Because simple seed- or breeding-zone guidelines are inadequate for controlling the risk of maladaptation to environmental stresses, we are developing operational procedures to assess the risk of frost kill to genetically improved families of Douglas-fir (Pseudotsuga menziesii Mirb. Franco). We have (1) determined the time course of cold hardening and dehardening of nursery-grown Douglas-fir seedlings over four winters, by means of controlled freezing tests, (2) fitted curves to relationships between temperature sum and both fall cold hardening and spring dehardening, (3) applied the temperature sum models to daily temperature records of 80 weather stations to estimate frequency of years with significant frost kill at those stations, (4) interpolated frost kill probabilities for tree farms, using a thin plate spline procedure with elevation, latitude and longitude as variables, and (5) prepared a coarse-scale frost risk map from the resulting grid point estimates. With the exception of a few high-elevation stations, the most damaging frost at any station in any year occurred in either the fall (October and November) or late spring (mid-April to mid-May). In general, damaging spring frosts were two to three times more frequent than fall frosts, and areas in Oregon were at greater risk than areas at similar elevations and longitudes further north. The spline surface was less precise for predicting spring frost risk than fall frost risk.

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Abstract:Using lidar for large-scale forest management can improve operational and management decisions. Using multi-temporal lidar sampling and remeasured field inventory data collected from 78 plots in the Panther Creek Watershed, Oregon, USA, we evaluated the performance of different fixed and mixed models in estimating change in aboveground biomass (∆AGB) and cubic volume including top and stump (∆CVTS) over a five-year period. Actual values of CVTS and AGB were obtained using newly fitted volume and biomass equations or the equations used by the Pacific Northwest unit of the Forest Inventory and Analysis program. Estimates of change based on fixed and mixed-effect linear models were more accurate than change estimates based on differences in LIDAR-based estimates. This may have been due to the compounding of errors in LIDAR-based estimates over the two time periods. Models used to predict volume and biomass at a given time were, however, more precise than the models used to predict change. Models used to estimate ∆CVTS were not as accurate as the models employed to estimate ∆AGB. Final models had cross-validation root mean squared errors as low as 40.90% for ∆AGB and 54.36% for ∆CVTS.

A system of three conditioned equations is used to describe whole-tree taper for western hemlock (Tsugaheterophylla (Raf.) Sarg.). Geometric attributes of the system are predicted as empirical functions of DBH and total height. This allows for a wide range of predicted stem profiles without risk of illogical profile predictions for any tree size. Fitting is by multivariate nonlinear regression, where the dependent variables are inside-bark diameters at 12 points on each sample tree. Residual analysis shows that the system does mimic the data in the prediction of different profiles for various combinations of DBH and height. The resultant system can produce analytically tractable estimates of volume. The goodness of fit of the compatible volume estimator is comparable with that of the best whole-tree volume equations. A product of the analysis is a multivariate description of the error distribution; this could have application in the development of profile prediction systems that utilize diameter measurements at multiple heights.

The problem of fitting height–diameter curves for repeated measurements on growth plots is addressed. The context of the problem is fitting historical data with varying sampling protocols and varying measurement accuracy. A key consideration is obtaining good estimates of top height and top-height increment. A particular model and objective function for fitting are presented. The model has two parameters for each measurement and one common parameter; limited crossovers in the height–diameter curves for the various measurements are allowed. The objective function minimizes errors in predicted height and in predicted change in height. The programming is described, and the availability of code is announced. Examples show both the strengths and weaknesses of this approach.