Published July 2021 | Version v1
Journal article

Using zooplankton metabarcoding to assess the efficacy of different techniques to clean-up an oil-spill in a boreal lake

  • 1. Toxicology Centre, University of Saskatchewan, Saskatoon, SK (Canada)
  • 2. School of Environmental Sciences, University of Guelph, Guelph, ON (Canada)
  • 3. Department of Environment and Geography, University of Manitoba, Winnipeg, MB (Canada)
  • 4. International Institute for Sustainable Development – Experimental Lakes Area, Kenora, ON (Canada)
  • 5. Department of Environmental Sciences, Baylor University, Waco, Texas (United States)
  • 6. Department of Veterinary Biomedical Sciences, University of Saskatchewan, Saskatoon, SK (Canada)

Description

Highlights: • Morphological and metabarcoding identification are comparable up to genus-level. • Shoreline cleaner application had larger impact on zooplankton community than eMNR. • Metabarcoding could be more sensitive than morphology to detect community changing. Regulators require adequate information to select best practices with less ecosystem impacts for remediation of freshwater ecosystems after oil spills. Zooplankton are valuable indicators of aquatic ecosystem health as they play pivotal roles in biochemical cycles while stabilizing food webs. Compared with morphological identification, metabarcoding holds promise for cost-effective, high-throughput, and benchmarkable biomonitoring of zooplankton communities. The objective of this study was to apply DNA and RNA metabarcoding of zooplankton for ecotoxicological assessment and compare it with traditional morphological identification in experimental shoreline enclosures in a boreal lake. These identification methods were also applied in context of assessing response of the zooplankton community exposed to simulated spills of diluted bitumen (dilbit), with experimental remediation practices (enhanced monitored natural recovery and shoreline cleaner application). Metabarcoding detected boreal zooplankton taxa up to the genus level, with a total of 24 shared genera, and while metabarcoding-based relative abundance served as an acceptable proxy for biomass inferred by morphological identification (ρ ≥ 0.52). Morphological identification determined zooplankton community composition changes due to treatments at 11 days post-spill (PERMANOVA, p = 0.0143) while metabarcoding methods indicated changes in zooplankton richness and communities at 38 days post-spill (T-test, p < 0.05; PERMANOVA, p ≤ 0.0429). Shoreline cleaner application overall seemed to have the largest impact on zooplankton communities relative to enhanced monitored natural recovery, regardless of zooplankton identification method. Both metabarcoding and morphological identification were able to discern the differences between the two experimental remediation practices. Metabarcoding of zooplankton could provide informative results for ecotoxicological assessment of the remediation practices of dilbit, advancing our knowledge of best practices for remediating oil-impacted aquatic ecosystems while serving to accelerate the assessment of at-risk freshwater ecosystems.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.aquatox.2021.105847

Additional details

Identifiers

DOI
10.1016/j.aquatox.2021.105847;
PII
S0166445X21001065;

Publishing Information

Journal Title
Aquatic Toxicology
Journal Volume
236
Journal Page Range
vp.
ISSN
0166-445X
CODEN
AQTODG

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
53109070
Subject category
S54: ENVIRONMENTAL SCIENCES;
Descriptors DEI
AQUATIC ECOSYSTEMS; BIOMASS; BITUMENS; DNA; FRESH WATER; OIL SPILLS; REMEDIAL ACTION; RNA; ZOOPLANKTON
Descriptors DEC
ACCIDENTS; AQUATIC ORGANISMS; ECOSYSTEMS; ENERGY SOURCES; HYDROGEN COMPOUNDS; NUCLEIC ACIDS; ORGANIC COMPOUNDS; OTHER ORGANIC COMPOUNDS; OXYGEN COMPOUNDS; PLANKTON; RENEWABLE ENERGY SOURCES; TAR; WATER

Optional Information

Copyright
Copyright (c) 2021 Elsevier B.V. All rights reserved.