Predictive systems ecology

Matthew R. Evans; Mike Bithell; Stephen J. Cornell; Sasha R. X. Dall; Sandra Diaz; Stephen Emmott; Bruno Ernande; Volker Grimm; David J. Hodgson; Simon L. Lewis; Georgina M. Mace; Michael Morecroft; Aristides Moustakas; Eugene Murphy; Tim Newbold; K. J. Norris; Owen Petchey; Matthew Smith; Justin M. J. Travis; Tim G. Benton

doi:10.1098/rspb.2013.1452

Predictive systems ecology

Matthew R. Evans^*, Mike Bithell, Stephen J. Cornell, Sasha R. X. Dall, Sandra Diaz, Stephen Emmott, Bruno Ernande, Volker Grimm, David J. Hodgson, Simon L. Lewis, Georgina M. Mace, Michael Morecroft, Aristides Moustakas, Eugene Murphy, Tim Newbold, K. J. Norris, Owen Petchey, Matthew Smith, Justin M. J. Travis, Tim G. Benton

^*Corresponding author for this work

Research output: Contribution to journal › Literature review › peer-review

117 Citations (Scopus)

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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.

Original language	English
Article number	20131452
Number of pages	9
Journal	Proceedings of the Royal Society of London. B, Biological Sciences
Volume	280
Issue number	1771
Early online date	2 Oct 2013
DOIs	https://doi.org/10.1098/rspb.2013.1452
Publication status	Published - 22 Nov 2013

Keywords

modelling
systems ecology
climate change
ecosystem assessment
end-to-end
terrestrial biosphere model
krill euphausia-superba
agent-based models
climate-change
Scotia Sea
population-dynamics
marine ecosystems
forest dynamics
global change

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1098/rspb.2013.1452Licence: CC BY

Predictive systems ecology
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/3.0/
Final published version, 423 KBLicence: CC BY

Cite this

Evans, M. R., Bithell, M., Cornell, S. J., Dall, S. R. X., Diaz, S., Emmott, S., Ernande, B., Grimm, V., Hodgson, D. J., Lewis, S. L., Mace, G. M., Morecroft, M., Moustakas, A., Murphy, E., Newbold, T., Norris, K. J., Petchey, O., Smith, M., Travis, J. M. J., & Benton, T. G. (2013). Predictive systems ecology. Proceedings of the Royal Society of London. B, Biological Sciences, 280(1771), Article 20131452. https://doi.org/10.1098/rspb.2013.1452

Evans, MR, Bithell, M, Cornell, SJ, Dall, SRX, Diaz, S, Emmott, S, Ernande, B, Grimm, V, Hodgson, DJ, Lewis, SL, Mace, GM, Morecroft, M, Moustakas, A, Murphy, E, Newbold, T, Norris, KJ, Petchey, O, Smith, M, Travis, JMJ & Benton, TG 2013, 'Predictive systems ecology', Proceedings of the Royal Society of London. B, Biological Sciences, vol. 280, no. 1771, 20131452. https://doi.org/10.1098/rspb.2013.1452

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AU - Moustakas, Aristides

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AU - Newbold, Tim

AU - Norris, K. J.

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AB - 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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KW - ecosystem assessment

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KW - climate-change

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KW - population-dynamics

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KW - forest dynamics

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DO - 10.1098/rspb.2013.1452

M3 - Literature review

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JO - Proceedings of the Royal Society of London. B, Biological Sciences

JF - Proceedings of the Royal Society of London. B, Biological Sciences

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ER -

Predictive systems ecology

Abstract

Keywords

UN SDGs

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