Treesearch

Logging utilization research results have informed land managers of changes in utilization of forest growing stock for more than 40 years. The logging utilization residue ratio- growing stock residue volume/mill delivered volume- can be applied to historic or projected timber harvest volumes to predict woody residue volumes at varied spatial scales. Researchers at the University of Montana’s Bureau of Business and Economic Research and USFS Southern Research Station are investigating variability in residue ratios across Montana, Idaho, Oregon, and Washington. This project has presented...

Projections of Alaska timber products output, the derived demand for logs, lumber, residues, and niche products, and timber harvest by owner are developed by using a trend-based analysis. This is the fifth such analysis performed since 1990 to assist planners in meeting statutory requirements for estimating planning cycle demand for timber from the Tongass National Forest. Results reflect the consequences of recent changes in the Alaska forest sector and trends in markets for Alaska products. Demand for Alaska national forest timber currently depends on markets for sawn wood and exports of...

The National Forest System (NFS) Pacific Northwest Region (R6) has been flying LiDAR on a per project basis. Additional field data was also collected in situ to many of these LiDAR projects to aid in the development of predictive models and estimate values which are unattainable through LiDAR data alone (e.g. species composition, tree volume, and downed woody material). Until now, the protocols for collecting vegetation field data within LiDAR project areas have varied from project to project, leading to the inability to share, use, or analyze data across multiple project areas. The R6...

DNR’s forest inventory group has completed its first version of a new remote-sensing based forest inventory system covering 1.4 million acres of DNR forest lands. We use a combination of field plots, lidar, NAIP, and a NAIP-derived canopy surface DSM. Given that height drives many key inventory variables (e.g. height, volume, biomass, carbon), remote-sensing derived height information provides a powerful tool to make fine scale inference about height related forest attributes. Predictions can also be aggregated to sub-stand, stand, or strata levels. Remote-sensing derived forest attributes...

Forested ecosystems are shaped by climate, soil and biotic interactions, resulting in constrained spatial distribution of species and biomes. Tolerance traits of species determine their fundamental ecological niche, while biotic interactions narrow tree distributions to the realized niche. In particular, shade, drought and waterlogging tolerances have been well-characterized at the species level in the Northern hemisphere tree species. Species distribution models explore fundamental niches and current geographic distributions with respect to environmental factors, but their ability to...

The state of Oregon recently invested in exploring options for increasing the extent of forest restoration activity. This initiative aims to reduce the incidence, effects, and expense of catastrophic fire events and restore economic stability to rural communities by enhancing the supply of raw materials for wood processing facilities and wood-based, renewable energy producers, particularly in the comparatively xeric, eastern two-thirds of the State. Collaborating with PNW-FIA and Portland State University, the Oregon Department of Forestry evaluated current levels of fire hazard as...

In many forest inventories, statistical models are employed to predict values for attributes that are difficult and/or time-consuming to measure. In some applications, models are applied across a large geographic area, which assumes the relationship between the response variable and predictors is ubiquitously invariable within the area. The extent to which this assumption holds for a tree height prediction model was evaluated at regional, ecoprovince, and ecosection spatial scales in the Northeastern United States. Two nonlinear regression models were tested, a spatially-ambiguous model...

Understanding changes in land use and land cover over space and time provides an important means to evaluate complex interactions between human and biophysical systems, to project future conditions, and to design mitigation and adaptive management strategies. Assessing and monitoring landscape change is evolving into a foundational element of climate change adaptation, ecological restoration, and resource sustainability. Landscape change data are core to Forest Service functions including: land management planning, restoration analysis, carbon accounting, greenhouse gas emission reporting,...

The USDA Forest Service is evaluating the status of current landscape change maps and assessing gaps in their information content. These activities have been occurring under the auspices of the Landscape Change Monitoring System (LCMS) project, which is a joint effort between USFS Research, USFS Remote Sensing Applications Center (RSAC), USGS Earth Resources Observation and Science (EROS) Center, and academic partners. One of the early needs identified was a system that facilitated the visual comparison of several change maps in a common visualization framework. The application presented...

Analysis of remeasurement data from 1079 Forest Inventory and Analysis (FIA) plots revealed multi-scale change occurring in the temperate rainforests of southeast Alaska. In the western half of the region, including Prince William Sound, aboveground live tree biomass and carbon are increasing at a rate of 8 ( ± 2 ) percent per decade, driven by an increase in Sitka spruce. In the Alexander Archipelago, western red cedar is increasing, as is overall biomass on gentler slopes and in higher latitudes. These increases, which occurred during a warmer period of the Pacific Decadal Oscillation,...