Transcript 下載講義1 - National Taiwan University

樹木學及實習
Dendrology and Practice
植物型態
Plant Morphology
國立臺灣大學 森林環境暨資源學系 鍾國芳 (Kuo-Fang Chung)
School of Forestry and Resource Conservation, National Taiwan University
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1
How to classify plants?
• How do we put different plants in groups?
• What is species? How to recognition and delimitate species? (物種的描述)
• Classification (分門別類)
2
What is a plant species?
• Since the ancient Greek, a species, such as particular species of oak, was
considered the manifestation of a unique, unchangeable essence (本質).
Any deviations from this essence were regarded as unimportant.
• Darwin’s “Origin of Species”
Darwin’s observations and inferences leading to the Evolution theories
Superfecundity
Variation
Steady state of
natural
populations
Struggle for
existence
Limited
resource
Heritability
of variation
Differential
survival (natural
selection)
Over many
generations,
evolution &
speciation
3
Modern corn—a miracle of artificial selection (人擇)
4
What should we do with the species problems?
• Different groups of organisms differ widely in morphology, genes, ecology,
geographic distribution, pollination ……
• The lack of consensus on species definition can partly attribute to idiosyncratic
nature of the biodiversity.
• Each lineage is unique.
• Morphology is the most accessible source of data about evolutionary relationship
and is the only basis for the easy recognition of most species today.
• Taxa are hypotheses, open to repeat testing as new data or methods of analysis
become available (e.g., DNA barcoding).
5
Darwin placed Linneaus scheme of classification within an
evolutionary framework—Descent with modification
“… species are nested within genera, genera within families, and so forth because of a history of
descent with modification within evolutionary lineages—“…the view that an arrangement
(hierarchical taxonomic system) is only so far natural as it is genealogical (evolutionary)”
6
The importance of (organism) classification
• Organizing knowledge of the natural world into a system aids
communication and helps us to understand better the organisms that
surround us and upon which we depend. ……. The basic function of words
is that of naming (Lyons 1977), and in the human mind nothing really exists
or can be communicated without a name.
Christenhusz et al. (2011) Preface to “Linear sequence, classification, synonymy, and bibliography of vascular plants:
Lycophytes, ferns, gymnosperms and angiosperms” Phytotaxa 19: 4-6.
7
Classification:
naming (命名), grouping (歸類), and naming the groups
• Names:
• Purposes of classification:
•
•
•
•
•
Easy to use
Stable
An aid to memory
Predictive
concise
• The logic of classification:
• Hierarchical, groups nested within groups
8
The hierarchical (階層) natural of classification—
groups nested within groups
9
Classification: naming and grouping
• Effective and efficient communication
•
•
•
•
Think about the amount of information a name carries!
The degree of confidence on a classification system.
Reducing the heterogeneity of a group of objects
Increase our understanding and ability to predict the characteristics of any one of the
objects.
• Scale, hierarchical
• Purpose-driven (no single best classification)
• Not a static, once-and-for-all activity
• Anything can be classified, but modern biological classification is different
because it involves evolutionary relationships.
10
植物分類學
Plant Classification/Taxonomy/Systematics
• 植物分類學
• Classification (分類學): classifying
• Taxonomy (命名學): Naming (taxon/taxa: 分類群)
• Systematics (系統分類學): classification + taxonomy + phylogenetics (親緣關係、
譜系關係)
• 植物辨識 (plant identification)
• 野外工作、標本館、形態學
• 植物命名 (nomenclature, taxonomy)
• 植物命名法規 (International Code of Botanical Nomenclature)
• 分類文獻 (priority)
• 植物親緣關係的重建 (phylogenetics, systematics)
• 穩定且能反映物種演化的分類架構 (Classification)
• Angiosperm Phylogeny Group Classification (APG III)
11
How to classify plants?
• Hierarchical taxonomic system is so far natural only as it is
genealogical (evolutionary)
• How do we put different plants in groups?
