Predictive systems ecology

Type Article
Date 2013-11
Language English
Author(s) Evans Matthew R.1, Bithell Mike2, Cornell Stephen J.3, Dall Sasha R. X.4, Diaz Sandra5, 6, Emmott Stephen7, Ernande BrunoORCID8, Grimm Volker9, Hodgson David J.4, Lewis Simon L.10, Mace Georgina M.11, Morecroft Michael12, Moustakas Aristides1, Murphy Eugene13, Newbold Tim14, Norris K. J.15, Petchey Owen16, Smith Matthew7, Travis Justin M. J.17, Benton Tim G.18
Affiliation(s) 1 : Queen Mary Univ London, Sch Biol & Chem Sci, London E1 4NS, England.
2 : Univ Cambridge, Dept Geog, Cambridge CB2 3EN, England.
3 : Univ Liverpool, Inst Integrat Biol, Liverpool L69 7ZB, Merseyside, England.
4 : Univ Exeter, Coll Life & Environm Sci, Ctr Ecol & Conservat, Exeter TR10 9EZ, Devon, England.
5 : Univ Nacl Cordoba, Inst Multidisciplinario Biol Vegetal CONICET UNC, RA-5000 Cordoba, Argentina.
6 : Univ Nacl Cordoba, FCEFyN, RA-5000 Cordoba, Argentina.
7 : Microsoft Res, Computat Sci Lab, Cambridge CB1 2FB, England.
8 : IFREMER, Lab Ressources Halieut, F-62321 Boulogne Sur Mer, France.
9 : Helmhotz Ctr Environm Res, Dept Ecol Modelling, D-04318 Leipzig, Germany.
10 : Univ Leeds, Earth & Biosphere Inst, Leeds LS2 9JT, W Yorkshire, England.
11 : UCL, Dept Genet Evolut & Environm, Ctr Biodivers & Environm Res, London WC1E 6BT, England.
12 : Nat England, Winchester SO23 7BT, Hants, England.
13 : British Antarctic Survey, Cambridge CB3 0ET, England.
14 : World Conservat Monitoring Ctr, United Nations Environm Programme, Cambridge CB3 0DL, England.
15 : Univ Reading, Sch Agr Policy & Dev, Ctr Agrienvironm Res, Reading RG6 6AR, Berks, England.
16 : Univ Zurich, Inst Evolutionary Biol & Environm Studies, CH-8057 Zurich, Switzerland.
17 : Inst Biol & Environm Sci, Aberdeen AB24 2TZ, Scotland.
18 : Univ Leeds, Sch Biol, Leeds LS2 9JT, W Yorkshire, England.
Source Proceedings Of The Royal Society B-biological Sciences (0962-8452) (Royal Soc), 2013-11 , Vol. 280 , N. 1771 , P. -
DOI 10.1098/rspb.2013.1452
WOS© Times Cited 57
Keyword(s) modelling, systems ecology, climate change, ecosystem assessment
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.
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Evans Matthew R., Bithell Mike, Cornell Stephen J., Dall Sasha R. X., Diaz Sandra, Emmott Stephen, Ernande Bruno, Grimm Volker, Hodgson David J., Lewis Simon L., Mace Georgina M., Morecroft Michael, Moustakas Aristides, Murphy Eugene, Newbold Tim, Norris K. J., Petchey Owen, Smith Matthew, Travis Justin M. J., Benton Tim G. (2013). Predictive systems ecology. Proceedings Of The Royal Society B-biological Sciences, 280(1771), -. Publisher's official version : https://doi.org/10.1098/rspb.2013.1452 , Open Access version : https://archimer.ifremer.fr/doc/00177/28816/