IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v299y2015icp147-155.html
   My bibliography  Save this article

Estimation of spatial sampling effort based on presence-only data and accessibility

Author

Listed:
  • Fernández, Daniel
  • Nakamura, Miguel

Abstract

Sampling bias contained in data of biological surveys is very common. Bias is clearly a function of roads, cities, rivers, or other physical features that determines accessibility of collectors, and many data sets of species are presence-only. We set out to estimate spatial sampling bias in a region, based on presence-only data, by explicitly incorporating information on these accessibility factors, and by considering a target group of species that may share a common search pattern. In order to indirectly estimate the number of individuals, we also resort to the concept of species richness. A probabilistic (multinomial) model is proposed, enabling standard likelihood inference procedures to be implemented. Simulation scenarios for exploration of the model and experimentation with the estimation procedure are included. Illustrative examples over a region of Mexico with mammals and butterflies are also reported with insightful results. Our model is able to estimate the sampling bias in a region and enhance the inferences regarding presence-only data.

Suggested Citation

  • Fernández, Daniel & Nakamura, Miguel, 2015. "Estimation of spatial sampling effort based on presence-only data and accessibility," Ecological Modelling, Elsevier, vol. 299(C), pages 147-155.
    • Handle: RePEc:eee:ecomod:v:299:y:2015:i:c:p:147-155
    DOI: 10.1016/j.ecolmodel.2014.12.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380014006309
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2014.12.017?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. David I Warton & Ian W Renner & Daniel Ramp, 2013. "Model-Based Control of Observer Bias for the Analysis of Presence-Only Data in Ecology," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-9, November.
    2. Robert M. Dorazio, 2012. "Predicting the Geographic Distribution of a Species from Presence-Only Data Subject to Detection Errors," Biometrics, The International Biometric Society, vol. 68(4), pages 1303-1312, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Adrien Guetté & Sébastien Caillault & Joséphine Pithon & Guillaume Pain & Hervé Daniel & Benoit Marchadour & Véronique Beaujouan, 2022. "Who and Where Are the Observers behind Biodiversity Citizen Science Data? Effect of Landscape Naturalness on the Spatial Distribution of French Birdwatching Records," Land, MDPI, vol. 11(11), pages 1-25, November.
    2. Liu, Fang & McShea, William J. & Li, Diqiang, 2017. "Correlating habitat suitability with landscape connectivity: A case study of Sichuan golden monkey in China," Ecological Modelling, Elsevier, vol. 353(C), pages 37-46.

    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. Leandro, Camila & Jay-Robert, Pierre & Mériguet, Bruno & Houard, Xavier & Renner, Ian W., 2020. "Is my sdm good enough? insights from a citizen science dataset in a point process modeling framework," Ecological Modelling, Elsevier, vol. 438(C).
    2. Christophe Botella & Alexis Joly & Pascal Monestiez & Pierre Bonnet & François Munoz, 2020. "Bias in presence-only niche models related to sampling effort and species niches: Lessons for background point selection," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-18, May.
    3. Martín, Gerardo & Yáñez-Arenas, Carlos & Chiappa-Carrara, Xavier, 2022. "Discrepancies between point process models and environmental envelopes identify the niche centroid – geography configuration," Ecological Modelling, Elsevier, vol. 469(C).
    4. Kenneth F Kellner & Robert K Swihart, 2014. "Accounting for Imperfect Detection in Ecology: A Quantitative Review," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-8, October.
    5. Hamilton, Serena H. & Pollino, Carmel A. & Jakeman, Anthony J., 2015. "Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data," Ecological Modelling, Elsevier, vol. 299(C), pages 64-78.
    6. Kosicki, Jakub Z., 2017. "Should topographic metrics be considered when predicting species density of birds on a large geographical scale? A case of Random Forest approach," Ecological Modelling, Elsevier, vol. 349(C), pages 76-85.

    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:eee:ecomod:v:299:y:2015:i:c:p:147-155. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    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.