Morphological analysis of Danube basin Black Poplars. Branislav Kovačević

Transcription

1 Morphological analysis of Danube basin Black Poplars Branislav Kovačević

2 European black poplar (Populus nigra L.) - autochthonous and endangered tree species of riparian zones of Danube basin Variability the basis of the species stability Major threats: decrease of number, size and variability of P. nigra populations and gene flow from cultivated poplars to Populus nigra natural populations Assessment and description of genetic diversity Leaf morphological characters: relatively efficient and affordable

3 Material and methods

4 12 populations of Danube basin Germany: D (DNI) - Donauauwald Neuburg-Ingolstadt Austria: A (NPDA) - Donau-Auen National Park Slovakia: SK (PLADL) - Protected landscape area Dunajské luhy Hungaria: H (DDNP) - Danube-Drava National Park, H (DINP) - Danube Ipoly National Park, H (FHNP) - Fertő-Hanság National Park Croatia: HR (NPLP) - Lonjsko Polje Nature Park, HR (NPKR) - Nature Park Kopacki Rit Serbia: SRB (SNRGP) Special Nature Reserve Gornje Podunavlje Bulgaria: BG (NPRL) - Nature Park Rusenski Lom, BG (PNP) - Persina Nature Park Romania: RO (DDBR) - Danube Delta Biosphere Reserve.

5 30 trees per population, 60 leaves per tree Position of used short shoots Position of sampling leaves

6 8 measured and 4 derived leaf morphometric characters Measured characters according to Krstinic et al. (1998) a - length of the leaf blade (mm) b width of the leaf blade (mm) c length of the leaf petiole (mm) d angle between the first leaf vein and horizontal line ( O ) e width of the leaf blade at the 1 cm from the top (mm) f distance between the base of leaf blade and the widest part of the blade (mm) g length of the whole leaf (leaf blade and petiole) (mm) h number of leaf veins on the left blade side i - number of leaf veins on the right blade side b/a f/a c/b f/b

7 Statistical analysis Descriptive statistics Analysis of variance (Hierarchically nested random design) Multivariate analysis (principal component analysis, discriminative analysis, cluster analysis)

8 Variability and discriminative power of leaf morphometric characters

9 F-test and coefficients of variation Examined characters F between test F within test Cv between Cv within Cv residual a 22,75 30,52 9,01 10,48 14,63 b 13,66 23,14 6,68 10,12 16,31 c 11,06 30,67 7,42 12,69 17,67 d 7,19 42,50 5,34 11,70 13,77 e 8,18 31,11 18,79 38,05 52,57 f 11,99 159,20 18,85 31,27 18,85 g 24,10 28,29 9,80 11,05 16,04 h 82,46 23,36 8,88 5,31 8,52 i 77,15 25,37 8,63 5,35 8,21 b/a 5,43 15,60 4,25 10,78 21,39 f/a 12,46 96,23 7,79 12,62 9,81 c/b 3,32 19,72 3,46 12,19 21,36 f/b 11,41 50,65 20,61 34,89 37,54 All examined characters significantly influenced by differences among and within populations The highest coefficients of variation: e width of the leaf blade at the 1 cm from the top, f - distance between the base of leaf blade and the widest part of the blade and ratio f/b

10 Contribution of examined sources of variation to the total expected variance 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% a b c d e f g h i b/a f/a c/b f/b Between populations Within populations Residual Considerable contribution of differences among populations to the variation of number of leaf veins on the left (h) and right (i) blade side f distance between the base of leaf blade and the widest part of the blade and ratios f/a and f/b considerable influence of variation within populations

