Validation of freshwater mussel life-history strategies: A database and multivariate analysis of freshwater mussel life-history traits

Adrian P. Moore, Nika Galic, Richard A. Brain, Daniel J. Hornbach, Valery E. Forbes

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Freshwater mussels are among the most critically endangered taxa globally. In the United States, 91 out of nearly 300 species are listed as Threatened or Endangered under the Endangered Species Act. Freshwater mussel species exhibit a range of life-history traits. Owing to the large number of North American species, the rarity of many listed species and the often limited data available for those species, it can be difficult to gather all of the information necessary to develop ecological risk assessments and effective management plans for freshwater mussel species. The primary objective of this study was to categorize North American freshwater mussel species into life-history categories to aid in the identification of representative species for risk assessment. To achieve these objectives, a literature review was conducted to identify available life-history data for a large range of mussel species. Using this dataset, two ordinations were performed, non-metric multidimensional scaling and discriminant analysis, to classify mussel species into previously described life-history categories. Both analyses facilitated species classification into life-history categories. Significant data gaps in basic life-history information still exist for many species, but previously described life-history categories were found to be robust and additional analysis allowed quantitative classification of additional species.

Original languageEnglish (US)
Pages (from-to)3386-3402
Number of pages17
JournalAquatic Conservation: Marine and Freshwater Ecosystems
Volume31
Issue number12
DOIs
StatePublished - Dec 2021

Bibliographical note

Funding Information:
The authors would like to thank Bernard Sietman, Zeb Secrist and the Minnesota Department of Natural Resources for sharing access to a database of freshwater mussel survey data. This work was funded by Syngenta Crop Protection, LLC and the University of Minnesota.

Funding Information:
The authors would like to thank Bernard Sietman, Zeb Secrist and the Minnesota Department of Natural Resources for sharing access to a database of freshwater mussel survey data. This work was funded by Syngenta Crop Protection, LLC and the University of Minnesota.

Publisher Copyright:
© 2021 John Wiley & Sons, Ltd.

Keywords

  • discriminant analysis
  • life history
  • multidimensional scaling
  • ordination
  • representative species
  • unionids

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