Habitat quality assessment using Weights-of-Evidence based GIS modelling: The case of Picoides tridactylus as species indicator of the biodiversity value of the Finnish forest

Ecological Modelling

Volumn 196, Issue 1-2, 2006, Pages 62-76

  Romero Calcerrada, Raul ^a   Luque, Sandra ^b  

^a UNIVERSIDAD REY JUAN CARLOS   (Spain)

^b FINNISH FOREST RESEARCH INSTITUTE   (Finland)

Author keywords

Bayesian statistics; Biodiversity indicators; Habitat quality modelling; Landscape monitoring; National Forest Inventory

Indexed keywords

FORESTRY; GEOGRAPHIC INFORMATION SYSTEMS; LAND USE; PROBABILITY DISTRIBUTIONS;

BAYESIAN STATISTICS; BIODIVERSITY INDICATORS; HABITAT QUALITY MODELLING; LANDSCAPE MONITORING; NATIONAL FOREST INVENTORY;

BIODIVERSITY;

BIODIVERSITY; BIRD; BOREAL FOREST; DATABASE; DECISION MAKING; FOREST MANAGEMENT; GIS; HABITAT QUALITY; HABITAT SELECTION; LANDSCAPE CHANGE; PROBABILITY; QUALITATIVE ANALYSIS;

BIODIVERSITY; FOREST MANAGEMENT; QUALITY CONTROL;

EURASIA; EUROPE; FINLAND; NORTHERN EUROPE; SCANDINAVIA;

PICOIDES TRIDACTYLUS;

EID: 33744543473     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2006.02.017     Document Type: Article

References (77)

