IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v323y2016icp61-76.html
   My bibliography  Save this article

Estimating absence locations of marine species from data of scientific surveys in OBIS

Author

Listed:
  • Coro, Gianpaolo
  • Magliozzi, Chiara
  • Vanden Berghe, Edward
  • Bailly, Nicolas
  • Ellenbroek, Anton
  • Pagano, Pasquale

Abstract

Estimating absence locations of a species is important in conservation biology and conservation planning. For instance, using reliable absence as much as presence information, species distribution models can enhance their performance and produce more accurate predictions of the distribution of a species. Unfortunately, estimating reliable absence locations is difficult and often requires a deep knowledge of the species’ distribution and of its abiotic and biotic environmental preferences and tolerance. In this paper, we propose a methodology to reconstruct reliable absence information from presence-only information, and the conditions that those presence-only data have to meet to make this possible.

Suggested Citation

  • Coro, Gianpaolo & Magliozzi, Chiara & Vanden Berghe, Edward & Bailly, Nicolas & Ellenbroek, Anton & Pagano, Pasquale, 2016. "Estimating absence locations of marine species from data of scientific surveys in OBIS," Ecological Modelling, Elsevier, vol. 323(C), pages 61-76.
    • Handle: RePEc:eee:ecomod:v:323:y:2016:i:c:p:61-76
    DOI: 10.1016/j.ecolmodel.2015.12.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380015005761
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2015.12.008?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. Coro, Gianpaolo & Pagano, Pasquale & Ellenbroek, Anton, 2013. "Combining simulated expert knowledge with Neural Networks to produce Ecological Niche Models for Latimeria chalumnae," Ecological Modelling, Elsevier, vol. 268(C), pages 55-63.
    2. McCullagh, Peter, 1984. "Generalized linear models," European Journal of Operational Research, Elsevier, vol. 16(3), pages 285-292, June.
    3. Jones, Miranda C. & Dye, Stephen R. & Pinnegar, John K. & Warren, Rachel & Cheung, William W.L., 2012. "Modelling commercial fish distributions: Prediction and assessment using different approaches," Ecological Modelling, Elsevier, vol. 225(C), pages 133-145.
    4. Coro, Gianpaolo & Webb, Thomas J. & Appeltans, Ward & Bailly, Nicolas & Cattrijsse, André & Pagano, Pasquale, 2015. "Classifying degrees of species commonness: North Sea fish as a case study," Ecological Modelling, Elsevier, vol. 312(C), pages 272-280.
    5. Zeller, Dirk & Froese, Rainer & Pauly, Daniel, 2005. "On losing and recovering fisheries and marine science data," Marine Policy, Elsevier, vol. 29(1), pages 69-73, January.
    6. Coro, Gianpaolo & Magliozzi, Chiara & Ellenbroek, Anton & Pagano, Pasquale, 2015. "Improving data quality to build a robust distribution model for Architeuthis dux," Ecological Modelling, Elsevier, vol. 305(C), pages 29-39.
    7. Lippitt, Christopher D. & Rogan, John & Toledano, James & Sangermano, Florencia & Eastman, J. Ronald & Mastro, Victor & Sawyer, Alan, 2008. "Incorporating anthropogenic variables into a species distribution model to map gypsy moth risk," Ecological Modelling, Elsevier, vol. 210(3), pages 339-350.
    8. Ready, Jonathan & Kaschner, Kristin & South, Andy B. & Eastwood, Paul D. & Rees, Tony & Rius, Josephine & Agbayani, Eli & Kullander, Sven & Froese, Rainer, 2010. "Predicting the distributions of marine organisms at the global scale," Ecological Modelling, Elsevier, vol. 221(3), pages 467-478.
    9. Platts, Philip J. & McClean, Colin J. & Lovett, Jon C. & Marchant, Rob, 2008. "Predicting tree distributions in an East African biodiversity hotspot: model selection, data bias and envelope uncertainty," Ecological Modelling, Elsevier, vol. 218(1), pages 121-134.
    10. Carl M. O'Brien & Clive J. Fox & Benjamin Planque & John Casey, 2000. "Climate variability and North Sea cod," Nature, Nature, vol. 404(6774), pages 142-142, March.
    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. Zhiqiang Chen & Zhibiao Chen, 2018. "Effects of ecological restoration measures on the distribution of Dicranopteris dichotoma at the microscale in the red soil hilly region of China," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-17, October.
    2. Coro, Gianpaolo & Vilas, Luis Gonzalez & Magliozzi, Chiara & Ellenbroek, Anton & Scarponi, Paolo & Pagano, Pasquale, 2018. "Forecasting the ongoing invasion of Lagocephalus sceleratus in the Mediterranean Sea," Ecological Modelling, Elsevier, vol. 371(C), pages 37-49.
    3. Gómez-Sanz, Valentín, 2019. "Site- scale ecological marginality: Evaluation model and application to a case study," Ecological Modelling, Elsevier, vol. 408(C), pages 1-1.
    4. Coro, Gianpaolo, 2020. "A global-scale ecological niche model to predict SARS-CoV-2 coronavirus infection rate," Ecological Modelling, Elsevier, vol. 431(C).

