uv•""
roeen.ng on AdVan,md Gmu•mtion 8r<?eding, 8oPdmiux-June
SESSION
14-18, 1976
4
THE IMPACT OF GENOTYPE-ENVIRONMENT INTERACTIONS
ON TREE IMPROVEMENT STRATEGY
C .J A SHELBOURNE
Fo1tut Ruea1tc.h 111.6.tU:ute
ROTORUA , New . Z eai.a.nd
.
.
. R.K. CAMPBELL
FD!tu:tli.y Sc.ienc.u Labo
CORVALLIS, OREGON, USA
1
2
1ty
ABSTRACT
- .
. · .. -
::,.'"
'
Genotype-environment interactions affect tree imorovement
strategy in two main ways; environments must be grouped into
breeding or plantation zones within which there are minimal
interactions both of provenance and individual genotype with
sites;
secondl well adapted pooulations and genotypes must
be selected for high and also stable performance.
At the
provenance level the variation between provenances usually .
shows some coherent pattern based on latitudinal and altitudinal
clines which can form the basis of provenance transfer models.
Interactions at the genotype level are likely to be much less
predictable and an empirical statistical approach is necessary
to elucidate them.
Characterisin environments for their
interactive behaviour with populations (or genotypes) is likely
to be a more useful strategy than the reverse. for tree
improvement as this will facilitate the grouping of environments
i·t
tes which give best resolution of
into zones and ident±
genetic differenc .
-
"!
Key words ·
Genotype-environment interaction,
of environments Author of sections I,III,
1
:
2
: Author of section
II
stability, grouping .INTRODUCTION
.
The selection of populations and genotypes that are well
adanted and high vielding wherever they are planted, with
superior tree f rm and wood nronerties, is the objective of most
tree improvement programmes.
This selection is hindered by.
genotyne - environment interaction which results in different
performance rankinRs of nopulations or genotypes in different
environments.
Almost any comnonentl!lof the environment may
interact with genotype;
the e will include soil, climRte,
photoperiod, nutrition, competition, diseases and nests, and
cultural effects.
In an earlier review of GE interactions in tree improvement
Shelbourne, (1972) emphasised that ther are two important prob­
lems, or tasks related to the effects of GE interactions on
improvement strategy.
The first is to predict which sites and
environmental factors are giving rise to interactions so that
these can be grouped into breeding regions of minimal inter­
action.
The second is to select populations and genotypes for
these different strata that are well adanted and grow fast on
all sites.
For individual g enotypes this task recurs, and it
will be necessar to select and mat e parents and raise pedigreed
offspring each generation.
Once the first problem is at least
partly solved it should be possible to identify a limited number
of sites within regions that give the best resolution of genetic
differences.
If ever a problem was over-researched, then genotype-environ­
ment interaction· must be itl
It is perhaps because .GE
interactions were particularly frustrating to the crop breeder
that attention was turned on the statistical aspect, but
subsequently it seems to have developed an academic fascination
of its own for numerous workers.
In an excellent review of
the statistical methodology, Freeman (1973) cited 96 references
on this asnect alone.
Other reviews of statistical, quantitative
genetic and ·breeding aspects of GE interactions have been made by
Comstock and Moll (1963), Moll and Stuber (1974) and Allard and
Bradshaw (1964).
·
In forest tree breedin"• general reviews of GE interactions
Zobel
have been made by Squillace (1970) and Shelbourne (1972).
and Roberds (1970) reviewed examples of family x fertiliser
interaction in tree breeding.
Wright (1973) summarised the
results of mainly provenance-site interactions in the north-central
USA and Burley and Kemp (1972) discussed the GE interaction
problems in international tropical provenance trials.
Many problems with GE interactions at the population
(provenance) and individual levels are similar, but there are
some important differences,
Provenance effects in a provenance
trial may be regarded as fixed, or if they are susceptible to
random samplinf< thev may show some coherent. pattern such as
latitudinal and altitudinal clin es which can form the basis of
provenance seed transfer models.
Individuals within a population
however are a ranOom collection and environmental factors
interactin with in i.vidual penotvpes may nr may not be fixed.
Jiowever their interactions are often unnredictahle and an
empirical statirtienl RnTiroach to their intPr r tetion is u eful.
- 74 -
There are a l so difference s in the notential solution o f GE
interaction problems between exotic and indigenous tree spe cie s .
