bpbond/biome-bgc

Biome-BGC ecophysiological model

Biome-BGC

The Biome-BGC ecophysiological model.

Publications using Biome-BGC include:

• Barcza, Z., Laszló, H., Somogyi, Z., Hidy, D., Lovas, K., Churkina, G., and Horvath, L.: Estimation of the biospheric carbon dioxide balance of Hungary using the BIOME-BGC model, Idojaras, 113, 203-219, 2009.

• Bond-Lamberty, B., Gower, S. T., and Ahl, D. E.: Improved simulation of poorly drained forests using Biome-BGC, Tree Physiol., 27, 703-715, 2007.

• Bond-Lamberty, B., Gower, S. T., Ahl, D. E., and Thornton, P. E.: Reimplementation of the BIOME-BGC model to simulate successional change, Tree Physiol., 25, 413-424, 2005.

• Bond-Lamberty, B., Gower, S. T., Goulden, M. L., and McMillan, A.: Simulation of boreal black spruce chronosequences: comparison to field measurements and model evaluation, J. Geophys. Res.-Biogeosci., 111, G02014, 10.1029/2005JG000123, 2006.

• Bond-Lamberty, B., Peckham, S. D., Gower, S. T., and Ewers, B. E.: Effects of fire on regional evapotranspiration in the central Canadian boreal forest, Global Change Biol., 15, 1242-1254, 10.1111/j.1365-2486.2008.01776.x, 2009.

• Bond-Lamberty, B., Wang, C., and Gower, S. T.: Spatiotemporal measurement and modeling of boreal forest soil temperatures, Agric. Forest Meteorol., 131, 27-40, 10.1016/j.agrformet.2005.04.008, 2005.

• Brugnach, M.: Process level sensitivity analysis for complex ecological models, Ecol. Model., 187, 99-120, 10.1016/j.ecolmodel.2005.01.044, 2005.

• Chen, H., and Tian, H.-Q.: Does a general temperature-dependent Q(10) model of soil respiration exist at biome and global scale?, Journal of Integrative Plant Biology, 47, 1288-1302, 2005.

• Churkina, G., Tenhunen, J. D., Thornton, P. E., Falge, E., Elbers, J. A., Ernhard, M., Grünwald, T., Kowalski, A. S., Rannik, Ü., and Sprinz, D.: Analyzing the ecosystem carbon dynamics of four European coniferous forests using a biogeochemistry model, Ecosystems, 6, 168-184, 10.1007/s10021-002-0197-2, 2003.

• Churkina, G., Zaehle, S., Hughes, J., Viovy, N., Chen, Y., Jung, M., Heumann, B. W., Ramankutty, N., Rödenbeck, C., Heimann, M., and Jones, C. D.: Interactions between nitrogen deposition, land cover conversion, and climate change determine the contemporary carbon balance of Europe, Biogeosciences, 7, 2749-2764, 10.5194/bg-7-2749-2010, 2010.

• Cienciala, E., and Tatarinov, F. A.: Application of BIOME-BGC model to managed forests. 2. Comparison with long-term observations of stand production for major tree species, Forest Ecol. Manage., 237, 252-266, 10.1016/j.foreco.2006.09.086, 2006.

• Di Vittorio, A. V., Anderson, R. S., White, J. D., Miller, N. L., and Running, S. W.: Development and optimization of an Agro-BGC ecosystem model for C4 perennial grasses, Ecol. Model., 221, 2038-2053, 10.1016/j.ecolmodel.2010.05.013, 2010.

• Engstrom, R., and Hope, A.: Parameter sensitvity of the Arctic Biome-BGC model for estimating evapotranspiration in the Arctic coastal plain, Arct. Antarct. Alp. Res., 43, 380-388, 10.1657/1938-4246-43.3.380, 2011.

• Engstrom, R., Hope, A., Kwon, H., Harazono, Y., Mano, M., and Oechel, W. C.: Modeling evapotranspiration in Arctic coastal plain ecosystems using a modified BIOME-BGC model, J. Geophys. Res.-Biogeosci., 111 (G2), art. no. G02021 (02020 pp.), 10.1029/2005JG000102, 2006.

• Golinkoff, J.: Biome BGC version 4.2: Theoretical Framework of Biome-BGC, 2010.

• Hibbard, K. A., Law, B. E., and Sulzman, J.: An analysis of soil respiration across northern hemisphere temperate ecosystems, Biogeochemistry, 73, 29-70, 10.1007/s10533-004-2946-0, 2005.

• Kang, S., Kimball, J. S., and Running, S. W.: Simulating effects of fire disturbance and climate change on boreal forest productivity and evapotranspiration, Science Total Environ., 362, 85-102, 2006.

• Kimball, J. S., Jones, L. A., Zhang, K., Heinsch, F. A., McDonald, K. C., and Oechel, W. C.: A satellite approach to estimate land-atmosphere CO2 exchange for Boreal and Arctic biomes using MODIS and AMSR-E, IEEE Transactions on Geoscience and Remote Sensing, 47, 569-587, 10.1109/TGRS.2008.2003248, 2009.

