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Keyword: logistic regression

Random forests for classification in ecology

Publications Posted on: September 10, 2019
Classification procedures are some of the most widely used statistical methods in ecology. Random forests (RF) is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology.

Improved predictions of deforestation in Borneo

Science Spotlights Posted on: October 12, 2017
A collaborative team, led by RMRS Research Ecologist Samuel Cushman, has produced a substantial breakthrough in advancing predictive modeling of drivers and patterns of deforestation. The method combines multi-scale optimization with machine-learning predictive modeling to identify the drivers of deforestation and map relative future deforestation risk.  

Predicting post-fire tree mortality for 12 western US conifers using the First-Order Fire Effects Model (FOFEM)

Publications Posted on: October 04, 2017
Accurate prediction of fire-caused tree mortality is critical for making sound land management decisions such as developing burning prescriptions and post-fire management guidelines. To improve efforts to predict post-fire tree mortality, we developed 3-year post-fire mortality models for 12 Western conifer species - white fir (Abies concolor [Gord. & Glend.] Lindl. ex Hildebr.), red fir (Abies magnifica A.

Predicting post-fire tree mortality for 14 conifers in the Pacific Northwest, USA: Model evaluation, development, and thresholds

Publications Posted on: June 08, 2017
Fire is a driving force in the North American landscape and predicting post-fire tree mortality is vital to land management. Post-fire tree mortality can have substantial economic and social impacts, and natural resource managers need reliable predictive methods to anticipate potential mortality following fire events.

Multiple-scale prediction of forest loss risk across Borneo

Publications Posted on: May 24, 2017
Context: The forests of Borneo have among the highest biodiversity and also the highest forest loss rates on the planet.

Mountain pine beetle attack in ponderosa pine: Comparing methods for rating susceptibility

Publications Posted on: May 12, 2016
Two empirical methods for rating susceptibility of mountain pine beetle attack in ponderosa pine were evaluated. The methods were compared to stand data modeled to objectively rate each sampled stand for susceptibly to bark-beetle attack.

Habitat use by mountain quail in Northern California

Publications Posted on: May 12, 2016
We studied habitat use by Mountain Quail (Oreortyx pictus) at four sites in northern California. Vegetative cover types (macrohabitats) were used in proportion to availability. Significant microhabitat variables which distinguished used from available microhabitat structure included proximity to water and tall, dense shrubs.

Seasonal resource selection of Canada lynx in managed forests of the northern Rocky Mountains

Publications Posted on: January 19, 2016
We investigated seasonal patterns in resource selection of Canada lynx (Lynx canadensis) in the northern Rockies (western MT, USA) from 1998 to 2002 based on backtracking in winter (577 km; 10 M, 7 F) and radiotelemetry (630 locations; 16 M, 11 F) in summer. During winter, lynx preferentially foraged in mature, multilayer forests with Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa) in the overstory and midstory.

Predicting relative species composition within mixed conifer forest pixels using zero‐inflated models and Landsat imagery

Publications Posted on: December 16, 2015
Ecological and land management applications would often benefit from maps of relative canopy cover of each species present within a pixel, instead of traditional remote-sensing based maps of either dominant species or percent canopy cover without regard to species composition.

The relative impacts of vegetation, topography and spatial arrangement on building loss to wildfires in case studies of California and Colorado

Publications Posted on: August 21, 2015
Wildfires destroy thousands of buildings every year in the wildland urban interface. However, fire typically only destroys a fraction of the buildings within a given fire perimeter, suggesting more could be done to mitigate risk if we understood how to configure residential landscapes so that both people and buildings could survive fire.