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K. Arthur Endsley

Researcher at University of Montana

Publications -  13
Citations -  391

K. Arthur Endsley is an academic researcher from University of Montana. The author has contributed to research in topics: Glacier & Water content. The author has an hindex of 5, co-authored 13 publications receiving 312 citations. Previous affiliations of K. Arthur Endsley include Michigan Technological University & University of Michigan.

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Estimating local biodiversity change: a critique of papers claiming no net loss of local diversity.

TL;DR: Reanalyses of the data detected a signal of study duration on biodiversity change, indicating net biodiversity loss is most apparent in studies of longer duration and estimates of species richness change can be biased if species gains during post-disturbance recovery are included without also including species losses that occurred during the disturbance.
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Evaluation of Commercially Available Remote Sensors for Highway Bridge Condition Assessment

TL;DR: In this paper, the authors evaluated 12 potential remote sensing technologies for assessing the bridge deck and superstructure condition, including ground- penetrating radar (GDR), ground-penetrating radar (GP radar) and ground-deflection radar (SDR).
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Bioclimatic and Soil Moisture Monitoring Across Elevation in a Mountain Watershed: Opportunities for Research and Resource Management

TL;DR: The interactive Roaring Fork Observation Network (iRON) as mentioned in this paper is a soil, weather, and ecological monitoring system in the Southern Rocky Mountains of Colorado, which is composed of nine stations, distributed in elevation from 1,890 to 3,680 m, that continually collect and transmit measurements of soil moisture at three depths, soil temperature, air temperature, humidity, and meteorological conditions.
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Housing Market Activity is Associated with Disparities in Urban and Metropolitan Vegetation

TL;DR: In this paper, the authors compare patterns of household income with new measures derived from housing market data and other parcel-level sources (sale prices, tax foreclosures, new housing construction, demolitions, and the balance of construction and demolition) to evaluate whether these spatially, temporally and semantically finer measures of neighborhood social conditions are better predictors of the distribution of urban vegetation.