scholarly journals Modeling light use efficiency in a subtropical mangrove forest equipped with CO<sub>2</sub> eddy covariance

2013 ◽  
Vol 10 (3) ◽  
pp. 2145-2158 ◽  
Author(s):  
J. G. Barr ◽  
V. Engel ◽  
J. D. Fuentes ◽  
D. O. Fuller ◽  
H. Kwon
Keyword(s):  
Eddy Covariance ◽  
Environmental Conditions ◽  
Mangrove Forest ◽  
Environmental Drivers ◽  
Model Parameters ◽  
Co2 Uptake ◽  
Light Use Efficiency ◽  
Co2 Fluxes ◽  
Use Efficiency ◽  
Reflectance Data

Abstract. Despite the importance of mangrove ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these forests remain poorly understood. This limited understanding is partly a result of the challenges associated with in situ flux studies. Tower-based CO2 eddy covariance (EC) systems are installed in only a few mangrove forests worldwide, and the longest EC record from the Florida Everglades contains less than 9 years of observations. A primary goal of the present study was to develop a methodology to estimate canopy-scale photosynthetic light use efficiency in this forest. These tower-based observations represent a basis for associating CO2 fluxes with canopy light use properties, and thus provide the means for utilizing satellite-based reflectance data for larger scale investigations. We present a model for mangrove canopy light use efficiency utilizing the enhanced green vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that is capable of predicting changes in mangrove forest CO2 fluxes caused by a hurricane disturbance and changes in regional environmental conditions, including temperature and salinity. Model parameters are solved for in a Bayesian framework. The model structure requires estimates of ecosystem respiration (RE), and we present the first ever tower-based estimates of mangrove forest RE derived from nighttime CO2 fluxes. Our investigation is also the first to show the effects of salinity on mangrove forest CO2 uptake, which declines 5% per each 10 parts per thousand (ppt) increase in salinity. Light use efficiency in this forest declines with increasing daily photosynthetic active radiation, which is an important departure from the assumption of constant light use efficiency typically applied in satellite-driven models. The model developed here provides a framework for estimating CO2 uptake by these forests from reflectance data and information about environmental conditions.

scholarly journals Satellite-based estimates of light-use efficiency in a subtropical mangrove forest equipped with CO<sub>2</sub> eddy covariance

2012 ◽  
Vol 9 (11) ◽  
pp. 16457-16492 ◽  
Author(s):  
J. G. Barr ◽  
V. Engel ◽  
J. D. Fuentes ◽  
D. O. Fuller ◽  
H. Kwon
Keyword(s):  
Eddy Covariance ◽  
Environmental Conditions ◽  
Mangrove Forest ◽  
Environmental Drivers ◽  
Model Parameters ◽  
Co2 Uptake ◽  
Light Use Efficiency ◽  
Co2 Fluxes ◽  
Use Efficiency ◽  
Reflectance Data

Abstract. Despite the importance of mangrove ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these forests remain poorly understood. This limited understanding is partly a result of the challenges associated with in situ flux studies. Tower-based carbon dioxide eddy covariance (EC) systems are installed in only a few mangrove forests worldwide and the longest EC record from the Florida Everglades contains less than 9 yr of observations. A primary goal of the present study was to develop a methodology to estimate canopy-scale photosynthetic light use efficiency in this forest. These tower-based observations represent a basis for associating CO2 fluxes with canopy light use properties, and thus provide the means for utilizing satellite-based reflectance data for larger-scale investigations. We present a model for mangrove canopy light use efficiency utilizing the enhanced green vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that is capable of predicting changes in mangrove forest CO2 fluxes caused by a hurricane disturbance and changes in regional environmental conditions, including temperature and salinity. Model parameters are solved for in a Bayesian framework. The model structure requires estimates of ecosystem respiration (RE) and we present the first-ever tower-based estimates of mangrove forest RE derived from night-time CO2 fluxes. Our investigation is also the first to show the effects of salinity on mangrove forest CO2 uptake, which declines 5% per each 10 parts per thousand (ppt) increases in salinity. Light use efficiency in this forest declines with increasing daily photosynthetic active radiation, which is an important departure from the assumption of constant light use efficiency typically applied in satellite-driven models. The model developed here provides a framework for estimating CO2 uptake by these forests from reflectance data and information about environmental conditions.

