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Baldocchi, Dennis D.; Krebs, Theresa; Leclerc, Monique Y. (2011)
Publisher: Tellus B
Journal: Tellus B
Languages: English
Types: Article
We modified the “Daisyworld” model of Watson and Lovelock to consider the energy balance of vegetation with differing potential to evaporate water vapour across a 2-D landscape. High-resolution spatial fields of surface temperature, latent heat exchange and net radiation are computed using cellular automata (CA). The CA algorithm considers competition between actively transpiring “wet daisies” and “dry daisies” for bare ground through temperature-dependent birth and death probabilities.This paper examines how differences in biophysical properties (e.g. surface albedo and surface conductance) affect the composition and heterogeneity of the landscape and its energy exchange. And with high resolution and gridded spatial information we evaluate bias errors and scaling rules associated with the subgrid averaging of the nonlinear functions used to compute surface energy balance.Among our key findings we observe that there are critical conditions, associated with albedo and surface resistance, when wet or dry/dark or bright “daisies” dominate the landscape. Second, we find that the heterogeneity of the spatial distribution of “daisies” depends on initial conditions (e.g. a bare field versus a random assemblage of surface classes). And third, the spatial coefficient of variation of land class, latent heat exchange, net radiation and surface temperature scale with the exponential power of the size of the averaging window.Though conceptual in nature, the 2-D “wet/dry Daisyworld” model produces a virtual landscape whose power-law scaling exponent resembles the one derived for the spatial scaling of a normalized difference vegetation index for a heterogeneous savanna ecosystem. This observation is conditional and occurs if the initial landscape is bare with two small colonies of “wet” and “dry” daisies.Bias errors associated with the nonlinear averaging of the surface energy balance equation increase as the coefficient of variation of the surface properties increases. Ignoring the subgrid variability of latent heat exchange produces especially large bias errors (up to 300%) for heterogeneous landscapes. We also find that spatial variations in latent heat exchange, surface temperature and net radiation, derived from our “Daisyworld” model, scale with the spatial variation in surface properties. These results suggest that we may be able to infer spatial patterns of surface energy fluxes from remote sensing data of surface features. “Wet/dry Daisyworld”, therefore, has the potential to provide a link between observations of landscape heterogeneity, deduced from satellites, and their interpretation into spatial fields of latent and sensible heat exchange and surface temperature.DOI: 10.1111/j.1600-0889.2005.00149.x
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    • Ackland, G. J., Clark, M. A. and Lenton, T. M. 2003. Catastrophic desert formation in Daisyworld. J. Theor. Biol. 223, 39-44.
    • Adams, B., Carr, J., Lenton, T. M. and White, A. 2003. One-dimensional daisyworld: spatial interactions and pattern formation. J. Theor. Biol. 223, 505-513.
    • Avissar, R. 1995. Scaling of land-atmosphere interactions-an atmospheric modeling perspective. Hydrol. Process. 9, 679-695.
    • Baldocchi, D. D. 2003. Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: past, present and future. Global Change Biol 9, 479-492.
    • Baldocchi, D. D., Falge, E., Gu, L. H., Olson, R., Hollinger, D. and co-authors. 2001. FLUXNET: a new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities. Bull. Am. Meteorol. Soc. 82, 2415-2434.
    • Baldocchi, D. D., Fuentes, J., Bowling, D., Turnipseed, A. and Monson, R. 1999. Scaling isoprene fluxes from leaves to canopies: test cases over a boreal aspen and a mixed temperate forest. J. Appl. Meteorol. 38, 885-898.
    • Baldocchi, D. D. and Meyers, T. 1998. On using eco-physiological, micrometeorological and biogeochemical theory to evaluate carbon dioxide, water vapor and trace gas fluxes over vegetation: a perspective. Agric. Forest Meteorol. 90, 1-25.
    • Baldocchi, D. D. and Rao, K. S. 1995. Intra-field variability of scalar flux densities across a transition between a desert and an irrigated potato advection field. Boundary Layer Meterol. 76, 109-136.
    • Baldocchi, D. D., Xu, L. and Kiang, N. 2004. How plant functional-type, weather, seasonal drought, and soil physical properties alter water and energy fluxes of an oak-grass savanna and an annual grassland. Agric. Forest Meteorol. 123, 13-39.
    • Bonan, G. B., Pollard, D. and Thompson, S. L. 1993. Influence of subgrid scale heterogeneity in leaf area index, stomatal resistance and soil moisture on grid scale land-atmosphere interactions. J. Climate 6, 1882-1897.
    • Brunsell, N. A. and Gillies, R. R. 2003. Scale issues in land-atmosphere interactions: implications for remote sensing of the surface energy balance. Agric. Forest Meteorol. 117, 203-221.
    • Bunzli, D. and Schmid, H. P. 1998. The influence of surface texture on regionally aggregated evaporation and energy partitioning. J. Atmos. Sci. 55, 961-972.