    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. Cheung, William W.L. & Jones, Miranda C. & Reygondeau, Gabriel & Stock, Charles A. & Lam, Vicky W.Y. & Frölicher, Thomas L., 2016. "Structural uncertainty in projecting global fisheries catches under climate change," Ecological Modelling, Elsevier, vol. 325(C), pages 57-66.
    2. Coro, Gianpaolo & Vilas, Luis Gonzalez & Magliozzi, Chiara & Ellenbroek, Anton & Scarponi, Paolo & Pagano, Pasquale, 2018. "Forecasting the ongoing invasion of Lagocephalus sceleratus in the Mediterranean Sea," Ecological Modelling, Elsevier, vol. 371(C), pages 37-49.
    3. Coro, Gianpaolo, 2020. "A global-scale ecological niche model to predict SARS-CoV-2 coronavirus infection rate," Ecological Modelling, Elsevier, vol. 431(C).
    4. Coro, Gianpaolo & Magliozzi, Chiara & Ellenbroek, Anton & Pagano, Pasquale, 2015. "Improving data quality to build a robust distribution model for Architeuthis dux," Ecological Modelling, Elsevier, vol. 305(C), pages 29-39.
    5. Gormley, Kate S.G. & Hull, Angela D. & Porter, Joanne S. & Bell, Michael C. & Sanderson, William G., 2015. "Adaptive management, international co-operation and planning for marine conservation hotspots in a changing climate," Marine Policy, Elsevier, vol. 53(C), pages 54-66.
    6. Melo-Merino, Sara M. & Reyes-Bonilla, Héctor & Lira-Noriega, Andrés, 2020. "Ecological niche models and species distribution models in marine environments: A literature review and spatial analysis of evidence," Ecological Modelling, Elsevier, vol. 415(C).
    7. Martín-García, Laura & González-Lorenzo, Gustavo & Brito-Izquierdo, Isabel T. & Barquín-Diez, Jacinto, 2013. "Use of topographic predictors for macrobenthic community mapping in the Marine Reserve of La Palma (Canary Islands, Spain)," Ecological Modelling, Elsevier, vol. 263(C), pages 19-31.
    8. Václavík, Tomáš & Meentemeyer, Ross K., 2009. "Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?," Ecological Modelling, Elsevier, vol. 220(23), pages 3248-3258.
    9. Renata Pelissari & Sarah Ben Amor & Álvaro Oliveira D’Antona & Eduardo José Marandola Júnior & Leonardo Tomazeli Duarte, 2024. "A semi-supervised multi-criteria sorting approach to constructing social vulnerability composite indicators," Annals of Operations Research, Springer, vol. 337(1), pages 235-260, June.
    10. Tengyuan Liang & Weijie J. Su, 2019. "Statistical inference for the population landscape via moment‐adjusted stochastic gradients," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 81(2), pages 431-456, April.
    11. Christian E. Galarza & Panpan Zhang & Víctor H. Lachos, 2021. "Logistic Quantile Regression for Bounded Outcomes Using a Family of Heavy-Tailed Distributions," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 325-349, November.
    12. Anglin, Aaron H. & Wolfe, Marcus T. & Short, Jeremy C. & McKenny, Aaron F. & Pidduck, Robert J., 2018. "Narcissistic rhetoric and crowdfunding performance: A social role theory perspective," Journal of Business Venturing, Elsevier, vol. 33(6), pages 780-812.
    13. Coro, Gianpaolo & Pagano, Pasquale & Ellenbroek, Anton, 2013. "Combining simulated expert knowledge with Neural Networks to produce Ecological Niche Models for Latimeria chalumnae," Ecological Modelling, Elsevier, vol. 268(C), pages 55-63.
    14. Xu Gao & Babak Shahbaba & Hernando Ombao, 2018. "Modeling Binary Time Series Using Gaussian Processes with Application to Predicting Sleep States," Journal of Classification, Springer;The Classification Society, vol. 35(3), pages 549-579, October.
    15. Kwanda Sydwell Ngwenduna & Rendani Mbuvha, 2021. "Alleviating Class Imbalance in Actuarial Applications Using Generative Adversarial Networks," Risks, MDPI, vol. 9(3), pages 1-33, March.
    16. Rodrigues, Lucas dos Santos & Daudt, Nicholas Winterle & Cardoso, Luis Gustavo & Kinas, Paul Gerhard & Conesa, David & Pennino, Maria Grazia, 2023. "Species distribution modelling in the Southwestern Atlantic Ocean: A systematic review and trends," Ecological Modelling, Elsevier, vol. 486(C).
    17. Jonathan Boss & Alexander Rix & Yin‐Hsiu Chen & Naveen N. Narisetty & Zhenke Wu & Kelly K. Ferguson & Thomas F. McElrath & John D. Meeker & Bhramar Mukherjee, 2021. "A hierarchical integrative group least absolute shrinkage and selection operator for analyzing environmental mixtures," Environmetrics, John Wiley & Sons, Ltd., vol. 32(8), December.
    18. Coll, Marta & Steenbeek, Jeroen & Sole, Jordi & Palomera, Isabel & Christensen, Villy, 2016. "Modelling the cumulative spatial–temporal effects of environmental drivers and fishing in a NW Mediterranean marine ecosystem," Ecological Modelling, Elsevier, vol. 331(C), pages 100-114.
    19. Simon J Pittman & Kerry A Brown, 2011. "Multi-Scale Approach for Predicting Fish Species Distributions across Coral Reef Seascapes," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-12, May.
    20. Herkt, K. Matthias B. & Barnikel, Günter & Skidmore, Andrew K. & Fahr, Jakob, 2016. "A high-resolution model of bat diversity and endemism for continental Africa," Ecological Modelling, Elsevier, vol. 320(C), pages 9-28.

    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:323:y:2016:i:c:p:61-76. 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.