Gross Primary Production Products Research Articles

Evaluation of MODIS NPP and GPP products across multiple biomes

Estimates of daily gross primary production (GPP) and annual net primary production (NPP) at the 1 km spatial resolution are now produced operationally for the global terrestrial surface using imagery from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. Ecosystem-level measurements of GPP at eddy covariance flux towers and plot-level measurements of NPP over the surrounding landscape offer opportunities for validating the MODIS NPP and GPP products, but these flux measurements must be scaled over areas on the order of 25 km 2 to make effective comparisons to the MODIS products. Here, we report results for such comparisons at 9 sites varying widely in biome type and land use. The sites included arctic tundra, boreal forest, temperate hardwood forest, temperate conifer forest, tropical rain forest, tallgrass prairie, desert grassland, and cropland. The ground-based NPP and GPP surfaces were generated by application of the Biome-BGC carbon cycle process model in a spatially-distributed mode. Model inputs of land cover and leaf area index were derived from Landsat data. The MODIS NPP and GPP products showed no overall bias. They tended to be overestimates at low productivity sites — often because of artificially high values of MODIS FPAR (fraction of photosynthetically active radiation absorbed by the canopy), a critical input to the MODIS GPP algorithm. In contrast, the MODIS products tended to be underestimates in high productivity sites — often a function of relatively low values for vegetation light use efficiency in the MODIS GPP algorithm. A global network of sites where both NPP and GPP are measured and scaled over the local landscape is needed to more comprehensively validate the MODIS NPP and GPP products and to potentially calibrate the MODIS NPP/GPP algorithm parameters.

Evaluation of MODIS Gross Primary Productivity (GPP) in tropical monsoon regions

Near real-time vegetation indices derived from MODIS (MODerate resolution Imaging Spectroradiometer) observations ( http://modis.gsfc.nasa.gov) provide a first opportunity to monitor ecohydrological systems globally at a spatial resolution consistent with biophysical processes at the field scale. Here, we present work toward the quantitative estimation of the uncertainty associated with MODIS Gross Primary Productivity (GPP), an end-product that depends on several MODIS derived vegetation indices. GPP products, available at 8-day and 1-km resolutions, were evaluated in two representative tropical ecosystems: a mixed forest site in the humid tropics (the Marsyandi river basin in the Nepalese Himalayas), and an open shrubland site in a semi-arid region (the Sonora river basin in northern Mexico). The MODIS-GPP products were compared against simulations made with a process-based biochemical-hydrology model driven by flux tower meteorological observations. Whereas the temporal march of vegetation indices and GPP products is consistent between the model and the algorithm, our study indicates that that there is a positive bias in the case of the mixed forest biome in the Marsyandi basin, and a negative bias in the case of open shrublands in the Sonora basin. We examined the error contribution from the DAO meteorological data used in the standard MODIS GPP products. The bias between the GPP estimates using DAO and tower meteorology is − 2.77 gC/m 2/day (i.e., − 77% of the mean of the tower-based GPP) in the Marsyandi, and 0.33 gC/m 2/day (i.e., 18% of the mean of the tower-based GPP) in Sonora. Analysis of the temporal evolution of the discrepancies between the model and the MODIS algorithm points to the need for examining the light use efficiency parameterization, especially with regard to the representation of nonlinear functional dependencies on vapor pressure deficit (VPD), photosynthetically available radiation (PAR), and seasonal evolution of the productive capacity of vegetation as influenced by water stress.

Site‐level evaluation of satellite‐based global terrestrial gross primary production and net primary production monitoring

