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Application of principal component analysis (PCA) in taxonomy research to derive plant functional types for use in dynamics models

Published: 08 January 2015 Publication History
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    Forest management is essential for maintaining environmental stability and ecological biodiversity. The high species diversity of tropical rainforest forests obstructs the development of forest dynamic models. A lot of tree species exist in the forest for which each type of species will have insufficient data for reliable parameter estimation. The best way to avoid bias prediction is to group the trees based on their characteristics similarity. In a tropical rain forest in Koh Kong province, Cambodia, four species groups have been classified using statistical analyses of principal component analysis (PCA) and cluster analysis. Some indices related to diameter structure, growth, mortality and recruitment of species were formed from measurement data rather than the parameter estimates of some predetermined growth regression functions.

    References

    [1]
    Vanclay J. K. 1994. Modelling forest growth and yield: application to Mixed Tropical Forest. CAB International, Wallingford. 312 pp.
    [2]
    Weithoff Guntram, 2003. The concepts of 'plant functional types' and 'functional diversity' in lake phytoplankton -- a new understanding of phytoplankton ecology? Freshwater Biology, 48, 1669--1675.
    [3]
    Kohler, P., T. Ditzer and A. Huth, 2000. Concepts for the aggregation of tropical tree species into functional types and the application to Sabah's lowland rain forests. Journal of Tropical Ecology 16(4): 591--602.
    [4]
    Gourlet-Fleury S., Blanc L., Picard N., Sist P., Dick J., Nasi R., Swaine M. D. and Forni E., 2005. Grouping species for predicting mixed tropical forest dynamics: looking for a strategy. Ann. For. Sci. 62 (8), 785--796.
    [5]
    Phillips, P. D., I. Yasman, T. E. Brash and P. R. van Gardingen, 2002. Grouping tree species for analysis of forest data in Kalimantan (Indonesian Borneo). Forest Ecology and Management 157: 205--216.
    [6]
    Vanclay, J. K., 1991. Aggregating tree species to develop diameter increment equations for tropical rainforests. Forest Ecology and Management 42: 143--168.
    [7]
    Tomas F. Domingues T. F, Martinelli L. A. and Ehleringer J. R, 2006. Ecophysiological traits of plant functional groups in forest and pasture ecosystems from eastern Amazonia, Brazil. Plant Ecol., 1--12
    [8]
    Ismail R., 2004. Forest concession management and control pilot project Cambodia. Forest system research and modeling handbook. (Not published)
    [9]
    Picard, N. and A. Franc, 2003. Are ecological groups of species optimal for forest dynamics modeling? Ecological Modelling 163: 175--186.
    [10]
    Zhao D., Borders B. and Wilson M., 2004. Individual-tree diameter growth and mortality models for bottomland mixed species hardwood stands in the lower Mississippi alluvial valley. Forest Ecology Management 199: 307--322
    [11]
    Kohler P., Huth A., 1998. The effects of tree species grouping in tropical rainforest modelling: simulations with the individual-based model Formind. Ecol. Model. 109 (3), 301--321.
    [12]
    Forestry Administration, 2011, Cambodia Forest Cover 2010, p 1--14
    [13]
    Condit R., Hubbell S. P. and Foster R. B., 1995. Mortality rates of 205 neotropical tree and shrub species and the impact of a severe drought. Ecological Monographs, 65(4), pp. 419--439.
    [14]
    Meldahl, R. S., Eriksson, M., Thomas, C. E., 1985. A method for grouping species-forest type combinations for the development of growth models for mixed species stands. In: Shoulders, E. (Ed.). Proc. Of the 3rd Biennial Southern Silvicultural Research Conference, 7--8 Nov 1984, Atlanta, GA. USDA Forest Service, Gen. Tech. Report. WO-54, pp. 422--428.
    [15]
    Kaiser H. F., 1960. The Application of electronic computers to factor analysis. Educ. Psychol. Meas., 20: 141--151

    Cited By

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    • (2020)Tree-mapping Technique as a Computer System for Sustainable Forest Management2020 14th International Conference on Ubiquitous Information Management and Communication (IMCOM)10.1109/IMCOM48794.2020.9001695(1-6)Online publication date: Jan-2020

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    1. Application of principal component analysis (PCA) in taxonomy research to derive plant functional types for use in dynamics models

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      cover image ACM Conferences
      IMCOM '15: Proceedings of the 9th International Conference on Ubiquitous Information Management and Communication
      January 2015
      674 pages
      ISBN:9781450333771
      DOI:10.1145/2701126
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      Published: 08 January 2015

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      Author Tags

      1. classification
      2. cluster analysis (CA)
      3. diversity
      4. principal component analysis (PCA)

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      View all
      • (2022)Riparian health conditions of headwater streams in Southwestern NigeriaInternational Journal of River Basin Management10.1080/15715124.2022.204771021:3(539-550)Online publication date: 20-Mar-2022
      • (2020)Tree-mapping Technique as a Computer System for Sustainable Forest Management2020 14th International Conference on Ubiquitous Information Management and Communication (IMCOM)10.1109/IMCOM48794.2020.9001695(1-6)Online publication date: Jan-2020

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