DOI QR코드

DOI QR Code

Geostatistical analyses and spatial distribution patterns of tundra vegetation in Council, Alaska

  • Park, Jeong Soo ;
  • Lee, Eun Ju
  • Received : 2013.10.21
  • Accepted : 2014.03.10
  • Published : 2014.05.27

Abstract

The arctic tundra is an important ecosystem in terms of the organic carbon cycle and climate change, and therefore, detailed analysis of vegetation distribution patterns is required to determine their association. We used grid-sampling method and applied geostatistics to analyze spatial variability and patterns of vegetation within a two-dimensional space, and calculated the Moran's I statistics and semivariance to assess the spatial autocorrelation of vegetation. Spatially autocorrelated vegetation consisted of moss, Eriophorum vaginatum, Betula nana, and Rubus chamaemorus. Interpolation maps and cross-correlograms revealed spatial specificity of Carex aquatilis and a strong negative spatial correlation between E. vaginatum and C. aquatilis. These results suggest differences between the species in water requirements for survival in the arctic tundra. Geostatistical methods could offer valuable information for identifying the vegetation spatial distribution.

Keywords

alaska;arctic tundra;geostatistics;spatial patterns;vegetation

References

  1. Zhao X, Wang Q, Kakubari Y. 2009. Stand-scale spatial patterns of soil microbial biomass in natural cold-temperate beech forests along an elevation gradient. Soil Biol Biochem 41: 1466-1474. https://doi.org/10.1016/j.soilbio.2009.03.028
  2. Oksanen J, Kindt R, Legendre P, O'Hara B, Stevens MHH, Oksanen MJ, Suggests M. 2007. The vegan package. Community ecology package Version: 1.8-5. http://cran.rproject.org/.
  3. KOPRI. 2013. Establishment of circum arctic permafrost environment change monitoring network and future prediction techniques (CAPEC Project). Minstry of Science ICT & Future Planning, Seoul.
  4. Lindsey AA. 1956. Sampling methods and community attributes in forest ecology. For Sci 2: 287-296.
  5. Nordbo E, Christensen S, Kristensen K, Walter M. 1994. Patch spraying of weed in cereal crops. Aspects Appl Biol 40: 325-334.
  6. Peterson KM, Billings WD. 1980. Tundra vegetational patterns and succession in relation to microtopography near Atkasook, Alaska. Arct Alp Res 12: 473-482. https://doi.org/10.2307/1550495
  7. Post WM, Emanuel WR, Zinke PJ, Stangenberger AG. 1982. Soil Carbon Pools and World Life Zones. Nature 298:156-159. https://doi.org/10.1038/298156a0
  8. Rew LJ, Cousens RD. 2001. Spatial distribution of weeds in arable crops: are current sampling and analytical methods appropriate? Weed Res 41: 1-18. https://doi.org/10.1046/j.1365-3180.2001.00215.x
  9. Ribeiro PJ, Diggle PJ. 2001. geoR: A package for geostatistical analysis. R News 1: 14-18.
  10. Spadavecchia L, Williams M, Bell R, Stoy PC, Huntley B, Van Wijk MT. 2008. Topographic controls on the leaf area index and plant functional type of a tundra ecosystem. J Ecol 96: 1238-1251. https://doi.org/10.1111/j.1365-2745.2008.01424.x
  11. Strandberg M, Johansson M. 1999. Uptake of nutrients in Calluna vulgaris seed plants grown with and without mycorrhiza. For Ecol Manage 114: 129-135. https://doi.org/10.1016/S0378-1127(98)00387-9
  12. Tiner RW. 1991. The concept of a hydrophyte for wetland identification. Bioscience 41: 236-247. https://doi.org/10.2307/1311413
  13. Viereck LA, Dyrness CT, Batten AR, Wenzlick KJ. 1992. The Alaska vegetation classification. USDA, Washington, DC.
  14. Heisel T, Andreasen C, Ersboll AK. 1996. Annual weed distributions can be mapped with kriging. Weed Res 36: 325-337. https://doi.org/10.1111/j.1365-3180.1996.tb01663.x
  15. Daubenmire R. 1959. A canopy coverage method of vegetational analysis. Northwest Sci 33: 43-64.
  16. Faith DP, Minchin PR, Belbin L. 1987. Compositional dissimilarity as a robust measure of ecological distance. Vegetatio 69: 57-68. https://doi.org/10.1007/BF00038687
  17. Goovaerts P. 1999. Geostatistics in soil science: state-of-theart and perspectives. Geoderma 89: 1-45. https://doi.org/10.1016/S0016-7061(98)00078-0
  18. Heisel T, Ersboll AK, Andreasen C. 1999. Weed mapping with co-kriging using soil properties. Precision Agric 1: 39-52. https://doi.org/10.1023/A:1009921718225
