Confronting expert-based and modelled distributions for species with uncertain conservation status: A case study from the corncrake (Crex crex)

Biological Conservation

Volumn 167, Issue , 2013, Pages 161-171

  Fourcade, Yoan ^a   Engler, Jan O ^b,c   Besnard, Aurélien G ^a   Rödder, Dennis ^b   Secondi, Jean ^a  

^a UNIVERSITÉ D'ANGERS   (France)

^b ZOOLOGISCHES FORSCHUNGSMUSEUM ALEXANDER KOENIG   (Germany)

^c UNIVERSITY OF GÖTTINGEN   (Germany)

Author keywords

Expert knowledge; Grassland birds; IUCN red list; Maxent; SDM; Species distribution modelling

Indexed keywords

AGRICULTURAL PRACTICE; AVIFAUNA; BIODIVERSITY; BIRD; CONSERVATION STATUS; ECOLOGICAL MODELING; EXPERT SYSTEM; GRASSLAND; HABITAT CONSERVATION; MAP; POPULATION DISTRIBUTION; POPULATION SIZE; RED LIST;

EID: 84883630192     PISSN: 00063207     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.biocon.2013.08.009     Document Type: Article

References (103)

1. Allouche O., Steinitz O., Rotem D., Rosenfeld A., Kadmon R. Incorporating distance constraints into species distribution models. J. Appl. Ecol. 2008, 45:599-609.
2. Allouche O., Tsoar A., Kadmon R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 2006, 43:1223-1232.
3. Araújo M.B., New M. Ensemble forecasting of species distributions. Trends Ecol. Evol. 2007, 22:42-47.
4. Araújo M.B., Pearson R., Thuiller W., Erhard M. Validation of species-climate impact models under climate change. Glob. Change Biol. 2005, 11:1504-1513.
5. Arino O., Bicheron P., Achard F., Latham J., Witt R., Weber J.-L. GLOBCOVER The most detailed portrait of Earth. ESA Bulletin - European Space Agency 2008, 136:24-31.
6. Barbet-Massin M., Thuiller W., Jiguet F. How much do we overestimate future local extinction rates when restricting the range of occurrence data in climate suitability models?. Ecography 2010, 33:878-886.
7. Berkes F. Rethinking community-based conservation. Conserv. Biol. 2004, 18:621-630.
8. BirdLife International Birds in Europe: Population Estimates, Trends and Conservation Status 2004, BirdLife International, Wageningen.
9. Birdlife International, 2012. Crex crex. In: IUCN Red List of Threatened Species Version 2012.1.
10. Boyce M., McDonald L. Relating populations to habitats using resource selection functions. Trends Ecol. Evol. 1999, 14:268-272.
11. Brambilla M., Ficetola G.F. Species distribution models as a tool to estimate reproductive parameters: a case study with a passerine bird species. J. Animal Ecol. 2012, 81:781-787.
12. Breiman L. Statistical modeling: the two cultures. Stat. Sci. 2001, 16:199-231.
13. Breiman L. Random forests. Mach. Learn. 2001, 5-32.
14. Breiman L., Friedman J., Stone C.J., Olshen R.A. Classification and Regression Trees 1984, Chapman & Hall.
15. Broennimann O., Fitzpatrick M.C., Pearman P.B., Petitpierre B., Pellissier L., Yoccoz N.G., Thuiller W., Fortin M.-J., Randin C., Zimmermann N.E., Graham C.H., Guisan A. Measuring ecological niche overlap from occurrence and spatial environmental data. Glob. Ecol. Biogeogr. 2012, 21:481-497.
16. Burgman M., Carr A., Godden L., Gregory R., McBride M., Flander L., Maguire L. Redefining expertise and improving ecological judgment. Conserv. Lett. 2011, 4:81-87.
17. Burgman M.A., Fox J.C. Bias in species range estimates from minimum convex polygons: implications for conservation and options for improved planning. Anim. Conserv. 2003, 6:19-28.
18. Burnham K.P., Anderson D.R. Model Selection and Multi-Model Inference: A Practical Information-Theoretic Approach 2002, Springer-Verlag, New York.
