Accurate classification of juvenile weakfish Cynoscion regalis to estuarine nursery areas based on chemical signatures in otoliths

Simon R. Thorrold, Cynthia M. Jones, Peter K Swart, Timothy E. Targett

Research output: Contribution to journalArticle

173 Citations (Scopus)

Abstract

We investigated the ability of trace element and isotopic signatures in otoliths to record the nursery areas of juvenile (young-of-the-year) weakfish Cynoscion regalis from the east coast of the USA. Juvenile C. regalis were captured with otter trawls at multiple sites in Doboy Sound (Georgia), Pamlico Sound (North Carolina), Chesapeake Bay (Virginia), Delaware Bay (Delaware) and Peconic Bay (New York), from July to September 1996. One sagittal otolith from each specimen was assayed for Mg/Ca, Mn/Ca, Sr/Ca and Be/Ca ratios using inductively coupled plasma mass spectrometry (ICP-MS), while δ13C and δ18O values from the other sagittal otolith in the pair were determined using isotope ratio mass spectrometry (IR-MS). A multivariate analysis of variance determined that there were significant differences in trace element signatures among locations. Bootstrapped 95% confidence ellipses on canonical variates indicated that all 5 locations were significantly isolated in discriminant space. On the basis of these differences, linear discriminant function analysis (LDFA) and artificial neural network (ANN) models were used to classify individual fish to their natal estuary with an overall error rate of 37% for LDFA and 29.6% for ANN. Addition of δ13C and δ18O values to the LDFA and ANN models derived from the trace element data resulted in overall error around 10%. We will, therefore, be able to use chemical signatures from the juvenile portion of adult C. regalis otoliths to accurately classify these fish to their natal estuary.

Original languageEnglish (US)
Pages (from-to)253-265
Number of pages13
JournalMarine Ecology Progress Series
Volume173
StatePublished - Nov 12 1998

Fingerprint

otolith
otoliths
discriminant analysis
artificial neural network
neural networks
trace elements
trace element
estuaries
mass spectrometry
estuary
Chesapeake Bay
ellipse
atomic absorption spectrometry
fish
multivariate analysis
variance analysis
isotopes
analysis of variance
isotope
plasma

Keywords

  • Estuarine nursery areas
  • Neural networks
  • Otolith chemistry
  • Stable isotopes
  • Trace elements

ASJC Scopus subject areas

  • Aquatic Science
  • Ecology

Cite this

Accurate classification of juvenile weakfish Cynoscion regalis to estuarine nursery areas based on chemical signatures in otoliths. / Thorrold, Simon R.; Jones, Cynthia M.; Swart, Peter K; Targett, Timothy E.

In: Marine Ecology Progress Series, Vol. 173, 12.11.1998, p. 253-265.

Research output: Contribution to journalArticle

@article{43241c754d5e42a18e111389b1cfaedc,
title = "Accurate classification of juvenile weakfish Cynoscion regalis to estuarine nursery areas based on chemical signatures in otoliths",
abstract = "We investigated the ability of trace element and isotopic signatures in otoliths to record the nursery areas of juvenile (young-of-the-year) weakfish Cynoscion regalis from the east coast of the USA. Juvenile C. regalis were captured with otter trawls at multiple sites in Doboy Sound (Georgia), Pamlico Sound (North Carolina), Chesapeake Bay (Virginia), Delaware Bay (Delaware) and Peconic Bay (New York), from July to September 1996. One sagittal otolith from each specimen was assayed for Mg/Ca, Mn/Ca, Sr/Ca and Be/Ca ratios using inductively coupled plasma mass spectrometry (ICP-MS), while δ13C and δ18O values from the other sagittal otolith in the pair were determined using isotope ratio mass spectrometry (IR-MS). A multivariate analysis of variance determined that there were significant differences in trace element signatures among locations. Bootstrapped 95{\%} confidence ellipses on canonical variates indicated that all 5 locations were significantly isolated in discriminant space. On the basis of these differences, linear discriminant function analysis (LDFA) and artificial neural network (ANN) models were used to classify individual fish to their natal estuary with an overall error rate of 37{\%} for LDFA and 29.6{\%} for ANN. Addition of δ13C and δ18O values to the LDFA and ANN models derived from the trace element data resulted in overall error around 10{\%}. We will, therefore, be able to use chemical signatures from the juvenile portion of adult C. regalis otoliths to accurately classify these fish to their natal estuary.",
keywords = "Estuarine nursery areas, Neural networks, Otolith chemistry, Stable isotopes, Trace elements",
author = "Thorrold, {Simon R.} and Jones, {Cynthia M.} and Swart, {Peter K} and Targett, {Timothy E.}",
year = "1998",
month = "11",
day = "12",
language = "English (US)",
volume = "173",
pages = "253--265",
journal = "Marine Ecology - Progress Series",
issn = "0171-8630",
publisher = "Inter-Research",

