Net Primary Production Studies Over Large Scales Daolan Zheng

1. Net Primary Production Studies Over Large Scales Daolan Zheng Dept. of Earth Ecological, and Environmental Sciences, Univ. of Toledo, Toledo, OH 43606 Contributors: T. Hame, K. Hibbard, R. Olson, W. Parton, S. Prince, and the Participants of the Global Primary Production Data Initiatives and the Ecosystem Model/Data Inter-comparisons

2. 1) Global Primary Production Data Initiatives (GPPDI) dataset (0.5 x 0.5 degree NPP); 2) Ecosystem Model/Data Inter-comparison (EMDI);

3. GPPDI ABSTRACT: Net Primary Production (NPP) is an important component of the carbon cycle but direct field measurement of NPP is tedious and not practical for large areas and so models are generally used to study the carbon cycle at a global scale. Most NPP data are for relatively small field plots that cannot represent the 0.50 x 0.50 grid cells that are commonly used in global NPP models. We summarize and present a series of methods (4) that were used by original authors OR us to prepare a consistent data set of NPP for 0.50 grid cells for a range of biomes. The grid cells are grouped to the biome level and are compared with existing compilations of field NPP and the results of the Miami potential NPP model. The full dataset currently contains 3654 cells. An edited subset consists of 2335 cells in which outliers were removed and all replicate measurements were averaged for each unique geographic location. (http://daacl.esd.ornl.gov/npq/GPPDI/Combined_GPPDI_des.html).

4. Major methods: ** Aggregation of fine-scale (plot or stand-level) vegetation inventory; ** Direct correlation of extensive data sets of ground measurements with remotely sensed spectral vegetation indices; ** Local modeling of NPP using key independent variables; ** Regression analysis to link productivity with controlling environmental variables.

10. EMDI Abstract. Validation of global net primary production (NPP) models on spatial and temporal dimensions is much needed. This study compared the predicted NPP from 9 global models with the observed NPP estimates developed in the United States and Australia at 0.50 x 0.50 spatial resolution. Differences among NPP estimates varied significantly over space and time. Overall, mean model results overestimated by about 65-83 and 148-198 gC/m2/yr for ANPP (0-600) and TNPP (0-1000), respectively, compared to the observed data. Such biases increased slightly for higher NPP values. Trend of inter-annual NPP variation derived from model mean for Queensland (1960-95), Australia did not significantly differ (p=0.1). While in Iowa (1982-95), USA between model/data mean differed (flood, 1993)..

11. Objectives a) Generate continuous NPP maps based on field inventory; b) Compare global model predictions with field-based NPP; c) Examine spatial patterns of modeled NPP; d) Compare model outputs with key environmental variables.

12. Sources Iowa Queensland Source: Barrett Source: Parton/Sala/Tieszen/Brown

13. Models Abbreviated name Full name Principal Modeler(s) Model type AVIM Atmosphere-Vegetation Interaction Model J. Ji / Y. Li Biogeochemical CASA Carnegie AMES Stanford Approach C. Field/J. Randerson Biogeochemical/Satellite CENT Century W. Parton Biogeochemical CVSA Carbon Exchange between Vegetation Soil and Atmosphere M. Cao Biogeochemical GPEM GLObal Production Efficiency Model S.D. Prince Remote sensing driven GTEC Global Terrestrial Ecosystem Carbon W.M. Post/T. King Biogeochemical LPJ Lund Potsdam Jena Dynamic Global Vegetation Model S. Sitch / B. Smith Dynamic Global Vegetation Model (DGVM) MC1 MAPSS/CENTURY version 1 R. Nielson / D. Bachelet Dynamic Global Vegetation Model (DGVM) VECO Vegetation Continuous Description model V. Brovkin Empirical Model

14. TNPP residual (Model-Data) USA Australia

15. U.S.A. (Xi-Xmin) / (Xmax – Xmin) Data Model mean R2 = 0.84

16. Australia Data Model mean (Xi-Xmin) / (Xmax – Xmin) R2 = 0.66

17. Mo-Tnpp Total Net Primary Production (TNPP)

18. Aboveground Net Primary Production (ANPP) Mo_Anpp

19. Mod-AET Comparison of model TNPP means with Actual Evapotranspiration (AET)

20. Mod-NDVI Comparison of model TNPP means with Normalized Difference Vegetation Index (NDVI)

21. Mod-PPT Comparison of model TNPP means with Annual total precipitation

22. Mod-TEMP Comparison of model TNPP means with Annual mean temperature

23. Aust.-Indiv. (-21.25S/143.75E)

24. AUS-mean (Annual) Australia: field data & model mean(-21.25°S/143.75°E)36 year sequence

25. Iowa: individual models14 year sequence

26. IOWA-Mean (Annual) Iowa: field data and model mean14 year sequence

27. Conclusions *** First model/data comparison at 0.5° grain with continental extent. *** Models differ substantially. *** Models overestimate NPP (or data underestimated) *** Uncertainty from this study (different methods in estimating litterfall in U.S., lack of data in Aus., grazing effects, BNPP allocation). *** Reasonable agreement between NPP data and model outputs (in both spatial patterns and temporal variations). *** ANPP comparisons may reduce uncertainty.

28. Acknowledgments • Many individuals and modeling groups who contributed data and model runs to GPPDI and EMDI. • International Geosphere-Biosphere Programme (IGBP), Data and Information System (DIS). • National Center for Ecological Analysis and Synthesis (NCEAS) for EMDI I, II, and III workshops, data organization and distribution.