12
How will you classify?
Which plants should be classified as groups?
13
How will you classify?
Which plants should be classified as groups?
Plant habit is important? (woody vs. herbaceous plants)
14
How will you classify?
Which plants should be classified as groups?
•Plant habit is important? (woody vs. herbaceous plants)
•Leaf shape is more important? (elliptic vs. linear)
15
How will you classify?
Which plants should be classified as groups?
•Plant habit is important? (woody vs. herbaceous plants)
•Leaf shape is more important? (elliptic vs. linear)
•Number of petals is more important (5 vs. 4)
16
How will you classify?
Which plants should be classified as groups?
•Plant habit is important? (woody vs. herbaceous plants)
•Leaf shape is more important? (elliptic vs. linear)
•Number of petals is more important (5 vs. 4)
•Color of petals is more important (yellow vs. red)
17
How will you classify?
Which plants should be classified as groups?
•Plant habit is important? (woody vs. herbaceous plants)
•Leaf shape is more important? (elliptic vs. linear)
•Number of petals is more important (5 vs. 4)
•Color of petals is more important (yellow vs. red)
•Number of stamen is more important (5 vs. 4 vs. 2)
18
How will you classify?
Which plants should be classified as groups?
•Plant habit is important? (woody vs. herbaceous plants)
•Leaf shape is more important? (elliptic vs. linear)
•Number of petals is more important (5 vs. 4)
•Color of petals is more important (yellow vs. red)
•Number of stamen is more important (5 vs. 4 vs. 2)
•Pollen surface is more important (smooth vs. spiny)
19
How will you classify?
Which plants should be classified as groups?
• Why should I believe you?
• A deeper understanding of morphological characters
• developmental, ontongenetic studies
20
The tradition of taxonomy……
“Young taxonomists are trained like performing monkeys, almost wholly
by imitation, and that only in the rarest cases are they given any
instruction in taxonomy theory”
—Cain (1959)
“…… because of the subjective nature of the problem, it is difficult to
lay down any hard and fast procedure for attaining satisfactory
results……” —Mayr, Linsley, and Usinger (1953)
21
Giants in plant taxonomy and
their classification systems
• Carolus Linnaeus (L.) (1707-1778)
‒ Species plantarum (1753), starting point of plant taxonomy
• de Jussieu
‒ Genera plantarum (1789)—the idea of family
• Augustin Pyramus de Candolle (DC.)
‒ Prodromus systematis naturalis regni vegetabilis (1824-1873)
• George Bentham and Joseph D. Hooker
‒ Genera plantarum (1862-1883)
22
Giants in plant taxonomy and
their classification systems (cont.)
• Engler and Prantl—Die Naturlichen Pflanzenfamilien (1889-1907)
• C. E. Bessey—The Essentials of Botany (1884)
• J. Hutchinson—The Families of Flowering Plants (1973)
• A. Takhtajan—Outline of the Classification of Flowering Plants (1980)
• A. Croquist—An Integrated System of Classification of Flowering Plants (1981)
• Angiosperm Phylogeny Group (1998- )
‒ Hopefully, from now on, this is the only system we have to remember and
follow!
23
分類學原理 (Principles of Classification)
• How to classify plants? How do we put different plants in groups?
‒ By comparing characters possessed by different plants and then placing them
in groups, guided by trained intuition, almost by instinct, taxonomy is largely
still practicing this way (～1960’s)
‒ By calculating the overall similarity of all (as many as possible) characters that
you can observed—phenetics (數值分類學/相似性分類學) (1960’s～)
‒ By tracking the transformation of character state series and find the shortest
possible trajectory (among the numerous possibilities) of all character
transformations—cladistics [支序(分類)學] (1960’s～)
24
Numerical Phenetics (numerical taxonomy)
數值分類、表形學派
• P.H.A. Sneath (bacteriologists) and R.R. Sokal (biostatistist, anthropologist)
• Searching for objective classification based on purely numerical (phenetic),
overall similarity among taxa.
