Three sets of linear models were developed to predict several forest attributes, using stand-level and single-tree remote sensing (STRS) light detection and ranging (LiDAR) metrics as predictor variables. The first used only area-level metrics (ALM) associated with first-return height distribution, percentage of cover, and canopy transparency. The second alternative included...
Les modèles de prédiction du microclimat pour différentes conditions de station dans les zones riveraines boisées
des cours d’eau de tête de bassin sont peu développés et les procédures d’échantillonnage pour caractériser les gradients
sous-jacents du microclimat riverain sont rares. Nous avons utilisé des données de microclimat riverain collectées le...
Sixteen sampling alternatives were examined for their performance to quantify selected attributes of overstory conifers in riparian areas of western Oregon. Each alternative was examined at eight headwater forest locations based on a 0.52 ha square stem maps. The alternatives were evaluated for selected stand attributes (trees per hectare, basal...
One of the challenges often faced in forestry is the estimation of forest attributes for smaller areas of interest within a larger population. Small-area estimation (SAE) is a set of techniques well suited to estimation of forest attributes for small areas in which the existing sample size is small and...
Selected tree height and diameter functions were evaluated for their predictive abilities for major tree species of southwest Oregon. Two sets of equations were evaluated. The first set included four base equations for estimating height as a function of individual tree diameter, and the remaining 16 equations enhanced the four...
Many growth and yield simulators require a stand table or tree-list to set the initial condition for projections in time. Most similar neighbour (MSN) approaches can be used for estimating stand tables from information commonly available on forest cover maps (e.g. height, volume, per cent canopy cover and species composition)....
Cavity trees contribute to diverse forest structure and wildlife habitat. For a given stand, the size and density of cavity trees indicate its diversity, complexity, and suitability for wildlife habitat. Size and density of cavity trees vary with stand age, density, and structure. Using Forest Inventory and Analysis (FIA) data...
Information on current forest condition is essential to assess and characterize resources and to support resource management and policy decisions. The 1998 Farm Bill mandates the US Forest Service to conduct annual inventories to provide annual updates of each state's forest. In annual inventories, the sample size of I year...
Regional estimation of potential forest productivity is important to diverse applications, including biofuels supply, carbon sequestration, and projections of forest growth. Using PRISM (Parameter-elevation Regressions on Independent Slopes Model) climate and productivity data measured on a grid of 3356 Forest Inventory and Analysis plots in Oregon and Washington, we evaluated...
Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as...