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Simple or complex: Relative impact of data availability and model purpose on the choice of model types for population viability analyses

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  • Radchuk, Viktoriia
  • Oppel, Steffen
  • Groeneveld, Jürgen
  • Grimm, Volker
  • Schtickzelle, Nicolas

Abstract

Population viability analysis (PVA) models are used to estimate population extinction risk under different scenarios. Both simple and complex PVA models are developed and have their specific pros and cons; the question therefore arises whether we always use the most appropriate model type. Generally, the specific purpose of a model and the availability of data are listed as determining the choice of model type, but this has not been formally tested yet. We quantified the relative importance of model purpose and nine metrics of data availability and resolution for the choice of a PVA model type, while controlling for effects of the different life histories of the modelled species. We evaluated 37 model pairs: each consisting of a generally simpler, population-based model (PBM) and a more complex, individual-based model (IBM) developed for the same species. The choice of model type was primarily affected by the availability and resolution of demographic, dispersal and spatial data. Low-resolution data resulted in the development of less complex models. Model purpose did not affect the choice of the model type. We confirm the general assumption that poor data availability is the main reason for the wide use of simpler models, which may have limited predictive power for population responses to changing environmental conditions. Conservation biology is a crisis discipline where researchers learned to work with the data at hand. However, for threatened and poorly-known species, there is no short-cut when developing either a PBM or an IBM: investments to collect appropriately detailed data are required to ensure PVA models can assess extinction risk under complex environmental conditions.

Suggested Citation

  • Radchuk, Viktoriia & Oppel, Steffen & Groeneveld, Jürgen & Grimm, Volker & Schtickzelle, Nicolas, 2016. "Simple or complex: Relative impact of data availability and model purpose on the choice of model types for population viability analyses," Ecological Modelling, Elsevier, vol. 323(C), pages 87-95.
  • Handle: RePEc:eee:ecomod:v:323:y:2016:i:c:p:87-95
    DOI: 10.1016/j.ecolmodel.2015.11.022
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    References listed on IDEAS

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    1. Frank, Béatrice M. & Baret, Philippe V., 2013. "Simulating brown trout demogenetics in a river/nursery brook system: The individual-based model DemGenTrout," Ecological Modelling, Elsevier, vol. 248(C), pages 184-202.
    2. Mantzouni, Irene & Somarakis, Stylianos & Moutopoulos, Dimitrios K. & Kallianiotis, Argyris & Koutsikopoulos, Constantin, 2007. "Periodic, spatially structured matrix model for the study of anchovy (Engraulis encrasicolus) population dynamics in N Aegean Sea (E. Mediterranean)," Ecological Modelling, Elsevier, vol. 208(2), pages 367-377.
    3. Radchuk, Viktoriia & Johst, Karin & Groeneveld, Jürgen & Grimm, Volker & Schtickzelle, Nicolas, 2013. "Behind the scenes of population viability modeling: Predicting butterfly metapopulation dynamics under climate change," Ecological Modelling, Elsevier, vol. 259(C), pages 62-73.
    4. Sable, Shaye E. & Rose, Kenneth A., 2008. "A comparison of individual-based and matrix projection models for simulating yellow perch population dynamics in Oneida Lake, New York, USA," Ecological Modelling, Elsevier, vol. 215(1), pages 105-121.
    5. Meli, Mattia & Palmqvist, Annemette & Forbes, Valery E. & Groeneveld, Jürgen & Grimm, Volker, 2014. "Two pairs of eyes are better than one: Combining individual-based and matrix models for ecological risk assessment of chemicals," Ecological Modelling, Elsevier, vol. 280(C), pages 40-52.
    6. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    7. Vanoverbeke, Joost, 2008. "Modeling individual and population dynamics in a consumer–resource system: Behavior under food limitation and crowding and the effect on population cycling in Daphnia," Ecological Modelling, Elsevier, vol. 216(3), pages 385-401.
    8. Billoir, Elise & Péry, Alexandre R.R. & Charles, Sandrine, 2007. "Integrating the lethal and sublethal effects of toxic compounds into the population dynamics of Daphnia magna: A combination of the DEBtox and matrix population models," Ecological Modelling, Elsevier, vol. 203(3), pages 204-214.
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    1. Trapp, Stephanie E. & Day, Casey C. & Flaherty, Elizabeth A. & Zollner, Patrick A. & Smith, Winston P., 2019. "Modeling impacts of landscape connectivity on dispersal movements of northern flying squirrels (Glaucomys sabrinus griseifrons)," Ecological Modelling, Elsevier, vol. 394(C), pages 44-52.
    2. Halsey, Samniqueka J. & Cinel, Scott & Wilson, Jared & Bell, Timothy J. & Bowles, Marlin, 2017. "Predicting population viability of a monocarpic perennial dune thistle using individual-based models," Ecological Modelling, Elsevier, vol. 359(C), pages 363-371.

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