    • Canadell, J., Mooney, H., Baldocchi, D., Berry, J., Ehleringer, J. and coauthors. 2000. Carbon metabolism of the terrestrial biosphere. Ecosystems 3, 115-130.
    • Cohen, J. E. and Rich, A. D. 2000. Interspecific competition affects temperature stability in Daisyworld. Tellus B 52, 980-984.
    • Crawford, T., Dobosy, R., McMillen, R., Vogel, C. and Hicks, B. 1996. Air-surface exchange measurement in heterogeneous regions: extending tower observations with spatial structure observed from small aircraft. Global Change Biol. 2, 275-285.
    • Cronhort, M. B. 2000. The interplay between reaction and diffusion. In: The Geometry of Ecological Interactions: Simplifying Spatial Complexity (eds U. Dieckmann, R. Law and J. Metz), pp. 151-170. Cambridge University Press, Cambridge.
    • Desjardins, R. L., MacPherson, J. I., Mahrt, L., Schuepp, P., Pattey, E. and co-authors. 1997. Scaling up flux measurements for the boreal forest using aircraft-tower combinations. J. Geophys. Res. 102, 29 125-29 134.
    • Dickinson, R. E. 1995. Land processes in climate models. Remote Sensing Environ. 51, 27-38.
    • Eagleson, P. J. 1982. Ecological optimality in water limited natural soilvegetation systems. Water Resour. Res. 18, 325-340.
    • Fernandez-Illescas, C. P. and Rodriguez-Iturbe, I. 2004. The impact of interannual rainfall variability on the spatial and temporal patterns of vegetation in a water-limited ecosystem. Adv. Water Resour. 27, 83-95.
    • Gardner, M. 1971. Cellular automata, self-reproduction, garden of Eden and Game of Life. Sci. Am. 224, 112.
    • Higgins, S. I., Bond, W. J. and Trollope, W. S. W. 2000. Fire, resprouting and variability: a recipe for grass-tree coexistence in savanna. J. Ecol. 88, 213-229.
    • Jeltsch, F., Milton, S. J., Dean, W. R. J. and van Rooyen, N. 1996. Tree spacing and coexistence in semiarid savannas. J. Ecol. 84, 583-595.
    • Kim, J., Guo, Q., Baldocchi, D., Xu, L., Leclerc, M. and co-authors. 2005. Upscaling CO2 fluxes from tower to landscape: overlaying tower flux footprint calculations on high resolution (IKONOS) vegetation density images. Agric. Forest Meteorol. in press.
    • Kustas, W. P., Norman, J. M., Anderson, M. C. and French, A. N. 2003. Estimating subpixel surface temperatures and energy fluxes from the vegetation index-radiometric temperature relationship. Remote Sensing Environ. 85, 429-440.
    • Lenton, T. M. and Lovelock, J. E. 2001. Daisyworld revisited: quantifying biological effects on planetary self-regulation. Tellus 53B, 288- 305.
    • Lenton, T. M. and van Oijen, M. 2002. Gaia as a complex adaptive system. Phil. Trans. R. Soc. Lond. B 357, 683-695.
    • Levin, S. A. 1992. The problem of pattern and scale in ecology. Ecology 73, 1943-1967.
    • Lyons, T. J. and Halldin, S. 2004. Surface heterogeneity and the spatial variation of fluxes. Agric. Forest Meteorol. 121, 153-165.
    • McGuffie, K. and Henderson-Sellers, A. 1997. A Climate Modeling Primer. 2nd edn. Wiley, Chichester.
    • McNaughton, K. G. 1994. Effective stomatal and boundary-layer resistances of heterogeneous surfaces. Plant Cell Environ. 17, 1061-1068.
    • Monteith, J. L. and Unsworth, M. H. 1990. Principles of Environmental Physics, Edward Arnold, London.
    • Morisette, J. T., Nickeson, J. E., Davis, P., Wang, Y., Tian, Y. and coauthors. 2003. High spatial resolution satellite observations for validation of MODIS land products: IKONOS observations acquired under the NASA scientific data purchase. Remote Sensing Environ. 88, 100- 110.
    • Nilson, T. 1971. A theoretical analysis of the frequency of gaps in plant stands. Agric. Meteorol. 8, 25-38.
    • Ogunjemiyo, S. O., Kaharabata, S. K., Schuepp, P. H., MacPherson, I. J., Desjardins, R. L. and co-authors. 2003. Methods of estimating CO2, latent heat and sensible heat fluxes from estimates of land cover fractions in the flux footprint. Agric. Forest Meteorol. 117, 125-144.
    • Park, Y.-S. and Paw U, K. T. 2004. Numerical estimation of horizontal advection inside canopies. J. Appl. Meteorol. 43, 1530-1538.
    • Paw U, K. T. and Gao, W. 1988. Applications of solutions to non-linear energy budget equations. Agric. Forest Meteorol. 43, 121-145.
