Trends In Gross Primary Production Research Articles

Interannual variations and trends of gross primary production and transpiration of four mature deciduous broadleaf forest sites during 2000–2020

The interannual variations of gross primary production (GPP) and transpiration (T) in deciduous broadleaf forests reflect how the forest responds to climate change. However, our knowledge remains limited due to lack of multi-decadal data. In this study, we selected four mature deciduous broadleaf forest sites in the United States of America and Canada from 2000 to 2020 to investigate decadal trends in atmospheric CO2 concentrations, climate, vegetation indices, phenology, and carbon and water fluxes. The Vegetation Photosynthesis Model (VPM v3.0) and the Vegetation Transpiration Model (VTM, v2.0) were used to estimate GPP and T at the four sites. The GPP from the VPM simulations (GPPVPM) is highly consistent with that from the eddy flux tower sites (GPPEC) (R2 range from 0.77 to 0.89). The interannual trends of carbon and water fluxes during the period from 2000 to 2020 varied by sites, ranging from increases (CA-Cbo) to no trend (US-Ha1, US-MMs, US-WCr sites), dependent upon the temporal changes in atmospheric CO2 concentration and climate. Spring phenology at these sites had no significant trends due to the lack of an interannual trend of air temperature during 2000–2020. In those years with hotter winter and early spring season (WESS), the start of the season (SOS) advanced and the growing season length (GSL) extended, but there were little changes in the end of the season (EOS) and annual GPP. This study highlights the value of long-term measurements at forest eddy flux tower sites and the skill of VPM v3.0 and VTM v2.0 models and the ERA5 climate dataset for simulations over the past two decades, which could be used to do regional and global simulations of deciduous broadleaf forests and assess their responses to climate change.

A new global time-series GPP production: DFRF-GPP

Understanding the global ecosystem carbon cycle requires a quantitative estimation of terrestrial gross primary production (GPP). Although most existing GPP estimates can accurately reflect the spatial distribution, interannual trends and even seasonal cycles of GPP under average conditions to some extent, the GPP estimates of different models under extreme climate conditions are still unsatisfactory. In this study, based on the random forest algorithm, we integrated the multimodel GPP simulation results published by the Multiscale Synthesis and Terrestrial Model Intercomparison Project, the FLUXNET flux-site-observed GPP, the standardized precipitation index (SPI) and the standardized temperature index (STI) to generate a set of global GPP time-series data products from 2001 to 2010. The new GPP product was named DFRF-GPP, referring to the GPP generated by data fusion based on random forest. The quality of DFRF-GPP was evaluated by comparison with current commonly used GPP datasets and GPP observations at FLUXNET flux sites. The results showed that DFRF-GPP is in great agreement with other GPP products and can reproduce the spatial and temporal patterns and interannual trends of global GPP, with optimal performance in regions such as those north of 30° in the Northern Hemisphere where there are more FLUXNET flux sites. DFRF-GPP has higher accuracy and excellent performance on drought and high-temperature samples, with higher sensitivity to drought and high temperature. This study not only provides a set of time-series products of global gross primary production but also provides a convenient and practical solution for enhancing the applicability of GPP estimation products in large-scale extreme climate studies.

Stronger Cumulative than Lagged Effects of Drought on Vegetation in Central Asia

In the context of global warming, the strength and frequency of drought events are projected to grow in the future, and the onset of drought can have dramatic effects on vegetation growth in terrestrial ecosystems. Central Asia is the largest non-territorial drought area in the world, and the response of vegetation to drought events is extremely sensitive in the area. However, few studies have quantified and compared the vegetation gross primary productivity (GPP) response to the lagged and cumulative effects of drought. In this research, the solar-induced chlorophyll fluorescence GPP and Standardized Precipitation Evaporation Index (SPEI) were used to analyze the time and space patterns of vegetation GPP and the SPEI in Central Asia and to quantify and compare the lagged and cumulative effects of drought on the GPP of various vegetation types. During the period from 2000 to 2018, the general trends of vegetation GPP showed a slight increase in Central Asia, with the ratio of variation being 1.35 g C m−2 y−1 and a spatially decreasing distribution from north to south. SPEI showed a trend of decreasing and then increasing over a period of 19 years, with a slight decreasing (drying) trend and a rate of change of −0.02 y−1, and the overall spatial pattern was drying out from north to south. In 13 months, 72.44% of regional droughts had lagged impacts on vegetation. The maximum correlation coefficients of vegetation and the lagged effectiveness of drought were concentrated in the range of 0.15–0.35, and the high correlation was distributed in southern and northwestern Kazakhstan, which are prairie regions. Of the regions in Central Asia, 75.86% showed cumulative drought effects concentrated at 9–12 months. The maximum correlation coefficients were concentrated in the range of 0.20–0.50, and the high correlation regions were primarily situated in south Kazakhstan and east Uzbekistan. Comparing the correlation coefficients of the lagged effect of vegetation GPP and SPEI with the cumulative effect shows that the cumulative rather than lagged impacts of drought on vegetation cover were found in 86.75% of the regions in Central Asia. This research enhances our comprehension of the influence of drought events on ecosystems in arid regions and has a certain reference value for helping arid region ecosystems to cope with global climate change.

Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data

While numerous studies report shifts in vegetation phenology, in this regard eddy covariance (EC) data, despite its continuous high-frequency observations, still requires further exploration. Furthermore, there is no general consensus on optimal methodologies for data smoothing and extracting phenological transition dates (PTDs). Here, we revisit existing methodologies and present new prospects to investigate phenological changes in gross primary productivity (GPP) from EC measurements. First, we present a smoothing technique of GPP time series through the derivative of its smoothed annual cumulative sum. Second, we calculate PTDs and their trends from a commonly used threshold method that identifies days with a fixed percentage of the annual maximum GPP. A systematic analysis is performed for various thresholds ranging from 0.1 to 0.7. Lastly, we examine the relation of PTDs trends to trends in GPP across the years on a weekly basis. Results from 47 EC sites with long time series (> 10 years) show that advancing trends in start of season (SOS) are strongest at lower thresholds but for the end of season (EOS) at higher thresholds. Moreover, the trends are variable at different thresholds for individual vegetation types and individual sites, outlining reasonable concerns on using a single threshold value. Relationship of trends in PTDs and weekly GPP reveal association of advanced SOS and delayed EOS to increase in immediate primary productivity, but not to the trends in overall seasonal productivity. Drawing on these analyses, we emphasise on abstaining from subjective choices and investigating relationship of PTDs trend to finer temporal trends of GPP. Our study examines existing methodological challenges and presents approaches that optimize the use of EC data in identifying vegetation phenological changes and their relation to carbon uptake.

Spatio-temporal analysis of the impact of land urbanization on the gross primary productivity of vegetation in the Middle Reaches of the Yangtze River Urban Agglomeration: new evidence from the township scale

The urgent need to maintain ecosystem provisioning services and achieve urban sustainable development goals has led to a long-standing focus on the driving effects of land urbanization (LU) in the Middle Reaches of the Yangtze River Urban Agglomeration (MRYRU) on vegetation cover system productivity. Previous studies have lacked consideration for the long-term correlation between land urbanization (LU) and the Gross Primary Productivity (GPP) of vegetation, as well as the spatial non-stationarity of LU’s impact in the region. This study is based on land cover remote sensing data and GPP imagery data to monitor the long-term evolution trends of LU and GPP in MRYRU from the perspectives of townships and grids. It further investigates the spatial correlation and clustering characteristics between the two using bivariate spatial autocorrelation method. Additionally, a Geographically and Temporally Weighted Regression (GTWR) model was employed to analyze the spatial effects of LU on GPP. The results indicate that the GPP of MRYRU grows to 1572.88gCm-2a-1 with an average annual growth rate of 0.848% from 2000 to 2020. High-value areas are distributed in the central and eastern mountainous of the urban agglomeration, while low-value areas gradually formed an “n”-shaped clustered distribution pattern. The negative spatial autocorrelation between LU and GPP shows a general upward trend, and Low-High is the dominant agglomeration type, concentrated in Hengyang and some mountainous cities in Jiangxi Province. The overall negative impact of land urbanization on GPP in MRYRU is maintained in the spatially nonstationary pattern of driving coefficients, with negative impact areas mostly concentrated in the city’s main city zone and positive impact areas concentrated in the urban agglomeration’s mountainous townships. This study provides support for MRYRU to adopt more resilient land optimization management strategies and vegetation ecological restoration plans.

