european larch breeding programme in poland - genetyka...

European Larch breeding programme in Poland

Jan Kowalczyk, Jan Matras, Marek Rzońca

Forest Research Institute

Sękocin Stary, Poland

Forest Tree Breeding Conference, Prague, Czech Republic, August 25-29, 2014


Outline

• European larch in Poland – Why Larch? – Distribution – Local circumstances

• Brief history of larch research in Poland • Present state of breeding activities

– Strategic aims – Methods – Results

• Plans for future - expected results


Why Larch?

– Fast growing tree

– Easy to plant

– Visible in the beginning of the grow

– Not seriously affected by pest and disease in Poland

– Durable wood

– Larch is beautiful

0

5

10

15

20

25

0

50

100

150

200

250

300

350

400

450A

rea

of

larc

h [

Ths.

hec

tare

s]

Larch area

% total conifers

[%]

Pâques, L. E. and all. (2013). Forest Tree Breeding in Europe: Current State-of-the-art and Perspectives (Vol. 25). Springer, pp 16.


Local circumstances

– Distribution is scattered

– Natural distribution– how it influence the practical utilization now?

– Larch was/is often planted

– Seeds was moved and also Japanese larch was introduced

– Hybrids !!! (vigorous grow – quality and performance of future generations)

Brief history of larch research in Poland

IUFR

O 1

94

4

IUFRO 1957

Lub

awka 1

93

2

Ro

gów

19

49

SSO 1

19

66

IBL 1

96

7

IBL 2

00

0

INR

A 2

00

3

Den

dro

Gen

1940 1930 2000 1970

18 provenances 10 from Sudeten 8 form Alps

23 provenances from Poland—6 trials located in all Poland

Kolanów1946 48 provenances from 4 sub area

4 provenances 3 from Polish Lowlands and 1 Sudeten (standard)

20 half sib familes from Świętokrzyskie Mt.

157 half sib families from Świętokrzyskie Mt. 2 trials in Poland and 3 in France (IBL—INRA collection)

67 half sib families from Jesiennik region 1 trials in Poland and 2 in France, 2 in Czech, 2 in Belgium (INRA series)

Several SSO in different age located in all Poland more then 600 half sib families

Kulej M. 2013

Breeding value families tested in Zwierzyniec

-2,00

-1,50

-1,00

-0,50

0,00

0,50

1,00

1,50

1730

1387

1857

1417

1702

1849

1402

1413

1419

1397

1408

1391

1420

1400

1394

1405

1418

1421

1388

1851

1396

1410

DBH

Stem straightness

BV

Families


Conclusions from research

• The large differences in the grow of the population was observed even in a relatively small area

• The regions of occurrence of larch Polish and the Sudeten may be regarded as homogeneous areas.

• For this reason, the breeding of larch have to be conducted primarily at the level of particular seed sources (forest stands, families)


Breeding programme

Classical low intensive

Seed stands

Plus tree selection

Classical

Progeny testing

Backward selection

Improvements

• As regards the indigenous European larch, there occurs locally an ‘infestation’ of the gene pool with genes from Japanese larch, in view of the easy crossing of these two species, and this leads to an erosion of the genome of the indigenous species. For this reason it is particularly important to take note of the species purity of the seed bases proposed for confirmation. The existing stands of Japanese larch and of hybrid ones in the vicinity of the populations selected and qualified as basic seed material should be successively removed.

Program … for years 2011-2035

Demand for seed of European larch according to felling requests

0

200

400

600

800

1000

1200

1400

1600

2001 2002 2003 2004 2005 2006 2007 2008 2009

[kg]

Year

Larch seed sources in Poland

Seed sources Number Area [ha] % to all conifers

Selected stands (reserved seed stands)

82 445 4

Plus trees 966 15

Seedling seed orchards 24 172 30

Seed orchards 38 247 30

Scheme of forest tree breeding in Poland

The scheme of realization of the breeding strategy

Intensive breeding

• It is planned to establish breeding populations in the Sudety and in the Świętokrzyskie Mountains. When choosing the initial material use should be made of the existing plus trees and the results of progeny trials. It is recommended to conduct the breeding program in international cooperation with such countries as the Czech Republic and France.

