scholarly journals Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data

2018 ◽  
Vol 10 (9) ◽  
pp. 1346 ◽  
Author(s):  
Joanna Joiner ◽  
Yasuko Yoshida ◽  
Yao Zhang ◽  
Gregory Duveiller ◽  
Martin Jung ◽  
...  
Keyword(s):  
Primary Production ◽  
Eddy Covariance ◽  
Satellite Data ◽  
Gross Primary Production ◽  
Satellite Observation ◽  
Data Driven ◽  
Spatial And Temporal Variability ◽  
Light Use Efficiency ◽  
High Productivity ◽  
Use Efficiency

We estimate global terrestrial gross primary production (GPP) based on models that use satellite data within a simplified light-use efficiency framework that does not rely upon other meteorological inputs. Satellite-based geometry-adjusted reflectances are from the MODerate-resolution Imaging Spectroradiometer (MODIS) and provide information about vegetation structure and chlorophyll content at both high temporal (daily to monthly) and spatial (∼1 km) resolution. We use satellite-derived solar-induced fluorescence (SIF) to identify regions of high productivity crops and also evaluate the use of downscaled SIF to estimate GPP. We calibrate a set of our satellite-based models with GPP estimates from a subset of distributed eddy covariance flux towers (FLUXNET 2015). The results of the trained models are evaluated using an independent subset of FLUXNET 2015 GPP data. We show that variations in light-use efficiency (LUE) with incident PAR are important and can be easily incorporated into the models. Unlike many LUE-based models, our satellite-based GPP estimates do not use an explicit parameterization of LUE that reduces its value from the potential maximum under limiting conditions such as temperature and water stress. Even without the parameterized downward regulation, our simplified models are shown to perform as well as or better than state-of-the-art satellite data-driven products that incorporate such parameterizations. A significant fraction of both spatial and temporal variability in GPP across plant functional types can be accounted for using our satellite-based models. Our results provide an annual GPP value of ∼140 Pg C year - 1 for 2007 that is within the range of a compilation of observation-based, model, and hybrid results, but is higher than some previous satellite observation-based estimates.

scholarly journals P-model v1.0: An optimality-based light use efficiency model for simulating ecosystem gross primary production

2019 ◽  
Author(s):  
Benjamin D. Stocker ◽  
Han Wang ◽  
Nicholas G. Smith ◽  
Sandy P. Harrison ◽  
Trevor F. Keenan ◽  
...  
Keyword(s):  
Primary Production ◽  
Satellite Data ◽  
Vegetation Type ◽  
Meteorological Data ◽  
Gross Primary Production ◽  
Satellite Monitoring ◽  
Light Use Efficiency ◽  
Spatial And Temporal Scales ◽  
Wide Range ◽  
Use Efficiency

Abstract. Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth System Model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a gross primary production (GPP, photosynthesis per unit ground area) model, the P-model, that combines the Farquhar-von Caemmerer-Berry model for C3 photosynthesis with an optimality principle for the carbon assimilation-transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C3 vegetation type. The model is forced here with satellite data for the fraction of absorbed photosynthetically active radiation and site-specific meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs and prescribed parameters, the R2 for predicted versus observed GPP based on the full model setup is 0.75 (8-day mean, 131 sites) – better than some state-of-the-art satellite data-driven light use efficiency models. The R2 is reduced to 0.69 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R2 for the P-model-predicted LUE is 0.37 (means by site) and 0.53 (means by vegetation type). The P-model provides a simple but powerful method for predicting – rather than prescribing – light use efficiency and simulating terrestrial photosythesis across a wide range of conditions. The model is available as an R package (rpmodel).

scholarly journals Technical note: Estimating light-use efficiency of benthic habitats using underwater O<sub>2</sub> eddy covariance

2020 ◽  
Author(s):  
Karl M. Attard ◽  
Ronnie N. Glud
Keyword(s):  
Primary Production ◽  
Eddy Covariance ◽  
Technological Development ◽  
Gross Primary Production ◽  
Technical Note ◽  
Light Use Efficiency ◽  
Atmospheric Sciences ◽  
In Situ Conditions ◽  
Order Of Magnitude ◽  
Use Efficiency

Abstract. Light-use efficiency defines the ability of primary producers to convert sunlight energy to primary production and is computed as the ratio between the gross primary production and the intercepted photosynthetic active radiation. While this measure has been applied broadly within the atmospheric sciences to investigate resource-use efficiency in terrestrial habitats, it remains underused within the aquatic realm. This report provides a conceptual framework to compute hourly and daily light-use efficiency using underwater O2 eddy covariance, a recent technological development that produces habitat-scale rates of primary production under unaltered in situ conditions. The analysis, tested on two flux datasets, documents that hourly light-use efficiency may approach the maximum theoretical limit of 0.125 O2 photon−1 under low light conditions but it decreases rapidly towards the middle of the day and is typically an order of magnitude lower on a 24 h basis. Overall, light-use efficiency provides a useful measure of habitat functioning and facilitates site comparison in time and space.

