Ecological models supporting environmental decision making: A strategy for the future

Trends in Ecology and Evolution

Volumn 25, Issue 8, 2010, Pages 479-486

  Schmolke, Amelie ^a   Thorbek, Pernille ^b   DeAngelis, Donald L ^c   Grimm, Volker ^a  

^a HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH UFZ   (Germany)

^b JEALOTT S HILL INTERNATIONAL RESEARCH CENTRE   (United Kingdom)

^c Department of Biology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION MAKING; DECISION SUPPORT SYSTEM; ECOLOGICAL MODELING; ENVIRONMENTAL MANAGEMENT; ENVIRONMENTAL POLICY; FUTURE PROSPECT; INCENTIVE; LITERATURE REVIEW;

BIOLOGICAL MODEL; DECISION MAKING; DOCUMENTATION; ECOSYSTEM; ENVIRONMENTAL PROTECTION; METHODOLOGY; REVIEW;

CONSERVATION OF NATURAL RESOURCES; DECISION MAKING; DOCUMENTATION; ECOSYSTEM; MODELS, BIOLOGICAL;

EID: 77954656798     PISSN: 01695347     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.tree.2010.05.001     Document Type: Review

References (72)

1. U.S.Fish and Wildlife Service (1973) Endangered Species Act of 1973.
2. European Commission (1992) Council Directive 92/43/EEC of 21 May 1992 on the conservation of natural habitats and of wild fauna and flora ('Habitats Directive').
3. Bugmann H., et al. Scaling issues in forest succession modeling. Climatic Change 2000, 44:265-289.
4. Duarte P., et al. Mathematical modelling to assess the carrying capacity for multi-species culture within coastal waters. Ecol. Model. 2003, 168:109-143.
5. Forbes V.E., et al. Ecological models in support of regulatory risk assessments of pesticides: developing a strategy for the future. Integr. Environ. Assess. Manage. 2009, 5:167-172.
6. Pretzsch H. Analysing and modelling forest stand dynamics for practical application - an European review and perspective. Eurasian J. Forest Res. 2007, 10:1-17.
7. Rose K.A., Cowan J.H. Data, models, and decisions in U.S. marine fisheries management: lessons for ecologists. Annu. Rev. Ecol. Syst. 2003, 34:127-151.
8. DeAngelis D.L., et al. Landscape modeling for Everglades ecosystem restoration. Ecosystems 1998, 1:64-75.
9. Grimm V., et al. CREAM: a European project on mechanistic effect models for ecological risk assessment of chemicals. Environ. Sci. Pollut. Res. 2009, 16:614-617.
10. Preuss T.G., et al. Mechanistic effect models for ecological risk assessment of chemicals (MEMoRisk) - a new SETAC Europe Advisory Group. Environ. Sci. Pollut. Res. 2009, 16:250-252.
11. U.S. Environmental Protection Agency (2009) Summary Report. Risk Assessment Forum Technical Workshop on Population-Level Ecological Risk Assessment, EPA/100/R-09/006.
12. Liu J.G., et al. Complexity of coupled human and natural systems. Science 2007, 317:1513-1516.
13. Liu J.G., et al. Coupled human and natural systems. Ambio 2007, 36:639-649.
14. Ostrom E., Nagendra H. Insights on linking forests, trees, and people from the air, on the ground, and in the laboratory. PNAS 2006, 103:19224-19232.
15. Hall C.A.S., Day J.W. Ecological Modeling in Theory and Practice 1977, John Wiley & Sons.
16. Jakeman A.J., et al. Modelling Change in Environmental Systems 1993, John Wiley & Sons.
17. Rykiel E.J. Testing ecological models: the meaning of validation. Ecol. Model. 1996, 90:229-244.
18. Ferrier S., Guisan A. Spatial modelling of biodiversity at the community level. J. Appl. Ecol. 2006, 43:393-404.
19. Jakeman A.J., et al. Ten iterative steps in development and evaluation of environmental models. Environ. Model. Softw. 2006, 21:602-614.
20. Schmolke A., et al. Ecological models and pesticide risk assessment: current modeling practice. Environ. Toxicol. Chem. 2010, 29:1006-1012.
