Predictive systems ecology

Author:

Evans Matthew R.1,Bithell Mike2,Cornell Stephen J.3,Dall Sasha R. X.4,Díaz Sandra5,Emmott Stephen6,Ernande Bruno7,Grimm Volker8,Hodgson David J.4,Lewis Simon L.9,Mace Georgina M.10,Morecroft Michael11,Moustakas Aristides1,Murphy Eugene12,Newbold Tim13,Norris K. J.14,Petchey Owen15,Smith Matthew6,Travis Justin M. J.16,Benton Tim G.17

Affiliation:

1. School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK

2. Department of Geography, University of Cambridge, Downing Place, Cambridge CB2 3EN, UK

3. Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK

4. Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Cornwall Campus TR10 9EZ, UK

5. Instituto Multidisciplinario de BiologíaVegetal (CONICET-UNC) and FCEFyN, Universidad Nacional de Córdoba, Casilla de Correo 495, Córdoba 5000, Argentina

6. Computational Science Laboratory, Microsoft Research, 21 Station Road, Cambridge CB1 2FB, UK

7. IFREMER, Laboratorie Ressources Halieutiques, 150 quai Gambetta, BP 699, Boulogne-sur-Mer 62321, France

8. Helmhotz Center for Environmental Research, Department of Ecological Modelling, Permoserstrasse 15, Leipzig 04318, Germany

9. Earth and Biosphere Institute, University of Leeds, Woodhouse Lane, Leeds LS2 9JT, UK

10. Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, Darwin Building, Gower Street, London WC1E 6BT, UK

11. Natural England, Cromwell House, Andover Road, Winchester SO23 7BT, UK

12. British Antarctic Survey, Madingley Road, High Cross, Cambridge CB3 0ET, UK

13. United Nations Environment Programme World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge CB3 0DL, UK

14. Centre for Agri-Environmental Research, School of Agriculture, Policy and Development, The University of Reading, Earley Gate, PO Box 237, Reading RG6 6AR, UK

15. Institute of Evolutionary Biology and Environmental Studies, University of Zurich, Winterhurerstrasse 190, Zurich 8057, Switzerland

16. Institute of Biological and Environmental Sciences, Zoology Building, Tillydrone Avenue, Aberdeen AB24 2TZ, UK

17. School of Biology, University of Leeds, Leeds LS2 9JT, UK

Abstract

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Environmental Science,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

Reference137 articles.

1. Haines-Young R et al. 2011 The UK NEA scenarios: development of storylines and analysis of outcomes in the UK National Ecosystem Assessment technical report . UK National Ecosystem Assessment . Cambridge UK: UNEP-WCMC.

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