Treesearch

An attempt was made to model diameter distributions of aspen (Populus spp) stands. The aspen (1,020,150 acres) cover type has the greatest acreage on DNR lands and it contains a variety of hardwood and softwood species. Aspen is a valuable pulpwood species, annually comprising around 50 percent of total timber harvest on DNR lands. Modeling distributions of this cover type has been minimal; stands often contain a variety of tree sizes and species, making modeling difficult, particularly given a disproportionate amount of smaller trees. For this analysis, a three-parameter Weibull-based...

For Minnesota, the only data available to conduct regional or state-wide level assessments across all ownerships is the Forest Inventory and Analysis Program (FIA). Some of the many alternatives available to estimate regional changes in standing volume are referred to here as 1.) FIA alternative, 2.) a commonly applied growth and yield system referred to as Walters and Ek, 3.) a calibrated Walters and Ek alternative, 4.) a different calibrated Walters and Ek alternative, and 5.) Forest Vegetation Simulator (FVS) estimates. The purpose of this study is to quantify the ability of these...

Understanding how climate affects tree growth is essential for assessing climate change impacts on forests, but is complicated by the effects of competition, which strongly influences growth and could alter how forests respond to climate change. We characterized the joint effects of climate and competition on diameter growth in the mountain forests of Mount Rainier National Park, Washington State, USA using long-term (32-year) forest monitoring data from permanent sample plots in mature and old-growth stands. To analyze the data, we adapted the diameter growth function from ORGANON (a...

Increasingly, random forest models are used in predictive mapping of forest attributes. Traditional random forests output the mean prediction from the random trees. Quantile regression forests (QRF) is an extension of random forests developed by Nicolai Meinshausen that provides non-parametric estimates of the median predicted value as well as prediction quantiles. It therefore allows spatially explicit non-parametric estimates of model uncertainty. Here, we illustrate how to use QRF in predictive mapping of continuous forest attributes such as tree canopy cover and biomass. Using FIA plot...

Since 1971, South Korea has implemented national forest inventory (NFI) in pursuance of understanding current state and change trend of national forest resources. NFI1 (1971~1975), NFI2 (1978~1981), NFI3 (1986~1992) and NFI4 (1996~2005) were implemented in order to produce national forest resources statistics. However, since the early 1990s, international conventions and organizations started to require diverse forest information for the sustainable forest management and periodic monitoring of forest resources. Following these requirement, South Korea reformed total national forest...

The Pacific Northwest (PNW) Research Station’s Forest Inventory and Analysis (FIA) program of the USDA Forest Service monitors and reports on the status and trends of the Pacific Island’s forest resources and ecosystem services. Since 2001 the FIA program has partnered with State and Private Forestry’s, Region 5 and the local governments in the U.S. Affiliated Western Pacific Islands to implement a nationally-standardized plot sampling design on a periodic basis. Permanent monitoring plots are measured on a 10 year periodic cycle across the island nations of American Samoa, Guam, Palau,...

Floods are the most frequent natural disaster, causing more loss of life and property than any other in the USA. Floods also strongly influence the structure and function of watersheds, stream channels, and aquatic ecosystems. The Pacific Northwest is particularly vulnerable to climatically driven changes in flood frequency and magnitude, because snowpacks that strongly influence flood generation are near the freezing point and thus sensitive to small changes in temperature. To improve predictions of future flooding potential and inform strategies to adapt to these changes, we mapped the...

In 2014 Urban Forest Inventory and Analysis (Urban-FIA) was implemented for the first time ever in Austin, Texas. Work was accelerated and a full complement of plots in the city was measured in six months. In 2015 results are to be released in an FIA report and data made available in a publicly accessible database. In this presentation we discuss the importance of seamless rural to urban monitoring in a state where 85 percent of the population lives in urban areas. We highlight major findings from the Austin analysis and report. We discuss how the data strengthen urban forest management...

In this presentation we describe the urban forest inventory database (U-FIADB) and demonstrate how to use the database to produce population estimates. Examples from the recently completed City of Austin inventory will be used to demonstrate the capabilities of the database. We will identify several features of U-FIADB that are different from the FIA database (FIADB) and discuss whether the differences are out of necessity or by design. Urban forest inventory is a melding of two different inventory systems and approaches, FIA and i-Tree, both of which are well-established and successful in...

In 2002, Wisconsin was part of two pilot projects in cooperation with the US Forest Service. The first was a street tree assessment, and the second was an urban FIA project. The data generated by these pilots changed the way that Wisconsin DNRs’ Urban Forestry Program conducts its business. Although there have been several urban FIA pilot projects throughout the U.S., in 2012, Wisconsin became the first state where those pilot FIA plots were re-measured. The results of this re-measurement demonstrate how urban foresters in Wisconsin have altered their tactics in recent years due to several...