Spatio-temporal patterns and drivers of carbon–water coupling in frozen soil zones across the gradients of freezing over the Qinghai-Tibet Plateau

The carbon and water cycle patterns of frozen soil ecosystems in regions, such as the Qinghai-Tibet Plateau (QTP), which have fragile and sensitive ecologies, are possibly affected by climate change. However, these patterns along the gradients of varying degrees of freezing remain poorly understood. In this study, we examine the spatio-temporal patterns of water use efficiency (WUE), gross primary productivity (GPP), and evapotranspiration (ET) in six frozen soil zones of the Qinghai-Tibet Plateau (QTP) with varying degrees of frozen soil. The analysis is based on the frozen soil classification criteria and remote sensing data from 2001 to 2020. The influences of six climatic, nine edaphic, and two botanic parameters on these patterns is also investigated. The results indicate that 48.05%, 24.07%, and 20% of the regions in QTP exhibit significantly upward trends of GPP, ET, and WUE, respectively. The highest increase trends were observed in GPP in the middle-thick seasonally frozen ground zone (2.36 g C m−2 yr−1), ET in the mountain permafrost zone (2.35 mm yr−1), and WUE in the predominantly continuous permafrost zone (0.003 g C kg−1 H2O yr−1). Meanwhile, GPP and WUE decrease progressively with the increase of freezing degrees, from the short-time frozen ground zone (GPP: 604.99 ± 51.99 g C m−2; WUE: 2.34 ± 0.15 g C kg−1 H2O) to the predominantly continuous permafrost zone (GPP: 114.07 ± 11.77 g C m−2; WUE: 0.33 ± 0.04 g C kg−1 H2O), while ET does not show significant differences across the three permafrost zones. The enhanced vegetation index is the primary factor affecting GPP and WUE in most frozen soil zones, whereas climate variables mainly impact ET. Our findings emphasize the importance of considering the effects of different freezing degrees of frozen soil when analyzing the response of the carbon and water cycles in the QTP in the context of climate change.

Land Surface Greening and CO2 Fertilization More than Offset the Gross Carbon Sequestration Decline Caused by Land Cover Change and the Enhanced Vapour Pressure Deficit in Europe

Satellite observations have revealed strong land surface “greening” (i.e., increases in vegetation greenness or leaf area index (LAI)) in the Northern Hemisphere over the past few decades. European terrestrial ecosystems are a greening hotspot, but how they respond to land surface greening, climate change, CO2 fertilization, land use and land cover change (LULCC) and other factors is unclear. Here, we assessed how these interacting factors might be combined to alter terrestrial gross primary production (GPP) throughout Europe during the period of 2001 to 2016 using a process-based Farquhar GPP model (i.e., FGM). We found a more productive European terrestrial ecosystem and most of the GPP enhancement in Europe was explained by increases in LAI (62%) and atmospheric CO2 concentration (29%). Spatially, the spatial signature of the LAI and GPP trends both suggested widespread (72–73% of the vegetated area) greening phenomena across Europe, among which 23.7% and 13.3% were statistically significant (p < 0.05). The interannual trend of GPP estimated by the FGM (0.55% yr−1) was reasonable compared with other GPP products (0.47% yr−1 to 0.92% yr−1) and the observed LAI increasing rate (0.62% yr−1). FGM factorial simulations suggested that land surface greening (+35.5 Pg C yr−2, p < 0.01), CO2 fertilization (+16.9 Pg C yr−2, p < 0.01), temperature warming (+3.7 Pg C yr−2, p < 0.05), and enhanced downwards solar radiation (+1.2 Pg C yr−2, p > 0.05) contributed to the GPP enhancement, while the enhanced vapour pressure deficit (−5.6 Tg C yr−2, p < 0.01) had significant negative impacts on GPP, especially in 2006 and 2012, when extreme droughts struck south-eastern Europe. Meanwhile, approximately 1.8% of the total area of Europe experienced LULCC from 2001 to 2016 and LULCC exerted a small but significant (−1.3 Tg C yr−2, p < 0.01) impact on GPP due to decreases in the total number of vegetated pixels (−159 pixels yr−1). Although the LULCC effect was negative, the largest increase occurred in forested land (+0.9% of total area). In addition, the increasing trends for the annual mean LAI (0.01 m2 m−2 yr−1, p < 0.001) and total GPP (22.2 Tg C yr−2, p < 0.001) of forests were more significant and higher than those of other vegetation types, suggesting that European forests may continue to play important roles in combating climate change in the future with long-lasting carbon storage potential. These results provide the first systematic quantitative analysis of the driving force of enhanced gross carbon assimilation by European ecosystems by considering variations in leaf physiological traits with environmental adaptations.

