Predicting novel riparian ecosystems in a changing climate

Catford, Jane, Naiman, Robert J., Chambers, Lynda E., Roberts, Jane, Douglas, Michael and Davies, Peter (2013) Predicting novel riparian ecosystems in a changing climate. Ecosystems, 16 (3), 382-400. (doi:10.1007/s10021-012-9566-7).

Abstract

Rapid changes in global climate are likely to alter species assemblages and environmental characteristics resulting in novel ecosystems. The ability to predict characteristics of future ecosystems is crucial for environmental planning and the development of effective climate change adaptation strategies. This paper presents an approach for envisioning novel ecosystems in future climates. Focusing on riparian ecosystems, we use qualitative process models to predict likely abiotic and biotic changes in four case study systems: tropical coastal floodplains, temperate streams, high mountain streams and urban riparian zones. We concentrate on functional groups rather than individual species and consider dispersal constraints and the capacity for genetic adaptation. Our scenarios suggest that climatic changes will reduce indigenous diversity, facilitate non-indigenous invasion (especially C4 graminoids), increase fragmentation and result in simplified and less distinctive riparian ecosystems. Compared to models based on biota-environment correlations, process models built on mechanistic understanding (like Bayesian belief networks) are more likely to remain valid under novel climatic conditions. We posit that predictions based on species’ functional traits will facilitate regional comparisons and can highlight effects of climate change on ecosystem structure and function. Ecosystems that have experienced similar modification to that expected under climate change (for example, altered flow regimes of regulated rivers) can be used to help inform and evaluate predictions. By manipulating attributes of these system models (for example, magnitude of climatic changes or adaptation strategies used), implications of various scenarios can be assessed and optimal management strategies identified.

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Contributors

Author: Jane Catford

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