scholarly journals Technical note: Estimating light-use efficiency of benthic habitats using underwater O<sub>2</sub> eddy covariance

2020 ◽  
Vol 17 (16) ◽  
pp. 4343-4353
Author(s):  
Karl M. Attard ◽  
Ronnie N. Glud
Keyword(s):  
Primary Production ◽  
Eddy Covariance ◽  
Technological Development ◽  
Gross Primary Production ◽  
Technical Note ◽  
Light Use Efficiency ◽  
In Situ Conditions ◽  
Use Efficiency ◽  
Habitat Scale

Abstract. Light-use efficiency defines the ability of primary producers to convert sunlight energy to primary production and is computed as the ratio between the gross primary production and the intercepted photosynthetic active radiation. While this measure has been applied broadly within terrestrial ecology to investigate habitat resource-use efficiency, it remains underused within the aquatic realm. This report provides a conceptual framework to compute hourly and daily light-use efficiency using underwater O2 eddy covariance, a recent technological development that produces habitat-scale rates of primary production under unaltered in situ conditions. The analysis, tested on two benthic flux datasets, documents that hourly light-use efficiency may approach the theoretical limit of 0.125 O2 per photon under low-light conditions, but it decreases rapidly towards the middle of the day and is typically 10-fold lower on a 24 h basis. Overall, light-use efficiency provides a useful measure of habitat functioning and facilitates site comparison in time and space.

scholarly journals Integration of Sentinel-3 OLCI Land Products and MERRA2 Meteorology Data into Light Use Efficiency and Vegetation Index-Driven Models for Modeling Gross Primary Production

2021 ◽  
Vol 13 (5) ◽  
pp. 1015
Author(s):  
Fengji Zhang ◽  
Zhijiang Zhang ◽  
Yi Long ◽  
Ling Zhang
Keyword(s):  
Primary Production ◽  
Eddy Covariance ◽  
Large Scale ◽  
Vegetation Index ◽  
Gross Primary Production ◽  
Regional Scale ◽  
Reanalysis Data ◽  
Light Use Efficiency ◽  
The Us ◽  
Use Efficiency

Accurately and reliably estimating total terrestrial gross primary production (GPP) on a large scale is of great significance for monitoring the carbon cycle process. The Sentinel-3 satellite provides the OLCI FAPAR and OTCI products, which possess a higher spatial and temporal resolution than MODIS products. However, few studies have focused on using LUE models and VI-driven models based on the Sentinel-3 satellites to estimate GPP on a large scale. The purpose of this study is to evaluate the performance of Sentinel-3 OLCI FAPAR and OTCI products combined with meteorology reanalysis data in estimating GPP at site and regional scale. Firstly, we integrated OLCI FAPAR and meteorology reanalysis data into the MODIS GPP algorithm and eddy covariance light use efficiency (EC-LUE) model (GPPMODIS-GPP and GPPEC-LUE, respectively). Then, we combined OTCI and meteorology reanalysis data with the greenness and radiation (GR) model and vegetation index (VI) model (GPPGR and GPPVI, respectively). Lastly, GPPMODIS-GPP, GPPEC-LUE, GPPGR, and GPPVI were evaluated against the eddy covariance flux data (GPPEC) at the site scale and MODIS GPP products (GPPMOD17) at the regional scale. The results showed that, at the site scale, GPPMODIS-GPP and GPPEC-LUE agreed well with GPPEC for the US-Ton site, with R2 = 0.73 and 0.74, respectively. The performance of GPPGR and GPPVI varied across different biome types. Strong correlations were obtained across deciduous broadleaf forests, mixed forests, grasslands, and croplands. At the same time, there are overestimations and underestimations in croplands, evergreen needleleaf forests and deciduous broadleaf forests. At the regional scale, the annual mean and maximum daily GPPMODIS-GPP and GPPEC-LUE agreed well with GPPMOD17 in 2017 and 2018, with R2 > 0.75. Overall, the above findings demonstrate the feasibility of using Sentinel-3 OLCI FAPAR and OTCI products combined with meteorology reanalysis data through LUE and VI-driven models to estimate GPP, and fill in the gaps for the large-scale evaluation of GPP via Sentinel-3 satellites.

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