An analysis of the sensitivity of sap flux to soil and plant variables assessed for an Australian woodland using a soil-plant-atmosphere model.

Daily and seasonal patterns of tree water use were measured for the two dominant tree species, Angophora bakeri E.C.Hall (narrow-leaved apple) and Eucalyptus sclerophylla (Blakely) L.A.S. Johnson & Blaxell (scribbly gum), in a temperate, open, evergreen woodland using sap flow sensors, along with information about soil, leaf, tree and micro-climatological variables. The aims of this work were to: (a) validate a soil-plant-atmosphere (SPA) model for the specific site; (b) determine the total depth from which water uptake must occur to achieve the observed rates of tree sap flow; (c) examine whether the water content of the upper soil profile was a significant determinant of daily rates of sap flow; and (d) examine the sensitivity of sap flow to several biotic factors. It was found that: (a) the SPA model was able to accurately replicate the hourly, daily and seasonal patterns of sap flow; (b) water uptake must have occurred from depths of up to 3 m; (c) sap flow was independent of the water content of the top 80 cm of the soil profile; and (d) sap flow was very sensitive to the leaf area of the stand, whole tree hydraulic conductance and the critical water potential of the leaves, but insensitive to stem capacitance and increases in root biomass. These results are important to future studies of the regulation of vegetation water use, landscape-scale behaviour of vegetation, and to water resource managers, because they allow testing of large-scale management options without the need for large-scale manipulations of vegetation cover.

An automated procedure for estimating the leaf area index (LAI) of woodland ecosystems using digital imagery, MATLAB programming and its application to an examination of the relationship between remotely sensed and field measurements of LAI.

Leaf area index (LAI) is one of the most important variables required for modelling growth and water use of forests. Functional-structural plant models use these models to represent physiological processes in 3-D tree representations. Accuracy of these models depends on accurate estimation of LAI at tree and stand scales for validation purposes. A recent method to estimate LAI from digital images (LAID) uses digital image capture and gap fraction analysis (Macfarlane et al. 2007b) of upward-looking digital photographs to capture canopy LAID (cover photography). After implementing this technique in Australian evergreen Eucalyptus woodland, we have improved the method of image analysis and replaced the time consuming manual technique with an automated procedure using a script written in MATLAB 7.4 (LAIM). Furthermore, we used this method to compare MODIS LAI values with LAID values for a range of woodlands in Australia to obtain LAI at the forest scale. Results showed that the MATLAB script developed was able to successfully automate gap analysis to obtain LAIM. Good relationships were achieved when comparing averaged LAID and LAIM (LAIM = 1.009 - 0.0066 LAID; R2 = 0.90) and at the forest scale, MODIS LAI compared well with LAID (MODIS LAI = 0.9591 LAID - 0.2371; R2 = 0.89). This comparison improved when correcting LAID with the clumping index to obtain effective LAI (MODIS LAI = 1.0296 LAIe + 0.3468; R2 = 0.91). Furthermore, the script developed incorporates a function to connect directly a digital camera, or high resolution webcam, from a laptop to obtain cover photographs and LAI analysis in real time. The later is a novel feature which is not available on commercial LAI analysis softwares for cover photography. This script is available for interested researchers.