• Hope to recover history but did not intend to reconstruct phylogenetic
relationship.
25
特徵 (character) 與特徵狀態 (character state)
•莖: 木本 (woody) vs. 草本 (herbaceous)
•葉形: 橢圓形 (elliptic) vs. 線形 (linear)
•花瓣數目: 5 vs. 4
•花瓣顏色: 黃 (yellow) vs. 紅 (red)
•雄蕊數目: 5 vs. 4. vs. 2
•花粉表面: 平滑 (smooth) vs. 有刺 (spiny)
26
特徵資料矩陣
Character
data matrix
•莖: 木本 (woody) vs. 草本 (herbaceous)
•葉形: 橢圓形 (elliptic) vs. 線形 (linear)
•花瓣數目: 5 vs. 4
•花瓣顏色: 黃 (yellow) vs. 紅 (red)
•雄蕊數目: 5 vs. 4. vs. 2
•花粉表面: 平滑 (smooth) vs. 有刺 (spiny)
葉形
莖
花瓣數目
花瓣顏色
雄蕊數目
花粉表面
X. alba
E
W
5
R
4
Sp
X. lutea
E
H
5
R
4
Sm
X. nigra
L
W
4
Y
2
Sm
X. purpurea
L
W
4
Y
2
Sp
X. rubens
L
W
4
Y
4
Sm
X. elliptica
E
W
5
Y
5
Sm
27
From data matrix to distance table
葉形
莖
花瓣數目
花瓣顏色
雄蕊數目
花粉表面
A- X. alba
E
W
5
R
4
Sp
B- X. lutea
E
H
5
R
4
Sm
C- X. nigra
L
W
4
Y
2
Sm
D- X. purpurea
L
W
4
Y
2
Sp
E- X. rubens
L
W
4
Y
4
Sm
F- X. elliptica
E
W
5
Y
5
Sm
• Calculate the differences
between two plants
‒
‒
‒
‒
‒
‒
X. alba: E
X. lutea:E
difference
X. alba: E
X: nigra:L
difference
• Fill the matrix
W
H
=
W
W
=
5
5
2
5
4
5
A
B
C
D
E
F
R 4 Sp
R 4 Sm
A
0
2
5
4
4
3
B
2
0
5
6
4
3
R 4 Sp
Y 2 Sm
C
5
5
0
1
1
3
D
4
6
1
0
2
4
E
4
4
1
2
0
3
F
3
3
3
4
3
0
28
Unweighted Pair Group Method with Arithmatic
Mean (UPGMA) (無權重群組算數平均法)
• clustering the pair of plants (operational
taxonomic units/OTUs) with the
smallest distance (and divided by 2)
0.5
0.5
• re-calculating the distance matrix
C
D
A
B
C
D
E
F
A
0
2
5
4
4
3
B
2
0
5
6
4
3
C
5
5
0
1
1
3
D
4
6
1
0
2
4
E
4
4
1
2
0
3
F
3
3
3
4
3
0
A
B
CD
E
F
‒ Dist (A,CD) = [(DistAC + DistAD)]/2 =[(5+4)/2] = 4.5
‒ Dist (B,CD) = [(DistBC + DistBD)]/2 =[(5+6)/2] = 5.5
A
0
2
4.5
4
3
‒ Dist (CD,E) = [(DistCE + DistDE)]/2 =[(1+2)/2] = 1.5
B
2
0
5.5
4
3
‒ Dist (CD,F) = [(DistCF + DistDF)/2] = =[(3+4)/2] = 3.5
CD 4.5 5.5
0
1.5 3.5
E
4
4
1.5
0
3
F
3
3
3.5
3
0
29
Unweighted Pair Group Method with
Arithmatic Mean (UPGMA)
• re-clustering the pair of OTUs with the
smallest distance
1.5/2 = 0.75
• re-calculating the distance matrix
‒ Dist(A,CDE)=[(DistA,CD)+(DistAE)]/2
=[(4.5+4)/2]=4.25
‒ Dist (B,CDE) =[(DistB.CD)+(DistBE)]/2
=[(5.5+4)/2]=4.75
‒ Dist (CDE,F) =[(DistCD.F)+(DistEF)]/2
=[(3.5+3)/2]=3.25
A
B
CD
E
F
A
0
2
4.5
4
3
B
2
0
5.5
4
3
0.75
CD CD 4.5 5.5
0.75
E
E
4
4
F
3
0
3
1.5 3.5
