2015
DOI: 10.1139/cjfas-2014-0181
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The spatial distribution of salmon and steelhead redds and optimal sampling design

Abstract: Redd surveys are used extensively to estimate spawner population size for Pacific salmon (Onchorynchus spp.). Because redds tend to be spatially aggregated, estimates of total redds based on subsamples of the potential spawning grounds can be uncertain unless the spatial structure is accounted for. Here we use known redd locations for three populations over several years to compare five different probability sampling designs through simulation. The coefficient of variation (CV) for estimates based on simple ra… Show more

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Cited by 6 publications
(4 citation statements)
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“…Second, without an estimate of observation error, the person conducting a PVA will assign all the annual variation in redds as coming from process error, which contributes directly to the probability of quasi-extinction (observation error does not). Observation error among redd survey protocols is variable (Chasco et al, 2014;Courbois et al, 2008;Liermann, Rawding, Pess, & Glaser, 2015) and covariates that vary through time (e.g., redd density and observer experience) influence error within a given protocol (e.g., this study). It is unclear to what extent this unknown variability in observation error within a single time series has biased population growth curves and ultimately predictions of quasi-extinction risk probability.…”
Section: Discussionmentioning
confidence: 94%
“…Second, without an estimate of observation error, the person conducting a PVA will assign all the annual variation in redds as coming from process error, which contributes directly to the probability of quasi-extinction (observation error does not). Observation error among redd survey protocols is variable (Chasco et al, 2014;Courbois et al, 2008;Liermann, Rawding, Pess, & Glaser, 2015) and covariates that vary through time (e.g., redd density and observer experience) influence error within a given protocol (e.g., this study). It is unclear to what extent this unknown variability in observation error within a single time series has biased population growth curves and ultimately predictions of quasi-extinction risk probability.…”
Section: Discussionmentioning
confidence: 94%
“…Stratified random and clustered random sampling designs can be beneficial for selecting sampling sites, especially when a species displays a clumped distribution (Table 4; Lawrence et al 2015;Liermann et al 2015;McGarvey et al 2016), as observed for larval lampreys.…”
Section: Scope Of Inferencementioning
confidence: 99%
“…Stratified random and clustered random sampling designs can be beneficial for selecting sampling sites, especially when a species displays a clumped distribution (Table 4; Lawrence et al 2015; Liermann et al 2015; McGarvey et al 2016), as observed for larval lampreys. Stratified random surveys require all potential sites to be characterized by “strata.” For example, one stratum may be sites with pool habitat, whereas another may be sites with nonpool habitat.…”
Section: Survey Designsmentioning
confidence: 99%
“…We suggest use of a spatially balanced design to ensure spatial coverage and improve precision when compared to simple random sampling, especially when a species exhibits a clumped distribution (Lawrence et al 2015;Liermann et al 2015;McGarvey et al 2016), as observed for larval lampreys (Torgersen and Close 2004;Stone and Barndt 2005).…”
Section: Stepwise Approach Descriptionmentioning
confidence: 99%