IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v390y2018icp79-87.html
   My bibliography  Save this article

Using macroecological constraints on spatial biodiversity predictions under climate change: the modelling method matters

Author

Listed:
  • Di Febbraro, Mirko
  • D’Amen, Manuela
  • Raia, Pasquale
  • De Rosa, Davide
  • Loy, Anna
  • Guisan, Antoine

Abstract

The prevailing method for estimating the potential impact of future climate change on biological communities is to stack binary predictions from species distribution models (binary stacked species distribution models, bS-SDM). However, it has been argued that bS-SDM may overestimate species richness and, hence, community composition. Alternative approaches, such as SESAM (‘Spatially Explicit Species Assemblage Modelling’), explicitly incorporate limits to species richness, preventing overestimation. We compared richness and taxonomic composition estimates as predicted by SESAM and bS-SDM for Mediterranean bird communities both in the present day and as projected in the future under simulated climate change scenarios. We trained single-species distribution models (S-SDM) and direct macroecological richness models (MEM) for 81 bird species, using climate, topographic, land-use and human-pressure indicators as predictors. Then, we compared and evaluated the models’ predictions. Species richness as predicted by bS-SDM was more accurate than under SESAM for present-day communities. Taxonomic composition was well predicted under both methods. However, we detected significant differences in future projections. Under bS-SDM, increased suitable area for a number of species leads to important changes in community composition and predicts higher levels of diversity in the future. In stark contrast, SESAM predicts lower species richness in the future and strong homogenization of bird communities across space. This study shows how the choice of the modelling approach drives substantially different expectations about future community composition under climate change. We therefore recommend contrasting predictions generated under different modelling approaches to gain better understanding of possible future scenario of biodiversity change. In addition, trasferability tests (i.e. hindcasting to past or predicting from the past to the present) should be used to effectively compare S-SDM and SESAM predictive abilities.

Suggested Citation

  • Di Febbraro, Mirko & D’Amen, Manuela & Raia, Pasquale & De Rosa, Davide & Loy, Anna & Guisan, Antoine, 2018. "Using macroecological constraints on spatial biodiversity predictions under climate change: the modelling method matters," Ecological Modelling, Elsevier, vol. 390(C), pages 79-87.
    • Handle: RePEc:eee:ecomod:v:390:y:2018:i:c:p:79-87
    DOI: 10.1016/j.ecolmodel.2018.10.023
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380018303600
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2018.10.023?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. Rubén G Mateo & Ángel M Felicísimo & Julien Pottier & Antoine Guisan & Jesús Muñoz, 2012. "Do Stacked Species Distribution Models Reflect Altitudinal Diversity Patterns?," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-9, March.
    2. Maggini, Ramona & Lehmann, Anthony & Kéry, Marc & Schmid, Hans & Beniston, Martin & Jenni, Lukas & Zbinden, Niklaus, 2011. "Are Swiss birds tracking climate change?," Ecological Modelling, Elsevier, vol. 222(1), pages 21-32.
    3. Steinmann, K. & Linder, H.P. & Zimmermann, N.E., 2009. "Modelling plant species richness using functional groups," Ecological Modelling, Elsevier, vol. 220(7), pages 962-967.
    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. Bazzato, Erika & Rosati, Leonardo & Canu, Simona & Fiori, Michele & Farris, Emmanuele & Marignani, Michela, 2021. "High spatial resolution bioclimatic variables to support ecological modelling in a Mediterranean biodiversity hotspot," Ecological Modelling, Elsevier, vol. 441(C).
    2. Mateo, Rubén G. & Arellano, Gabriel & Gómez-Rubio, Virgilio & Tello, J. Sebastián & Fuentes, Alfredo F. & Cayola, Leslie & Loza, M. Isabel & Cala, Victoria & Macía, Manuel J., 2022. "Insights on biodiversity drivers to predict species richness in tropical forests at the local scale," Ecological Modelling, Elsevier, vol. 473(C).
    3. Mirko Di Febbraro & Ludovico Frate & Maria Carla de Francesco & Angela Stanisci & Francesco Pio Tozzi & Marco Varricchione & Maria Laura Carranza, 2021. "Modelling Beach Litter Accumulation on Mediterranean Coastal Landscapes: An Integrative Framework Using Species Distribution Models," Land, MDPI, vol. 10(1), pages 1-17, January.
    4. He, Pinglin & Zhang, Shuhao & Wang, Lei & Ning, Jing, 2023. "Will environmental taxes help to mitigate climate change? A comparative study based on OECD countries," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1440-1464.

    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. Nicoletta Cannone & M. Guglielmin & P. Convey & M. R. Worland & S. E. Favero Longo, 2016. "Vascular plant changes in extreme environments: effects of multiple drivers," Climatic Change, Springer, vol. 134(4), pages 651-665, February.
    2. 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.
    3. Mateo, Rubén G. & Arellano, Gabriel & Gómez-Rubio, Virgilio & Tello, J. Sebastián & Fuentes, Alfredo F. & Cayola, Leslie & Loza, M. Isabel & Cala, Victoria & Macía, Manuel J., 2022. "Insights on biodiversity drivers to predict species richness in tropical forests at the local scale," Ecological Modelling, Elsevier, vol. 473(C).
    4. Diego Lizana-Ciudad & Víctor J. Colino-Rabanal & Óscar J. Arribas & Miguel Lizana, 2021. "Connectivity Predicts Presence but Not Population Density in the Habitat-Specific Mountain Lizard Iberolacerta martinezricai," Sustainability, MDPI, vol. 13(5), pages 1-14, March.
    5. Cormont, Anouk & Wieger Wamelink, G.W. & Jochem, René & WallisDeVries, Michiel F. & Wegman, Ruut M.A., 2013. "Host plant-mediated effects of climate change on the occurrence of the Alcon blue butterfly (Phengaris alcon)," Ecological Modelling, Elsevier, vol. 250(C), pages 329-337.
    6. Nicoletta Cannone & M. Guglielmin & P. Convey & M. Worland & S. Favero Longo, 2016. "Vascular plant changes in extreme environments: effects of multiple drivers," Climatic Change, Springer, vol. 134(4), pages 651-665, February.
    7. Nicoletta Cannone & Sandro Pignatti, 2014. "Ecological responses of plant species and communities to climate warming: upward shift or range filling processes?," Climatic Change, Springer, vol. 123(2), pages 201-214, March.
    8. Cao, Yong & DeWalt, R. Edward & Robinson, Jason L. & Tweddale, Tari & Hinz, Leon & Pessino, Massimo, 2013. "Using Maxent to model the historic distributions of stonefly species in Illinois streams: The effects of regularization and threshold selections," Ecological Modelling, Elsevier, vol. 259(C), pages 30-39.

    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:390:y:2018:i:c:p:79-87. 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.