11 Correlation between leaf morphometric characters a b c d e f g h i b/a f/a c/b f/b a 1,000 0,859 0,802-0,234-0,682* 0,152 0,928 0,157 0,121-0,655* 0,296 0,034-0,179 b 1,000 0,818-0,545-0,373 0,068 0,846-0,034-0,077-0,182 0,317-0,129-0,289 c 1,000-0,173-0,534 0,243 0,886 0,058 0,026-0,364 0,133 0,456-0,074 d 1,000-0,236 0,115-0,148 0,481 0,485-0,380-0,199 0,527 0,274 e 1,000-0,483-0,723-0,368-0,329 0,754 0,170-0,341-0,299 f 1,000 0,216 0,175 0,170-0,190-0,898 0,394 0,933 g 1,000 0,168 0,106-0,539 0,206 0,214-0,112 h 1,000 0,994-0,322-0,110 0,056 0,138 i 1,000-0,316-0,121 0,065 0,149 b/a 1,000-0,109-0,296-0,078 f/a 1,000-0,345-0,981 c/b 1,000 0,401 f/b 1,000 Some of examined characters expressed considerable collinearity (number of leaf veins (h and i))

12 Relations among examined leaf morphometric characters according to their highest communalities with principal components Examined characters PC1 PC2 PC3 PC4 PC5 PC6 PC7 a 0,774 0,006 0,005 0,008 0,202 0,000 0,003 b 0,927 0,012 0,004 0,036 0,001 0,001 0,014 c 0,838 0,000 0,000 0,149 0,004 0,000 0,007 d 0,122 0,007 0,172 0,216 0,082 0,002 0,398 e 0,252 0,084 0,052 0,015 0,335 0,253 0,006 f 0,043 0,931 0,006 0,009 0,010 0,000 0,000 g 0,863 0,000 0,005 0,007 0,069 0,032 0,003 h 0,003 0,006 0,968 0,000 0,012 0,003 0,007 i 0,000 0,006 0,976 0,001 0,014 0,000 0,001 b/a 0,080 0,000 0,039 0,022 0,848 0,000 0,010 f/a 0,038 0,935 0,003 0,012 0,010 0,001 0,000 c/b 0,011 0,079 0,000 0,883 0,015 0,001 0,011 f/b 0,022 0,946 0,004 0,019 0,006 0,001 0,002 Eigenvalue 3,974 3,010 2,235 1,378 1,608 0,294 0,462 Ratio to the total variance 0,306 0,232 0,172 0,106 0,124 0,023 0,036 Characters are divided in six groups characters within groups highly correlated, among groups weakly In the first group leaf size characters, in second characters based on distance between the base of leaf blade and the widest part of the blade, in the third number of leaf veins on left and right side

13 Discrimination loadings between examined and canonical characters Examined Characters 1) Canonical variable 2) R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 a -0,032 0,668-0,372 0,443 0,114 0,342 0,021-0,203 0,041 0,203 0,058 b -0,090 0,492-0,212 0,275 0,245-0,486-0,031-0,524-0,092 0,085 0,156 c -0,031 0,420-0,061 0,275 0,744-0,022 0,249 0,057-0,175 0,135-0,066 d 0,153-0,059 0,107-0,192 0,255 0,749-0,381-0,003-0,004-0,076 0,156 e -0,082-0,333-0,095-0,255 0,091-0,632-0,447 0,241-0,149-0,112 0,041 f 0,095 0,086 0,417 0,691 0,011 0,073-0,437 0,256 0,114 0,055 0,108 g -0,010 0,789-0,092 0,250 0,341 0,193 0,138 0,017-0,093 0,293-0,142 h 0,831 0,296-0,387 0,023-0,052-0,091 0,106-0,041-0,050-0,036-0,104 i 0,807 0,154-0,451 0,120 0,025-0,038 0,196-0,097-0,113 0,084-0,157 b/a -0,048-0,168 0,149-0,158 0,048-0,794-0,016-0,224-0,360-0,207 0,192 f/a -0,108 0,146-0,538-0,535 0,075 0,063 0,393-0,340-0,022-0,009-0,066 c/b 0,028 0,020 0,157 0,071 0,538 0,376 0,177 0,414-0,184 0,119-0,273 f/b 0,107-0,096 0,477 0,554-0,087 0,195-0,442 0,378 0,092 0,173 0,094 Eigenvalue 3,293 1,071 0,698 0,451 0,193 0,148 0,072 0,059 0,029 0,019 0,004 Cumulative proportion 0,545 0,723 0,838 0,913 0,945 0,970 0,982 0,991 0,996 0,999 1,000 Characters are divided in seven groups The first three canonical characters explain more than 80% of total variation In the first group number of leaf veins characters, in second leaf size characters, in third f/a

