scholarly journals Moisture availability mediates the relationship between terrestrial gross primary production and solar‐induced chlorophyll fluorescence: Insights from global‐scale variations

2020 ◽  
Author(s):  
Anping Chen ◽  
Jiafu Mao ◽  
Daniel Ricciuto ◽  
Jingfeng Xiao ◽  
Christian Frankenberg ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Primary Production ◽  
Gross Primary Production ◽  
Global Scale ◽  
Moisture Availability ◽  
The Relationship

scholarly journals The Links between Canopy Solar-Induced Chlorophyll Fluorescence and Gross Primary Production Responses to Meteorological Factors in the Growing Season in Deciduous Broadleaf Forest

2021 ◽  
Vol 13 (12) ◽  
pp. 2363
Author(s):  
Xiangfen Cheng ◽  
Yu Zhou ◽  
Meijun Hu ◽  
Feng Wang ◽  
Hui Huang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Chlorophyll Fluorescence ◽  
Primary Production ◽  
Forest Canopy ◽  
Meteorological Factors ◽  
Gross Primary Production ◽  
Terrestrial Ecosystems ◽  
Growing Season ◽  
Near Surface ◽  
The Relationship

Solar-induced chlorophyll fluorescence (SIF) is a hopeful indicator, which along with remote sensing, is used to measure the photosynthetic efficiency and gross primary production (GPP) of vegetation in regional terrestrial ecosystems. Studies have found a significant linear correlation between SIF and GPP in a variety of ecosystems. However, this relationship has mainly been established using SIF and GPP data derived from satellite remote sensing and continuous ground-based observations, respectively, which are difficult to accurately match. To overcome this, some studies have begun to use tower-based automatic observation instruments to study the changes of near-surface SIF and GPP. This study conducts continuous simultaneous observation of SIF, carbon flux, and meteorological factors on the forest canopy of a cork oak plantation during the growing season to explore how meteorological factors impact on canopy SIF and its relationship with GPP. This research found that the canopy SIF has obvious diurnal and day-to-day variations during the growing season but overall is relatively stable. Furthermore, SIF is greatly affected by incident radiation in different weather conditions and can change daily. Meteorological factors have a major role in the relationship between SIF and GPP; overall, the relationship shows a significant linear regression on the 30 min scale, but weakens when aggregating to the diurnal scale. Photosynthetically active radiation (PAR) drives SIF on a daily basis and changes the relationship between SIF and GPP on a seasonal timescale. As PAR increases, the daily slopes of the linear regressions between SIF and GPP decrease. On the 30 min timescale, both SIF and GPP increase with PAR until it reaches 1250 μmol·m−2·s−1; subsequently, SIF continues to increase while GPP decreases and they show opposite trends. Soil moisture and vapor pressure deficit influence SIF and GPP, respectively. Our findings demonstrate that meteorological factors affect the relationship between SIF and GPP, thereby enhancing the understanding of the mechanistic link between chlorophyll fluorescence and photosynthesis.

scholarly journals Global Analysis of the Relationship between Reconstructed Solar-Induced Chlorophyll Fluorescence (SIF) and Gross Primary Production (GPP)

2021 ◽  
Vol 13 (14) ◽  
pp. 2824
Author(s):  
Haiqiang Gao ◽  
Shuguang Liu ◽  
Weizhi Lu ◽  
Andrew R. Smith ◽  
Rubén Valbuena ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Primary Production ◽  
Landscape Heterogeneity ◽  
Global Analysis ◽  
Gross Primary Production ◽  
Spatiotemporal Variability ◽  
Spatial And Temporal Scales ◽  
Discriminatory Analysis ◽  
Positive Correlations ◽  
The Relationship