19. Bustamante J., Seoane J. Predicting the distribution of four species of raptors (Aves: Accipitridae) in southern Spain: statistical models work better than existing maps. J. Biogeogr. 2004, 31:295-306.
20. Bystriakova N., Peregrym M., Erkens R.H.J., Bezsmertna O., Schneider H. Sampling bias in geographic and environmental space and its effect on the predictive power of species distribution models. Syst. Biodivers. 2012, 10:1-11.
21. Cassini M.H. Ranking threats using species distribution models in the IUCN Red List assessment process. Biodivers. Conserv. 2011, 20:3689-3692.
22. Chen I.-C., Hill J.K., Ohlemüller R., Roy D.B., Thomas C.D. Rapid range shifts of species associated with high levels of climate warming. Science 2011, 333:1024-1026.
23. Costa G.C., Nogueira C., Machado R.B., Colli G.R. Sampling bias and the use of ecological niche modeling in conservation planning: a field evaluation in a biodiversity hotspot. Biodivers. Conserv. 2009, 19:883-899.
24. Czech B. Economic growth as the limiting factor for wildlife conservation. Wildl. Soc. Bull. 2000, 28:4-15.
25. Czech B., Krausman P.R. Distribution and causation of species endangerment in the United States. Science 1997, 277:1116-1117.
26. Drew C.A., Perera A.H. Expert knowledge as a basis for landscape ecological predictive models. Predictive Species and Habitat Modeling in Landscape Ecology: Concepts and Applications 2011, 229-248. Springer, New York. C.A. Drew, Y.F. Wiersma, F. Huettmann (Eds.).
27. Dudík, M., Schapire, R.E., Phillips, S.J., 2005. Correcting sample selection bias in maximum entropy density estimation. Appearing in Advances in Neural Information Processing Systems, p. 18.
28. Elith J., Graham C.H., Anderson R.P., Dudík M., Ferrier S., Guisan A., Hijmans R.J., Huettmann F., Leathwick J.R., Lehmann A., Li J., Lohmann L.G., Loiselle B., Manion G., Moritz C., Nakamura M., Nakazawa Y., Overton J.M., Townsend Peterson A., 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.
29. Elith J., Kearney M., Phillips S.J. The art of modelling range-shifting species. Methods Ecol. Evol. 2010, 1:330-342.
30. Elith J., Leathwick J.R. Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 2009, 40:677-697.
31. 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, 17:43-47.
32. FAO, 2007. FAOSTAT - Machinery and Equipment statistics. Food and Agriculture Organization of the United Nations, Rome, Italy.
33. Fielding A.H., Bell J.F. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ. Conserv. 1997, 24:38-49.
34. Filz K.J., Schmitt T., Engler J.O. How fine is fine-scale? Questioning the use of fine-scale bioclimatic data in species distribution models used for forecasting abundance patterns in butterflies. Eur. J. Entomol. 2013, 110:311-317.
35. Fourcade, Y., Engler, J.O., Rödder, D., Secondi, J., submitted for publication. Assessing the performance of correction methods for geographical sampling bias in species distribution models.
36. Franklin J. Mapping Species Distributions: Spatial Inference and Prediction (Ecology, Biodiversity and Conservation) 2010, Cambridge University Press.
37. Freeman E.A., Moisen G. {PresenceAbsence}: An R package for presence absence analysis. J. Stat. Softw. 2008, 23:1-31.
38. Friedman J. Multivariate adaptive regression splines. Annals Stat. 1991, 19:1-67.
39. Gaston K.J., Blackburn T., Greenwood J., Gregory R., Quinn R.M., Lawton J.H. Abundance-occupancy relationships. J. Appl. Ecol. 2000, 37:39-59.
