IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v449y2021ics0304380021000727.html
   My bibliography  Save this article

Which spatial interpolators I should use? A case study applying to marine species

Author

Listed:
  • Rufino, Marta M.
  • Albouy, Camille
  • Brind'Amour, Anik

Abstract

Species are spread in space, whereas sampling is sparse. Thus, to describe and map along environmental gradients, it is necessary to interpolate the species abundance. Considering the plethora of valid methods, the researcher gets easily puzzled to choose the most appropriate interpolation approach with reference to the ecological question being asked.

Suggested Citation

  • Rufino, Marta M. & Albouy, Camille & Brind'Amour, Anik, 2021. "Which spatial interpolators I should use? A case study applying to marine species," Ecological Modelling, Elsevier, vol. 449(C).
  • Handle: RePEc:eee:ecomod:v:449:y:2021:i:c:s0304380021000727
    DOI: 10.1016/j.ecolmodel.2021.109501
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380021000727
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2021.109501?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. Jin Li, 2017. "Assessing the accuracy of predictive models for numerical data: Not r nor r2, why not? Then what?," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-16, August.
    2. Tomislav Hengl & Gerard B M Heuvelink & Bas Kempen & Johan G B Leenaars & Markus G Walsh & Keith D Shepherd & Andrew Sila & Robert A MacMillan & Jorge Mendes de Jesus & Lulseged Tamene & Jérôme E Tond, 2015. "Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-26, June.
    3. Nicole H. Augustin & Verena M. Trenkel & Simon N. Wood & Pascal Lorance, 2013. "Space‐time modelling of blue ling for fisheries stock management," Environmetrics, John Wiley & Sons, Ltd., vol. 24(2), pages 109-119, March.
    4. Marta Mega Rufino & Nicolas Bez & Anik Brind’Amour, 2018. "Integrating spatial indicators in the surveillance of exploited marine ecosystems," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-21, November.
    5. Austin, Mike, 2007. "Species distribution models and ecological theory: A critical assessment and some possible new approaches," Ecological Modelling, Elsevier, vol. 200(1), pages 1-19.
    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. Santiago José Elías Velazco & Franklin Galvão & Fabricio Villalobos & Paulo De Marco Júnior, 2017. "Using worldwide edaphic data to model plant species niches: An assessment at a continental extent," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-24, October.
    2. Laura M. Sangalli, 2021. "Spatial Regression With Partial Differential Equation Regularisation," International Statistical Review, International Statistical Institute, vol. 89(3), pages 505-531, December.
    3. 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.
    4. Meyer, Maximilian & Hulke, Carolin & Kamwi, Jonathan & Kolem, Hannah & Börner, Jan, 2022. "Spatially heterogeneous effects of collective action on environmental dependence in Namibia’s Zambezi region," World Development, Elsevier, vol. 159(C).
    5. Muñoz-Mas, Rafael & Vezza, Paolo & Alcaraz-Hernández, Juan Diego & Martínez-Capel, Francisco, 2016. "Risk of invasion predicted with support vector machines: A case study on northern pike (Esox Lucius, L.) and bleak (Alburnus alburnus, L.)," Ecological Modelling, Elsevier, vol. 342(C), pages 123-134.
    6. Sabastine Ugbemuna Ugbaje & Thomas F.A. Bishop, 2020. "Hydrological Control of Vegetation Greenness Dynamics in Africa: A Multivariate Analysis Using Satellite Observed Soil Moisture, Terrestrial Water Storage and Precipitation," Land, MDPI, vol. 9(1), pages 1-15, January.
    7. Meineri, Eric & Dahlberg, C. Johan & Hylander, Kristoffer, 2015. "Using Gaussian Bayesian Networks to disentangle direct and indirect associations between landscape physiography, environmental variables and species distribution," Ecological Modelling, Elsevier, vol. 313(C), pages 127-136.
