3. Global Terrestrial Gross and Net Primary Productivity from the Earth Observing System
55
ning 1998; Churkina et al. 1999). A formal intercomparison of 17 global NPP models was
presented in a complete issue of Global Change
Biology (Cramer and Field 1999). These intercomparisons help highlight our areas of greatest uncertainty in global NPP. For example, midsummer boreal forest and dry-season tropical evergreen forest
NPP had the highest disagreement among models
(Kicklighter et al. 1999). Schloss et al. (1999)
found the greatest variability among models in
areas that were simultaneously limited by both temperature and precipitation, and Churkina and Running (1998) estimated that 52% of global terrestrial
area has NPP fundamentally limited by water availability. Bondeau et al. (1999) found greatest errors
in tracking the rain-green phenology of subtropical
savannas. Despite not being actual data, the models
do give some critical insight into global-scale NPP
variability and dynamics.
In the future, a combination of these techniques
of measurements at various scales interpolated and
extrapolated with ecosystem models will be required to determine the validity of the regular
global NPP produced by EOS. More local validation activities will immediately be possible by extracting the local area from the global EOS NPP
data set and comparing with any local measurements available (Running et al. 1999).
Summary
A near-weekly calculation of global terrestrial NPP
driven by EOS satellite data began in 2000. This
NPP will be computed for 150 million km 2 of the
vegetated terrestrial surface of Earth. These data
will be available for nominal cost to scientists
worldwide, and should initiate a new era of more
easily attainable spatially georeferenced biophysical information for landscape ecological study and
management.
Acknowledgments This research was funded by
the Earth Science Enterprise at NASA. As much
of this work is in progress, updates on this global
data availability will be available at http://
www.forestry.umt.edulntsg.
References
Asrar, G.; Myneni, R.; Choudhury, BJ. Spatial heterogeneity in vegetation canopies and remote sensing of
absorbed photosynthetically active radiation: A modeling study. Remote Sens. Environ. 41:85-103;
1992.
Baldocchi, D.; Valentini, R.; Running, S.W.; Oechel, w.;
Dahlman, R. Strategies for measuring and modelling
carbon dioxide and water vapor fluxes over terrestrial
ecosystems. Global Change BioI. 2:159-168; 1996.
Bondeau, A.; Kicklighter, J.; Kaduk:, J.; and participants
of the Potsdam NPP Model Intercomparison. Comparing global models of terrestrial net primary productivity (NPP): Importance of vegetation structure on
seasonal NPP estimates. Global Change Biology
5:35-45; 1999.
Cannell, M.G.R. World Forest Biomass and Primary Production Data. London: Academic; 1982.
Churkina, G.; Running, S.W. Contrasting climatic controls on the estimated productivity of different biomes.
Ecosystems 1:206-215; 1998.
Churkina, G.; Running, S.w.; Schloss, A.L.; PIK-NPP
Participants. Comparing global models of terrestrial
net primary productivity (NPP): The importance of
water availability. Global Change BioI. 5:46-55;
1999.
Ciais, P., Tans, P.P., Trolier, M., White, 1.W.C., and Francey, R.J. A large northern hemisphere terrestrial CO2
sink indicated by 13C/12C of atmospheric CO 2 , Science
269:1098-1102; 1995.
Cramer, W.; Field, C.B. Comparing global models ofterrestrial net primary productivity (NPP): Introduction.
Global Change BioI. 5:iii-iv; 1999.
DeFries, R.S.; Townshend, J.R.G.; Hansen, M.C. Continuous fields of vegetation characteristics at the
global scale at 1 kIn resolution. J. Geophys. Res. Atmos. 104(D14):16911-16924; 1999.
Field, C.B.; Behrenfeld, M.J.; Randerson, 1.T.; Falkowski, P. Primary production of the biosphere: Integrating terrestrial and oceanic components. Science
281:237-240; 1998.
Field, C.B.; Randerson, J.T.; Malmstrom, C.M. Global
net primary production: Combining ecology and remote sensing. Remote Sens. Environ. 51:74--88; 1995.
Goulden, M.L., Munger, J.W., Fan, S-M., Daube, B.C.,
and Wofsy, S.C. Exchange of carbon dioxide by a deciduous forest: Response to interannual climate variability. Science 271:1576-1578; 1996.
DeFries, R.S.; Hansen, M.C.; Townshend, J.R.G.; Sohlberg, R. Global land cover classification at 8 kIn spatial resolution: the use of training data derived from
Landsat imagery in decision tree classifiers. Internat.
