scholarly journals Increased atmospheric vapor pressure deficit reduces global vegetation growth

2019 ◽  
Vol 5 (8) ◽  
pp. eaax1396 ◽  
Author(s):  
Wenping Yuan ◽  
Yi Zheng ◽  
Shilong Piao ◽  
Philippe Ciais ◽  
Danica Lombardozzi ◽  
...  
Keyword(s):  
Vapor Pressure ◽  
Vapor Pressure Deficit ◽  
Vegetation Index ◽  
Global Climate ◽  
Gross Primary Production ◽  
Ecosystem Responses ◽  
Climate Conditions ◽  
Vegetation Growth ◽  
Current Century ◽  
Global Vegetation

Atmospheric vapor pressure deficit (VPD) is a critical variable in determining plant photosynthesis. Synthesis of four global climate datasets reveals a sharp increase of VPD after the late 1990s. In response, the vegetation greening trend indicated by a satellite-derived vegetation index (GIMMS3g), which was evident before the late 1990s, was subsequently stalled or reversed. Terrestrial gross primary production derived from two satellite-based models (revised EC-LUE and MODIS) exhibits persistent and widespread decreases after the late 1990s due to increased VPD, which offset the positive CO2 fertilization effect. Six Earth system models have consistently projected continuous increases of VPD throughout the current century. Our results highlight that the impacts of VPD on vegetation growth should be adequately considered to assess ecosystem responses to future climate conditions.

scholarly journals Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks

2021 ◽  
Author(s):  
Bin He ◽  
Chen Chen ◽  
Shangrong Lin ◽  
Wenping Yuan ◽  
Hans W Chen ◽  
...  
Keyword(s):  
Vapor Pressure ◽  
Interannual Variability ◽  
Environmental Variables ◽  
Vapor Pressure Deficit ◽  
Carbon Sink ◽  
Gross Primary Production ◽  
Terrestrial Ecosystem ◽  
Carbon Sinks ◽  
Terrestrial Carbon ◽  
Climate Conditions

Abstract Interannual variability of the terrestrial ecosystem carbon sink is substantially regulated by various environmental variables and highly dominates the interannual variation of atmospheric carbon dioxide (CO2) concentrations. Thus, it is necessary to determine dominating factors affecting the interannual variability of the carbon sink to improve our capability of predicting future terrestrial carbon sinks. Using global datasets derived from machine learning methods and process-based ecosystem models, this study reveals that the interannual variability of the atmospheric vapor pressure deficit (VPD) was significantly negatively correlated with net ecosystem production (NEP) and substantially impacted the interannual variability of the atmospheric CO2 growth rate (CGR). Further analyses found widespread constraints of VPD interannual variability on terrestrial gross primary production (GPP), causing VPD to impact NEP and CGR. Partial correlation analysis confirms the persistent and widespread impacts of VPD on terrestrial carbon sinks compared to other environmental variables. Current Earth system models underestimate the interannual variability in VPD and its impacts on GPP and NEP. Our results highlight the importance of VPD for terrestrial carbon sinks in assessing ecosystems’ responses to future climate conditions.

Climate-forced changes of bio-productivity of Belorussian terrestrial ecosystems

2019 ◽  
pp. 77-88
Author(s):  
S. A. Lysenko
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Vegetation Index ◽  
Precipitation Amount ◽  
Terrestrial Ecosystems ◽  
Vegetation Period ◽  
Climatic Trend ◽  
Vegetation Growth ◽  
Current Century ◽  
The Impact

The spatial and temporal particularities of Normalized Differential Vegetation Index (NDVI) changes over territory of Belarus in the current century and their relationship with climate change were investigated. The rise of NDVI is observed at approximately 84% of the Belarus area. The statistically significant growth of NDVI has exhibited at nearly 35% of the studied area (t-test at 95% confidence interval), which are mainly forests and undeveloped areas. Croplands vegetation index is largely descending. The main factor of croplands bio-productivity interannual variability is precipitation amount in vegetation period. This factor determines more than 60% of the croplands NDVI dispersion. The long-term changes of NDVI could be explained by combination of two factors: photosynthesis intensifying action of carbon dioxide and vegetation growth suppressing action of air warming with almost unchanged precipitation amount. If the observed climatic trend continues the croplands bio-productivity in many Belarus regions could be decreased at more than 20% in comparison with 2000 year. The impact of climate change on the bio-productivity of undeveloped lands is only slightly noticed on the background of its growth in conditions of rising level of carbon dioxide in the atmosphere.

