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Evaluation of Sampling Strategies for Scuba Surveys to Assess Spawn Deposition by Pacific Herring
Author(s) -
Schweigert J. F.,
Haegele C. W.,
Stocker M.
Publication year - 1990
Publication title -
north american journal of fisheries management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 72
eISSN - 1548-8675
pISSN - 0275-5947
DOI - 10.1577/1548-8675(1990)010<0185:eossfs>2.3.co;2
Subject(s) - quadrat , transect , pacific herring , environmental science , sampling (signal processing) , biomass (ecology) , statistics , ecology , herring , fishery , mathematics , biology , clupea , filter (signal processing) , fish <actinopterygii> , computer science , computer vision
Spawning stock biomass of Pacific herring Clupea harengus pallasi can be accurately assessed by scuba surveys of egg deposition based on either a two‐ or three‐stage subsampling design. A prediction model is incorporated to estimate the egg density in individual sample quadrats along transects set across the spawning beds. Two models are presented that estimate egg density almost equally well. Both rely on an estimate of the average number of egg layers on the vegetation, the type of predominant vegetation, the size of the sampling quadrat, and either an estimate of the proportion of the quadrat covered by vegetation (visual model) or a measure of the wet weight of the vegetation and attached eggs (biomass model). The biomass model is more accurate, but requires more labor‐intensive, time‐consuming sampling than does the visual model. Estimates of the optimal sampling designs for the two models reflect this and indicate that the biomass model should be used when very accurate estimates of stock abundance are desired, whereas the visual model is applicable when a rapid and efficient means of estimating stock size is needed and less accuracy is acceptable. A sampling intensity of 3 transects/km with a minimum of 4 samples/ 100 m of transect length should result in estimates of the mean egg density with a standard error no larger than 25% of the true mean. Optimal sampling fractions for a three‐stage subsampling design indicate that from 1 to 12 spawning beds, representing from 10 to 100% of the total egg deposition in each statistical area, should be routinely surveyed.