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Deriving simple predictions from complex models to support environmental decision-making

Author

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  • Stillman, Richard A.
  • Wood, Kevin A.
  • Goss-Custard, John D.

Abstract

Recent decades have seen great advances in ecological modelling and computing power, enabling ecologists to build increasingly detailed models to more accurately represent ecological systems. To better inform environmental decision-making, it is important that the predictions of these models are expressed in simple ways that are straightforward for stakeholders to comprehend and use. One way to achieve this is to predict threshold values for environmental perturbations (e.g. climate change, habitat modification, food loss, sea level rise) associated with negative impacts on individuals, populations, communities or ecosystems. These thresholds can be used by stakeholders to inform management and policy. In this paper we demonstrate how this approach can use individual-based models of birds, their prey and habitats, to provide the evidence-base for coastal bird conservation and shellfishery management. In particular, we show how such models can be used to identify threshold values for perturbations of food abundance that can impact negatively on bird populations. We highlight how environmental thresholds could be used more widely to inform management of species and habitats under environmental change.

Suggested Citation

  • Stillman, Richard A. & Wood, Kevin A. & Goss-Custard, John D., 2016. "Deriving simple predictions from complex models to support environmental decision-making," Ecological Modelling, Elsevier, vol. 326(C), pages 134-141.
  • Handle: RePEc:eee:ecomod:v:326:y:2016:i:c:p:134-141
    DOI: 10.1016/j.ecolmodel.2015.04.014
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    References listed on IDEAS

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    1. West, Andrew D. & Yates, Michael G. & McGrorty, Selwyn & Stillman, Richard A., 2007. "Predicting site quality for shorebird communities: A case study on the Wash embayment, UK," Ecological Modelling, Elsevier, vol. 202(3), pages 527-539.
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    Cited by:

    1. Cunha-Santino, Marcela B. & Fushita, Ângela T. & Bianchini, Irineu, 2017. "A modeling approach for a cascade of reservoirs in the Juquiá-Guaçu River (Atlantic Forest, Brazil)," Ecological Modelling, Elsevier, vol. 356(C), pages 48-58.
    2. Grimm, Volker & Berger, Uta, 2016. "Structural realism, emergence, and predictions in next-generation ecological modelling: Synthesis from a special issue," Ecological Modelling, Elsevier, vol. 326(C), pages 177-187.

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