Combining field data with computer simulations to determine a representative reach for brook trout assessment

John A. Sweka, Tyler Wagner, Jason Detar, David Kristine

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Fisheries biologists often use backpack electrofishing to sample stream fish. A common goal of sampling is to estimate density and/or biomass to make inferences about the status and trends of fish populations. One challenge when estimating population size is determining an appropriate site or reach length to sample. In this study, we empirically determined the required length of stream that needs to be sampled, assuming the study design is one site per stream, in order to achieve a desired level of accuracy for brook trout density and biomass estimates in Pennsylvania headwater streams. Long sample reaches (600 m) were chosen on seven first to third order streams and these sites were broken into twelve 50-m subreaches. Each subreach was sampled by removal electrofishing techniques until either five electrofishing passes were completed or no brook trout were captured. The total density and biomass of brook trout over all 50-m subreaches was considered the "true" density and biomass for the entire reach. We then performed computer simulations in which various numbers of 50-m subreaches were randomly selected and catches from each subreach were summed within the first three electrofishing passes to simulate removal sampling of site lengths ranging from 50 to 550 m. Population estimates were made using a removal estimator and density and biomass were calculated using various stratification schemes based on fish age and size. Estimates of density and biomass were then compared to the true values to assess the possible range in bias of estimates for a given reach length. Results from our simulations suggest a 200-to 250-m-long or a 400-to 450-m-long stream reach or site is needed to estimate brook trout density and biomass within 50% and 25%, respectively, of the true density and biomass. This information and our methodology will be valuable to fisheries managers in developing standardized protocols for assessing trout populations in small streams.

Original languageEnglish (US)
Pages (from-to)209-222
Number of pages14
JournalJournal of Fish and Wildlife Management
Issue number2
StatePublished - Dec 1 2012

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Animal Science and Zoology
  • Nature and Landscape Conservation


Dive into the research topics of 'Combining field data with computer simulations to determine a representative reach for brook trout assessment'. Together they form a unique fingerprint.

Cite this