The amount and variability of living and dead wood in a forest stand are important indicators of forest biodiversity, as it relates to structural heterogeneity and habitat availability. In this study, we investigate whether light detection and ranging (lidar) can be used to estimate the distribution of standing dead tree classes within forests. Twenty-two field plots were established in which each stem (DBH >10 cm) was assigned to a wildlife tree (WT) class. For each plot, a suite of lidar-derived predictor variables were extracted. Ordinal regression using a negative log–log link function was then employed to predict the cumulative proportions of stems within the WT classes. Results indicated that the coefficient of variation of the lidar height data was the best predictor variable (χ2 = 106.11, p < 0.00; Wald = 4.83, p = 0.028). The derived relationships allowed for the prediction of the cumulative proportion of stems within WT classes (r = 0.90, RMSE = 6.0%) and the proportion of dead stems within forest plots (r = 0.61, RMSE = 16.8%). Our research demonstrates the capacity of lidar remote sensing to estimate the relative abundances of standing living and dead trees in forest stands and its ability to characterize vegetation structure across large spatial extents.

The ratio of live crown length to tree height (crown ratio; CR) is often used as an important predictor variable for tree level growth equations, particularly for multi-species and multi-layered stands. Also, CR indicates tree vigour and can be an important habitat variable. Measurement of CR for each tree can be time-consuming and difficult to obtain in very dense stands and for very tall trees where the base of live crown is obscured. Models to predict CR from size, competition and site variables were developed for several coniferous and one hardwood tree species growing in multispecies and multi-layered forest stands (complex stands) of southeastern British Columbia. Simple correlations indicated the expected relationships of CR decreasing with increasing height, and with increasing competition. A logistic model form was used to constrain predicted CR values to the interval [0,1]. Also, predictors were divided into tree size, stand competition, and site measures, and the contribution of each set of contributors was examined. For all models, height was an important predictor. The stand competition measure, basal area of larger trees, contributed significantly to predicting CR given that crown competition factor was also included as a measure of competition. Logical trends in CR versus size and competition variable groups were reflected by the models; site variable slightly improved predictions for some species. Much of the variability in CR was not accounted for, indicating that other variables are important for explaining CR changes in these complex stands.Key words: crown ratio, multi-species stands, multi-layered stands, basal area of larger trees RÉSUMÉ Le ratio entre la longueur de la cime vivante par rapport à la hauteur de l'arbre ( ratio de la cime; RC) est souvent utilisé en tant que variable importante de prédiction dans le cas d'équations de la croissance des arbres, spécialement pour les peuplements composés de nombreuses espèces et présentant plusieurs étages. De plus, le RC indique la vigueur de l'arbre et peut être une variable importante de l'habitat. La mesure du RC pour chaque arbre peut prendre beaucoup de temps et être difficile à obtenir dans des peuplements très denses et dans le cas d'arbres très grands pour lesquels la base de la cime vivante se retrouve dans l'ombre. Les modèles de prédiction du RC à partir des variables de diamètre, de compétition et de station ont été élaborées pour diverses espèces résineuses et pour une espèce feuillue retrouvées dans des peuplements composés de nombreuses espèces et présentant plusieurs étages (peuplements complexes) du sud-est de la Colombie-Britannique. Des corrélations simples ont démontré tel que prévu des relations de RC en décroissance avec l'augmentation de la hauteur et de l'augmentation de la compétition. Une forme de modèle logistique a été utilisée pour contraindre les valeurs prévues de RC selon un intervalle de [0,1]. De plus, les variables de prédiction ont été divisées selon le diamètre de l'arbre, la compétition au sein du ...

Summary1. We used replicated, repeated-measures data to examine the spatio-temporal structure of multistoried, multi-aged interior Douglas fir (Pseudotsuga menziesii var glauca (Mirb.) Franco) stands growing on dry sites under more than 50 years of fire protection. Along with the univariate and bivariate Ripley's K and related functions, we used a random coefficients mixed model to investigate the variation in these functions over replicates and time. 2. The spatio-temporal analyses revealed that trees greater than 1.3 m in height were clustered over space, and clustering was more evident for small trees (i.e. diameter at breast height (d.b.h.) £ 7.0 cm). 3. Bivariate functions indicated that small trees were spatially aggregated with large trees, indicating higher germination success and early survival near large trees. For these dry sites, moisture is more limiting than light and large trees provide moister microsites. 4. Dead trees were clustered, more commonly smaller in size and aggregated near large trees, indicating competition for moisture. 5. For the 16-year period of the study, there was very little evidence that the spatio-temporal patterns changed from a clustered to a more regular arrangement over time, unlike evidence from studies in other forest types. 6. Using the random coefficients mixed model approach, the majority of spatio-temporal variation was due to differences among replicates, with little variation over time. 7. Under fire protection, interior Douglas fir stands on dry sites might be expected to have lower mortality but any increase in density will be limited by moisture availability. Since interior Douglas fir is moderately shade-tolerant, this may result in an approach to a steady state of regeneration and death over the long term. 8. Synthesis. Spatio-temporal analysis using replicated, repeated-measures data, including a random coeffcieints mixed model approach, gave useful insights into mortality and recruitment in multi-storied and multi-aged stands. Similar patterns might be expected in other naturally occurring multi-storied and multi-aged stands. The use of replicated, repeated-measures data rather than chronosequence data allows for the examination of true changes in spatial patterns over time.

The inability to obtain sufficient numbers of naturally regenerated trees following partial harvests of some Mediterranean Basin managed forests has prompted the need to critically assess common silvicultural practices. In this study, we examined Scots pine ( Pinus sylvestris L.) regeneration patterns under two shelterwood systems using a multiscale framework. The uniform shelterwood (US) system includes heavier and less frequent timber extractions than the group shelterwood (GS) system. Removal of competing vegetation to expose mineral soil (soil preparation) is sometimes used for US but is not commonly needed in GS. A generalized linear model was used to predict regeneration density for each shelterwood system using environmental variables at microsite- and forest-level scales, medium-scale overstory tree characteristics, and spatial metrics that represent a range of spatial scales. Although US had a higher mean regeneration density, GS had a wider range of regeneration ages. The results derived from this study suggest that ground-level disturbance to break up the herb or organic layer may be required for regeneration establishment. This may occur during repeated partial harvests; otherwise, soil preparation may be required. Overall, this multiscale framework approach resulted in improved predictions and a better understanding of regeneration processes.