Skip to content

Research at St Andrews

Fitting complex ecological point process models with integrated nested Laplace approximation

Research output: Contribution to journalArticle

Author(s)

Janine Baerbel Illian, Sara Martino, Sigrunn H. Sørbye, Juan B. Gallego-Fernández, Maria Zunzunegui, M. Paz Esquivias, Justin M. Travis

School/Research organisations

Abstract

Summary
1. We highlight an emerging statistical method, integrated nested Laplace approximation (INLA), which is ideally suited for fitting complex models to many of the rich spatial data sets that ecologists wish to analyse.
2. INLA is an approximation method that nevertheless provides very exact estimates. In this article, we describe the INLA methodology highlighting where it offers opportunities for drawing inference from (spatial) ecological data that would previously have been too complex to make practical model fitting feasible.
3. We use INLA to fit a complex joint model to the spatial pattern formed by a plant species, Thymus carnosus, as well as to the health status of each individual.
4. The key ecological result revealed by our spatial analysis of these data, relates to the distance-to-water covariate. We find that T. carnosus plants are generally healthier when they are further away from the water.
5. We suggest that this may be the result of a combination of (1) plants having alternative rooting strategies depending on how close to water they grow and (2) the rooting strategy determining how well the plants were able to tolerate an unusually dry summer.
6. We anticipate INLA becoming widely used within spatial ecological analysis over the next decade and suggest that both ecologists and statisticians will benefit greatly from working collaboratively to further develop and apply these emerging statistical methods.
Close

Details

Original languageEnglish
Pages (from-to)305-315
Number of pages11
JournalMethods in Ecology and Evolution
Volume4
Issue number4
Early online date19 Feb 2013
DOIs
Publication statusPublished - Apr 2013

    Research areas

  • Marked point patterns, Spatial modelling, Log-Gaussian Cox processes

Discover related content
Find related publications, people, projects and more using interactive charts.

View graph of relations

Related by author

  1. inlabru: an R package for Bayesian spatial modelling from ecological survey data

    Bachl, F. E., Lindgren, F., Borchers, D. L. & Illian, J. B., 21 Mar 2019, In : Methods in Ecology and Evolution. Early View, 7 p.

    Research output: Contribution to journalArticle

  2. Understanding species distribution in dynamic populations: a new approach using spatio‐temporal point process models

    Soriano-Redondo, A., Jones-Todd, C. M., Bearhop, S., Hilton, G. M., Lock, L., Stanbury, A., Votier, S. C. & Illian, J. B., 4 Mar 2019, In : Ecography. Early View

    Research output: Contribution to journalArticle

  3. Non-stationary Gaussian models with physical barriers

    Bakka, H., Vanhatalo, J., Illian, J. B., Simpson, D. & Rue, H., 18 Jan 2019, In : Spatial Statistics. In press

    Research output: Contribution to journalArticle

  4. Accounting for preferential sampling in species distribution models

    Pennino, M. G., Paradinas, I., Illian, J. B., Muñoz, F., Bellido, J. M., López-Quílez, A. & Conesa, D., 1 Jan 2019, In : Ecology and Evolution. 9, 1, p. 653-663 11 p.

    Research output: Contribution to journalArticle

  5. Level set Cox processes

    Hildeman, A., Bolin, D., Wallin, J. & Illian, J. B., Dec 2018, In : Spatial Statistics. 28, p. 169-193

    Research output: Contribution to journalArticle

Related by journal

  1. A 2.6-gram sound and movement tag for studying the acoustic scene and kinematics of echolocating bats

    Stidsholt, L., Johnson, M., Beedholm, K., Jakobsen, L., Kugler, K., Brinkløv, S., Salles, A., Moss, C. F. & Madsen, P. T., Jan 2019, In : Methods in Ecology and Evolution. 10, 1, p. 48-58 11 p.

    Research output: Contribution to journalArticle

  2. Model selection with overdispersed distance sampling data

    Howe, E. J., Buckland, S. T., Després-Einspenner, M-L. & Kühl, H. S., Jan 2019, In : Methods in Ecology and Evolution. 10, 1, p. 38-47

    Research output: Contribution to journalArticle

  3. State-switching continuous-time correlated random walks

    Michelot, T. & Blackwell, P. G., 14 Feb 2019, In : Methods in Ecology and Evolution. Early View

    Research output: Contribution to journalArticle

  4. inlabru: an R package for Bayesian spatial modelling from ecological survey data

    Bachl, F. E., Lindgren, F., Borchers, D. L. & Illian, J. B., 21 Mar 2019, In : Methods in Ecology and Evolution. Early View, 7 p.

    Research output: Contribution to journalArticle

  5. Estimating effective detection area of static passive acoustic data loggers from playback experiments with cetacean vocalisations

    Nuuttila, H. K., Brundiers, K., Dähne, M., Koblitz, J. C., Thomas, L., Courtene-Jones, W., Evans, P. G. H., Turner, J. R., Bennell, J. D. & Hiddink, J. G., Dec 2018, In : Methods in Ecology and Evolution. 9, 12, p. 2362-2371

    Research output: Contribution to journalArticle

Related by journal

  1. Methods in Ecology and Evolution (Journal)

    Michael Blair Morrissey (Member of editorial board)
    1 Jan 20171 Jan 2020

    Activity: Publication peer-review and editorial work typesEditor of research journal

  2. Methods in Ecology and Evolution (Journal)

    Theoni Photopoulou (Editor)
    2017 → …

    Activity: Publication peer-review and editorial work typesEditor of research journal

  3. Methods in Ecology and Evolution (Journal)

    Oscar Eduardo Gaggiotti (Member of editorial board)
    1 Sep 2014 → …

    Activity: Publication peer-review and editorial work typesEditor of research journal

ID: 46184216