Program … for years 2011-2035

Cel pracy

Seminarium Zakładowe, Sękocin, 4 III 2014

Aims

• Estimation of breeding value half sib families grooving on SSO

• Selecting the best family (tested)

• Creation of SO 1.5 generation and clonal archive (backward selection method)

• Establishing new breeding population

SSO

Plus trees

Forests Seed regions

European larch SSO and plus trees


Seed transfer

rules

Local circumsta-

nces

Technical aspects,

Time

Cost

Seed demand

Analyses

Condition of trials and

minimum n. of trees per family

Existing low

SO 1.5 gen Existing infrastructure (trial, SSO)

Inwentaryzacja PUN i doświadczeń rodowych


SSO 1

SSO 68

SSO 46

SSO 89

SSO 90 SSO 67


1 46 67 68 89 90

Plantation year

1966 1992 1996 1996 2001 2001

Number of trees

4000 1911 1669 3784 1837 1849

Number of families

20 36 42 52 67 97

Area [ha] 7,2 12,1 5,3 14,8 5,2 5,1

Studied SSO description

Skala oceny prostości strzały


1 2 3 4 5

Stem straightens


1 2 3 4 5

1 2 3 4 5

Crown widths and branch angle

1. Data cleaning

2. Removing extremes – ( 3SD<x<3SD)

3. Calculation for each trials – variance i BV for features

4. Stand arising data

5. Summary index

6. Selection the best families – SO 1.5 generation

7. Calculation BV for single tree

8. Choosing the best trees for crossing


Recepture

Wyniki – pierśnica dla PUN: 1, 41, 46, 69


1

46

Przykładowe zróżnicowanie dla PUN1

> summary(DBH.aov<- aov(DBH~Family+Family*Block, data=plik))

Df Sum Sq Mean Sq F value Pr(>F)

Family 19 341628 17980 5.614 3.61e-13 ***

Block 9 134645 14961 4.671 4.77e-06 ***

Family:Block 171 520657 3045 0.951 0.654

Residuals 764 2446870 3203

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


TUKEY TEST TO COMPARE MEANS Confidence level: 0.95 Dependent variable: DBH Variation Coefficient: 13.60573 % Independent variable: Family Factors Means 5p 453.657407407407 a 7p 443.820754716981 ab 1p 442.84 ab 11p 439.244680851064 abc 4p 424.722222222222 abcd 19 422.96511627907 abcd 18p 422.798076923077 abcd 15 422.518867924528 abcd 6 415.840425531915 abcd 13 413.795454545455 abcd 17p 413.539215686275 abcd 14p 413.142857142857 abcd 20p 409.48 bcd 16 404.076923076923 bcd 3 399.25 cd 2 395.878048780488 d 10 394.7 d 9p 394.031914893617 d 12p 391.12037037037 d 8 384.776315789474 d

Independent variable: Block Factors Means 10 434.021739130435 a 3 426.572222222222 a 8 424.833333333333 a 5 421.016304347826 ab 9 420.103092783505 abc 4 414.651685393258 abc 7 414.556701030928 abc 2 414.546391752577 abc 1 395.775510204082 bc 6 395.024752475248 c

Tytuł slajdu


> summary(m.lm) Linear mixed model fit by REML ['lmerMod'] Formula: DBH ~ Block + (1 | Family) Data: plik REML criterion at convergence: 10477.41 Random effects: Groups Name Variance Std.Dev. Family (Intercept) 303 17.41 Residual 3174 56.34 Number of obs: 964, groups: Family, 20 Fixed effects: Estimate Std. Error t value (Intercept) 396.096 6.899 57.41 Block2 17.838 8.074 2.21 Block3 28.941 8.243 3.51 Block4 18.039 8.258 2.18 Block5 25.017 8.190 3.05 Block6 -1.838 8.007 -0.23 Block7 16.474 8.083 2.04 Block8 28.522 7.838 3.64 Block9 22.991 8.087 2.84 Block10 37.732 8.197 4.60 > 4*303/(303+3174) [1] 0.3485764