1. Ahti T., Hämet-Ahti L., and Jalas J. Vegetation zones and their sections in northwestern Europe. Ann. Bot. Fenn. 5 (1968) 169-211
2. Agterberg F.P., Bonham-Carter G.F., and Wright D.F. Statistical pattern integration for mineral exploration. In: Gaal G., and Merriam D.F. (Eds). Computer Applications in Resource Estimation: Prediction and Assessment for Metals and Petroleum (1990), Pergamon Press, Oxford 1-21
3. An P., Moon W.M., and Bonham-Carter G.F. On Knowledge-based Approach Of Integrating Remote Sensing, Geophysical And Geological Information. Geoscience and Remote Sensing Symposium, IGARSS'92 International (1992) 34-38
4. Asadi H.H., and Hale M. A predictive GIS model for potential mapping of gold and base metal mineralization in Takab area, Iran. In: Diaz J., Tynes R., Caldwell D., and Ehlen J. (Eds). Fourth International Conference on GeoComputation Mary Washington College Fredericksburg. GeoComputation CD-ROM, Virginia, USA (1999) 14
5. Asadi H.H., and Hale M. A predictive GIS model for mapping potential gold and base metal mineralization in Takab area, Iran. Comput. Geosci. 27 (2001) 901-912
6. Aspinall R. An inductive modelling procedure based on Bayes' theorem for analysis of pattern in spatial data. Int. J. Geogr. Inf. Syst. 6 (1992) 105-121
7. Aspinall R., and Veitch N. Habitat mapping from satellite imagery and wildlife survey data using a Bayesian modeling procedure in a GIS. Photogramm. Eng. Remote Sens. 59 (1993) 537-543
8. Austin M.P. Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecol. Modell. 157 (2002) 101-118
9. BirdLife International, 2005. Species factsheet: Picoides tridactylus. Downloaded from http://www.birdlife.org on 9/20/2005.
10. Bonham-Carter G.F. Geographic Information Systems for Geoscientists, Modelling with GIS. Computer Methods in Geosceinces vol. 13 (1994), Pergamon, Tarrytwon, New York 398 pp.
11. Bonham-Carter G.F., and Agterberg F.P. Arc-WofE: A GIS Tool for Statistical Integration of Mineral Exploration Datasets. The 52 Session of the International Statistical Institute (1999), Bulletin of the International Statistical Institute, Helsinki, Finland p. 4
12. Bonham-Carter G.F., Agterberg F.P., and Wright D.F. Integration of geological datasets for gold explotation in Nova Scotia. Photogramm. Eng. Remote Sens. 54 (1988) 1585-1592
13. Bonham-Carter G.F., Agterberg F.P., and Wright D.F. Weights of evidence modelling: a new approach to mapping mineral potential. In: Agterberg F.P., and Bonham-Carter G.F. (Eds). Statistical Applications in the Earth Science (1989), Geological Survey of Canada 171-183
14. Carranza E.J.M., and Hale M. Geologically-constrained probabilistic mapping of gold potential, Baguio District, Philippines. In: Diaz J., Tynes R., Caldwell D., and Ehlen J. (Eds). Fourth International Conference on GeoComputation Mary Washington College Fredericksburg. GeoComputation CD-ROM, Virginia, USA (1999) 14
15. Carranza E.J.M., and Hale M. Geologically constrained probabilistic mapping of gold potential, Baguio District, Philippines. Nat. Resour. Res. 9 (2000) 237-253
16. Carranza E.J.M., and Hale M. Where are porphyry copper deposits spatially localized? A case study in Benguet Province, Philippines. Nat. Resour. Res. 11 (2002) 45-59
17. Cowley M.J.R., Wilson R.J., Leon-Cortes J.L., Gutierrez D., Bulman C.R., and Thomas C.D. Habitat-based statistical models for predicting the spatial distribution of butterflies and day-flying moths in a fragmented landscape. J. Appl. Ecol. 37 (2000) 60-72
18. Derleth P., Bütler R., and Schlaepfer R. Le Pic tridactyle (Picoides tridactylus): un indicateur de la qualité écologicue de l'écosystème forestier du Pays-d'Enhaut (Préalpes suisses). Schweizerische Z. Forstwesen 151 (2000) 282-289
19. Dixon P., and Ellison A.M. Introduction: ecological applications of Bayesian inference. Ecol. Appl. 6 (1996) 1034-1035
20. Duffy S.B., Corson M.S., and Grant W.E. Simulating land-use decisions in the La Amistad biosphere reserve buffer zone in Costa Rica and Panama. Ecol. Modell. 140 (2001) 9-29
21. Ellison A.M. Bayesian inference in ecology. Ecol. Lett. 7 (2004) 509-520
22. Essen P.A., Ehnström B., Ericson L., and Sjöberg K. Boreal forests. Ecol. Bull. 46 (1997) 16-47
23. Fayt P. Available insect prey in bark patches selected by the three-toed Woodpecker Picoides tridactylus prior to reproduction. Ornis Fenn. 76 (1999) 135-140
24. Fielding A.H., and Bell J.F. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ. Conserv. 24 (1997) 38-49
25. Finnish Environmental Institute, University of Helsinki/Department of Biological Sciences, Finnish Forest Research Institute, MTT Agrifood Research Finland, 2005. Evaluation of the Finnish National Action Plan 1997-2005 for Biodiversity. Downloaded from http://www.ymparisto.fi/default.asp?node=8410&lan=en on 10/2005.
26. Gibson L.A., Wilson B.A., Cahill D.M., and Hill J. Spatial prediction of rufous bristlebird habitat in a coastal heathland: a GIS-based approach. J. Appl. Ecol. 41 (2004) 213-223
