13 research outputs found
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A large proportion of North American net ecosystem production is offset by emissions from harvested products, river/stream evasion, and biomass burning
Diagnostic carbon cycle models produce estimates of net ecosystem production (NEP, the balance of net primary production
and heterotrophic respiration) by integrating information from (i) satellite-based observations of land surface
vegetation characteristics; (ii) distributed meteorological data; and (iii) eddy covariance flux tower observations of
net ecosystem exchange (NEE) (used in model parameterization). However, a full bottom-up accounting of NEE (the
vertical carbon flux) that is suitable for integration with atmosphere-based inversion modeling also includes emissions
from decomposition/respiration of harvested forest and agricultural products, CO₂ evasion from streams and
rivers, and biomass burning. Here, we produce a daily time step NEE for North America for the year 2004 that
includes NEP as well as the additional emissions. This NEE product was run in the forward mode through the CarbonTracker
inversion setup to evaluate its consistency with CO₂ concentration observations. The year 2004 was climatologically
favorable for NEP over North America and the continental total was estimated at 1730± 370 TgC yr
⁻¹ (a
carbon sink). Harvested product emissions (316 ± 80 TgC yr
⁻ ¹), river/stream evasion (158 ± 50 TgC yr
⁻¹), and fire
emissions (142 ± 45 TgC yr
⁻¹) counteracted a large proportion (35%) of the NEP sink. Geographic areas with strong
carbon sinks included Midwest US croplands, and forested regions of the Northeast, Southeast, and Pacific Northwest.
The forward mode run with CarbonTracker produced good agreement between observed and simulated wintertime
CO₂ concentrations aggregated over eight measurement sites around North America, but overestimates of
summertime concentrations that suggested an underestimation of summertime carbon uptake. As terrestrial NEP is
the dominant offset to fossil fuel emission over North America, a good understanding of its spatial and temporal variation
– as well as the fate of the carbon it sequesters ─ is needed for a comprehensive view of the carbon cycle.Keywords: net ecosystem exchange, river evasion, biomass burning, net ecosystem production, atmospheric inversion model, carbon flu
MODIS land cover and LAI Collection 4 product quality across nine sites in the western hemisphere
Global maps of land cover and leaf area index (LAI) derived from the Moderate Resolution Imaging Spectrometer (MODIS) reflectance data are an important resource in studies of global change, but errors in these must be characterized and well understood. Product validation requires careful scaling from ground and related measurements to a grain commensurate with MODIS products. We present an updated BigFoot project protocol for developing 25-m validation data layers over 49-km2 study areas. Results from comparisons of MODIS and BigFoot land cover and LAI products at nine contrasting sites are reported. In terms of proportional coverage, MODIS and BigFoot land cover were in close agreement at six sites. The largest differences were at low tree cover evergreen needleleaf sites and at an Arctic tundra site where the MODIS product overestimated woody cover proportions. At low leaf biomass sites there was reasonable agreement between MODIS and BigFoot LAI products, but there was not a particular MODIS LAI algorithm pathway that consistently compared most favorably. At high leaf biomass sites, MODIS LAI was generally overpredicted by a significant amount. For evergreen needleleaf sites, LAI seasonality was exaggerated by MODIS. Our results suggest incremental improvement from Collection 3 to Collection 4 MODIS products, with some remaining problems that need to be addresse
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Decadal Trends in Net Ecosystem Production and Net Ecosystem Carbon Balance for a Regional Socioecological System
Carbon sequestration is increasingly recognized as an ecosystem service, and forest management has a large potential to alter regional carbon fluxes − notably by way of harvest removals and related impacts on net ecosystem production (NEP). In the Pacific Northwest region of the U.S.,
the implementation of the Northwest Forest Plan (NWFP) in 1993 established a regional
socioecological system focused on forest management. The NWFP resulted in a large (82%)
decrease in the rate of harvest removals on public forest land, thus significantly impacting the
regional carbon balance. Here we use a combination of remote sensing and ecosystem modeling
to examine the trends in NEP and Net Ecosystem Carbon Balance (NECB) in this region over the
1985 to 2007 period, with particular attention to land ownership since management now differs
widely between public and private forestland. In the late 1980s, forestland in both ownership
classes was subject to high rates of harvesting, and consequently the land was a carbon source
(i.e. had a negative NECB). After the policy driven reduction in the harvest level, public forest
land became a large carbon sink − driven in part by increasing NEP − whereas private forest
lands were close to carbon neutral. In the 2003-2007 period, the trend towards carbon
accumulation on public lands continued despite a moderate increase in the extent of wildfire.
