title: Detecting the differences in responses of stomatal conductance to moisture stresses between deciduous shrubs and Artemisia subshrubs.
abstract: Shrubs and subshrubs can tolerate wider ranges of moisture stresses in both soil and air than other plant life forms, and thus represent greater nonlinearity and uncertainty in ecosystem physiology. The objectives of this paper are to model shrub/subshrub stomatal conductance by synthesizing the field leaf gas exchanges data of 24 species in China, in order to detect the differences between deciduous shrubs and Artemisia subshrubs in their responses of stomatal conductance to changes in the moisture stresses. We revised a model of stomatal conductance by incorporating the tradeoff between xylem hydraulic efficiency and cavitation loss risk. We then fit the model at the three hierarchical levels: global (pooling all data as a single group), three functional groups (deciduous non-legume shrubs, deciduous legume shrubs, and subshrubs in Artemisia genus), and individual observations (species × sites). Bayesian inference with Markov Chain Monte Carlo method was applied to obtain the model parameters at the three levels. We found that the model at the level of functional groups is a significant improvement over that at the global level, indicating the significant differences in the stomatal behavior among the three functional groups. The differences in tolerance and sensitivities to changes in moisture stresses are the most evident between the shrubs and the subshrubs: The two shrub groups can tolerate much higher soil water stress than the subshrubs. The analysis at the observation level is also a significant improvement over that at the functional group level, indicating great variations within each group. Our analysis offered a clue for the equivocal issue of shrub encroachment into grasslands: While the invasion by the shrubs may be irreversible, the dominance of subshrubs, due to their lower resistance and tolerance to moisture stresses, may be put down by appropriate grassland management.
authors.affiliation: Landscape Analysis and Modeling Group, National Laboratory of Earth Surface Processes and Resources Ecology, Beijing Normal University, Beijing, China.
authors.forename: Qiong
authors.initials: Q
authors.lastname: Gao
authors.affiliation: Institute for Tropical Ecosystem Studies, University of Puerto Rico - Rio Piedras, San Juan, Puerto Rico, United States of America.
authors.forename: Mei
authors.initials: M
authors.lastname: Yu
authors.affiliation: College of Life Sciences, Liaoning University, Shenyang, China.
authors.forename: Chan
authors.initials: C
authors.lastname: Zhou
mesh_terms: D019306:Artemisia / Q000502:physiology*; D008954:Models, Biological; D018515:Plant Leaves / Q000502:physiology*; D018526:Plant Transpiration; D013045:Species Specificity; D013312:Stress, Physiological