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Constructing a hybrid species distribution model from standard large-scale distribution data

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  • Singer, Alexander
  • Schweiger, Oliver
  • Kühn, Ingolf
  • Johst, Karin

Abstract

Species range shifts under climate change have predominantly been projected by models correlating species observations with climatic conditions. However, geographic range shifting may depend on biotic factors such as demography, dispersal and species interactions. Recently suggested hybrid models include these factors. However, parameterization of hybrid models suffers from lack of detailed ecological data across many taxa. Further, it is methodologically unclear how to upscale ecological information from scales relevant to ecological processes to the coarser resolution of species distribution data (often 100 km2 or even 2500 km2). We tackle these problems by developing a novel modelling and calibration framework, which allows hybrid model calibration from (static) presence-absence data that is available for many species. The framework improves understanding of the influence of biotic processes on range projections and reveals critical sources of uncertainty that limit projection reliability. We demonstrate its performance for the case of the butterfly Titania’s Fritillary (Boloria titania).

Suggested Citation

  • Singer, Alexander & Schweiger, Oliver & Kühn, Ingolf & Johst, Karin, 2018. "Constructing a hybrid species distribution model from standard large-scale distribution data," Ecological Modelling, Elsevier, vol. 373(C), pages 39-52.
    • Handle: RePEc:eee:ecomod:v:373:y:2018:i:c:p:39-52
    DOI: 10.1016/j.ecolmodel.2018.02.002
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    References listed on IDEAS

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    1. Holloway, Paul & Miller, Jennifer A., 2017. "A quantitative synthesis of the movement concepts used within species distribution modelling," Ecological Modelling, Elsevier, vol. 356(C), pages 91-103.
    2. Singer, Alexander & Johst, Karin & Banitz, Thomas & Fowler, Mike S. & Groeneveld, Jürgen & Gutiérrez, Alvaro G. & Hartig, Florian & Krug, Rainer M. & Liess, Matthias & Matlack, Glenn & Meyer, Katrin M, 2016. "Community dynamics under environmental change: How can next generation mechanistic models improve projections of species distributions?," Ecological Modelling, Elsevier, vol. 326(C), pages 63-74.
    3. Jakoby, Oliver & Grimm, Volker & Frank, Karin, 2014. "Pattern-oriented parameterization of general models for ecological application: Towards realistic evaluations of management approaches," Ecological Modelling, Elsevier, vol. 275(C), pages 78-88.
    4. Buse, Jörn & Griebeler, Eva Maria, 2011. "Incorporating classified dispersal assumptions in predictive distribution models – A case study with grasshoppers and bush-crickets," Ecological Modelling, Elsevier, vol. 222(13), pages 2130-2141.
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    1. Barber-O'Malley, Betsy & Lassalle, Géraldine & Chust, Guillem & Diaz, Estibaliz & O'Malley, Andrew & Paradinas Blázquez, César & Pórtoles Marquina, Javier & Lambert, Patrick, 2022. "HyDiaD: A hybrid species distribution model combining dispersal, multi-habitat suitability, and population dynamics for diadromous species under climate change scenarios," Ecological Modelling, Elsevier, vol. 470(C).

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