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Marine Ecology Progress Series

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MEPS 413:291-304 (2010)  -  DOI:

Predicting future ecological degradation based on modelled thresholds

Peter G. Fairweather*, Rebecca E. Lester

School of Biological Sciences, Flinders University, GPO Box 2100, Adelaide, South Australia 5001, Australia

ABSTRACT: Threshold models are becoming important in determining the ecological consequences of our actions within the environment and have a key role in setting bounds on targets used by natural resource managers. We have been using thresholds and related concepts adapted from the multiple stable-states literature to model ecosystem response in the Coorong, the estuary for Australia’s largest river. Our modelling approach is based upon developing a state-and-transition model, with the states defined by the biota and the transitions defined by a classification and regression tree (CART) analysis of the environmental data for the region. Here we explore the behaviour of thresholds within that model. Managers tend to plan for a set of often arbitrarily-derived thresholds in their natural resource management. We attempt to assess how the precision afforded by analyses such as CART translates into ecological outcomes, and explicitly trial several approaches to understanding thresholds and transitions in our model and how they might be relevant for management. We conclude that the most promising approach would be a mixture of further modelling (using past behaviour to predict future degradation) in conjunction with targeted experiments to confirm the results. Our case study of the Coorong is further developed, particularly for the modelling stages of the protocol, to provide recommendations to improve natural resource management strategies that are currently in use.

KEY WORDS: Coorong · Ecosystem states · Empirical anticipation · Environmental futures · Physico-chemical transitions · South Australia · Statistical modelling · Water allocation

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Cite this article as: Fairweather PG, Lester RE (2010) Predicting future ecological degradation based on modelled thresholds. Mar Ecol Prog Ser 413:291-304.

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