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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 邱祈榮(Chyi-Rong Chiou) | |
| dc.contributor.author | Chiao-Lin Chen | en |
| dc.contributor.author | 陳巧霖 | zh_TW |
| dc.date.accessioned | 2021-06-16T08:12:29Z | - |
| dc.date.available | 2014-03-21 | |
| dc.date.copyright | 2014-03-21 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-02-16 | |
| dc.identifier.citation | 方精云 (2001) 也論我國東部植被的劃分。植物學報43(5): 522-533。
白宏益 (2003) 用熵最大法分析磁腦儀模擬數據。中興大學研究所碩士論文。 呂光洋 (1999) 生物多樣性熱點如何選定?。行政院農業委員會。生物多樣性研討會。159-165。 李培芬 (2008) 氣候變遷對生態的衝擊。科學發展。424: 34-43。 宋永昌 (1999) 中國東部森林植被帶劃分之我見。植物學報41(5): 541-552。 吳宜昭、陳永明、朱容練 (2010) 台灣氣候變遷趨勢。國研科技專題企畫。25: 40-46。 邱清安、林鴻志、廖敏君、曾彥學、歐辰雄、呂金誠、曾喜育 (2008) 台灣潛在植群形象分類方案。林業研究季刊30(4): 89-112。 孫世鐸 (2011) 應用物種分布模式於氣候變遷下監測樣區之篩選。台灣大學碩士論文。 徐嘉君 (2007) 利用生態棲地模擬(Ecological Niche Modeling, ENM)預測物種分佈模式及其於保育聖物學上的利用。 林業研究專刊 14(1): 36。 麥愛堂 (2003) 生物多樣性世界與生態保育。科學發展。372: 46-53。 陳正祥 (1957) 台灣氣候之分類。氣候學報。3(2): 1-9。 陳守泓、姚銘輝、申雍 (2005) 氣候變遷對台灣地區糧食安全之衝擊與因應對策。 全球變遷通訊雜誌。46: 7-13。 許晃雄、陳正達、盧孟明等 (2001) 台灣氣候變遷科學報告2001。行政院國家科學委員會。2001:32。 梁啟源 (2008) 氣候變遷對台灣經濟的影響。科學發展。424: 50-53。 劉棠瑞、蘇鴻傑 (1983) 森林植物生態學。台灣商務印書館股份有限公司。221-223。 蘇鴻傑 (2004) 植群多樣性及多樣化之分類法。臺大實驗林研究報告。18(3): 207-220。 蘇鴻傑 (1984) 台灣天然林氣候與植群型之研究(二)山地植群帶與溫度低度之關係。中華林學季刊17(4): 57-73。 Anderson, R.P. & E. Martìnez-Meyer (2004) Modeling species’geographic distributions for preliminary conservation assessments: an implementation with the spiny pocket mice (Heteromys) of Ecuador. Biological Conservation. 116: 167-179. Bässler,C., J. Müller, T. Hothorn, T. Kneid, F. Badeck & D. Dziock(2010) Estimation of the extinction risk for high-montane species as a consequence of global warming and assessment of their suitability as cross-taxon indictors. Ecological Indicators 10: 341-352. Beggs, P.J. (2004) Impacts of climate change on aeroallergens: past and future. CliN Exp Allergy.34: 1507-1513. Benzing, D.H. (1998) Vulnerabilities of tropical forest to climate change: the significance of resident epiphytes.Climate Change, 39: 519-540. Chou, C.H., T.J. Huang, Y.P.,Lee, C.Y. Chen, T.W.,Hsu & C.H. Chen (2011) Diversity of the alpine vegetation in central Taiwan is affected by climate change based on a century of floristic inventories. Botanical Studies. 52: 503-516. Cuttet, S.L. (1996) Vulnerability to environmental hazards. Progress in Humam Geography. 20(4): 529-539. Esteve-Selma, M.A., J. Martínez-Fernández, I.Hernández-García, J.P. Montávez, J.J. López-Hernández & J.F. Calvo (2012) Potential effects of climatic change on the distribution of Tetraclinis articulate, an endemic tree from arid Mediterranean ecosystems. Climatic Change 113: 663-678. Faraggi, D. & R. Benjamin (2002) Estimation of the area under the ROC curve. Statistics in Medicine.21: 3093-3106. Fawcett,T. (2005) An introduction to AUC analysis.Elsevier.27: 861-874. Hsu, R.C.C., W.L.M. Tamis, N. Reas, G.R. de Snoo, J.H.D. Wolf, G. Oostermeijer, & S.H. Lin (2011) Simulating climate change impacts on forest and associated vascular epithytes in a subtropical island of East Asia. Diversity and Distributions.18: 334-347. IPCC (2001) IPCC Third Assessment Report.Available from http://www.ipcc.ch/. Jaynes,E.T. (1957) Information Theory and Statistical Mechanics. Physical Review. 