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研究生:王文千
研究生(外文):Wen-ChienWang
論文名稱:臺灣繁殖鳥類氣候變遷脆弱性評估
論文名稱(外文):Climate Change Vulnerability Assessment of Breeding Birds in Taiwan
指導教授:陳一菁陳一菁引用關係
指導教授(外文):I-Ching Chen
學位類別:碩士
校院名稱:國立成功大學
系所名稱:生命科學系
學門:生命科學學門
學類:生物學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:英文
論文頁數:86
中文關鍵詞:氣候變遷族群趨勢脆弱度生物特徵繁殖鳥類調查
外文關鍵詞:Climate changePopulation trendVulnerabilitySpecies traitBreeding Bird Survey
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氣候變遷脆弱度評估 (Climate Change Vulnerability Assessment, CCVA) 框架定義包含三個面向:暴露度 (exposure) 為物種暴露於未來氣候威脅之程度;敏感度 (sensitivity) 為物種族群波動反應氣候變化之程度;調適能力 (adaptive capacity) 為物種通過自身調整來消弭氣候威脅之能力,如遷移與演化適應。迄今為止,許多研究使用生物特徵(species trait) 進行氣候變遷脆弱度評估,然而此方式可能無法反應物種對氣候變化的實際狀況,同時相較於溫帶地區,亞熱帶物種的脆弱度評估仍存在知識缺口。本研究利用臺灣繁殖鳥類大調查 (BBS Taiwan) 數據,配合臺灣氣候變遷推估資訊平台計畫之氣候資料庫與各種生物特徵進行氣候變遷脆弱度評估。此外,我們進一步發展氣候變遷脆弱度評估中敏感度的方法。我們針對資料筆數足夠的83種繁殖鳥進行評估,暴露方面利用最大熵模型(Maximum Entropy Model, MaxEnt)預測當前與未來的物種分佈,未來預測考慮兩個時期 (2041-2060及2061-2080) 與三種情境(RCP 2.6、4.5和8.5),以計算五種暴露指標: 物種範圍改變量(Predicted range changes, PRC)、與保護區範圍重疊變化 (Protected areas changes, PAC)、形狀指數改變量 (Shape index changes, SIC)、核心區域指數改變量 (Core area index changes, CAIC) 和關聯族群連結程度 (Population migration effort, PME)。敏感度使用偏最小平方路徑模型(partial least square path modeling, PLS-PM),區分鳥種族群動態是否對氣候敏感。調適能力則選用窩卵數 (clutch size) 與食性廣度 (diet breadth)篩選之。結果可分為四類:(1) 高度脆弱之物種共13種;(2) 可能適應之物種共4種;(3) 可能續存之物種共19種;(4) 潛在風險之物種共11種。與臺灣國家鳥類紅皮書所指出的瀕危名錄相較,上述鳥種中僅5種被列入接近受脅(NNT)等級,意味著氣候變遷的潛在威脅仍大幅度低估,存在相當的保育缺口。本研究是第一個亞洲低緯度地區的鳥類氣候變遷脆弱度評估,提供氣候變遷脆弱度評估的四種分類資訊,進而促進台灣鳥類不同的保育作為。
The Climate Change Vulnerability Assessment (CCVA) framework definition includes three dimensions: exposure is the extent to which a species exposed to future climate threats; sensitivity is the extent to which a population dynamic responds to climate change; adaptive capacity is the ability of a species to eliminate climate threats through its own adjustments, such as migration and evolutionary adaptation. To date, many studies have used species traits to conduct CCVA, however this approach may not reflect the actual state of the species to climate change. While compared to temperate regions, there is still a knowledge gap in the vulnerability assessment of subtropical species. This study used the Taiwan Breeding Bird Survey (BBS Taiwan), the climate database of Taiwan Climate Change Projection and Information Platform Project (TCCIP) and species traits to conduct CCVA. In addition, we advanced the methodology of sensitivity in CCVA instead of using species traits. We evaluated 83 breeding birds with sufficient data. To assess exposure, we used the Maximum Entropy Model (MaxEnt) to predict current and future distributions of species. We used future predictions in two periods (2041-2060 and 2061-2080), and under three scenarios (RCP 2.6, 4.5, and 8.5) to calculate five exposure metrics: predicted range changes (PRC), protected areas changes (PAC), shape index changes (SIC), core area index changes (CAIC) and population migration effort (PME). To evaluate sensitivity, we used partial least square path modeling (PLS-PM) to distinguish whether the bird population dynamics are sensitive to climate. Adaptive capacity was evaluated based on the species traits of clutch size and diet breadth. The results can be divided into four categories: (1) Highly vulnerable, including 13 species; (2) Potential adapters, including 4 species; (3) Potential persisters, including 19 species; (4) 11 species of High latent risk. Compared with Taiwan National Red List, only 5 species are Nationally Near-threatened (NNT), meaning that the potential threat of climate change is still largely underestimated, and there is a considerable gap in conservation. This study is the first CCVA of bird in low latitude of Asia and provides four categories of vulnerability need different strategy to promote the conservation of Taiwanese birds.
口試合格證明 i
中文摘要 ii
ABSTRACT iii
致謝 iv
CONTENTS v
LIST OF TABLES vii
LIST OF FIGURES viii
LIST OF APPENDIX TABLES ix
LIST OF APPENDIX FIGURES x
INTRODUCTION 1
1.1. Climate change 1
1.2. Impact of climate change on birds 1
1.3. Climate Change Vulnerability Assessment 2
1.4. Challenges of trait-based vulnerability assessments 3
1.5. Gap of CCVA in tropical and subtropical area 4
1.6. Aim 4
2. MATERIALS AND METHODS 6
2.1. Species occurrences 6
2.2. Bioclimatic data 6
2.3. High exposure 7
2.3.1. Species distribution model techniques 7
2.3.2. Final measures of species range exposure 8
2.3.3. Defined as highly exposed species in CCVA 10
2.4. High sensitivity 11
2.5. Low adaptive capacity 12
3. RESULTS 13
3.1. Defined as highly exposed species in CCVA 13
3.2. Defined as high sensitivity and low adaptive capacity species in CCVA 13
3.3. Climate change vulnerability list 14
4. DISCUSSTION 15
4.1. High exposure to climate change 15
4.2. High sensitivity to climate change 15
4.3. Low adaptive capacity to climate change 16
4.4. Comparisons CCVA result with IUCN Red List 17
4.5. Summary of vulnerability 17
4.6. Limitation of our study 18
5. CONCLUSTION 19
6. REFERENCE 20
TABLES 28
FIGURES 49
TABELS IN APPENDIX 64
FIGURES IN APPENDIX 83
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