The NWFP was originally implemented in the context of biodiversity conservation, but its
consequences in terms of carbon sequestration are also of societal interest. Ultimately,
management within the NWFP socioecological system will have to consider trade-offs among
these and other ecosystem services.Keywords: net ecosystem production, ecosystem services, carbon sequestration, socioecological system, Pacific Northwest Forest Plan, regionalKeywords: net ecosystem production, ecosystem services, carbon sequestration, socioecological system, Pacific Northwest Forest Plan, regiona
Assessing interannual variation in MODIS-based estimates of gross primary production
Global estimates of terrestrial gross primary production (GPP) are now operationally produced from Moderate Resolution Imaging Spectrometer (MODIS) imagery at the 1-km spatial resolution and eight-day temporal resolution. In this study, MODIS GPP products were compared with ground-based GPP estimates over multiple years at three sites-a boreal conifer forest, a temperate deciduous forest, and a desert grassland. The ground-based estimates relied on measurements at eddy covariance flux towers, fine resolution remote sensing, and modeling. The MODIS GPP showed seasonal variation that was generally consistent with the in situ observations. The sign and magnitude of year-to-year variation in the MODIS products agreed with that of the ground observations at two of the three sites. Examination of the inputs to the MODIS GPP algorithm-notably the fraction of photosynthetically active radiation (FPAR) that is absorbed by the canopy), minimum temperature scalar, and vapor pressure deficit scalar-provided explanations for cases of disagreement between the MODIS and ground-based GPP estimates. Continued evaluation of interannual variation in MODIS products and related climate variables will aid in assessing potential biospheric feedbacks to climate change
Comparisons of land cover and LAI estimates derived from ETM+ and MODIS for four sites in North America: a quality assessment of 2000/2001 provisional MODIS products
The MODIS land science team produces a number of standard products, including land cover and leaf area index (LAI). Critical to the success of MODIS and other sensor products is an independent evaluation o f product quality. In that context, we describe a study using field data and Landsat ETM+ to map land cover and LAI at four 4 9-km \u27 sites in Noith America containing agricultural cropland (AGRO), prairie grassland (KONZ), boreal needleleaf forest, and temperate mixed forest. The purpose was to: (1) develop accurate maps of land cover, based on the MODIS IGBP (Intemational G eosphere-B iosphere Programme) land cover classification scheme; (2) derive continuous surfaces of LAI that capture the mean and variability o f the LAI field measurements; and (3) conduct initial MODIS validation exercises to assess the quality of early (i.e., provisional) MODIS products. ETM + land cover maps varied in overall accuracy from 81% to 95%. The boreal forest was the most spatially complex, had the greatest num ber of classes, and the lowest accuracy. The intensive agricultural cropland had the simplest spatial structure, the least number of classes, and the highest overall accuracy. At each site, mapped LAI pattems generally followed pattems of land cover across the site. Predicted versus observed LAI indicated a high degree of correspondence between field-based measures and ETM + predictions of LAI. Direct comparisons of ETM + land cover maps with Collection 3 MODIS cover maps revealed several important distinctions and similarities. One obvious difference was associated with image/map resolution. ETM+ captured much of the spatial complexity of land cover at the sites. In contrast, the relatively coarse resolution of MODIS did not allow for that level of spatial detail. Over the extent of all sites, the greatest difference was an overprediction by MODIS of evergreen needleleaf forest cover at the boreal forest site, which consisted largely of open shrubland, woody savanna, and savanna. At the agricultural, temperate mixed forest, and prairie grassland sites, ETM+ and MODIS cover estimates were similar. Collection 3 MODIS-based LAI estimates were considerably higher (up to 4 m2 m-2) than those based on ETM-F LAI at each site. There are numerous probable reasons for this, the most important being the algorithms’ sensitivity to MODIS reflectance calibration, its use of a prelaunch AVHRR-based land cover map, and its apparent reliance on mainly red and near-IR reflectance. Samples of Collection 4 LAI products were examined and found to consist of significantly improved LAI predictions for KONZ, and to some extent for AGRO, but not for the other two sites. In this study, we demonstrate that MODIS reflectance data are highly correlated with LAI across three study sites, with relationships increasing in strength from 500 to 1000 m spatial resolution, when shortwave-infrared bands are included
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
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 km2 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
Site-level evaluation of satellite-based global terrestrial gross primary production and net primary production monitoring
Operational 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