Evaluation and improvement of MODIS gross primary productivity in typical forest ecosystems of East Asia based on eddy covariance measurements

2013 ◽  
Vol 18 (1) ◽  
pp. 31-40 ◽  
Author(s):  
Mingzhu He ◽  
Yanlian Zhou ◽  
Weimin Ju ◽  
Jingming Chen ◽  
Li Zhang ◽  
...  
Keyword(s):  
East Asia ◽  
Eddy Covariance ◽  
Primary Productivity ◽  
Forest Ecosystems ◽  
Gross Primary Productivity ◽  
Eddy Covariance Measurements

Legacy effects of drought on gross primary productivity from eddy-covariance measurements

2021 ◽  
Author(s):  
Xin Yu ◽  
René Orth ◽  
Markus Reichstein ◽  
Ana Bastos
Keyword(s):  
Eddy Covariance ◽  
Primary Productivity ◽  
Carbon Balance ◽  
Climatic Conditions ◽  
Gross Primary Productivity ◽  
Legacy Effects ◽  
Ecosystem Carbon ◽  
Ecosystem Carbon Balance ◽  
Eddy Covariance Measurements ◽  
Effects Of Drought

<p>The frequency and severity of droughts are expected to increase in the wake of climate change. Drought events not only cause direct impacts on the ecosystem carbon balance but also result in legacy effects during the following years. These legacies result from, for example, drought damage to the xylem or the crown which causes impaired growth, or from higher vulnerability to pests and diseases. To understand how droughts might affect the carbon cycle in the future, it is important to consider both direct and legacy effects. Such effects likely affect interannual variability in C fluxes but are challenging to detect in observations, and poorly represented in models. Therefore, the patterns and mechanisms inducing the legacy effects of drought on ecosystem carbon balance are necessarily needed to improve.</p><p>In this study, we analyze gross primary productivity (GPP) from eddy-covariance measurements in Germany to detect legacy effects from recent droughts. We follow a data-driven modeling approach using a random forest model trained in different sets of drought and non-drought periods. This approach allows quantifying legacy effects as deviations of observed GPP from modeled GPP in legacy years, which indicates a change in the vegetation response to hydro-climatic conditions as compared with the training period.</p>

scholarly journals Joint control of terrestrial gross primary productivity by plant phenology and physiology

2015 ◽  
Vol 112 (9) ◽  
pp. 2788-2793 ◽  
Author(s):  
Jianyang Xia ◽  
Shuli Niu ◽  
Philippe Ciais ◽  
Ivan A. Janssens ◽  
Jiquan Chen ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Primary Productivity ◽  
Abiotic Factors ◽  
Plant Phenology ◽  
Gross Primary Productivity ◽  
Fire Disturbance ◽  
Spatiotemporal Variability ◽  
Joint Control ◽  
Time And Space ◽  
Over Time

Terrestrial gross primary productivity (GPP) varies greatly over time and space. A better understanding of this variability is necessary for more accurate predictions of the future climate–carbon cycle feedback. Recent studies have suggested that variability in GPP is driven by a broad range of biotic and abiotic factors operating mainly through changes in vegetation phenology and physiological processes. However, it is still unclear how plant phenology and physiology can be integrated to explain the spatiotemporal variability of terrestrial GPP. Based on analyses of eddy–covariance and satellite-derived data, we decomposed annual terrestrial GPP into the length of the CO2 uptake period (CUP) and the seasonal maximal capacity of CO2 uptake (GPPmax). The product of CUP and GPPmax explained >90% of the temporal GPP variability in most areas of North America during 2000–2010 and the spatial GPP variation among globally distributed eddy flux tower sites. It also explained GPP response to the European heatwave in 2003 (r2 = 0.90) and GPP recovery after a fire disturbance in South Dakota (r2 = 0.88). Additional analysis of the eddy–covariance flux data shows that the interbiome variation in annual GPP is better explained by that in GPPmax than CUP. These findings indicate that terrestrial GPP is jointly controlled by ecosystem-level plant phenology and photosynthetic capacity, and greater understanding of GPPmax and CUP responses to environmental and biological variations will, thus, improve predictions of GPP over time and space.