Vegetation growth due to CO2 fertilization is threatened by increasing vapor pressure deficit

Numerous studies found that the CO2 fertilization effect can enhance vegetation growth, however, some recent studies showed that the increase of vapor pressure deficit (VPD) could reduce vegetation growth due to an increase in surface resistance. It remains unclear to what extent VPD increases can offset the CO2 fertilization effect. Here, we examined the long-term trends of terrestrial gross primary productivity (GPP) at the global scale using six products derived from satellite observations, machine learning algorithms, and dynamic vegetation model simulations. While we found significant increases (p less than 0.05) in GPP in most of the world, we also found significant decreases in GPP over the Amazon basin, western North America, eastern Europe and central Asia. Our attribution analysis showed that although the elevated CO2 concentration dominated the long-term trends of GPP, VPD also played an important role. The increasing VPD could explain the decreasing GPP over the arid and tropical regions. The negative contribution of VPD to GPP trends appeared to become amplified with time, leading to suppressed global vegetation growth in the last two decades. The amplified contribution of VPD to GPP trends was directly related to the decrease in soil moisture, indicating the soil moisture-induced land–atmosphere coupling (LAC) and the vegetation growth stagnation since the year 2000. Our results provide insight into the negative contribution of VPD to long-term GPP trends, which can partly offset 68.21 % of the CO2 fertilization effect and even stagnate the vegetation growth with time. The possible mechanisms behind the effect of soil moisture-VPD coupling on the vegetation dynamics at the global scale needs further investigation.

Recent Seasonal Variations in Ecosystem Water Use Efficiency in China's Key Tropical‐Subtropical Transitional Zones in Response to Climate Change

AbstractUnderstanding the response of terrestrial ecosystem water use efficiency (WUE) to climate change is critical to accurately represent the carbon‐water cycle processes. However, how WUE dynamics are evolving under seasonal climate variations and biome‐specific characteristics remains still unclear. In this study, we integrated two state‐of‐the‐art retrieval algorithms to estimate gross primary productivity (GPP) and evapotranspiration (ET) from satellite MODIS records. Such metrics served as input to quantify ecosystem WUE, expressed as the ratio of GPP to ET, and explore its dynamics during the dry and wet season from 2001 to 2018 in China's key tropical to subtropical transitional zones, that is, Yunnan Province. Results show large spatial and seasonal variability in WUE over the observational period. During the dry season, the increasing trends in GPP and ET have led to contrasting WUE patterns in forest and non‐forest biomes, leading to positive and negative WUE trends, respectively. During the wet season, the declining trends in GPP occurring in combination with opposite trends in ET, have caused decreasing WUE consistently across all biomes except croplands, likely further modulated by human factors. The observed changes in WUE appear primarily driven by variations in air temperature (Ta) and vapor pressure deficit (VPD) during both dry and wet seasons. Overall, these results contribute to a better understanding of the carbon‐water interplay in tropical‐subtropical transitional zones and provide new insights to improve our capacity to predict the terrestrial ecosystem's response to climate change.

Increased carbon assimilation and efficient water usage may not compensate for carbon loss in European forests

Phenological responses of vegetation to global warming impact ecosystem gross primary production and evapotranspiration. However, high resolution and large spatial scale observational evidence of such responses in undisturbed core forest areas is lacking. Here, we analyse MODIS satellite data to assess monthly trends in gross primary productivity and evapotranspiration across undisturbed core forest areas in Europe between 2000 and 2020. Both parameters increased during the early spring and late autumn in nearly half of the total undisturbed core forest area (3601.5 km2). Enhanced productivity drove increased water-use-efficiency (the ratio of gross primary productivity to evapotranspiration). However, productivity increases during spring and autumn were not sufficient to compensate for summertime decreases in 25% of core forest areas. Overall, 20% of total gross primary productivity across all European forest core areas was offset by forest areas that exhibited a net decrease in productivity.