40. Grand J., Cummings M.P., Rebelo T.G., Ricketts T.H., Neel M.C. Biased data reduce efficiency and effectiveness of conservation reserve networks. Ecol. Lett. 2007, 10:364-374.
41. Green R.E., Rayment M.D. Geographical variation in the abundance of the Corncrake Crex crex in Europe in relation to the intensity of agriculture. Bird Conserv. Int. 1996, 6:201-211.
42. Green R.E., Rocamora G., Schäffer N. Populations, ecology and threats to the Corncrake Crex crex in Europe. Vogelwelt 1997, 118:117-134.
43. Green R.E., Stowe T.J. The decline of the corncrake Crex crex in Britain and Ireland in relation to habitat change. J. Appl. Ecol. 1993, 30:689-695.
44. Green R.E., Tyler G.A., Stowe T.J., Newton A.V. A simulation model of the effect of mowing of agricultural grassland on the breeding success of the corncrake (Crex crex). J. Zool. 1997, 243:81-115.
45. Guisan A., Zimmermann N.E. Predictive habitat distribution models in ecology. Ecol. Model. 2000, 135:147-186.
46. Guthery F., Brennan L., Peterson M., Lusk J. Information theory in wildlife science: critique and viewpoint. J. Wildlife Manage. 2005, 69:457-465.
47. Hanley A., Mcneil J. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982, 143:29-36.
48. Hayward M.W. The need to rationalize and prioritize threatening processes used to determine threat status in the IUCN Red List. Conserv. Biol. 2009, 23:1568-1576.
49. Heikkinen R.K., Luoto M. Methods and uncertainties in bioclimatic envelope modelling under climate change. Prog. Phys. Geogr. 2006, 6:751-777.
50. Herzog S.K., Maillard Z.O., Embert D., Caballero P., Quiroga D. Range size estimates of Bolivian endemic bird species revisited: the importance of environmental data and national expert knowledge. J. Ornithol. 2012, 153:1189-1202.
51. Hijmans R.J. Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model. Ecology 2012, 93:679-688.
52. 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.
53. IUCN, 2001. IUCN Red List Categories and Criteria, Version 3.1. IUCN - The World Conservation Union, Gland, Switzerland.
54. IUCN, 2005. Resolution 3.013: The Uses of the IUCN Red List of Threatened Species. In: Resolutions and Recommendations: World Conservation Congress, Bangkok, Thailand, 17-25 November 2004. IUCN ed., pp. 14-16.
55. IUCN Standards and Petitions Subcommittee, 2010. Guidelines for Using the IUCN Red List Categories and Criteria. Version 8.1. Standards and Petitions Subcommittee,
56. Jeschke J., Strayer D. Usefulness of bioclimatic models for studying climate change and invasive species. Ann. NY Acad. Sci. 2008, 1134:1-24.
57. Jetz W., Sekercioglu C.H., Watson J.E.M. Ecological correlates and conservation implications of overestimating species geographic ranges. Conserv. Biol. 2008, 22:110-119.
58. Jiménez-Alfaro B., Draper D., Nogués-Bravo D. Modeling the potential area of occupancy at fine resolution may reduce uncertainty in species range estimates. Biol. Conserv. 2012, 147:190-196.
59. Jiménez-Valverde A., Acevedo P., Barbosa a.M., Lobo J.M., Real R. Discrimination capacity in species distribution models depends on the representativeness of the environmental domain. Glob. Ecol. Biogeogr. 2012.
60. Kadmon R., Farber O., Danin A. Effect of roadside bias on the accuracy of predictive maps produced by bioclimatic models. Ecol. Appl. 2004, 14:401-413.
61. Kamp J., Urazaliev R., Donald P.F., Hölzel N. Post-Soviet agricultural change predicts future declines after recent recovery in Eurasian steppe bird populations. Biol. Conserv. 2011, 144:2607-2614.
