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研究生:熊大維
研究生(外文):Ta-Wei Hsiung
論文名稱:宜蘭地區陸貝的空間分布模式
論文名稱(外文):The Spatial Distribution Models of Land Snails in I_Lan
指導教授:丁宗蘇丁宗蘇引用關係巫文隆
指導教授(外文):Tzung-Su DingWen-Lung Wu
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:森林環境暨資源學研究所
學門:農業科學學門
學類:林業學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:106
中文關鍵詞:陸貝邏輯迴歸生態棲位因子分析棲地預測宜蘭地區地理資訊系統空間分析棲地選擇台灣貝類相
外文關鍵詞:land snailslogistic regressionEcological-Niche Factor Analysishabitat predictionI-LanGISspatial analysishabitat selectionTaiwanMalacofauna
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研究生物空間分布的型態,建立生物的分布資料庫與分布模式,在物種多樣性的熱點、棲地保育、物種的經營管理等延伸課題中,將可以提供極大的幫助。過去台灣在陸棲貝類方面,曾有針對南亞蝸牛科在台灣分布的研究,但並未進一步進行分布模式的建立與潛在棲地的預測。因此本研究針對宜蘭地區的陸棲貝類進行: (一)全區的陸棲貝類空間分布調查;(二)將整理調查所得之出現紀錄與現有之環境因子資料庫整合;(三)再將生態模型與地理資訊系統整合運用,建立宜蘭地區陸棲貝類的空間分布模式,並預測宜蘭地區之陸棲貝類各物種之出現機率,找出各物種的潛在棲地。本研究在2004-2008四年的調查期間,一共調查了226個調查點,記錄到了3,252個陸貝個體,其中有1,515個活體、1,737個死殼,分屬於24個科,共89種的陸貝物種。再將陸貝出現紀錄與環境因子結合,針對出現記錄最多的前11種陸貝套用邏輯迴歸 (Logistic regression)與生態棲位因子分析 (Ecological-Niche Factors Analysis, ENFA)兩種生態模式,預測宜蘭地區這11種陸貝的出現機率。結果顯示:(一)11種陸貝中,多數物種之分布熱點都位在蘭陽平原與周邊丘陵地交界之地帶。(二)外來種及廣布種則主要分布在平原地區,縣境內之山地區域各物種之出現機率皆低。(三)微小型的陸貝物種則偏向於出現在中海拔之地區,而不是低海拔之丘陵與平原交界地帶。兩種模式之預測結果、選擇之重要環境因子與模式準確率都存有差異,邏輯迴歸之整體預測準確率雖然良好,但是敏感性卻稍偏低;而生態棲位因子分析之準確率普遍較低。出現紀錄越多的物種,兩種模式預測的結果與熱點越接近,而且準確率也越高。顯示模式之預測結果與預測準確率可能與出現紀錄之數量有關。造成兩種模式之預測不同的可能原因有(一)調查點分布不均;(二)物種出現紀錄不足;(三)生態習性不滿足模式假設前提;及(四)使用的環境因子有修正的空間。
Studying the spatial distribution of organisms is one essential topic for ecological research. By using data of field investigations, spatial distribution database of species and prediction models that depict environmental relationships of species distribution can be constructed and will provide tremendous helps for relevant issues such as identifying biodiversity hotspot, habitat conservation, and species management. The spatial distribution of Camaenidae in Taiwan has been reported, however no study has constructed spatial distribution models and predicted potential habitats of land snails in Taiwan. This study was aimed to (1) investigate the spatial distribution of land snails in I-Lan County ; (2) link the species presence records with environmental factors by Geographic Information System; and (3) construct spatial distribution models that predict occurrence probabilities and potential habitats of species. During the four-year field investigations, 226 sites were sampled, and 3,252 individuals (1,515 living snails and 1,737 emptied shells) were recorded, including 24 families and 89 species. Logistic regression and Ecological-Niche Factor Analysis (ENFA) were employed to link the records of land snails with environmental factors and predict the occurrence probability of land snail species in I-Lan County. Results showed that distribution hotspots of most species were located in the borders of I-Lan Plain with surrounding foothills. Non-native species and common species were mainly distributed in the plains. The occurrence probabilities were low in mountain areas for most species. Nevertheless, many tiny land snail species were tended to distribute in mid-elevation areas in I-Lan County, instead of lower-elevation foothills and plains. Differences in predicted distribution, model predictor variables, and model accuracy were found between logistic regression and ENFA. Although the overall accuracy of logistic regression was satisfying, its sensitivity was low, and the accuracy of ENFA was generally low. For species with more presence records, logistic regression and ENFA provided better match in predicted distribution and hotspots and had higher model accuracy, indicating the predicted results and model accuracy might be affected by the number of presence records. The discrepancy in the predictions of logistic regression and ENFA might result from (1) uneven distribution of sampling sites, (2) insufficient presence records of species, (3) not match the model presumptions and prerequisites, and (4) inadequate environmental factors.