Three Decades of Gross Primary Production (GPP) in China: Variations, Trends, Attributions, and Prediction Inferred from Multiple Datasets and Time Series Modeling

The accurate estimation of gross primary production (GPP) is crucial to understanding plant carbon sequestration and grasping the quality of the ecological environment. Nevertheless, due to the inconsistencies of current GPP products, the variations, trends and short-term predictions of GPP have not been sufficiently well studied. In this study, we explore the spatiotemporal variability and trends of GPP and its associated climatic and anthropogenic factors in China from 1982 to 2015, mainly based on the optimum light use efficiency (LUEopt) product. We also employ an autoregressive integrated moving average (ARIMA) model to forecast the monthly GPP for a one-year lead time. The results show that GPP experienced an upward trend of 2.268 g C/m2 per year during the studied period, that is, an increasing rate of 3.9% per decade since 1982. However, these trend changes revealed distinct heterogeneity across space and time. The positive trends were mainly distributed in the Yellow River and Huaihe River out of the nine major river basins in China. We found that the dynamics of GPP were concurrently affected by climate factors and human activities. While air temperature and leaf area index (LAI) played dominant roles at a national level, the effects of precipitation, downward shortwave radiation (SRAD), carbon dioxide (CO2) and aerosol optical depth (AOD) exhibited discrepancies in terms of degree and scope. The ARIMA model achieved satisfactory prediction performance in most areas, though the accuracy was influenced by both data values and data quality. The model can potentially be generalized for other biophysical parameters with distinct seasonality. Our findings are further verified and corroborated by four widely used GPP products, demonstrating a good consistency of GPP trends and prediction. Our analysis provides a robust framework for characterizing long-term GPP dynamics that shed light on the improved assessment of the environmental quality of terrestrial ecosystems.

Divergent historical GPP trends among state-of-the-art multi-model simulations and satellite-based products

Abstract. Understanding historical changes in gross primary productivity (GPP) is essential for better predicting the future global carbon cycle. However, the historical trends of terrestrial GPP, due to the CO2 fertilization effect, climate, and land-use change, remain largely uncertain. Using long-term satellite-based near-infrared radiance of vegetation (NIRv), a proxy for GPP, and multiple GPP datasets derived from satellite-based products, dynamic global vegetation model (DGVM) simulations, and an upscaled product from eddy covariance (EC) measurements, here we comprehensively investigated their trends and analyzed the causes for any discrepancies during 1982–2015. Although spatial patterns of climatological annual GPP from all products and NIRv are highly correlated (r>0.84), the spatial correlation coefficients of trends between DGVM GPP and NIRv significantly decreased (with the ensemble mean of r=0.49) and even the spatial correlation coefficients of trends between other GPP products and NIRv became negative. By separating the global land into the tropics plus extratropical Southern Hemisphere (Trop+SH) and extratropical Northern Hemisphere (NH), we found that, during 1982–2015, simulated GPP from most of the models showed a stronger increasing trend over Trop+SH than NH. In contrast, the satellite-based GPP products indicated a substantial increase over NH. Mechanistically, model sensitivity experiments indicated that the increase of annual global total GPP was dominated by the CO2 fertilization effect (83.9 % contribution), however, with the largest uncertainty in magnitude in individual simulations among the three drivers of CO2 fertilization, climate, and land-use change. Interestingly, the spatial distribution of inter-model spreads of GPP trends resulted mainly from climate and land-use change rather than CO2 fertilization effect. After 2000, trends from satellite-based GPP products were different from the full time series, suggesting weakened rising trends over NH and even significantly decreasing trends over Trop+SH, while the trends from DGVMs and NIRv kept increasing. The inconsistencies of GPP trends are very likely caused by the contrasting performance between satellite-derived and DGVM simulated vegetation structure parameter (leaf area index, LAI). Therefore, the uncertainty in satellite-based GPP products induced by highly uncertain LAI data in the tropics undermines their roles in assessing the performance of DGVM simulations and understanding the changes of global carbon sinks. The higher consistency between DGVM GPP and NIRv suggests that the trends from a DGVM ensemble might even have better performance than satellite-based GPP products.

Attributions of Evapotranspiration and Gross Primary Production Changes in Semi-Arid Region: A Case Study in the Water Source Area of the Xiong’an New Area in North China

