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N-mixture models for population estimation: Application in spotted lanternfly egg mass survey.

Houping Liu1, James T Julian2

  • 1Pennsylvania Department of Conservation and Natural Resources, 400 Market Street, Harrisburg, PA 17105, United States.

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Summary

N-mixture models estimate insect populations using repeated counts, proving useful for invasive species like the spotted lanternfly. This method accounts for imperfect detection, offering higher abundance estimates than traditional surveys.

Keywords:
AbundanceDetection probabilityFulgoridaeLycorma delicatulaZero-inflation Poisson distribution

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Area of Science:

  • Ecology
  • Conservation Biology
  • Entomology

Background:

  • Accurate population density and structure are vital for conservation and pest management.
  • Traditional sampling methods are often infeasible when individuals cannot be captured or marked.
  • N-mixture models offer a solution by using repeated count data to estimate abundance and detection probability.

Purpose of the Study:

  • To describe the application of N-mixture models for population studies, including data collection, model fitting, and evaluation.
  • To apply N-mixture models to survey data of Lycorma delicatula (spotted lanternfly) egg masses.
  • To assess the potential of N-mixture models for insect population surveys in agriculture and forestry.

Main Methods:

  • Utilized N-mixture models with repeated egg mass count data from 28 plots across seven sites.
  • Analyzed the relationship between detection probability and tree diameter at breast height (DBH).
  • Investigated the association between egg mass abundance (λ) and basal area (BA), focusing on tree of heaven (TOH) and other species.

Main Results:

  • Detection probability (p) ranged from 0.516 to 0.614 and was negatively correlated with DBH.
  • Egg mass abundance (λ) was positively associated with BA, with higher densities on TOH trees and in TOH plots.
  • N-mixture model abundance estimates were generally higher than observed maximum counts, with predicted densities varying significantly by site and tree type.

Conclusions:

  • N-mixture models provide a robust framework for estimating insect abundance, particularly when traditional methods are impractical.
  • The study highlights the effectiveness of N-mixture models for surveying invasive species like Lycorma delicatula.
  • These models show significant potential for future insect population surveys in agricultural and forestry settings.