1.5
0
3
3.5
3
0
A
B
CDE
F
A
0
2
4.25
3
B
2
0
4.75
3
0
3.25
3.25
0
CDE 4.25 4.75
F
3
3
30
Unweighted Pair Group Method with
Arithmatic Mean (UPGMA)
• re-clustering the pair of OTUs with the
smallest distance
1
2/2 = 1
1
• re-calculating the distance matrix
A
B
CDE
F
A
A
0
2
4.25
3
B
B
2
0
4.75
3
0
3.25
3
3.25
0
AB
CDE
F
AB
0
4.5
3
CDE
4.5
0
3.25
F
3
3.25
0
CDE 4.25 4.75
F
3
‒ Dist(AB,CDE)=[(DistA,CDE)+(DistB.CDE)]/2
=[(4.25+4.75)/2]=4.5
‒ Dist (AB,F) =[(DistAF)+(DistBF)]/2 =[(3+3)/2]=3
31
Unweighted Pair Group Method with
Arithmatic Mean (UPGMA)
• re-clustering the pair of OTUs with the
smallest distance
3/2 = 1.5
AB
1
1
AB CDE
F
F
AB
CDE
F
0
4.5
3
4.5
0
3.25
3
3.25
0
• re-calculating the distance matrix
‒ Dist(ABF,CDE)=[(DistAB,CDE)+(DistF.CDE)]/2
=[(4.5+3.25)/2]=3.875
C- X. nigra
D- X. purpurea
E- X rubens
F- X. elliptica
A- X. alba
B- X. lutea
2.0
1.5
1.0
0.5
ABF
ABF
CDE
0
3.875
CDE 3.875
0
3.875/2 = 1.9375
0.0
32
C- X. nigra
D- X. purpurea
E- X rubens
F- X. elliptica
A- X. alba
B- X. lutea
2.0
1.5
1.0
0.5
0.0
33
Advantages and pitfalls of phenetic approaches
Easy to operate
Computationally fast
Most alike ≠ most closely related (parallel and convergent evolution;
e.g. Euphorbia vs. cacti)
Aiming for objective, but difficult to achieve
‒ Selection of characters
• Phenetic approaches are now widely used in ecology
34
35
Phylogenetic Systematics/Cladistics (支序學)
• Willi Hennig (German entomologist)
• Hennig recognized the logical consequences of evolutionary
constraint—new structure and functions resulting from modification of
existing ones.
‒ Evolution is recognized as changes from a preexisting ancestral (primitive,
plesiomorphic) condition to a new, derived (advanced, apomorphic) condition.
• Reconstructing history of lineage diversification (cladogensis) by
tracing the character transformation
36
The concept of Characters and Homology
(特徵與同源性)
• Homology (同源性): character shared by a group of organisms or taxa
due to inheritance from a common ancestor.
• Homoplasy (同塑性、非同源相似性): character that appears similar
among a group of organism or taxa, but the similarity is due to parallel
or convergent evolution rather than inheritance from a common
ancestor (wings of bats, birds, flying squirrel, butterflies, etc. .