Investigating the attributions of evapotranspiration (ET) and gross primary production (GPP) changes is of great importance for regional, sustainable water resources and ecological management in semi-arid regions. Based on the simulation conducted during 2000–2019 by improving water-carbon coupling Distributed Time Variant Gain Model, the trends of ET and GPP were estimated and the driving factors were identified via 10 experimental scenarios in the water source area of the Xiong’an New Area in North China. The results show significant increases both in ET and GPP by 2.4 mm/a and 6.0 gC/m2/a in the region, respectively. At the annual scale, increasing precipitation dominates the ET uptrend. Air temperature, humidity and the interactive effects also contribute to the ET uptrend, and the contributions are 12.8%, 2.0% and 2.3%, respectively, while elevated atmospheric CO2 concentration (eCO2) and solar dimming lead to ET changes of about −7.2% and −12.4%, respectively. For the GPP changes, the increase in GPP is mainly caused by eCO2, increasing precipitation and rising temperature with the contributions of 56.7%, 34.8% and 27.8%, respectively. Solar dimming, humidity and windspeed contribute −6.8%, −4.8% and −3.5% of the GPP changes. Compared to climate change, land use and cover change has smaller effects on both ET and GPP for the few changes in land coverage. At the seasonal scale, ET and GPP increase to a greater extent during the growing season in spring and summer than in autumn and winter. Precipitation, temperature and eCO2 are generally the main causes for ET and GPP changes. Meanwhile, the decreasing humidity and rising temperature are dominant factors for ET and GPP increases, respectively, in winter. Furthermore, solar dimming has strong effects on ET reduction in autumn. The contribution of the interactive effects is much higher on a seasonal scale than annual scale, contributing to considerable decreases in ET and GPP in spring, increases in ET in autumn and winter, and an increase in GPP in winter. This study highlights the importance of considering water-carbon coupling on the attributions of ET and GPP changes and the differentiation of the effects by the abovementioned influential factors at annual and seasonal scales.

气候变化下中国不同植被区总初级生产力对干旱的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 气候变化下中国不同植被区总初级生产力对干旱的响应 DOI: 10.5846/stxb202010232707 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划资助（2019YFAO606900）；国家自然科学基金面上基金项目（42077436） Response of gross primary production to drought under climate change in different vegetation regions of China Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:干旱变化具有明显的空间分异，不同植被类型对干旱的响应亦有差别。开展气候变化下不同植被覆盖类型对干旱响应的差异分析，厘清温升干旱化进程对植被的影响，对了解植被发展动态及预测未来格局有着非常重要的意义。基于1982-2017年的总初级生产力（GPP）数据和同时期东安格利亚大学气候研究中心（CRU）时间序列（TS）气候数据，分析了中国8个植被区GPP和干旱的变化趋势，通过对比标准化降水指数（SPI）和标准化降水蒸散指数（SPEI）的趋势差异识别了典型的温升干旱化区域，在此基础上研究气温上升如何影响GPP对干旱的响应，进一步讨论了不同植被类型对干旱的敏感性差异。结果表明：（1）36年来8个植被区除青藏高原高寒植被区呈湿润化，其他植被区均呈现变干趋势；（2）气温上升大面积加剧了温带荒漠区和温带草原区的变干趋势；（3）亚热带常绿阔叶林区和热带季风雨林、雨林区的GPP受温度和干旱影响相当，青藏高原高寒植被区和针叶、落叶林混交林区的GPP受温度主导，其他植被区GPP均受干旱主导。 Abstract:Variations of drought have obviously spatial differentiation, and different vegetation types have different responses to drought. However, few studies have been conducted to distinguish the contribution of temperature increase to the variations of drought and to investigate the differences in the responses of different vegetation types to warming aridification on a large scale. Analyzing differences in the response of different vegetation cover types to drought under climate change and clarifying the impact of warming aridification on vegetation in China are of great importance for understanding the development dynamics of vegetation and predicting future patterns. In this study, based on climatic data from the University of East Anglia Climatic Research Unit (CRU) Time-series (TS) version 4.04 dataset, the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) were calculated in 1982-2017. Using Theil-Sen median trend analysis and the Mann-Kendall test, we analyzed trends in gross primary production (GPP) and drought in the eight vegetation regions of China. By comparing the trend differences between SPI and SPEI, typical warming aridification areas were identified under three scenarios ([SPI not significantly drier+SPEI significantly drier],[SPI wetter+ SPEI not significantly drier], and[SPI wetter+SPEI significantly drier]). Finally, after detrending GPP and temperature, the correlation analysis and multiple regression were used to investigate how temperature increase affected the response of GPP to drought and further discuss the differences in sensitivity of different vegetation regions to drought. The results showed that all eight vegetation regions showed a drying trend over past 36 years, except for Qinghai-Tibet plateau high cold vegetation region, which was getting wet. The GPP of each vegetation region mainly increased, among which the Qinghai-Tibet plateau high cold vegetation region showed the most significant increase in GPP, which might be related to the warming and wetting trend in this region. The temperature increase had the strongest exacerbating effect on drying in temperate desert region and temperate steppe region, and the weakest exacerbating effect on drying in temperate needleleaf and broadleaf forest region and cold temperate needleleaf forest region, while it significantly increased the sensitivity of GPP to drought in the latter. There was variability in the response of GPP to temperature and drought conditions in different vegetation regions:the GPP of the subtropical evergreen broad-leaved forest region and the tropical monsoon forest and rain forest region was comparably affected by both temperature and drought, the GPP of the Qinghai-Tibet plateau high cold vegetation region and temperate needleleaf and broadleaf forest region was dominantly affected by temperature, and the GPP in all other vegetation regions was mainly affected by drought. 参考文献 相似文献 引证文献

