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The Gradient Paradigm: A Conceptual and Analytical Framework for Landscape Ecology

Cushman, Samuel A., Gutzweiler, Kevin, Evans, Jeffrey S., McGarigal, Kevin·2010·Spatial Complexity, Informatics, and Wildlife Conservation
DOI 10.1007/978-4-431-87771-4_5
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Crossref · 10.1007/978-4-431-87771-4_5

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  • Spatial scales are variable and landscapes should rather be seen as fuzzy geometries where heterogeneous patterns generate processes.

    “Consequently, spatial scales are variable and landscapes should rather be seen as fuzzy geometries where heterogeneous patterns generate processes (Cushman et al. 2010; Kent 2007; McGarigal and Cushman 2009).”

    From From landscape affordances to landscape connectivity: contextualizing an archaeology of human ecology (2020) · cites this paper as Cushman et al. 2010

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Research works printed but not linked: 69

  1. Allen TFH, Starr TB (1982) Hierarchy: perspectives for ecological complexity. University of Chicago Press, Chicago, IL
  2. Baker WL, Cai Y (1992) The r.le programs for multiscale analysis of landscape structure using the GRASS geographical information system. Landsc Ecol 7:291–302 · DOI
  3. Barnsely MF, Devaney RL, Mandelbrot BB, Petigen H, Saupe D, Voss RF (1988) The science of fractal images. Springer, New York · DOI
  4. Bradshaw GA, Spies TA (1992) Characterizing canopy gap structure in forests using wavelet analysis. J Ecol 80:205–215 · DOI
  5. Cho E, Chon T (2006) Application of wavelet analysis to ecological data. Ecol Informat 1:229–233 · DOI
  6. Chui CK (1992) An introduction to wavelets. Academic, San Diego, CA
  7. Clements FE (1916) The nature and structure of the climax. J Ecol 24:252–284 · DOI
  8. Cohen A (1995) Wavelets and multiscale signal processing. Chapman & Hall, London · DOI
  9. Corander J, Waldmann P, Sillanpää MJ (2003) Bayesian analysis of genetic differentiation between populations. Genetics 163:367–374 · DOI
  10. Cushman SA, McGarigal K (2004) Hierarchical analysis of forest bird species-environment relationships in the Oregon Coast Range. Ecological Applications. 14(4):1090–1105. · DOI
  11. Dutilleul P (1993) Modifying the t-test for assessing the correlation between two spatial processes. Biometrics 49:305–314 · DOI
  12. Evans JS, Hudak AT (2007) A multiscale curvature algorithm for classifying discrete return lidar in forested environments. IEEE Transactions on Geoscience and Remote Sensing, 45:1029–1038 · DOI
  13. Evans JS, Cushman SA (2009) Gradient modeling of conifer species using random forests. Landscape Ecology 24:673–683. · DOI
  14. Ewe HT, Au WC, Shin RT, Kong JA (1993) Classification of SAR images using a fractal approach. Proceedings of Progress in Electromagnetic Research Symposium (PIERS) Los Angeles
  15. Forman RTT (1995) Land mosaics: the ecology of landscapes and regions. Cambridge University Press, Cambridge · DOI · Paper page
  16. Forman RTT, Godron M (1986) Landscape ecology. Wiley, New York
  17. François O, Ancelet S, Guillot G (2006) Bayesian clustering using hidden Markov random fields in spatial population genetics. Genetics 174:805–816 · DOI
  18. Funk WC, Blouin MS, Corn PS, Maxell BA, Pilliod DS, Amish S, Allendorf FW (2005) Population structure of Columbia spotted frogs (Rana luteiventris) is strongly affected by the landscape. Mol Ecol14:483–496 · DOI
  19. Gleason HA (1926) The individualistic concept of the plant association. Bull Torr Bot Club 53:7–26 · DOI
  20. Guthrie KA, Sheppard L (2001) Overcoming biases and misconceptions in ecological studies. J Roy Stat Soc Stat Soc 164:141–154 · DOI