37
Homoplasy
• Convergent evolution (趨同演化): evolution of similar features
independent in different evolutionary lineages, usually from different
antecedent features or by different development pathways. (e.g., 仙人
掌的刺 vs. 小檗的刺；鳥、蝙蝠、翼手龍的翅膀)
• Parallel evolution (平行演化): the evolution of similar or identical
features independently in related lineage, though usually to be based
on similar modification of the same developmental pathway. (e.g., 寄
生或腐生植物在不同分類群獨立演化)
38
Cladogram (phylogenetic tree)
39
cladogram (支序圖): depicting relationships only
X nigra
X nigra
X purpurea
X purpurea
X rubens
X rubens
X alba
X alba
X lutea
X lutea
Outgroup
Outgroup
perpendicular lines
diagonal lines
Xr
phylogram (譜系圖):
relationships with branch
lengths
s
en
ub
X pu
rpu
rea
Xa
lba
Unrooted tree (無根樹)
X nigra
a
igr
Xn
X purpurea
X rubens
X alba
X lutea
X lu
tea
Outgroup
0.5
Outgroup
0.5
40
Anatomy of Cladistics
1. Monophyletic (Holo-) group (單系/源群)
• Grouping (clade 支序群) includes all descendant taxa and their
common ancestor
• All taxonomic groups (taxa) should be monophyletic.
41
Paraphyletic group (並/側系群)
• Grouping includes an ancestor and some but not all of its descendents
42
Paraphyletic group (並/側系群)
• Grouping includes an ancestor and some but not all of its descendents
43
Monophyly and paraphyly
• Grouping includes an ancestor and some but not all of its descendents
The problem with ranked taxonomy!
44
Angiosperm phylogeny
45
Polyphyletic group (多源群)
• Grouping includes taxa that trace back through two or more separate
ancestors before reaching a common ancestor.
46
Chirita 唇柱苣苔屬, a polyphyletic taxon
47
Cladogram (支序樹), ingroup (內群), sister group (姊妹群),
outgroup (外群)
• Ingroup: focal set of taxa within a monophyletic group.
• Sister group: outgroup that most close to the ingroup
• Outgroup is use to root the tree and provide an ancestor-descendent
orientation of characters.
Additional
outgroups
Sister
outgroups
Ingroups
X
Y
Z
48
葉形
莖
花瓣數目
花瓣顏色
雄蕊數目
花粉表面
X. alba
E
W
5
R
4
Sp
X. Lutea
E
H
5
R
4
Sm
X. Nigra
L
W
4
Y
2
Sm
X. Purpurea
L
W
4
Y
2
Sp
X. Rubens
L
W
4
Y
4
Sm
X. elliptica
Outgroup
E
W
5
Y
5
Sm
E↔L
W↔H
5↔4
Y↔R
5 → 4 → 2 Sp ↔ Sm
49
1
2
3
4
5
6
X. alba
0
0
0
1
1
1
X. lutea
0
1
0
1
1
0
X. nigra
1
0
1
0
2
0
X. purpurea
1
0
1
0
2
1
X. rubens
1
0
1
0
1
0
Outgroup
0
0
0
0
0
0
50
1
2
3
4
5
6
X. alba
0
0
0
1
1
1
X. lutea
0
1
0
1
1
0
X. nigra
1
0
1
0
2
0
X. purpurea
1
0
1
0
2
1
X. rubens
1
0
1
0
1
0
Outgroup
0
0
0
0
0
0
homoplasious character
51
Tree length (樹長) = 8
52
Tree length (樹長) = 8
Tree length (樹長) = 11
53
Parsimony methods
• The goal is to find the most parsimonious tree (MP)
• Parsimony: 檢約、吝嗇
• The criteria are to calculate the changes of character states, i.e. the
evolutionary steps
• First, we have to know the way to evaluate a given tree
54
Molecular (DNA) data
• Molecular data are particular suitable for cladistic analyses
• The number of characters is theoretically unlimited
• Everyone interprets the data in the same way
• Easier to assess homology
• Less subject to selection; independent of the morphological data and
thus can be used to test previous taxonomic hypotheses.
