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A multispecies dependent double-observer model: A new method for estimating multispecies abundance.

Jessie D Golding1, J Joshua Nowak2, Victoria J Dreitz1

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Accurate species abundance estimates are crucial for conservation. A new multispecies dependent double-observer abundance model (MDAM) improves accuracy by reducing false positives and accounting for detection errors in multispecies datasets.

Keywords:
Bayesian N‐mixture modelabundance modeldependent double‐observerfalse positivemultiple species

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Area of Science:

  • Ecology
  • Wildlife Biology
  • Statistical Modeling

Background:

  • Accurate species abundance estimation is vital for effective conservation strategies.
  • Multispecies N-mixture models address variation but often overlook false-positive errors.
  • The dependent-double observer (DDO) method reduces false positives but hasn't been integrated with multispecies models.

Purpose of the Study:

  • To develop a novel statistical model integrating the DDO method with multispecies N-mixture models.
  • To create a multispecies dependent double-observer abundance model (MDAM) for improved abundance estimation.
  • To address the challenge of false-positive errors in multispecies ecological surveys.

Main Methods:

  • Derived an extension of multispecies N-mixture models incorporating the DDO survey method.
  • Developed a hierarchical framework within the MDAM to account for biological and observational processes.
  • Utilized simulated and real-world multispecies data for model validation.

Main Results:

  • The MDAM demonstrated accurate and precise abundance and detection estimates in simulations.
  • Achieved high credible interval coverage (94.5% for abundance, 92.5% for detection).
  • Showed low mean absolute percent error (7.7%) for abundance estimates, with 92.2% within 0-20% error.

Conclusions:

  • The MDAM represents a significant advancement for applying DDO methods to multispecies abundance estimation.
  • This model offers a statistically robust framework for handling complex observational data.
  • The MDAM is a valuable tool for researchers assessing biological communities and improving conservation efforts.