A time-lapse photography method for monitoring salmon (Oncorhynchus spp.) passage and abundance in streams

William W. Deacy, William B. Leacock, Lisa A. Eby, Jack A. Stanford

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Accurately estimating population sizes is often a critical component of fisheries research and management. Although there is a growing appreciation of the importance of small-scale salmon population dynamics to the stability of salmon stock-complexes, our understanding of these populations is constrained by a lack of efficient and cost- effective monitoring tools for streams. Weirs are expensive, labor intensive, and can disrupt natural fish movements. While conventional video systems avoid some of these shortcomings, they are expensive and require excessive amounts of labor to review footage for data collection. Here, we present a novel method for quantifying salmon in small streams (< 15 m wide, < 1 m deep) that uses both time-lapse photography and video in a model-based double sampling scheme. This method produces an escapement estimate nearly as accurate as a video-only approach, but with substantially less labor, money, and effort. It requires servicing only every 14 days, detects salmon 24 h/day, is inexpensive, and produces escapement estimates with confidence intervals. In addition to escapement estimation, we present a method for estimating in-stream salmon abundance across time, data needed by researchers interested in predator-prey interactions or nutrient subsidies. We combined daily salmon passage estimates with stream specific estimates of daily mortality developed using previously published data. To demonstrate proof of concept for these methods, we present results from two streams in southwest Kodiak Island, Alaska in which high densities of sockeye salmon spawn.

Original languageEnglish
Article numbere2120
Issue number6
StatePublished - 2016


  • Alaska
  • Escapement
  • Kodiak
  • Migration
  • Salmon
  • Sockeye
  • Spawning
  • Time-lapse photography
  • Video
  • Weir


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