Excessive spatial resolution decreases performance of quantitative models, contrary to expectations from error analyses

Marine Ecology Progress Series

Volumn 485, Issue , 2013, Pages 57-73

  Svensson, J Robin ^a   Jonsson, Lisbeth ^a   Lindegarth, Mats ^a  

^a UNIVERSITY OF GOTHENBURG   (Sweden)

Author keywords

Distribution; Marine; Model; Quantitative; Scale; Sessile; Spatial

Indexed keywords

BIODIVERSITY; ERROR ANALYSIS; HABITAT CONSERVATION; INVERTEBRATE; MACROALGA; MARINE ENVIRONMENT; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; POLICY MAKING; PREDICTION; SCALE EFFECT; SESSILE SPECIES; SPATIAL DISTRIBUTION; SPATIAL RESOLUTION;

SWEDEN;

EID: 84879678286     PISSN: 01718630     EISSN: None     Source Type: Journal    
DOI: 10.3354/meps10307     Document Type: Article

References (66)

1. Anderson RP, Peterson AT, Gomez-Laverde M (2002) Using niche-based GIS modeling to test geographic predictions of competitive exclusion and competitive release in South American pocket mice. Oikos 98: 3-16
2. Araujo MB, Guisan A (2006) Five (or so) challenges for species distribution modelling. J Biogeogr 33: 1677-1688
3. Beale CM, Lennon JJ (2012) Incorporating uncertainty in predictive species distribution modelling. Philos Trans R Soc Lond B 367: 247-258
4. Benedetti-Cecchi L (2001) Beyond BACI: optimization of environmental sampling designs through monitoring and simulation. Ecol Appl 11: 783-799
5. Breiman L (2001) Random forests. Mach Learn 45: 5-32
6. Chatfield C (1995) Model uncertainty, data mining and statistical inference. J R Stat Soc Ser A Stat Soc 158: 419-466
7. Chust G, Pretus JL, Ducrot D, Ventura D (2004) Scale dependency of insect assemblages in response to landscape pattern. Landsc Ecol 19: 41-57
8. Clarke RT, Furse MT, Gunn RJM, Winder JM, Wright JF (2002) Sampling variation in macroinvertebrate data and implications for river quality indices. Freshw Biol 47: 1735-1751
9. Diesing M, Coggan R, Vanstaen K (2009) Widespread rocky reef occurrence in the central English Channel and the implications for predictive habitat mapping. Estuar Coast Shelf Sci 83: 647-658
10. Ducrotoy JP (1999) Protection, conservation and biological diversity in the North East Atlantic. Aquat Conserv 9: 313-325
11. Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annu Rev Ecol Evol Syst, Book 40:677-697
12. European Commission (1992) Council Directive 92/43/EEC. Conservation of natural habitats and of wild flora and fauna. Off J Euro Comm L 206: 7-49
13. European Commission (2007) An integrated maritime policy for the European Union. COM (2007) 2575
14. European Commission, Brussels European Commission (2008)Council Directive 2008/56/EC. A framework for community action in the field of marine environmental policy. Off J Euro Comm L 164: 19-40
15. Evans MR, Norris KJ, Benton TG (2012) Predictive ecology: systems approaches. Philos Trans R Soc Lond B 367: 163-169
16. Ford ED (2000) Scientific method for ecological research. Cambridge University Press, Cambridge
17. Gonzalez-Mirelis G, Bergstrom P, Lindegarth M (2011) Interaction between classification detail and prediction of community types: implications for predictive modelling of benthic biotopes. Mar Ecol Prog Ser 432: 31-44
18. Gottschalk TK, Aue B, Hotes S, Ekschmitt K (2011) Influence of grain size on species-habitat models. Ecol Model 222: 3403-3412
19. Graf RF, Bollmann K, Suter W, Bugmann H (2005) The importance of spatial scale in habitat models: capercaillie in the Swiss Alps. Landsc Ecol 20: 703-717
20. Graham CH, Ron SR, Santos JC, Schneider CJ, Moritz C (2004) Integrating phylogenetics and environmental niche models to explore speciation mechanisms in dendrobatid frogs. Evolution 58: 1781-1793
21. Guisan A, Thuiller W (2005) Predicting species distribution: offering more than simple habitat models. Ecol Lett 8: 993-1009
22. Guisan A, Zimmermann NE (2000) Predictive habitat distribution models in ecology. Ecol Model 135: 147-186
23. Guisan A, Graham CH, Elith J, Huettmann F, Distri NS (2007a) Sensitivity of predictive species distribution models to change in grain size. Divers Distrib 13: 332-340
24. Guisan A, Zimmermann NE, Elith J, Graham CH, Phillips S, Peterson AT (2007b) What matters for predicting the occurrences of trees: techniques, data, or species' characteristics? Ecol Monogr 77: 615-630
25. Håkanson L (1999) On the principles and factors determining the predictive success of ecosystem models, with a focus on lake eutrophication models. Ecol Model 121: 139-160
26. Håkanson L, Duarte CM (2008) Data variability and uncertainty limits the capacity to identify and predict critical changes in coastal systems-A review of key concepts. Ocean Coast Manag 51: 671-688
27. Håkanson L, Peters RH (1995) Predictive limnology. Methods for predictive modelling, Vol 1. SPB Academic Publishing, Amsterdam
28. Heikkinen RK, Luoto M, Kuussaari M, Toivonen T (2007) Modelling the spatial distribution of a threatened butterfly: impacts of scale and statistical technique. Landsc Urban Plan 79: 347-357
29. Hilborn R, Mangel M (1997) The ecological detective, Vol 1. Princeton University Press, Princeton
30. NJ Jager HI, King AW(2004) Spatial uncertainty and ecological models. Ecosystems 7: 841-847