• Better in keeping the signature of the evolutionary history of
organisms
55
Character optimization (特徵最佳化)
Sp_1: TCAGACGATTGTCAGACCATTG
Sp_2: TCAGTCGACTGTCAAACCATTG
Sp_3: TCGGTCAATTGTCAAACGATTG
Sp_4: TCGGTCAATTGTCAAACGATTG
Sp_1 is outgroup. Three different tree topologies.
56
Character optimization: character 3
Sp_1
Sp_2
Sp_3
Sp_4
A
A
G
G
A
2
A
Step=2
G
G
1
A
1
0000000000111111111122
1234567890123456789012
TCAGACGATTGTCAGACCATTG
TCAGTCGACTGTCAAACCATTG
TCGGTCAATTGTCAAACGATTG
TCGGTCAATTGTCAAACGATTG
Step=2
A
G
A
Step=2
3
G
G
G
A
Step=1
A→G
G→A
57
Sp_1
Sp_2
Sp_3
Sp_4
0000000000111111111122
1234567890123456789012
TCAGACGATTGTCAGACCATTG
TCAGTCGACTGTCAAACCATTG
TCGGTCAATTGTCAAACGATTG
TCGGTCAATTGTCAAACGATTG
A
A
A
A
G
Step=2
A
Step=2
A→G
G →A
A
G
G
A
A
Step=2
G
A
A
A
G
Step=2
Step=1
G
G
A←G
G
G
G
A→G
A
G
G
A
Unrooted trees
G
A
Step=1
G
58
Character optimization: character 7
Sp_1
Sp_2
Sp_3
Sp_4
G
G
A
A
G
2
G
Step=2
A
A
1
G
1
0000000000111111111122
1234567890123456789012
TCAGACGATTGTCAGACCATTG
TCAGTCGACTGTCAAACCATTG
TCGGTCAATTGTCAAACGATTG
TCGGTCAATTGTCAAACGATTG
Step=2
G
A
G
Step=2
3
A
A
A
G
Step=1
G→A
A→G
59
2
1
Step=9
3
Step=9
Step=6
Most parsimonious tree
60
How many trees out there are we dealing with?
3 OTUs
Root
1 tree
3 trees
61
Unrooted trees
Rooted trees
15 trees
3 trees
Four taxa
62
How many trees we need to search?
• The number of unrooted trees:
(2n  5)!
Nunrooted  n3
2 (n  3)!
• The number of rooted trees:
(2n  3)!
N rooted  n2
2 (n  2)!
63
Taxon number
All possible unrooted tree number
3
4
5
1
3
15
6
7
8
9
105
945
10,395
135,135
10
11
12
2,027,025
34,459,425
654,729,075
13
14
15
16
13,749,310,575
316,234,143,225
7,905,853,580,625
213,458,046,676,875
17
18
19
6,190,283,353,629,375
191,898,783,962,510,625
6,332,659,870,762,850,625
20
21
221,643,095,476,699,771,875
8,200,794,532,637,891,559,375
22
23
319,830,986,772,877,770,815,625
13,113,070,457,687,988,603,440,625
24
25
563,862,029,680,583,509,947,946,875
25,373,791,335,626,257,947,657,609,375 >1029
-
etc.
64
In real world, how many trees can we search?
• Say a computer can evaluate 106 trees per second.
• If we want to evaluate all of the trees for 25 taxa, we will need
x = 1029/106/60/60/24/365 = 3.17x1015
>三千兆年
• Many ways to get-by this problems
‒ faster computer, software……..
65
Phenetics vs. Cladistics
• Phentics: Algorithm—by defining a specific sequence of steps that
leads to the determination of tree (UPGMA, NJ)—fast and you get one
tree
• Cladistics: Optimality criteria—by defining a (optimal) criterion for
comparing alternative phylogenies to one another and deciding which
is better (parsimony, maximum likelihood, Bayesian)—slow and you
can get many trees
66
Which method is better in reflecting true evolutionary relationship?