27. Goodacre A.K., Bonham-Carter G.F., Agterberg F.P., and Wright D.F. A statistical analysis of the spatial association of seismicity with drainage patterns and magnetic anomalies in western Quebec. Tectonophysics 217 (1993) 285-305
28. Guisan A., and Zimmermann N.E. Predictive habitat distribution models in ecology. Ecol. Modell. 135 (2000) 147-186
29. Gutzwiller K.J. Applying landscape ecology in biological conservation (2002), Springer, New York 518 pp
30. Harris D.A., and Pan R. Mineral favorability mapping: a comparison of artificial neural networks, logistic regression, and discriminant analysis. Nat. Resour. Res. 8 (1999) 93-109
31. Harris J.R., Wilkinson L., and Grunsky E.C. Effective use and interpretation of lithogeochemical data in regional mineral exploration programs: application of Geographic Information Systems (GIS) technology. Ore Geol. Rev. 16 (2000) 107-143
32. Harris J.R., Wilkinson L., Heather K., Fumerton S., Bernier M.A., Ayer J., and Dahn R. Application of GIS processing techniques for producing mineral prospectivity maps-a case study: mesothermal Au in the Swayze Greenstone Belt, Ontario, Canada. Nat. Resour. Res. 10 (2001) 91-124
33. Hastie T., Tibshirani R., and Friedman J. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer Series in Statistics (2001), Springer-Verlag, New York 533 pp.
34. Hay G.J., Dubé P., Bouchard A., and Marceau D.J. A scale-space primer for exploring and quantifying complex landscapes. Ecol. Modell. 153 (2002) 27-49
35. Hilborn R., and Mangel M. The Ecological Detective: Confronting Models with Data (1997), Princeton University Press, Princeton, NJ
36. Hooten M.B., Larsen D.R., and Wikle C.K. Predicting the spatial distribution of ground flora on large domains using a hierarchical Bayesian model. Landsc. Ecol. 18 (2003) 487-502
37. Imbeau L., and Desrochers A. Area sensitivity and edge avoidance: the case of the three-toed Woodpecker (Picoides tridactylus) in a managed forest. Forest Ecol. Manage. 164 (2002) 249-256
38. Jaberg C., and Guisan A. Modelling the distribution of bats in relation to landscape structure in a temperate mountain environment. J. Appl. Ecol. 38 (2001) 1169-1181
39. Jerina K., Debeljak M., Dzeroski S., Kobler A., and Adamic M. Modeling the brown bear population in Slovenia: a tool in the conservation management of a threatened species. Ecol. Modell. 170 (2003) 453-469
40. Jumppanen J., Kurttila M., Pukkala T., and Uuttera J. Spatial harvest scheduling approach for areas involving multiple ownership. Forest Pol. Econ. 5 (2003) 27-38
41. Kemp, L.D., Bonham-Carter, G.F. and Raines, G.L., 1999. WofE: Arcview extension for weights of evidence mapping. http://ntserv.gis.nrcan.gc.ca/wofe.
42. Kemp, L.D., Bonham-Carter, G.F., Raines, G.L. and Looney, C.G., 2001. Arc-SDM: Arcview extension for spatial data modelling using weights of evidence, logistic regression, fuzzy logic and neuronal networks analysis. http://ntserv.gis.nrcan.gc.ca/sdm/.
43. Kouki J. Biodiversity in the Fennoscandian boreal forests: natural variation and its management. Ann. Zool. Fenn. 31 (1994) 1-217
44. Kouki J., and Niemelä P. The biological heritage of Finnish forests. In: Opas L.L. (Ed). Finnish Forests (1997), University of Joensuu, Joensuu 13-33
45. Kouki J., and Löfman S. Forest fragmentation: processes, concepts and implications for especies. In: Dover J.W., and Bunce R.G.H. (Eds). Key Concepts of Landscape Ecology (1998), IALE (UK), Preston 187-203
46. Larson M.A., Thompson III F.R., Millspaugh J.J., Dijak W.D., and Shifley S.R. Linking population viability, habitat suitability, and landscape simulation models for conservation planning. Ecol.l Modell. 180 (2004) 103-118
47. Linder P., and Ostlund L. Structural changes in three mid-boreal Swedish forest landscapes, 1885-1996. Biol. Conserv. 85 (1998) 9-19
48. Luque, S., Joenssu, J.J., Romero-Calcerrada R., Tomppo, E., 2006. Changes in the Finnish forest landscape: a multicriteria biodiversity assessment approach. Landsc. Urban Plann., in press (Special Issue on Biodiversity Indicators).
49. Luque S., Riutta T., Joensuu J., Rautjärvi N., and Tomppo E. Multi-source forest inventory data for biodiversity monitoring and planning at the forest landscape level. In: Marchetti M. (Ed). Monitoring and Indicators of Forest Biodiversity in Europe-From Ideas to Operationality (2004), EFI, IUFRO 430-444
50. Luque S., Riutta T., Joensuu J., and Tomppo E. Spatial analysis and remote sensing for biodiversity monitoring and planning at the forest landscape level. Actes Hermes-science CASSINI'04, 7ème Conference GDR SIGMA, Géomatique et Analyse Spatiale (2004) 149-155
51. Löfman S., and Kouki J. Fifty years of landscape transformation in managed forests of southern Finland. Scand. J. For. Res. 16 (2001) 44-53
52. Miller K.R., and Lanou S.M. National biodiversity planning: guidelines based on early experiences around the world. World Resources Institute; United Nations Environment Programme; World Conservation Union. Washington, USA; Nairobi; Gland, Switzerland (1995)
