Erratum to: Application of systematic adaptive cluster sampling for the assessment of black sea bass Centropristis striata abundance
Autor: | Daniel W. Cullen, Bradley G. Stevens |
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Rok vydání: | 2017 |
Předmět: |
0106 biological sciences
education.field_of_study food.ingredient Adaptive sampling biology Ecology 010604 marine biology & hydrobiology Population Estimator Systematic sampling 04 agricultural and veterinary sciences Aquatic Science biology.organism_classification 01 natural sciences Nautical mile Bass (fish) food Statistics 040102 fisheries 0401 agriculture forestry and fisheries Environmental science Cluster sampling Centropristis education |
Zdroj: | Fisheries Science. 83:683-683 |
ISSN: | 1444-2906 0919-9268 |
DOI: | 10.1007/s12562-017-1120-2 |
Popis: | In this study, we applied systematic adaptive cluster sampling (SACS) to assess the abundance of black sea bass Centropristis striata on hard bottom habitats in the Mid-Atlantic Bight (MBA; USA). We used a remote underwater video system to obtain video recordings of black sea bass from 25 June to 6 August 2013 within a 25-square nautical mile (nmi2) sampling region. Data in the form of fish counts were collected from video recordings and used to estimate parameters including sample means and population totals of black sea bass for two adaptive cluster sampling estimators and a single systematic sampling estimator. The precision and relative efficiencies of the parameter estimates were also calculated and compared. In total, two adaptive cluster samples were encountered within the sampling region. Sample means and population totals were largest for the systematic sampling (SS) estimator while the adaptive sampling estimators produced parameter estimates with the lowest variances and highest precision. Our results indicated that SACS was more efficient and advantageous with respect to sampling costs [i.e., sampling time (hours) and travel distance (kilometers)] than SS alone for assessing the abundance of clustered populations of C. striata on hard bottom habitats in the MBA. |
Databáze: | OpenAIRE |
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