The d e ve l opment o f nrnvenance tra n sf e r m o de l s a r e o n l y norma l l y
applicab l e t o n ative specie s .
I n e xotic snecie s the hand ling
o f provenRnce-site interacti n s·is more o ften o n ly possib l e
through the empirical statistical approach.
.
'
In Section II of this paper a hypothe tica l ca se for a
na tive specie s is used to illu strate t e r e l ation of nrovenance
ad antatinn and GE interactio n .
The caE>e is then e xte nd e d to
the orob le
of de v e l o pin an e f f e ctive improvement strategy for
prove nance s e l e ction u z::inp: predetermined b re e d in zone s , in
both native a n d e xotic soe cie s.
Wherea s it i s r e l ative ly e a sy
to d e l imit b r e e d ing z o n e s ·for native spe cie s , o n a priori
ground s the task is imme n se l y complicated fo r e xotics, or f o r
n ative spe cie s in forest regions whe re origin o f present s ta n d s
is u n known .
The third section e xam ine s recent d e ve lopments in
GE inte raction methodology; mainly from the plan t bre e d ing
lite ratu re .
Empha siz e d a re statistical m e t o d s fo r devising
b re e d in g zone s or for m atchin genotype s to site s , mainly in
regions where little o r no a priori informa tion e xists about
adapta tion of the rele vant populatio n s or of potential inte rac­
tio n s with habitat facto r s .
Thu s , these m e thod s a re e specially
pertin e n t f or e xotics.
In the final two sectio n s , genotype­
site inte raction is d iscu ssed with m ain e mphasis o n its de tection
in progeny a nd clona l e xperiments and its han d l in g in the tree
b re e d in g conte xt .
II .
_-,
PROVENANCE-SITE ADAPTATION
In this Rection we d i cuss, first, the re lation between
provenance a daptation and GE inte raction an d , secon_d , the
initial steps in a b r e e d ing strategy which recognizes pote ntial
e f fe cts o f ad aptation .
Before di sc11 ssing the re la tio n shi'P o f
provena nce-site ad aptatio n a n d provenance -site inte ractio n , some
common u n d e r standing o f termF is n e ce ssary .
Based on Knirht's
( 1 970) argu :ne n t s , we assume that GE inte raction s re su l t b ecau se
genotype s have different resnonse.curves f o r the
ul tinlicity
o f factors that constitute "environments".
Conse q u e ntly, we will
Figure 1 a
illu strate this discussion wi th re sponse curve s .
pre sents a set o f hypnthetical, b u t b y n o means improbable trait
re sponse curves f or l o w ,
id d l e a n d high e le vation popul atio n s
Curve s
from a single mou ntain slone ( se e Fryer & Ledig 1 972 ) .
are constructed from ponu lation ave rage s and measure a
quan titative trait re sponEe ( e .g. , pho to synthetic C0 uptake)
2
over a quantitative shift in some environmenta l component (e.r,.,
( temperature ) .
Gene tic variation b e twe e n tre e s within source s,
as d e te rm inP.d in each o f three e nvironmP.nts A , B, C, is ind ica ted
by be ll-sha ped c11rve s which re pre sent frequency d iFtrib11tio ns of
indivirlual-Fenotvpe resnonre curveF sR ole d Rt e n v i ron e nta l
points A, B, c.
lndivirJ ial reRponse curvP.s mav be parallel to
the population avPra17e re sponr;e curve, but thif; se e m s unlikely.
·
.
- 75 -
--'
The concert o
adaptation· used here
In preparation)
elcewhere--Campbell,
· pron
E"trateg,y for
strategy ir.
allocciti.on of tr.e nurvival re ources available to a
Levins identifies polymorphism as the optimum
a heteroge eous
Oifferent
mentE are very
plant genotype,
resulting
and the
on e of
&urvivinr tree
·,
envir nment,
when
c mpared to the
alternative Pr.viron­
la ticity of a single.
environment iF. coarse grained.
"adapted" pol;'lulation is a mixture of types,
F>!lecialized t11
in
(1969)
on Levins'
fial that natura.l selection tends to produce an opti
" mum.
population.
of
(discussed more fully
iF baserl
i.e.,
envi }onm n t
The greater
the
types
po s Rible environmPnte.:..
change
in a continuous
the nrobahilit:v of' ::i!'l
i,
the
environment,
the l.arger the
in
fro
ace and
time.
Proportion of noMdapted seedlings
from one location to another.
