remote sensing

Legacy ID: 
4 499
Publication Title: 

Influence of nonnative and native ungulate biomass and seasonal precipitation on vegetation production in a great basin ecosystem

Authors: 
Zeigenfuss, L.C., K.A. Schoenecker, J.I. Ransom, D.A. Ignizio and T. Mask
Publication Date: 
2014
Parent Publication Title: 
Western North American Naturalist
Publication Type: 
Archive number: 
2014/0089 FORT
States: 

Pub Abstract: 

The negative effects of equid grazers in semiarid ecosystems of the American West have been considered disproportionate to the influence of native ungulates in these systems because of equids’ large body size, hoof shape, and short history on the landscape relative to native ungulates. Tools that can analyze the degree of influence of various ungulate herbivores in an ecosystem and separate effects of ungulates from effects of other variables (climate, anthropomorphic disturbances) can be useful to managers in determining the location of nonnative herbivore impacts and assessing the effect of management actions targeted at different ungulate populations. We used remotely sensed data to determine the influence of native and nonnative ungulates and climate on vegetation productivity at wildlife refuges in Oregon and Nevada. Our findings indicate that ungulate biomass density, particularly equid biomass density, and precipitation in winter and spring had the greatest influence on normalized difference vegetation index (NDVI) values. Our results concur with those of other researchers, who found that drought exacerbated the impacts of ungulate herbivores in arid systems.

Publication Title: 

Forecasting sagebrush ecosystem components and greater sage-grouse habitat for 2050—Capitalizing on 28 years of Landsat satellite imagery and climate data

Authors: 
Homer, C.G., G. Xian, C.L. Aldridge, D.K. Meyer, T.L. Loveland, and M.S. O’Donnell
Publication Date: 
2015
Parent Publication Title: 
Ecological Indicators
Publication Type: 
Archive number: 
2015/0037 FORT
States: 

Pub Abstract: 

Sagebrush (Artemisia spp.) ecosystems constitute the largest single North American shrub ecosystem and provide vital ecological, hydrological, biological, agricultural, and recreational ecosystem services. Disturbances have altered and reduced this ecosystem historically, but climate change may ultimately represent the greatest future risk. Improved ways to quantify, monitor, and predict climate-driven gradual change in this ecosystem is vital to its future management. We examined the annual change of Daymet precipitation (daily gridded climate data) and five remote sensing ecosystem sagebrush vegetation and soil components (bare ground, herbaceous, litter, sagebrush, and shrub) from 1984 to 2011 in southwestern Wyoming. Bare ground displayed an increasing trend in abundance over time, and herbaceous, litter, shrub, and sagebrush showed a decreasing trend. Total precipitation amounts show a downward trend during the same period. We established statistically significant correlations between each sagebrush component and historical precipitation records using a simple least squares linear regression. Using the historical relationship between sagebrush component abundance and precipitation in a linear model, we forecasted the abundance of the sagebrush components in 2050 using Intergovernmental Panel on Climate Change (IPCC) precipitation scenarios A1B and A2. Bare ground was the only component that increased under both future scenarios, with a net increase of 48.98 km2 (1.1%) across the study area under the A1B scenario and 41.15 km2 (0.9%) under the A2 scenario. The remaining components decreased under both future scenarios: litter had the highest net reductions with 49.82 km2 (4.1%) under A1B and 50.8 km2 (4.2%) under A2, and herbaceous had the smallest net reductions with 39.95 km2 (3.8%) under A1B and 40.59 km2 (3.3%) under A2. We applied the 2050 forecast sagebrush component values to contemporary (circa 2006) greater sage-grouse (Centrocercus urophasianus) habitat models to evaluate the effects of potential climate-induced habitat change. Under the 2050 IPCC A1B scenario, 11.6% of currently identified nesting habitat was lost, and 0.002% of new potential habitat was gained, with 4% of summer habitat lost and 0.039% gained. Our results demonstrate the successful ability of remote sensing based sagebrush components, when coupled with precipitation, to forecast future component response using IPCC precipitation scenarios. Our approach also enables future quantification of greater sage-grouse habitat under different precipitation scenarios, and provides additional capability to identify regional precipitation influence on sagebrush component response.