scholarly journals Climate Dynamics of the Spatiotemporal Changes of Vegetation NDVI in Northern China from 1982 to 2015

2021 ◽  
Vol 13 (2) ◽  
pp. 187
Author(s):  
Rui Sun ◽  
Shaohui Chen ◽  
Hongbo Su
Keyword(s):  
Solar Radiation ◽  
Vegetation Index ◽  
Global Climate ◽  
Regional Scale ◽  
Northern China ◽  
Climate Dynamics ◽  
High Coverage ◽  
Vegetation Growth ◽  
Temperature And Precipitation ◽  
Precipitation And Temperature

As an important part of a terrestrial ecosystem, vegetation plays an important role in the global carbon-water cycle and energy flow. Based on the Global Inventory Monitoring and Modeling System (GIMMS) third generation of Normalized Difference Vegetation Index (NDVI3g), meteorological station data, climate reanalysis data, and land cover data, this study analyzed the climate dynamics of the spatiotemporal variations of vegetation NDVI in northern China from 1982 to 2015. The results showed that growth season NDVI (NDVIgs) increased significantly at 0.006/10a (p < 0.01) in 1982–2015 on the regional scale. The period from 1982 to 2015 was divided into three periods: the NDVIgs increased by 0.026/10a (p < 0.01) in 1982–1990, decreased by −0.002/10a (p > 0.1) in 1990–2006, and then increased by 0.021/10a (p < 0.01) during 2006–2015. On the pixel scale, the increases in NDVIgs during 1982–2015, 1982–1990, 1990–2006, and 2006–2015 accounted for 74.64%, 85.34%, 48.14%, and 68.78% of the total area, respectively. In general, the dominant climate drivers of vegetation growth had gradually switched from solar radiation, temperature, and precipitation (1982–1990) to precipitation and temperature (1990–2015). For woodland, high coverage grassland, medium coverage grassland, low coverage grassland, the dominant climate drivers had changed from temperature and solar radiation, solar radiation and precipitation, precipitation and solar radiation, solar radiation to precipitation and solar radiation, precipitation, precipitation and temperature, temperature and precipitation. The areas controlled by precipitation increased significantly, mainly distributed in arid, sub-arid, and sub-humid areas. The dominant climate drivers for vegetation growth in the plateau climate zone or high-altitude area changed from solar radiation to temperature and precipitation, and then to temperature, while in cold temperate zone, changed from temperature to solar radiation. These results are helpful to understand the climate dynamics of vegetation growth, and have important guiding significance for vegetation protection and restoration in the context of global climate change.

scholarly journals Soil moisture dominates dryness stress on ecosystem production globally

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Laibao Liu ◽  
Lukas Gudmundsson ◽  
Mathias Hauser ◽  
Dahe Qin ◽  
Shuangcheng Li ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Vapor Pressure Deficit ◽  
Arid Ecosystems ◽  
Drought Risk ◽  
Relative Role ◽  
Ecosystem Responses ◽  
Vegetation Growth ◽  
Ecosystem Production ◽  
Valid Data

Abstract Dryness stress can limit vegetation growth and is often characterized by low soil moisture (SM) and high atmospheric water demand (vapor pressure deficit, VPD). However, the relative role of SM and VPD in limiting ecosystem production remains debated and is difficult to disentangle, as SM and VPD are coupled through land-atmosphere interactions, hindering the ability to predict ecosystem responses to dryness. Here, we combine satellite observations of solar-induced fluorescence with estimates of SM and VPD and show that SM is the dominant driver of dryness stress on ecosystem production across more than 70% of vegetated land areas with valid data. Moreover, after accounting for SM-VPD coupling, VPD effects on ecosystem production are much smaller across large areas. We also find that SM stress is strongest in semi-arid ecosystems. Our results clarify a longstanding question and open new avenues for improving models to allow a better management of drought risk.

