Treesearch

This paper explores the information FIA data can produce regarding forest types that were not sampled and develops the equations necessary to define the upper confidence bounds on not-sampled forest types. The problem is reduced to a Bernoulli variable. This simplification allows the upper confidence bounds to be calculated based on Cochran (1977). Examples are provided that demonstrate how the resultant equations are relevant to creating mid-level vegetation maps by assisting in the development of statistically defensible map units.

Climate information frequently is included in geospatial modeling efforts to improve the predictive capability of other data sources. The selection of an appropriate climate data source requires consideration given the number of choices available. With regard to climate data, there are a variety of parameters (e.g., temperature, humidity, precipitation), time intervals (e.g., 30- year normal, seasonal average), and summary statistics (e.g., mean, minimum) which can be selected. In this study, we propose a technique for evaluating the combination of climate parameters that are most closely...

In 2006, the Bureau of Land Management (BLM) contracted with the Forest Service Forest Inventory and Analysis Program (FIA) to assist in the preparation of a report specific to all forest lands under the administration of the BLM. The BLM requested that the FIA provide information on the extent and general conditions of BLM- managed forests and woodlands, within certain statistical reliability parameters. The report focused on the 33 million acres of forest land managed by the BLM outside of Alaska by using data gathered from more than 2,500 FIA plots. The analysis included information on...

Changes in tree species distributions are a potential impact of climate change on forest ecosystems. The examination of tree species shifts in forests of the eastern United States largely has been limited to modeling activities with little empirical analysis of long-term forest inventory datasets. The goal of this study was to compare historic and current spatial distributions of tree species for sets of northern and southern tree species in the eastern United States using regionwide forest inventories. Based on the results of this study, no conclusions could be drawn about tree migration...

Forest genetic sustainability is an important component of forest health because genetic diversity and evolutionary processes allow for the adaptation of species and for the maintenance of ecosystem functionality and resilience. Phylogenetic community analyses, a set of new statistical methods for describing the evolutionary relationships among species, offer an innovative approach for assessing the health of forest communities from an evolutionary perspective. Forest Inventory and Analysis data are ideal for conducting phylogenetic community analyses for forest tree species at broad...

Plot data from the USFS FIA program could be combined with terrain variables to attempt to explain how terrain characteristics influence forest growth, species composition, productivity, fire behavior, wildlife habitat, and other phenomena. While some types of analyses using FIA data have been shown to be insensitive to precision of plot locations, it has been suggested that terrain-based models may require the use of precise plot coordinates. This study compares results obtained from a variety of terrain-based analyses conducted in the Blue Ridge of North Carolina using both precise and...

The Interior-West, Forest Inventory and Analysis (FIA), Nevada Photo-Based Inventory Pilot (NPIP), launched in 2004, involved acquisition, processing, and interpretation of large scale aerial photographs on a subset of FIA plots (both forest and nonforest) throughout the state of Nevada. Two objectives of the pilot were to use the interpreted photo data to enhance satellite-based mapping capabilities by providing training information at a moderate scale, and to refine definitions of forest land by facilitating explorations of forest land definition changes. This study examines the usefulnes...

The Forest Inventory and Analysis (FIA) program attempts to inventory all forested lands throughout the United States. Each of the four FIA units has developed a process to minimize inventory costs by refraining from visiting those plots in the national inventory grid that are undoubtedly nonforest. We refer to this process as pre-field operations. Until recently, the pre-field process of differentiating forest from nonforest plots received very little attention or scrutiny. No national pre-field manual currently exists, nor does any other form of formal documentation of the pre-field...

Tree canopy cover is an important stand characteristic that affects understory light, fuel moisture, decomposition rates, wind speed, and wildlife habitat. Canopy cover also is a component of most definitions of forest land used by US and international agencies. The USDA Forest Service Forest Inventory and Analysis (FIA) Program currently does not provide a national standard measurement of tree canopy cover, and most regional FIA units do not measure canopy cover in the field.This paper describes a model for predicting canopy cover of FIA plots by mapping the locations of trees ≥ 5.0 in....

Historically, Forest Inventory and Analysis (FIA) has processed field inventory data at the county level and county estimates of land area were constrained to equal those reported by the Census Bureau. Currently, the Southern Research Station FIA unit processes field inventory data at the survey unit level (groups of counties with similar ecological characteristics). In short, the estimation unit has changed from an individual county to groups of counties. However, changing the estimation unit to a survey unit does not constrain the total area of each county when expansion factors are...