Modeling individual tree mortality for Austrian forest species

Individual tree mortality models were developed for the six major forest sp ecies of Austria: Norway spruce (Picea abies), white fir (Abies alba), Euro pean larch (Larix decidua), Scots pine (Pinus sylvestris), European beech ( Fagus silvatica), and oak (Quercus spp.); a joint model for the remaining b roadleaf species was also developed. Data came from 5-year remeasurements o f the permanent plot network of the Austrian National Forest Inventory. Par ameters of the logistic equation were estimated using maximum likelihood me thods. For all species, we found the hyperbolic transformation of diameter (D-1) to be highly significant in predicting the high mortality rates for s mall diameter trees and decreasing mortality rates for larger diameters. Fo r spruce, a quadratic transformation in D was needed to accurately model th e increase in mortality observed for large, low-vigor trees with diameter > 70 cm, which resulted in a U-shaped distribution. Crown ratio was also cons istently significant, except for oak. We likewise found basal-area-in-large r-trees (BAL) to be a highly significant predictor of mortality rate for al l species except fir and oak. Predicted mortality rate increases as the bas al area in larger trees increases and as crown ratio decreases. The resulti ng logistic mortality model had the same general form for all species, with the signs of all parameters conforming to expectations. In general, chi-sq uare statistics indicate that the most important variable is D-L, th, secon d most important is crown ratio, and the third most important predictor is BAL. The relative importance of crown ratio appears to be greater for shade tolerant species (fir, beech, spruce) than for shade intolerant species (l arch, Scots pine, oak). Examination of graphs of observed vs. predicted mor tality rates reveals that the species-specific mortality models are all wel l behaved, and match the observed mortality rates quite well. The D-1 trans formation is flexible, as can be seen by comparing rather different mortali ty rates of larch and Scots pine. Predicted and observedmortality rates wit h respect to crown ratio are quite close to the observed mortality rates fo r all but the smallest crown ratios (CR<20%), a class with very few observa tions. Finally, the logistic mortality models passed a validation test on i ndependent data not used in parameter estimation. The key ingredient for ob taining a good mortality model is a data set that is both large and represe ntative of the population under study, and the Austrian National Forest Inv entory data satisfy both requirements. (C) 1999 Published by Elsevier Scien ce B.V. All rights reserved.