Proxy For Gross Primary Production Research Articles

A carbon sink-driven approach to estimate gross primary production from microwave satellite observations

Global estimation of Gross Primary Production (GPP) - the uptake of atmospheric carbon dioxide by plants through photosynthesis - is commonly based on optical satellite remote sensing data. This presents a source-driven approach since it uses the amount of absorbed light, the main driver of photosynthesis, as a proxy for GPP. Vegetation Optical Depth (VOD) estimates obtained from microwave sensors provide an alternative and independent data source to estimate GPP on a global scale, which may complement existing GPP products. Recent studies have shown that VOD is related to aboveground biomass, and that both VOD and temporal changes in VOD relate to GPP. In this study, we build upon this concept and propose a model for estimating GPP from VOD. Since the model is driven by vegetation biomass, as observed through VOD, it presents a carbon sink-driven approach to quantify GPP and, therefore, is conceptually different from common source-driven approaches. The model developed in this study uses single frequencies from active or passive microwave VOD retrievals from C-, X- and Ku-band (Advanced Scatterometer (ASCAT) and Advanced Microwave Scanning Radiometer for Earth Observation (AMSR-E)) to estimate GPP at the global scale. We assessed the ability for temporal and spatial extrapolation of the model using global GPP from FLUXCOM and in situ GPP from FLUXNET. We further performed upscaling of in situ GPP based on different VOD data sets and compared these estimates with the FLUXCOM and MODerate-resolution Imaging Spectroradiometer (MODIS) GPP products. Our results show that the model developed for individual grid cells using VOD and change in VOD as input performs well in predicting temporal patterns in GPP for all VOD data sets. For spatial extrapolation of the model, however, additional input variables are needed to represent the spatial variability of the VOD-GPP relationship due to differences in vegetation type. As additional input variable, we included the grid cell median VOD (as a proxy for vegetation cover), which increased the model performance during cross validation. Mean annual GPP obtained for AMSR-E X-band data tends to overestimate mean annual GPP for FLUXCOM and MODIS but shows comparable latitudinal patterns. Overall, our findings demonstrate the potential of VOD for estimating GPP. The sink-driven approach provides additional information about GPP independent of optical data, which may contribute to our knowledge about the carbon source-sink balance in different ecosystems.

Assessing the relationship between microwave vegetation optical depth and gross primary production

At the global scale, the uptake of atmospheric carbon dioxide by terrestrial ecosystems through photosynthesis is commonly estimated through vegetation indices or biophysical properties derived from optical remote sensing data. Microwave observations of vegetated areas are sensitive to different components of the vegetation layer than observations in the optical domain and may therefore provide complementary information on the vegetation state, which may be used in the estimation of Gross Primary Production (GPP). However, the relation between GPP and Vegetation Optical Depth (VOD), a biophysical quantity derived from microwave observations, is not yet known. This study aims to explore the relationship between VOD and GPP. VOD data were taken from different frequencies (L-, C-, and X-band) and from both active and passive microwave sensors, including the Advanced Scatterometer (ASCAT), the Soil Moisture Ocean Salinity (SMOS) mission, the Advanced Microwave Scanning Radiometer for Earth Observation System (AMSR-E) and a merged VOD data set from various passive microwave sensors. VOD data were compared against FLUXCOM GPP and Solar-Induced chlorophyll Fluorescence (SIF) from the Global Ozone Monitoring Experiment-2 (GOME-2). FLUXCOM GPP estimates are based on the upscaling of flux tower GPP observations using optical satellite data, while SIF observations present a measure of photosynthetic activity and are often used as a proxy for GPP. For relating VOD to GPP, three variables were analyzed: original VOD time series, temporal changes in VOD (ΔVOD), and positive changes in VOD (ΔVOD≥0). Results show widespread positive correlations between VOD and GPP with some negative correlations mainly occurring in dry and wet regions for active and passive VOD, respectively. Correlations between VOD and GPP were similar or higher than between VOD and SIF. When comparing the three variables for relating VOD to GPP, correlations with GPP were higher for the original VOD time series than for ΔVOD or ΔVOD≥0 in case of sparsely to moderately vegetated areas and evergreen forests, while the opposite was true for deciduous forests. Results suggest that original VOD time series should be used jointly with changes in VOD for the estimation of GPP across biomes, which may further benefit from combining active and passive VOD data.

