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2012 Annual Science Report

VPL at University of Washington Reporting  |  SEP 2011 – AUG 2012

The VPL Life Modules

Project Summary

The VPL Life Modules involve development of simulation models of how biological processes – such as photosynthesis, breathing, and decay of organic materials – work on a planetary scale. When this is combined with the work of the atmospheric and planetary modeling teams, we are able simulate how these processes impact the atmosphere and climate of a planet. This information helps us understand how we might be able to detect whether or not a planet has life by looking at its atmosphere and surface. The Life Modules team has engaged in previous work coupling early Earth biogeochemistry and 1D models in the VPL’s suite of planetary models. Current work now focuses on the development of a land biosphere model coupled with a previously developed ocean biogeochemistry model and a 3D general circulation model (GCM). This terrestrial biosphere model is designed to simulate geographic distributions of life adapted to different climate zones, surface albedo, and carbon dioxide exchange and other biogenic gases with the atmosphere. These coupled models are first tested against Earth ground and satellite observations. A large data mining effort is now under way for the model of land-based ecosystem dynamics to uncover vegetation adaptations to climate that may be generalizable for both the Earth and alternative planetary environments.

4 Institutions
3 Teams
0 Publications
0 Field Sites
Field Sites

Project Progress

During the past year, the coupled Earth system suite of the Ent Terrestrial Biosphere Model (Ent TBM)1, the NASA Ocean Biogeochemical Model (NOBM)2, and the NASA Goddard Institute for Space Studies General Circulation Model (GISS GCM) achieved simulation of conserved carbon dynamics over seasonal cycles over 30-year late 20th century runs. However, these simulations were conducted with a simplified description of global land cover 3 that does not take into account fine structural variation within “plant functional types” that have grown in different climate zones, such that fluxes exhibit a trend that results from this vegetation map being out of equilibrium with climate variation over the globe. To provide fidelity to the existing land surface vegetation structure and geographic variation in surface fluxes, the first version of a satellite-derived global geographic vegetation structure data set was completed. This data set combines cover type, leaf area and albedo, from the Moderate Resolution Imaging Spectrometer (MODIS)4, forest canopy heights from the Geoscience Laser Altimeter System (GLAS) aboard the Ice, Cloud, and land Elevation Satellite(ICESat)5, inventories of human land uses 6, and several decades of 20th century climate statistics 7. This data set is the first attempt to introduce observed global forest heights into a global dynamic vegetation model (DGVM). Introduction of this detailed dataset, for both off-line simulations with observed meteorology as well as coupled to the GISS GCM, resulted in a fast equilibrium within three years and stable seasonal cycles.

Further refinement of the Ent TBM is still necessary to cover the full diversity of vegetation biophysical behavior and seasonal dynamics, and to reproduce the exact magnitude of latitudinal variation in the seasonal cycle of atmospheric CO2, something that has not been satisfactorily been achieved by any DGVM yet to date. To take advantage of the diversity and canopy details that are possible now with the Ent TBM, Kiang and colleagues have commenced a large data mining effort with a newly compiled database of plant traits, the TRY database 8. This data mining effort aims to derive both parameter fits as well as identify new, hopefully simpler, generalizable relations between plant biophysical, phenological, and allometric quantities, as well as their geographic variation with climate. 65 researchers from around the world have granted permission to use their data, and a data set of over 3 million records has now been compiled. Preliminary example studies using linear manifold clustering on a data subset indicates a promising technique for identifying distinctions between overstory and shaded vegetation.

A proposal has also been submitted to alter the Ent TBM to simulate novel hypothetical life forms, with alternative spectral albedoes such as for red dwarf planets and tolerances for extreme climate conditions.

a) Geographic variation in plant biomass (t-C/ha) derived from the Ent Global Vegetation Structure Dataset, assuming maximum forest heights from Simard et al (2011). b) Estimate of individual plant density for uniform canopies. The latter uncovers the high density of trees in Manitoba, Canada, where frequent fires promote short, dense, high-leaf area vegetation. These structural attributes as model boundary conditions enable constraints on model biophysical, phenological, and allometric parameters, with an aim to uncover generalizable relations with regard to climate adaptation.

1. Kiang, N.Y., R.D. Koster, P.R. Moorcroft, W. Ni-Meister, and D. Rind. (2006). “Ent: A Dynamic Global Terrestrial Ecosystem Model for Coupling with GCMs,” American Geophysical Union Fall Meeting, San Francisco, CA, December 10-15, 2006.

