Biodiversity & Conservation

, Volume 12, Issue 2, pp 255–278 | Cite as

A nested-intensity design for surveying plant diversity

Article

Abstract

Managers of natural landscapes need cost-efficient, accurate, and precise systems to inventory plant diversity. We investigated a nested-intensity sampling design to assess local and landscape-scale heterogeneity of plant species richness in aspen stands in southern Colorado, USA. The nested-intensity design used three vegetation sampling techniques: the Modified-Whittaker, a 1000-m2 multiple-scale plot (n = 8); a 100-m2 multiple-scale Intensive plot (n = 15); and a 100-m2 single-scale Extensive plot (n = 28). The large Modified-Whittaker plot (1000 m2) recorded greater species richness per plot than the other two sampling techniques (P < 0.001), estimated cover of a greater number of species in 1-m2 subplots (P < 0.018), and captured 32 species missed by the smaller, more numerous 100-m2 plots of the other designs. The Intensive plots extended the environmental gradient sampled, capturing 17 species missed by the other techniques, and improved species–area calculations. The greater number of Extensive plots further expanded the gradient sampled, and captured 18 additional species. The multi-scale Modified-Whittaker and Intensive designs allowed quantification of the slopes of species–area curves in the single-scale Extensive plots. Multiple linear regressions were able to predict the slope of species–area curves (adj R2 = 0.64, P < 0.001) at each Extensive plot, allowing comparison of species richness at each sample location. Comparison of species–accumulation curves generated with each technique suggested that small, single-scale plot techniques might be very misleading because they underestimate species richness by missing locally rare species at every site. A combination of large and small multi-scale and single-scale plots greatly improves our understanding of native and exotic plant diversity patterns.

