A model of stomatal conductance was developed to relate plant transpiration rate to photosynthetic active radiation (PAR), vapour pressure deficit and soil water potential. Parameters of the model include sensitivity of osmotic potential of guard cells to photosynthetic active radiation, elastic modulus of guard cell structure, soil-to-leaf conductance and osmotic potential of guard cells at zero PAR. The model was applied to field observations on three functional types that include 11 species in subtropical southern China. Non-linear statistical regression was used to obtain parameters of the model. The result indicated that the model was capable of predicting stomatal conductance of all the 11 species and three functional types under wide ranges of environmental conditions. Major conclusions included that coniferous trees and shrubs were more tolerant for and resistant to soil water stress than broad-leaf trees due to their lower osmotic potential, lignified guard cell walls, and sunken and suspended guard cell structure under subsidiary epidermal cells. Mid-day depression in transpiration and photosynthesis of pines may be explained by decreased stomatal conductance under a large vapour pressure deficit. Stomatal conductance of pine trees was more strongly affected by vapour pressure deficit than that of other species because of their small soil-to-leaf conductance, which is explainable in terms of xylem tracheids in conifer trees. Tracheids transport water by means of small pit-pairs in their side walls, and are much less efficient than the endperforated vessel members in broad-leaf xylem systems. These conclusions remain hypothetical until direct measurements of these parameters are available.

A linear, semi-theoretical relationship between the coverage change of plant communities due to spatial processes and a partial patchiness index of the community distribution patterns in a grassland landscape was established by partitioning the overall coverage change into a spatial increment caused by species migration and a local increment due to local ecological processes. This relationship implies that patchiness of grassland landscapes can accelerate either recovery or degradation of a community, depending on the environmental conditions depicted by a parameter termed as gradient strength. The established relationship also has potential applications in simulating pattern dynamics of plant community distributions for a grassland landscape using a spatially homogeneous patch-scale model. The derived linear relationship was applied to a one-hectare alkaline grassland observatory in northeast China. Gradient strengths of two major plant community types were determined via linear regression from simulation results for selected subregions of the grassland. The calibrated linear relationship was then applied to the rest of the grassland landscape. Preliminary comparisons with complete spatial simulations and observations indicated that using this linear relationship with a patch-scale model can simulate the coverage changes as accurately as using a comprehensive spatial simulation model.

The spatiotemporal variations of vegetation biomass of the ecological transect in northeast China were simulated. State variables of the model included green biomass and nongreen biomass of 12 vegetation categories and water contents of three soil layers. The simulated monthly green biomass was converted into NDVI, or Normalized Differential Vegetation Index of AVHRR (Advanced Very High Resolution Radiometry). A comparison between the modeled and the observed NDVI was made at 10' spatial resolution. Atmospheric CO2 concentration and monthly precipitation were used as two driving variables for global change simulation. Effects of precipitation increments on percentage sunshine, relative humidity, radiation, evapotranspiration, and eventually soil water and plant growth, were considered. Two levels of CO2 concentration (present, doubled) and seven levels of precipitation increments (0, 0.05, 0.1, 0.15, 0.2, 0.25, and 0.30) were prescribed for a total of 14 simulation runs. A steady-state solution was obtained for each simulation run. The results of simulation showed that with the present climate conditions, doubling atmospheric CO2 concentration led approximately to a 20.3% increase in green biomass, 11.0% increase in nongreen biomass, 19.0% increase in green NPP, 12.8% increase in nongreen NPP, and 14.9% increase in overall average NPP at steady state. These increases go, respectively, to 32.9, 13.9, 30.0, 20.1, and 23.4% when a 30% precipitation increase was superimposed on the doubled CO2 concentration.

A computer simulation model of regional vegetation dynamics was applied to the terrestrial ecosystems of China to study the responses of vegetation to elevated CO2 and global climatic change. The primary production processes were coupled with vegetation structure in the model. The model was parameterized and partially validated in light of a large number of field observations made throughout China on primary productivity, 10 years of monthly meteorological data, 5 years of monthly normalized differential vegetation index observed by NOAA-11 satellite, and digital vegetation and terrain maps. Eight different climatic scenarios, set by perturbations from the present climate, 100% in atmospheric CO2 concentration, 2 C in monthly mean temperature, and 20% in monthly precipitation, were applied to analyze the sensitivity of the Chinese terrestrial ecosystems to climatic change. Simulation results were obtained for each of the climatic scenarios with the model running toward equilibrium solutions at a time step of 1 month. Preliminary validation indicated that the model was capable of simulating the net primary productivity of most vegetation classes and the potential vegetation structure in China under present climatic conditions. The simulations for the altered climatic scenarios predicted that grasslands, shrubs, and conifer forests are more sensitive to environmental changes than evergreen broadleaf forests in warm, wet southeast China and desert vegetation in cold, arid northwest China. For less than 150% of changes in vegetation structure under altered climatic conditions, about three quarters of the changes in net primary productivity of individual vegetation classes were shown to be attributed to the changes in the corresponding distribution area.

A model for the alkaline grassland ecosystems, MAGE, was applied to plant communities dominated by three species. Field observations on two communities dominated respectively by Puccinellia tenuiflora and Suaeda corniculata were used to parameterize the model for multiple species interaction. The model behaves reasonably in following the seasonal variations of water content, soluble sodium cation and calcium cation in surface soil, as well as biomass of the plant communities. Simulations were run to investigate the effects of ground water quality, ground water table depth, maximum noncapillary porosity in surface soil and harvest intensity, on ecosystem dynamics. The results indicated that ground water sodium concentration and ground water table depth had primary control on soil alkalization and vegetation status. The improvement of soil conditions by vegetation is limited to an extent with moderate ground water depth and sodium concentration. Noncapillary pores are critical for vegetation to affect the soil alkalization/dealkalization process, but the effect of noncapillary pores tends to saturate when maximum noncapillary porosity is greater than 0.1.