21. Guisan A., Zimmermann N.E. Predictive habitat distribution models in ecology. Ecol. Model. 2000, 135:147-186.
22. Electric Power Research Institute (EPRI) (2000) Instream flow assessment methods: guidance for evaluating instream flow needs in hydropower licensing, EPRI Report 1000554.
23. Comiskey E.J., et al. Evaluating impacts to Florida panther habitat: how porous is the umbrella?. Southeastern Nat. 2004, 3:51-74.
24. Gross L. Why not the best? How science failed the Florida panther. PLoS Biol. 2005, 3:e333.
25. Pilkey O.H., Pilkey-Jarvis L. Useless Arithmetic 2007, Columbia University Press.
26. Patterson B.R., Murray D.L. Flawed population viability analysis can result in misleading population assessment: A case study for wolves in Algonquin park. Canada. Biol. Conserv. 2008, 141:669-680.
27. Parker P., et al. Progress in integrated assessment and modelling. Environ. Model. Softw. 2002, 17:209-217.
28. Prisley S.P., Mortimer M.J. A synthesis of literature on evaluation of models for policy applications, with implications for forest carbon accounting. Forest Ecol. Manag. 2004, 198:89-103.
29. Janssen S., van Ittersum M.K. Assessing farm innovations and responses to policies: a review of bio-economic farm models. Agric. Syst. 2007, 94:622-636.
30. Bart J. Acceptance criteria for using individual-based models to make management decisions. Ecol. Appl. 1995, 5:411-420.
31. Pascual, P. et al. (2003) Draft guidance on the development, evaluation, and application of regulatory environmental models, Council for Regulatory Environmental Modeling.
32. Ecological Modeling in Risk Assessment: Chemical Effects on Populations, Ecosystems, and Landscapes 2002, Lewis Publishers. R.A. Pastorok (Ed.).
33. Crout N., et al. Good modelling practice. Environmental Modelling, Software and Decision Support: State of the Art and New Perspectives 2008, 15-31. Elsevier. A.J. Jakeman (Ed.).
34. Oreskes N., et al. Verification, validation, and confirmation of numerical models in the Earth Sciences. Science 1994, 263:641-646.
35. Bellocchi G., et al. Validation of biophysical models: issues and methodologies. A review. Agron. Sustain. Dev. 2010, 30:109-130.
36. Rose K.A., et al. Compensatory density dependence in fish populations: importance, controversy, understanding, and prognosis. Fish Fisheries 2001, 2:293-327.
37. Grimm V., Railsback S.F. Individual-Based Modeling and Ecology 2005, Princeton University Press.
38. Landsberg J. Modelling forest ecosystems: state of the art, challenges, and future directions. Can. J. Forest Res. 2003, 33:385-397.
39. Nicolson C.R., et al. Ten heuristics for interdisciplinary modeling projects. Ecosystems 2002, 5:376-384.
40. Oxley T., et al. Integrated modelling and decision-support tools: a Mediterranean example. Environ. Model. Softw. 2004, 19:999-1010.
41. Harwood J., Stokes K. Coping with uncertainty in ecological advice: lessons from fisheries. Trends Ecol. Evol. 2003, 18:617-622.
42. Gopen G.D., Swan J.A. The science of scientific writing. Am. Sci. 1990, 78:550-558.
43. Grimm V., et al. A standard protocol for describing individual-based and agent-based models. Ecol. Model. 2006, 198:115-126.
44. Beveridge W.I.B. The Art of Scientific Investigation 1950, The Blackburn Press.
45. Kanare H.M. Writing the Laboratory Notebook 1985, American Chemical Society.
46. Noble W.S. A quick guide to organizing computational biology projects. PLoS Comput. Biol. 2009, 5:e1000424.
47. Rabin, R. and Pastorius, E. (2005) Electronic laboratory notebook systems. Genet. Eng. News 25 (). http://www.genengnews.com/gen-articles/electronic-laboratory-notebook-systems/1075/.
