◎系所教育目標：
本所旨在培育進階生物資源科學人才，教學理念上理論與實務並重，研究生物多樣性及生物與環境的關係，培養學生在物種系統分類、物種與生存環境特性，及生物資源永續利用之研究能力，使具有判斷環境變異，保護環境與資源利用價值之能力。用以監測環境、生物多樣性及入侵物種，保育珍稀物種與棲地復育，進而尋求開發永續利用生物資源的方法，促進人類的生活福祉。本所教育目標分述如下：
1.奠定學生生命科學研究之專業能力。
2.培養學生生物多樣性保育與生物資源永續利用之應用能力。
3.強化學生團隊合作與全方位學習之能力。
4.培育學生成為術德兼備、追求卓越與創新之人才。 |
| ◎核心能力 | 關聯性 |
| 1.具備生命科學進階理論之專業知能。 | 5 關聯性最強 |
| 2.具備研究生物多樣性、物種及生存環境特性之專業知能。 | 5 關聯性最強 |
| 3.具備監測環境及生物多樣性、研究環境變異與保護環境之專業知能。 | 5 關聯性最強 |
| 4.具備生態保育與永續經營的觀念及服務之專業能力。 | 3 關聯性中等 |
| 5.具備觀察、資料蒐集、推理及創造之能力。 | 5 關聯性最強 |
| 6.具備發掘、分析及解決問題之能力。 | 5 關聯性最強 |
| 7.有效溝通與團隊合作之能力。 | 2 關聯性稍弱 |
| 8.培養人文素養、專業倫理責任、社會關懷與生活技能之能力。 | 1 關聯性最弱 |
◎本學科內容概述：
"Advanced vegetation analysis course aims to develop students' ability to process vegetation data. The course includes several advanced analytic procedures of vegetation science,
(1)pattern recognition of vegetation
types
(2) multivariate analyses of
vegetation data
(3) vegetation classification
(4) species distribution modeling and analyses of vegetation dynamics. " |
◎本學科教學內容大綱：
1.Patterns in vegetation ecology
2.Data transformation
3.Multivariate analyses
4.Vegetation classification
5.Joining ecological patterns
6.Static explanatory modelling
7.Vegetation change in temporal scale
8.Dynamic modelling
9.Species distribution modelling" |
◎本學科學習目標：
Advanced vegetation analysis course aims to develop students' ability to process vegetation data. The course includes several advanced analytic procedures of vegetation science,
(1) pattern recognition of vegetation types
(2) multivariate analyses of vegetation data
(3) vegetation classification
(4) species distribution modeling and analyses of vegetation dynamics.
In this course, I will introduce most of the modern techniques applied in vegetation science and the students will have the chance to analyse big data sets of Taiwan Vegetation D a t a b a s e (National Vegetation Diversity Inventory and Mapping Project; NVDIMP). |
| ◎教學進度： |
| 週次 | 主題 | 教學內容 | 教學方法 |
01
09/11 | 植群生態學資料分析簡介 | 課程簡介 | 操作/實作、講授、討論。 |
02
09/18 | 植群生態中的特徵 | Pattern recognition of vegetation types | 操作/實作、講授、討論。 |
03
09/25 | Data transformation (1) | Vegetation data transformation | 操作/實作、講授、討論。 |
04
10/02 | Multivariate analyses (1) | Multivariate statistics. | 操作/實作、講授、討論。 |
05
10/09 | Multivariate analyses (2) | Ordination analyses (1) — PCA, PCoA, DCA | 操作/實作、講授、討論。 |
06
10/16 | Multivariate analyses (3) | Ordination analyses (2) — NMDS | 操作/實作、講授、討論。 |
07
10/23 | Vegetation classification (1) | Cluster analyses | 操作/實作、講授、討論。 |
08
10/30 | Vegetation classification (2) | Using JUICE vegetation analyses software to classify syntaxa | 操作/實作、講授、討論。 |
09
11/06 | Vegetation classification (3) | Structured synoptic tables | 操作/實作、講授、討論。 |
10
11/13 | Mid-term exam | Mid-term exam | exam。 |
11
11/20 | Joining ecological patterns | Joining ecological patterns | 操作/實作、講授、討論。 |
12
11/27 | Static explanatory modelling | Static explanatory modelling | 操作/實作、講授、討論。 |
13
12/04 | Vegetation change in temporal scale | Vegetation change in temporal scale | 操作/實作、講授、討論。 |
14
12/11 | Dynamic modelling | Dynamic modelling | 操作/實作、講授、討論。 |
15
12/18 | Species distribution modelling | Species distribution modelling | 操作/實作、講授、討論。 |
16
12/25 | Case studies (1) | Practical analyses of Taiwan National Vegetation Databas e (1) | 操作/實作、講授、討論。 |
17
01/01 | Case studies (2) | Practical analyses of Taiwan National Vegetation Databas e (1) | 操作/實作、講授、討論。 |
18
01/08 | Final exam | Final exam | exam。 |
◎課程要求：
This course is an advanced data analysis course of vegetation ecology. Preliminary course is vegetation ecology and fundamental ecology. We will use R and JUICE vegetation analysis software to teach, so you must bring your own laptop and install them first. |
◎成績考核
期中考30%
期末考40%
作業/習題演練30%
|
◎參考書目與學習資源
Wildi, O. (2017). Data Analysis in Vegetation Ecology. 3rd Edi. CABI. 352pp.
Borcard, D., Gillet, F. and Legendre, P (2011) Numerical Ecology With R. Springer-Verlag, New York. 306pp.
Mucina, L. (2018) Vegetation Survey and Classification of Subtropical Forests of Southern Africa. Springer-Verlag, New York. 236 pp. |
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