Th.i s concept lead" to a 1uantitative indeY
re ult
hanres
with
between l"cetions in terms of average
distance
useful in regions where fore!';t
stands
roporti.on
The
way
organiE>:m finding itself in
where envirnnmente are meae11red
hen tranefP-rs are made
The
each
of adaptation
.f-pecies are iniiigenous and parent
natural reger!eration.
Three
furtl'"_er assump­
tions are r.eed e d.
1.
At maturity,
or natural
selection,
each
and
tree has survived from
i te parents are,
reVious generations of selection at that
trees
types i
location.
envi.ronmental typeF: at a location.
nrorortional tn
2.
Thus,
the ran e of
possible
response di ferences amon
decades
Surv ving
The mixture of
environments.
survivinr. trees nefine
relative proportions of poF ible environment ,
3.
50
survivors of
the mixture of types specialized each to one of
repre se nt
the possible
5 to
in turn,
i.e.,
the £ •
i
Frequencies of adaoted types and corresnonding environ­
ments are normally
distributed
population ·reFpon<e ano
and
can
be estimated by the mean
within-nopulation adnitive
genetic
variance.
Using these
assumntionF,
ability of a seP.d]inr findinr
it is adapte
by optimum
(Fi ure
1a)
indic te
hi h elevRtion ponulation n t
As meai=>ured hy trait a
vA.tion
popul tion
w ereas,
ie
the cross-hatched area in bell­
the proportion of seedlin s o
a anted to middle elev tion
in P'1Virnnment.s A anr.
Onl•:
C,
the
low
the
sites.
•ni. ri1e e]e­
;:!rtl:v ad81"ted t,-, hi,r:h elevations,
in env ro ment B it is comDletely adapted.
teFt environmentB,
prob­
itFelf in an environment t, which
str?tegy.
Bv the above definition,
curves
the index is defined as the
el. evatinn
nopul
middle and hir,h elevatior. .
- 76 -
In all
tionF are nonada ted to
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HIGH
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A
B
c
ENVIRONMENTAL
FIGURE 1a,
Trait
a
A
-
I
I !
- --1m
,9
---
c
COMPONENT
FIGURE 1b,
Trait b
Resnon e curves or low, mid and high altitude prove
nances to changes in environment (A,
B, & C)
, lj
In terms of trait a, middle and high elevation populations
tested in environments A and B, or B and C, would show provenance
if tested
differences and provenance-environment interactions;
in A, B and c, si nificant interaction, but no provenance
differences.
Similar tests of low and middle elevation
populations would show provenance differences but no interactions.
In a test of trait b measured in environments A, B, and C,
there would be large between-population differences, but no
poPulation-environment interaction (Figure 1b).
Nonadapted
seedlinp-s in seed transfers from high to middle elevations would
be Predicted to be fewer than for trait a, due to large within­
pop lation variations compared to between-populAtion diffe-rences.
-
..
:·f
-
-
_,
·<
:::::;
..
·Provenance-environment interaction arises becallse rrovenance
response curves produce average trait effects that differ between
Provenances depending on the test environment.
To the degree
that curves for individual trees are parallel to the average curve
for their provenance, interaction at the genotypic level will
reflect provenance-environment interaction.
Genotype-environment
interactions will be minimised in sets of environments that
eliminate provenance-site interactions
Provenance-site interaction, and adaptation, both influence
genetic gain.
This is illustrated in Figures 1a and b.
If
environments A and C represent high and middle elevation
conditions, respectively and an incorrectly delimited breeding
zone is large enough to include individuals (and environments)
from high and middle elevation - populations, selection for trait
a (Figure 1a) is ineffective, because the reversal of superiority
of each population at mid and high elevation sites makes it
impossible to select a single best population at both sites.
In a te·st for trait b in the same two populations at
environments A and C, individuals selected for high response would
come almost exclusively from the middle elevation provenance.
On the surface this test is highly effective--parallel response
curves indicate little or no GE interaction.
But in this case
gain from directed selection in the long term is likely to be
partly offset by natural selection, because middle e levation
individuals are generally not adapted to environment A and may
not survive the r igours of the high elevation site.
The situation described for the hypothetical trait b
apparently happens quite commonly, in fact, for growth traits.
Sources from ood sites often are vegetatively more vigorous
than sources from poor sites, even when growinR on poorer sites
(Wells and Wakely 1970).