Angular normalization of GOME‐2 Sun‐induced chlorophyll fluorescence observation as a better proxy of vegetation productivity

AbstractSun‐induced chlorophyll fluorescence (SIF) has been regarded as a promising proxy for gross primary productivity (GPP) over land. Considerable uncertainties in GPP estimation using remotely sensed SIF exist due to variations in the Sun‐satellite view observation geometry that could induce unwanted variations in SIF observation. In this study, we normalize the far‐red Global Ozone Monitoring Experiment‐2 SIF observations on sunny days to hot spot direction (SIFh) to represent sunlit leaves and compute a weighted sum of SIF (SIFt) from sunlit and shaded leaves to represent the canopy. We found that SIFh is better correlated with sunlit GPP simulated by a process‐based ecosystem model and SIFt is better correlated with the simulated total GPP than the original SIF observations. The coefficient of determination (R2) are increased by 0.04 ± 0.03, and 0.07 ± 0.04 on a global average using SIFh and SIFt, respectively. The most significant increases of the R2 (0.09 ± 0.04 for SIFt and 0.05 ± 0.03 for SIFh) appear in deciduous broadleaf forests.

Global Analysis of Bioclimatic Controls on Ecosystem Productivity Using Satellite Observations of Solar-Induced Chlorophyll Fluorescence

Ecosystem productivity models rely on regional climatic information to estimate temperature and moisture constraints influencing plant growth. However, the productivity response to these environmental factors is uncertain at the global scale and has largely been defined using limited observations from sparse monitoring sites, including carbon flux towers. Recent studies have shown that satellite observations of Solar-Induced chlorophyll Fluorescence (SIF) are highly correlated with ecosystem Gross Primary Productivity (GPP). Here, we use a relatively long-term global SIF observational record from the Global Ozone Monitoring Experiment-2 (GOME-2) sensors to investigate the relationships between SIF, used as a proxy for GPP, and selected bio-climatic factors constraining plant growth at the global scale. We compared the satellite SIF retrievals with collocated GPP observations from a global network of tower carbon flux monitoring sites and surface meteorological data from model reanalysis, including soil moisture, Vapor Pressure Deficit (VPD), and minimum daily air temperature (Tmin). We found strong correspondence (R2 > 80%) between SIF and GPP monthly climatologies for tower sites characterized by mixed, deciduous broadleaf, evergreen needleleaf forests, and croplands. For other land cover types including savanna, shrubland, and evergreen broadleaf forest, SIF showed significant but higher variability in correlations between sites. In order to analyze temperature and moisture related effects on ecosystem productivity, we divided SIF by photosynthetically active radiation (SIFp) and examined partial correlations between SIFp and the climatic factors across a global range of flux tower sites, and over broader regional and global extents. We found that productivity in arid ecosystems is more strongly controlled by soil water content to an extent that soil moisture explains a higher proportion of the seasonal cycle in productivity than VPD. At the global scale, ecosystem productivity is affected by joint climatic constraint factors so that VPD, Tmin, and soil moisture were significant (p < 0.05) controls over 60, 59, and 35 percent of the global domain, respectively. Our study identifies and confirms dominant climate control factors influencing productivity at the global scale indicated from satellite SIF observations. The results are generally consistent with climate response characteristics indicated from sparse global tower observations, while providing more extensive coverage for verifying and refining global carbon and climate model assumptions and predictions.