AbstractOperational monitoring of global terrestrial gross primary production (GPP) and net primary production (NPP) is now underway using imagery from the satellite‐borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Evaluation of MODIS GPP and NPP products will require site‐level studies across a range of biomes, with close attention to numerous scaling issues that must be addressed to link ground measurements to the satellite‐based carbon flux estimates. Here, we report results of a study aimed at evaluating MODIS NPP/GPP products at six sites varying widely in climate, land use, and vegetation physiognomy. Comparisons were made for twenty‐five 1 km2 cells at each site, with 8‐day averages for GPP and an annual value for NPP. The validation data layers were made with a combination of ground measurements, relatively high resolution satellite data (Landsat Enhanced Thematic Mapper Plus at ∼30 m resolution), and process‐based modeling. There was strong seasonality in the MODIS GPP at all sites, and mean NPP ranged from 80 g C m−2 yr−1 at an arctic tundra site to 550 g C m−2 yr−1 at a temperate deciduous forest site. There was not a consistent over‐ or underprediction of NPP across sites relative to the validation estimates. The closest agreements in NPP and GPP were at the temperate deciduous forest, arctic tundra, and boreal forest sites. There was moderate underestimation in the MODIS products at the agricultural field site, and strong overestimation at the desert grassland and at the dry coniferous forest sites. Analyses of specific inputs to the MODIS NPP/GPP algorithm – notably the fraction of photosynthetically active radiation absorbed by the vegetation canopy, the maximum light use efficiency (LUE), and the climate data – revealed the causes of the over‐ and underestimates. Suggestions for algorithm improvement include selectively altering values for maximum LUE (based on observations at eddy covariance flux towers) and parameters regulating autotrophic respiration.

AN EXPERIMENTAL TEST OF THE CAUSES OF FOREST GROWTH DECLINE WITH STAND AGE

The decline in aboveground wood production after canopy closure in even‐aged forest stands is a common pattern in forests, but clear evidence for the mechanism causing the decline is lacking. The problem is fundamental to forest biology, commercial forestry (the decline sets the rotation age), and to carbon storage in forests. We tested three hypotheses about mechanisms causing the decline in wood growth by quantifying the complete carbon budget of developing stands for over six years (a full rotation) in replicated plantations of Eucalyptus saligna near Pepeekeo, Hawaii. Our first hypothesis was that gross primary production (GPP) does not decline with stand age, and that the decline in wood growth results from a shift in partitioning from wood production to respiration (as tree biomass accumulates), total belowground carbon allocation (as a result of declining soil nutrient supply), or some combination of these or other sinks. An alternative hypothesis was that GPP declines with stand age and that the decline in aboveground wood production is proportional to the decline in GPP. A decline in GPP could be driven by reduced canopy leaf area and photosynthetic capacity resulting from increasing nutrient limitation, increased abrasion between tree canopies, lower turgor pressure to drive foliar expansion, or hydraulic limitation of water flux as tree height increases. A final hypothesis was a combination of the first two: GPP declines, but the decline in wood production is disproportionately larger because partitioning shifts as well.We measured the entire annual carbon budget (aboveground production and respiration, total belowground carbon allocation [TBCA], and GPP) from 0.5 years after seedling planting through 6½ years (when trees were ∼25 m tall). The replicated plots included two densities of trees (1111 trees/ha and 10 000 trees/ha) to vary the ratio of canopy leaf mass to wood mass in the individual trees, and three fertilization regimes (minimal, intensive, and minimal followed by intensive after three years) to assess the role of nutrition in shaping the decline in GPP and aboveground wood production.The forest closed its canopy in 1–2 years, with peak aboveground wood production, coinciding with canopy closure, of 1.2–1.8 kg C·m−2·yr−1. Aboveground wood production declined from 1.4 kg C·m−2·yr−1 at age 2 to 0.60 kg C·m−2·yr−1 at age 6. Hypothesis 1 failed: GPP declined from 5.0 kg C·m−2·yr−1 at age 2 to 3.2 kg C·m−2·yr−1 at age 6. Aboveground woody respiration declined from 0.66 kg C·m−2·yr−1 at age 2 to 0.22 kg C·m−2·yr−1 at age 6 and TBCA declined from 1.9 kg C·m−2·yr−1 at age 2 to 1.4 kg C·m−2·yr−1 at age 6. Our data supported hypothesis 3: the decline in aboveground wood production (42% of peak) was proportionally greater than the decline in canopy photosynthesis (64% of peak). The fraction of GPP partitioned to belowground allocation and foliar respiration increased with stand age and contributed to the decline in aboveground wood production. The decline in GPP was not caused by nutrient limitation, a decline in leaf area or in photosynthetic capacity, or (from a related study on the same site) by hydraulic limitation. Nutrition did interact with the decline in GPP and aboveground wood production, because treatments with high nutrient availability declined more slowly than did our control treatment, which was fertilized only during stand establishment.

