DYNAMIC SIMULATION OF TREE–GRASS INTERACTIONS FOR GLOBAL CHANGE STUDIES

The objective of this study was to simulate dynamically the response of a complex landscape, containing forests, savannas, and grasslands, to potential climate change. Thus, it was essential to simulate accurately the competition for light and water between trees and grasses. Accurate representation of water competition requires simulating the appropriate vertical root distribution and soil water content. The importance of different rooting depths in structuring savannas has long been debated. In simulating this complex landscape, we examined alternative hypotheses of tree and grass vertical root distribution and the importance of fire as a disturbance, as they influence savanna dynamics under historical and changing climates. MC1, a new dynamic vegetation model, was used to estimate the distribution of vegetation and associated carbon and nutrient fluxes for Wind Cave National Park, South Dakota, USA. MC1 consists of three linked modules simulating biogeography, biogeochemistry, and fire disturbance. This new tool allows us to document how changes in rooting patterns may affect production, fire frequency, and whether or not current vegetation types and life-form mixtures can be sustained at the same location or would be replaced by others. Because climate change may intensify resource deficiencies, it will probably affect allocation of resources to roots and their distribution through the soil profile. We manipulated the rooting depth of two life-forms, trees and grasses, that are competing for water. We then assessed the importance of variable rooting depth on eco- system processes and vegetation distribution by running MC1 for historical climate (1895- 1994) and a GCM-simulated future scenario (1995-2094). Deeply rooted trees caused higher tree productivity, lower grass productivity, and longer fire return intervals. When trees were shallowly rooted, grass productivity exceeded that of trees even if total grass biomass was only one-third to one-fourth that of trees. Deeply rooted grasses developed extensive root systems that increased N uptake and the input of litter into soil organic matter pools. Shallowly rooted grasses produced smaller soil carbon pools. Under the climate change scenario, NPP and live biomass increased for grasses and decreased for trees, and total soil organic matter decreased. Changes in the size of biogeochemical pools produced by the climate change scenario were overwhelmed by the range of responses across the four rooting configurations. Deeply rooted grasses grew larger than shallowly rooted ones, and deeply rooted trees outcompeted grasses for resources. In both historical and future scenarios, fire was required for the coexistence of trees and grasses when deep soil water was available to trees. Consistent changes in fire frequency and intensity were simulated during the climate change scenario: more fires occurred because higher temperatures resulted in decreased fuel moisture. Fire also increased in the deeply rooted grass configurations because grass biomass, which serves as a fine fuel source, was relatively high.

[1]  R. B. Jackson,et al.  A global budget for fine root biomass, surface area, and nutrient contents. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Edward T. Linacre,et al.  A simple formula for estimating evaporation rates in various climates, using temperature data alone , 1977 .

[3]  B. Walker,et al.  Aspects of the Stability and Resilience of Savanna Ecosystems , 1982 .

[4]  A. G. Marshall,et al.  The Ecology of Neotropical Savannas. , 1984 .

[5]  Jack D. Cohen,et al.  The 1978 National Fire-Danger Rating System: technical documentation , 1984 .

[6]  T. Black,et al.  Processes Controlling Understorey Evapotranspiration , 1989 .

[7]  Partitioning evapotranspiration into tree and understorey components in two young pinus radiata D. Don stands , 1990 .

[8]  R. Sands,et al.  Water relations of Pinusradiata in competition with weeds , 1984 .

[9]  W. Cramer,et al.  A global biome model based on plant physiology and dominance, soil properties and climate , 1992 .

[10]  B. Walker,et al.  Interactions of woody and herbaceous vegetation in a southern African Savanna , 1985 .

[11]  T. Black,et al.  Effects of salal understory removal on photosynthetic rate and stomatal conductance of young Douglas-fir trees , 1986 .

[12]  W. Parton,et al.  Testing the ‘CENTURY’ ecosystem level model on data sets from eight grassland sites in the former USSR representing a wide climatic/soil gradient , 1997 .

[13]  W. Parton,et al.  Analysis of factors controlling soil organic matter levels in Great Plains grasslands , 1987 .

[14]  Vemap Participants Vegetation/ecosystem modeling and analysis project: Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling , 1995 .

[15]  C. E. Van Wagner,et al.  Prediction of crown fire behavior in two stands of jack pine , 1993 .

[16]  P. G. Jarvis,et al.  Productivity of temperate de-ciduous and evergreen forests , 1983 .

[17]  J. Menaut,et al.  Tree and grass rooting patterns in an African humid savanna , 1997 .

[18]  A. J. Belsky,et al.  Influences of Trees on Savanna Productivity: Tests of Shade, Nutrients, and Tree-Grass Competition , 1994 .

[19]  J. Menaut,et al.  Influence of trees on above‐ground production dynamics of grasses in a humid savanna , 1995 .