}

TY - JOUR

T1 - Accurate classification of juvenile weakfish Cynoscion regalis to estuarine nursery areas based on chemical signatures in otoliths

AU - Thorrold, Simon R.

AU - Jones, Cynthia M.

AU - Swart, Peter K

AU - Targett, Timothy E.

PY - 1998/11/12

Y1 - 1998/11/12

N2 - We investigated the ability of trace element and isotopic signatures in otoliths to record the nursery areas of juvenile (young-of-the-year) weakfish Cynoscion regalis from the east coast of the USA. Juvenile C. regalis were captured with otter trawls at multiple sites in Doboy Sound (Georgia), Pamlico Sound (North Carolina), Chesapeake Bay (Virginia), Delaware Bay (Delaware) and Peconic Bay (New York), from July to September 1996. One sagittal otolith from each specimen was assayed for Mg/Ca, Mn/Ca, Sr/Ca and Be/Ca ratios using inductively coupled plasma mass spectrometry (ICP-MS), while δ13C and δ18O values from the other sagittal otolith in the pair were determined using isotope ratio mass spectrometry (IR-MS). A multivariate analysis of variance determined that there were significant differences in trace element signatures among locations. Bootstrapped 95% confidence ellipses on canonical variates indicated that all 5 locations were significantly isolated in discriminant space. On the basis of these differences, linear discriminant function analysis (LDFA) and artificial neural network (ANN) models were used to classify individual fish to their natal estuary with an overall error rate of 37% for LDFA and 29.6% for ANN. Addition of δ13C and δ18O values to the LDFA and ANN models derived from the trace element data resulted in overall error around 10%. We will, therefore, be able to use chemical signatures from the juvenile portion of adult C. regalis otoliths to accurately classify these fish to their natal estuary.

AB - We investigated the ability of trace element and isotopic signatures in otoliths to record the nursery areas of juvenile (young-of-the-year) weakfish Cynoscion regalis from the east coast of the USA. Juvenile C. regalis were captured with otter trawls at multiple sites in Doboy Sound (Georgia), Pamlico Sound (North Carolina), Chesapeake Bay (Virginia), Delaware Bay (Delaware) and Peconic Bay (New York), from July to September 1996. One sagittal otolith from each specimen was assayed for Mg/Ca, Mn/Ca, Sr/Ca and Be/Ca ratios using inductively coupled plasma mass spectrometry (ICP-MS), while δ13C and δ18O values from the other sagittal otolith in the pair were determined using isotope ratio mass spectrometry (IR-MS). A multivariate analysis of variance determined that there were significant differences in trace element signatures among locations. Bootstrapped 95% confidence ellipses on canonical variates indicated that all 5 locations were significantly isolated in discriminant space. On the basis of these differences, linear discriminant function analysis (LDFA) and artificial neural network (ANN) models were used to classify individual fish to their natal estuary with an overall error rate of 37% for LDFA and 29.6% for ANN. Addition of δ13C and δ18O values to the LDFA and ANN models derived from the trace element data resulted in overall error around 10%. We will, therefore, be able to use chemical signatures from the juvenile portion of adult C. regalis otoliths to accurately classify these fish to their natal estuary.

KW - Estuarine nursery areas

KW - Neural networks

KW - Otolith chemistry

KW - Stable isotopes

KW - Trace elements

UR - http://www.scopus.com/inward/record.url?scp=0032512046&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032512046&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0032512046

VL - 173

SP - 253

EP - 265

JO - Marine Ecology - Progress Series

JF - Marine Ecology - Progress Series

SN - 0171-8630

ER -