62. Keišs O. Recent increases in numbers and the future of Corncrake Crex crex in Latvia. Ornis Hungarica 2003, 12-13:151-156.
63. Keišs O. Impact of changes in agricultural land use on the Corncrake Crex crex population in Latvia. Acta Universitatis Latviensis 2005, 691:93-109.
64. Koffijberg K., Schäffer N. Species Action Plan Corncrake Crex crex 2005, BirdLife International.
65. Kramer-Schadt, S., Niedballa, J., Pilgrim, J.D., Schröder, B., Lindenborn, J., Reinfelder, V., Stillfried, M., Heckmann, I., Scharf, A.K., Augeri, D.M., Cheyne, S.M., Hearn, A.J., Ross, J., Macdonald, D.W., Mathai, J., Eaton, J., Marshall, A.J., Semiadi, G., Rustam, R., Bernard, H., Alfred, R., Samejima, H., Duckworth, J.W., Breitenmoser-Wuersten, C., Belant, J.L., Hofer, H., Wilting, A., 2013. The importance of correcting for sampling bias in MaxEnt species distribution models. Diversity and Distributions.
66. Leitão P.J., Moreira F., Osborne P.E. Effects of geographical data sampling bias on habitat models of species distributions: a case study with steppe birds in southern Portugal. Int. J. Geogr. Inform. Sci. 2011, 25:439-454.
67. Lobo J.M., Jiménez-Valverde A., Real R. AUC: a misleading measure of the performance of predictive distribution models. Glob. Ecol. Biogeogr. 2008, 17:145-151.
68. Mace G.M., Collar N.J., Gaston K.J., Hilton-Taylor C., Akçakaya H.R., Leader-Williams N., Milner-Gulland E.J., Stuart S.N. Quantification of extinction risk: IUCN's system for classifying threatened species. Conserv. Biol. 2008, 22:1424-1442.
69. Maisongrande P., Duchemin B., Dedieu G. VEGETATION/SPOT: an operational mission for the Earth monitoring; presentation of new standard products. Int. J. Remote Sens. 2004, 25:9-14.
70. Manly B.F.J., McDonald L.L., Thomas D. Resource Selection by Animals: Statistical Design and Analysis for Field Studies 1993, Chapman & Hall.
71. Martin T.G., Burgman M.a., Fidler F., Kuhnert P.M., Low-Choy S., Mcbride M., Mengersen K. Eliciting Expert Knowledge in Conservation Science. Conserv. Biol. 2012, 26:29-38.
72. Matthews S.N., Iverson L.R., Prasad A.M., Peters M.P. Changes in potential habitat of 147 North American breeding bird species in response to redistribution of trees and climate following predicted climate change. Ecography 2011, 34:933-945.
73. McCullagh P., Nelder J.A. Generalized Linear Models 1989, Chapman & Hall, London, UK.
74. Merow, C., Smith, M.J., Silander, J.a., 2013. A practical guide to MaxEnt for modeling species' distributions: what it does, and why inputs and settings matter. Ecography, no-no.
75. Mischenko A. Corncrake Crex crex monitoring in European Russia in 2002-2003: a pilot study. Revista Catalana d'Ornitologia 2008, 65-70.
76. Ockendon N., Hewson C.M., Johnston A., Atkinson P.W. Declines in British-breeding populations of Afro-Palaearctic migrant birds are linked to bioclimatic wintering zone in Africa, possibly via constraints on arrival time advancement. Bird Study 2012, 59:111-125.
77. Olesen J.E., Bindi M. Consequences of climate change for European agricultural productivity, land use and policy. Eur. J. Agron. 2002, 16:239-262.
78. Osborne P.E., Suárez-Seoane S. Should data be partitioned spatially before building large-scale distribution models?. Ecol. Model. 2002, 157:249-259.
79. Pearce J.L., Cherry K.M.D.S.F., Whish G. Incorporating expert opinion and fine-scale vegetation mapping into statistical models of faunal distribution. J. Appl. Ecol. 2001, 38:412-424.
80. Expert Knowledge and Its Application in Landscape Ecology 2012, Springer, New York. A.H. Perera, C.A. Drew, C.J. Johnson (Eds.).