• Kimball, J. S., Keyser, A. R., Running, S. W., and Saatchi, S. S.: Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps, Tree Physiol., 20, 761-775, 2000.

• Kimball, J. S., White, M. A., and Running, S. W.: BIOME-BGC simulations of stand hydrological processes for BOREAS, J. Geophys. Res.-Atmos., 102, 29043-29051, 1997.

• Lagergren, F., Grelle, A., Lankreijer, H., Mölder, M., and Lindroth, A.: Current carbon balance of the forested area in Sweden and its sensitivity to global change as simulated by Biome-BGC, Ecosystems, 9, 894-908, 10.1007/s10021-005-0046-1 2006.

• Law, B. E., Thornton, P. E., Irvine, J., Anthoni, P. M., and Van Tuyl, S.: Carbon storage and fluxes in Ponderosa pine forests at different developmental stages, Global Change Biol., 7, 755-777, 2001.

• Meigs, G. W., Turner, D. P., Ritts, W. D., Zhiqiang, Y., and Law, B. E.: Landscape-scale simulation of heterogeneous fire effects on pyrogenic carbon emissions, tree mortality, and net ecosystem production, Ecosystems, 14, 758-775, 10.1007/s10021-011-9444-8, 2011.

• Mitchell, S., Beven, K., Freer, J., and Law, B. E.: Processes influencing model-data mismatch in drought-stressed, fire-disturbed eddy flux sites, J. Geophys. Res.-Biogeosci., 116, G02008, 10.1029/2009JG001146, 2011.

• Pietsch, S. A., Hasenauer, H., Kucera, J., and Cermák, J.: Modeling effects of hydrological changes on the carbon and nitrogen balance of oaks in floodplains, Tree Physiol., 23, 735-746, 2003.

• Pietsch, S. A., Hasenauer, H., and Thornton, P. E.: BGC-model parameters for tree species growing in central European forests, Forest Ecol. Manage., 211, 264-295, 10.1016/j.foreco.2005.02.046, 2005.

• Raj, R., Hamm, N. A. S., van der Tol, C., and Stein, A.: Variance-based sensitivity analysis of BIOME-BGC for gross and net primary production, Ecol. Model., 292, 26-36, 10.1016/j.ecolmodel.2014.08.012, 2014.

• Running, S. W., and Gower, S. T.: FOREST-BGC, A general model of forest ecosystem processes for regional applications. II. Dynamic carbon allocation and nitrogen budgets, Tree Physiol., 9, 147-160, 1991.

• Running, S. W., and Hunt, R. E.: Generalization of a forest ecosystem process model for other biomes, BIOME-BGC, and an application for global-scale models, in: Scaling Physiologic Processes: Leaf to Globe, edited by: Ehleringer, J. R., and Field, C. B., Academic Press, San Diego, CA, 141-158, 1993.

• Tatarinov, F. A., and Cienciala, E.: Application of BIOME-BGC model to managed forests. 1. Sensitivity analysis, Forest Ecol. Manage., 237, 267-279, 10.1016/j.foreco.2006.09.085, 2006.

• Tatarinov, F. A., and Cienciala, E.: Long-term simulation of the effect of climate changes on the growth of main Central-European forest tree species, Ecol. Model., 220, 3081-3088, 10.1016/j.ecolmodel.2009.01.029, 2009.

• 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. Y., Falk, M., Chen, J., and Sparks, J. P.: Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests, Agric. Forest Meteorol., 113, 185-222, 10.1016/S0168-1923(02)00108-9, 2002.

• Thornton, P. E., and Rosenbloom, N. A.: Ecosystem model spin-up: estimating steady state conditions in a coupled terrestrial carbon and nitrogen cycle model, Ecol. Model., 189, 25-48, 10.1016/j.ecolmodel.2005.04.008, 2005.

• Tupek, B., Zanchi, G., Verkerk, P. J., Churkina, G., Viovy, N., Hughes, J. K., and Lindner, M.: A comparison of alternative modelling approaches to evaluate the European forest carbon fluxes, Forest Ecol. Manage., 260, 241-251, 10.1016/j.foreco.2010.01.045, 2010.

• Turner, D. P.: Scaling net ecosystem production and net biome production over a heterogeneous region in the western United States, Biogeosciences, 4, 597-612, 2007.

• Turner, D. P., Ritts, W. D., Cohen, W. B., Gower, S. T., Running, S. W., Zhao, M., Costa, M. H., Kirschbaum, A. A., Ham, J. M., Saleska, S. R., and Ahl, D. E.: Evaluation of MODIS NPP and GPP products across multiple biomes, Remote Sens. Environ., 102, 282-292, 10.1016/j.rse.2006.02.017, 2006.

• Ueyama, M., Harazono, Y., Kim, Y., and Tanaka, N.: Response of the carbon cycle in sub-arctic black spruce forests to climate change: Reduction of a carbon sink related to the sensitivity of heterotrophic respiration, Agric. Forest Meteorol., 149, 582-602, 10.1016/j.agrformet.2008.10.011, 2009.

