Quantitative prediction of the distribution and abundance of Vaccinium myrtillus with climatic and edaphic factors

Journal of Vegetation Science

Volumn 18, Issue 4, 2007, Pages 517-524

  Coudun, Christophe ^a   Gegout, Jean Claude ^b  

^a AREP Center   (France)

^b AGROPARISTECH   (France)

Author keywords

Ecoinformatics; EcoPlant; France; Nitrogen nutrition; Ordinal data; pH; Predictive mapping; Proportional odds model; Species distribution modelling

Indexed keywords

ABUNDANCE; CLIMATE CONDITIONS; ECOLOGICAL MODELING; ENVIRONMENTAL FACTOR; GEOGRAPHICAL DISTRIBUTION; HABITAT SELECTION; RANGE EXPANSION; SHRUB; SOIL NUTRIENT; SOIL PROPERTY; SPECIES OCCURRENCE;

EURASIA; EUROPE; FRANCE; MASSIF CENTRAL; WESTERN EUROPE;

VACCINIUM MYRTILLUS;

EID: 34249995145     PISSN: 11009233     EISSN: None     Source Type: Journal    
DOI: 10.1658/1100-9233(2007)18[517:QPOTDA]2.0.CO;2     Document Type: Article

References (62)

1. Anon. 1999. S-Plus 2000: programmer's guide. MathSoft, Inc., Seattle, WA, US.
2. Araújo, M.B. & Guisan, A. 2006. Five (or so) challenges for species distribution modelling. J. Biogeogr. 33: 1677-1688.
3. Atlegrim, O. & Sjoberg, K. 1996. Response of bilberry (Vaccinium myrtillus) to clear-cutting and single-tree selection harvests in uneven-aged boreal Picea abies forests. For. Ecol. Manage. 86: 39-50.
4. Austin, M.P. 1999. The potential contribution of vegetation ecology to biodiversity research. Ecography 22: 465-484.
5. Austin, M.P. 2002. Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecol. Model. 157: 101-118.
6. Baines, D., Moss, R. & Dugan, D. 2004. Capercaillie breeding success in relation to forest habitat and predator abundance. J. Appl. Ecol. 41: 59-71.
7. Bender, R. & Benner, A. 2000. Calculating ordinal regression models in SAS and S-Plus. Biometretical J. 42: 677-699.
8. Benichou, P. & Le Breton, O. 1987. Prise en compte de la topographie pour la cartographie des champs pluviometriques statistiques. La Météorologie 7: 23-34.
9. Braun-Blanquet, J. 1932. Plant sociology, the study of plant communities. McGraw Hill, New York, NY, US.
10. Brisse, H., de Ruffray, P., Grandjouan, G. & Hoff, M. 1995. European Vegetation Survey. The phytosociological database "SOPHY". Part 1. Calibration of indicator plants. Part 2. Socio-ecological classification of the relevés. Annali di Botanica 53: 177-223.
11. Brown, J.H. 1984. On the relationship between abundance and distribution of species. Am. Nat. 124: 255-279.
12. Brown, J.H., Mehlman, D.W. & Stevens, G.C. 1995. Spatial variation in abundance. Ecology 76: 2028-2043.
13. Callaway, R.M., Brooker, R.W., Choler, P., Kikvidze, Z., Lortie, C.J., Michalet, R., Paolini, L., Pugnaire, F.L., Newingham, B., Aschehoug, E.T., Armas, C., Kikodze, D., & Cook, B.J. 2002. Positive interactions among alpine plants increase with stress. Nature 417: 844-848.
14. Chapin, F.S. III, Vitousek, P.M. & Van Cleve, K. 1986. The nature of nutrient limitation in plant communities. Am. Nat. 127: 48-58.
15. Coudun, Ch. 2005. Approche quantitative de la réponse écologique des espèces végétales forestières à l'échelle de la France. Ph.D. Thesis, French Institute of Forestry, Agricultural and Environmental Engineering, Nancy, FR.
16. Coudun, Ch. & Gégout, J.-C. 2006. The derivation of species response curves with Gaussian logistic regression models is sensitive to sampling intensity and curve characteristics. Ecol. Model. 199: 164-175.
17. Coudun, Ch., Gégout, J.-C., Piedallu, Ch. & Rameau, J.-C. 2006. Soil nutritional factors improve plant species distribution models: an illustration with Acer campestre (L.) in France. J. Biogeogr. 33: 1750-1763.
18. de Ruffray, P. 1980. Caractérisation climatique de deux espèces spontanées à petits fruits: le framboisier (Rubus idaeus L.) et la myrtille (Vaccinium myrtillus L.). Productions spontanées, INRA (French National Institute for Agricultural Research), Colmar, FR.