High sensitivity of gross primary production in the Rocky Mountains to summer rain

AbstractIn the catchments of the Rocky Mountains, peak snowpack is declining in response to warmer spring temperatures. To understand how this will influence terrestrial gross primary production (GPP), we compared precipitation data across the intermountain west with satellite retrievals of solar‐induced fluorescence (SIF), a proxy for GPP. Annual precipitation patterns explained most of the spatial and temporal variability of SIF, but the slope of the response was dependent on site to site differences in the proportion of snowpack to summer rain. We separated the response of SIF to different seasonal precipitation amounts and found that SIF was approximately twice as sensitive to variations in summer rain than snowpack. The response of peak GPP to a secular decline in snowpack will likely be subtle, whereas a change in summer rain amount will have precipitous effects on GPP. The study suggests that the rain use efficiency of Rocky Mountain ecosystems is strongly dependent on precipitation form and timing.

Modelling sun-induced fluorescence and photosynthesis with a land surface model at local and regional scales in northern Europe

Abstract. Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provide a large-scale proxy for gross primary production (GPP), thus providing a new way to assess the performance of land surface models (LSMs). In this study, we assessed how well SIF is able to predict GPP in the Fenno-Scandinavian region and what potential limitations for its application exist. We implemented a SIF model into the JSBACH LSM and used active leaf-level chlorophyll fluorescence measurements (Chl F) to evaluate the performance of the SIF module at a coniferous forest at Hyytiälä, Finland. We also compared simulated GPP and SIF at four Finnish micrometeorological flux measurement sites to observed GPP as well as to satellite-observed SIF. Finally, we conducted a regional model simulation for the Fenno-Scandinavian region with JSBACH and compared the results to SIF retrievals from the GOME-2 (Global Ozone Monitoring Experiment-2) space-borne spectrometer and to observation-based regional GPP estimates. Both observations and simulations revealed that SIF can be used to estimate GPP at both site and regional scales. At regional scale the model was able to simulate observed SIF averaged over 5 years with r2 of 0.86. The GOME-2-based SIF was a better proxy for GPP than the remotely sensed fAPAR (fraction of absorbed photosynthetic active radiation by vegetation). The observed SIF captured the seasonality of the photosynthesis at site scale and showed feasibility for use in improving of model seasonality at site and regional scale.

Spatially downscaling sun-induced chlorophyll fluorescence leads to an improved temporal correlation with gross primary productivity

Abstract Sun-induced chlorophyll fluorescence (SIF) is known to relate directly to leaf and canopy scale photosynthesis. Retrieving SIF from space can thus provide an indication on the temporal and spatial patterns of the terrestrial gross primary productivity (GPP). Recent studies have successfully demonstrated the serendipitous retrieval of SIF from satellite remote sensing instruments originally destined to atmospheric studies. However, the finest spatial resolution achieved by these products is 0.5°, which remains too coarse for many applications, including the early detection of drought impacts on vegetation and the integration with ground GPP measurements from flux-towers. This paper proposes a methodology to spatially disaggregate the information contained within each coarse SIF pixels by using a non-linear model based on the concept of light use efficiency (LUE). The strategy involves the aggregation of high-resolution (0.05°) remote sensing biophysical variables to calibrate the downscaling model locally and independently at each time step, which can then be applied to non-aggregated data to create a new layer, denoted SIF*, with a spatial resolution of 0.05°. A global SIF* dataset is generated by applying this methodology globally to 7 years of monthly GOME-2 SIF data. SIF* is shown to be a better proxy for GPP than the original coarse spatial resolution product according to flux-tower eddy covariance measurements. Its performance is comparable to dedicated GPP products despite that (unlike SIF*) these are calibrated based on the same flux towers, driven by meteorological data and not hampered by the large noise caused by the SIF retrieval. To further illustrate the added-value of the global SIF* product, this paper also presents: (1) an ecosystem level assessment showing a considerable reduction of noise with respect to the original SIF; (2) a spatio-temporal inter-comparison with existing GPP products; and (3) estimations of global terrestrial productivity per selected vegetation types based on SIF*.