Solar-induced chlorophyll fluorescence (SIF) is increasingly known as an effective proxy for plant photosynthesis, and therefore, has great potential in monitoring gross primary production (GPP). However, the relationship between SIF and GPP remains highly uncertain across space and time. Here, we analyzed the SIF (reconstructed, SIFc)–GPP relationships and their spatiotemporal variability, using GPP estimates from FLUXNET2015 and two spatiotemporally contiguous SIFc datasets (CSIF and GOSIF). The results showed that SIFc had significant positive correlations with GPP at the spatiotemporal scales investigated (p < 0.001). The generally linear SIFc–GPP relationships were substantially affected by spatial and temporal scales and SIFc datasets. The GPP/SIFc slope of the evergreen needleleaf forest (ENF) biome was significantly higher than the slopes of several other biomes (p < 0.05), while the other 11 biomes showed no significant differences in the GPP/SIFc slope between each other (p > 0.05). Therefore, we propose a two-slope scheme to differentiate ENF from non-ENF biome and synopsize spatiotemporal variability of the GPP/SIFc slope. The relative biases were 7.14% and 11.06% in the estimated cumulative GPP across all EC towers, respectively, for GOSIF and CSIF using a two-slope scheme. The significantly higher GPP/SIFc slopes of the ENF biome in the two-slope scheme are intriguing and deserve further study. In addition, there was still considerable dispersion in the comparisons of CSIF/GOSIF and GPP at both site and biome levels, calling for discriminatory analysis backed by higher spatial resolution to systematically address issues related to landscape heterogeneity and mismatch between SIFc pixel and the footprints of flux towers and their impacts on the SIF–GPP relationship.

scholarly journals Estimating Global Gross Primary Production from Sun-Induced Chlorophyll Fluorescence Data and Auxiliary Information Using Machine Learning Methods

2021 ◽  
Vol 13 (5) ◽  
pp. 963
Author(s):  
Yu Bai ◽  
Shunlin Liang ◽  
Wenping Yuan
Keyword(s):  
Machine Learning ◽  
Chlorophyll Fluorescence ◽  
Primary Production ◽  
Gross Primary Production ◽  
Global Scale ◽  
In Situ Measurements ◽  
Estimation Methods ◽  
Coefficient Of Determination ◽  
Flux Tower

The gross primary production (GPP) is important for regulating the global carbon cycle and climate change. Recent studies have shown that sun-induced chlorophyll fluorescence (SIF) is highly advantageous regarding GPP monitoring. However, using SIF to estimate GPP on a global scale is limited by the lack of a stable SIF-GPP relationship. Here, we estimated global monthly GPP at 0.05° spatial resolution for the period 2001–2017, using the global OCO-2-based SIF product (GOSIF) and other auxiliary data. Large amounts of flux tower data are not available to the public and the available data is not evenly distributed globally and has a smaller measured footprint than the GOSIF data. This makes it difficult to use the flux tower GPP directly as an input to the model. Our strategy is to scale in situ measurements using two moderate-resolution satellite GPP products (MODIS and GLASS). Specifically, these two satellite GPP products were calibrated and eventually integrated by in situ measurements (FLUXNET2015 dataset, 83 sites), which was then used to train a machine learning model (GBRT) that performed the best among five evaluated models. The GPP estimates from GOSIF were highly accurate coefficient of determination (R2) = 0.58, root mean square error (RMSE) = 2.74 g C·m−2, bias = –0.34 g C·m−2) as validated by in situ measurements, and exhibited reasonable spatial and seasonal variations on a global scale. Our method requires fewer input variables and has higher computational efficiency than other satellite GPP estimation methods. Satellite-based SIF data provide a unique opportunity for more accurate, near real-time GPP mapping in the future.

scholarly journals Extreme events in gross primary production: a characterization across continents

2014 ◽  
Vol 11 (1) ◽  
pp. 1869-1907 ◽  
Author(s):  
J. Zscheischler ◽  
M. D. Mahecha ◽  
S. Harmeling ◽  
A. Rammig ◽  
E. Tomelleri ◽  
...  
Keyword(s):  
South America ◽  
Primary Production ◽  
Extreme Events ◽  
Gross Primary Production ◽  
Climate Extremes ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Early Summer ◽  
Seasonal Effects ◽  
Data Sets

Abstract. Climate extremes can affect the functioning of terrestrial ecosystems, for instance via a reduction of the photosynthetic capacity or alterations of respiratory processes. Yet the dominant regional and seasonal effects of hydrometeorological extremes are still not well documented. Here we quantify and characterize the role of large spatiotemporal extreme events in gross primary production (GPP) as triggers of continental anomalies. We also investigate seasonal dynamics of extreme impacts on continental GPP anomalies. We find that the 50 largest positive (increase in uptake) and negative extremes (decrease in uptake) on each continent can explain most of the continental variation in GPP, which is in line with previous results obtained at the global scale. We show that negative extremes are larger than positive ones and demonstrate that this asymmetry is particularly strong in South America and Europe. Most extremes in GPP start in early summer. Our analysis indicates that the overall impacts and the spatial extents of GPP extremes are power law distributed with exponents that vary little across continents. Moreover, we show that on all continents and for all data sets the spatial extents play a more important role than durations or maximal GPP anomaly when it comes to the overall impact of GPP extremes. An analysis of possible causes implies that across continents most extremes in GPP can best be explained by water scarcity rather than by extreme temperatures. However, for Europe, South America and Oceania we identify also fire as an important driver. Our findings are consistent with remote sensing products. An independent validation against a literature survey on specific extreme events supports our results to a large extent.