    8. Marmion, Mathieu & Luoto, Miska & Heikkinen, Risto K. & Thuiller, Wilfried, 2009. "The performance of state-of-the-art modelling techniques depends on geographical distribution of species," Ecological Modelling, Elsevier, vol. 220(24), pages 3512-3520.
    9. Kaiping Wang & Weiqi Wang & Niyi Zha & Yue Feng & Chenlan Qiu & Yunlu Zhang & Jia Ma & Rui Zhang, 2022. "Spatially Heterogeneity Response of Critical Ecosystem Service Capacity to Address Regional Development Risks to Rapid Urbanization: The Case of Beijing-Tianjin-Hebei Urban Agglomeration in China," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
    10. Sellami, Mohamed Habib & Sifaoui, Mohamed Salah, 2008. "Modelling of heat and mass transfer inside a traditional oasis: Experimental validation," Ecological Modelling, Elsevier, vol. 210(1), pages 144-154.
    11. Joachim Eisenberg & Fabrice A. Muvundja, 2020. "Quantification of Erosion in Selected Catchment Areas of the Ruzizi River (DRC) Using the (R)USLE Model," Land, MDPI, vol. 9(4), pages 1-18, April.
    12. Chantal M. J. Hendriks & Harry S. Gibson & Anna Trett & André Python & Daniel J. Weiss & Anton Vrieling & Michael Coleman & Peter W. Gething & Penny A. Hancock & Catherine L. Moyes, 2019. "Mapping Geospatial Processes Affecting the Environmental Fate of Agricultural Pesticides in Africa," IJERPH, MDPI, vol. 16(19), pages 1-22, September.
    13. Di Traglia, Mario & Attorre, Fabio & Francesconi, Fabio & Valenti, Roberto & Vitale, Marcello, 2011. "Is cellular automata algorithm able to predict the future dynamical shifts of tree species in Italy under climate change scenarios? A methodological approach," Ecological Modelling, Elsevier, vol. 222(4), pages 925-934.
    14. Mouton, Ans M. & De Baets, Bernard & Goethals, Peter L.M., 2010. "Ecological relevance of performance criteria for species distribution models," Ecological Modelling, Elsevier, vol. 221(16), pages 1995-2002.
    15. Menafoglio, Alessandra & Secchi, Piercesare, 2017. "Statistical analysis of complex and spatially dependent data: A review of Object Oriented Spatial Statistics," European Journal of Operational Research, Elsevier, vol. 258(2), pages 401-410.
    16. Carlos Manuel Hernández & Aliou Faye & Mamadou Ousseynou Ly & Zachary P. Stewart & P. V. Vara Prasad & Leonardo Mendes Bastos & Luciana Nieto & Ana J. P. Carcedo & Ignacio Antonio Ciampitti, 2021. "Soil and Climate Characterization to Define Environments for Summer Crops in Senegal," Sustainability, MDPI, vol. 13(21), pages 1-17, October.
    17. Aertsen, Wim & Kint, Vincent & van Orshoven, Jos & Özkan, Kürşad & Muys, Bart, 2010. "Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests," Ecological Modelling, Elsevier, vol. 221(8), pages 1119-1130.
    18. Ravic Nijbroek & Kristin Piikki & Mats Söderström & Bas Kempen & Katrine G. Turner & Simeon Hengari & John Mutua, 2018. "Soil Organic Carbon Baselines for Land Degradation Neutrality: Map Accuracy and Cost Tradeoffs with Respect to Complexity in Otjozondjupa, Namibia," Sustainability, MDPI, vol. 10(5), pages 1-20, May.
    19. Leroux, L. & Falconnier, G.N. & Diouf, A.A. & Ndao, B. & Gbodjo, J.E. & Tall, L. & Balde, A.A. & Clermont-Dauphin, C. & Bégué, A. & Affholder, F. & Roupsard, O., 2020. "Using remote sensing to assess the effect of trees on millet yield in complex parklands of Central Senegal," Agricultural Systems, Elsevier, vol. 184(C).
    20. Lyndsie S Wszola & Victoria L Simonsen & Erica F Stuber & Caitlyn R Gillespie & Lindsey N Messinger & Karie L Decker & Jeffrey J Lusk & Christopher F Jorgensen & Andrew A Bishop & Joseph J Fontaine, 2017. "Translating statistical species-habitat models to interactive decision support tools," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-13, 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:eee:ecomod:v:449:y:2021:i:c:s0304380021000727. 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.