A Method to Efficiently Apply a Biogeochemical Model to a Landscape Research Article Received: 19 December 2004 Accepted: 08 July 2005 DOI:
Cite this article as: Kennedy, R.E., Turner, D.P., Cohen, W.B. et al. Landscape Ecol (2006) 21: 213. doi:10.1007/s10980-005-0827-0 Abstract
Biogeochemical models offer an important means of understanding carbon dynamics, but the computational complexity of many models means that modeling all grid cells on a large landscape is computationally burdensome. Because most biogeochemical models ignore adjacency effects between cells, however, a more efficient approach is possible. Recognizing that spatial variation in model outputs is solely a function of spatial variation in input driver variables such as climate, we developed a method to sample the model outputs in input variable space rather than geographic space, and to then use simple interpolation in input variable space to estimate values for the remainder of the landscape. We tested the method in a 100 km×260 km area of western Oregon, U.S.A. , comparing interpolated maps of net primary production (NPP) and net ecosystem production (NEP) with maps from an exhaustive, wall-to-wall run of the model. The interpolation method can match spatial patterns of model behavior well (correlations>0.8) using samples of only 5 t o 15% of the landscape. Compression of temporal variation in input drivers is a key step in the process, with choice of input variables for compression largely determining the upper bounds on the degree of match between interpolated and original maps. The method is applicable to any model that does not consider adjacency effects, and could free up computational expense for a variety of other computational burdens, including spatial sensitivity analyses, alternative scenario testing, or finer grain-size mapping.
Keywords Biome-BGC Carbon modeling Interpolation Mapping Net ecosystem production Net primary production Oregon References Aber, J.D., Federer, C.A. 1992 A generalizedlumped-parameter model of photosynthesis, evapotranspiration and net primary production in temperate and boreal forest ecosystems Oecologia 92 463 474 CrossRef Google Scholar Acevedo, M.F., Pamarti, S., Ablan, M., Urban, D., Mikler, A. 2001 Modeling forest landscapes: parameter estimation from gap models over heterogeneous terrain Simulation 77 53 68 Google Scholar Alexandrov, G.A., Oikawa, T., Yamagata, Y. 2002 The scheme for globalization of a process-based model explaining gradations in terrestrial NPP and its application Ecol. Model. 148 293 306 CrossRef Google Scholar Band, L.E., Peterson, D.L., Running, S.W., Coughlan, J., Lammers, R., Dungan, J., Nemani, R. 1991 Forest ecosystem processes at the watershed scale: basis for distributed simulation Ecol. Model. 56 171 196 CrossRef Google Scholar Box, G.E.P., Draper, N.R. 1987Empirical Model-Building and Response Surfaces John Wiley & Sons New York Google Scholar Burke, I.C., Kittel, T.G.F., Lauenroth, W.K., Snook, P., Yonker, C.M., Parton, W.J. 1991 Regional analysis of the central Great Plains BioScience 41 685 692 Google Scholar Coops, N.C., Waring, R.H. 2001 Estimating forest productivity in the eastern Siskiyou Mountains of southwestern Oregon using a satellite driven process model, 3-PGS Can. J. For. Res. 31 143 154 CrossRef Google Scholar Franklin, S.E. 2001 Modeling forest net primary productivity with reduced uncertainty by remote sensing of cover type and leaf area index Hunsaker, C.T. Goodchild, M.F. Friedl, M. Case, T.J. eds. Spatial Uncertainty in Ecology: Implications for Remote Sensing and GIS Applications Springer-Verlag New York, NY 402 Google Scholar Friedman, L.W. 1996The Simulation Metamodel Kluwer Academic Publishers Norwell, Massachusetts Google Scholar Garman, S.L. 2004 Design and evaluation of a forest landscape change model for western Oregon Ecol. Model. 