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Keyword: forest cover

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.  

The extent of forest in dryland biomes

Publications Posted on: September 27, 2017
Dryland biomes cover two-fifths of Earth’s land surface, but their forest area is poorly known. Here, we report an estimate of global forest extent in dryland biomes, based on analyzing more than 210,000 0.5-hectare sample plots through a photo-interpretation approach using large databases of satellite imagery at (i) very high spatial resolution and (ii) very high temporal resolution, which are available through the Google Earth platform.

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.

Effects of forest cover on drinking water treatment costs

Publications Posted on: November 17, 2016
This paper explores the relationship between forest cover and drinking water treatment costs using results from a 2014 survey by the American Water Works Association (AWWA) that targeted utilities in forested ecoregions in the United States. On the basis of the data collected, there is a negative relationship between forest cover and turbidity, i.e. as forest cover increased, turbidity decreased.

Fire control planning in the Northern Rocky Mountain region

Publications Posted on: August 12, 2015
In the northern Rocky Mountain region a high degree of protection from fire is necessary to perpetuate forest yields and communities industrially dependent upon them. On rugged and inaccessible areas a green, healthy forest cover is needed for recreation, erosion control, and regulation of water resources. Immense conflagrations continue to challenge the forester.

Forest canopy effects on snow accumulation and ablation: an integrative review of empirical results

Publications Posted on: July 28, 2015
The past century has seen significant research comparing snow accumulation and ablation in forested and open sites. In this review we compile and standardize the results of previous empirical studies to generate statistical relations between changes in forest cover and the associated changes in snow accumulation and ablation rate.

Simulating long-term landcover change and water yield dynamics in a forested, snow-dominated Rocky Mountain watershed

Publications Posted on: July 28, 2015
Changes in the extent, composition, and configuration of forest cover over time due to succession or disturbance processes can result in measurable changes in streamflow and water yield. Removal of forest cover generally increases streamflow due to reduced canopy interception and evapotranspiration.

Initial turnover rates of two standard wood substrates following land-use change in subalpine ecosystems in the Swiss Alps

Publications Posted on: July 08, 2015
Forest cover has increased in mountainous areas of Europe over the past decades because of the abandonment of agricultural areas (land-use change). For this reason, understanding how land-use change affects carbon (C) source-sink strength is of great importance. However, most studies have assessed mountainous systems C stocks, and less is known about C turnover rates, especially of “fresh” organic material (OM).

Effects of forest cover and environmental variables on snow accumulation and melt

Publications Posted on: September 06, 2012
The goal of this study was to assess the effects of topography and forest cover resulting from different treatments on snow accumulation and melt in small watersheds in the western United States.

Kalman filter for statistical monitoring of forest cover across sub-continental regions [Symposium]

Publications Posted on: August 03, 2009
The Kalman filter is a generalization of the composite estimator. The univariate composite estimate combines 2 prior estimates of population parameter with a weighted average where the scalar weight is inversely proportional to the variances. The composite estimator is a minimum variance estimator that requires no distributional assumptions other than estimates of the first 2 moments.