Continued Increases of Gross Primary Production in Urban Areas during 2000–2016

Urbanization affects vegetation within city administrative boundary and nearby rural areas. Gross primary production (GPP) of vegetation in global urban areas is one of important metrics for assessing the impacts of urbanization on terrestrial ecosystems. To date, very limited data and information on the spatial-temporal dynamics of GPP in the global urban areas are available. In this study, we reported the spatial distribution and temporal dynamics of annual GPP during 2000–2016 from 8,182 gridcells (0.5° by 0.5° latitude and longitude) that have various proportion of urban areas. Approximately 79.3% of these urban gridcells had increasing trends of annual GPP during 2000-2016. As urban area proportion (%) within individual urban gridcells increased, the means of annual GPP trends also increased. Our results suggested that for those urban gridcells, the negative effect of urban expansion (often measured by impervious surfaces) on GPP was to large degree compensated by increased vegetation within the gridcells, mostly driven by urban management and local climate and environment. Our findings on the continued increases of annual GPP in most of urban gridcells shed new insight on the importance of urban areas on terrestrial carbon cycle and the potential of urban management and local climate and environment on improving vegetation in urban areas.

Gross primary productivity and water use efficiency are increasing in a high rainfall tropical savanna.

Despite their size and contribution to the global carbon cycle, we have limited understanding of tropical savannas and their current trajectory with climate change and anthropogenic pressures. Here we examined interannual variability and externally forced long‐term changes in carbon and water exchange from a high rainfall savanna site in the seasonal tropics of north Australia. We used an 18‐year flux data time series (2001–2019) to detect trends and drivers of fluxes of carbon and water. Significant positive trends in gross primary productivity (GPP, 15.4 g C m2 year−2), ecosystem respiration (R eco, 8.0 g C m2 year−2), net ecosystem productivity (NEE, 7.4 g C m2 year−2) and ecosystem water use efficiency (WUE, 0.0077 g C kg H2O−1 year−1) were computed. There was a weaker, non‐significant trend in latent energy exchange (LE, 0.34 W m−2 year−1). Rainfall from a nearby site increased statistically over a 45‐year period during the observation period. To examine the dominant drivers of changes in GPP and WUE, we used a random forest approach and a terrestrial biosphere model to conduct an attribution experiment. Radiant energy was the dominant driver of wet season fluxes, whereas soil water content dominated dry season fluxes. The model attribution suggested that [CO2], precipitation and T air accounting for 90% of the modelled trend in GPP and WUE. Positive trends in fluxes were largest in the dry season implying tree components were a larger contributor than the grassy understorey. Fluxes and environmental drivers were not significant during the wet season, the period when grasses are active. The site is potentially still recovering from a cyclone 45 years ago and regrowth from this event may also be contributing to the observed trends in sequestration, highlighting the need to understand fluxes and their drivers from sub‐diurnal to decadal scales.

Spatiotemporal analysis of forest cover change and associated environmental challenges: a case study in the Central Highlands of Vietnam

Spatiotemporal regression combining Theil-Sen median trend and Man-Kendall tests was applied to MODIS time-series data to quantify the trend and rate of change to forest cover in the Central Highlands, Vietnam from 2001 to 2019. Several MODIS data products, including Percent Tree Cover (PTC), Evapotranspiration (ET), Land Surface Temperature (LST), and Gross Primary Productivity (GPP) were selected as indicators for forest cover and climate and carbon cycle patterns. Emerging hot spot analysis was applied to identify patterns of long-term deforestation. Spatial regression analysis using Geographically Weighted Regression (GWR) was performed to understand variations in the relationship between vegetation changes and trends in LST, ET, and GPP. Our analysis reveals that deforestation occurred significantly in the study area with a total decrease of 14.5% in PTC and a total of 7314 deforestation hot spots were identified. Results indicate that forest cover loss explains 72.9%, 67.7%, and 89.4% of the changes in ET, GPP, and LST, respectively, and the levels of influence are heterogenous across space and dependent on the types of deforestation hot spots. The approach introduced in our study can be performed worldwide to address complex research questions about environmental challenges that emerge from deforestation.

