Making predictions in a changing world: The benefits of individual-based ecology

BioScience

Volumn 65, Issue 2, 2015, Pages 140-150

  Stillman, Richard A ^a   Railsback, Steven F ^b   Giske, Jarl ^c   Berger, Uta ^d   Grimm, Volker ^e,f,g  

^a BOURNEMOUTH UNIVERSITY   (United Kingdom)

^b HUMBOLDT STATE UNIVERSITY   (United States)

^c UNIVERSITY OF BERGEN   (Norway)

^d DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

^e HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH UFZ   (Germany)

^f UNIVERSITY OF POTSDAM   (Germany)

^g German Centre for Integrative Biodiversity Research (iDiv) Halle Jena Leipzig   (Germany)

Author keywords

Ecology; fitness maximization; individual based; modeling; prediction

Indexed keywords

EID: 84922554553     PISSN: 00063568     EISSN: 15253244     Source Type: Journal    
DOI: 10.1093/biosci/biu192     Document Type: Review

References (60)

1. Bauer S, Klaassen M. 2013. Mechanistic models of animal migration behaviour their diversity, structure and use. Journal of Animal Ecology 82: 498-508.
2. Bauer S, Berger U, Hildenbrandt H, Grimm V. 2002. Cyclic dynamics in plant populations. Proceedings of the Royal Society B 269: 2443-2450.
3. Berger U, Hildenbrandt H. 2000. A new approach to spatially explicit modelling of forest dynamics: Spacing, ageing and neighbourhood competition of mangrove trees. Ecological Modelling 132: 287-302.
4. Botkin DB, Janak JF, Wallis JR. 1972. Some ecological consequences of a computer model of forest growth. Journal of Ecology 60: 849-872.
5. Bovee KD, Lamb BL, Bartholow JM, Stalnaker CB, Taylor J, Henriksen J. 1998. Stream Habitat Analysis Using the Instream Flow Incremental Methodology. US Geological Survey, Biological Resources Division. Report no. USGS/BRD-1998-0004.
6. Bugmann H. 2001. A review of forest gap models. Climatic Change 51: 259-305.
7. DeAngelis DL, Cox DK, Coutant CC. 1980. Cannibalism and size dispersal in young-of-the-year largemouth bass: Experiment and model. Ecological Modelling 8: 133-148.
8. DeAngelis DL, Gross LJ, Huston MA, Wolff WF, Fleming DM, Comiskey EJ, Sylvester SM. 1998. Landscape modeling for Everglades ecosystem restoration. Ecosystems 1: 64-75.
9. Durell SEALVD, Goss-Custard JD, Stillman RA, West AD. 2001. The effect of weather and density-dependence on oystercatcher Haematopus ostralegus winter mortality. Ibis 143: 498-499.
10. Duriez O, Bauer S, Destin A, Madsen J, Nolet B, Stillman R, Klaassen M. 2009. What decision rules might pink-footed geese use to depart on migration? An individual-based model. Behavioural Ecology 20: 560-569.
11. EPRI] Electric Power Research Institute. 2000. Instream Flow Assessment Methods: Guidance for Evaluating Instream Flow Needs in Hydropower Licensing. EPRI. Report no. TR-1000554.
12. Evans MR. 2012. Modelling ecological systems in a changing world. Philosophical Transactions of the Royal Society B 367: 181-190.
13. Evans MR, et al. 2013. Do simple models lead to generality in ecology? Trends in Ecology and Evolution 28: 578-583.
14. Giske J, Huse G, Fiksen E. 1998. Modelling spatial dynamics of fish. Reviews in Fish Biology and Fisheries 8: 57-91.
15. Giske J, Eliassen S, Fiksen E, Jakobsen PJ, Aksnes DL, Jørgensen C, Mangel M. 2013. Effects of the emotion system on adaptive behavior. American Naturalist 182: 689-703.
16. Goss-Custard JD, Caldow RWG, Clarke RT, Durell SEAlVd, Sutherland WJ. 1995. Deriving population parameters from individual variations in foraging behaviour. 1. Empirical game-theory distribution model of oystercatchers Haematopus ostralegus feeding on mussels Mytilus edulis. Journal of Animal Ecology 64: 265-276.
