A method of determining rooting depth from a terrestrial biosphere model and its impacts on the global water and carbon cycle

We outline a method of inferring rooting depth from a Terrestrial Biosphere Model by maximizing the benefit of the vegetation within the model. This corresponds to the evolutionary principle that vegetation has adapted to make best use of its local environment. We demonstrate this method with a simple coupled biosphere/soil hydrology model and find that deep rooted vegetation is predicted in most parts of the tropics. Even with a simple model like the one we use, it is possible to reproduce biome averages of observations fairly well. By using the optimized rooting depths global Annual Net Primary Production (and transpiration) increases substantially compared to a standard rooting depth of one meter, especially in tropical regions that have a dry season. The decreased river discharge due to the enhanced evaporation complies better with observations. We also found that the optimization process is primarily driven by the water deficit/surplus during the dry/wet season for humid and arid regions, respectively. Climate variability further enhances rooting depth estimates. In a sensitivity analysis where we simulate changes in the water use efficiency of the vegetation we find that vegetation with an optimized rooting depth is less vulnerable to variations in the forcing. We see the main application of this method in the modelling communities of land surface schemes of General Circulation Models and of global Terrestrial Biosphere Models. We conclude that in these models, the increased soil water storage is likely to have a significant impact on the simulated climate and the carbon budget, respectively. Also, effects of land use change like tropical deforestation are likely to be larger than previously thought.

[1]  R. Burgy,et al.  The Relationship between oak tree roots and groundwater in fractured rock as determined by tritium tracing , 1964 .

[2]  E. Davidson,et al.  The role of deep roots in the hydrological and carbon cycles of Amazonian forests and pastures , 1994, Nature.

[3]  P. Jarvis,et al.  CHAPTER 1 – PREDICTING EFFECTS OF VEGETATION CHANGES ON TRANSPIRATION AND EVAPORATION , 1983 .

[4]  Piers J. Sellers,et al.  Amazonian Deforestation and Regional Climate Change , 1991 .

[5]  A. Friend.  Parameterisation of a global daily weather generator for terrestrial ecosystem modelling , 1998 .

[6]  E. Rastetter,et al.  Potential Net Primary Productivity in South America: Application of a Global Model. , 1991, Ecological applications : a publication of the Ecological Society of America.

[7]  Wolfgang Cramer,et al.  A simulation model for the transient effects of climate change on forest landscapes , 1993 .

[8]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .

[9]  Jörg Kaduk,et al.  A prognostic phenology scheme for global terrestrial carbon cycle models , 1996 .

[10]  William H. Press,et al.  Book-Review - Numerical Recipes in Pascal - the Art of Scientific Computing , 1989 .

[11]  Axel Kleidon,et al.  Optimised rooting depth and its impacts on the simulated climate of an atmospheric general circulation model , 1998 .

[12]  C. Federer,et al.  Transpirational supply and demand: Plant, soil, and atmospheric effects evaluated by simulation , 1982 .

[13]  D. Randall,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part I: Model Formulation , 1996 .

[14]  Ann Henderson-Sellers,et al.  Biosphere-atmosphere transfer scheme(BATS) version 1e as coupled to the NCAR community climate model , 1993 .

[15]  Iwan Supit,et al.  A simple method for generating daily rainfall data , 1986 .

[16]  William H. Press,et al.  Numerical Recipes: FORTRAN , 1988 .

[17]  Cort J. Willmott,et al.  GLOBAL DISTRIBUTION OF PLANT‐EXTRACTABLE WATER CAPACITY OF SOIL , 1996 .

[18]  A. Henderson‐sellers,et al.  A global archive of land cover and soils data for use in general circulation climate models , 1985 .

[19]  L. Dümenil,et al.  Discharge data from 50 selected rivers for GCM validation , 1993 .

[20]  H. Mooney,et al.  PREDICTING ECOSYSTEM RESPONSES TO ELEVATED CO2 CONCENTRATIONS , 1991 .

[21]  Niels H. Batjes,et al.  Development of a world data set of soil water retention properties using pedotransfer rules , 1996 .

[22]  E. T. Linacre,et al.  Estimating the net-radiation flux , 1968 .

[23]  E. L. Stone,et al.  On the maximum extent of tree roots , 1991 .

[24]  Ann Henderson-Sellers,et al.  Tropical deforestation: Modeling local‐ to regional‐scale climate change , 1993 .

[25]  M. Claussen,et al.  The atmospheric general circulation model ECHAM-4: Model description and simulation of present-day climate , 1996 .

[26]  Robert S. Webb,et al.  A global data set of soil particle size properties , 1991 .

[27]  J. Randerson,et al.  Terrestrial ecosystem production: A process model based on global satellite and surface data , 1993 .

[28]  Simulating root carbon storage with a coupled carbon — Water cycle root model , 1996 .