Translated Titles

Multi-Modeling Assessment of Ecological Niche of Polygonum Cuspidatum in Taiwan



Key Words

生態棲位模擬 ; 地理資訊系統 ; 多重模式評估 ; 空間分布 ; 虎杖 ; ecological niche modeling ; geographic information systems ; spatial distribution ; multi-modeling assessment ; Polygonum Cuspidatum



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Chinese Abstract

生態棲位模擬 (Ecological Niche Modeling) 結合地理資訊系統 (Geographic Information Systems) 為近幾年來生態學、生物地理學和保育生物學所廣泛使用之分析方法。動植物的空間分布型態為生物和所在棲地生態環境因子間綜合交互作用的結果,由於物種生理習性與生態系統交互作用的複雜問題,使得生態棲位分佈模擬的結果往往具有高度的不確定性,在使用不同模式分析方法時,常會出現不一致的模擬結果。因此,本研究提出以多重模式綜合評估方法 (Multi-Modeling Assessment),使用多個模式綜合推估出物種之潛在空間分佈。近二十年來,虎杖 (Polygonum Cuspidatum Sieb. & Zucc.) 經人為傳播而成為歐美各國嚴重的外來入侵植物,為能了解其空間分佈特性,本研究分析台灣本島原生虎仗之棲地特性,以 GARP (Genetic Algorithm for Ruleset Prediction)、MAXENT (Maximum Entropy Method) 以及邏輯迴歸 (Logistic Regression) 等三種最為廣泛使用之生態棲位模擬分析方法,結合 20 個生態環境因子,預測全台灣虎杖之潛在棲地分布並歸納其原生棲地之環境特徵。研究使用現有虎杖調查樣點共 75 筆,以及現地野外調查 71 筆,共 146 筆觀測資料進行分析,比較三種模式建立之環境因子變數並評估預測準確度,以多重模式評估方式綜合預測出虎杖潛在棲地空間分布。

English Abstract

Ecological niche modeling combined with a geographic information system can model and display the spatial distributions of species efficiently. Species’ spatial distributions are the result of dynamic interactions between species and environmental factors. However, the complexity and uncertainty due to the interplay of ecosystem and species can cause difficulties when an individual model is used for the assessment purpose. Therefore, the multi-modeling assessment approach is proposed in this study. We combined various modeling techniques and records of known species occurrences with digital layers of environmental variables to predict species’ probability distributions over broad areas. This study aims to explore the native habitat characteristics of Polygonum Cuspidatum Sieb. & Zucc. (Japanese knotweed) in Taiwan, which has seriously invaded North America and Europe. This study applies three widely-used ecological niche models, GARP (Genetic Algorithm for Ruleset Prediction), MAXENT (Maximum Entropy Method) and logistic regression, with 20 environmental variables to predict the potential distribution of Japanese knotweed in Taiwan. Further, the results are compared between the models, and an optimum combination of habitat characteristics of the species is derived from intersecting the models.

