IDEAS home Printed from https://ideas.repec.org/a/wly/envmet/v34y2023i2ne2761.html
   My bibliography  Save this article

Shooting for abundance: Comparing integrated multi‐sampling models for camera trap and hair trap data

Author

Listed:
  • Mehnaz Jahid
  • Holly N. Steeves
  • Jason T. Fisher
  • Simon J. Bonner
  • Saman Muthukumarana
  • Laura L. E. Cowen

Abstract

Abundance estimation is a vital goal in wildlife monitoring. Camera‐traps are a tool to survey wildlife populations noninvasively and can be used for abundance estimation if individuals are identifiable. However, for species without individual identification characteristics, camera‐trap surveys have often been combined with some other survey method such as capture‐recapture (CR, using traditional tags or DNA through hair snags or scat) to inform an integrated model. We discuss and apply two integrated models involving presence‐absence data from camera traps and CR data from hair traps to compare bias and precision to estimate the population density of grizzly bears of the central Rocky Mountains of Alberta, Canada. Unlike many other studies, we found that integrating presence‐absence data with CR data does not improve the precision of the density estimates. The possible reasons for such results are discussed in detail.

Suggested Citation

  • Mehnaz Jahid & Holly N. Steeves & Jason T. Fisher & Simon J. Bonner & Saman Muthukumarana & Laura L. E. Cowen, 2023. "Shooting for abundance: Comparing integrated multi‐sampling models for camera trap and hair trap data," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.
  • Handle: RePEc:wly:envmet:v:34:y:2023:i:2:n:e2761
    DOI: 10.1002/env.2761
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/env.2761
    Download Restriction: no