Large spatial variation and stagnation of cropland gross primary production increases the challenges of sustainable grain production and food security in China

Sustainable crop grain production and food security is a grand societal challenge. Substantial investments in China's agriculture have been made in the past decades, but our knowledge on cropland gross primary production in China remains limited. Here we analyzed gross primary production (GPP), solar-induced chlorophyll fluorescence (SIF), terrestrial water storage, crop grain production, and agricultural investment and policy during 2000–2018. We found that based on croplands in 2000, approximately 52 × 106 ha (~37%) had continuous increasing trends in GPP during 2000–2018, which were mainly located in northern China. GPP for 63% of croplands was stagnant, declined, or had no significant change. At the national scale, annual cropland GPP increased during 2000–2008 but became stagnant in 2009–2018, which was inconsistent with the interannual trend in the crop grain production data for 2009–2018. The spatial mismatch between crop production and water availability became worse. The major grain exporting provinces, mostly located in water-stressed regions, experienced increased water resource constraints, which posed a challenge for sustainable grain production. The stagnant cropland GPP and increasing water resource constraints highlight the urgent need for sustainable management for crop production and food security in China.

Land cover change-induced decline in terrestrial gross primary production over the conterminous United States from 2001 to 2016

As one of the most dynamic aspects of global environmental change, land cover change (LCC) has a profound impact on terrestrial carbon sequestration. However, LCC-induced carbon fluxes are still the most uncertain terms in global and regional carbon budgets. Ecosystem gross primary production (GPP) is the total carbon uptake by vegetation through photosynthesis, serving as a major control on ecosystem function and land carbon balance during and after the modification of the land surface. However, accurately capturing LCC-induced GPP changes requires both high-quality land cover data and controlling for variation driven by other environmental factors such as climate. In this study, we comprehensively examined the effects of LCC on annual GPP trends over the conterminous United States (CONUS) from 2001 to 2016 using the USGS National Land Cover Database, a remote sensing-driven ecosystem model, and the Google Earth Engine cloud computing platform. We designed a series of model experiments to identify LCC effects on GPP by controlling climate effects. During the study period, LCC exerted a strong negative effect on total GPP across the CONUS ([-2.2, -1.8] Tg C yr−2), while climate had smaller positive effects ([0.17, 0. 92] Tg C yr−2). The LCC-induced reduction of GPP was mainly caused by net forest loss ([-1.98, -1.39] Tg C yr−2) and urban expansion ([-2.03, -1.92] Tg C yr−2), but was partially offset by increases in crop area ([+0.66, +0.79] Tg C yr−2). Ensemble simulations from TRENDY did not capture the strong negative LCC influences on GPP, likely due to limitations of the adopted land use/cover data. Our study provides a novel perspective on LCC-induced GPP changes, which could help to improve our understanding of ecosystem function changes and constrain the estimation of land carbon balance in the context of anthropogenic activity and climate change.

Spatial, Phenological, and Inter-Annual Variations of Gross Primary Productivity in the Arctic from 2001 to 2019

Quantifying the spatial, seasonal (phenological), and inter-annual variations of gross primary productivity (GPP) in the Arctic is critical for comprehending the terrestrial carbon cycle and its feedback to climate warming in this region. Here, we evaluated the accuracy of the MOD17A2H GPP product using the FLUXNET 2015 dataset in the Arctic, then explored the spatial patterns, seasonal variations, and interannual trends of GPP, and investigated the dependence of the spatiotemporal variations in GPP on land cover types, latitude, and elevation from 2001 to 2019. The results showed that MOD17A2H was consistent with in situ measurements (R = 0.8, RMSE = 1.26 g C m−2 d−1). The functional phenology was also captured by the MOD17A2H product (R = 0.62, RMSE = 9 days) in the Arctic. The spatial variation of the seasonal magnitude of GPP and its interannual trends is partly related to land cover types, peaking in forests and lowest in grasslands. The interannual trend of GPP decreased as the latitude and elevation increased, except for the latitude between 62°~66° N and elevation below 700 m. Our study not only revealed the variation of GPP in the Arctic but also helped to understand the carbon cycle over this region.