Bias correction in species distribution models: pooling survey and collection data for multiple species.

@article{Fithian2015BiasCI,
  title={Bias correction in species distribution models: pooling survey and collection data for multiple species.},
  author={William Fithian and Jane Elith and Trevor J. Hastie and David A. Keith},
  journal={Methods in ecology and evolution},
  year={2015},
  volume={6 4},
  pages={
          424-438
        }
}
  • William Fithian, Jane Elith, +1 author David A. Keith
  • Published in
    Methods in ecology and…
    2015
  • Mathematics, Geography, Biology, Medicine
  • Presence-only records may provide data on the distributions of rare species, but commonly suffer from large, unknown biases due to their typically haphazard collection schemes. Presence-absence or count data collected in systematic, planned surveys are more reliable but typically less abundant.We proposed a probabilistic model to allow for joint analysis of presence-only and survey data to exploit their complementary strengths. Our method pools presence-only and presence-absence data for many… CONTINUE READING

    Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

    Figures, Tables, and Topics from this paper.

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 87 CITATIONS

    Birds and Berries: Projecting the Responses of Seed Dispersal Networks to Climate Change

    VIEW 14 EXCERPTS
    CITES BACKGROUND & METHODS
    HIGHLY INFLUENCED

    Evaluating citizen science data for forecasting species responses to national forest management

    VIEW 4 EXCERPTS
    CITES BACKGROUND, METHODS & RESULTS
    HIGHLY INFLUENCED

    Stochastic ecological models for predicting species distribution and extinction

    VIEW 4 EXCERPTS
    CITES BACKGROUND & RESULTS
    HIGHLY INFLUENCED

    Integrated species distributionmodels: combining presence-background data and site-occupancy datawith imperfect detection

    • AscelinGordon, RobertM. Dorazio, MattWhite, Lewi, Stone
    • 2018
    VIEW 5 EXCERPTS
    CITES BACKGROUND, RESULTS & METHODS
    HIGHLY INFLUENCED

    Hierarchical Species Distribution Models

    VIEW 6 EXCERPTS
    CITES BACKGROUND & METHODS
    HIGHLY INFLUENCED

    Towards Process-based Range Modeling of Many Species.

    VIEW 9 EXCERPTS
    CITES METHODS
    HIGHLY INFLUENCED

    A fast Monte Carlo test for preferential sampling

    VIEW 1 EXCERPT
    CITES BACKGROUND

    FILTER CITATIONS BY YEAR

    2013
    2020

    CITATION STATISTICS

    • 8 Highly Influenced Citations

    • Averaged 22 Citations per year from 2017 through 2019

    References

    Publications referenced by this paper.