Population variability complicates the accurate detection of climate change responses

Christy McCain, Tim Szewczyk, Kevin Bracy Knight

Research output: Contribution to journalArticlepeer-review

50 Citations (Scopus)

Abstract

The rush to assess species' responses to anthropogenic climate change (CC) has underestimated the importance of interannual population variability (PV). Researchers assume sampling rigor alone will lead to an accurate detection of response regardless of the underlying population fluctuations of the species under consideration. Using population simulations across a realistic, empirically based gradient in PV, we show that moderate to high PV can lead to opposite and biased conclusions about CC responses. Between pre- and post-CC sampling bouts of modeled populations as in resurvey studies, there is: (i) A 50% probability of erroneously detecting the opposite trend in population abundance change and nearly zero probability of detecting no change. (ii) Across multiple years of sampling, it is nearly impossible to accurately detect any directional shift in population sizes with even moderate PV. (iii) There is up to 50% probability of detecting a population extirpation when the species is present, but in very low natural abundances. (iv) Under scenarios of moderate to high PV across a species' range or at the range edges, there is a bias toward erroneous detection of range shifts or contractions. Essentially, the frequency and magnitude of population peaks and troughs greatly impact the accuracy of our CC response measurements. Species with moderate to high PV (many small vertebrates, invertebrates, and annual plants) may be inaccurate 'canaries in the coal mine' for CC without pertinent demographic analyses and additional repeat sampling. Variation in PV may explain some idiosyncrasies in CC responses detected so far and urgently needs more careful consideration in design and analysis of CC responses.

Original languageEnglish
Pages (from-to)2081-2093
Number of pages13
JournalGlobal Change Biology
Volume22
Issue number6
Early online date3 May 2016
DOIs
Publication statusPublished - 1 Jun 2016

Keywords

  • Abundance change
  • Demography
  • Extinction risk
  • Local extirpation
  • Population monitoring
  • Range contractions
  • Range shifts
  • Stochasticity

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