謝誌
中文摘要…………………………………………………………………i
英文摘要………………………………………………………………. iii
前言………………………………………………………………………1
研究地區…………………………………………………………………6
研究方法…………………………………………………………………8
陸貝分布的現地調查……………………………………………………………..… 8
環境因子資料的取得與處理……………………………………………………….10
物種資料與環境資料之整合……………………………………………………….15
分布模式的建立與預測…………………………………………………………….15
模式之驗證………………………………………………………………………….18
結果……………………………………………………………………. 22
陸貝的分布狀況…………………………………………………………………….22
分布模式—Logistic regression與ENFA之模式預測…………………………….43
模式驗證……………………………………………………………………….........55
討論……………………………………………………………………..61
陸貝分布狀況………………………………………………………………….........61
進行模式預測之陸貝物種特性………………………………………………........62
模式預測之探討與比較………………………………………………………........63
結論……………………………………………………………………..72
參考文獻………………………………………………………………..73
附錄一…………………………………………………………………100
巫文隆、簡士傑 (2006) 宜蘭貝類研究圖誌,IV+267。行政院農委會林務局。台北,台灣。
巫文隆、簡士傑 (2007) 大台北地區貝類研究圖誌,IV+215。行政院農委會林務局。台北,台灣。
李培芬、廖倩瑜、李玉琪、潘彥宏、傅維馨、陳宣汶 (1997) 臺灣地區生態與環境因子地理資訊資料庫。行政院農業委員會。台北,台灣。
李彥錚、陳文德 (2003) 自然觀察圖鑑3-蝸牛,287頁。親親文化出版。台北,台灣。
李彥錚 (2008) 大山蝸牛屬及台灣山蝸牛屬之種化事件與山蝸牛科之系統發育學研究。博士論文。國立台灣師範大學。台北,台灣。161pp.
宜蘭縣政府 (1992) 蘭陽地理鄉土教材,VIII+118。宜蘭縣政府。宜蘭,台灣。
邱祈榮 (1997) 臺灣網格化高程評估之研究。中華林學季刊 30(1): 85-91.
吳書平 (2007) 臺灣地區樹棲性南亞蝸牛科白高腰蝸牛群系統分類與親緣關係研究。博士論文。國立台灣大學。台北,台灣。141pp.
孫志鴻、張長義、張春蘭 (1988) 台灣地區主題圖繪製及查詢資訊系統建立之研究。國立台灣大學。台北,台灣。
徐國士 (1984) 太魯閣國家公園植物生態資源調查報告。內政部營建署。台北,台灣。
楊國昌 (1993) 貝友趣聞「溜蝸牛」。貝友 19:19
廖倩瑜 (1997) 臺灣產畫眉亞科鳥種之空間分布與預測模式。碩士論文。國立台灣大學。台北,台灣。136pp.
