Regional Variability of the Romanian Main Tree Species Growth Using National Forest Inventory Increment Cores

In many countries, National Forest Inventory (NFI) data is used to assess the variability of forest growth across the country. The identification of areas with similar growths provides the foundation for development of regional models. The objective of the present study is to identify areas with similar diameter and basal area growth using increment cores acquired by the NFI for the three main Romanian species: Norway spruce (Picea abies L. Karst), European beech (Fagus sylvatica L.), and Sessile oak (Quercus petraea (Matt.) Liebl.). We used 6536 increment cores with ages less than 100 years, a total of 427,635 rings. The country was divided in 21 non-overlapping ecoregions based on geomorphology, soil, geology and spatial contiguousness. Mixed models and multivariate analyses were used to assess the differences in annual dimeter at breast height and basal area growth among ecoregions. Irrespective of the species, the mixed models analysis revealed significant differences in growth between the ecoregions. However, some ecoregions were similar in terms of growth and could be aggregated. Multivariate analysis reinforced the difference between ecoregions and showed no temporal grouping for spruce and beech. Sessile oak growth was separated not only by ecoregions, but also by time, with some ecoregions being more prone to draught. Our study showed that countries of median size, such as Romania, could exhibit significant spatial differences in forest growth. Therefore, countrywide growth models incorporate too much variability to be considered operationally feasible. Furthermore, it is difficult to justify the current growth and yield models as a legal binding planning tool.Forestry, Faculty ofNon UBCReviewedFacult

Deterministic Models of Growth and Mortality for Jack Pine in Boreal Forests of Western Canada

We developed individual tree deterministic growth and mortality models for jack pine (Pinus banksiana Lamb.) using data from permanent sample plots in Alberta, Saskatchewan and Manitoba, Canada. Height and diameter increment equations were fitted using nonlinear mixed effects models. Logistic mixed models were used to estimate jack pine survival probability based on tree and stand characteristics. The resulting models showed that (1) jack pine growth is significantly influenced by competition; (2) competitive effects differ between species groups; and (3) survival probability is affected by tree size and growth, stand composition, and stand density. The estimated coefficients of selected growth and mortality functions were implemented into the Mixedwood Growth Model (MGM) and the simulated predictions were evaluated against independently measured data. The validation showed that the MGM can effectively model jack pine trees and stands, providing support for its use in management planning