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Disentangling data discrepancies with integrated population models.

Sarah P Saunders1,2, Matthew T Farr1,3, Alexander D Wright1,3

  • 1Department of Integrative Biology, Michigan State University, 288 Farm Lane RM 203, East Lansing, Michigan, 48824, USA.

Ecology
|March 31, 2019
PubMed
Summary

Integrated population models (IPMs) unify diverse wildlife survey data to resolve conflicting population trends. This approach identifies limiting life-cycle stages for migratory birds, improving conservation strategies.

Keywords:
American Woodcockannual cycleband-recoverydata integrationdata integration for population models Special Featureharvestsinging-ground survey

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Area of Science:

  • Ecology
  • Population Biology
  • Conservation Science

Background:

  • Wildlife population studies often face challenges with inconsistent data from various survey methods.
  • Conflicting or incomplete data hinder accurate assessment of population trends, dynamics, and viability.

Purpose of the Study:

  • To provide guidance on using integrated population models (IPMs) to resolve discrepancies arising from spatiotemporal data mismatches.
  • To illustrate the application of IPMs using the migratory American Woodcock (Scolopax minor) as a case study.

Main Methods:

  • Synthesized long-term datasets (1963-2015) for the American Woodcock within an IPM framework.
  • Estimated continental-scale population trends and linked demographic drivers across the species' annual cycle and geographic range.
  • Identified limiting life-cycle stages and key demographic drivers of population change.

Main Results:

  • The IPM successfully integrated disparate data sources to estimate American Woodcock population trends.
  • Analysis revealed specific time periods and regions where vital rates were lowest and most variable.
  • Key demographic parameters driving population change were identified, highlighting conservation priorities.

Conclusions:

  • Integrated population models offer a robust solution for reconciling conflicting data in wildlife ecology.
  • IPMs can identify critical life-history stages and drivers, informing targeted conservation efforts for migratory species.
  • Cross-disciplinary strategies, such as data thinning and expert elicitation, can enhance the integration of incongruent ecological data.