Land Model

The coupled models of both the Global Ocean-Atmosphere-Land System （GOALS） and the Atmosphere- Vegetation Interaction Model （GOALS-AVIM） are used to study the main characteristics of interannual variations. The simulated results are also used to investigate some significant interannual variability and correlation analysis of the atmospheric circulation and terrestrial ecosystem. By comparing the simulations of the climate model GOALS-AVIM and GOALS, it is known that the simulated results of the interannual variations of the spatial and temporal distributions of the surface air temperatures and precipitation are generally improved by using AVIM in GOALS-AVIM. The interannual variation displays some distinct characteristics of the geographical distribution. Both the Net Primary Production （NPP） and the Leap Area Index （LAI） have quasi 1-2-year cycles. Meanwhile, precipitation and the surface temperatures have 2-4- year cycles. Conditions when the spectrum density values of GOALS are less than those of GOALS-AVIM, tell us that the model coupled with AVIM enhances the simulative capability for interannual variability and makes the annual cycle variability more apparent. Using Singular Value Decomposition （SVD） analysis, the relationship between the ecosystem and the atmospheric circulation in East Asia is explored. The result shows that the strengthening and weakening of the East Asian monsoon, characterized by the geopotential heights at 500 hPa and the wind fields at 850 hPa, correspond to the spatiotemporal pattern of the NPP. The correlation between NPP and the air temperature, precipitation and solar radiation are different in interannual variability because of the variation in vegetation types.

基于PIE-Engine云计算平台和CASA模型的植被NPP时空动态遥感监测:以道孚县为例

【目的】为深入了解道孚县的植被固碳水平以及其长期变化趋势,【方法】以MODIS数据、站点气象和土地覆盖等资料为基础,通过PIE-Engine遥感云计算平台建立了CASA模型,估算了2001—2016年道孚县陆地植被净初级生产力(NPP)。同时,结合Theil-Sen Median趋势分析、稳定性分析、分区统计和冷热点分析等手段,探讨了其时空分布和演变特征。【结果】结果显示:(1)基于PIE-Engine云平台模型和CASA模型估算的道孚县2001—2016年的NPP,其精度较高并与MODIS NPP数据有良好的拟合效果。(2)道孚县NPP呈持续上升趋势,其中中部和东南部NPP较高,东北部和中南部NPP较低,同时NPP的低值区正在逐年减少,反映出该地区生态状况正在逐渐改善。(3)所有乡镇的NPP在2001—2016年间均有增长,NPP的空间变化整体稳定,大部分地区NPP波动较小。(4)道孚县的NPP在2001—2016年间总体显著增长,增长区域面积占全县的93%以上。(5)高NPP值区域在空间上形成聚类,“热点”现象明显,这为进一步研究和理解NPP的空间分布和变化规律提供了依据。【结论】研究成果为道孚县的生态环境改善和持续发展提供了科学依据,并提出了一种基于云平台的快速、高效的区域植被NPP评估方法,这对于全面评估可持续发展目标和推动生态文明建设具有积极意义。

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.

Plant Biomass, Primary Production and Mineral Cycling of a Mixed Oak Forest in Linnebjer, Sweden

Plant biomass, primary production and mineral cycling were studied in a mixed deciduous forest (Quercus robur L., Tilia cordata L. and Corylus avellana L.) in southern Sweden. Plant biomass amount above and below ground was 201 and 37 t&middotha-1, respectively. Primary production above and below ground was an estimated 13.3 and 2.3 t&middotha-1, respectively. Carbon was the dominant element in the forest ecosystem, comprising 133 t&middotha-1. Other major elements were: N > Ca > K > Si > Mg > S > Mn > P > Fe and Na (range 1123 to 18 kg&middotha-1), followed by some trace elements. Yearly litterfall restored 6.0 t&middotha-1 organic matter or 2.3 t&middotha-1 carbon. Approximately 45% decomposed and returned to the soil during the year. Monitoring of other elements revealed that the ecosystem received inputs through dry and wet deposition, in particular 34.4 kg&middotha-1 S and 9.4 kg&middotha-1 of N yearly as throughfall. Determination of yearly biomass increase showed that the oak forest ecosystem was still in an aggradation or accumulation phase.