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Abstract:
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Quantifying aspects of dependence within a food web/ecological network (EN) has largely been descriptive or deterministic. Existing schemes to assess reliability of such quantification are often non-statistical. This paper focuses on understanding ENs in the context of mass balance. Our statistical inferential approach employs Bayesian melding, and embodies the traditional deterministic views on network relations; yet, it is developed for the estimation of physical quantities and assessment of the estimation, both from a statistical perspective. The result is a more honest representation of the true state of nature, and the ability to formally assess balance before data are passed on to later stages of an EN analysis (ENA). We also find that general Bayesian inference for ENA can yield new ecological insight that may not be available through standard classical inference.
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