This superiority may persiBt, but
fast-growing rovenances occasionally succumb to disease
(Dietrichson 1968) or some unmeasured factor, sometimes after
- 78 -
Lack
several decane
of anDarently normal gro1.1;t.., (Silen 1964).
of
enotvpe-environment interaction, es eciaJly in early tP.sts
. n-.
fnr :vield, does nnt hecessaril:v p.:unrant.ee adequate adapta i.o
There are two rrrycedurP.s t at can minimise th
ri ks of
selecting poorly adanted ?rovenances.
The first involves a
selectio!1 method '"hich chooses nopulationr- or arents based on an
ada tive trait (Auch as h11rl-burst timing, or some other develop­
mental-cycle trait) as well as on growth (Dietrichson 1969, Holzer
1969;.Nienstaedt & King 1969, Tiech & HolPt 1969, Hagner 1970,
This method implies using a selection index
Lacaze & Polge 1970).
includinp: both adaptive and growth traits.
.---T"-'
·-· -�.:
The second method is to stratify ·the species distribution
into plantation zones within which there are minimal adantational
problems.
The. zones
must first be delineated and then
breeding populations selected for the zones.
Delineating of
zones using climati geoy,ranhic and ecolo icRl information is
feasible for indi enous suecies.
Zonation for exotics should be
based on results of provenance experiments.
Methods for
delineating nlantation zones objectively have received little
attention.
Related studies deal primarily with geographic
variatior., often with mention of potential effects of transfer.
Some authors (Morgenstern & Roche 1969, Campbell 1974a) treat
specifically the question of seed transfer anrl provide models for
predicting transfer effects.
A few (e.g. Langlet 1945, 1957;
Kleinschmit et. al 1974) address the nroblem of
Rehfeldt 1974a;
boundaries which are essential to the concept of zone.
Very few
(Eneroth 1926, Langlet 1957, Namkoonr. 1967, Campbell 1974b)
provide for quantitative assessment of risk, a necessity for
evaluatinr, transfer effects or for objectively deciding on zone
dimensions.
These latter have used survival ·perce:itages as risk
fA.Ct:')rs though adautive differe-nces amonr. nopulationl"\ 'Tl.:::i.v not be
reflecterl as survival differences until tests arP. fairly old
(compare Eiche 1066 with Eiche and GurtafsFon 1o70;
Dietrichson
1q6 ).
Therefore, for mild areas, a more sensitive and earlier
indicator of adaptation is nee ed.
Also, for delin ating zones,
a short-term test, though less conclusive than lonr,-term test·s,
has many advantages.
A short-term method which is modified slightlv from
nronosed by Stern·(1964) and Morgenstern and Roche (1069)
estimetes of relRtive risk to determine zone boundaries.
odels
uti ises
The first FteP in developing a trR.nsfer morl.el is to quanti ta­
tively de cribe the complex clinal uattern in the recies and
region of intereEt.
The equation deFcribin
the clin
can he
as comnlex as ir necesFarv to e plain Prove ance VAriati,n in the
trait of intere t (i) a t B- Joc tion (z), e.p:., a. f:e co n r. orrier
f'ln1ynomia :
- 79 -
b
-o
where, e. g. , x
x
1
2
=
latitude of
=
elevation of
z
z
and b's are established by experiment.
Provenance means for the trait can be then calculated for
Y. 1 , the moved Provenance, and Y. , the local provenance, by
a?t ostituting apnropriah latituQ_ 2
s · and altitudes for the two
locations.
With estimates ttf within-population genetic variance
in trait i, a risk factor associated with transferring seed from
location 1 to 2 can be calculated as the proportion of nonadapted
seedlings (i. e. proportion of deaths).
A similarly constructed model mil'"ht be used for assigning
provenances of exotics.
This is less satisfactory than for
indigenous species because a newly introduced species has not
been subjected to natural selection in the "new" environment.
;-:;:
When a satisfactory . transfer equation has been developed and
an estimate of within-population genetic variance is available a
maximum· death rate of nonadapted seedlings (the risk factor)
that can be accepted in transfers from one boundary of a breeding
zone to the other must then be ch.osen.
This sets the upner limit
to risks of maladaptation within the zone,
A difference (d)
between pairs of population means (Y.) that provides this factor
1
Then an array of Y's is chosen so as to
can then be calculated.
reflect this difference (Y ; Y = Y + d; Y3 = Y + 2d; Y =
4
1
2
1
1
Y + 3d; etc.).
