Hydrobiologia

, Volume 807, Issue 1, pp 53–65 | Cite as

Microscopy versus automated imaging flow cytometry for detecting and identifying rare zooplankton

  • Keara Stanislawczyk
  • Mattias L. Johansson
  • Hugh J. MacIsaac
Primary Research Paper

Abstract

Many zooplankton surveys underestimate species richness owing to difficulties in detecting rare species. This problem is particularly acute for studies designed to detect non-indigenous species (NIS) when their abundance is low. Our goal was to test the difference in detection efficiency between traditional microscopy and image analysis (i.e., FlowCAM). We hypothesized that detection of rare species should become easier as they become abundant in a sample, if they are morphologically distinct, or if counting effort increased. We spiked different densities of Cladocera into zooplankton samples from Lake Ontario to simulate rarity, and assessed detection rate. Our results indicated that there was a positive relationship between the probability of finding at least one spiked NIS and its abundance, distinctiveness, and counting effort employed. FlowCAM processed more subsamples, though morphologically similar taxa were distinguished more readily with microscopy. The expected probability for detecting one individual spiked into a sample with ~ 8000 individuals (300 counted) was 3.60%, though observed values were considerably lower using both classical microscopy (4.58 × 10−3 to 1.00%) and FlowCAM (0.10 to 3.00%). Our experiments highlight that many plankton ecologists use subsample counts too low to detect rare native species and NIS, resulting in low species richness estimates and false negatives.

Keywords

Invasive species Early detection Risk assessment Taxonomy FlowCAM Great Lakes Hamilton Harbour 

Notes

Acknowledgements

We thank Colin van Overdijk for assistance with field work, Emma DeRoy for assisting with spiking zooplankton, Drs. Linda Weiss and Marina Manca for providing spiked species, and Joelle Pecz and Sarah-Jayne Collins for assistance with sample processing. Financial support was provided by an NSERC CREATE (Multiple Stressors and Cumulative Effects in the Great Lakes to Paul Sibley) training grant, Fluid Imaging, and by a Canada Research Chair and NSERC Discovery Grant to HJM.

Supplementary material

10750_2017_3382_MOESM1_ESM.docx (19 kb)
Supplementary material 1 (DOCX 19 kb)

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Keara Stanislawczyk
    • 1
  • Mattias L. Johansson
    • 1
  • Hugh J. MacIsaac
    • 1
  1. 1.Great Lakes Institute for Environmental ResearchUniversity of WindsorWindsorCanada

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