of model and data complexity on predictions from species distributions models

Ecological Modelling

Volumn 326, Issue , 2016, Pages 4-12

  García Callejas, David ^a,b   Araújo, Miguel B ^a,b,c,d  

^a UNIVERSITY OF ÉVORA   (Portugal)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

^c MUSEO NACIONAL DE CIENCIAS NATURALES   (Spain)

^d UNIVERSITY OF COPENHAGEN   (Denmark)

Author keywords

Climate change; Data complexity; Model complexity; Species distributions models; Transferability; Virtual species

Indexed keywords

CLIMATE CHANGE; CLIMATE MODELS; COMPUTATIONAL COMPLEXITY; DECISION TREES; FORECASTING; POPULATION DISTRIBUTION;

DATA COMPLEXITY; MODEL COMPLEXITY; SPECIES DISTRIBUTIONS; TRANSFERABILITY; VIRTUAL SPECIES;

PREDICTIVE ANALYTICS;

CLIMATE CHANGE; DATA INTERPRETATION; DATA SET; ECOLOGICAL MODELING; ENVIRONMENTAL RESEARCH; POPULATION DISTRIBUTION; SPECIES OCCURRENCE;

EID: 84960800428     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2015.06.002     Document Type: Article

References (56)

1. Araújo M.B., Peterson A.T. Uses and misuses of bioclimatic envelope modeling. Ecology 2012, 93(7):1527-1539. 10.1890/11-1930.1.
2. Araújo M.B., Rahbek C. How does climate change affect biodiversity?. Science 2006, 313:1396-1397. 10.1126/science.1131758.
3. Araújo M.B., Whittaker R.J., Ladle R.J., Erhard M. Reducing uncertainty in projections of extinction risk from climate change. Glob. Ecol. Biogeogr. 2005, 14:529-538. 10.1111/j.1466-822x.2005.00182.x.
4. Araújo M.B., Pearson R.G., Thuiller W., Erhard M. Validation of species-climate impact models under climate change. Glob. Change Biol. 2005, 11:1504-1513. 10.1111/j.1365-2486.2005.01000.x.
5. Araújo M.B., Thuiller W., Yoccoz N.G. Reopening the climate envelope reveals macroscale associations with climate in European birds. Proc. Natl. Acad. Sci. 2009, 106:45-46.
6. Arora S., Barak B. Computational Complexity: A Modern Approach 2009, Cambridge University Press. 10.1017/CBO9780511804090.
7. Austin M. Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecol. Model. 2002, 157:101-118. 10.1016/S0304-3800(02)00205-3.
8. Barry S., Elith J. Error and uncertainty in habitat models. J. Appl. Ecol. 2006, 43(3):413-423. 10.1111/j.1365-2664.2006.01136.x.
9. Data Complexity in Pattern Recognition 2006, Springer-Verlag, London. 10.1007/978-1-84628-172-3. M. Basu, T.K. Ho (Eds.).
10. Blonder B., Lamanna C., Violle C., Enquist B.J. The n-dimensional hypervolume. Glob. Ecol. Biogeogr. 2014, 23:595-609. 10.1111/geb.12146.
11. Booth T.H., Nix H.A., Busby J.R., Hutchinson M.F. Bioclim: the first species distribution modelling package, its early applications and relevance to most current MaxEnt studies. Divers. Distrib. 2014, 20:1-9. 10.1111/ddi.12144.
12. Breiman L. Random forests. Machine Learning 2001, 45:5-32. 10.1023/A:1010933404324.
13. Brook B.W., Akçakaya H.R., Keith D.A., Mace G.M., Pearson R.G., Araújo M.B. Integrating bioclimate with population models to improve forecasts of species extinctions under climate change. Biol. Lett. 2009, 5(6):723-725. 10.1098/rsbl.2009.0480.
14. Brotons L., Thuiller W., Araújo M.B., Hirzel A.H. Presence-absence versus presence-only modelling methods for predicting bird habitat suitability. Ecography 2004, 27:437-448. 10.1111/j.0906-7590.2004.03764.x.
15. Cutler D.R., Edwards T.C., Beard K.H., Cutler A., Hess K.T., Gibson J., Lawler J.J. Random forests for classification in ecology. Ecology 2007, 88(11):2783-2792. 10.1890/07-0539.1.
16. Dobrowski S.Z., Thorne J.H., Greenberg J.A., Safford H.D., Mynsberge A.R., Crimmins S.M., et al. Modeling plant ranges over 75 years of climate change in California USA: temporal transferability and species traits. Ecol. Monogr. 2011, 81:241-257. 10.1890/10-1325.1.