14 Percentage of correct allocation according to forward stepwise discrimination analysis h g f/a a i d e b c b/a c/b f/b f The first four characters achieved more than 50% of correct allocation The first three characters representatives of the first three PCA groups (number of leaf veins on left side (h), length of the whole leaf (g), ratio between distance between the base of leaf blade and the widest part of the blade and length of leaf blade (f/a), length of leaf blade (a) Model with all 12 characters achieved 60% of correct allocation

15 Relationship between populations of Populus nigra

16 Relationship among populations based on the first three principal components 2,0 1,5 1,0 0,5 SK(PLADL) D(DNI) H(DINP) H(FHNP) The first three principal components explain more than 70% of total variation Populations Dunajské luhy, Neuburg- Ingolstadt, Fertő-Hanság and Duna Ipoly are considerably apart from the others The populatins of main group distributated along the first principal component FACTOR3 0,0-0,5-1,0 H(DDNP) SRB(SNRGP) BG(NPRL) HR(NPLP) RO(DDBR) HR(NPKR) BG(PNP) 3,5 3,0 2,5 2,0 1,5 FACTOR2 1,0 0,5 0,0-0,5-1,0-1,5 A(NPDA) -2,0-2,0-1,5-1,0-0,5 0,0 0,5 1,0 FACTOR1 1,5 2,0

17 Allocations of trees according to all character discrimination model Populations from which the trees are allocated Percent (Correct) Fertő- Hanság Kopacki rit Lonjsko polje Donau Auen Population by which the discrimination functions are defined Danube Ipoly Danube- Drava Persina Rusenski lom Dunajské luhy Danube delta Neuburg- Ingolstadt Fertő-Hanság 56, Kopacki rit 43, Lonjsko polje 60, Donau Auen 90, Danube-Ipoly 56, Dunav-Drava 63, Persina 64, Rusenski lom 80, Dunajské luhy 30, Danube delta 56, Neuburg-Ingolstadt 90, Gornje Podunavlje 33, Total 60, Gornje Podunavlje The most correct allocation (90%) Donau Auen and Neuberg-Ingolstadt The least correct allocation Dunajské luhy (Danube Ipoly and Gornje Podunavlje) and Gornje Podunavlje (Kopacki rit and Danube Ipoly) Reasons: high variability within population, high similarity between populations

18 Dendrogram of cluster analysis for examined Populus nigra populations Dunajské luhy Danube delta Lonjsko polje Fertő-Hanság Danube Ipoly Squared Euclidian distance, Unweight pair-group average method (UPGMA) of agglomeration According to Scree test five groups defined Neuburg-Ingolstadt Kopacki rit Gornje Podunav lje Danube-Drav a Rusenski lom Donau Auen Persina Linkage Distance

19 Dendrogram of cluster analysis for examined Populus nigra populations alternative standardization with standard deviation within groups (populations) Dunajské luhy Danube delta Lonjsko polje Kopacki rit Danube-Drava According to Scree test five groups defined Danube delta and Lonjsko polje in the Main group Donau Auen separate group Rusenski lom Gornje Podunavlje Persina Fertő-Hanság Danube-Ipoly Neuburg-Ingolstadt Donau Auen Linkage Distance

20 Concluding remarks Neighboring populations are similar (important for restoration) Leaf morphometric characters are useful tool in Populus nigra population studies As discriminative model with all characters achieved just 60,38% of correct allocation it is necessary to include other morphological characters and molecular markers

21 Thank you for your attention