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using a production efficiency approach. In this study, the 2001 MODIS GPP product was compared with scaled GPP estimates (25 km 2) based on ground measurements at two forested sites. The ground-based GPP scaling approach relied on a carbon cycle process model run in a spatially distributed mode. Land cover classification and maximum annual leaf area index, as derived from Landsat ETM+ imagery, were used in model initiation. The model was driven by daily meteorological observations from an eddy covariance flux tower situated at the center of each site. Model simulated GPPs were corroborated with daily GPP estimates from the flux tower. At the hardwood forest site, the MODIS GPP phenology started earlier than was indicated by the scaled GPP, and the summertime GPP from MODIS was generally lower than the scaled GPP values. The fall-off in production at the end of the growing season was similar to the validation data. At the boreal forest site, the GPP phenologies generally agreed because both responded to the strong signal associated with minimum temperature. The midsummer MODIS GPP there was generally higher than the ground-based GPP. The differences between the MODIS GPP products and the ground-based GPPs were driven by differences in the timing of FPAR and the magnitude of light use efficiency as well as by differences in other inputs to the MODIS GPP algorithm—daily incident PAR, minimum temperature, and vapor pressure deficit. Ground-based scaling of GPP has the potential to improve the parameterization of light use efficiency in satellite-based GPP monitoring algorithms.

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using a production efficiency approach. In this study, the 2001 MODIS GPP product was compared with scaled GPP estimates (25 km2) based on ground measurements at two forested sites. The ground-based GPP scaling approach relied on a carbon cycle process model run in a spatially distributed mode. Land cover classification and maximum annual leaf area index, as derived from Landsat ETM+ imagery, were used in model initiation. The model was driven by daily meteorological observations from an eddy covariance flux tower situated at the center of each site. Model simulated GPPs were corroborated with daily GPP estimates from the flux tower. At the hardwood forest site, the MODIS GPP phenology started earlier than was indicated by the scaled GPP, and the summertime GPP from MODIS was generally lower than the scaled GPP values. The fall-off in production at the end of the growing season was similar to the validation data. At the boreal forest site, the GPP phenologies generally agreed because both responded to the strong signal associated with minimum temperature. The midsummer MODIS GPP there was generally higher than the ground-based GPP. The differences between the MODIS GPP products and the ground-based GPPs were driven by differences in the timing of FPAR and the magnitude of light use efficiency as well as by differences in other inputs to the MODIS GPP algorithm—daily incident PAR, minimum temperature, and vapor pressure deficit. Ground-based scaling of GPP has the potential to improve the parameterization of light use efficiency in satellite-based GPP monitoring algorithms.

Modelling plant carbon and nitrogen dynamics of a boreal aspen forest in CLASS — the Canadian Land Surface Scheme

The formulation of the physiological processes of plant carbon and nitrogen that have recently been implemented in CLASS — the Canadian Land Surface Scheme is presented, including plant photosynthesis of sunlit and shaded leaves, root nitrogen uptake, tissue respiration, growth, and senescence. Results from this formulation provide the vegetation parameters (e.g. stomatal resistance, leaf area index, and root length and distribution) for simulating energy and water exchange, and contribute to the carbon and nitrogen biogeochemical calculations and ecosystem CO 2 flux estimations in CLASS. The model was parameterized for deciduous trees and run at a time step of 30 min. Modelled results were tested with measurements of leaf CO 2 exchange, half-hourly and daily plant CO 2 exchange, and annual plant carbon budgets from the Old Aspen ( Populus tremuloides) site in the Southern Study Area (SSA-OA) of the Boreal Ecosystem-Atmosphere Study (BOREAS). Model tests at leaf level and half-hourly timescale improve confidence in the predictive capabilities of the model at canopy level and longer timescale. At half-hourly timescale, simulated plant CO 2 exchange explained 81% of the variance in the measured CO 2 flux derived from eddy correlation measurements and soil chamber measurements in the three comparing weeks in 1994. At a coarser timescale, simulated daily plant CO 2 exchange explained 86% of the variance in the measured values during 1994 and 1996. Annual gross primary production (GPP) accumulated from half-hourly values in the model in 1994 and 1996 averaged about 1053 g C m −2 for this aspen site, close to the estimations from field eddy correlation measurements. Of this carbon fixation, 59% was consumed by autotrophic respiration ( R a) for plant growth and maintenance in the model, similar to estimations from chamber measurements. Sensitivity analyses show that the modelled plant GPP, R a and net primary production NPP (=GPP− R a) were very sensitive to the changes in temperature, implying that this boreal aspen ecosystem is strongly constrained by temperature conditions.