Topic Category 人文學 > 地理及區域研究
理學院 > 地理環境資源學研究所
  1. 徐嘉君 (2007) 利用生態棲位模擬 (Ecological Niche Modeling, ENM) 預測物種分佈模式及其於保育生物學上的應用。林業研究專訊,14(1) : 36。
  2. 梁玉琦 (2004) 台灣生態區分區之研究。國立台灣大學森林環境暨資源學研究所碩士論文。
  3. Beerling, D.J., Bailet, J.P. and Conolly, A.P. (1994) Fallopia Japonica (Houtt.) Ronse Decraene. The Journal of Ecology, 82(4): 959–979.
  4. DiTomaso, J.M. (2000) Invasive weeds in rangelands. Species, impacts, and management. Weed Science, 48: 255–265.
  5. Ficetola, G. F., Thuiller, W. and Miaud, C. (2007) Prediction and validation of the potential global distribution of a problematic alien invasive species — the American bullfrog. Diversity and Distributions, 13: 476–485.
  6. Groves, R. H. (2006) Are some weeds sleeping? Some concepts and reasons. Euphytica, 148: 111 – 120.
  7. Hobbs, R. J. and Humphries, S. E. (1995) An integrated approach to the ecology and management of plant invasions. Conservation Biology, 9: 761 – 770.
  8. Hutchinson, G.E. (1957) Concluding remarks. Cold Spring Harbor Symp. Quantitative Biol, 22: 415–427.
  9. Kolar, C.S. and Lodge, D.M. (2001) Progress in invasion biology: predicting invaders. Trends in Ecology and Evolution, 16: 199–204.
  10. Kuo, C.F., Liu, H. Y. and Yang, Y. P. (1996) Polygonum in Huang, T. C. et al. [eds.], Flora of Taiwan 2nd. 2: 295–313. Editorial Committee of the Flora of Taiwan 2nd. Ed., Taipei.
  11. Lockwood, J.L., Cassey, P. and Blackburn, T.M. (2005) The role of propagule pressure in explaining species invasions. Trends in Ecology and Evolution, 20: 223–228.
  12. Mack, R.N. (1996) Traits associated with invasiveness in alien plants: Where do we stand? Biological Conservation, 78: 107 – 121.
  13. McCullagh, P. and Nelder, J.A. (1989) Generalized Linear Models. Chapman & Hall, New York.
  14. Panetta, F.D. and Mitchell, N.D. (1991) Homoclime analysis and the prediction of weediness. Weed Research, 31, 273–284.
  15. Pape, M. and Gaubert, P. (2007) Modelling ecological niches from low numbers of occurrences: assessment of the conservation status of poorly known viverrids (Mammalia, Carnivora) across two continents. Diversity and Distributions, 13: 890–902.
  16. Pereira, J.M.C. and Itami, R.M. (1991) GIS-Based habitat modeling using logistic multiple regression: a study of the Mt. Graham red squirrel. Photogrammetric Engineering and Remote Sensing, 57(11): 1475–1486.
  17. Peterson, A.T. and Cohoon, K.P. (1999) Sensitivity of distributional prediction algorithms to geographic data completeness. Ecological Modelling, 117: 159–164.
  18. Robertson, M.P., Villet, M.H. and Palmer, A.R. (2004) A fuzzy classification technique for predicting species’ distributions: applications using invasive alien plants and indigenous insects. Diversity and Distributions, 10: 461 – 474.
  19. Richardson, D.M. and Thuiller, W. (2007) Home away from home — objective mapping of high-risk source areas for plant introductions. Diversity and Distributions, in press.
  20. Stohlgren, T.J. and Schnase, J.L. (2006) Risk analysis for biological hazards: What we need to know about invasive species. Risk Analysis, 26: 163–173.
  21. Sánchez-Flores E. (2007) GARP modeling of natural and human factors affecting the potential distribution of the invasives Schismus arabicus and Brassica tournefortii in ‘El Pinacate y Gran Desierto de Altar’ Biosphere Reserve. Ecological modeling, 204: 457–474.
  22. Stockwell, D.R.B. and Noble, I.R. (1992) Induction of sets of rules from animal distribution data: a robust and informative method of data analysis. Mathematics and Computers in Simulation, 33: 385–390.
  23. Stockwell, D.R.B. and Peters, D. (1999) The GARP modelling system: problems and solutions to automated spatial prediction. Int. J. Geogr. Inf. Sci. 13(2): 143–158.
  24. Thuiller, W., Richardson, D.M., Pysek, P., Midgley, G.F., Hughes, G.O. and Rouget, M. (2005) Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale. Global Change Biology, 11: 2234–2250.