Carbonyl sulfide exchange in soils for better estimates of ecosystem carbon uptake

Abstract. Carbonyl sulfide (COS) measurements are one of the emerging tools to better quantify gross primary production (GPP), the largest flux in the global carbon cycle. COS is a gas with a similar structure to CO2; COS uptake is thought to be a proxy for GPP. However, soils are a potential source or sink of COS. This study presents a framework for understanding soil–COS interactions. Excluding wetlands, most of the few observations of isolated soils that have been made show small uptake of atmospheric COS. Recently, a series of studies at an agricultural site in the central United States found soil COS production under hot conditions an order of magnitude greater than fluxes at other sites. To investigate the extent of this phenomenon, soils were collected from five new sites and incubated in a variety of soil moisture and temperature states. We found that soils from a desert, an oak savannah, a deciduous forest, and a rainforest exhibited small COS fluxes, behavior resembling previous studies. However, soil from an agricultural site in Illinois, > 800 km away from the initial central US study site, demonstrated comparably large soil fluxes under similar conditions. These new data suggest that, for the most part, soil COS interaction is negligible compared to plant uptake of COS. We present a model that anticipates the large agricultural soil fluxes so that they may be taken into account. While COS air-monitoring data are consistent with the dominance of plant uptake, improved interpretation of these data should incorporate the soil flux parameterizations suggested here.

Sea Surface Temperature Influence on Terrestrial Gross Primary Production along the Southern California Current.

Some land and ocean processes are related through connections (and synoptic-scale teleconnections) to the atmosphere. Synoptic-scale atmospheric (El Niño/Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO], and North Atlantic Oscillation [NAO]) decadal cycles are known to influence the global terrestrial carbon cycle. Potentially, smaller scale land-ocean connections influenced by coastal upwelling (changes in sea surface temperature) may be important for local-to-regional water-limited ecosystems where plants may benefit from air moisture transported from the ocean to terrestrial ecosystems. Here we use satellite-derived observations to test potential connections between changes in sea surface temperature (SST) in regions with strong coastal upwelling and terrestrial gross primary production (GPP) across the Baja California Peninsula. This region is characterized by an arid/semiarid climate along the southern California Current. We found that SST was correlated with the fraction of photosynthetic active radiation (fPAR; as a proxy for GPP) with lags ranging from 0 to 5 months. In contrast ENSO was not as strongly related with fPAR as SST in these coastal ecosystems. Our results show the importance of local-scale changes in SST during upwelling events, to explain the variability in GPP in coastal, water-limited ecosystems. The response of GPP to SST was spatially-dependent: colder SST in the northern areas increased GPP (likely by influencing fog formation), while warmer SST at the southern areas was associated to higher GPP (as SST is in phase with precipitation patterns). Interannual trends in fPAR are also spatially variable along the Baja California Peninsula with increasing secular trends in subtropical regions, decreasing trends in the most arid region, and no trend in the semi-arid regions. These findings suggest that studies and ecosystem process based models should consider the lateral influence of local-scale ocean processes that could influence coastal ecosystem productivity.

Solar‐induced chlorophyll fluorescence that correlates with canopy photosynthesis on diurnal and seasonal scales in a temperate deciduous forest

AbstractPrevious studies have suggested that solar‐induced chlorophyll fluorescence (SIF) is correlated with Gross Primary Production (GPP). However, it remains unclear to what extent this relationship is due to absorbed photosynthetically active radiation (APAR) and/or light use efficiency (LUE). Here we present the first time series of near‐surface measurement of canopy‐scale SIF at 760 nm in temperate deciduous forests. SIF correlated with GPP estimated with eddy covariance at diurnal and seasonal scales (r2 = 0.82 and 0.73, respectively), as well as with APAR diurnally and seasonally (r2 = 0.90 and 0.80, respectively). SIF/APAR is significantly positively correlated with LUE and is higher during cloudy days than sunny days. Weekly tower‐based SIF agreed with SIF from the Global Ozone Monitoring Experiment‐2 (r2 = 0.82). Our results provide ground‐based evidence that SIF is directly related to both APAR and LUE and thus GPP, and confirm that satellite SIF can be used as a proxy for GPP.