Amazon forest responses to drought: scaling from individuals to ecosystems.

2020 ◽  
Author(s):  
Scott R. Saleska ◽  
Natalia Restrepo-Coupe ◽  
Fernanda V. Barros ◽  
Paulo R. L. Bittencourt ◽  
Neill Prohaska ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Cycle ◽  
Ecosystem Respiration ◽  
Global Climate ◽  
Forest Composition ◽  
Future Climate Change ◽  
Amazon Forest ◽  
Ecosystem Responses ◽  
Climate Conditions ◽  
Dry Seasons

&lt;p&gt;Scaling from individuals or species to ecosystems is a fundamental challenge of modern ecology and understanding tropical forest response to drought is a key challenge of predicting responses to global climate change.&amp;#160; We here synthesize our developing understanding of these twin challenges by examining individual and ecosystem responses to the 2015 El Ni&amp;#241;o drought at two sites in the central Amazon of Brazil, near Manaus and Santarem, which span a precipitation gradient from moderate (Manaus) to long (Santarem) dry seasons.&amp;#160; We will focus on how ecosystem water and carbon cycling, measured by eddy flux towers, emerges from individual trait-based responses, including photosynthetic responses of individual leaves, and water cycle responses in terms of stomatal conductance and hydraulic xylem embolism resistance.&amp;#160; We found the Santarem forest (with long dry seasons) responded strongly to drought: sensible heat values significantly increased and evapotranspiration decreased.&amp;#160; Consistent with this, we also observed reductions in photosynthetic activity and ecosystem respiration, showing levels of stress not seen in the nearly two decades since measurements started at this site.&amp;#160; Forests at the Manaus site showed significant, however, less consistent reductions in water and carbon exchange and a more pronounced water deficit.&amp;#160; We report an apparent community level forest composition selecting for assemblies of traits and taxa manifest of higher drought tolerance at Santarem, compared to the Manaus forest (short dry seasons) and other forest sites across Amazonia.&amp;#160; These results suggest that we may be able to use community trait compositions (as selected by past climate conditions) and environmental threshold values (e.g. cumulative rainfall, atmospheric moisture and radiation) as to help forecast ecosystem responses to future climate change.&lt;/p&gt;

scholarly journals Inconsistency of Global Vegetation Dynamics Driven by Climate Change: Evidences from Spatial Regression

2021 ◽  
Vol 13 (17) ◽  
pp. 3442
Author(s):  
Dou Zhang ◽  
Xiaolei Geng ◽  
Wanxu Chen ◽  
Lei Fang ◽  
Rui Yao ◽  
...  
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Potential Evapotranspiration ◽  
Anthropogenic Activities ◽  
Test Method ◽  
Spatial Error ◽  
Vegetation Growth ◽  
Annual Peak ◽  
Global Vegetation

Global greening over the past 30 years since 1980s has been confirmed by numerous studies. However, a single-dimensional indicator and non-spatial modelling approaches might exacerbate uncertainties in our understanding of global change. Thus, comprehensive monitoring for vegetation’s various properties and spatially explicit models are required. In this study, we used the newest enhanced vegetation index (EVI) products of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 to detect the inconsistency trend of annual peak and average global vegetation growth using the Mann–Kendall test method. We explored the climatic factors that affect vegetation growth change from 2001 to 2018 using the spatial lag model (SLM), spatial error model (SEM) and geographically weighted regression model (GWR). The results showed that EVImax and EVImean in global vegetated areas consistently showed linear increasing trends during 2001–2018, with the global averaged trend of 0.0022 yr−1 (p < 0.05) and 0.0030 yr−1 (p < 0.05). Greening mainly occurred in the croplands and forests of China, India, North America and Europe, while browning was almost in the grasslands of Brazil and Africa (18.16% vs. 3.08% and 40.73% vs. 2.45%). In addition, 32.47% of the global vegetated area experienced inconsistent trends in EVImax and EVImean. Overall, precipitation and mean temperature had positive impacts on vegetation variation, while potential evapotranspiration and vapour pressure had negative impacts. The GWR revealed that the responses of EVI to climate change were inconsistent in an arid or humid area, in cropland or grassland. Climate change could affect vegetation characteristics by changing plant phenology, consequently rendering the inconsistency between peak and mean greening. In addition, anthropogenic activities, including land cover change and land use management, also could lead to the differences between annual peak and mean vegetation variations.

