RELATIVES IN SEED ORCHARDS AND
CLONE MIXTURES
A clone deployment and selective harvest model and algorithms
for seed orchards and clonal mixtures.
Lindgren, Dag.(Swedish University of Agricultural Sciences, Sweden),
Danusevicius, Darius. (Lithuanian Forest Research Institute. Lithuania),
Högberg, Karl-Anders. (The Forestry Research Institute of Sweden, Sweden),
Weng, Yuhui. (New Brunswick Dept. of Nat. Resources, Canada),
Hallingbäck, H.R. (Swedish University of Agricultural Sciences, Sweden)
IUFRO conference Seoul August 28, 2010
http://daglindgren.upsc.se/iufro10/
RELATIVES IN SEED ORCHARDS
In advanced generations, avoiding relatives
becomes problematic.
 Relatives may be beneficial.
 Avoidance of relatives becomes costly in gain and
requires structuring breeding populations.
 Seedling seed orchards are common and always
contain relatives, so relatedness occurs in seed
orchards today.
 Natural seeds in natural forests contain matings of
relatives, relatives are normal in nature.

PROS AND CONS ALLOWING RELATIVES
PROS
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Higher gain
More options
More clones can be chosen,
thus less selfing and more
diversity.
CONS
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Inbreeding
Lower diversity at same
clone number
Unrelated clones require
structuring the breeding
population (e.g. many
sublines), which reduces
gain.
GROUP COANCESTRY IS KEY FACTOR!
“Group coancestry” = “Average relatedness”
(large full sib family =0.25)
 Note self-coancestry included
 Effective number = Status number = half the
inverse of group coancestry
 Group coancestry = loss of gene diversity since
breeding started

NET GAIN
net gain   pi BVi  WΘ
i
i  clone (genotype)
pi  deployed proportion
BVi  breeding value
Θ  group coancestry
W  weight (e.g. 1 )
NET GAIN AT GIVEN GROUP COANCESTRY
net gain   pi BVi  WΘ
i
If comparing (maximizing) net gain at
the same group coancestry (status
number) the last term becomes
constant and the weight not needed!
WEIGHT AND INBREEDING
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The weight (W) considers both inbreeding depression and
loss of diversity.
Inbreeding seems generally to be a less important constraint
for relatives than gene diversity.
Self-coancestry (relatedness of clones with themselves) and
Cross-coancestry may be assigned different weights.
Selfing yields few planted seedlings for conifers and
wherefore selfing causes little production loss, while mating
among relatives may give higher production loss.
In results presented here these weighting options has not
been used, but studying weights indicated that inbreeding
was a less important constraint on relatives than gene
diversity.
INVESTIGATED DEPLOYMENT STRATEGIES
Maximizing net gain (optimal selection). By
definition best, but other strategies may be
good enough and simpler.
 Linear deployment (proportions proportional to
breeding value) allowing relatives or restricting
against relatives.
 Truncation selection allowing relatives or
restricting against relatives.

The algorithm is able to optimize
Number of families
 Number of family members
 Number of copies (ramets) of each family
member

Candidate entries can be combined to return
highest net gain (=BV - coancestry)
MAXIMIZING NET GAIN (OPTIMAL SELECTION)
 Individuals are deployed in the proportions maximizing net gain.
feed a computer
Fam1
(”solver” in EXCEL)
Fam2
Fam3
Fam4
Fam5
Results
SHORT LISTING
With many candidates, calculations may
become difficult, uncertain and non
transparent.
 Short-listing the candidates before the final
maximization helps!