潘彥宏 (1997) 台灣無尾目兩生類之空間分布模式。碩士論文。國立台灣大學。台北,台灣。137pp.

歐�琣� (2008) 台灣陸域蛇類之分布、預測與熱點分析。碩士論文。國立台灣大學。台北,台灣。125pp.
盧冠安 (2004) 台灣山麻雀的分布模式及棲地選擇。碩士論文。國立台灣大學。台北,台灣。68pp.
盧冠安 (2008) 淺談生物分布預測模式。自然保育季刊 61:3-6
謝伯娟 (1998) 應用外表形態與粒線體探討台灣產煙管蝸牛科陸蝸之親緣關係。 碩士論文。國立台灣大學。台北,台灣。117pp.
謝伯娟 (2003) 臺灣蝸牛圖鑑。行政院農業委員會。台北,台灣。239pp.
Berg, Å., Gärdenfors, U., von Proschwitz, T. (2004) Logistic regression models for predicting occurrence of terrestrial molluscs in southern Sweden – importance of environmental data quality and model complexity. Ecography, 27:83-93.
Bonham, K. J., Mesibov, R.,and Bashford, R. (2002) Diversity and abundance of some ground-dwelling invertebrates in plantation vs. native forest in Tasmania, Australia. Forest Ecology and Management, 158:237-247.
Box, G. E. P., and Cox, D. R. (1964) An analysis of transformations. Journal of the Royal Statistical Society, 26:211-252.
Boyce, M. S., Vernier, P. R., Nielsen, S. E., and Schmiegelow, F. K. A. (2002) Evaluating resource selection functions. Ecological Modelling, 157:281-300.
Brotons, L., Thuiller, W., Araújo, M. B., and Hirzel, A. H. (2004) Presence-absence versus presence-only modelling methods for predicting bird habitat suitability. Ecography, 27:437-448.
Buckland, S. T., and Elston, D. A. (1993) Empirical models for the spatial distribution of wildlife. Journal of Applied Ecology, 30:478-495.


Chang, K. M. (2002a) Description and anatomy of Coniglobus pekanensis insularis Kuroda et Kano MS from Lutao, Taiwan (Pulmonata: Camaenidae). Bulletin of Malacology, Taiwan, 26:35-40.
Chang, K. M. (2002b) Luchuena species from Pahsientung, Taitung county (Pulmonata: Enidae). Bulletin of Malacology, Taiwan, 26:17-26.
Chefaoui, R. M., Hortal, J., and Lobo, J. M. (2005) Potential distribution modeling, niche characterization and conservation status assessment using GIS tools: a case study of Iberian Copris species. Biological Conservation, 122:327-338.
Cook, A. (2005) Behavioural Ecology: On Doing the Right Thing, in the Right Place at the Right Time, In: Barker, G. M. (Ed.), The Biology of Terrestrial Molluscs, CABI publishing, UK, p447-487.
Cowie, R. H., Nishida, G. M., Basset, Y., and Gon, S. M. III (1995) Patterns of land snail distribution in a montane habitat on the island of Hawaii. Malacologia, 36(1-2):155-169.
Cumming, G. S. (2000a) Using habitat models to map diversity: pan-Africa species richness of ticks (Acari: Ixodida). Journal of Biogeography, 27:425-440.
Cumming, G. S. (2000b) Using between-model comparisons to fine-tune linear models of species ranges. Journal of Biogeography, 27:441-455.
Engler, R., Guisan, A., and Rechsteiner, L. (2004) An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data. Journal of Applied Ecology, 41:263-274.
Fielding, A. H., and Bell, J. F. (1997) A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation, 24:38-49.


Graveland, J., van der Wal, R., van Balen, J. H., and van Noordwijk, A. J. (1994) Poor reproduction in forest passerines from decline of snail abundance on acidified soils. Nature, 368:446-448.
Guisan, A., and Zimmermann, N. E. (2000) Predictive habitat distribution models in Ecology. Ecological Modelling, 135:147-186.