  25. Thuiller, W., Richardson, D.M., Rouget, M., Proche4, 5 and Wilson, J.R.U. (2006) Interactions between environment, species traits, and human uses describe patterns of plant invasions. Ecology, 87: 1755–1769.
  26. Welk, E., Schubert, K. and Hoffman, M.H. (2002) Present and potential distribution of invasive garlic mustard (Alliaria petiolata) in North America. Diversity and Distributions, 8: 219–233.
  27. Weston, L.A., Barney, J.N., and DiTommaso, A. (2005) A review of the biology and ecology of three invasive perennials in New York State: Japanese knotweed (Polygonum cuspidatum), mugwort (Artemisia vulgaris) and pale swallow-wort (Vincetoxicum rossicum). Plant and Soil, 277:53–69.
  28. Wiley, E.O., McNyset, K.M., Peterson, A.T., Robins, C.R. and Stewart, A.M. (2003) Niche modeling and geographic range predictions in the marine environment using a machine-learning algorithm. Oceanography, 16:120–127.
  29. Wang, J. and Ni, J. (2006) Review of Modelling the Distribution of Plant Species. Journal of Plant Ecology, 30(6): 1040–1053.
  30. Yiming, L., Zhengjun, W. and Duncan, R.P. (2006) Why islands are easier to invade: human influences on bullfrog invasion in the Zhoushan archipelago and neighboring mainland China. Oecologia, 148: 129–136.
  31. Zuo, W.Y., Lao, N., Geng, Y.Y. and Ma, K.P. (2007) Predicting Species’ Potential Distribution – SVM Compared with GARP. Journal of Plant Ecology, 31(4): 711–719.
  32. 呂光洋、鄭勝華、林登秋、徐堉峰 (2007) 生物地理學 ─ 從生態及演化的角度來探討。藝軒圖書出版社。2007。
  33. 李培芬、白梅玲、林瑞興 (2005) 利用遙測與GIS 探討瀕危物種八色鳥之棲地喜好與分布。農委會 94 年度遙測應用計畫成果發表會專刊。
  34. 郭紀凡 (1997) 台灣蓼屬植物之分類研究。國立中山大學生命科學研究所碩士論文。
  35. Breiman, L., Friedman, J.H., Olsen, R.A. and Stone, C.J. (1984) Classification and Regression Trees. Wadsworth International Group, Belmont, CA.
  36. Child, W., and Wade, M. (2000) The Japanese Knotweed Manual. The Management and Control of an Invasive Alien Weed. Packard Publishing Limited, Chichester, UK. 123 pp.
  37. Conolly, A.P. (1977) The distribution and history in the British Isles of some alien species of Polygonum and Reynoutria. Watsonia, 11: 291 – 311.
  38. Colasanti, R.L. (1991) Discussion of the possible use of neural network algorithms in ecological modelling. Binary, 3: 13–15.
  39. Crooks, J. and Soulé, M.E. (1999) Lag times in population explosions of invasive species: causes and implications. Invasive species and biodiversity management (ed. by O.T. Sandlund, S.J. Schei and A. Viken), pp. 103–125. Kluwer Academic Publishers, Dordrecht, the Netherlands.
  40. Cunningham, D.C., G. Woldendorp, M.B. Burgess and Barry, S.C. (2003) Prioritising sleeper weeds for eradication: Selection of species based on potential impacts on agriculture and feasibility of eradication. Bureau of Rural Sciences, Canberra.
  41. Hastie, T.J. and Tibshirani, R.J. (1990) Generalized Additive Models. Chapman & Hall, New York.
  42. Kvamme, K.L. (1985) Determining empirical relationships between the natural environment and pre-historic site locations: a hunter-gatherer example. For Concordance in Archeological Analysis, edited by C. Carr (Kansas: Wesport Publishers), pp. 208–238.
  43. Phillips, S.J., Dud´ık, M., Schapire, R.E., 2004. A maximum entropy approach to species distribution modeling. In: Proceedings of the 21st International Conference on Machine Learning,ACMPress, New York, pp. 655–662.
  44. Sperduto, M. B. and Congalton, R. G. (1996) Predicting rare orchid (small whorled pogonia) habitat using GIS. Photogrammetric Engineering & Remote Sensing 62(11): 1269–1279.
  45. Yim, Y. and Kira, T. (1975) Distribution of Forest Vegetation and Climate in the Korean Peninsula (Ⅰ. Distribution of some Indices of Thermal Climate), Japanese Journal of Ecology, 25(2): 77–88.
  46. Yim, Y. and Kira, T. (1976) Distribution of Forest Vegetation and Climate in the Korean Peninsula (Ⅱ. Distribution of Climatic Humidity/Aridity) , Japanese Journal of Ecology, 26(3): 157–164.
Times Cited
  1. 林雅(2010)。運用空間資訊技術在社區監測─以宜蘭縣無尾港鳥類調查為例。臺灣大學地理環境資源學研究所學位論文。2010。1-116。