Modeling Tree Growth Potential Based on Effective Evapotranspiration
Abstract:Annual tree growth potential is assessed by modeling effective evapotranspiration and taken as an index expressing interaction between atmospheric energy, tential evapotranspiration (PET), and soil moisture supply. The model has been calibrated for 11 forest stands of two evergreen species, Scots pine (Pinus Sylvestris) and Corsican pine (Pinus Nigra), located in England. Four calibrated effective evapotranspiration values (EET) together with a simple climatic index (PET/R), which expresses the balance between potential evapotranspiration and rainfall, were subsequently multiplied by tree age to incorporate the physiological efficiency of trees. The derived potential growth indexes (PGIs) were comparatively examined with actual annual tree growth data for a period of 30 to 40 years. Regression analysis was carried out in evaluating the model performance and the applicability of the model to predict environmental potential. All four predictions based on assessment of effective evapotranspiration were positively correlated with annual tree growth, having coefficients of determination above 0.40, and often reaching 0.70, with significance at the 0.001 level of probability. For. Sci. 34(4):864-881.
Document Type: Journal Article
Affiliations: Department of Geography, The University of Peradeniya, Peradeniya, Sri Lanka
Publication date: 1988-12-01
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- Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
Forest Science is published bimonthly in February, April, June, August, October, and December.
2015 Impact Factor: 1.702
Ranking: 16 of 66 in forestry
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