A novel approach for estimating ecosystem production and respiration in estuaries: Application to the oligohaline and mesohaline Hudson River

Most estimates of metabolism in estuaries are based on water samples incubated in bottles. Such approaches may severely underestimate rates of both gross primary production (GPP) and respiration for a variety of reasons, including reduced turbulence, unnatural light fields, respiration of 14C‐labeled organic matter, and altered grazer communities. These problems may be particularly intense in turbid and deeply mixed estuaries. The measurement of metabolism from in situ changes in dissolved oxygen (DO) concentration over a diel time period offers a potential solution to these problems, but complicated patterns of water advection and mixing in estuaries have limited the use of such open‐water approaches. Here, we describe a method of using diel changes in oxygen concentrations in the oligohaline and mesohaline Hudson River estuary to estimate GPP, whole‐ecosystem respiration (ER), and net ecosystem production (NEP). For this approach, concentrations of DO at any given time for several stations are described as a function of salinity and depth, providing a surface in the three‐dimensional space of oxygen, depth, and salinity. The change in this “response surface” for oxygen over time, once corrected for atmospheric exchange, allows the estimation of metabolism rates. The regression procedures used allow an estimate of the standard error associated with the metabolism measures. For the mesohaline Hudson River estuary, these standard errors are reasonably small. Similarly, any potential errors associated with the estimation of atmospheric exchange in oxygen are small for the Hudson. The technique should be useful for estimating GPP, NEP, and ER in other partially mixed estuaries without the biases associated with incubations in bottles.

Photosynthesis and Related Processes : Rabinowitch, Eugene I. Vol. 2, pt. 2: Kinetics of Photosynthesis (Continued); Addenda to Vol. 1 and Vol. 2, pt. 1. N.Y., Interscience, 1956. pp. 1209–2088

Accurate estimation of carbon fluxes across space and time is of great importance for quantifying global carbon balances. Current production efficiency models for calculation of gross primary production (GPP) depend on estimates of light-use-efficiency (LUE) obtained from look-up tables based on biome type and coarse-resolution meteorological inputs that can introduce uncertainties. Plant function is especially difficult to parameterize in the savanna biome due to the presence of varying mixtures of multiple plant functional types (PFTs) with distinct phenologies and responses to environmental factors. The objective of this study was to find a simple and robust method to accurately up-scale savanna GPP from local, eddy covariance (EC) flux tower GPP measures to regional scales utilizing entirely remote sensing oservations. Here we assessed seasonal patterns of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation products with seasonal EC tower GPP (GPPEC) at four sites along an ecological rainfall gradient (the North Australian Tropical Transect, NATT) encompassing tropical wet to dry savannas.The enhanced vegetation index (EVI) tracked the seasonal variations of GPPEC well at both site- and cross-site levels (R2 = 0.84). The EVI relationship with GPPEC was further strengthened through coupling with ecosystem light-use-efficiency (eLUE), defined as the ratio of GPP to photosynthetically active radiation (PAR). Two savanna landscape eLUE models, driven by top-of-canopy incident PAR (PARTOC) or top-of-atmosphere incident PAR (PARTOA) were parameterized and investigated. GPP predicted using the eLUE models correlated well with GPPEC, with R2 of 0.85 (RMSE = 0.76 g C m− 2 d− 1) and 0.88 (RMSE = 0.70 g C m− 2 d− 1) for PARTOC and PARTOA, respectively, and were significantly improved compared to the MOD17 GPP product (R2 = 0.58, RMSE = 1.43 g C m− 2 d− 1). The eLUE model also minimized the seasonal hysteresis observed between green-up and brown-down in GPPEC and MODIS satellite product relationships, resulting in a consistent estimation of GPP across phenophases. The eLUE model effectively integrated the effects of variations in canopy photosynthetic capacity and environmental stress on photosynthesis, thus simplifying the up-scaling of carbon fluxes from tower to regional scale. The results from this study demonstrated that region-wide savanna GPP can be accurately estimated entirely with remote sensing observations without dependency on coarse-resolution ground meteorology or estimation of light-use-efficiency parameters.