A Representation of Variable Root Distribution in Dynamic Vegetation Models

Abstract Root distribution is treated as a static component in most current dynamic vegetation models (DVMs). While changes in leaf and stem biomass are reflected in leaf area index (LAI) and vegetation height via specific leaf area (SLA) and allometric relationships, most DVMs assume that changes in root biomass do not result in changes in the root distribution profile and rooting depth. That is, the fraction of roots in soil layers, which is used to estimate transpiration, is taken to be constant and independent of root biomass and/or vegetation age. A methodology for parameterizing root distribution as a function of root biomass is proposed for use in dynamic vegetation models. In this representation, root distribution and rooting depth evolve and increase as root biomass increases, as is expected intuitively and as is seen in observations. Root biomass data from temperate coniferous, tropical evergreen, and tundra sites show that the approach successfully represents, to the first order, the change of ...

[1]  C. Huttel.  Root Distribution and Biomass in Three Ivory Coast Rain Forest Plots , 1975 .

[2]  Christopher Potter,et al.  Dynamic global vegetation modelling for prediction of plant functional types and biogenic trace gas fluxes , 1999 .

[3]  Wolfgang Knorr,et al.  Annual and interannual CO2 exchanges of the terrestrial biosphere: process-based simulations and uncertainties , 2000 .

[4]  T. Wright.  PROFILE DEVELOPMENT IN THE SAND DUNES OF CULBIN FOREST, MORAYSHIRE , 1955 .

[5]  S. Running,et al.  Simulated impacts of historical land cover changes on global climate in northern winter , 2000 .

[6]  Peter M. Cox,et al.  Description of the "TRIFFID" Dynamic Global Vegetation Model , 2001 .

[7]  J. Charney.  Dynamics of deserts and drought in the Sahel , 1975 .

[8]  Vivek K. Arora,et al.  Simulating energy and carbon fluxes over winter wheat using coupled land surface and terrestrial ecosystem models , 2003 .

[9]  H. Kage,et al.  Root growth of cauliflower (Brassica oleracea L. botrytis) under unstressed conditions: Measurement and modelling , 2000, Plant and Soil.

[10]  H. Douville,et al.  Importance of vegetation feedbacks in doubled‐CO2 climate experiments , 2000 .

[11]  G. McPherson,et al.  Spatial and temporal soil moisture resource partitioning by trees and grasses in a temperate savanna, Arizona, USA , 1997, Oecologia.

[12]  B. Law,et al.  Water limitations to carbon exchange in old-growth and young ponderosa pine stands. , 2002, Tree physiology.

[13]  J. G. Dennis,et al.  Shoot and rhizome-root standing crops of tundra vegetation at Barrow, Alaska. , 1970 .

[14]  I. C. Prentice,et al.  An integrated biosphere model of land surface processes , 1996 .

[15]  R. B. Jackson,et al.  Rooting depths, lateral root spreads and below‐ground/above‐ground allometries of plants in water‐limited ecosystems , 2002 .

[16]  N. Nadkarni,et al.  Root biomass distribution in a moist tropical montane forest , 1992, Plant and Soil.

[17]  P. Ketner,et al.  Terrestrial primary production and phytomass , 1979 .

[18]  R. B. Jackson,et al.  A global analysis of root distributions for terrestrial biomes , 1996, Oecologia.

[19]  S S I T C H,et al.  Evaluation of Ecosystem Dynamics, Plant Geography and Terrestrial Carbon Cycling in the Lpj Dynamic Global Vegetation Model , 2022 .

[20]  Robert B. Jackson,et al.  THE GLOBAL BIOGEOGRAPHY OF ROOTS , 2002 .

[21]  D. Verseghy,et al.  CLASS-A Canadian Land Surface Scheme for GCMs , 1993 .

[22]  V. Arora.  MODELING VEGETATION AS A DYNAMIC COMPONENT IN SOIL‐VEGETATION‐ATMOSPHERE TRANSFER SCHEMES AND HYDROLOGICAL MODELS , 2002 .

[23]  Mei Zhao,et al.  The impact of land cover change on the atmospheric circulation , 2001 .

[24]  Edward B. Rastetter,et al.  Global Change and the Carbon Balance of Arctic EcosystemsCarbon/nutrient interactions should act as major constraints on changes in global terrestrial carbon cycling , 1992 .

[25]  C. Justice,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part II: The Generation of Global Fields of Terrestrial Biophysical Parameters from Satellite Data , 1996 .

[26]  P. Rowntree,et al.  Understanding the Sensitivity of a GCM Simulation of Amazonian Deforestation to the Specification of Vegetation and Soil Characteristics , 1997 .

[27]  W. J. Shuttleworth,et al.  The water use of two dominant vegetation communities in a semiarid riparian ecosystem , 2000 .

[28]  Lisa J. Graumlich,et al.  Interactive Canopies for a Climate Model , 1998 .

[29]  B. Bonan,et al.  A Land Surface Model (LSM Version 1.0) for Ecological, Hydrological, and Atmospheric Studies: Technical Description and User's Guide , 1996 .

[30]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[31]  Michael T. Coe,et al.  Testing the performance of a dynamic global ecosystem model: Water balance, carbon balance, and vegetation structure , 2000 .

[32]  J. Ehleringer,et al.  Water stress and use of summer precipitation in a Great Basin shrub community , 1994 .

[33]  M. P.R.,et al.  A METHOD FOR SCALING VEGETATION DYNAMICS: THE ECOSYSTEM DEMOGRAPHY MODEL (ED) , 2022 .

[34]  R. Ceulemans,et al.  TRAP: a modelling approach to below-ground carbon allocation in temperate forests , 2001, Plant and Soil.

[35]  Debra P. C. Peters,et al.  Plant species dominance at a grassland–shrubland ecotone: an individual-based gap dynamics model of herbaceous and woody species , 2002 .

[36]  David Pollard,et al.  Use of a land-surface-transfer scheme (LSX) in a global climate model: the response to doubling stomatal resistance , 1995 .

[37]  I. Rodríguez‐Iturbe,et al.  Tree‐grass competition in space and time: Insights from a simple cellular automata model based on ecohydrological dynamics , 2002 .

[38]  Karl J Niklas,et al.  Global Allocation Rules for Patterns of Biomass Partitioning in Seed Plants , 2002, Science.