• Ueyama, M., Ichii, K., Hirata, R., Takagi, K., Asanuma, J., Machimura, T., Nakai, Y., Ohta, Y., Saigusa, N., Takahashi, Y., and Hirano, T.: Simulating carbon and water cycles of larch forests in East Asia by the BIOME-BGC model with AsiaFlux data, Biogeosciences, 7, 959-977, 2010.

• Wang, Q., Masataka, W., and Zhu, O.: Simulation of water and carbon fluxes using BIOME-BGC model over crops in China Agric. Forest Meteorol., 131, 209-224, 10.1016/j.agrformet.2005.06.002, 2005.

• Wang, W., Dungan, J., Hashimoto, H., Michaelis, A. R., Milesi, C., Ichii, K., and Nemani, R. R.: Diagnosing and assessing uncertainties of terrestrial ecosystem models in a multimodel ensemble experiment: 1. Primary production, Global Change Biol., 17, 1350-1366, 10.1111/j.1365-2486.2010.02309.x, 2011.

• Wang, W., Dungan, J., Hashimoto, H., Michaelis, A. R., Milesi, C., Ichii, K., and Nemani, R. R.: Diagnosing and assessing uncertainties of terrestrial ecosystem models in a multimodel ensemble experiment: 2. Carbon balance, Global Change Biol., 17, 1367-1378, 10.1111/j.1365-2486.2010.02315.x, 2011.

• Wang, W., Ichii, K., Hashimoto, H., Michaelis, A. R., Thornton, P. E., Law, B. E., and Nemani, R. R.: A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration, Ecol. Model., 220, 2009-2023, 10.1016/j.ecolmodel.2009.04.051 2009.

• Warren, J. M., Pötzelsberger, E., Wullschleger, S. D., Thornton, P. E., Hasenauer, H., and Norby, R. J.: Ecohydrologic impact of reduced stomatal conductance in forests exposed to elevated CO2, Ecohydrology, 4, 196-210, 10.1002/eco.173, 2011.

• White, M. A., Thornton, P. E., Running, S. W., and Nemani, R. R.: Parameterization and sensitivity analysis of the BIOME-BGC terrestrial ecosystem model: net primary production controls, Earth Interact., 4, paper no. 3, 1-85, 2000.

biome-bgc's Issues

question about litter and soil organic matter decomposition

Hello,

I am new to Biome-BGC and particularly interested in decomposition. I understand that there are 3 litter pools and 4 soil OM pools sorting OM by their recalcitrant levels. I am reading through the codes and found that the base decomposition rates (1/day) seems extremely high, e.g., 0.7 (day-1) for labile litter pool. Although this rate would be adjusted by soil temperature and moisture (let say t_scalar = 0.5 and w_scaler = 0.5), the adjusted decay rate 0.7_0.5_0.5 = 0.175 (day-1) is still very high. Litter decay rate from litter bags experiments is about 0.038 (day-1). The decay rate in the model is almost five times higher than the observed. Are these base decomposition rate constants mean to be calibrated or adjusted when use? Do you have any references for the current base decomposition rate constants?
Thanks.

Laurence

Unrealistic ecosystem productivity values

Hi,
I have tried to use the example initialization, met data, and EPC file to test the model, and the results from the code are significantly low for both the NPP and NEP values. I don't know if I have made some mistake interpreting the results or units, though I saw in the user guide that the NEP/NPP unit is gc/m2/yr. The maximum NEP value I have for this model run is 0.0002. Could you please help me with this issue?

Thank you,
Manaswini

how to convert binary output file into text for using?

canopy.c-all_sided-proj_LAI

Hello:

What is written in the comment is to multiply ALL_SIDED , but it is actually multiplied by PROJ_LAI.  canopy.c

   /* Leaf conductance to sensible heat, per unit all-sided LAI */
gl_sh = gl_bl;                                                                                                              

/* Canopy conductance to evaporated water vapor */
gc_e_wv = gl_e_wv * proj_lai;                                                                                               

/* Canopy conductane to sensible heat */
gc_sh = gl_sh * proj_lai;

Thanks

Could you improve the unfrozen soil water in Biome-BGCMuSo based on its empirical relationship with soil temperature?

Hi! I am interested in the Biome-BGCMuSo model and want to use it to model biogeochemical process in areas with freezing and thawing process (FTP). However, it seems that the current version has not considered FTP, which makes a great difference in simulation of soil water and subsequent other processes such as decomposition of the SOM . As a beginner, I am not good at C language and modify the model but I have to use the model. Thus, I sincerely expect to get help from you. As I know, there is a simple power function between unfrozen soil water and soil temperature as following:
unfrozen_SWC=a(Tf-Ts)^b
where a and b are two empirical coefficients associated with soil type. The details can be found in "Frozen soil parameterization in SiB2 and its validation with GAME-Tibet observations".
I would appreciate it if you could make some adjustments in the above aspect! if it is infeasible, what should I do to make the results are more accurate in frozen soils? I am looking forward to your reply! Thank you very much