106: 620-630. Kira, T. (1997) A climatological interpretation of Japanese vegetation zones. Vegetation science and environmental protection (ed. Miyawaki, A. & Tüxwn, R.). Maruzen, Tokyo, 21-30. Kovats, R.S., S.J. Edwards, S. Hajat, B.G. Armstrong, K.L. Ebi, B. Menne & The Collaborating Group (2004) The effect of temperature on food poisoning: a time-series analysis of salmonellosis in ten European countries.Epidemiol infect.132: 443-453. Kuhlmann, M., D. Guo, R. Veldtman & J. Donaldson (2012) Conseduences of watming up a hotspot: species range shifts within a centre a centre of bee diversity. Biodiversity research.18: 855-897. Li,C.F., M. Chytrý, D. Zelený, M.Y. Chen, T.Y. Chen, C.R. Chiou, Y.J. Hsia, H.Y. Liu, S.Z. Yang,. C.L. Yeh, J.C. Wang, C.F. Yu, Y.J. Lai, W.C. Chao, & C.F. Hsieh (2013) Classification of Taiwan forest vegetation. Applied Vegetation Science.1-22. Linden, W. (1995) Maximun-entropy data analysis. Applied Physic A, 60: 155-165. Luedeling,E., E.H. Girvetz, M.A. Semenov, P.H. Brown (2011) Climate Change Affects Winter Chill for Temperate Fruit and Nut Trees.Plos One,6(5): 1-13. Luers, A.L. (2005) The surface of vulnerability: An analytical framework for examining environmental change. Global Environmental Change.15: 214-223. Matsuo, T. (1985) Late-Quaternary Shift of Fagus Distribution. Tokyo. 95: 203 – 217 Marzban, C. (2004) A Comment on the ROC Curve and the Area Under it as Performance Measures. Weather and Forecasting. 19: 1106-1114. Matsui, T., T. Yagihashi, T. Nakaya, N. Tanaka & H. Taoda (2004) Climatic controls on distribution of Fagus crenata forests in Japan. Journal of Vegetation Science, 15: 57-66 Midgley, G.F., L. Hannahm, D. Millar, M. C. Rutherford & L.W. Powrie (2002) Assessing the vulnerability of species richness to anthropogenic climate change in a biodiversity hotspot. Global & Biogeogrophy,11: 445-451. Mills, J.A. (1992) Making inflexible investment decisions with incomplete information. Computers & Mathematics with Applications. 24: 247-258. Muniz, W.B., F.M. Ramos & H.F. Campos Velho (2000) Computer and Mathematic with Applications40: 1071-1084. Ochoa-Ochoa, L.M., P. Rodríguez, f. Mora, O. Flores-Villela & R.J. Whittaker (2012) Climate change and amphibian diversity patterms in Mexico. Biological Conservation,150: 94-102. Ogawa-Onishi, Y., P.M., Berry, & N. Tanaka, (2010) Assessing the potential impacts of climate change and their conservation implications in Japan: A case study of conifers.Biological Conservation 143: 1778-1736. Pearman,P.B., A. Gusisan, & N.E. Zimmermann (2012) Impacts of climate change on Swiss biodiversity: An indicator taxa approach. Biological Conservation 144: 866-875. Phillips,S.J., & M. Dudik (2008) Modeling of species distribution with Maxent: new extensions and a comprehensive evaluation. Ecography,31: 161-175. Phillips,S.J., P.R. Anderson & R.E. Schapire (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190: 231-259. Pounds, J-A., M.P.I. Fogden & J.H. Campbell (1999) Biological response to climate change on a tropical mountain. Nature,398: 611-615. Pulliam, H.R. (2000) On the relationship between niche and distribution. Ecology Letters.3: 