1
By using· these Y's as constants and by solving the transfer
equation for appropriate sets of X's, isograms for each Y can be
calculated and nlotted on topographic or climatic maps for the
regio in question, Isograms provide boundaries for zones.
Boundaries are functions of the environments that have been
operational in natural selection and of the risk factor.
Difficulties encountered in delineating zones stem mainly
from problems in developing a transfer equation.
The first dif­
ficulty is in describing clines and arises becauae different traits
have, different response _curves;
clines depend on the trait
measured a well as on the test environment (e. g. Scots pine
(King 1965), white fir (Hamrick & Libby 1972) , Douglas-fir
(Campbell & SorenEen , in preparation). )
- 80 -
Choice of traits to measure adaptation is not likely to
Traits can also be combined by several
cause serious roblems.
multivariate methods (Namkoong 1967, Morgenstern 1969, Hagner 1970,
Rem1lting variates, e.g., from principle
Rehfeldt 1974b).
com?onent analysis, can be used in transfer models.
The oroblem of choosing an appropriate set of test environ­
ments has not been s riously examined for tree species.
Possible
solutions are discussed in Section III.
-
·-""
.
--.-
·-
·<
Another ?roblem iF to achieve the necessary precision in the
transfer equation.
The main difficulty is to discover and include
in the equation all relevant variables.
In coastal Douglas-fir,
genetic differentiation amonp- sources is associated ·.,ith sub­
regional effects of aspect (Hermann & Lavender 1968) and drainage
pattern (Campbell, in preparation) as well as regional effects of
latitude, elevation and distance from the ocean (Campbell and
Sorensen, in preparation).
Devising equations for regions where
climates are more severe and more locally variable than in the
A suggested
Pacific Northwest may be even more complicated.
alternative to zones based on a clinal transfer model has been to
delineate zones according to vegetative habitat type (Rehfeldt
1974a).
A further problem is that the use of adaptation (survival
nercent) to define a risk factor may not be completely realistic
in the context of artificial regeneration where environments in
relation to the natural condition may he made milder (Schober 1963)
or harsher (Eiche 1966).
In the first case, populations within
the breeding zone might not be as vegetatively vigorous as would
be optimal (Namkoong 1969).
In the second, the local population
may not be sufficiently hardy (Campbell 1974b).
--· --
After breeding zones have been established, the breeder must
next choose provenances or breeding populations for each zone.
In this process, several traneoffs can be expected among plant­
ation-zone size, and stability and productivity in the breeding
opulation.
We can expect that trees from near the severe
boundary of a zone (higher elevation or farther north) will be
more harrly and less vegetatively luxuriant than tho e from the
mild boundary (Kiellander 1966, Eriksson 1972, Eiche & Anderson
1974).
To increase growth, we therefore should choose trees
from the mild boundary as our breeding population or seed source;
the wider the zone the p:reater the potential average increase
in growth.
Stability of the individual genotynes is decreased as zone
size is increased becau e resnonFe curves are likely to become
There­
more dispar,i:ite as populationn diverge, on the averar-e.
fore, p;enotypes frnm Fubnopuia tions in the center of the zone
should be more stahl" thRn from subpopulations at the edges.
- 81
-
-
-
--.-.------
----
Crossing of provenances has been surgested to break up co-adaoted gene c0mplexes and thereby .increase stability by p:enotyuic and populat.ional buffering.
This is a risky nrocedure, because, as Libby (1968) notes, a new taxon is created.
In this case, long-term tests, uerhaps for more A
than one rotation, are needed to· assess adaptation.
compara le effort might better be used to find those rare natural nrovenances that seem to combine adaptability a.nd productivity (Eiche & Andersson 1974). III.
•
•
-
..
-
ii
···i
STATISTICAL MBTHODS FOR HANDLING GE INTERACTIONS
Most of the plant breeding literature on GE interaction has
been directed to the task of making interactions more nredictable
in agricultural
for individual plant varieties or f.enotypes;
The
crous these are usually exotic to the cultivation region.
most useful method has been the joint regression procedure
developed by Finlay and Wilkinson C1963) furt'ier improved by
Eberhardt and Russell (1966), and genetically analyzed by
Bucio Alanis (1966) and Perkins and Jinks (1969).
Its use in
the context of tree breeding was reviewed by Shelbourne ( 1 g72).