Guisan, A., and Thuiller W. (2005) Predicting species distribution: offering more than simple habitat models. Ecology Letters, 8:993-1009.
Hernandez, P. A., Graham, C. H., Master, L. L., and Albert, D. L. (2006) The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography, 29:773-785.
Hirzel, A. H., Helfer, V., Métral, F. (2001) Assessing habitat-suitability models with a virtual species. Ecological Modelling, 145:111-121.
Hirzel, A. H., Hausser, J., Chessel, D., and Perrin, N. (2002) Ecological-niche factor analysis: how to compute habitat-suitability maps without absence data? Ecology, 83:2027-2036.
Hirzel, A. H., Hausser, J., and Perrin, N. (2007) Biomapper 4.0. Laboratory for Conservation Biology, Department of Ecology and Evolution, University of Lausanne, Switzerland. URL: http://www2.unil.ch/biomapper
Hotopp, K. P. (2002) Land snails and soil calcium in central appalachian mountain forest. Southeastern Naturalist, 1:27–44.
Jiménez-Valverde, A., Ortuño, V. M., and Lobo, J. M. (2007) Exploring the distribution of Sterocorax Ortuño, 1990 (Coleoptera, Carabidae) species in the Iberian peninsula. Journal of Biogeography, 34:1426-1438.
Karlin, E. J. (1961) Ecological relationships between vegetation and the distribution of land snails in Montana, Colorado and New Mexico. American Midland Naturalist, 65(1):60-66.
Krebs, C. J. (1994) Ecology: the experimental analysis of distribution and abundance. 4th ed, Harper Collins College Publisher, New York.
Lawton, J. H. (1996) Pattern in Ecology. Oikos, 75:145-147.
Lee, P. F., Lue, K. Y., and Wu, S. H. (2006) Predictive distribution of hynobiid salamanders in Taiwan. Zoological Studies, 45:244-254.
Lee, Y. C., and Wu, W. L., (2006) An invasive Ariophantid species from India. Bulletin of Malacology, Taiwan, 30:55-60.
Levin, S. A. (1992) The problem of pattern and scale in Ecology. Ecology, 73:1943-1967.
Livingston, S. A., Todd, C. S., Krohn, W. B., and Owen, R. B. (1990) Habitat models for nesting bald eagles in Maine. Journal of Wildlife Management, 54:644-657.
Lütolf, M., Kienast, F., and Guisan, A. (2006) The ghost of past species occurrence: improving species distribution models for presence-only data. Journal of Applied Ecology, 43:802-815.
Lydeard, C., Cowie, R. H., Ponder, W. F., Bogan, A. E., Bouchet, P., Clark, S. A., Cummings, K. S., Frest, T. J., Gargominy, O., Herbert, D. G., Hershler, R., Perez, K. E., Roth, B., Seddon, M., Strong, E. E, and Thompson, F. G. (2004) The Global Decline of Nonmarine Mollusks. BioScience,54(4):321-330.
Mand, R., Tilgar, V., Leivits, A. (2000) Calcium, snails, and birds: a case study. Web Ecology, 1:63-69.
Manel, S., Dias, J. M., Buckton, S. T., and Ormerod, S. J. (1999a) Alternative methods for predicting species distribution: an illustration with Himalayan river birds. Journal of Applied Ecology, 36:734-747.


Manel, S., Dias, J. M., and Ormerod, S. J. (1999b) Comparing discriminant analysis, neural networks and logistic regression for prediction species distribution: a case study with a Himalayan river bird. Ecological Modelling, 120:337-347.
Margules, C. R., and Pressey, R. L. (2000) Systematic conservation planning. Nature, 405:243-253.
Orstan, A. (1999) Land Snails of Black HilI Regional Park, Montgomery County, Maryland. The Maryland Naturalist, 43:20-24.
