Treesearch

The Ring Profiler was developed to examine the cross-sectional morphology of wood tracheids in a 12.5-mm core sample. The instrument integrates a specially designed staging apparatus with an optical imaging system to obtain high-contrast, high-resolution images containing about 200-500 tracheids. These images are further enhanced and analyzed to extract tracheid cross-sectional properties such as shape, double-wall thickness, and lumen area. Subsequently, localized density can be calculated for specific regions of interest (e.g., earlywood and latewood), as it varies throughout the tree.

Methods for estimating present and future carbon storage in trees and forests rely on measurements or estimates of tree volume or volume growth multiplied by specific gravity. Wood density can vary by tree ring and height in a tree. If data on density by tree ring could be obtained and linked to tree size and stand characteristics, it would be possible to more accurately predict changes in density and weight of tree biomass with projected changes in tree size and stand characteristics. Ring Profiler is a patented method for characterizing the structure of softwood tracheids and their...

New models were presented to understand the relationship between the dominant stem and a whole tree using cumulative, whole-tree mass/volume profiles which are compatible with the current bole taper modeling paradigm. New models were developed from intensive, destructive sampling of 32 trees from a temperate hardwood forest in Michigan. The species in the sample were primarily American beech (Fagus grandifolia Ehrh.) and sugar maple (Acer saccharum Marsh.). The new profile models allowed for both mass and volume of both the dominant stem and branches to be estimated from ground level to...

An update of the Jenkins et al. (2003) biomass estimation equations for North American tree species resulted in 35 generalized equations developed from published equations. These 35 equations, which predict aboveground biomass of individual species grouped according to a taxa classification (based on genus or family and sometimes specific gravity), generally predicted higher biomass than estimates from the U.S. Department of Agriculture, Forest Service Forest Inventory and Analysis Program (FIA). FIA uses a conversion approach called the component ratio method (CRM) (Woodall et al. 2011)...

Standing dead trees are an important component of forest ecosystems. However, reliable estimates of standing dead tree population parameters can be difficult to obtain due to their low abundance and spatial and temporal variation. After 1999, the Forest Inventory and Analysis (FIA) Program began collecting data for standing dead trees at the Phase 2 stage of sampling. However, the estimates have relatively large variations compared to the estimates of live trees. The results represent that EZ-Hurdle method shows better precision than the FIA method for both spatial patterns and densities...

An example of endogenous post-stratification is the use of remote sensing data with a sample of ground data to build a logistic regression model to predict the probability that a plot is forested and using the predicted probabilities to form categories for post-stratification. An optimized endogenous post-stratified estimator of the proportion of forest has been recently proposed in the literature, but there are no known literature results describing the operating characteristics of this estimator. This study reports the results of a detailed Monte Carlo investigation of the performance of...

Post-stratification is used in survey statistics as a method to improve variance estimates. In traditional post-stratification methods, the variable on which the data is being stratified must be known at the population level. In many cases this is not possible, but it is possible to use a model to predict values using covariates, and then stratify on these predicted values. This method is called endogenous post-stratification estimation (EPSE). In this paper, we investigate methods to automatically select the number of post-strata for EPSE. We do this in the context of models fitted by...

Data from hardwood trees in Michigan were analyzed to investigate how differences in whole-tree form and wood density between trees of different stem diameter relate to residual error in standard-type biomass equations. The results suggested that whole-tree wood density, measured at breast height, explained a significant proportion of residual error in standard-type allometric equations, but whole-tree form factors explained more. However, such form factors are highly variable from tree to tree and may be difficult to predict with any precision from simple tree measurements. Whole-tree...

Biomass models for most commercially important hardwood species in the northern region of the U.S. are often based on data of very limited spatial extent and range of tree characteristics, suggesting uncertain accuracy when applied at regional scales. Also, the current models can have poor predictive ability for the proportions of biomass found in major tree components considered for utilization, namely the merchantable bole, bole tops, tree branches, and foliage. The Forest Inventory and Analysis Program of the U.S. Forest Service is currently undertaking a project to obtain regionally...

Wildfire hazard mitigation and bioenergy harvesting have emerged as forest management priorities throughout the Interior West (IW) of the USA. Regional forest inventory and forecasting applications are therefore increasingly focused on tree biomass, including biomass in traditionally non-merchantable components. Yet accurate biomass equations for the latter components are typically lacking, even for major commercial species. This is because previous assessment efforts have focused on distinct components, have used inconsistent methodologies, or have relied on data with limited spatial or...