48. Denny-Gouldson P. Meeting the specialized requirements of the biologist through a biology-focused electronic laboratory notebook. Am. Lab. 2007, 39:26-28.
49. Jackson L.J., et al. An introduction to the practice of ecological modeling. BioScience 2000, 50:694-706.
50. Perry G.L.W., Enright N.J. Spatial modelling of vegetation change in dynamic landscapes: a review of methods and applications. Progr. Phys. Geogr. 2006, 30:47-72.
51. Bartell S.M., et al. Realism and relevance of ecological models used in chemical risk assessment. Hum. Ecol. Risk Assess. 2003, 9:907-938.
52. Boorman D., et al. A model selection protocol to support the use of models for water management. Hydrol. Earth Syst. Sci. 2007, 11:634-646.
53. Jakeman A.J., Letcher R.A. Integrated assessment and modelling: features, principles and examples for catchment management. Environ. Model. Softw. 2003, 18:491-501.
54. Radomski P.J., Goeman T.J. Decision making and modeling in freshwater sport-fisheries management. Fisheries 1996, 21:14-21.
55. Beissinger S.R., Westphal M.I. On the use of demographic models of population viability in endangered species management. J. Wildlife Manage. 1998, 62:821-841.
56. Jongejans E., et al. Dispersal, demography and spatial population models for conservation and control management. Perspect. Plant Ecol. Evol. Syst. 2008, 9:153-170.
57. Petersen J.H., DeAngelis D.L. An overview of methods for developing bioenergetic and life history models for rare and endangered species. Trans. Am. Fish. Soc. 2008, 137:244-253.
58. Wiegand T., et al. Using pattern-oriented modeling for revealing hidden information: a key for reconciling ecological theory and application. Oikos 2003, 100:209-222.
59. Fulton E.A., et al. Effect of complexity on marine ecosystem models. Mar. Ecol. Prog. Ser. 2003, 253:1-16.
60. Mooij W.M., DeAngelis D.L. Uncertainty in spatially explicit animal dispersal models. Ecol. Appl. 2003, 13:794-805.
61. Nelson W.A., et al. Balancing ecological complexity in predictive models: a reassessment of risk models in the mountain pine beetle system. J. Appl. Ecol. 2008, 45:248-257.
62. Wennergren U., et al. The promise and limitations of spatial models in conservation biology. Oikos 1995, 74:349-356.
63. Cary G.J., et al. Comparison of the sensitivity of landscape-fire-succession models to variation in terrain, fuel pattern, climate and weather. Landscape Ecol. 2006, 21:121-137.
64. Brook B.W. Pessimistic and optimistic bias in population viability analysis. Conserv. Biol. 2000, 14:564-566.
65. Glaser D., Bridges T.S. Separating the wheat from the chaff: the effective use of mathematical models as decision tools. Integr. Environ. Assess. Manage. 2007, 3:442-449.
66. Ferson S. Automated quality assurance checks on model structure in ecological risk assessments. Hum. Ecol. Risk Assess. 1996, 2:558-569.
67. Oriade C.A., Dillon C.R. Developments in biophysical and bioeconomic simulation of agricultural systems: a review. Agric. Econ. 1997, 17:45-58.
68. Holst N., et al. Field weed population dynamics: a review of model approaches and applications. Weed Res. 2007, 47:1-14.
69. Jager H.I., et al. Spatial uncertainty analysis of population models. Ecol. Model. 2005, 185:13-27.
70. Brook B.W., et al. Predictive accuracy of population viability analysis in conservation biology. Nature 2000, 404:385-387.
71. Fuller M.M., et al. Testing the robustness of management decisions to uncertainty: Everglades restoration scenarios. Ecol. Appl. 2008, 18:711-723.
72. Scheller R.M., Mladenoff D.J. An ecological classification of forest landscape simulation models: tools and strategies for understanding broad-scale forested ecosystems. Landscape Ecol. 2007, 22:491-505.