The MAPSS Model

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MAPSS (Mapped Atmosphere-Plant-Soil System) is a global biogeography model which simulates the potential natural vegetation that can be supported at any upland site in the world under a long-term steady-state climate. MAPSS operates on the fundamental principle that ecosystems will tend to maximize the leaf area that can be supported at a site by available soil moisture or energy (Woodward 1987; Neilson et al. 1989; Neilson 1993a; Neilson 1995).

Conceptual Framework

The conceptual framework for this approach is that vegetation distributions are, in general, constrained by either the availability of water in relation to transpirational demands or the availability of energy for growth (Neilson and Wullstein 1983, Neilson et al. 1989, Stephenson 1990, Woodward 1987). In temperate latitudes, water is the primary constraint, while at high latitudes energy is the primary constraint (exceptions occur, of course, particularly in some areas that may be nutrient limited). The energy constraints on vegetation type and leaf area index (LAI) are currently modeled in MAPSS using a growing degree day algorithm as a surrogate for net radiation (e.g. Botkin et al. 1972; Shugart 1984).

The model calculates the leaf area index of both woody and grass life forms (trees or shrubs, but not both) in competition for both light and water, while maintaining a site water balance consistent with observed runoff (Neilson 1995). Water in the surface layer is apportioned to the two life forms in relation to their relative LAIs and stomatal conductances, i.e., canopy conductance, while woody vegetation alone has access to deeper soil water.

Biomes are not explicitly simulated in MAPSS; rather, the model simulates the distribution of vegetation lifeforms (tree, shrub, grass), the dominant leaf form (broadleaf, needleleaf), leaf phenology (evergreen, deciduous), thermal tolerances and vegetation density (LAI). These characteristics are then combined into a vegetation classification consistent with the biome level (Neilson 1995).

Model Workings

The principal features of the MAPSS model include algorithms for:

1) formation and melt of snow,
2) interception and evaporation of rainfall,
3) infiltration and percolation of rainfall and snowmelt through three soil layers,
4) runoff,
5) transpiration based on LAI and stomatal conductance,
6) biophysical 'rules' for leaf form and phenology,
7) iterative calculation of LAI, and
8) assembly rules for vegetation classification.

Infiltration, and saturated and unsaturated percolation, are represented by an analog of Darcy's Law specifically calibrated to a monthly time step. Water holding capacities at saturation, field potential, and wilting point are calculated from soil texture, as are soil water retention curves (Saxton et al., 1986). Transpiration is driven by potential evapotranspiration (PET) as calculated by an aerodynamic turbulent transfer model based upon Brutsaert's (1982) ABL model (Marks and Dozier, 1992; Marks 1990), with actual transpiration being constrained by soil water, leaf area and stomatal conductance. Stomatal conductance is modulated as a function of PET (a surrogate for vapor pressure deficit) and soil water content (Denmead and Shaw 1962). Canopy conductance ( i.e., actual transpiration) is an exponential function of LAI, modulated by stomatal conductance.

Elevated CO2 can affect vegetation responses to climate change through changes in carbon fixation and water-use-efficiency (WUE, carbon atoms fixed per water molecule transpired). The WUE effect is often noted as a reduction in stomatal conductance (Eamus 1991). Since MAPSS simulates carbon indirectly (through LAI), a WUE effect can be imparted directly as a change in stomatal conductance, which results in increased LAI (carbon stocks) and usually a small decrease in transpiration per unit land area.

MAPSS has been implemented at a 10 km resolution over the continental U.S. and at a 0.5o resolution globally (Neilson 1995, Neilson 1993a, Neilson and Marks 1994). The model has been partially validated within the U.S. and globally with respect to simulated vegetation distribution, LAI, and runoff (Neilson 1993a; Neilson 1995; Neilson and Marks 1994). MAPSS has also been implemented at the watershed scale (MAPSS-W, 200 m resolution) via a partial hybridization with a distributed catchment hydrology model (Daly 1994, Wigmosta 1994).


References

Botkin, D.B., J.F. Janak, and J.R. Wallis (1972)
Rationale, limitation, and assumptions of a northeastern forest growth simulator. IBM Journal of Research and Development 16(2):101-116.
Brutsaert, W. (1982)
Evaporation into the Atmosphere, D. Reidel, Dordrecht.
Daly, C. (1994)
Modeling climate, vegetation, and water balance at landscape to regional scales. Ph.D. Dissertation, Department of General Science, Oregon State University, Corvallis, OR.
Denmead, O.T. and R.H. Shaw (1962)
Availability of soil water to plants as affected by soil moisture content and meteorological conditions. Agronomy Journal 54:385-390.
Eamus, D. (1991)
The interaction of rising CO2 and temperatures with water use efficiency. Plant, Cell and Environment 14:843-852.
Marks, D. (1990)
The sensitivity of potential evapotranspiration to climate change over the continental United States. In: Gucinski, H., Marks, D., & Turner, D.A. (eds.) Biospheric feedbacks to climate change: The sensitivity of regional trace gas emissions, evapotranspiration, and energy balance to vegetation redistribution, pp. IV-1 - IV-31. EPA/600/3-90/078. U.S. Environmental Protection Agency, Corvallis, OR.
Marks, D. & Dozier, J. (1992)
Climate and energy exchange at the snow surface in the alpine region of the Sierra Nevada: 2. Snow cover energy balance. Water Resources Research 28: 3043-3054.
Neilson, R.P. (1993a)
Vegetation redistribution: A possible biosphere source of CO2 during climatic change. Water, Air and Soil Pollution 70:659-673.
Neilson, R.P. (1995)
A model for predicting continental scale vegetation distribution and water balance. Ecol. Appl. 5: 362-385.
Neilson, R.P. and D. Marks (1994)
A global perspective of regional vegetation and hydrologic sensitivities from climatic change. Journal of Vegetation Science 5:715-730.
Neilson, R.P., G.A. King, R.L. DeVelice, J. Lenihan, D. Marks, J. Dolph, W. Campbell, and G. Glick (1989)
Sensitivity of ecological landscapes to global climatic change. U.S. Environmental Protection Agency, EPA-600-3-89-073, NTIS-PB-90-120-072-AS, Washington, D.C., USA.
Neilson, R.P. and L.H. Wullstein (1983)
Biogeography of two southwest American oaks in relation to atmospheric dynamics. Journal of Biogeography 10:275-297.
Saxton, K.E., W.J. Rawls, J.S. Romberger, and R.I. Papendick (1986)
Estimating generalized soil-water characteristics from texture. Soil Science Society of America 50:1031-1036.
Shugart, H.H. (1984)
A theory of forest dynamics. Springer-Verlag, New York, New York, USA.
Stephenson, N.L. (1990)
Climatic control of vegetation distribution: The role of the water balance. The American Naturalist 135:649-670.
Wigmosta, M.S., L.W. Vail, and D.A. Lettenmaier (1994)
A distributed hydrology-vegetation model for complex terrain. Water Resources Research 30:1665-1679.
Woodward, F.I. (1987)
Climate and plant distribution. Cambridge University Press, London, England.

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