APPLICATION: COMPARING STRATEGIES WHEN COMPOSING
A CLONAL SEED ORCHARD FROM UNRELATED HALF-SIBS
Status number = 12, Swedish Scots pine values
Ordered by rank
Optimal proportions
Linear unrelated
Truncation unrelated
Linear related
Truncation related
•“Linear deployment”
restricting against relatives was
good enough if there are more
than double as many unrelated
candidates as needed!
•Other deployment
alternatives were clearly
inferior to optimal!
APPLICATION – ESTABLISHMENT OF NORWAY SPRUCE SEED ORCHARDS
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Deployment was performed for two new Norway spruce seed
orchards in southern Sweden (replacer of current orchards
Runesten and Gälltofta, Finnvid Prescher responsible).
The candidates were tested clones from controlled crosses.
Problem with candidates: Different degree of relatedness, in
particular the best parents are heavily represented in progeny
with high BV!
Breeding value for different characteristics were weighted to get a
value index BV for the selections.
APPLICATION – ESTABLISHMENT OF SEED ORCHARDS
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A shortlist was made with 30 candidates with high BV, but
not sharing the same parent more than 3 times. The shortlisted population status number was 17.5.
Deployment to seed orchard maximizing gain at status
number 13 was made by EXCEL function “Solver”.
Both growth and wood density could be considerably
improved by the optimization procedure.
Cross-coancestry at optimum was 0.01, thus some relatives.
90% (27) of the short-listed clones were deployed in varying
proportions, those selected against would have added much
to relatedness.
Seems the optimum clonal number become higher if some
relatives are selected.
APPLICATION – SELECTIVE HARVEST IN MATURE SEED ORCHARDS
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Harvesting only the best clones become a common praxis in Sweden
as progeny-test results become available and orchards become mature
and produce surplus seeds. There is also a need for two genetic
fractions, the best for plant production and the second for direct
seeding.
The number of ramets per clone often varies considerable, which
increases the demand for suitable tools when genetic thinning is
applied.
Suggestions were made for selective harvest procedures in the mature
Scots pine seed orchards of a Swedish forest company.
APPLICATION – SELECTIVE HARVEST IN MATURE SEED ORCHARDS
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An assumption of pollen contamination 50% was made. Each ramet
was assumed to give the same pollen and seed contribution.
The number of ramets harvested for each clone can be input. Seed
production, genetic gain and gene diversity appear as outputs.
The algorithms made it possible to identify solutions where the clone
representation is heterogeneous and non optimal (due to
establishment constraints or to calamities).
The number of ramets per clone can be optimized maximizing genetic
value for required seed need at a given status number in seed orchard
crop by using the EXCEL function (solver).
Optimizing selective harvest in a seed orchard with very different clone
contributions have the potential to increase both the gain and gene
diversity,
Based on such runs of the relevant worksheet recommendations to the
company was given.
APPLICATION – CLONE MIXTURE FROM BLACK SPRUCE FAMILIES
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To deploy clones to plantations can be made in almost the same way
as for a seed orchard. The penalty for high diversity may be chosen
lower as there is no inbreeding and less concerns with diversity.
This application was planning clone mixtures for New Brunswick,
Canada with tested clones from known families. Figures refers to ten
year volume.
The data was a black spruce clonal test. The trial includes 17 full-sib
families, on average 10 clones per family. These families were created
by crossings among 12 trees.
In New Brunswick where are strict restrictions on clonal mixtures, thus
status number must be high and not relaxed. Only part of an
acceptable clonal mixture could be derived from the material analyzed.
Efficiencies of selection methods
Shortlist:
the top 50 (BV)
clones without restriction on
relatedness.
Trunction
50
Linear
Gain in VOL10 (%)
45
Optimization
40
Optimization
was
considerable superior. At
Ns=5, Optimization gave 9%
larger gain than the
Truncation and 6% larger
than Linear.
35
30
25
20
15
1
2
3
4
5
6
Ns
7
8
9
10
For
Ns=5, Truncation
choose12, while
Optimization 15 and Linear
18 clones.
Effects by restrictions on family contribution
Shortlists can limit the contributions from individual families
Restriction
Clones
Ns=5
Gain
CrossCo
Gain
Ns=8.6
CrossCo
1Clone/Fam
17
37,7
0.022
24.3
0.028
2Clone/Fam
34
37.7
0.025
25.7
0.034
3Clone/Fam
50
37.7
0.027
26.8
0.035
No
50
37.7
0.027
27.1
0.037
For a low status number (Ns) - around half of the maximal - the shortlisted
number per family did not matter for gain, but for a status number near the
maximum, it was beneficial to have some families well-represented.
Cross-Coancestry is relatedness among different clones and was not small (first
cousin =0.0625), thus it can be beneficial to allow some related clones.
END