Volume 35, Issue 4
Management Brief

Multiscale Analysis of River Networks using the R Package linbin

Ethan Z. Welty

Corresponding Author

E-mail address: ethan.welty@colorado.edu

U.S. Geological Survey, Forest and Rangeland Ecosystem Science Center, Cascadia Field Station, School of Environmental and Forest Sciences, University of Washington, Box 352100, Seattle, Washington, 98195 USA

Present address: Institute of Arctic and Alpine Research, University of Colorado, Campus Box 450, Boulder, Colorado 80309, USA.

Corresponding author: E-mail address: ethan.welty@colorado.eduSearch for more papers by this author
Christian E. Torgersen

U.S. Geological Survey, Forest and Rangeland Ecosystem Science Center, Cascadia Field Station, School of Environmental and Forest Sciences, University of Washington, Box 352100, Seattle, Washington, 98195 USA

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Samuel J. Brenkman

U.S. National Park Service, Olympic National Park, 600 East Park Avenue, Port Angeles, Washington, 98362 USA

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Jeffrey J. Duda

U.S. Geological Survey, Western Fisheries Research Center, 6505 Northeast 65th Street, Seattle, Washington, 98115 USA

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Jonathan B. Armstrong

Wyoming Cooperative Fish and Wildlife Unit, University of Wyoming, 1000 East University Avenue, Laramie, Wyoming, 82071 USA

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First published: 17 July 2015
Citations: 4

Abstract

Analytical tools are needed in riverine science and management to bridge the gap between GIS and statistical packages that were not designed for the directional and dendritic structure of streams. We introduce linbin, an R package developed for the analysis of riverscapes at multiple scales. With this software, riverine data on aquatic habitat and species distribution can be scaled and plotted automatically with respect to their position in the stream network or—in the case of temporal data—their position in time. The linbin package aggregates data into bins of different sizes as specified by the user. We provide case studies illustrating the use of the software for (1) exploring patterns at different scales by aggregating variables at a range of bin sizes, (2) comparing repeat observations by aggregating surveys into bins of common coverage, and (3) tailoring analysis to data with custom bin designs. Furthermore, we demonstrate the utility of linbin for summarizing patterns throughout an entire stream network, and we analyze the diel and seasonal movements of tagged fish past a stationary receiver to illustrate how linbin can be used with temporal data. In short, linbin enables more rapid analysis of complex data sets by fisheries managers and stream ecologists and can reveal underlying spatial and temporal patterns of fish distribution and habitat throughout a riverscape.

Received November 13, 2014; accepted April 14, 2015

Number of times cited according to CrossRef: 4

  • Generation and application of river network analogues for use in ecology and evolution, Ecology and Evolution, 10.1002/ece3.6479, 10, 14, (7537-7550), (2020).
  • Longitudinal, Lateral, Vertical, and Temporal Thermal Heterogeneity in a Large Impounded River: Implications for Cold-Water Refuges, Remote Sensing, 10.3390/rs12091386, 12, 9, (1386), (2020).
  • Assessing the Relative Importance of Factors at Multiple Spatial Scales Affecting Terrestrial and Aquatic Wildlife, Current Landscape Ecology Reports, 10.1007/s40823-019-00047-3, (2019).
  • Spatial Variability of Chinook Salmon Spawning Distribution and Habitat Preferences, Transactions of the American Fisheries Society, 10.1080/00028487.2016.1254112, 146, 2, (206-221), (2017).