A latent process model approach to improve the utility of indicator species

Jill Fleming*, Chris Sutherland, Sean C Sterrett, Evan H Campbell Grant

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The state of an ecosystem is governed by dynamic biotic and abiotic processes, which can only be partially observed. Costs associated with measuring each component limit the feasibility of comprehensive assessments of target ecosystems. Instead, indicator species are recommended as a surrogate index. While this is an attractive concept, indicator species have rarely proven to be an effective tool for monitoring ecosystems and informing management decisions. One deficiency in the existing theoretical development of indicator species may be overcome with the incorporation of latent (i.e. unobservable) states. Advancements in quantitative ecological models allow for latent-state models to be tested empirically, facilitating the robust evaluation and practical use of indicator species for ecosystem science and management. Here, we extend the existing conceptual models of indicator species to include a direct relationship between an indicator species, ecosystem change drivers and latent processes and variables. Our approach includes explicit consideration of important estimation uncertainty and narrows the range of values a latent variable may take by relating it to measurable attribute(s) of an indicator species. We demonstrate the utility of this approach by relating a commonly cited indicator species, the red-backed salamander Plethodon cinereus, to a typical latent process of interest – ecosystem health.
Original languageEnglish
Pages (from-to)1753-1762
Number of pages10
JournalOikos
Volume129
Issue number12
Early online date8 Oct 2020
DOIs
Publication statusPublished - Dec 2020

Keywords

  • Ecosystem change drivers
  • Ecosystem health
  • Indicator species
  • Pethodon cinereus
  • Red-backed salamander
  • Surrogate species

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