17. Duncan R.P., Cassey P., Blackburn T.M. Do climate envelope models transfer? A manipulative test using dung beetle introductions. Proc. R. Soc. B: Biol. Sci. 2009, 276:1449-1457. 10.1098/rspb.2008.1801.
18. Elith J., Leathwick J.R. Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 2009, 40(1):677-697. 10.1146/annurev.ecolsys.110308.120159.
19. Elith J., Graham C.H., Anderson R.P., Dudik M., Ferrier S., Guisan A., Hijmans R.J., Huettmann F., Leathwick J.R., Lehmann A., Li J., Lohmann L.G., Loiselle B.A., Manion G., Moritz C., Nakamura M., Nakazawa Y., Mcc Overton J., Peterson A.T., Phillips S.J., Richardson K., Scachetti-Pereira R., Schapire R.E., Soberón J., Williams S., Wisz M.S., Zimmermann N.E. Novel methods improve prediction of species' distributions from occurrence data. Ecography 2006, 29:129-151. 10.1111/j.2006.0906-7590.04596.x.
20. Elith J., Leathwick J.R., Hastie T. A working guide to boosted regression trees. J. Anim. Ecol. 2008, 77(4):802-813. 10.1111/j.1365-2656.2008.01390.x.
21. Elith J., Phillips S.J., Hastie T., Dudík M., Chee Y.E., Yates C.J. A statistical explanation of MaxEnt for ecologists. Divers. Distrib. 2011, 17:43-57. 10.1111/j.1472-4642.2010.00725.x.
22. Foody G.M. Impacts of imperfect reference data on the apparent accuracy of species presence-absence models and their predictions. Glob. Ecol. Biogeogr. 2011, 20:498-508. 10.1111/j.1466-8238.2010.00605.x.
23. Fordham D.A., Akçakaya H.R., Araújo M.B., Keith D.A., Brook B.W. Tools for integrating range change, extinction risk and climate change information into conservation management. Ecography 2013, 36:956-964. 10.1111/j.1600-0587.2013.00147.x.
24. Friedman J.H. Multivariate adaptive regression splines. Ann. Stat. 1991, 19:1-67.
25. García-Valdés R., Gotelli N.J., Zavala M.A., Purves D., Araújo M.B. Effects of climate, species interactions, and dispersal on decadal colonization and extinction rates of Iberian tree species. Ecol. Model. 2015, 309:118-127.
26. Guisan A., Zimmermann N.E. Predictive habitat distribution models in ecology. Ecol. Model. 2000, 135(2-3):147-186. 10.1016/S0304-3800(00)00354-9.
27. Halekoh U., Højsgaard S. A Kenward-Roger approximation and parametric bootstrap methods for tests in linear mixed models - the R package pbkrtest. J. Stat. Softw. 2014, 59(9):1-30.
28. Hastie T., Tibshirani R. Generalized Additive Models 1990, Chapman and Hall.
29. Heikkinen R.K., Marmion M., Luoto M. Does the interpolation accuracy of species distribution models come at the expense of transferability?. Ecography 2012, 35(3):276-288. 10.1111/j.1600-0587.2011.06999.x.
30. Hijmans R.J., Cameron S.E., Parra J.L., Jones P.G., Jarvis A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 2005, 25:1965-1978. 10.1002/joc.1276.
31. Ho T.K. Data complexity analysis: linkage between context and solution in classification. Structural Syntactic, and Statistical Pattern Recognition 2008, vol. 1:986-995. Springer, Berlin.
32. Ho T.K., Basu M. Complexity measures of supervised classification problems. IEEE Trans. Pattern Anal. Mach. Intel. 2002, 24:289-300.
33. Hoekstra A., Duin R.P.W. On the nonlinearity of pattern classifiers. Proc. of the 13th ICPR 1996, 271-275.
34. IPCC. Climate Change Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change 2007, IPCC, Geneva, Switzerland.
35. Jiménez-Valverde A. Insights into the area under the receiver operating characteristic curve (AUC) as a discrimination measure in species distribution modelling. Glob. Ecol. Biogeogr. 2012, 21(4):498-507. 10.1111/j.1466-8238.2011.00683.x.