    • Pielke, R. A. Sr., Avissar, R., Raupach, M., Dolman, A. J. and co-authors. 1998. Interactions between the atmosphere and terrestrial ecosystems: influence on weather and climate. Global Change Biol. 4, 461-475.
    • Press, W. H., Teukolsky, S. A., Vetterling, W. T. and Flannery, B. P. 1988. Numerical Recipes in C. Cambridge University Press, Cambridge.
    • Pyles, R. D., Weare, B. C., Paw U, K. T. and Gustafson, W. 2003. Coupling between the University of California, Davis, Advanced CanopyAtmosphere-Soil Algorithm (ACASA) and MM5: preliminary results for July 1998 for western North America. J. Appl. Meteorol. 42, 557- 569.
    • Raupach, M. R. 1991. Vegetation-atmosphere interaction in homogeneous and heterogeneous terrain-some implications of mixed-layer dynamics. Vegetatio 91, 105-120.
    • Raupach, M. R. and Finnigan, J. J. 1995. Scale issues in boundary layer meteorology-surface energy balances in heterogeneous terrain. Hydrol. Process. 9, 589-612.
    • Rietkerk, M., Dekker, S. C., de Ruiter, P. C. and van de Koppel, J. 2004. Self-organized patchiness and catastrophic shifts in ecosystems. Science 305, 1926-1929.
    • Rodriguez-Iturbe, I., D'Odorico, P., Porporato, A. and Ridolfi, L. 1999. Tree-grass coexistence in savannas: the role of spatial dynamics and climate fluctuations. Geophys. Res. Lett. 26, 247-250.
    • Running, S. W., Baldocchi, D. D., Turner, D., Gower, S. T., Bakwin, P. and co-authors. 1999. A global terrestrial monitoring network, scaling tower fluxes with ecosystem modeling and EOS satellite data. Remote Sensing Environ. 70, 108-127.
    • Running, S. W., Loveland, T. R., Pierce, L. L., Nemani, R. R. and Hunt, J. E. R. 1995. A remote sensing based vegetation classification logic for global land cover analysis 1. Remote Sensing Environ. 51, 39-48.
    • Running, S., Nemani, R., Heinsch, F., Zhao, M., Reeves, M. and coauthors. 2004. A continuous satellite-derived measure of global terrestrial primary production. BioScience 54, 547-560.
    • Sankaran, M., Ratnam, J. and Hanan, N. P. 2004. Tree-grass coexistence in savannas revisited-insights from an examination of assumptions and mechanisms invoked in existing models. Ecol. Lett. 7, 480- 490.
    • Saunders, P. T. 1994. Evolution without natural selection: further implications of the Daisyworld parable. J. Theor. Biol. 166, 365-373.
    • Schmid, H. P. 2002. Footprint modeling for vegetation atmosphere exchange studies: a review and perspective. Agric. Forest Meteorol. 113, 159-183.
    • Scholes, R. J. and Archer, S. R. 1997. Tree-grass interactions in savannas. Annu. Rev. Ecol. Syst. 28, 517-544.
    • Sellers, P. J. 1987. Canopy reflectance, photosynthesis, and transpiration, II. The role of biophysics in the linearity of their interdependence. Remote Sensing Environ. 21, 143-183.
    • Sellers, P. J., Dickinson, R. E., Randall, D. A., Betts, A. K., Hall, F. G. and co-authors. 1997. Modeling the exchanges of energy, water, and carbon between continents and the atmosphere. Science 275, 502- 509.
    • Ustin, S. L., Roberts, D. A., Gamon, J. A., Asner, G. P. and Green, R. O. 2004. Using imaging spectroscopy to study ecosystem processes and properties. BioScience 54, 523-534.
    • van Wijk, M. T. and Rodriguez-Iturbe, I. 2002. Tree-grass competition in space and time: insights from a simple cellular automata model based on ecohydrological dynamics. Water Resour. Res. 38(9), 1179, doi:10.1029/2001WR000768.
    • von Bloh, W., Block, A. and Schellnhuber, H. J. 1997. Self-stabilization of the biosphere under global change: a tutorial geophysiological approach. Tellus B 49, 249-262.
    • von Bloh, W., Block, A., Parade, M. and Schellnhuber, H. J. 1999. Tutorial modelling of geosphere-biosphere interactions: the effects of percolation-type habitat fragmentation. Physica A 266, 186-196.
    • Watson, A. and Lovelock, J. 1983. Biological homeostasis of the global environment: the parable of Daisyworld. Tellus 35B, 286-289.
    • Wilson, K., Goldstein, A., Falge, E., Aubinet, M., Baldocchi, D. and co-authors. 2002. Energy balance closure at FLUXNET sites. Agric. Forest Meteorol. 113, 223-243.
    • Wolfram, S. 2002. A New Kind of Science. Wolfram Media, Champaign, IL.
    • Zeng, X., Pielke, R. A. and Eykholt, R. 1990. Chaos in Daisyworld. Tellus 42B, 309-318.
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