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A Procedure for Calculating Daily Moisture Stress and Its Utility in Regressions of Tree Growth on Weather
Author(s) -
Zahner Robert,
Stage Albert R.
Publication year - 1966
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.2307/1935744
Subject(s) - environmental science , moisture , moisture stress , precipitation , vegetation (pathology) , water content , transpiration , hydrology (agriculture) , atmospheric sciences , soil science , mathematics , meteorology , geography , botany , biology , geology , medicine , photosynthesis , geotechnical engineering , pathology
A method is described for computing daily values of moisture stress on forest vegetation, or water deficits, based on the differences between Thornthwaite's potential evapo—transpiration and computed soil—moisture depletion. More realistic functions are used for soil—moisture depletion on specific soil types than have been customary. These functions related daily rates of depletion to characteristics of soil—moisture tension. Separate functions account for surface soil wetting and drying processes following rain and during dry periods. Two methods of summarizing the day—to—day distribution of moisture stress are illustrated. One utilizes directly accumulated stress values during such logical growth intervals as periods of leaf flushing or bud setting. In an example of a regression of red pine shoot growth on water deficits, 72% of the variation in annual growth was accounted for by moisture stress during certain periods of both previous and current growing seasons. The second method computes moisture stress and weather variables as functions of time over two growing seasons and utilizes the coefficients of orthogonal polynomials as independent variables in regressions of growth. In an example of western white pine basal area growth utilizing this latter method, moisture stress accounted for a 28% reduction in the variance of growth remaining after the effects of temperature and precipitation per se had been removed. The complete model accounted for 78% of the total variation.