81. Peterson A., Soberón J., Pearson R., Anderson R., Martínez-Meyer E., Nakamura M., Araújo M.B. Ecological Niches and Geographic Distributions 2011, Princeton University Press, Princeton, NJ, USA.
82. Phillips S.J., Anderson R.P., Schapire R.E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 2006, 190:231-259.
83. Phillips S.J., Dudík M., Elith J., Graham C.H., Lehmann A., Leathwick J.R., Ferrier S. Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecol. Appl. 2009, 19:181-197.
84. Phillips, S.J., Dudík, M., Schapire, R.E., 2004. A maximum entropy approach to species distribution modeling. In: Proceedings of the Twenty-first International Conference on Machine Learning. ACM, New York, New York, USA, p. 83.
85. Renner I.W., Warton D.I. Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology. Biometrics 2013, 69:274-281.
86. Ridgeway G. The state of boosting. Comput. Sci. Stat. 1999, 31:172-181.
87. Ripley B.D. Pattern Recognition and Neural Networks 1996, Cambridge University Press, Cambridge, UK.
88. Rödder D., Engler J.O. Quantitative metrics of overlaps in Grinnellian niches: advances and possible drawbacks. Glob. Ecol. Biogeogr. 2011, 20:915-927.
89. Rödder D., Kielgast J., Bielby J., Schmidtlein S., Bosch J., Garner T.W.J., Veith M., Walker S., Fisher M.C., Lötters S. Global amphibian extinction risk assessment for the panzootic chytrid fungus. Diversity 2009, 1:52-66.
90. Rodrigues A.S.L., Pilgrim J.D., Lamoreux J.F., Hoffmann M., Brooks T.M. The value of the IUCN Red List for conservation. Trends Ecol. Evol. 2006, 21:71-76.
91. Sanderson F.J., Kucharz M., Jobda M., Donald P.F. Impacts of agricultural intensification and abandonment on farmland birds in Poland following EU accession. Agric. Ecosyst. Environ. 2013, 168:16-24.
92. Schäffer N., Koffijberg K. Crex crex Corncrake. Bwp Update 2004, 6:57-78.
93. Schoener T. The Anolis lizards of Bimini: resource partitioning in a complex fauna. Ecology 1968, 49:704-726.
94. Schwarz G. Estimating the dimension of a model. Annals Stat. 1978, 6:461-464.
95. Sing, T., Sander, O., Beerenwinkel, N., Lengauer, T., 2012. ROCR: Visualizing the performance of scoring classifiers.
96. Stephens P.a., Buskirk S.W., Hayward G.D., Martinez Del Rio C. Information theory and hypothesis testing: a call for pluralism. J. Appl. Ecol. 2005, 42:4-12.
97. Sukhanova O., Mischenko A. Monitoring Corncrake Crex crex numbers in European Russia: the first stage. Ornis Hungarica 2003, 12:135-141.
98. Sutherland W.J., Pullin A.S., Dolman P.M., Knight T.M. The need for evidence-based conservation. Trends Ecol. Evol. 2004, 19:305-308.
99. Swets J.A. Measuring the accuracy of diagnostic systems. Science 1988, 240:1285-1293.
100. TÔrres N.M., De Marco P., Santos T., Silveira L., de Almeida Jácomo A.T., Diniz-Filho J.A.F. Can species distribution modelling provide estimates of population densities? A case study with jaguars in the Neotropics. Divers. Distrib. 2012, 18:615-627.
101. Tyler G.A., Green R.E., Casey C. Survival and behaviour of Corncrake Crex crex chicks during the mowing of agricultural grassland. Bird Study 1998, 45:35-50.
102. VanDerWal J., Shoo L.P., Johnson C.N., Williams S.E. Abundance and the environmental niche: environmental suitability estimated from niche models predicts the upper limit of local abundance. Am. Nat. 2009, 174:282-291.
103. Wisz M.S., Hijmans R.J., Li J., Peterson A.T., Graham C.H., Guisan A. Effects of sample size on the performance of species distribution models. Divers. Distrib. 2008, 14:763-773.