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Census data aggregation decisions can affect population-level inference in heterogeneous populations.

Søs Engbo1, James C Bull2, Luca Börger2

  • 1Department of Biology University of Southern Denmark Odense Denmark.

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|August 8, 2020
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Summary

Conservation decisions using population models are biased by heterogeneous census data. Site selection and data aggregation significantly impact grey seal pup survival estimates and population dynamics predictions.

Keywords:
conservationgrey sealmatrix population modelingpopulation dynamicspopulation managementsurvey methods

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Area of Science:

  • Ecology
  • Population Biology
  • Conservation Science

Background:

  • Conservation and management decisions often depend on population models.
  • These models are typically parameterized using census data.
  • Census data frequently exhibit spatiotemporal heterogeneity in sampling, precision, and methodology.

Purpose of the Study:

  • To investigate the influence of site selection and data aggregation on pup survival estimates.
  • To assess the downstream effects of these data handling decisions on matrix population models (MPMs).
  • To utilize a long-term grey seal (Halichoerus grypus) dataset from southwestern Wales as a model system.

Main Methods:

  • Analyzed a 25-year dataset on grey seal pup survival from 46 sampling locations.
  • Explored data handling impacts by varying the combination of years and sampling locations for parameterizing pup survival in MPMs.
  • Focused on pup survival due to data availability and quality.

Main Results:

  • Pup survival probability exhibited high variability, primarily at the site level and with poor correlation among sites.
  • Sampling strategy significantly influenced predicted population dynamics.
  • Geographically, the required sample size for reliable survival estimates varied considerably.

Conclusions:

  • Site selection and data aggregation are critical for populations with spatially variable vital rates.
  • Inclusion of peripheral or less-used areas can introduce substantial variation into population estimates.
  • Careful consideration of data handling, including weighting methods, is essential for successful management actions.