  19. Hill MO, Gauch HG Jr. 1980. Detrended correspondence analysis: an improved ordination technique. Vegetatio 42: 47-58. https://doi.org/10.1007/BF00048870
  20. Isaaks EH, Srivastava RM. 1989. An Introduction to Applied Geostatistics. Oxford University Press, New York, NY.
  21. Jacquemart A-L. 1996. Vaccinium uliginosum L. J Ecol 84: 771-785. https://doi.org/10.2307/2261339
  22. Johnson PL, Vogel TC. 1966. Vegetation of the Yukon Flats region, Alaska (No. CRREL-RR-209). Cold regions research and engineering lab, Hanover, NH.
  23. Jongman RHG, Ter Braak CJF, van Tongeren OFR. 1995. Data analysis in community and landscape ecology. Cambridge University Press, Cambrige.
  24. Jurado-Exposito M, Lopez-Granados F, Gonzalez-Andujar JL, Garcia-Torres L. 2004. Spatial and temporal analysis of Convolvulus arvensis L. populations over four growing seasons. Eur J Agron 21: 287-296. https://doi.org/10.1016/j.eja.2003.10.001
  25. Karlsson PS. 1987a. Micro‐site performance of evergreen and deciduous dwarf shrubs in a subarctic heath in relation to nitrogen status. Ecography 10: 114-119. https://doi.org/10.1111/j.1600-0587.1987.tb00747.x
  26. Karlsson PS. 1987b. Niche differentiation with respect to light utilization among coexisting dwarf shrubs in a subarctic woodland. Pol Biol 8: 35-39. https://doi.org/10.1007/BF00297162
  27. Bjørnstad ON, Falck W. 2001. Nonparametric spatial covariance functions: estimation and testing. Environ Ecol Stat 8: 53-70. https://doi.org/10.1023/A:1009601932481
  28. Allen TR, Walsh SJ, Cairns DM, Messina JP, Butler DR, Malanson GP. 2004. Geostatistics and spatial analysis: characterizing form and pattern at the alpine treeline. In: Geographic Information Science and Mountain Geomorphology (Bishop M, Shroder JF, eds). Springer, New York, pp 189-218.
  29. Bekryaev RV, Polyakov IV, Alexeev VA. 2010. Role of polar amplification in long-term surface air temperature variations and modern Arctic warming. J Clim 23: 3888-3906. https://doi.org/10.1175/2010JCLI3297.1
  30. Bivand R. 2013. spdep: spatial dependence: weighting schemes, statistics and models. R package version 0.5-56. http://cran.r-project.org/web/packages/spdep/index.html.
  31. Bjørnstad ON, Stenseth NC, Saitoh T. 1999. Synchrony and scaling in dynamics of voles and mice in northern Japan. Ecology 80: 622-637. https://doi.org/10.1890/0012-9658(1999)080[0622:SASIDO]2.0.CO;2
  32. Bregt AK, Gesink HJ, Alkasuma. 1992. Mapping the conditional probability of soil variables. Geoderma 53: 15-29. https://doi.org/10.1016/0016-7061(92)90018-3
  33. Britton ME. 1967. Vegetation of the arctic tundra. In: Arctic Biology (Hansen HP, ed). Oregon State University Press, Corvallis, pp 67-130.
  34. Burgess TM, Webster R. 1980. Optimal interpolation and isarithmic mapping of soil properties. II. Block kriging. J Soil Sci 31: 333-341. https://doi.org/10.1111/j.1365-2389.1980.tb02085.x
  35. Cambardella CA, Moorman TB, Novak JM, Parkin TB, Karlen DL, Turco RF, Konopka AE. 1994. Field-scale variability of soil properties in central Iowa soils. Soil Sci Soc Am J 58: 1501-1511. https://doi.org/10.2136/sssaj1994.03615995005800050033x
  36. Chapin III FS, Shaver GR. 1985. Individualistic growth response of tundra plant species to environmental manipulations in the field. Ecology 66: 564-576. https://doi.org/10.2307/1940405
  37. Comiso JC, Parkinson CL, Gersten R, Stock L. 2008. Accelerated decline in the Arctic sea ice cover. Geophys Res Lett 35: L01703.
  38. Cressie N. 1993. Statistics for spatial data. Wiley, New York.

Cited by

  1. Spatial variation, mapping, and classification of moss families in semi-arid landscapes in NW Turkey vol.187, pp.3, 2015, https://doi.org/10.1007/s10661-014-4240-5
  2. Mapping forest vegetation patterns in an Atlantic–Mediterranean transitional area by integration of ordination and geostatistical techniques pp.1752-993X, 2016, https://doi.org/10.1093/jpe/rtw112
  3. Interactive effect of soil moisture and temperature regimes on the dynamics of soil organic carbon decomposition in a subarctic tundra soil pp.1598-7477, 2017, https://doi.org/10.1007/s12303-017-0052-2
  4. Spatial properties of sessile benthic organisms and the design of repeat visual survey transects pp.10527613, 2018, https://doi.org/10.1002/aqc.2960

Acknowledgement

Supported by : National Research Foundation of Korea