19. Ellenberg, H., Weber, H.E., Düll, R., Wirth, V., Werner, W. & Paulißen, D. 1992. Zeigerwerte von Pflanzen in Mitteleuropa. Scripta Geobot. 18: 1-248.
20. Fielding, A.H. & Bell, J.F. 1997. A review of methods for the assessment of prediction errors in conservation presence/ absence models. Envir. Conserv. 24: 38-49.
21. Flower-Ellis, J.G.K. 1971. Age structure and dynamics in stands of bilberry (Vaccinium myrtillus L.). Ph.D. Thesis, Royal College of Forestry, Stockholm, SE.
22. Gaston, K.J., Blackburn, T.M., Greenwood, J.J.D., Gregory, R.D., Quinn, R. & Lawton, J.H. 2000. Abundance-occupancy relationships. J. Appl. Ecol. 37: 39-59.
23. Gégout, J.-C. 2001. Création d'une base de données phytoécologiques pour déterminer l'autécologie des espèces de la Flore Forestière de France. Rev. For. Fr. 53: 397-403.
24. Gégout, J.-C., Coudun, Ch., Brisse, H. & Bergès, L. 2002. Comportement écologique des espèces forestières vis-à-vis du climat et du sol en France: application à l'évaluation des charges critiques d'acidité et d'azote. Tech. Rep. French Institute of Forestry, Agricultural and Environmental Engineering, Nancy, FR.
25. Gégout, J.-C., Hervé, J.-C., Houllier, F. & Pierrat, J.-C. 2003. Prediction of forest soil nutrient status using vegetation. J. Veg. Sci. 14: 55-62.
26. Gégout, J.-C., Coudun, Ch., Bailly, G. & Jabiol, B. 2005. EcoPlant: a forest site database linking floristic data with soil and climate variables. J. Veg. Sci. 16: 257-260.
27. Guisan, A. 2002. Semi-quantitative models for predicting the spatial distribution of plant species. In: Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, M., Raphael, M. & Wall, B. (eds.) Predicting species occurrences: issues of accuracy and scale, pp. 315-326. Island Press, Covelo, CA, US.
28. Guisan, A. & Harrell, F.E. Jr. 2000. Ordinal response regression models in ecology. J. Veg. Sci. 11: 617-626.
29. Guisan, A., Edwards, T.C. Jr. & Hastie, T.J. 2002. Generalized linear and generalized additive models in studies of species distributions: setting the scene. Ecol. Model. 157: 89-100.
30. Guisan, A., Lehmann, A., Ferrier, S., Austin, M.P., Overton, J.McC., Aspinall, R.J. & Hastie, T.J. 2006. Making better biogeographical predictions of species' distributions. J. Appl. Ecol. 43: 386-392.
31. Hester, A.J., Miles, J., & Gimingham, C.H. 1991. Succession from heather moorland to birch woodland. II. Growth and competition between Vaccinium myrtillus, Deschampsia flexuosa and Agrostis capillaris. J. Ecol. 79: 317-328.
32. Holt, R.D., Lawton, J.H., Gaston, K.J. & Blackburn, T.M. 1997. On the relationship between range size and local abundance: back to basics. Oikos 78: 183-190.
33. Ihalainen, M. & Pukkala, T. 2001. Modelling cowberry (Vaccinium vitis-idaea) and bilberry (Vaccinium myrtillus) yields from mineral soils and peatlands on the basis of visual field estimates. Silva Fennica 35: 329-340.
34. Ihalainen, M., Alho, J., Kolehmainen, O. & Pukkala, T. 2002. Expert models for bilberry and cowberry yields in Finnish forests. For. Ecol. Manage. 157: 15-22.
35. Ihalainen, M., Salo, K. & Pukkala, T. 2003. Empirical prediction models for Vaccinium myrtillus and V. vitis-idaea berry yields in North Karelia, Finland. Silva Fennica 37: 95-108.
36. Ihalainen, M., Pukkala, T. & Saastamoinen, O. 2005. Regional expert models for bilberry and cowberry yields in Finland. Boreal Environ. Res. 10: 145-158.
37. James, F.C. & McCulloch, C.E. 2002. Predicting species presence and abundance. In: Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, M., Raphael, M. & Wall, B. (eds.) Predicting species occurrences: issues of accuracy and scale, pp. 461-465. Island Press, Covelo, CA, US.
38. Jones, M.T., Niemi, G.J., Hanowski, J.M. & Regal, R.R. 2002. Poisson regression: a better approach to modelling abundance data? In: Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, M., Raphael, M. & Wall, B. (eds) Predicting species occurrences: issues of accuracy and scale, pp. 411-418. Island Press, Covelo, CA, US.