Amazon rainforest increases photosynthesis in reponse to atmospheric dryness

2020 ◽  
Author(s):  
Julia K. Green ◽  
Pierre Gentine ◽  
Yao Zhang ◽  
Joe Berry ◽  
Philippe Ciais
Keyword(s):  
Vapor Pressure ◽  
Vapor Pressure Deficit ◽  
Carbon Sink ◽  
Gross Primary Production ◽  
Remote Sensing Data ◽  
Amazon Rainforest ◽  
Machine Learning Techniques ◽  
Earth System ◽  
System Models ◽  
Earth System Models

&lt;p&gt;Earth system models predict that atmospheric dryness reduces photosynthesis due to its reductive effect on stomatal conductance. However, while this representation may be appropriate in many environments, in the wet Amazonian tropical rainforest, this is not the case. Using remote sensing data combined with machine learning techniques (k-means clustering and artificial neural networks), we show that in the wettest parts of the Amazon rainforest, gross primary production and evapotranspiration continue to increase alongside atmospheric dryness, i.e. vapor pressure deficit, despite reductions in ecosystem conductance. On the other hand, Earth system models have the opposite photosynthetic response to vapor pressure deficit in the wettest part of the Amazon, overestimating its reductive effect on tropical vegetation photosynthesis and evapotranspiration, leading to an exaggerated carbon source to the atmosphere. As vapor pressure deficit is expected to increase with climate change, our study highlights the importance of reframing how we understand and represent the response of ecosystem photosynthesis to atmospheric dryness in the wettest ecosystems, to accurately quantify the future land carbon sink and atmospheric CO2 growth rate.&lt;/p&gt;

scholarly journals Global Vegetation Photosynthetic Phenology Products Based on MODIS Vegetation Greenness and Temperature: Modeling and Evaluation

2021 ◽  
Vol 13 (24) ◽  
pp. 5080
Author(s):  
Xiaojun Xu ◽  
Yan Tang ◽  
Yiling Qu ◽  
Zhongsheng Zhou ◽  
Junguo Hu
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Deciduous Forest ◽  
Forest Type ◽  
Gross Primary Production ◽  
Plant Functional Types ◽  
Linear Regression Models ◽  
Climatic Regions ◽  
Functional Types ◽  
Global Vegetation

Land surface phenology (LSP) products that are derived from different data sources have different definitions and biophysical meanings. Discrepancies among these products and their linkages with carbon fluxes across plant functional types and climatic regions remain somewhat unclear. In this study, to differentiate LSP related to gross primary production (GPP) from LSP related to remote sensing data, we defined the former as vegetation photosynthetic phenology (VPP), including the starting and ending days of GPP (SOG and EOG, respectively). Specifically, we estimated VPP based on a combination of observed VPP from 145 flux-measured GPP sites together with the vegetation index and temperature data from MODIS products using multiple linear regression models. We then compared VPP estimates with MODIS LSP on a global scale. Our results show that the VPP provided better estimates of SOG and EOG than MODIS LSP, with a root mean square error (RMSE) for SOG of 12.7 days and a RMSE for EOG of 10.5 days. The RMSE was approximately three weeks for both SOG and EOG estimates of the non-forest type. Discrepancies between VPP and LSP estimates varied across plant functional types (PFTs) and climatic regions. A high correlation was observed between VPP and LSP estimates for deciduous forest. For most PFTs, using VPP estimates rather than LSP improved the estimation of GPP. This study presents a useful method for modeling global VPP, investigates in detail the discrepancies between VPP and LSP, and provides a more effective global vegetation phenology product for carbon cycle modeling than the existing ones.

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