Inventory Nested-intensity designs Plant species richness Sample plot size 

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References

  1. Baker W.L. 1989. Landscape ecology and nature preserve design in the boundary waters canoe area, Minnesota. Ecology 70: 23–35.Google Scholar
  2. Baker W.L., Munroe J.A. and Hessl A.E. 1997. The effects of elk on aspen in the winter range of Rocky Mountain National Park. Ecography 20: 155–165.Google Scholar
  3. Bonham C.D. 1989. Measurement for Terrestrial Vegetation. John Wiley and Sons Inc., New York.Google Scholar
  4. Bunge J. and Fitzpatrick M. 1993. Estimating the number of species: a review. Journal of the American Statistical Association 88: 364–373.Google Scholar
  5. Burnham K.P. and Anderson D.R. 1998. Model Selection and Inference: A Practical Information – Theoretic Approach. Springer-Verlag, New York.Google Scholar
  6. Chong G.W., Reich R.M., Kalkhan M.A. and Stohlgren T.J. 2001. New approaches for sampling and modeling native and exotic plant species richness. Great Basin Naturalist 61: 328–335.Google Scholar
  7. Colwell R.K. 1997. EstimateS: Statistical Estimation of Species Richness and Shared Species from Samples. Version 5. User's Guide and Application. Published at: http://viceroy.eeb.uconn.edu/estimate.Google Scholar
  8. Connor E.F. and McCoy E.D. 1979. The statistics and biology of the species–area relationship. The American Naturalist 113: 791–833.Google Scholar
  9. Daubenmire R.F. 1959. Canopy coverage method of vegetation analysis. Northwest Science 33: 43–64.Google Scholar
  10. DeByle N.V. 1985. Wildlife. In: DeByle N.V. and Winokur R.P. (eds), Aspen: Ecology and Management in the Western United States. General Technical Report RM-119. USDA Forest Service, Fort Collins, Colorado pp. 135–152.Google Scholar
  11. Flather C.H. 1996. Fitting species–accumulation functions and assessing regional land use impacts on avian diversity. Journal of Biogeography 23: 155–168.Google Scholar
  12. Gaston K.J. 2000. Global patterns in biodiversity. Nature 405: 220–227.Google Scholar
  13. Green D.G. 1989. Simulated effects of fire, dispersal, and spatial pattern on competition within forested mosaics. Vegetatio 82: 139–153.Google Scholar
  14. Harte J., Kinzig A. and Green J. 1999. Self-similarity in the distribution and abundance of species. Science 284: 334–336.Google Scholar
  15. Kalkhan M.A., Reich R.M. and Stohlgren T.J. 1998. Assessing the accuracy of Landsat Thematic Mapper classification using double sampling. International Journal of Remote Sensing 19: 2049–2060.Google Scholar
  16. Kotliar N.B. 1996. Scale dependency and the expression of hierarchical structure in Delphinium patches. Vegetatio 127: 117–128.Google Scholar
  17. Krebill R.G. 1972. Mortality of aspen on the Gros Ventre Elk Winter Range. USDA Forest Service Research Paper INT-129. Intermountain Forest and Range Experiment Station, Ogden, Utah.Google Scholar
  18. Krebs C.J. 1989. Ecological Methodology. Harper & Row, New York.Google Scholar
  19. Leitner W.A. and Rosenzweig M.L. 1997. Nested species–area curves and stochastic sampling: a new theory. Oikos 79: 503–512.Google Scholar
  20. Levin S.A. 1992. The problem of pattern and scale in ecology. Ecology 73: 1943–1967.Google Scholar
  21. Ludwig J.A. and Reynolds J.F. 1988. Statistical Ecology. John Wiley & Sons Inc., New York.Google Scholar
  22. Margules C.R. and Pressey R.L. 2000. Systematic conservation planning. Nature 405: 243–253.Google Scholar
  23. MathSoft Inc. 1999. S-Plus 2000. MathSoft Inc., Seattle, Washington.Google Scholar
  24. Mulder B.S., Noon B.R., Spies T.A., Raphael M.G., Palmer C.J., Olsen A.R. et al., 1999. The strategy and design for the effectiveness monitoring program for the Northwest Forest Plan. General Technical Report PNW-GTR-437. USDA National Forest Service, Portland, Oregon.Google Scholar
  25. Myers N., Mittermeier R.A., Mittermeier C.G., da Fonseca G.A.B. and Kent J. 2000. Biodiversity hotspots for conservation priorities. Nature 403: 853–858.Google Scholar
  26. Nusser S.M. and Goebel J.J. 1997. The National Resources Inventory: a long-term multi-resource monitoring programme. Environmental and Ecological Systematics 4: 181–204.Google Scholar
  27. Parker K.W. 1951. A Method for Measuring Trend in Range Condition in National Forest Ranges. USDA National Forest Service, Washington, DC.Google Scholar
  28. Peterson D.L., Silsbee D.G. and Schmoldt D.L. 1995. A planning approach for developing inventory and monitoring programs in national parks. Natural Resources Report NPS/NRUW/NRR-95/16. National Park Service, Washington, DC.Google Scholar
  29. Reed R.A., Peet R.K., Palmer M.W. and White P.S. 1993. Scale dependence of vegetation–environment correlations: a case study of a North Carolina piedmont woodland. Journal of Vegetation Science 4: 329–340.Google Scholar
  30. Reich R.L. and David R. 1998. Quantitative Spatial Analysis. Colorado State University, Fort Collins, Colorado, www.CNR.colostate.edu/~robin.Google Scholar
  31. Reich and Bravo 1998. Integrating spatial statistics with GIS and remote sensing in designing multiresource inventories The North American Symposium Towards a Unified Framework for Inventory and Monitoring Forest Ecosystem Resources. Guadalajara, Mexico.Google Scholar
  32. Ripple W.J. and Larsen E.J. 2000. Historic aspen recruitment, elk, and wolves in Northern Yellowstone National Park, USA. Biological Conservation 95: 361–370.Google Scholar
  33. Romme W.H., Turner M.G., Wallace L.L. and Walker J.S. 1995. Aspen, elk, and fire in Northern Yellowstone National Park. Ecology 76: 2097–2106.Google Scholar
  34. Rosenzweig M.L. 1995. Species Diversity in Space and Time. Cambridge University Press, Cambridge, UK.Google Scholar
  35. SAS Institute 1998. SAS for Windows. SAS Institute, Cary, North Carolina.Google Scholar
  36. Schreuder H.T., Williams M.S. and Reich R.M. 1999. Estimating the number of tree species in a forest community using survey data. Environmental Monitoring and Assessment 56: 293–303.Google Scholar
  37. Shmida A. 1984. Whittaker's plant diversity sampling method. Israel Journal of Botany 33: 41–46.Google Scholar
  38. Simonson S.E., Opler P.A., Stohlgren T.J. and Chong G.W. 2001. Rapid assessment of butterfly diversity in a montane landscape. Biodiversity and Conservation 10: 1369–1386.Google Scholar
  39. SPSS Inc. 2000. SYSTAT 9. SPSS Inc., Chicago, Illinois.Google Scholar
  40. Stohlgren T.J. 1994. Planning long-term vegetation studies at landscape scales. In: Powell T.M. and Steele J.H. (eds), Ecological Time Series. Chapman & Hall, New York, pp. 209–241.Google Scholar
  41. Stohlgren T.J., Binkley D., Chong G.W., Kalkhan M.A., Schell L.D., Bull K.A. et al. 1999. Exotic plant species invade hot spots of native plant diversity. Ecological Monographs 69: 25–46.Google Scholar
  42. Stohlgren T.J., Bull K.A. and Otsuki Y. 1998a. Comparison of rangeland vegetation sampling techniques in the Central Grasslands. Journal of Range Management 51: 164–172.Google Scholar
  43. Stohlgren T.J., Bull K.A., Otsuki Y., Villa C.A. and Lee M. 1998b. Riparian zones as havens for exotic plant species in the central grasslands. Plant Ecology 138: 113–125.Google Scholar
  44. Stohlgren T.J., Chong G.W., Kalkhan M.A. and Schell L.D. 1997a. Multi-scale sampling of plant diversity: effects of minimum mapping unit size. Ecological Applications 7: 1064–1074.Google Scholar
  45. Stohlgren T.J., Chong G.W., Kalkhan M.A. and Schell L.D. 1997b. Rapid assessment of plant diversity patterns: a methodology for landscapes. Environmental Monitoring and Assessment 48: 25–43.Google Scholar
  46. Stohlgren T.J., Coughenour M.B., Chong G.W., Binkley D., Kalkhan M.A., Schell L.D. et al. 1997c. Landscape analysis of plant diversity. Landscape Ecology 12: 155–170.Google Scholar
  47. Stohlgren T.J., Falkner M.B. and Schell L.D. 1995. A modified-Whittaker nested vegetation sampling method. Vegetatio 4: 1–8.Google Scholar
  48. Stohlgren T.J., Owen A. and Lee M. 2000. Monitoring shifts in plant diversity in response to climate change: a method for landscapes. Biodiversity and Conservation 9: 67–86.Google Scholar
  49. Turner M.B. 1989. Landscape ecology: the effect of pattern on process. Annual Review of Ecological Systematics 20: 171–197.Google Scholar
  50. USDA, NRCS 2001. The PLANTS Database. Version 3.1. National Plant Data Center, Baton Rouge, Louisiana, US, (http://plants.usda.gov).Google Scholar

Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  1. 1.Natural Resource Ecology LaboratoryColorado State UniversityFort CollinsUSA
  2. 2.Midcontinent Ecological Science Center, United States Geological Survey, Natural Resource Ecology LaboratoryColorado State UniversityFort CollinsUSA

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