Overcoming data constraints to create meaningful ecological models

Rebecca Lester, Peter Fairweather

    Research output: Contribution to conferencePaperpeer-review


    Many techniques used to model ecosystems cannot be meaningfully applied to large-scale ecological problems due to data constraints. Disparate collection methods, data types and incomplete data sets, or limited theoretical understanding mean that a wide range of modelling techniques used to model physical processes or for problems specific to species or populations cannot be used at an ecosystem scale. In developing an ecological response model for the Coorong, a South Australian hypersaline estuary, we combined several flexible modelling approaches in a statistical framework to develop an approach we call 'ecosystem states'. This model uses simulated hydrodynamic conditions as input to predict one of a suite of states per space and time, allowing prediction of likely ecological conditions under a variety of scenarios. Each ecosystem state has defined sets of biota and physico-chemical parameters. The existing model is limited in that its predictions have yet to be tested and, as yet, no spatial or temporal connectivity has been incorporated into simulated time series of ecosystem states. This approach can be used in a wide range of ecosystems, where enough data are available to model ecosystem states. We are in the process of applying the technique to a nearby lake system. This has been more difficult than for the Coorong as there is little overlap in the spatial and temporal coverage of biological data sets for that region. The approach is robust to low-quality biological data and missing environmental data, so should suit situations where community or management monitoring programs have occurred through time.

    Original languageEnglish
    Number of pages9
    Publication statusPublished - 1 Dec 2010
    Event2010 International Conference on Environmental Modelling and Software, 5th Biennial Meeting -
    Duration: 5 Jul 2010 → …


    Conference2010 International Conference on Environmental Modelling and Software, 5th Biennial Meeting
    Period5/07/10 → …


    • Data limitations
    • Ecological response models
    • Statistical modelling


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