39. Lehmann, A., Overton, J.McC. & Austin, M.P. 2002. Regression models for spatial prediction: their role for biodiversity and conservation. Biodiv. Conserv. 11: 2085-2092.
40. Maestre, F.T., Valladares, F. & Reynolds, J.F. 2005. Is the change of plant-plant interactions with abiotic stress predictable? A meta-analysis of field results in arid environments. J. Ecol. 93: 748-757.
41. Mäkipää, R. 1999. Response patterns of Vaccinium myrtillus and V. vitis-idaea along nutrient gradients in boreal forest. J. Veg. Sci. 10: 17-26.
42. Manel, S., Williams, H.C. & Ormerod, S.J. 2001. Evaluating presence-absence models in ecology: the need to account for prevalence. J. Appl. Ecol. 38: 921-931.
43. Maurer, B.A. 2002. Predicting distribution and abundance: thinking within and between scales. In: Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, M., Raphael, M. & Wall, B. (eds.) Predicting species occurrences: issues of accuracy and scale, pp. 411-418. Island Press, Covelo, CA, US.
44. McCullagh, P. & Nelder, J.A. 1997. Generalized linear models. Chapman & Hall, London, UK.
45. Moisen, G.G., Edwards, T.C. Jr. & Osborne, P.E. 2006. Further advances in predicting species distributions. Ecol. Model. 199: 129-131.
46. Mueller-Dombois, D. & Ellenberg, H. 1974. Aims and methods of vegetation ecology. Wiley, New York, NY, US.
47. Noest, V., van der Maarel, E., van der Meulen, F. & van der Laan, D. 1989. Optimum-transformation of plant species cover-abundance values. Vegetatio 83: 167-178.
48. Pearce, J. & Ferrier, S. 2001. The practical value of modelling relative abundance of species for regional conservation planning: a case study. Biol. Conserv. 98: 33-43.
49. Pinto, P. & Gégout, J.-C. 2005. Assessing the nutritional and climatic response of temperate tree species in the Vosges Mountains. Ann. For. Sci. 62: 1-10.
50. Potts, J.M. & Elith, J. 2006. Comparing species abundance models. Ecol. Model. 199: 153-163.
51. Rameau, J.-C., Mansion, D., Dumé, G., Timbal, J., Lecointe, A., Dupont, P. & Keller, R. 1989. Flore forestière franc̀aise. Guide écologique illustré. Tome 1: plaines et collines. Institut pour le Développement Forestier, Paris, FR.
52. Rameau, J.-C., Mansion, D. & Dumé, G. 1993. Flore forestière française. Guide écologique illustré. Tome 2 : montagnes. Institut pour le Développement Forestier, Paris, FR.
53. Ritchie, J.C. 1956. Vaccinium myrtillus L. J. Ecol. 44: 291-299.
54. Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, M., Raphael, M. & Wall, B. 2002. Predicting species occurrences: issues of accuracy and scale. Island Press, Covelo, CA, US.
55. Selas, V. 2000. Population dynamics of capercaillie Tetrao urogallus in relation to bilberry (Vaccinium myrtillus) production in southern Norway. Wildl. Biol. 6: 1-11.
56. Seynave, I., Gégout, J.-C., Hervé, J.-C., Dhôte, J.-F., Drapier, J., Bruno, E. & Dumé, G. 2005. Picea abies site index prediction by environmental factors and understorey vegetation: a two-scale approach based on survey databases. Can. J. For. Res. 35: 1669-1678.
57. Storch, I. 1993. Habitat selection by Capercaillie in summer and autumn - Is Bilberry important? Oecologia 95: 257-265.
58. ter Braak, C.J.F. & Looman, C.W.N. 1986. Weighted averaging, logistic regression and the Gaussian response model. Vegetatio 65: 3-11.
59. Turc, L. 1961. Evaluation des besoins en eau d'irrigation et évaporation potentielle. Ann. Agron. 12: 13-49.
60. van der Maarel, E. 1979. Transformation of cover-abundance values in phytosociology and its effects on community similarity. Vegetatio 39: 97-114.
61. Vincent, P.J. & Haworth, J.M. 1983. Poisson regression models of species abundance. J. Biogeogr. 10: 153-160.
62. Woodward, F.I. 1986. Ecophysiological studies on the shrub Vaccinium myrtillus L. taken from a wide altitudinal range. Oecologia 70: 580-586.