Seasonal variations and environmental control of water use efficiency in subtropical plantation

To understand the seasonal variations of water use efficiency (WUE) of coniferous plantation in the subtropical monsoon area, the experiment was conducted in 2003 and 2004 which presented two distinguished climatic conditions (severe summer drought in 2003 and normal climatic condition in 2004). The water stress influenced WUE greatly, which caused a special seasonal WUE pattern. WUE reached the minimum in summer drought and the maximum in winter, which was contrary to the variation of gross primary production (GPP) and canopy evaporation (Fw). In winter, GPP and Fw increased along with the increasing of air temperature and vapor pressure deficit (VPD), with the similar increasing rate. However, in drought summer, there was an adverse trend among GPP/Fw and air temperature and VPD, and the decreasing rate of GPP was far larger than that of Fw. In summer, the conservation of WUE was changed because of the environmental factors, resulting in the decreasing WUE. The photosynthesis and transpiration of vegetation were mainly controlled by the environmental factors in winter, and the impact of stomatal regulation was relatively weak. In summer, Fw was mainly controlled by the stomatal closure and GPP by both environmental factors and stomatal closure.

Simulation of CO_2 and latent heat fluxes in the North China Plain

We constructed a coupled model for simulating plant photosynthesis and evapotranspiration (CPCEM). In the model, non-rectangular hyperbola is used to simulate leaf photosynthesis rate that is scaled up to estimate canopy gross photosynthesis rate by an integral method. Whole canopy in the model is separated into multi-layers, each of which is divided into sunlit leaves and shade leaves. Canopy net photosynthesis rate is expressed as a function of canopy conductance which is coupled with evapotranspiration. Included the coupled function,evapotranspiration is estimated with a two-layer submodel. The main features of CPCEM are: (1)easy suitability, (2) good physiological base, and (3) simple calculation procedure. Simulated results of CPCEM were compared with those by an eddy covariance system that was installed in a winter wheat farmland of the North China Plain. CPCEM gave a quite well diurnal and seasonal dynamics of net ecosystem exchange, compared with the measurements. The root mean square error between simulation and measurements was only about 2.94 μ mol m-2 s-1. Diurnal and seasonal patterns of latent heat flux with the CPCEM were similar to those of measurements.Whereas, simulated latent heat flux was evidently higher than the measured.

Generalizing plant–water relations to landscapes

Aims Changing climate and land use patterns make it increasingly important that the hydrology of catchments and ecosystems can be reliably characterized.The aim of this paper is to identify the biophysical factors that determine the rates of water vapor loss from different types of vegetation,and to seek,from an array of currently available satelliteborne sensors,those that might be used to initialize and drive landscape-level hydrologic models.Important Findings Spatial variation in the mean heights,crowd widths,and leaf area indices(LAI)of plant communities are important structural variables that affect the hydrology of landscapes.Canopy stomatal conductance(G)imposes physiological limitation on transpiration by vegetation.The maximum value of G(Gmax)is closely linked to canopy photosynthetic capacity,which can be estimated via remote sensing of foliar chlorophyll or nitrogen contents.Gcan be modeled as a nonlinear multipliable function of:(i)leaf–air vapor pressure deficit,(ii)water potential gradient between soil and leaves,(iii)photosynthetically active radiation absorbed by the canopy,(iv)plant nutrition,(v)temperature and(vi)the CO_(2) concentration of the air.Periodic surveys with Light Detection and Ranging(LiDAR)and interferometric RADAR,along with high-resolution spectral coverage in the visible,near-infrared,and thermal infrared bands,provide,along with meteorological data gathered from weather satellites,the kind of information required to model seasonal and interannual variation in transpiration and evaporation from landscapes with diverse and dynamic vegetation.