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Time-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation.

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The time-for-space substitution (TSS) in N-mixture models reliably estimates population abundance and trends for single populations. This method is valuable for monitoring rare species, especially those with limited known locations.

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Area of Science:

  • Ecology
  • Population Biology
  • Statistical Modeling

Background:

  • N-mixture models typically require spatial replication for population abundance and trend estimation.
  • The time-for-space substitution (TSS) offers a method to estimate these parameters for a single population without spatial replication.
  • Previous reliability assessments of TSS were limited to a single case study.

Purpose of the Study:

  • To conduct a comprehensive simulation-based evaluation of the time-for-space substitution (TSS) application in N-mixture models.
  • To assess the reliability of TSS for estimating population abundance and trends in single populations.
  • To identify factors influencing the accuracy of TSS estimates.

Main Methods:

  • Generated count data for 144 simulated scenarios representing a single population surveyed multiple times annually with varying dynamics.
  • Employed N-mixture models with the time-for-space substitution (TSS) approach.
  • Compared simulated abundance and trend values against TSS estimates.

Main Results:

  • TSS estimates demonstrated good agreement with actual population abundance.
  • Detection probability and population size were identified as key factors influencing the accuracy of trend and abundance estimation.
  • The simulation study supported the reliability of TSS for single-population analysis.

Conclusions:

  • The time-for-space substitution (TSS) in N-mixture models is a reliable method for monitoring abundance in single populations.
  • This approach is particularly useful for rare or difficult-to-study species, especially those with restricted ranges or few known localities.
  • TSS provides a valuable tool for ecological studies and conservation programs when spatial replication is not feasible.