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Keyword: models

Reply to Cruz and Alexander: Comments on “Evaluating Crown Fire Rate of Spread Predictions from Physics-Based Models"

Publications Posted on: June 14, 2019
We have read Cruz and Alexander’s comments regarding our manuscript titled ‘‘Evaluating Crown Fire Rate of Spread Predictions from Physics-Based Models’’ [1] and appreciate the opportunity to respond to their comments. In our original manuscript [1], we presented an evaluation of crown fire rate of spread predictions from two physics-based wildland fire behavior models: FIRETEC and the Wildland Urban Interface Fire Dynamics Simulator (WFDS).

Transferability of lidar-derived basal area and stem density models within a northern Idaho ecoregion

Publications Posted on: December 14, 2018
A patchwork of disjunct lidar collections is rapidly developing across the USA, often acquired with different acquisition goals and parameters and without field data for forest inventory. Airborne lidar and coincident field data have been used to estimate forest attributes across individual lidar extents, where forest measurements are collected using project-specific inventory designs.

National forest climate change maps: your guide to the future

Projects Posted on: April 17, 2017
The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans.  The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation, air temperature, snow (including April 1 snow-water equivalent (SWE) and snow residence time), and stream flow.

Potential postwildfire debris-flow hazards - A prewildfire evaluation for the Jemez Mountains, north-central New Mexico

Publications Posted on: August 16, 2016
Wildfire can substantially increase the probability of debris flows, a potentially hazardous and destructive form of mass wasting, in landscapes that have otherwise been stable throughout recent history.

Resistance-surface-based wildlife conservation connectivity modeling: Summary of efforts in the United States and guide for practitioners

Publications Posted on: June 05, 2015
Resistance-surface-based connectivity modeling has become a widespread tool for conservation planning. The current ease with which connectivity models can be created, however, masks the numerous untested assumptions underlying both the rules that produce the resistance surface and the algorithms used to locate low-cost paths across the target landscape.

A mathematical model of salmonid spawning habitat

Publications Posted on: May 14, 2015
A simulation model [Salmonid Spawning Analysis Model (SSAM)I was developed as a management tool to evaluate the relative impacts of stream sediment load and water temperature on salmonid egg survival. The model is usefi.il for estimating acceptable sediment loads to spawning habitat that may result from upland development, such as logging and agriculture.

Understory-overstory relationships in ponderosa pine forests, Black Hills, South Dakota

Publications Posted on: May 07, 2015
Under-story-overstory relationships were examined over 7 different growing stock levels(GSLs) of 2 size classes(saplings,8-10 cm d.b.h. and poles, 15-18 cm d.b.h.) of ponderosa pine (Pinus ponderosa) in the Black Hills, South Dakota. Generally, production of graminoids, forbs, and shrubs was similar between sapling and pole stands. Trends among GSLs were also similar between these tree size classes.

The science and opportunity of wildfire risk assessment (Chapter 6)

Publications Posted on: October 01, 2012
Wildfire management within the United States continues to increase in complexity, as the converging drivers of (1) increased development into fire-prone areas, (2) accumulated fuels from historic management practices, and (3) climate change potentially magnify threats to social and ecological values (Bruins et al., 2010; Gude et al., 2008; Littell et al., 2009).

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