Palma, L., Beja, P., and Rodgrigues, M. (1999) The use of sighting data to analysis Iberian lynx habitat and distribution. Journal of Applied Ecology, 36:812-824.
Pearce, J. L., and Venier, L. A. (2006) The use of ground beetles (Coleoptera: Carabidae) and spiders (Araneae) as bioindicators of sustainable forest management: A review. Ecological Indicators, 6:780-793.
Pearson, R. G., and Dawson, T. P. (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecology and Biogeography, 12:361-371.
Riddle, W. A. (1993) Physiological Ecology of Land Snails and Slugs. In: The Mollusca - Ecology.W.D. Russel-Hunter. Academic Press, Inc., London.
Romero, J., and Real, R. (1996) Macroenvironmental factors as ultimate determinants of distribution of common toad and natterjack toad in the south Spain. Ecography, 19:305-312.
Rushton, S. P., Ormerod, S. J., and Kerby, G. (2004) New paradigms for modeling species distributions? Journal of Applied Ecology, 41:193-200.
SAS Institute Inc. (2004) SAS OnlineDoc® 9.1.3. Cary, NC: SAS Institute Inc.
Seigel, R. A., Collins, J. T., and Novak, S. S. (1987) Snakes-Ecology and Evolutionary Biology. McGraw Hill, New York.
Smith, P. A. (1994) Autocorrelation in logistic regression modeling of species’ distribution. Global Ecology and Biogeography Letters, 4:47-61.
Sokal, R. R., and Rohlf, F. J. (1995) Biometry: the principles and practice of statistics in biological research. Third edition. W.H. Freeman and Company, New York.
Solhøy, T., Skartveit, J., and Eide, E. W. (1998) Evertebrater i skogbunnen - Terrestre skalldektesnegl. Aktuelt fra Skogforskningen, 3: 8-12.
Stockwell, D. R. B., Peterson, A. T. (2002) Effects of sample size on accuracy of species distribution models. Ecological Modelling, 148:1-13.
Su, H. J. (1984a) Studies on the climate and vegetation types of the natural forests in Taiwan (I): analysis of the variations in climatic factors. Quarterly Journal of Chinese Forestry, 17:1-14.
Su, H. J. (1984b) Studies on the climate and vegetation types of the natural forests in Taiwan (II): altitudinal vegetation zones in relation to temperature gradient. Quarterly Journal of Chinese Forestry, 17:53-73.
Tattersfield, P., Seddon, M. B., and Lange, C. N. (2001) Land-snail faunas in indigenous rainforest and commercial forestry plantations in Kakamega Forest, western Kenya. Biodiversity and Conservation, 10:1809-1829.
Tsoar, A., Allouche, O., Steinitz, O., Rotem, D., and Kadmon, R. (2007) A comparative evaluation of presence-only methods for modeling species distribution. Diversity and Distributions, 13:397-405.
Upton, G. J. G., Fingleton, B. (1989) Spatial Data Analysis by Example, Vol 2: Categorical and Directional data. John Wiley & Sons, Chichester.
Vollen, T. I. (2003) Predicting abundance, species richness and assemblages of woodland snails using environmental variables. Candidatus Scientiarum Thesis, Department of Zoology, University of Bergen, Norway.
Wells, S. M., Pyle, R. M. and Collins, N. M. (1983) The IUCN Invertebrate Red Data Book, IUCN and the UN Environment Programme. L+632, Cambridge, UK.

Wu, S. P. and Wu, W. L. (1998) The distribution of Camaenidae in Taiwan. Bulletin of Malacology, Taiwan, 22:43-48.
Wu, W. L. (1999) Mollusks in CITES. III+143, Council of Agriculture, Executive Yuan, Taipei, Taiwan.
Zaniewski, A. E., Lehmann, A., and Overton, J. McC. (2002) Predicting species spatial distributions using presence-only data: a case study of native New Zealand ferns. Ecological Modelling, 157:261-280.
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