scholarly journals Sensitivity of Estimated Total Canopy SIF Emission to Remotely Sensed LAI and BRDF Products

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Zhaoying Zhang ◽  
Yongguang Zhang ◽  
Jing M. Chen ◽  
Weimin Ju ◽  
Mirco Migliavacca ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Chlorophyll Fluorescence ◽  
Energy Balance ◽  
Primary Production ◽  
Gross Primary Production ◽  
Structural Effects ◽  
Canopy Interception ◽  
Monitoring Instrument ◽  
Uncertainty Level ◽  
Scope Model

Remote sensing of solar-induced chlorophyll fluorescence (SIF) provides new possibilities to estimate terrestrial gross primary production (GPP). To mitigate the angular and canopy structural effects on original SIF observed by sensors (SIFobs), it is recommended to derive total canopy SIF emission (SIFtotal) of leaves within a canopy using canopy interception (i0) and reflectance of vegetation (RV). However, the effects of the uncertainties in i0 and RV on the estimation of SIFtotal have not been well understood. Here, we evaluated such effects on the estimation of GPP using the Soil-Canopy-Observation of Photosynthesis and the Energy balance (SCOPE) model. The SCOPE simulations showed that the R2 between GPP and SIFtotal was clearly higher than that between GPP and SIFobs and the differences in R2 (ΔR2) tend to decrease with the increasing levels of uncertainties in i0 and RV. The resultant ΔR2 decreased to zero when the uncertainty level in i0 and RV was ~30% for red band SIF (RSIF, 683 nm) and ~20% for far-red band SIF (FRSIF, 740 nm). In addition, as compared to the TROPOspheric Monitoring Instrument (TROPOMI) SIFobs at both red and far-red bands, SIFtotal derived using any combination of i0 (from MCD15, VNP15, and CGLS LAI products) and RV (from MCD34, MCD19, and VNP43 BRDF products) showed comparable improvements in estimating GPP. With this study, we suggest a way to advance our understanding in the estimation of a more physiological relevant SIF datasets (SIFtotal) using current satellite products.

scholarly journals Extreme events in gross primary production: a characterization across continents

2014 ◽  
Vol 11 (11) ◽  
pp. 2909-2924 ◽  
Author(s):  
J. Zscheischler ◽  
M. Reichstein ◽  
S. Harmeling ◽  
A. Rammig ◽  
E. Tomelleri ◽  
...  
Keyword(s):  
South America ◽  
Primary Production ◽  
Extreme Events ◽  
Gross Primary Production ◽  
Climate Extremes ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Seasonal Effects ◽  
Carbon Uptake ◽  
Uptake Rates

Abstract. Climate extremes can affect the functioning of terrestrial ecosystems, for instance via a reduction of the photosynthetic capacity or alterations of respiratory processes. Yet the dominant regional and seasonal effects of hydrometeorological extremes are still not well documented and in the focus of this paper. Specifically, we quantify and characterize the role of large spatiotemporal extreme events in gross primary production (GPP) as triggers of continental anomalies. We also investigate seasonal dynamics of extreme impacts on continental GPP anomalies. We find that the 50 largest positive extremes (i.e., statistically unusual increases in carbon uptake rates) and negative extremes (i.e., statistically unusual decreases in carbon uptake rates) on each continent can explain most of the continental variation in GPP, which is in line with previous results obtained at the global scale. We show that negative extremes are larger than positive ones and demonstrate that this asymmetry is particularly strong in South America and Europe. Our analysis indicates that the overall impacts and the spatial extents of GPP extremes are power-law distributed with exponents that vary little across continents. Moreover, we show that on all continents and for all data sets the spatial extents play a more important role for the overall impact of GPP extremes compared to the durations or maximal GPP. An analysis of possible causes across continents indicates that most negative extremes in GPP can be attributed clearly to water scarcity, whereas extreme temperatures play a secondary role. However, for Europe, South America and Oceania we also identify fire as an important driver. Our findings are consistent with remote sensing products. An independent validation against a literature survey on specific extreme events supports our results to a large extent.

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