The regression method characterizes varietal stability by
uoinR the mean of all genetic entries to measure average environ­
ment at a site.
Because of this it has been attacked on
statistical and theoretical grounds (Knight 1970).
nowever,
it is generally recognized that the procedure has few practical
disadvantages, provided the test includes a good sample of
genotvpes.
In com arison, Wricke's (1962) "Ecovalance", which
uses the contribution of the interaction sums of equares to
also ·measure e:tabilitv, has not proved so successful in practice
(Morgenstern and Teich 1969).
Tai (1971) used structural
relationship analysis as an alternative method for circumventing
the statistical objections to joint regressinn.
Provided orthngonal comparisons are possible for genetic
entries planted on representative sites, then selection for
stability and performance is simply a matter of selecting entries
that rank hiizhest on overall arithmetic means.
Where different
sites and different sets of entries are involved it may be
advantageous to compute a Predicted mean for each genetic entry,
based on its regression on the mean of all entries at each site
(Pinthus, 1973;
Pederson, 1 974 ),
- 82
-
Rather few attempts have been made to tackle the GE interaction
nroblem at the other end, so to speak, by characterizing environ­
Horner and
ments according to their contribution to interaction.
Frey (1957) attempte d to divide the State of Iowa into sub-regions
for oat varie ties which had minimum intra-re gional variety x site
interactions.
Abou-el-Fittough e t al. (1969) examine d existing
re gions for cotton varieties in the southern USA which had been
define d by a subje ctive evaluation of the mean differences in certain
e nvironmental factors thought to be important.
They compared
corre lation and distance coefficients as measures of similarity in
performance of varieties at different pairs of sites.
Cluster
analysis was then used to group environments using each me asure of
similarity (for all possible pairs of sites).
For clustering,
distance coefficients proved slightly more effective than corre­
lation coefficients.
The e xperiment resulted in-a ne w zoning
syste m expected to re duce variety x location interaction within
regions by about half.
",__.,.
¥!
-
:. .·' - .t:.::
-
- ..:,;
Other authors have used correlations of genetic e ntry means
be twe e n pairs of environme nts as a means of grouping environments.
Stuber e t al. (1973) used correlations of single, three way and
double cross means in differing e nvironments to evaluate the
relative importance of epiatatic and GE interaction deviations in
Burdon suggested this me thod in She lbourne (1972) and
maize.
used it in intP.rpreting clone -site inte ractions in radiata pine
(Burdon 1973 ) •
Falconer (1952) was the first to point out that, when two
e nvir nments are involved, GE interaction may be e xpresse d as a
g enetic corre lation betwe e n two "characters", pe rformance at one
site, and performance at the other.
Unde r these conditions it
is possible to comnute oredicte d genetic g ains from sele ction
for one "character" (at one site) for pe rformance at anothe r.
Burdon (in MS) has extended Falcone r's the ory to the tre e
bre eding situation to enable environments to be characterised
for their inte ractive behaviour with a
of ge notype s,
He
emphasises that most papers on GE interaction have be e n concerned
with the statistical characterisation of the interactive behaviour
.
The
of a limite d numbe r of ge notypes, or cult1v r populations.
re asons for this lie in the fact that much of the work was with
annual or annually harve sted crop plants so that at a give n site
This make s
any one se a.Son will 'Produce a unique e nvironment.
much of the environme ntal variation unpredictable, even if it is
possible to inte rpret the be haviour of the different varieties
afte rwards using joint re gression analysis.
With crop plants too
there are usually onlv a limite d number of varie tie< to be
con sidered.
- 83
-
---
-
·-�------------------· -----
·------
It is Burdon'e main contention that in tree improvement, the greatest attention should be given to the role of environments, not enotypes, in enerating interactions.
Forest environments are largely nermanent features and annual fluctuations of climate and nests have rather little effect on harvested yield, unless these are c ta trophic.
New genotypes on the other hand (or new varieties) can be created at an.v time and with outcrossing, heterozvr-our and initially unselected populations in which to select and breed, large numbers of genotypes will have to be screened.
It is therefore sensible to evaluate these at a few environments, after investigations have revealed which are representative of sites in that breeding region. •
•
'
Burdon's method uses a matrix of genetic correlations to show
which environments are out of line with the rest.
Then, by using
Falconer's formula for correlated selection reE::ponEe, a matrix of
gain expectations is comnuted for gains at one site after selection
at another.