349-361. Ratnaparkhi, A. (1997) A Simple Introduction to Maximum Entropy Models for Natural Language Processing. Technical Report. Institute for Research in Cognitive Science. University of Pennsylvania. Rebelo,H., P. Tarross & G. Jones (2010) Predicted impact of climate change on European bats in relation to their biogeographic patterns. Global Change Biology,16: 651-576. Reeves, W.C., J.L. Hardy, W.K. Reisen & M.M. Milby (1994) Potential effect of globl warming on mosquito-borne arboviruses. Journal of Medical Entomology. 31: 323 - 332. Richardson, D.M., N. Allsopp, C.M. D’Antonio, S.J. Milton, & M. Rejmanek (2000) Plant invasion – the role of mutualisms. Biological Review, 75, 65-93. Rogers, D.J., & S.E. Randolph (2000) The global spread of malaria in a future, warmer world. Science. 289: 1763-1766. Rose, J.B., P.R. Epstein, E.K. Lipp, B.H. Sherman, S.M. Berbard & J.A. Patz (2001) Climate variability and change in the United States: potential impacts on water- and foodborne diseases caused by microbiologic agents. Environmental Health Perspect.109:211-221. Rosset, S. (2004) Model Selection via theAUC. In Proceedings of the 21st International Conference on Machine Learning. Sørensen, T. (1948) A method of establishing groups of equal amplitude in plant sociology based on similiarity of species content. Danske Videnskabernes Selskabs Biologiske Skrifter. 5(4): 1-34. Su, H.J. (1984) Studies on the climate and vegetation types of the natural forest in Taiwan.(Ⅱ) Altitudinal vegetation zones in relation to temperature gradient. Jour. Chin. For.17:57-73. Summers, D.M., B.A. Bryan, N.D. Crossman & W.S. Meyer (2012) Species vulnerability to climate change: impact on spatial conservation priorities and species representation. Global Change Biology.18: 2335-2348. Swab, R.M., H.M. Regan, D.A. Keith, J.R. Tracey & M.K.I. Ooi (2012) Nich models tell half the story: spatial context and life-history traits influence species responses to global change. Journal of Biogeography.39: 1266-1277. TurnerII, B.L., R.E. Kasperson, P.A. Matson, J.J. McCarthy, R.W. Corell, L. Christensen, N. Eckley, J.X. Kasperson, A. Luers, M.L. Martello, C. Polsky, A. Pulsiper, & A. Schiller (2003) A framework for vulnerability analysis in sustainability science. Proceedings of the National Academy of Sciences .100: 8074-8079. Vanagas, G. (2004) Receiver operating characteristic curves and comparison of cardiac surgery risk stratification systems. Interactive Cardiovascular and Thoracic Surgery.3: 319-322. Woodward, F.I. & B.G. Williams (1987) Climate and plant distribution at global and local scales. Vegetatio. 69: 189-197. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/58359 | - |
| dc.description.abstract | 氣候變遷對於生態系的衝擊十分的可觀，為了預測氣候變遷對物種的影響，本研究以2003年行政院農委會林務局推動的「國家植群多樣性調查及製圖計畫」所收集的物種資料，以櫟林帶中21種特徵種為研究對象。氣候資料使用台灣氣候變遷評估與資訊平台計畫 ( Taiwan Climate Change Projection & Information Platform, TCCIP )提供之溫量指數、一月均溫、夏季降雨量與冬季降雨量為因子，未來情境則選用IPCC提出之A1B模擬情境，之後利用Maxent套裝軟體進行物種分布機率預測作業。結果顯示未來櫟林帶核心區海拔平均上升至2,192m的高度，約上升了296.83m，而海拔分布範圍將縮減約60.12m。特徵種中海拔分布範圍減少最多者為假柃木(Eurya crenatifolia)，次者為台灣扁柏(Chamaecyparis obtusa var. formosana)。另外，以脆弱度進行評估的結果顯示，脆弱度指數大於5所占面積最大者為台灣扁柏，次者為赤柯(Cyclobalanopsis morii)。特徵種熱點方面顯示，以中央山脈南段與南澳等地區物種數目變化最大。整體而言，未來櫟林帶將往高海拔移動，且未來氣候下分布於南部者明顯減少，多往北部山區集中。 | zh_TW |