[20]  J. Wallace,et al.  Seasonal changes in leaf area, stomatal and canopy conductances and transpiration from bracken below a forest canopy. , 1980 .

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

[22]  J. Hall,et al.  Root Distribution under a Thicket Clump on the Accra Plains, Ghana: Its Relevance to Clump Localization and Water Relations , 1973 .

[23]  Ronald P. Neilson,et al.  A rule-based vegetation formation model for Canada , 1993 .

[24]  R. Sands,et al.  Effects of compaction and simulated root channels in the subsoil on root development, water uptake and growth of radiata pine. , 1992, Tree physiology.

[25]  Paul B. Alaback,et al.  Software for computing plant biomassBIOPAK users guide. , 1994 .

[26]  Kevin C. Ryan,et al.  Modeling postfire conifer mortality for long-range planning , 1986 .

[27]  W. E. Larson,et al.  Estimating soil water retention characteristics from particle size distribution, organic matter percent, and bulk density , 1979 .

[28]  J. E. Means,et al.  Software for computing plant biomass: Biopak users guide. Forest Service general technical report , 1994 .

[29]  R. Scholes,et al.  Tree-grass interactions in Savannas , 1997 .

[30]  C. Rose,et al.  Tree pasture interactions at a range of tree densities in an agroforestry experiment. I. Rooting patterns , 1990 .

[31]  Rexford F. Daubenmire,et al.  Ecology of Fire in Grasslands , 1968 .

[32]  D. State,et al.  Equations Predicting Primary Productivity (Biomass) of Trees, Shrubs and Lesser Vegetation Based on Current Literature , 1979 .

[33]  C. Skarpe,et al.  Dynamics of savanna ecosystems , 1992 .

[34]  R. B. Jackson,et al.  BELOWGROUND CONSEQUENCES OF VEGETATION CHANGE AND THEIR TREATMENT IN MODELS , 2000 .

[35]  W. Parton,et al.  Modelling water, nitrogen, and crop yield for a long-term fallow management experiment , 1995 .

[36]  John F. B. Mitchell,et al.  The second Hadley Centre coupled ocean-atmosphere GCM: model description, spinup and validation , 1997 .

[37]  C. E. Van Wagner,et al.  Height of Crown Scorch in Forest Fires , 1973 .

[38]  Helmut Lieth,et al.  Primary Production of the Major Vegetation Units of the World , 1975 .

[39]  L. Akpo Influence du couvert ligneux sur la structure et le fonctionnement de la strate herbacée en milieu sahélien : les déterminants écologiques , 1992 .

[40]  Susan E. Trumbore,et al.  AGE OF SOIL ORGANIC MATTER AND SOIL RESPIRATION: RADIOCARBON CONSTRAINTS ON BELOWGROUND C DYNAMICS , 2000 .

[41]  E. K. Sadanandan Nambiar,et al.  Interplay between nutrients, water, root growth and productivity in young plantations , 1990 .

[42]  F. Steward,et al.  A method for predicting the depth of lethal heat penetration into mineral soils exposed to fires of various intensities. , 1990 .

[43]  R. B. Jackson,et al.  THE VERTICAL DISTRIBUTION OF SOIL ORGANIC CARBON AND ITS RELATION TO CLIMATE AND VEGETATION , 2000 .

[44]  P. S. Eagleson,et al.  Water‐Limited Equilibrium of Savanna Vegetation Systems , 1985 .

[45]  R. Neilson A Model for Predicting Continental‐Scale Vegetation Distribution and Water Balance , 1995 .

[46]  W. Lauenroth,et al.  Spatial Distributions of Grass and Shrub Root Systems in the Shortgrass Steppe , 1994 .

[47]  W. Ruhland Encyclopedia of plant physiology. , 1958 .

[48]  J. Jeník,et al.  A Study of a Vegetation Catena in Guinea Savanna at Mole Game Reserve (Ghana) , 1968 .

[49]  L. H. Allen,et al.  Advances in carbon dioxide effects research. Proceedings of a symposium, Cincinnati, Ohio, USA, 7-12 November 1993. , 1997 .

[50]  W. Parton,et al.  A general model for soil organic matter dynamics: sensitivity to litter chemistry, texture and management. , 1994 .

[51]  W. Neilsen,et al.  Root distribution of Pinus radiata related to soil characteristics in five Tasmanian soils , 1983 .

[52]  D. Benkert Ellenberg, H., Vegetation Mitteleuropas mit den Alpen in ökologischer Sicht. 2., völlig neubearbeitete Aufl. 981 S., 499 Abb. und 130 Tab. Leinen mit Schutzumschlag. Verlag Eugen Ulmer. Stuttgart, 1978. DM 120.— , 1979 .

[53]  T. Black,et al.  Transpiration rate of Douglas fir trees in thinned and unthinned stands. , 1980 .