36. Jiménez-Valverde A. Threshold-dependence as a desirable attribute for discrimination assessment: implications for the evaluation of species distribution models. Biodivers. Conserv. 2014, 23:369-385. 10.1007/s10531-013-0606-1.
37. Lobo J.M. More complex distribution models or more representative data?. Biodivers. Inform. 2008, 82:14-19.
38. Madon B., Warton D.I., Araújo M.B. Community-level vs species-specific approaches to model selection. Ecography 2013, 36:1291-1298. 10.1111/j.1600-0587.2013.00127.x.
39. Matias M.G., Gravel D., Guilhaumon F., Desjardins-Proulx P., Loreau M., Münkemüller T., Mouquet N. Estimates of species extinctions from species-area relationships strongly depend on ecological context. Ecography 2014, 37:431-442. 10.1111/j.1600-0587.2013.00448.x.
40. Merow C., Smith M.J., Edwards T.C., Guisan A., McMahon S.M., Normand S., et al. What do we gain from simplicity versus complexity in species distribution models?. Ecography 2014, 37:1-15. 10.1111/ecog.00845.
41. Ministerio de Medio Ambiente Tercer Inventario Forestal Nacional, Barcelona 2006, Dirección General para la Biodiversidad, Madrid.
42. Moudrý V., Šímová P. Influence of positional accuracy, sample size and scale on modelling species distributions: a review. Int. J. Geogr. Inform. Sci. 2012, 26:2083-2095. 10.1080/13658816.2012.721553.
43. Pagel J., Schurr F.M. Forecasting species ranges by statistical estimation of ecological niches and spatial population dynamics. Glob. Ecol. Biogeogr. 2012, 21(2):293-304. 10.1111/j.1466-8238.2011.00663.x.
44. Papadimitriou C.H. Computational Complexity 1994, John Wiley and Sons Ltd.
45. Pearson R.G., Dawson T.P. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?. Glob. Ecol. Biogeogr. 2003, 12:361-371. 10.1046/j.1466-822X.2003.00042.x.
46. Pearson R.G., Thuiller W., Araújo M.B., Martinez-Meyer E., Brotons L., McClean C., Miles L., Segurado P., Dawson T.P., Lees D.C. Model-based uncertainty in species range prediction. J. Biogeogr. 2006, 33:1704-1711. 10.1111/j.1365-2699.2006.01460.x.
47. R Core Team R: A Language and Environment for Statistical Computing 2014, R Foundation for Statistical Computing, Vienna.
48. Randin C.F., Dirnböck T., Dullinger S., Zimmermann N.E., Zappa M., Guisan A. Are niche-based species distribution models transferable in space?. J. Biogeogr. 2006, 33(10):1689-1703. 10.1111/j.1365-2699.2006.01466.x.
49. Segurado P., Araújo M.B. An evaluation of methods for modelling species distributions. J. Biogeogr. 2004, 31:1555-1568. 10.1111/j.1365-2699.2004.01076.x.
50. Smith A.B., Santos M.J., Koo M.S., Rowe K.M.C., Rowe K.C., Patton J.L., et al. Evaluation of species distribution models by resampling of sites surveyed a century ago by Joseph Grinnell. Ecography 2013, 36:1017-1031. 10.1111/j.1600-0587.2013.00107.x.
51. Swets J.A. Measuring the accuracy of diagnostic systems. Science 1988, 240(4857):1285-1293. 10.1126/science.3287615.
52. Thuiller W. Patterns and uncertainties of species' range shifts under climate change. Glob. Change Biol. 2004, 10:2020-2027. 10.1111/j.1365-2486.2004.00859.x.
53. Valladares F., Matesanz S., Guilhaumon F., Araújo M.B., Balaguer L., Benito-Garzón M., et al. The effects of phenotypic plasticity and local adaptation on forecasts of species range shifts under climate change. Ecol. Lett. 2014, 17:1351-1364. 10.1111/ele.12348.
54. Vapnik V. Statistical Learning Theory 1998, Wiley.
55. Wilson D.R., Martinez T.R. Improved heterogeneous distance functions. J. Artif. Intel. Res. 1997, 6:1-34.
56. Zanini F., Pellet J., Schmidt B.R. The transferability of distribution models across regions: an amphibian case study. Divers. Distrib. 2009, 25:469-480. 10.1111/j.1472-4642.2008.00556.x.