scholarly journals A Comparison between the MODIS Product (MOD17A2) and a Tide-Robust Empirical GPP Model Evaluated in a Georgia Wetland

2018 ◽  
Vol 10 (11) ◽  
pp. 1831 ◽  
Author(s):  
Jianbin Tao ◽  
Deepak Mishra ◽  
David Cotten ◽  
Jessica O’Connell ◽  
Monique Leclerc ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Vegetation Index ◽  
Gross Primary Production ◽  
Training Data ◽  
Environmental Drivers ◽  
Canopy Reflectance ◽  
Co2 Fluxes ◽  
Moisture Index ◽  
Validation Data ◽  
Reflectance Data

Despite the importance of tidal ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these wetlands remain poorly understood. This limited understanding results from the challenges associated with in situ flux studies and their correlation with satellite imagery which can be affected by periodic tidal flooding. Carbon dioxide eddy covariance (EC) towers are installed in only a few wetlands worldwide, and the longest eddy-covariance record from Georgia (GA) wetlands contains only two continuous years of observations. The goals of the present study were to evaluate the performance of existing MODIS Gross Primary Production (GPP) products (MOD17A2) against EC derived GPP and develop a tide-robust Normalized Difference Moisture Index (NDMI) based model to predict GPP within a Spartina alterniflora salt marsh on Sapelo Island, GA. These EC tower-based observations represent a basis to associate CO2 fluxes with canopy reflectance and thus provide the means to use satellite-based reflectance data for broader scale investigations. We demonstrate that Light Use Efficiency (LUE)-based MOD17A2 does not accurately reflect tidal wetland GPP compared to a simple empirical vegetation index-based model where tidal influence was accounted for. The NDMI-based GPP model was capable of predicting changes in wetland CO2 fluxes and explained 46% of the variation in flux-estimated GPP within the training data, and a root mean square error of 6.96 g C m−2 in the validation data. Our investigation is the first to create a MODIS-based wetland GPP estimation procedure that demonstrates the importance of filtering tidal observations from satellite surface reflectance data.

scholarly journals The effects of clouds and aerosols on net ecosystem CO<sub>2</sub> exchange over semi-arid Loess Plateau of Northwest China

2010 ◽  
Vol 10 (5) ◽  
pp. 13337-13372
Author(s):  
X. Jing ◽  
J. Huang ◽  
G. Wang ◽  
K. Higuchi ◽  
J. Bi ◽  
...  
Keyword(s):  
Loess Plateau ◽  
Air Temperature ◽  
Northwest China ◽  
Co2 Uptake ◽  
Observation Data ◽  
Light Use Efficiency ◽  
Clearness Index ◽  
Use Efficiency ◽  
The Difference ◽  
Semi Arid

Abstract. The impacts of clouds and atmospheric aerosols on the terrestrial carbon cycle at semi-arid Loess Plateau in Northwest China are investigated, by using the observation data obtained at the SACOL (Semi-Arid Climate and Environment Observatory of Lanzhou University) site. Daytime (solar elevation angles of larger than 50°) NEE of CO2 obtained during the midgrowing season (July–August) are analyzed with respect to variations in the diffuse radiation, cloud cover and aerosol optical depth (AOD). Results show a significant impact by clouds and aerosols on the CO2 uptake by the grassland (with smaller LAI values) located in a semi-arid region, quite different from areas covered by forests and crops. The light saturation levels in canopy are lower, with a value of about 434.8 W m−2. Thus, under overcast conditions of optically thick clouds, the CO2 uptake increases with increasing clearness index, and a maximum CO2 uptake and light use efficiency of vegetation occur with the clearness index of about 0.37 and lower air temperature. Under other sky conditions the CO2 uptake decreases with the cloudiness but the light use efficiency is enhanced, due to increase in the fraction of diffuse PAR. Additionally, under cloudy conditions, changes in the NEE of CO2 also result from the interactions of many environmental factors, especially the air temperature. In contrast to its response to changes in solar radiation, the carbon uptake shows a negative response to increased AOD. The reason for the difference in the response of the semi-arid grassland from that of the forest and crop lands may be due to the difference in the canopy's architectural structure.

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.

