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R. Dan Moore

Researcher at University of British Columbia

Publications -  36
Citations -  2789

R. Dan Moore is an academic researcher from University of British Columbia. The author has contributed to research in topics: Riparian zone & Snow. The author has an hindex of 18, co-authored 36 publications receiving 2470 citations. Previous affiliations of R. Dan Moore include University of Northern British Columbia.

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Recent advances in stream and river temperature research

TL;DR: In this article, the authors reviewed the advances in understanding gained since 1990 and on investigations of fundamental controls on thermal behavior, thermal heterogeneity at different spatial scales, the influence of human impacts and the nature of past and future trends.
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Riparian microclimate and stream temperature response to forest harvesting: a review

TL;DR: In this article, a range of studies have demonstrated that streams may or may not cool after flowing from clearings into shaded environments, and further research is required in relation to the factors controlling downstream cooling.
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Forest canopy effects on snow accumulation and ablation: an integrative review of empirical results.

TL;DR: In this paper, a review of previous empirical studies to generate statistical relations between changes in forest cover and the associated changes in snow accumulation and ablation rate is presented, and two simple linear models using forest cover as the sole predictor of changes in SNR are provided, as well as the main sources of variation that prevent the elaboration of more accurate multiple regression models.
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Movement of outbreak populations of mountain pine beetle: influences of spatiotemporal patterns and climate

TL;DR: In this paper, the authors examined an outbreak of mountain pine beetle covering an 800 thousand ha area on the Chilcotin Plateau of British Columbia, Canada, during the 1970s and early 1980s.
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Climate change could alter the distribution of mountain pine beetle outbreaks in western Canada

TL;DR: In this paper, the authors studied the individual associations of several biologically-relevant cold temperature variables, and other temperature/degree-day terms, with outbreak occurrences in a spatial-temporal logistic regression model using data from the current outbreak.