1. Remote Sens. 19(16):3141-3168.
55
ning 1998; Churkina et al. 1999). A formal intercomparison of 17 global NPP models was
presented in a complete issue of Global Change
Biology (Cramer and Field 1999). These intercomparisons help highlight our areas of greatest uncertainty in global NPP. For example, midsummer boreal forest and dry-season tropical evergreen forest
NPP had the highest disagreement among models
(Kicklighter et al. 1999). Schloss et al. (1999)
found the greatest variability among models in
areas that were simultaneously limited by both temperature and precipitation, and Churkina and Running (1998) estimated that 52% of global terrestrial
area has NPP fundamentally limited by water availability. Bondeau et al. (1999) found greatest errors
in tracking the rain-green phenology of subtropical
savannas. Despite not being actual data, the models
do give some critical insight into global-scale NPP
variability and dynamics.
In the future, a combination of these techniques
of measurements at various scales interpolated and
extrapolated with ecosystem models will be required to determine the validity of the regular
global NPP produced by EOS. More local validation activities will immediately be possible by extracting the local area from the global EOS NPP
data set and comparing with any local measurements available (Running et al. 1999).
Summary
A near-weekly calculation of global terrestrial NPP
driven by EOS satellite data began in 2000. This
NPP will be computed for 150 million km 2 of the
vegetated terrestrial surface of Earth. These data
will be available for nominal cost to scientists
worldwide, and should initiate a new era of more
easily attainable spatially georeferenced biophysical information for landscape ecological study and
management.
Acknowledgments This research was funded by
the Earth Science Enterprise at NASA. As much
of this work is in progress, updates on this global
data availability will be available at http://
www.forestry.umt.edulntsg.
References
Asrar, G.; Myneni, R.; Choudhury, BJ. Spatial heterogeneity in vegetation canopies and remote sensing of
absorbed photosynthetically active radiation: A modeling study. Remote Sens. Environ. 41:85-103;
1992.
Baldocchi, D.; Valentini, R.; Running, S.W.; Oechel, w.;
Dahlman, R. Strategies for measuring and modelling
carbon dioxide and water vapor fluxes over terrestrial
ecosystems. Global Change BioI. 2:159-168; 1996.
Bondeau, A.; Kicklighter, J.; Kaduk:, J.; and participants
of the Potsdam NPP Model Intercomparison. Comparing global models of terrestrial net primary productivity (NPP): Importance of vegetation structure on
seasonal NPP estimates. Global Change Biology
5:35-45; 1999.
Cannell, M.G.R. World Forest Biomass and Primary Production Data. London: Academic; 1982.
Churkina, G.; Running, S.W. Contrasting climatic controls on the estimated productivity of different biomes.
Ecosystems 1:206-215; 1998.
Churkina, G.; Running, S.w.; Schloss, A.L.; PIK-NPP
Participants. Comparing global models of terrestrial
net primary productivity (NPP): The importance of
water availability. Global Change BioI. 5:46-55;
1999.
Ciais, P., Tans, P.P., Trolier, M., White, 1.W.C., and Francey, R.J. A large northern hemisphere terrestrial CO2
sink indicated by 13C/12C of atmospheric CO 2 , Science
269:1098-1102; 1995.
Cramer, W.; Field, C.B. Comparing global models ofterrestrial net primary productivity (NPP): Introduction.
Global Change BioI. 5:iii-iv; 1999.
DeFries, R.S.; Townshend, J.R.G.; Hansen, M.C. Continuous fields of vegetation characteristics at the
global scale at 1 kIn resolution. J. Geophys. Res. Atmos. 104(D14):16911-16924; 1999.
Field, C.B.; Behrenfeld, M.J.; Randerson, 1.T.; Falkowski, P. Primary production of the biosphere: Integrating terrestrial and oceanic components. Science
281:237-240; 1998.
Field, C.B.; Randerson, J.T.; Malmstrom, C.M. Global
net primary production: Combining ecology and remote sensing. Remote Sens. Environ. 51:74--88; 1995.
Goulden, M.L., Munger, J.W., Fan, S-M., Daube, B.C.,
and Wofsy, S.C. Exchange of carbon dioxide by a deciduous forest: Response to interannual climate variability. Science 271:1576-1578; 1996.
DeFries, R.S.; Hansen, M.C.; Townshend, J.R.G.; Sohlberg, R. Global land cover classification at 8 kIn spatial resolution: the use of training data derived from
Landsat imagery in decision tree classifiers. Internat.
1. Remote Sens. 19(16):3141-3168.