  21. He HS, DeZonia BE, Mladenoff DJ (2000) An aggregation index (AI) to quantify spatial patterns of landscapes. Landsc Ecol 15:591–601 · DOI
  22. Holderegger R, Wagner HH (2006) A brief guide to landscape genetics. Landsc Ecol 21:793–796 · DOI
  23. Jelinski DE, Wu J (1996) The modifiable areal unit problem and implications for landscape ecology. Landsc Ecol 11:129–140 · DOI
  24. Johnson DH (1980) The comparison of usage and availability measurements for evaluating resource preference. Ecology 61:65–71. · DOI
  25. Kotliar NB, Wiens JA (1990) Multiple scales of patchiness and patch structure: a hierarchical framework for the study of heterogeneity. Oikos 59:253–260 · DOI
  26. Levin SA (1992) The problem of pattern and scale in ecology. Ecology 73:1943–1967 · DOI
  27. Mandelbrot BB (1982) The fractal geometry of nature. W.H. Freeman, New York
  28. Manel S, Schwartz MK, Luikart G, Taberlet P (2003) Landscape genetics: the combination of landscape ecology and population genetics. Trends in Ecol Evol 18:189–197 · DOI · Paper page
  29. Manni F, Guerard E, Heyer E (2004) Geographic patterns of (genetic, morphologic, linguistic) variation: how barriers can be detected by using Monmonier's algorithm. Hum Biol 76:173–190 · DOI
  30. Manning AD, Lindenmayer B, Nix HA (2004) Continua and umwelt: novel perspectives on viewing landscapes. Oikos 104:621–628 · DOI
  31. McGarigal K, Cushman SA (2005) The gradient concept of landscape structure. In: Wiens J, Moss M (eds) Issues and Perspectives in Landscape Ecology. Cambridge University Press, Cambridge
  32. McGarigal K, Marks BJ (1995) FRAGSTATS: spatial analysis program for quantifying landscape structure. USDA For Serv Gen Tech Rep PNW-GTR-351 · DOI
  33. McGarigal K, Cushman SA, Stafford S (2000) Multivariate statistics for wildlife and ecology research. Springer, New York · DOI · Paper page
  34. McIntyre S, Barrett GW (1992) Habitat variegation, an alternative to fragmentation. Conservat Biol 4:197–202
  35. McGarigal K, Cushman SA (2005) The gradient concept of landscape structure. In: Wiens J, Moss M (eds) Issues and Perspectives in Landscape Ecology. Cambridge University Press, Cambridge
  36. Michels E, Cottenie K, Neys L, DeGalas K, Coppin P, DeMeester L (2001) Geographical and genetic distances among zooplankton populations in a set of interconnected ponds: a plea for using GIS modeling of the effective geographical distance. Mol Ecol 10:1929–1938 · DOI
  37. Moore ID, Gryson RB, Ladson AR (1991) Digital terrain modeling: a review of hydrological, geomorphological, and biological applications. Hydrolog Process 5:3–30 · DOI
  38. Murphy MA, Evans JS, Cushman SA, Storfer A (2008) Representing genetic variation as continuous surfaces: An approach for identifying spatial dependency in landscape genetic studies. Ecography 31:685–697 · DOI
  39. Ohmann JL, Gregory MJ (2002) Predictive mapping of forest composition and structure with direct gradient analysis and nearest-neighbor imputation in coastal Oregon, USA. Canadian Journal of Forest Resources 32:725–741. · DOI
  40. O'Neill RV, DeAngelis DL, Waide JB, Allen TFH (1986) A hierarchical concept of ecosystems. Princeton University Press, Princeton, NJ
  41. O'Neill RV, Johnson AR, King AW (1989) A hierarchical framework for the analysis of scale. Landsc Ecol 3:193–205 · DOI
  42. Pentland AP (1984) Fractal-based description of natural scenes. IEEE Trans Patt Anal Mach Intel 6:661–674 · DOI
  43. Peterson DL, Parker VT (1998) Ecological scale: theory and applications. Columbia University Press, New York
  44. Plotnick RE, Gardner RH, O'Neill RV (1993) Lacunarity indices as measures of landscape texture. Landsc Ecol 8:201–211 · DOI
  45. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959 · DOI