31. Kendall MS, Miller TJ, Pittman SJ (2011) Patterns of scaledependency and the influence of map resolution on the seascape ecology of reef fish. Mar Ecol Prog Ser 427: 259-274
32. Leathwick JR (1998) Are New Zealand's Nothofagus species in equilibrium with their environment? J Veg Sci 9: 719-732
33. Levin SA (1992) The problem of pattern and scale in eco-logy. Ecology 73: 1943-1967
34. Liaw A, Wiener M (2002) Classification and regression by randomForest. R News 2: 18-22
35. Lindblad C, Nikolopoulos A (2012) Survey of off-shore banks, Report 6385, Vol 1. Swedish Environmental Protection Agency, Stockholm (in Swedish)
36. Lobo JM (2008) More complex distribution models or more representative data? Biodivers Informatics 5: 14-19
37. Morrisey DJ, Howitt L, Underwood AJ, Stark JS (1992) Spatial variation in soft-sediment benthos.Mar Ecol Prog Ser 81: 197-204
38. Norén K, Lindegarth M (2005) Spatial, temporal and inter-active variability of infauna in Swedish coastal sediments. J Exp Mar Biol Ecol 317: 53-68
39. Parysow P, Gertner G, Westervelt J (2000) Efficient approximation for building error budgets for process models. Ecol Model 135: 111-125
40. Pearce J, Lindenmayer D (1998) Bioclimatic analysis to enhance reintroduction biology of the endangered helmeted honeyeater (Lichenostomus melanops cassidix) in southeastern Australia. Restor Ecol 6: 238-243
41. Peters RH (1991) A critique for ecology. Cambridge University PressCambridge
42. Peterson AT (2003) Predicting the geography of species' invasions via ecological niche modeling. Q Rev Biol 78: 419-433
43. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190: 231-259
44. Prasad AM, Iverson LR, Liaw A (2006) Newer classification and regression tree techniques: bagging and random forests for ecological prediction. Ecosystems 9: 181-199
45. Punt AE, Hilborn R (1997) Fisheries stock assessment and decision analysis: the Bayesian approach. Rev Fish Biol Fish 7: 35-63
46. Quinn GP, Keough MJ (2002) Experimental design and data analysis for biologists, Vol 1. Cambridge University Press
47. Cambridge R Development Core Team (2011) R: a language and en-vironment for statistical computing. R Foundation for Statistical Computing, Vienna
48. Reese GC, Wilson KR, Hoeting JA, Flather CH (2005) Factors affecting species distribution predictions: a simulation modeling experiment. Ecol Appl 15: 554-564
49. Refsgaard JC, van der Sluijs JP, Hojberg AL, VanrolleghemPA (2007) Uncertainty in the environmental modelling process-A framework and guidance. Environ Model Softw 22: 1543-1556
50. Renard B, Kavetski D, Kuczera G, Thyer M, Franks SW (2010) Understanding predictive uncertainty in hydrologic modeling: the challenge of identifying input and structural errors. Water Resour Res 46: 1-22
51. Robinson LM, Elith J, Hobday AJ, Pearson RG, Kendall BE, Possingham HP, Richardson AJ (2011) Pushing the limits in marine species distribution modelling: lessons from the land present challenges and opportunities. Glob Ecol Biogeogr 20: 789-802
52. Schneider DC (2001) The rise of the concept of scale in ecology. BioScience 51: 545-553
53. Segal MR (2004) Machine learning benchmarks and random forest regression. eScholarship Repository University of California, San Francisco, CA, available at http: //repositories.cdlib.org/cbmb/bench-rf-regn
54. Seoane J, Bustamante J, Diaz-Delgado R (2004) Are existing vegetation maps adequate to predict bird distributions? Ecol Modell 175: 137-149
55. Stockwell DRB, Peterson AT (2002) Effects of sample size on accuracy of species distribution models. Ecol Model 148: 1-13
56. Stokland JN, Halvorsen R, Stoa B (2011) Species distribution modeling-effect of design and sample size of pseudoabsence observations. Ecol Model 222: 1800-1809
57. Sundblad G, Bergström U, Sandström A (2011) Ecological coherence of marine protected area networks: a spatial assessment using species distribution models. J Appl Ecol 48: 112-120
58. Thompson CM, McGarigal K (2002) The influence of research scale on bald eagle habitat selection along the lower Hudson River, New York (USA). Landsc Ecol 17: 569-586
59. Thuiller W (2004) Patterns and uncertainties of species' range shifts under climate change. Glob Change Biol 10: 2020-2027
60. ThuillerW, Araujo MB, Lavorel S (2003) Generalized models vs. classification tree analysis: predicting spatial distributions of plant species at different scales. J Veg Sci 14: 669-680
61. Tobalske C (2002) Effects of spatial scale on the predictive ability of habitat models for the green woodpecker in Switzerland. In: Scott JM, Heglund PJ, Samson F, Hauf-ler J, Morrison M, Raphael M, Wall B (eds) Predicting species occurrences: issues of accuracy and scale. Island Press, Covelo, CA, p 197-204
62. Turner MG, Dale VH, Gardner RH (1989) Predicting across scales: theory development and testing. Landsc Ecol 3: 245-252
63. Underwood AJ (1994) On beyond BACI: sampling designs that might reliably detect environmental disturbances. Ecol Appl 4: 3-15
64. Underwood AJ (1997) Experiments in ecology-Their logical design and interpretation using analysis of variance, Vol 1. Cambridge University Press, Cambridge
65. Underwood AJ, Chapman MG (1996) Scales of spatial patterns of distribution of intertidal invertebrates. Oecologia 107: 212-224
66. Wiens JA (1989) Spatial scaling in ecology. Funct Ecol 3: 385-397.