    File URL: https://libkey.io/10.1002/env.2761?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. D. L. Borchers & M. G. Efford, 2008. "Spatially Explicit Maximum Likelihood Methods for Capture–Recapture Studies," Biometrics, The International Biometric Society, vol. 64(2), pages 377-385, June.
    2. Murray G. Efford & Christine M. Hunter, 2018. "Spatial capture–mark–resight estimation of animal population density," Biometrics, The International Biometric Society, vol. 74(2), pages 411-420, June.
    3. P. Besbeas & S. N. Freeman & B. J. T. Morgan & E. A. Catchpole, 2002. "Integrating Mark–Recapture–Recovery and Census Data to Estimate Animal Abundance and Demographic Parameters," Biometrics, The International Biometric Society, vol. 58(3), pages 540-547, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xinhai Li & Ning Li & Baidu Li & Yuehua Sun & Erhu Gao, 2022. "AbundanceR: A Novel Method for Estimating Wildlife Abundance Based on Distance Sampling and Species Distribution Models," Land, MDPI, vol. 11(5), pages 1-13, April.
    2. Simone Tenan & Paolo Pedrini & Natalia Bragalanti & Claudio Groff & Chris Sutherland, 2017. "Data integration for inference about spatial processes: A model-based approach to test and account for data inconsistency," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-18, October.
    3. Soumen Dey & Mohan Delampady & Ravishankar Parameshwaran & N. Samba Kumar & Arjun Srivathsa & K. Ullas Karanth, 2017. "Bayesian Methods for Estimating Animal Abundance at Large Spatial Scales Using Data from Multiple Sources," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(2), pages 111-139, June.
    4. Zhang, Hongmei & Ghosh, Kaushik & Ghosh, Pulak, 2012. "Sampling designs via a multivariate hypergeometric-Dirichlet process model for a multi-species assemblage with unknown heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 56(8), pages 2562-2573.
    5. Nichols, J.M. & Spendelow, J.A. & Nichols, J.D., 2017. "Using Optimal Transport Theory to Estimate Transition Probabilities in Metapopulation Dynamics," Ecological Modelling, Elsevier, vol. 359(C), pages 311-319.
    6. Leo Polansky & Ken B. Newman & Lara Mitchell, 2021. "Improving inference for nonlinear state‐space models of animal population dynamics given biased sequential life stage data," Biometrics, The International Biometric Society, vol. 77(1), pages 352-361, March.
    7. Riki Herliansyah & Ruth King & Dede Aulia Rahman & Stuart King, 2025. "Animal Density Estimation for Large Unmarked Populations Using a Spatially Explicit Model," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 30(1), pages 193-210, March.
    8. D. L. Borchers & B. C. Stevenson & D. Kidney & L. Thomas & T. A. Marques, 2015. "A Unifying Model for Capture-Recapture and Distance Sampling Surveys of Wildlife Populations," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 195-204, March.
    9. Blanca Sarzo & Ruth King & David Conesa & Jonas Hentati-Sundberg, 2021. "Correcting Bias in Survival Probabilities for Partially Monitored Populations via Integrated Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(2), pages 200-219, June.
    10. Murray G. Efford & Christine M. Hunter, 2018. "Spatial capture–mark–resight estimation of animal population density," Biometrics, The International Biometric Society, vol. 74(2), pages 411-420, June.
    11. Abadi, Fitsum & Gimenez, Olivier & Jakober, Hans & Stauber, Wolfgang & Arlettaz, Raphaël & Schaub, Michael, 2012. "Estimating the strength of density dependence in the presence of observation errors using integrated population models," Ecological Modelling, Elsevier, vol. 242(C), pages 1-9.
    12. Riecke, Thomas V. & Ravussin, Pierre-Alain & Longchamp, Ludovic & Trolliet, Daniel & Gibson, Dan & Schaub, Michael, 2025. "A hierarchical population model for the estimation of latent prey abundance and demographic rates of a nomadic predator," Ecological Modelling, Elsevier, vol. 504(C).
    13. José J. Lahoz-Monfort & Michael P. Harris & Sarah Wanless & Stephen N. Freeman & Byron J. T. Morgan, 2017. "Bringing It All Together: Multi-species Integrated Population Modelling of a Breeding Community," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(2), pages 140-160, June.
    14. Russell, Robin E. & Walsh, Daniel P. & Samuel, Michael D. & Grunnill, Martin D. & Rocke, Tonie E., 2021. "Space matters: host spatial structure and the dynamics of plague transmission," Ecological Modelling, Elsevier, vol. 443(C).
    15. Mosnier, A. & Doniol-Valcroze, T. & Gosselin, J.-F. & Lesage, V. & Measures, L.N. & Hammill, M.O., 2015. "Insights into processes of population decline using an integrated population model: The case of the St. Lawrence Estuary beluga (Delphinapterus leucas)," Ecological Modelling, Elsevier, vol. 314(C), pages 15-31.
    16. Bart J Harmsen & Rebecca J Foster & Howard Quigley, 2020. "Spatially explicit capture recapture density estimates: Robustness, accuracy and precision in a long-term study of jaguars (Panthera onca)," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-19, June.
    17. Barraquand, Frédéric & Gimenez, Olivier, 2019. "Integrating multiple data sources to fit matrix population models for interacting species," Ecological Modelling, Elsevier, vol. 411(C).
    18. Murray G. Efford & Matthew R. Schofield, 2020. "A spatial open‐population capture‐recapture model," Biometrics, The International Biometric Society, vol. 76(2), pages 392-402, June.
    19. Michael R. Whitehead & Rod Peakall, 2013. "Short-term but not long-term patch avoidance in an orchid-pollinating solitary wasp," Behavioral Ecology, International Society for Behavioral Ecology, vol. 24(1), pages 162-168.
    20. R. B. O'Hara & S. Lampila & M. Orell, 2009. "Estimation of Rates of Births, Deaths, and Immigration from Mark–Recapture Data," Biometrics, The International Biometric Society, vol. 65(1), pages 275-281, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:envmet:v:34:y:2023:i:2:n:e2761. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1180-4009/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.