IDEAS home Printed from https://ideas.repec.org/a/spr/jagbes/v21y2016i1d10.1007_s13253-015-0234-1.html
   My bibliography  Save this article

Accounting for Lack of Independence and Partial Overlap of Observation Zones in Line-Transect Mark-Recapture Distance Sampling

Author

Listed:
  • D. I. MacKenzie

    (Proteus Wildlife Research Consultants)

  • D. Clement

    (Cawthron Institute)

Abstract

Line-transect mark-recapture distance sampling methods can be used to estimate abundance when at least two observers sight and record distances to detected groups of individuals within the survey area. However, a lack of independence between the observer’s detections will cause biased abundance estimates. Studies are also typically designed such that there is complete overlap of the regions searched by the two observers, but that may not always be possible. Here we detail an intuitive approach for line-transect distance sampling applications based upon logistic regression to account for a potential lack of independence by using the detections of one observer as a covariate in the detection function of the second observer. Partial overlap of the observer survey regions can be addressed by constraining detection probability to equal 0 for the respective observer outside of the overlap zone. We show via simulation that the method provides reliable estimates of abundance and is not affected by random unmodeled heterogeneity in detection probability. The method is illustrated by estimating abundance within the covered region of an aerial line-transect survey for New Zealand’s endemic Hector’s dolphin (Cephalorhynchus hectori hectori) conducted in the austral summer of 2013, the motivating application for this work. Supplementary materials accompanying this paper appear on-line.

Suggested Citation

  • D. I. MacKenzie & D. Clement, 2016. "Accounting for Lack of Independence and Partial Overlap of Observation Zones in Line-Transect Mark-Recapture Distance Sampling," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(1), pages 41-57, March.
    • Handle: RePEc:spr:jagbes:v:21:y:2016:i:1:d:10.1007_s13253-015-0234-1
    DOI: 10.1007/s13253-015-0234-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13253-015-0234-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13253-015-0234-1?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stephen T. Buckland & Jeffrey L. Laake & David L. Borchers, 2010. "Double-Observer Line Transect Methods: Levels of Independence," Biometrics, The International Biometric Society, vol. 66(1), pages 169-177, March.
    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. Paul B Conn & Jeffrey L Laake & Devin S Johnson, 2012. "A Hierarchical Modeling Framework for Multiple Observer Transect Surveys," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-13, August.
    2. S. T. Buckland & C. S. Oedekoven & D. L. Borchers, 2016. "Model-Based Distance Sampling," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(1), pages 58-75, March.
    3. Hiroshi Okamura & Shingo Minamikawa & Hans J. Skaug & Toshiya Kishiro, 2012. "Abundance Estimation of Long-Diving Animals Using Line Transect Methods," Biometrics, The International Biometric Society, vol. 68(2), pages 504-513, June.
    4. Justin J. Van Ee & Christian A. Hagen & David C. Pavlacky Jr. & Kent A. Fricke & Matthew D. Koslovsky & Mevin B. Hooten, 2023. "Melding wildlife surveys to improve conservation inference," Biometrics, The International Biometric Society, vol. 79(4), pages 3941-3953, December.

    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:spr:jagbes:v:21:y:2016:i:1:d:10.1007_s13253-015-0234-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.