> ranef(m.lm, level=1) $Family (Intercept) 10 -15.1567705 11p 20.1488115 12p -21.5872893 13 -0.2192024 14p -3.2430080 15 5.9509466 16 -7.9591342 17p -3.3589419 18p 6.6019899 19 6.0476027 1p 22.4833640 2 -15.6581160 20p -5.0588889 3 -13.3290967 4p 8.7460731 5p 31.7171197 6 0.1086741 7p 23.6306150 8 -23.6215560 9p -16.2431928

Wyniki – najlepsze rody


site Reg fam ind_me

an

h_perc d_perc str_perc cro_per

c

89 604 1845 1.63 3.67 7.00 1.76 -4.16

90 604 1845 1.63 3.66 3.51 -1.06 -1.34

70 852 684 1.57 16.82 7.24 12.47 7.37

89 604 7006 1.54 0.72 0.33 1.91 0.40

90 604 7006 1.54 3.52 1.99 0.63 -1.13

89 604 1833 1.47 3.69 4.48 1.45 -0.48

90 604 1833 1.47 -0.13 1.88 0.64 1.22

89 604 7696 1.44 2.65 4.27 0.63 -0.58

90 604 7696 1.44 1.38 2.43 0.71 1.78

1 604 5p 1.42 6.09 14.90 -5.32 -20.87

70 852 647 1.35 8.71 4.42 14.50 3.72

89 604 1837 1.32 2.49 0.85 0.44 2.54

90 604 1837 1.32 2.84 4.02 -0.31 -3.48

69 803 601 1.29 12.58 26.49 13.53 -12.16

89 604 1826 1.27 -3.28 -8.36 0.88 7.26

90 604 1826 1.27 2.66 2.79 1.03 11.67

70 852 673 1.25 24.50 23.11 6.77 -8.44

89 604 7017 1.22 3.69 5.14 0.56 0.12

90 604 7017 1.22 0.80 0.17 0.43 0.66

41 803 624 1.05 11.42 17.85 -1.28 -5.86

69 803 624 1.05 11.88 7.68 8.25 7.70

89 604 1849 1.02 2.38 2.12 0.74 0.34

90 604 1849 1.02 -0.08 1.78 0.75 -0.22

Index=1.25*H_BV + DBH_BV

+str_BV + crown_BV

Zysk w % - efekt selekcji


SSO h_effect d_effect str_effect cro_effect

1 3.78 11.94 2.50 -11.10

41 6.90 8.68 5.97 -2.38

69 12.79 15.68 4.37 -0.58

Average 7,8 12,1 4,3 -4,7


• It is reasonable to choose the best families to establish SO 1.5 generation – we know what we get

• Selection priorities - growth and quality • Not take into account the characteristics of wood in the

selection - task for the future? • We do not include survival • Not take into account the reaction to action of biotic and

abiotic • SSO has a specific history and it affects the interpretation of

the results - necessity more digging in data • The average gain for DBH - 12% for straightness 4%, crown

width -4%

Summary - conclusions


1. Research is conduced by - dendrogen.pl

• IBL, IDPAN, UP Poznań, UR Kraków, SGGW

• UAM Poznań, ID PAN, UKW

2. The grant is funded by State Forest – BLP 397 (2013- 2017)

3. Thank you for my coauthors

• – Jan Matras , Marek Rzońca

• Technical staf– Jerzy Przyborowski, Marek Rzońca,

Marcin Konieczyński, Danuta Pieniążkiewicz, Tomasz Wojda, Paweł Przybylski,

Władysław Kantorowicz

european larch breeding programme in poland - genetyka...

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