Intercomparison of sugar maple ( Acer saccharum Marsh.) stand transpiration responses to environmental conditions from the Western Great Lakes Region of the United States

Abstract

We investigated the assumption, necessary for comparison between bottom-up scaling of plot level fluxes to top-down scaling of regional models, that small plots of sap flux are representative of the transpiration component of regional land-surface atmosphere water vapor interactions. We conducted sap flux measurements in three stands dominated by sugar maple ( Acer saccharum Marsh.) representing old-growth (Sylvania, SV), second-growth (Willow Creek, WC), and thinned second-growth stands (Hay Creek, HC). Using the sap flux-scaled estimates of transpiration we tested whether (1) differences in A. saccharum transpiration between the three stands could be explained by leaf area index and/or stand inventory measures, and (2) the Terrestrial Regional Ecosystem Exchange Simulator (TREES) model could capture differences in the response of transpiration to environmental variables. We found large differences between the three stands over two growing seasons in A. saccharum canopy transpiration per unit ground area (1.61, 3.66, and 0.85 mm day −1 for SV, WC, and HC respectively) and canopy transpiration per unit leaf area (0.31, 1.00, and 0.21 mm day −1 for SV, WC, and HC respectively). While none of these differences could be explained with stand or environmental variables, the TREES model was able to effectively capture the half-hourly temporal variability in the sap flux data. TREES incorporates an adaptive parameterization scheme which improves upon traditional sensitivity tests of models. By incorporating both simple plant hydraulic theory and adaptive parameterization we were able to minimize the necessary parameters to those that are sensible and easily applied regionally. Our results indicate that while the assumption of uniform water loss from A. saccharum forests regionally is incorrect, models that incorporate simple plant hydraulics effectively capture the dynamics of transpiration across disparate stands.