175 319 337 CrossRef Google Scholar Jongman, R.H.G., ter Braak, C.J.F., Tongeren, O.F.R. 1995Data Analysis in Community and Landscape Ecology Cambridge University Press Cambridge Google Scholar Kern, J.S., Turner, D.P., Dodson, R.F. 1997 Spatial patterns in soil organic carbon pool size in the northwestern United States Lal, R. Kimbal, J.M. Follett, R. Stewart, B.A. eds. Soil Processes and the Carbon Cycle CRC Press Boca Raton 29 43 Google Scholar Law, B.E., Turner, D.P., Lefsky, M., Campbell, J., Guzy, M., Sun, O., Tuyl, S., Cohen, W.B. 2004 Disturbance and climate effects on carbon stocks and fluxes across Western Oregon USA Global Change Biol. 10 1429 1444 CrossRef Google Scholar Myers, R.H., Montgomery, D. 2002Response Surface Methodology: Process and Product Optimization using Designed Experiments John Wiley & Sons New York Google Scholar Ollinger, S.V., Aber, J.D., Federer, C.A. 1998 Estimating regional forest productivity and water yield using an ecosystem model linked to a GIS Landscape Ecol. 13 323 334 CrossRef Google Scholar Parton, W.J., Stewart, J.W.B., Cole, C.V. 1987 Analysis of factors controlling soil organic matter levels in Great Plains grasslands Soil Sci. Soc. Am. J. 51 1173 1179 Google Scholar Peters, D.P., Herrick, J.E., Urban, D.L., Gardner, R.H., Breshears, D.D. 2004 Strategies for ecological extrapolation Oikos 106 627 636 CrossRef Google Scholar Running, S.W., Hunt, E.R.J. 1993 Generalization of a forest ecosystem process model for other biomes, BIOME-BGC, and an application for global-scale models Field, C.B. Ehleringer, J.R. eds. Scaling Ecophysiological Processes: Leaf to Globe Academic Press San Diego 388 Google Scholar
Thornton P. 1998.Regional Ecosystem Simulation: Combining Surface- and Satellite-based Observations to Study Linkages between Terrestrial Energy and Mass Budgets. PhD Dissertation, University of Montana.
Thornton, P., Hasenauer, H., White, M.A. 2000 Simultaneous estimation of daily solar radiation and humidity from observed temperature and precipitation: an application over complex terrain in Austria Agric. For. Meteorol. 104 255 271 CrossRef Google Scholar Thornton, P., Running, S.W., White, M.A. 1997 Generating surfaces of daily meteorological variables over large regions of complex terrain J. Hydrol. 190 214 251 CrossRef Google Scholar Thornton, P.E., Law, B.E., Gholz, H.L., Clark, K.L., Falge, E., Ellsworth, D.S., Goldstein, A.H., Monson, R.K., Hollinger, D., Falk, M., Chen, J., Sparks, J.P. 2002 Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests Agric. For. Meteorol. 113 185 222 CrossRef Google Scholar Urban, D., Acevedo, M.F., Garman, S.L. 1999 Scaling fine-scale processes to large-scale patterns using models derived from models: meta-models Mladenoff, D. Baker, W. eds. Spatial Modeling of Forest Landscape Change: Approaches and Applications Cambridge University Press Cambridge 70 98 Google Scholar
VEMAP Members 1995. Vegetation/ecosystem modeling and analysis project: Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling. Global Biogeochem. Cycles 9: 407–437.
Waring, R.H., Franklin, J.F. 1979 Evergreen coniferous forests of the Pacific Northwest Science 204 1380 1386 Google Scholar
White M.A., Thornton P.E., Running S.W. and Nemani R.R. 2000. Parameterization and sensitivity analysis of the BIOME-BGC terrestrial ecosystem model: net primary production controls. Earth Interact. 4–003.
Williams, M., Rastetter, E.B., Fernandes, D.N., Goulden, M.L., Shaver, G.R., Johnson, L.C. 1997 Predicting gross primary productivity in terrestrial ecosystems Ecol. Appl. 7 882 894 Google Scholar Williams, M., Rastetter, E.B., Shaver, G.R., Hobbie, J.E., Carpino, E., Kwiatkowski, B.L. 2001 Primary production of an arctic watershed: an uncertainty analysis Ecol. Appl. 11 1800 1816 Google Scholar