Estimating photosynthetic light-use efficiency using the photochemical reflectance index: variations among species

2004 ◽  
Vol 31 (3) ◽  
pp. 255 ◽  
Author(s):  
Jianmin Guo ◽  
Craig M. Trotter
Keyword(s):  
Light Response ◽  
Species Group ◽  
Photosynthetic Parameters ◽  
Co2 Uptake ◽  
Light Use Efficiency ◽  
Photochemical Reflectance Index ◽  
Response Data ◽  
Use Efficiency ◽  
Species Specific ◽  
The Relationship

Recent studies have shown that the photochemical reflectance index (PRI), derived from narrow waveband reflectance at 531 and 570 nm, can be used as a remote measure of photosynthetic light-use efficiency (LUE). However, uncertainty remains as to the consistency of the relationship between PRI and LUE across species. In this study we examined the relationship between the PRI and various photosynthetic parameters for a group of species with varying photosynthetic capacity. At constant irradiance, for the species group as a whole, the PRI was well correlated with LUE (r2=0.58) and with several other photosynthetic parameters, but best correlated with the ratio of carotenoids to chlorophylls contents (Caro / Chl). Despite the interspecific trends observed, determination of light response functions for the PRI in relation to photosynthetic parameters revealed that species-specific relationships were clearly stronger. For example, r2>0.90 for species-level PRI / LUE relationships. Also, the species-specific light-response data show that the magnitude of the PRI can be related to the magnitude of the saturated irradiance and the rate of CO2 uptake. As demonstrated here, a light response function provides a simple yet precise approach for characterising the relationship between the PRI and photosynthetic parameters, which should assist with improved evaluation of the usefulness of the PRI as a generalised measure of LUE.

scholarly journals Identification of a general light use efficiency model for gross primary production

2011 ◽  
Vol 8 (4) ◽  
pp. 999-1021 ◽  
Author(s):  
J. E. Horn ◽  
K. Schulz
Keyword(s):  
Primary Production ◽  
Large Scale ◽  
Gross Primary Production ◽  
Daily Basis ◽  
Climatic Conditions ◽  
Environmental Drivers ◽  
Light Use Efficiency ◽  
Meteorological Forcing ◽  
Use Efficiency ◽  
Light Use Efficiency Model

Abstract. Non-stationary and non-linear dynamic time series analysis tools are applied to multi-annual eddy covariance and micrometeorological data from 44 FLUXNET sites to derive a light use efficiency model for gross primary production on a daily basis. The extracted typical behaviour of the canopies in response to meteorological forcing leads to a model formulation allowing for a variable influence of the environmental drivers temperature and moisture availability modulating the light use efficiency. Thereby, the model is applicable to a broad range of vegetation types and climatic conditions. The proposed model explains large proportions of the variation of the gross carbon uptake at the study sites while the optimized set of six parameters is well defined. With the parameters showing explainable and meaningful relations to site-specific environmental conditions, the model has the potential to serve as basis for general regionalization strategies for large scale carbon flux predictions.

scholarly journals Short-term forecasting of regional biospheric CO<sub>2</sub> fluxes in Europe using a light-use-efficiency model (VPRM, MPI-BGC version 1.2)

2020 ◽  
Vol 13 (9) ◽  
pp. 4091-4106
Author(s):  
Jinxuan Chen ◽  
Christoph Gerbig ◽  
Julia Marshall ◽  
Kai Uwe Totsche
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Vegetation Type ◽  
Weather Prediction ◽  
Shortwave Radiation ◽  
Light Use Efficiency ◽  
Co2 Fluxes ◽  
Downward Shortwave Radiation ◽  
Use Efficiency ◽  
Light Use Efficiency Model

