Models
; Poisson distribution
; Regulatory compliance
; Water
; Accuracy and precision
; Ballast water
; International maritime organizations
; Nonindigenous species
; Performance standards
; Sampling efforts
; Sampling strategies
; Zooplankton
; Probability density function
; ballast water
; unclassified drug
; water
; abundance
; accuracy assessment
; ballast water
; fieldwork
; future prospect
; introduced species
; modeling
; precision
; probability density function
; zooplankton
; analytical parameters
; Article
; error rate
; measurement accuracy
; nonhuman
; population abundance
; ship
; simulation
; water sampling
; zooplankton
; animal
; isolation and purification
; Poisson distribution
; ship
; zooplankton
; Animals
; Poisson Distribution
; Ships
; Water
; Zooplankton
Scopus学科分类:
Agricultural and Biological Sciences: Aquatic Science
; Earth and Planetary Sciences: Oceanography
; Environmental Science: Pollution
英文摘要:
Ballast water has been a major source of non-indigenous species introductions. The International Maritime Organization has proposed performance standard that will establish an upper limit for viable organisms in discharged ballast. Here we test different sampling efforts for zooplankton in ballast water on a commercial vessel. We fit different probability density functions to find the most representative and evaluated sampling efforts necessary to achieve error rates (α, β) of <�0.05. Our tests encompassed four seasonal trials and five sample volumes. To estimate error rates, we performed simulations which drew from 1 to 30 replicates of each volume (0.10–3.00m3) for mean densities ranging between 1 and 20 organisms m−�3. Fieldwork and simulations suggested that >�0.5�m3samples had the best accuracy and precision, and that the Poisson distribution fit these communities best. This study provides the first field test of a sampling strategy to assess compliance with the future IMO standard for large vessels. � 2016 Elsevier Ltd
Great Lakes Institute for Environmental Research, University of Windsor, Windsor, Ontario, Canada; Department of Mathematical and Statistical Sciences, Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada; Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH, United States
Recommended Citation:
Hernandez M.R.,Johansson M.L.,Xiao Y.,et al. Modeling sampling strategies for determination of zooplankton abundance in ballast water[J]. Marine Pollution Bulletin,2017-01-01,115(2018-01-02)