  46. Proctor MF, McLellan BN, Strobeck C, Barclay RMR (2005) Genetic analysis reveals demographic fragmentation of grizzly bears yielding vulnerability by small populations. Proceedings of the Royal Society B: Biological Sciences 272:2409–2416 · DOI
  47. Rehfeldt GE, Crookston NL, Warwell MV, Evans JS (2006) Empirical analyses of plant-climate relationships for the western United States. Int J Plant Sci 167:1123–1150 · DOI
  48. Robinson WS (1950) Ecological correlations and the behavior of individuals. Am Socio Rev 15:351–357 · DOI
  49. Spear SF, Peterson CR, Matacq M, Storfer A (2005) Landscape genetics of the blotched tiger salamander (Ambystoma tigrinum melanostictum). Mol Ecol 14:2553–2564 · DOI
  50. Schneider DC (1994) Quantitative ecology: spatial and temporal scaling. Academic, San Diego, CA.
  51. Stout KJ, Sullivan PJ, Dong WP, Mainsah E, Lou N, Mathia T, Zahouani H (1994) The development of methods for the characterization of roughness on three dimensions. Publication no EUR 15178 EN of the Commission of the European Communities, Luxembourg
  52. Storfer A, Murphy MA, Evans JS, Goldberg CS, Robinson S, Spear SF, Dezzani R, Delmelle E, Vierling L, Waits LP (2006) Putting the ‘landscape’ in landscape genetics. Heredity 2006:1–15
  53. ter Braak CJF (1988) Partial canonical correspondence analysis. In: Bock HH (ed.) Classification and related methods of data analysis. North-Holland, Amsterdam
  54. Turner MG (1989) Landscape ecology: the effect of pattern on process. Annl Rev Ecol System 20:171–197 · DOI
  55. Turner MG, O'Neill RV, Gardner RH, Milne BT (1989) Effects of changing spatial scale on the analysis of landscape pattern. Landsc Ecol 3:153–162 · DOI
  56. Urban DL, O'Neill RV, Shugart HH (1991) Landscape ecology. BioScience 37:119–127 · DOI
  57. Urban DL, Goslee S, Pierce K, Lookingbill T (2002) Extending community ecology to landscapes. Ecoscience 9:200–212 · DOI
  58. Villarrubia JS (1997) Algorithms for scanned probe microscope, image simulation, surface reconstruction and tip estimation. J Nat Inst Stand Tech 102:435–454
  59. Webster R, Oliver M (2001) Geostatistics for environmental scientists. Wiley, Chichester
  60. Whittaker RH (1967) Gradient analysis of vegetation. Biol Rev 42:207–264 · DOI
  61. Wiens JA (1989) Spatial scaling in ecology. Funct Ecol 3:385–397 · DOI · Paper page
  62. Wiens JA (2001) Understanding the problem of scale in experimental ecology. In: Gardner RH, Kemp WM, Kennedy VS, Petersen JE (eds) Scaling relations in experimental ecology. Columbia University Press, New York
  63. Wiens JA, Stenseth NC, Van Horne B, Ims RA (1993) Ecological mechanisms and landscape ecology. Oikos 66:369–380 · DOI
  64. Wood CH, Skole D (1998) Linking satellite, census, and survey data to study deforestation in the Brazilian Amazon. In: Liverman D, Moran EF, Rindfuss RR, Stern PC (eds) People and pixels: linking remote sensing and social science. National Academy Press, Washington, DC
  65. Wright S (1921) Correlation and causation. J Agric Res 20:557–585
  66. Wright S (1943) Isolation by distance. Genetics 28:114–138 · DOI
  67. Wright S (1960) Path coefficients and path regressions: alternative or complementary concepts? Biometrics 16:189–202 · DOI
  68. Wu J (2007) Scale and scaling: a cross-disciplinary perspective. In: Wu J, Hobbs RJ (eds) Key topics in landscape ecology. Cambridge University Press, Cambridge · DOI
  69. Wu J, Hobbs R (2002) Key issues and research priorities in landscape ecology: an idiosyncratic synthesis. Landsc Ecol 17:355–365 · DOI

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Metadata

Authors
Cushman, S. A., Gutzweiler, K., Evans, J. S., & McGarigal, K.
Venue
Spatial Complexity, Informatics, and Wildlife Conservation
Publisher
Springer Japan
Published
2010
Pages
83-108
DOI
10.1007/978-4-431-87771-4_5
Cited by
104
References
2
Language
en

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