Abstract. Forecasting atmospheric CO2 concentrations on synoptic timescales (∼ days) can benefit the planning of field campaigns by better predicting the location of important gradients. One aspect of this, accurately predicting the day-to-day variation in biospheric fluxes, poses a major challenge. This study aims to investigate the feasibility of using a diagnostic light-use-efficiency model, the Vegetation Photosynthesis Respiration Model (VPRM), to forecast biospheric CO2 fluxes on the timescale of a few days. As input, the VPRM model requires downward shortwave radiation, 2 m temperature, and enhanced vegetation index (EVI) and land surface water index (LSWI), both of which are calculated from MODIS reflectance measurements. Flux forecasts were performed by extrapolating the model input into the future, i.e., using downward shortwave radiation and temperature from a numerical weather prediction (NWP) model, as well as extrapolating the MODIS indices to calculate future biospheric CO2 fluxes with VPRM. A hindcast for biospheric CO2 fluxes in Europe in 2014 has been done and compared to eddy covariance flux measurements to assess the uncertainty from different aspects of the forecasting system. In total the range-normalized mean absolute error (normalized) of the 5 d flux forecast at daily timescales is 7.1 %, while the error for the model itself is 15.9 %. The largest forecast error source comes from the meteorological data, in which error from shortwave radiation contributes slightly more than the error from air temperature. The error contribution from all error sources is similar at each flux observation site and is not significantly dependent on vegetation type.

scholarly journals Using MODIS derived <i>f</i>PAR with ground based flux tower measurements to derive the light use efficiency for two Canadian peatlands

2008 ◽  
Vol 5 (2) ◽  
pp. 1765-1794 ◽  
Author(s):  
J. Connolly ◽  
N. T. Roulet ◽  
J. W. Seaquist ◽  
N. M. Holden ◽  
P. M. Lafleur ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Photosynthetically Active Radiation ◽  
Vapour Pressure Deficit ◽  
Remote Sensing Data ◽  
Limiting Factor ◽  
Light Use Efficiency ◽  
Active Radiation ◽  
Flux Tower ◽  
Use Efficiency ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. We used satellite remote sensing data; fraction of photosynthetically active radiation absorbed by vegetation (fPAR) from the Moderate Resolution Imaging Spectroradiometer (MODIS) in combination with tower eddy covariance and meteorological measurements to characterise the light use efficiency parameter (ε) variability and the maximum ε (εmax) for two contrasting Canadian peatlands. Eight-day MODIS fPAR data were acquired for the Mer Bleue (2000 to 2003) and Western Peatland (2004). Flux tower eddy covariance and meteorological measurements were integrated to the same eight-day time stamps as the MODIS fPAR data. A light use efficiency model: GPP=ε * APAR (where GPP is Gross Primary Productivity and APAR is absorbed photosynthetically active radiation) was used to calculated ε. The εmax value for each year (2000 to 2003) at the Mer Bleue bog ranged from 0.58 g C MJ−1 to 0.78 g C MJ−1 and was 0.91 g C MJ−1 in 2004, for the Western Peatland. The average growing season ε for the Mer Bleue bog for the four year period was 0.35 g C MJ−1 and for the Western Peatland in 2004 was 0.57 g C MJ−1. The average snow free period ε for the Mer Bleue bog over the four year period was 0.27 g C MJ−1 and for the Western Peatland in 2004 was 0.39 g C MJ−1. Using the light use efficiency method we calculated the εmax and the annual variability in ε for two Canadian peatlands. We determined that temperature was a growth-limiting factor at both sites Vapour Pressure Deficit (VPD) however was not. MODIS fPAR is a useful tool for the characterization of ε at flux tower sites.

scholarly journals Identification of a general light use efficiency model for gross primary production

2010 ◽  
Vol 7 (5) ◽  
pp. 7673-7726 ◽  
Author(s):  
J. E. Horn ◽  
K. Schulz
Keyword(s):  
Large Scale ◽  
Gross Primary Production ◽  
Daily Basis ◽  
Climatic Conditions ◽  
Model Parameters ◽  
Light Use Efficiency ◽  
Meteorological Forcing ◽  
Use Efficiency ◽  
Study Sites ◽  
Light Use Efficiency Model

Abstract. Non-stationary and non-linear dynamic time series analysis tools are applied to multi-annual eddy covariance and micrometeorological data from 45 FLUXNET sites to derive a light use efficiency model on a daily basis. The extracted typical behaviour of the canopies in response to meteorological forcing leads to a model formulation allowing a variable influence of the model parameters modulating the light use efficiency. Thereby, the model is applicable to a broad range of vegetation types and climatic conditions. The proposed model explains large proportions of the variation of the gross carbon uptake at the study sites while the optimized set of six parameters is well defined. With the parameters showing explainable and meaningful relations to site-specific environmental conditions, the model has the potential to serve as basis for general regionalization strategies for large scale carbon flux predictions.

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