Remote‐sensing constraints on South America fire traits by Bayesian fusion of atmospheric and surface data

AbstractSatellite observations reveal substantial burning during the 2007 and 2010 tropical South America fire season, with both years exhibiting similar total burned area. However, 2010 CO fire emissions, based on satellite CO concentration measurements, were substantially lower (−28%), despite the once‐in‐a‐century drought in 2010. We use Bayesian inference with satellite measurements of CH4 and CO concentrations and burned area to quantify shifts in combustion characteristics in 2010 relative to 2007. We find an 88% probability in reduced combusted biomass density associated with the 2010 fires and an 82% probability of lower fire carbon losses in 2010 relative to 2007. Higher combustion efficiency was a smaller contributing factor to the reduced 2010 CO emissions. The reduction in combusted biomass density is consistent with a reduction (4–6%) in Global Ozone Monitoring Experiment 2 solar‐induced fluorescence (a proxy for gross primary production) during the preceding months and a potential reduction in biomass (≤8.3%) due to repeat fires.

Prospects for chlorophyll fluorescence remote sensing from the Orbiting Carbon Observatory-2

The Orbiting Carbon Observatory-2 (OCO-2), scheduled to launch in July 2014, is a NASA mission designed to measure atmospheric CO2. Its main purpose is to allow inversions of net flux estimates of CO2 on regional to continental scales using the total column CO2 retrieved using high-resolution spectra in the 0.76, 1.6, and 2.0μm ranges. Recently, it was shown that solar-induced chlorophyll fluorescence (SIF), a proxy for gross primary production (GPP, carbon uptake through photosynthesis), can be accurately retrieved from space using high spectral resolution radiances in the 750nm range from the Japanese GOSAT and European GOME-2 instruments. Here, we use real OCO-2 thermal vacuum test data as well as a full repeat cycle (16days) of simulated OCO-2 spectra under realistic conditions to evaluate the potential of OCO-2 for retrievals of chlorophyll fluorescence and also its dependence on clouds and aerosols. We find that the single-measurement precision is 0.3–0.5Wm−2sr−1μm−1 (15–25% of typical peak values), better than current measurements from space but still difficult to interpret on a single-sounding basis. The most significant advancement will come from smaller ground-pixel sizes and increased measurement frequency, with a 100-fold increase compared to GOSAT (and about 8 times higher than GOME-2). This will largely decrease the need for coarse spatial and temporal averaging in data analysis and pave the way to accurate local studies. We also find that the lack of full global mapping from the OCO-2 only incurs small representativeness errors on regional averages. Eventually, the combination of net ecosystem exchange (NEE) derived from CO2 source/sink inversions and SIF as proxy for GPP from the same satellite will provide a more process-based understanding of the global carbon cycle.

Camera derived vegetation greenness index as proxy for gross primary production in a low Arctic wetland area

The Arctic is experiencing disproportionate warming relative to the global average, and the Arctic ecosystems are as a result undergoing considerable changes. Continued monitoring of ecosystem productivity and phenology across temporal and spatial scales is a central part of assessing the magnitude of these changes. This study investigates the ability to use automatic digital camera images (DCIs) as proxy data for gross primary production (GPP) in a complex low Arctic wetland site. Vegetation greenness computed from DCIs was found to correlate significantly (R2=0.62, p<0.001) with a normalized difference vegetation index (NDVI) product derived from the WorldView-2 satellite. An object-based classification based on a bi-temporal image composite was used to classify the study area into heath, copse, fen, and bedrock. Temporal evolution of vegetation greenness was evaluated and modeled with double sigmoid functions for each plant community. GPP at light saturation modeled from eddy covariance (EC) flux measurements were found to correlate significantly with vegetation greenness for all plant communities in the studied year (i.e., 2010), and the highest correlation was found between modeled fen greenness and GPP (R2=0.85, p<0.001). Finally, greenness computed within modeled EC footprints were used to evaluate the influence of individual plant communities on the flux measurements. The study concludes that digital cameras may be used as a cost-effective proxy for potential GPP in remote Arctic regions.