Phenogram-UPGMA
Maximum Parsimony Tree
X alba
X lutea
X nigra
Outgroup
X purpurea
X nigra
X rubens
X rubens
Outgroup
2.0 1.5 1.0 0.5 0.0
X purpurea
X alba
X lutea
67
Angiosperm families with nodular nitrogen-fixing symbioses and
the frequency of this association in each family
Prokaryote
Angiosperm family [Genera having root nodules/Approx. total
genera] Bold, family/genus in Taiwan
Rhizobiaceae
Fabaceae 豆科 [530/730]
Cannabaceae 大麻科 (Trema) [1/11]
Frankia
(Actinorhizal
plants, 放線根瘤
植物)
Betulaceae (Alnus) 樺木科 [1/6]
Cassuarinacedae 木麻黃科 (Allocasuarina, Casuarina,
Gymnostoma) [4/4]
Elaeagnaceae 胡頹子科 (Elaeagnus, Hippophae, Shepherdia) [3/3]
Myricaceae 楊梅科 (Morella, Myrica, Comptonia) [2/3]
Rhamnaceae 鼠李科 (Ceanothus, Colletia, Discaria,
Kentrothamnus, Retanilla, Trevoa) [7/55]
Rosaceae 薔薇科 (Cercocarpus, Chamaebatia , Purshia, Dryas)
[5/100]
Datiscaceae 疣柱花科 (Datisca) [1/1]
Coriariacaee 馬桑科 (Coriaria) [1/1]
68
fabids 豆類
Cucurbitales 瓜目
Nitrogen-fixing clade
Fagales 殼斗目
Rosales 薔薇目
Fabales 豆目
Celastrales 衛矛目
Oxalidales 酢醬草目
Malpighiales 黃褥花目
Zygophyllales 蒺藜目
維管束植物約400個科中，僅有分屬於10個科的少數植物在根瘤與固氮細菌共生
具固氮的能力，這10個科在APG的分類中，分屬於瓜目、殼斗目、薔薇目及豆目。
These orders share a genetic predisposition for nitrogen fixation via root nodules, and
this condition represents a possible synapomorphy for this group of four orders.
69
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參考來源：Charles Darwin, On the Origin of Species by Natural Selection, 1859.
3
4
Wikimedia Commons / Author: John Doebley
http://commons.wikimedia.org/wiki/File:Maize-teosinte.jpg，
http://teosinte.wisc.edu/images.html，瀏覽日期：2014/10/13 。本作品採創用CC
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Wikimedia Commons / illustration by Charles Darwin, SVG file by Inductiveload
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2014/10/13 。本作品屬公共領域之著作。
6
“…the view that an
arrangement is only so
far natural as it is
genealogical”
Charles Darwin, On the Origin of Species by Natural Selection, 1859. 本作品屬公
共領域之著作。
7
Organizing
knowledge …be
communicated without a
name.
Christenhusz et al. (2011) Preface to “Linear sequence, classification, synonymy,
and bibliography of vascular plants: Lycophytes, ferns, gymnosperms and
angiosperms” Phytotaxa 19: 4-6.
瀏覽日期：2014/08/23。本作品依據著作權法第 46、52、65 條合理使用。
圖表繪製：國立臺灣大學 鍾國芳
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19
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“Young taxonomists…in
taxonomy theory”
Cain, A.J. (1959) The post-Linnaean development of taxonomy. Proceedings of the
Linnean Society, London, 170, 234–244.本作品依據著作權法第 46、52、65 條
合理使用。
“because of the
subjective
nature …results…”
Mayr, Ernst, Linsley, E. Gorton and Usinger, Robert L. 1953. Methods and
Principles of Systematic Zoology. p. 168; also pp. 176–177. McGraw-Hill. 本作品
依據著作權法第 46、52、65 條合理使用。
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Wikimedia Commons / Author: Petter Bøckman
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