Publication Title: 

Detecting annual and seasonal changes in a sagebrush ecosystem with remote sensing derived continuous fields

Authors: 
Homer, C.G., D.K. Meyer, C.A. Aldridge, and S. Schell
Publication Date: 
2013
Parent Publication Title: 
Journal of Applied Remote Sensing
Publication Type: 
Archive number: 
2013/0105 FORT

Pub Abstract: 
Publication Title: 

Modeling mountain pine beetle disturbance in Glacier National Park using multiple lines of evidence

Authors: 
Assal, T.J., J. Sibold, and R. Reich
Publication Date: 
2013
Updated Date (text): 
2013-09-04
Parent Publication Title: 
Vegetation Dynamics II, Association of American Geographers 2013 Annual Meeting, Los Angeles, CA. April 13, 2013
Publication Type: 
Archive number: 
NONCTR/00400
States: 

Pub Abstract: 
Publication Title: 

Using spatial models with remote sensing to map invasive species distributions: a case study of Tamarix along the Arkansas River, Colorado

Authors: 
Carter, L., P. Evangelista, N. Young, A. West, and C. Jarnevich
Updated Date (text): 
2012-10-05
Parent Publication Title: 
AASPRS 2013 Annual Conference, Confluence by the Bay – A Gathering of Geospatial Insights, Baltimore, Maryland, March 24 – 28, 2013
Publication Type: 
Archive number: 

Pub Abstract: 
Publication Title: 

Utilizing Remote Sensing and GIS to Detect Prairie Dog Colonies

Authors: 
Assal, T.J., and J.A. Lockwood
Publication Date: 
2007
Updated Date (text): 
2012-08-13
Parent Publication Title: 
Rangeland Ecology & Management
Publication Type: 
Archive number: 
NONCTR/00381
States: 

Pub Abstract: 

The locations of black-tailed prairie dog (Cynomys ludovicianus [Ord]) colonies on a 550-km2 study site in northeastern Wyoming, United States, were estimated using 3 remote sensing methods: raw satellite imagery (Landsat 7 ETMþ), enhanced satellite imagery (integration of imagery with thematic layers via a Geographic Information System), and aerial reconnaissance (observations taken from a small plane). A supervised classification of the raw satellite imagery yielded an overall accuracy of 64.4%, relative to ground-truthed locations of prairie dog colonies. The enhanced satellite imagery, resulting from a filtering of the data based on an index derived from the sum of weighted ecological factors associated with prairie dog colonies (slopes, land cover, soil, and ‘‘greenness’’ via the Normalized Difference Vegetation Index) yielded an overall accuracy of 69.2%. The aerial reconnaissance method provided 65.1% accuracy. The highest rate of false positives resulted from the aerial reconnaissance method (39.9%). The highest rate of false negatives resulted from the raw satellite imagery (60.0%), a value that was markedly reduced via the enhancement with ecological data from thematic layers (45.8%). Given the accuracy, interpretability of results, repeatability, objectivity, cost, and safety, the enhanced satellite imagery method is the recommended approach to large-scale detection of black-tailed prairie dog colonies. If a greater accuracy is required, this method can be employed as a coarse filter to narrow the scale and scope of a more costly and laborious fine-scale analysis effectively.

Publication Title: 

Multi-scale remote sensing sagebrush characterization with regression trees over Wyoming, USA: Laying a foundation for monitoring

Authors: 
Homer, C.G., C.L. Aldridge, D.K. Meyer, and S.J. Schell
Publication Date: 
2012
Updated Date (text): 
2011-11-09
Parent Publication Title: 
International Journal of Applied Earth Observation and Geoinformation
Publication Type: 
Archive number: 
2012/0001 FORT
States: 

Pub Abstract: 
Publication Title: 

Assessing long-term variations in sagebrush habitat – characterization of spatial extents and distribution patterns using multi-temporal satellite remote-sensing data

Authors: 
Xian, G., C. Homer, and C. Aldridge
Publication Date: 
2012
Updated Date (text): 
2012-01-13
Parent Publication Title: 
International Journal of Remote Sensing
Publication Type: 
Archive number: 
2012/0002 FORT

Pub Abstract: 
Publication Title: 

Applying remote sensing to invasive species science—A tamarisk example

Authors: 
Morisette, J.T
Publication Date: 
2011
Updated Date (text): 
2011-10-19
Parent Publication Title: 
Publication Type: 
Archive number: 
2011/0125 FORT

Pub Abstract: 

The Invasive Species Science Branch of the Fort Collins Science Center provides research and technical assistance relating to management concerns for invasive species, including understanding how these species are introduced, identifying areas vulnerable to invasion, forecasting invasions, and developing control methods. This fact sheet considers the invasive plant species tamarisk (Tamarix spp)...

Publication Title: 

High throughput computing: A solution for scientific analysis

Authors: 
O'Donnell, M
Publication Date: 
2011
Updated Date (text): 
2011-10-04
Parent Publication Title: 
Publication Type: 
Archive number: 
2011/0100 FORT

Pub Abstract: 

Public land management agencies continually face resource management problems that are exacerbated by climate warming, land-use change, and other human activities. As the U.S. Geological Survey (USGS) Fort Collins Science Center (FORT) works with managers in U.S. Department of the Interior (DOI) agencies and other federal, state, and private entities, researchers are finding that the science needed to address these complex ecological questions across time and space produces substantial amounts of data...

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