Cloudiness regulates gross primary productivity of a poplar plantation under different environmental conditions

2017 ◽  
Vol 47 (5) ◽  
pp. 648-658 ◽  
Author(s):  
Hang Xu ◽  
Zhiqiang Zhang ◽  
Jiquan Chen ◽  
Mengxun Zhu ◽  
Manchun Kang
Keyword(s):  
Primary Productivity ◽  
Forest Ecosystems ◽  
Northern China ◽  
Gross Primary Productivity ◽  
Poplar Plantation ◽  
Radiation Component ◽  
Growing Seasons ◽  
Photosynthetic Productivity ◽  
Photosynthetic Potential ◽  
Lower Vapor Pressure

Cloud cover regulates the gross primary productivity (GPP) of forest ecosystems by changing the radiation component and other environmental factors. In this study, we used an open-path eddy covariance system and microclimate sensors installed over a poplar plantation in northern China to measure the carbon exchange and climate variables during the mid-growing seasons (June to August) in 2014 and 2015. The results indicated that the GPP of the plantation peaked when the clearness index (CI) was between 0.45 and 0.65, at which point diffuse photosynthetically active radiation (PARdif) had reached its maximum. Cloudy skies increased the maximum ecosystem photosynthetic capacity (Pmax) by 28% compared with clear skies. PARdif and soil moisture were the most and the least crucial drivers for photosynthetic productivity of the plantation under cloudy skies, respectively. The ecosystem photosynthetic potential was higher under lower vapor pressure deficit (VPD < 1.5 kPa), lower air temperature (Ta < 30 °C), and nonstressed conditions (REW > 0.4) for cloudy skies due to effects of Ta and VPD on stoma. Overall, our research highlighted the importance of cloud-induced radiation component change and environmental variation in quantifying the GPP of forest ecosystems.

Evaluation of MODIS gross primary productivity for Africa using eddy covariance data

2013 ◽  
Vol 131 ◽  
pp. 275-286 ◽  
Author(s):  
M. Sjöström ◽  
M. Zhao ◽  
S. Archibald ◽  
A. Arneth ◽  
B. Cappelaere ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Primary Productivity ◽  
Gross Primary Productivity

Evapotranspiration and gross primary productivity of secondary vegetation in Amazonia inferred by eddy covariance

2020 ◽  
Vol 294 ◽  
pp. 108141
Author(s):  
Rita de Cassia Silva von Randow ◽  
Javier Tomasella ◽  
Celso von Randow ◽  
Alessandro Carioca de Araújo ◽  
Antonio Ocimar Manzi ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Primary Productivity ◽  
Gross Primary Productivity ◽  
Secondary Vegetation

scholarly journals The Impact of the 20–50-Day Atmospheric Intraseasonal Oscillation on the Gross Primary Productivity between the Yangtze and Yellow Rivers

2020 ◽  
Vol 33 (8) ◽  
pp. 2967-2984
Author(s):  
Jianying Li ◽  
Jin-Soo Kim ◽  
Jong-Seong Kug
Keyword(s):  
Soil Moisture ◽  
East Asia ◽  
Primary Productivity ◽  
Meteorological Data ◽  
Intraseasonal Oscillation ◽  
Terrestrial Ecosystems ◽  
Gross Primary Productivity ◽  
Mean Power ◽  
Vegetation Growth ◽  
The Impact

AbstractGiven their high carbon uptake, the terrestrial ecosystems in the East Asia summer monsoon (EASM) region play an irreplaceable role in the global carbon cycle. Because the rich vegetation growth over East Asia benefits mainly from the sufficient water supply brought by the EASM, which is characterized by a strong intraseasonal oscillation (ISO), the intraseasonal spatiotemporal variations and underlying drivers of photosynthesis activity over East Asia have been comprehensively investigated using the daily gross primary productivity (GPP) and meteorological data. Strong intraseasonal fluctuations of GPP have been identified over the area between the Yangtze and Yellow Rivers (YYR) with a magnitude of 0.4 gC m−2 day−1. The mean power spectrum suggests that 20–50-day variation is the major component of the intraseasonal GPP anomalies over the YYR during the summers of 1980–2013. The 20–50-day ISO of YYR GPP anomalies is modulated by the local 20–50-day precipitation variation via soil moisture, with precipitation (soil moisture) leading GPP by 10 (7) days. The 20–50-day YYR precipitation anomalies are in turn controlled by tropical ISO signals, particularly the convective activity over the western North Pacific. This leading relationship between the 20–50-day atmospheric ISO and GPP suggests a potential for extended-range predictability of vegetation growth.

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