The potential of carbonyl sulfide as a proxy for gross primary production at flux tower sites

[1] Seasonal dynamics of atmospheric carbonyl sulfide (OCS) at regional and continental scales and plant OCS exchange at the leaf level have shown a close relationship with those for CO2. CO2 has both sinks and sources within terrestrial ecosystems, but the primary terrestrial exchange for OCS is thought to be leaf uptake, suggesting potential for OCS uptake as a proxy for gross primary production (GPP). We explored the utility of OCS uptake as a GPP proxy in micrometeorological studies of biosphere-atmosphere CO2 exchange by applying theoretical concepts from earlier OCS studies to estimate GPP. We partitioned measured net ecosystem exchange (NEE) using the ratio of measured vertical mole fraction gradients of OCS and CO2. At the Harvard Forest AmeriFlux site, measured CO2 and OCS vertical gradients were correlated and were related to NEE and GPP, respectively. Estimates of GPP from OCS-based NEE partitioning were similar to those from established environmental regression techniques, providing evidence that OCS uptake can potentially serve as a GPP proxy. Measured vertical CO2 mole fraction gradients at five other AmeriFlux sites were used to project anticipated vertical OCS mole fraction gradients to provide indication of potential OCS signal magnitudes at sites where no OCS measurements were made. Projected OCS gradients at sites with short canopies were greater than those in forests, including measured OCS gradients at Harvard Forest, indicating greater potential for OCS uptake as a GPP proxy at these sites. This exploratory study suggests that continued investigation of linkages between OCS and GPP is warranted.

Remote estimation of gross primary production in maize and support for a new paradigm based on total crop chlorophyll content

The accurate quantification of gross primary production (GPP) in crops is important for regional and global studies of carbon budgets. Because of the observed close relationship between GPP and total canopy chlorophyll content in crops, vegetation indices related to chlorophyll can be used as a proxy of GPP. In this study, we justified the approach, tested the performance of several widely used chlorophyll-related vegetation indices in estimating total chlorophyll content and GPP in maize based on spectral data collected at a close range, 6 meters above the top of the canopy, over a period of eight years (2001 to 2008). The results show that GPP can be accurately estimated with chlorophyll-related indices that use near infra-red and either green or the red edge range of the spectrum. These indices provide the best approximation of the widely variable GPP in maize under both irrigated and rainfed conditions.

Remote estimation of gross primary production in wheat using chlorophyll-related vegetation indices

A number of recent studies have focused on estimating gross primary production (GPP) using vegetation indices (VIs). In this paper, GPP is retrieved as a product of incident light use efficiency (LUE), defined as GPP/PAR, and the photosynthetically active radiation (PAR). As a good correlation is found between canopy chlorophyll content and incident LUE for six types of wheat canopy ( R 2 = 0.87, n = 24), indices aimed for chlorophyll assessment can be used as an indicator of incident LUE and the product of chlorophyll indices and PAR will be a proxy of GPP. In a field experiment, we investigated four canopy chlorophyll content related indices (Red edge Normalized Difference Vegetation Index [Red Edge NDVI], modified Chlorophyll Absorption Ratio Index [MCARI 710], Red Edge Chlorophyll Index [CI red edge] and the MERIS Terrestrial Chlorophyll Index [MTCI]) for GPP estimation during the growth cycle of wheat. These indices are validated for leaf and canopy chlorophyll estimation with ground truth data of canopy chlorophyll content. With ground truth data, a strong correlation is observed for canopy chlorophyll estimation with correlation coefficients R 2 of 0.79, 0.84, 0.85 and 0.87 for Red Edge NDVI, MCARI 710, CI red edge and MTCI, respectively ( n = 24). As evidence of the existence of a relationship between canopy chlorophyll and GPP/PAR, these indices are shown to be a good proxy of GPP/PAR with R 2 ranging from 0.70 for Red Edge NDVI and 0.75 for MTCI ( n = 240). Remote estimation of GPP from canopy chlorophyll content × PAR is proved to be relatively successful ( R 2 of 0.47, 0.53, 0.65 and 0.66 for Red edge NDVI, MCARI 710, CI red edge and MTCI respectively, n = 240). These results open up a new possibility to estimate GPP and should inspire new models for remote sensing of GPP.