2. Gregg, W.W., A coupled ocean general circulation, biogeochemical, and radia
tive model of the global oceans: seasonal distributions of coean chlorophyll and nutrients, 2000, NASA Goddard Space Flight Center: Greenbelt, Maryland. p. 32.
3. Matthews, E. (1983). Global vegetation and land use: new high-resolution data bases for climate studies. Journal of Climate and Applied Meteorology, 22: p. 474-487.

4. Friedl, M.A., D.K. McIver, and (2002). Global land cover mapping from MODIS: Algorithms and early results. Remote Sensing of Environment, 83(1-2): p. 287-302.

5. Simard, M., N. Pinto, J.B. Fisher, and A. Baccini. (2011). Mapping forest canopy height globally with spaceborne lidar. Journal of Geophysical Research-Biogeosciences, 116.

6. Monfreda, C., N. Ramankutty, and J.A. Foley. (2008). Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Global Biogeochemical Cycles, 22(1): p. 19.

7. Sheffield, J., G. Goteti, and E.F. Wood. (2006). Development of a 50-yr high-resolution global dataset of meteorological forcings for land surface modeling. Journal of Climate, 19(13): p. 3088-3111.

8. Kattge, J., S. Diaz, S. Lavorel, C. Prentice, P. Leadley, G. Bonisch, E. Garnier, M. Westoby, P.B. Reich, I.J. Wright, J.H.C. Cornelissen, C. Violle, S.P. Harrison, P.M. van Bodegom, M. Reichstein, B.J. Enquist, N.A. Soudzilovskaia, D.D. Ackerly, M. Anand, O. Atkin, M. Bahn, T.R. Baker, D. Baldocchi, R. Bekker, C.C. Blanco, B. Blonder, W.J. Bond, R. Bradstock, D.E. Bunker, F. Casanoves, J. Cavender-Bares, J.Q. Chambers, F.S. Chapin, J. Chave, D. Coomes, W.K. Cornwell, J.M. Craine, B.H. Dobrin, L. Duarte, W. Durka, J. Elser, G. Esser, M. Estiarte, W.F. Fagan, J. Fang, F. Fernandez-Mendez, A. Fidelis, B. Finegan, O. Flores, H. Ford, D. Frank, G.T. Freschet, N.M. Fyllas, R.V. Gallagher, W.A. Green, A.G. Gutierrez, T. Hickler, S.I. Higgins, J.G. Hodgson, A. Jalili, S. Jansen, C.A. Joly, A.J. Kerkhoff, D. Kirkup, K. Kitajima, M. Kleyer, S. Klotz, J.M.H. Knops, K. Kramer, I. Kuhn, H. Kurokawa, D. Laughlin, T.D. Lee, M. Leishman, F. Lens, T. Lenz, S.L. Lewis, J. Lloyd, J. Llusia, F. Louault, S. Ma, M.D. Mahecha, P. Manning, T. Massad, B.E. Medlyn, J. Messier, A.T. Moles, S.C. Muller, K. Nadrowski, S. Naeem, U. Niinemets, S. Nollert, A. Nuske, R. Ogaya, J. Oleksyn, V.G. Onipchenko, Y. Onoda, J. Ordonez, G. Overbeck, W.A. Ozinga, S. Patino, S. Paula, J.G. Pausas, J. Penuelas, O.L. Phillips, V. Pillar, H. Poorter, L. Poorter, P. Poschlod, A. Prinzing, R. Proulx, A. Rammig, S. Reinsch, B. Reu, L. Sack, B. Salgado-Negre, J. Sardans, S. Shiodera, B. Shipley, A. Siefert, E. Sosinski, J.F. Soussana, E. Swaine, N. Swenson, K. Thompson, P. Thornton, M. Waldram, E. Weiher, M. White, S. White, S.J. Wright, B. Yguel, S. Zaehle, A.E. Zanne and C. Wirth. (2011). TRY – a global database of plant traits. Global Change Biology, 17(9): p. 2905-2935.

    Nancy Kiang Nancy Kiang
    Project Investigator
    Wenge Ni-Meister

    Crystal Schaaf
    Unspecified Role

    Objective 1.2
    Indirect and direct astronomical observations of extrasolar habitable planets.

    Objective 6.1
    Effects of environmental changes on microbial ecosystems

    Objective 6.2
    Adaptation and evolution of life beyond Earth

    Objective 7.2
    Biosignatures to be sought in nearby planetary systems