53. Milne B.T., Johnston K.M., and Forman R.T.T. Scale-dependent proximity of wildlife habitat in a spatially-neutral Bayesian model. Landsc. Ecol. 2 (1989) 101-110
54. Ministry of Environment, 1992. Uhanalaisten eläinten ja kasvien seurantatoimikunnan mietintö-Betänkande av komissionen för övervakning av hotade djur och växter (Report on the monitoring of threatened animals and plants in Finland). Komiteanmietintö-Commitee Report 1991: 3019.2.1992. Ympäristöministeriö-Helsinki (In Finnish with Swedish and English summaries).
55. Ministry of Environment, 1999. Metsien suojelupinta-alat. Suojelupinta-alaprojektin raportti. Ympäristöministeriö-Helsinki. 43 pp. (In Finnish).
56. Nuutinen T., Anola-Pukkila A., Haara A., Kärkkäinen L., Lempinen R., Muinoven E., Redsven V., Hirvelä H., Härkönen K., Salminen O., Siitonen M., Teuri M., and Lappi J. Team report from Finnish Forest Research Institute, MELA Team. Nordic Trends in Forest Inventory, Management Planning and Modelling Proceedings of SNS Meeting. Slovalla, Finland, April 17-19 (2001) 21-28
57. Osborne P.E., Alonso J.C., and Bryant R.G. Modelling landscape-scale habitat use using GIS and remote sensing: a case study with great bustards. J. Appl. Ecol. 38 (2001) 458-471
58. Pakkala T., Hanski I., and Tomppo E. Spatial ecology of the three-toed Woodpecker in managed forest landscapes. Silva Fenn. 36 (2002) 279-288
59. Pechacek P., and d'Oleire-Oltmanns W. Habitat use of the three-toed woodpecker in central Europe during the breeding period. Biol. Conserv. 116 (2004) 333-341
60. Rautjärvi N., Luque S., and Tomppo E. Mapping spatial patterns from National Forest Inventory data: a regional conservation planning tool. GGRS Proceedings: Göttingen GIS and Remote Sensing Days: Environmental Studies. GGRS, Göttingen, Germany (2004)
61. Romero-Calcerrada, R., 2002. Metodología para la planificación y desarrollo sostenible en espacios naturales protegidos europeos: las zonas de especial protección para las aves. GeoFocus (Artículos), 2: 1-32. www.geo-focus.org.
62. Rushton S.P., Barreto G.W., Cormack R.M., Macdonald D.W., and Fuller R. Modelling the effects of mink and habitat fragmentation on the water vole. J. Agric. Sci. 37 (2000) 475-490
63. Skidmore A.K. An expert system classifies eucalypt forest types using Thematic Mapper data and a digital terrain model. Photogramm. Eng. Remote Sens. 55 (1989) 1449-1464
64. Smart S.M., Firbank L.G., Bunce R.G.H., and Watkins J.W. Quantifying changes in abundance of food plants for butterfly larvae and farmland birds. J. Appl. Ecol. 37 (2000) 398-414
65. Soulé M., and Sanjayan M. Conservation targets: do they help?. Science 279 (1998) 2060-2061
66. Spence J.R. The new boreal forestry: adjusting timber management to accommodate biodiversity. Trends Ecol. Evol. 16 11 (2001) 591-593
67. Store R., and Kangas J. Integrating spatial multi-criteria evaluation and expert knowledge for GIS-based habitat suitability modelling. Landsc. Urban Plann. 55 (2001) 79-93
68. Store R., and Jokimaki J. A GIS-based multi-scale approach to habitat suitability modeling. Ecol. Modell. 169 (2003) 1-15
69. Tomppo E. Satellite image-based National Forest Inventory of Finland. Int. Arch. Photogramm. Remote Sens. 28 (1991) 419-424
70. Tomppo E. Satellite image aided forest site fertility estimation for forest income taxation purposes. Acta For. Fenn. 229 (1992) 70
71. Tomppo, E., Varjo, J., Korhonen, K., Ahola, A., Ihalainen, A., Heikkinen, J., Hirvelä, H., Mikkelä, H., Mikkola, E., Salminen, S., Tuomainen, T., 1997. Country Report for Finland. In: Study on European Forestry Information and Communication Systems. Reports on forestry inventory and survey systems, vol. 1. European Commission, pp. 145-226.
72. Tomppo, E., Henttonen, H., Korhonen, K.T., Aarnio, A., Ahola, A., Heikkinen, J., Ihalainen, A., Mikkelä, H., Tonteri, T., Tuomainen, T., 1998. Etelä-Pohjanmaan metsäkeskuksen alueen metsävarat ja niiden kehitys 1968-97. Julkaisussa: Etelä-Pohjanmaa. Metsävarat 1968-97, hakkuumahdollisuudet 1997-2026. Metsätieteen aikakauskirja-Folia Forestalia 2B/1998: 293-374.
73. Tomppo E., and Halme M. Using coarse scale forest variables as ancillary information and weighting of variables in k-NN estimation: a genetic algorithm approach. Remote Sens. Environ. 92 (2004) 1-20
74. Tucker K., Rushton S.P., Sanderson R.A., Martin E.B., and Blaiklock J. Modelling bird distributions-a combined GIS and Bayesian rule-based approach. Landsc. Ecol. 12 (1997) 77-93
75. Väisänen R., Järvinen O., and Rauhala P. How are extensive, human-caused habitat alterations expressed on the scale of local bird populations in boreal forests?. Ornis Scand. 17 (1996) 282-292
76. Weclaw P., and Hudson R.J. Simulation of conservation and management of woodland caribou. Ecol. Modell. 177 (2004) 75-94
77. Wintle B.A., McCarthy M.A., Volinsky C.T., and Kavanagh R.P. The use of Bayesian model averaging to better represent uncertainty in ecological models. Conserv. Biol. 17 (2003) 1579-1590