17. Goss-Custard JD, Stillman RA, West AD, Caldow RWG, Triplet P, Durell S, McGrorty S. 2004. When enough is not enough: Shorebirds and shellfishing. Proceedings of the Royal Society B 271: 233-237
18. Grimm V. 1999. Ten years of agent-based modelling in ecology: What have we learned and what could we learn in the future? Ecological Modelling 115: 129-148.
19. Grimm V, Railsback SF. 2005. Individual-Based Modeling and Ecology. Princeton University Press.
20. 2012. Pattern-oriented modelling: A 'multiscope' for predictive systems ecology. Philosophical Transactions of the Royal Society B 367: 298-310.
21. Grimm V, Berger U, DeAngelis DL, Polhill G, Giske J, Railsback SF. 2010. The ODD protocol: A review and first update. Ecological Modelling 221: 2760-2768.
22. Grimm V, et al. 2014. Towards better modelling and decision support: Documenting model development, testing, and analysis using TRACE. Ecological Modelling 280: 129-139.
23. Hellweger FL, Bucci V. 2009. A bunch of tiny individuals-Individual-based modeling for microbes. Ecological Modelling 220: 8-22.
24. Hughes NF. 1992. Selection of positions by drift-feeding salmonids in dominance hierarchies: Model and test for arctic grayling (Thymallus arcticus) in subarctic mountain streams, interior Alaska. Canadian Journal of Fisheries and Aquatic Sciences 49: 1999-2008.
25. Huse G, Giske J. 1998. Ecology in Mare Pentium: an individual based model for fish with adapted behavior. Fisheries Research 37: 163-178.
26. Huse G, Strand E, Giske J. 1999. Implementing behavior in individual-based models using artificial neural networks and genetic algorithms. Evolutionary Ecology 13: 469-483.
27. Kreft J-U, et al. 2013. Mighty small: Observing and modeling individual microbes becomes big science. Proceedings of the National Academy of Sciences 110: 18027-18028.
28. Lin Y, Berger U, Grimm V, Ji Q-R. 2012. Differences between symmetric and asymmetric facilitation matter: Exploring the interplay between modes of positive and negative plant interactions. Journal of Ecology 100: 1482-1491.
29. Lin Y, Berger U, Grimm V, Huth F, Weiner J. 2013. Plant interactions alter the predictions of metabolic scaling theory. PLOS ONE 8, e57612.
30. Liu J, Ashton PS. 1995. Individual-based simulation models for forest succession and management. Forest Ecology and Management 73: 157-175.
31. Momnicki A. 1978. Individual differences between animals and the natural regulation of their numbers. Journal of Animal Ecology 47: 461-475.
32. Mangel M, Clark CW. 1986. Toward a unified foraging theory. Ecology 67: 1127-1138.
33. Martin B, Jager T, Nisbet RM, Preuss TG, Grimm V. 2013. Predicting population dynamics from the properties of individuals: A cross-level test of Dynamic Energy Budget theory. American Naturalist 181: 506-519.
34. Monserud RA. 1976. Simulation of forest tree mortality. Forest Science 22: 438-444.
35. Piou C, Berger U, Hildenbrandt H, Grimm V, Diele K, D'Lima C. 2007. Simulating cryptic movements of a mangrove crab: Recovery phenomena after small scale fishery. Ecological Modelling 205: 110-122.
36. Piou C, Berger U, Hildenbrandt H, Feller IC. 2008. Testing the intermediate disturbance hypothesis in species-poor systems: A simulation experiment for mangrove forests. Journal of Vegetation Science 19: 417-424.
37. Railsback SF. 2001. Concepts from complex adaptive systems as a framework for individual-based modelling. . Ecological Modelling 139: 47-62.
38. Railsback SF, Grimm V. 2012. Agent-Based and Individual-Based Modeling: A Practical Introduction. Princeton University Press.
39. Railsback S, Harvey B. 2002. Analysis of habitat selection rules using an individual-based model. Ecology 83: 1817-1830.
40. 2011. Importance of fish behaviour in modelling conservation problems: Food limitation as an example. Journal of Fish Biology 79: 1648-1662
