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研究生:林依靜
研究生(外文):Lin, Yi-Ching
論文名稱:多層次功能多樣性分解測度:一般架構與軟體開發
論文名稱(外文):Hierarchical Decomposition of Functional Diversity Measures:General Framework and Software Development
指導教授:趙蓮菊趙蓮菊引用關係
指導教授(外文):Chao, Lien-Ju
口試委員:邱春火林宜靜江智民
口試委員(外文):Chiu, Chih-HungLin, Yi-ChingChiang, Jyh-min
口試日期:2018-07-18
學位類別:碩士
校院名稱:國立清華大學
系所名稱:統計學研究所
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:2018
畢業學年度:106
語文別:中文
論文頁數:209
中文關鍵詞:功能多樣性多層次分解
外文關鍵詞:Functional DiversityHierarchical Decomposition
相關次數:
  • 被引用被引用:1
  • 點閱點閱:140
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  • 收藏至我的研究室書目清單書目收藏:0
隨著環境保育與生物多樣性的概念逐漸受到重視,許多量化多樣性的指標相繼被提出,透過這些指標可以了解多樣性隨著時間或空間的變化,除了僅考慮物種相對豐富度的物種多樣性和物種演化歷史的系統演化多樣性,考慮物種特徵並量化的多樣性近年來逐漸受到重視,稱為功能多樣性指標(functional diversity)。功能多樣性越高代表一地區的生態功能越健全,越不容易受到外在環境變化的影響。另一方面,大部分多樣性指標僅考慮單一群落或群落間的關係,局限於兩層次下的多樣性分析,然而隨著蒐集資料技術的進步,包含基因、個體、物種、群落、地域、地景或整個生態系的多層次結構資料越來越常見,勢必要以結構關係來衡量各層次的多樣性。
本文的研究主題分為兩部分,第一部分為Chao等人(2018)和Gregorius & Kosman(2017)的單一群落功能多樣性指標的比較,探討各指標的性質及優劣,合理指標必須滿足特定基本性質,結果顯示Chao等人(2018)的功能多樣性指標滿足較多常見的基本性質且適用範圍較無限制;第二部分為基於Chao等人(2018)功能多樣性指標,以廣義熵指標的形式及加法分解的概念,建構多層次的功能多樣性分解形式,包含多層次架構、指標分解形式及衡量各層次差異的標準化相異性指標等,本文分解形式可考量不同階次q>=0及距離差異門檻下各層次的alpha、beta、gamma指標。兩部分均透過電腦模擬驗證結果並以真實資料介紹其實際應用,此外,透過R語言及網路套件Shiny,將本文功能多層次內容撰寫成互動式網頁軟體hiDIP Online,方便不擅長程式語言的使用者進行分析。
As more people are paying attention to the issue of environmental protection and biodiversity conservation, an enormous number of diversity measures have been proposed to quantify diversity and assess diversity change across spatial or temporal scales. In addition to the species diversity and the phylogenetic diversity, functional diversity has been increasingly used to take the difference between species traits into account. The higher the functional diversity is, the more stable the ecosystem is, and thus the whole ecosystem is less affected by the change of environment. Most functional diversity measures were derived for a single community, or multiple communities under two-level structure. Nowadays, because of the rapid advances of collecting-data technique, multi-level structures are involved in most data sets, which includes various levels of genes, individuals, species, communities, regions, landscapes, and ecosystems. Therefore, hierarchical analysis across multiple levels is essential to diversity analysis.
This thesis includes two parts. The first part focuses on the comparisons between the single community functional diversity measures of Chao et al.(2018) and Gregorius & Kosman (2017), and discusses the properties, advantages and disadvantages of each measure. The results show that the functional diversity measure of Chao et al.(2018)satisfies more good properties, and can be practically applied to a wide range of ecosystems. For the second part, based on Chao et al.’s(2018)functional diversity measure, hierarchical decomposition of functional diversity based on generalized entropies and addition decomposition is developed under a specified multi-level hierarchical structure. Standardized dissimilarity indices measuring the difference among aggregates (e.g., communities or subregions) at each level are also derived. The proposed decomposition quantifies alpha, beta and gamma diversity of each level under various diversity order q >= 0 and under varying thresholds of functional distinctiveness tau. For both parts, computer simulations are reported to show the performance of the proposed formulas; real data sets are used for illustrating practical application of the proposed hierarchical analysis. In addition, using R language and network package Shiny, an online software hiDIP Online (hierarchical Diversity Partitioning) is developed to facilitate the application of the proposed hierarchical functional analysis for users without R backgrounds.
第一章 緒論 1
第二章 符號介紹與相關文獻探討 4
2.1 模式假設與符號定義 4
2.1.1 抽樣方法與模式假設 4
2.1.2 符號介紹 4
2.2 物種多樣性相關文獻回顧 7
2.2.1 單一群落物種多樣性 7
2.2.2 多群落物種多樣性 10
2.3 功能多樣性相關文獻回顧 16
2.3.1 單一群落功能多樣性(Functional diversity) 16
2.3.2 Gregorius & Kosman功能多樣性概念 17
2.3.3 Gregorius & Kosman結構多樣性(Structural diversity)概念 19
2.3.4 Ricotta(2006)推廣至多層次分解架構 22
2.3.5 Pavoine et al.(2016)多層次分解架構 27
2.3.6 Smouse等人(2017)多層次分解架構 32
第三章 功能多樣性(Functional Diversity)相關探討 34
3.1功能多樣性指標族介紹 36
3.1.1 Chao等人(2018)功能多樣性指標族介紹 36
3.1.2 Gregorius & Kosman(2017)功能多樣性指標族介紹 38
3.2功能多樣性指標族性質比較 41
3.3 模擬研究與討論 48
3.3.1 模擬設定說明 48
3.3.2 模擬結果 49
3.4 實例分析 53
3.4.1 墾丁樣區資料 53
3.4.2 福山樣區資料 60
第四章 功能多層次分解架構 67
4.1 分解形式與架構建立 67
4.1.1 相對豐富度分解形式 67
4.1.2 絕對豐富度分解形式 73
4.2 結構與應用範圍 75
4.3 相異性指標轉換與定義 77
4.3.1 相對豐富度相異性指標 77
4.3.2 絕對豐富度相異性指標 79
4.4 與乘法分解的關係 80
4.4.1 相對豐富度 80
4.4.2 絕對豐富度 85
4.5 模擬研究與討論 90
4.5.1 模擬設定說明 90
4.5.2模擬結果 93
4.6 實例分析 101
4.6.1 羅亞爾河(Loire River)無脊椎動物資料 101
4.6.2 澳洲有袋類(marsupial)寬足袋鼩(Antechinus)基因資料 126
第五章 網頁開發與介紹 136
5.1 簡介 136
5.2 使用說明 136
5.3 輸出結果 139
第六章 結論與後續研究 146
參考文獻 148
附錄 151
附錄S1 功能多樣性指標性質證明 151
附錄S2 功能多層次 多樣性範圍證明 161
附錄S3 功能多樣性模擬 178
附錄S4 功能多層次架構模擬 184
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