| dc.description.abstract | Climate change has a great impact on ecosystems. In order to predict the impact of climate change on species, this study selected 21 characteristic species of Quercus zone in the project, 'Taiwanese National Vegetation Diversity Inventory and Mapping Project ', of Forestry Bureau in 2003. This study chose average temperature in January, warmth index, summer precipitation, and winter precipitation of which provided by Taiwan Climate Change Projection & Information Platform (TCCIP) as the climate factor. Futhermore, A1B, provided by Intergovernmental Panel on Climate Change (IPCC), was selected as the future scenario and Maxent software was used to predict the probability of species distribution. The results showed that the core area of the Quercus zone would retreat to 2,192 meters in the future, which would be 296.83 meters higher than the current altitude. Besides, the altitude distribution range would be reduced approximately 60.12 meters as Eurya crenatifolia and and Chamaecyparis obtusa var. formosana show the most declination respectively. In addition, the vulnerability assessment results showed that the vulnerability index greater than 5 and occupying the most space is Cyclobalanopsis morii. In terms of hotspots, number of species in southern part of the Central Mountain Range, Smangus and Nan Oau would reduce the most. This study emphasized that Quercus zone would retreat towards higher altitudes and most of all species would concentrate in the northern mountains in the future. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T08:12:29Z (GMT). No. of bitstreams: 1 ntu-103-R00625016-1.pdf: 5618335 bytes, checksum: 19886b5886513f3571b5231c4cd16323 (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | 摘要 i
Abstract ii 目錄 iii 圖目錄 iv 表目錄 vii 壹、前言 1 貳、文獻回顧 2 一、氣候變遷衝擊 2 二、最大熵值法(maximum entropy, MAXENT) 5 三、植群帶與特徵種 8 參、研究區域與材料 11 一、研究區域 11 二、資料來源 13 (一)氣候資料 13 (二)物種資料 18 肆、研究流程與方法 21 一、研究流程 21 二、研究方法 22 (一)物種分布機率預測 22 (二)特徵種分類 23 (三)脆弱度評估 23 (四)特徵種熱點 24 伍、結果 26 一、櫟林帶與21種特徵種個論 26 (一)櫟林帶 26 (二)特徵種個論 29 二、特徵種熱點評估 92 陸、討論 94 一、特徵種交互關係 94 二、特徵種與櫟林帶關係 99 三、櫟林帶與特徵種脆弱度 104 四、特徵種熱點 105 柒、結論 110 捌、參考文獻 112 | |
| dc.language.iso | zh-TW | |
| dc.subject | 櫟林帶 | zh_TW |
| dc.subject | 脆弱度 | zh_TW |
| dc.subject | 分布熱點 | zh_TW |
| dc.subject | 特徵種 | zh_TW |
| dc.subject | 最大熵值法 | zh_TW |
| dc.subject | Quercus zone | en |
| dc.subject | vulnerability | en |
| dc.subject | hotspot | en |
| dc.subject | characteristic species | en |
| dc.subject | maximum entropy | en |
| dc.title | 氣候變遷對櫟林帶特徵種之衝擊評估 | zh_TW |
| dc.title | Impact Assessment on the Characteristic Species in Quercus Zone under Climate Change | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳子英,曾彥學 | |
| dc.subject.keyword | 櫟林帶,脆弱度,分布熱點,特徵種,最大熵值法, | zh_TW |
| dc.subject.keyword | Quercus zone,vulnerability,hotspot,characteristic species,maximum entropy, | en |
| dc.relation.page | 118 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2014-02-17 | |
| dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
| dc.contributor.author-dept | 森林環境暨資源學研究所 | zh_TW |
| 顯示於系所單位： | 森林環境暨資源學系 | |
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