41. 2013. Trait-mediated trophic interactions: Is foraging theory keeping up Trends in Ecology and Evolution 28: 119-125.
42. Railsback SF, Lamberson RH, Harvey BC, Duffy WE. 1999. Movement rules for spatially explicit individual-based models of stream fish. Ecological Modelling 123: 73-89.
43. Railsback S, Harvey B, Lamberson R, Lee D, Clausen N, Yoshihara S. 2002. Population-level analysis and validation of an individual-based cutthroat trout model. Natural Resource Modeling 14: 465-474.
44. Railsback SF, Stauffer HB, Harvey BC. 2003. What can habitat preference models tell us Tests using a virtual trout population. Ecological Applications 13: 1580-1594.
45. Railsback SF, Harvey BC, Hayse JW, LaGory KE. 2005. Tests of theory for diel variation in salmonid feeding activity and habitat use. Ecology 86: 947-959.
46. Railsback SF, Harvey BC, Jackson SK, Lamberson RH. 2009. InSTREAM: The Individual-Based Stream Trout Research and Environmental Assessment Model. US Department of Agriculture Forest Service, Pacific Southwest Research Station. Report no. PSW-GTR-218.
47. Railsback SF, Gard M, Harvey BC, White JL, Zimmerman JKH. 2013. Contrast of degraded and restored stream habitat using an individual-based salmon model. North American Journal of Fisheries Management 33: 384-399.
48. Rappoldt C, Stillman RA, Ens BJ. 2010. A geometrical model for the effect of interference on food intake. Ecological Modelling 221: 147-151.
49. Rose KA. 2000. Why are quantitative relationships between environmental quality and fish populations so elusive Ecological Applications 10: 367-385.
50. Schwinning S, Weiner J. 1998. Mechanisms determining the degree of size asymmetry in competition among plants. Oecologia 113: 447-455.
51. Sibly RM, Grimm V, Martin BT, Johnston ASA, Kulakowska K, Topping CJ, Calow P, Nabe-Nielsen J, Thorbek P, DeAngelis DL. 2013. Representing the acquisition and use of energy by individuals in agent-based models of animal populations. Methods in Ecology and Evolution 4: 151-161.
52. Sousa T, Domingos T, Poggiale J-C, Kooijman SALM. 2010. Dynamic energy budget theory restores coherence in biology. Philosophical Transactions of the Royal Society B 365: 3413-3428.
53. Stillman RA. 2008. MORPH: An individuals-based model to predict the effect of environmental change on foraging animal populations. Ecological Modelling 216: 265-276.
54. Stillman RA, Goss-Custard JD. 2010. Individual-based ecology of coastal birds. Biological Reviews 85: 413-434.
55. Stillman RA, Goss-Custard JD, West AD, Durell S, Caldow RWG, McGrorty S, Clarke RT. 2000a. Predicting mortality in novel environments: tests and sensitivity of a behaviour-based model. Journal of Applied Ecology 37: 564-588.
56. Stillman RA, Goss-Custard JD, Alexander MJ. 2000b. Predator search pattern and the strength of interference through prey depression. Behavioral Ecology 11: 597-605.
57. Stillman RA, et al. 2001. Predicting shorebird mortality and population size under different regimes of shellfishery management. Journal of Applied Ecology 38: 857-868.
58. Stillman RA, Poole AE, Goss-Custard JD, Caldow RWG, Yates MG, Triplet P. 2002. Predicting the strength of interference more quickly using behaviour-based models. Journal of Animal Ecology 71: 532-541.
59. Stillman RA, et al. 2003. An individual behaviour-based model can predict shorebird mortality using routinely collected shellfishery data. Journal of Applied Ecology 40: 1090-1101.
60. Van Winkle W, Jager HI, Railsback SF, Holcomb BD, Studley TK, Baldrige JE. 1998. Individual-based model of sympatric populations of brown and rainbow trout for instream flow assessment: Model description and calibration. Ecological Modelling 110: 175-207.