This allows the breeder to comnare the value of
different environments for screening either by phenotype, progeny
test or combined selection
•
An advantage of Burdon's procedure is that different designs
and sets of entries can be used at each site ( provided a set of
All that is required is the
entries is common to both sites ) .
correlation between entry means and the repeatability of entry
means for the trait at each site.
Then, using an alternative
f ormulation of the genetic correlation:
r,
,\
..'
"
=
xy
Correlati0n between entry means at environments x &
Repeatability of entry means at x x repeatability of entry means at Y• The formula for correlated respo se to selection is:
--
For a somewhat similar problem, Tai (1974) used Falconer's
concept to analyze d ta collected from two clonal generatione of
potatoes grown under different cultural conditions.
Expected
gains were calculated for a_ E:e conci commercially-reared generation
based on selection in a first eneration where an unconventional
cultivation system had been used.
Recently several multivariate methons, mainly based on
princi al component Analvsis, have heen explored AS means for
elucidatin GE interactions.
Although principal components
analysis is a descriptive rather than an explanatory technique,
its use in analyzinp carrot variety trials enable d the most
important component of the interaction between genotypes and
environments to he i entified ( freeman and Dowker 1973).
- 84 -
Pe rkins ( 1 972 ) also used principal comnone nt analvsis as a means
of imnroving on the }'redi tion of r:e' n o i yne meRns obtained from
joint re gres inn analysis.
Another for of multivariate analysis combines descrl tion of
a causal RYl'te m by nath c<:>efficients with the cnnce nt of seque ntial
deve lopment of yiP.ld components (Tai 1975).
The me thod is an
application of factor analysis where a small number of factors
account for a matrix of corre lations amonR a eroup of variables.
The succe ss of the method depends on the validity of the causation
sche me .
The multivariate te chnique s have so far be e n dire cted at making
genotype performance more predictable.
It is theore tically
acceptable however to regard a set of measure ments on several
phenotypes (e.g. , from a prove nance , family or clone) as being
analogous to measurement of a single genotype.
Also, there seems
to be no re ason why multivariate methods cannot be used to 1<roup
e nvironme nts.
IV .
:
-:--
GE INTERACTION WITH I N A BRESDING POPULATION
A vital pre re quisite for intra-population bree dinrr is a high
quality, high yie lding base population, stable over the e nvironments
in which it is to be grown.
Inevitably, if the range of e nviron­
ments is wide e nough, GE interaction variance will be large re lative
to overall ge netic variance .
For this re ason prior stratification
of site s into broad "plantation" or breeding zones of similar
adaptation re quire ments is a desirable first step in breeding of
both e xotic and indigenous species.
Unfortunate ly, it cannot be
aseumed that se lection .,.,. a F.table proven::.ince for a given zone
will nece ssarily be accomoanied by absence of genotype x site
interaction.
It will be necessary to first investigate the GE
interaction situation ithin ·each zone and breeding population in
order to iOe ntif,y anv site types that are cauFiinp:" majl")r interac­
tions and then to decide if furthe r stratification of the plantation
zone is de sirable .
Exuerimental dep,igns for exulorin
interaction8, and
internre tation of results
While it may be posPihle to e xplore GE interaction patterns
using prop:eny experiment:s from the breedinr: prop-ram, it is desir­
able to de si
exPeriments specifically for this purpose .
Additive g e netic x e nvironmental effe cts, the most important
interactions in recurrent-sel ction-base d breeding, can be
detected with wind-pollin3te d or polycross progeny, but this
material is not very sensitive;
only one quarter of the additive
genetic variance (betwe e n families) interacts with environmental
e ffects.
- 85 -
Full-sib matine designs enable e'Stimates of GCA and
at the expense of samplinR many fewer parents.
diallel,
with small units of ;. to 5
SCA effects
The disconnected
parents may be a reasonable
alternative. mating desi n for this type of experiment.
Clones have not been generally used to explore GE interaction
in forest trees except in species in which rooted cuttings are the
.
common plantine; stock.
Most conifers are quite easy to propagate
by cuttings when they are still very young.
Thus,
"seedling clones"
can be developed by multiplying a clone before the ortet is more
than
1
m hi h;
propagating from seedlings should
aginp; effects on the ramets
(Burdon and
avoid imposing
Shelbourne,
197 4 ) .
Using
clones to exnlore interactions in field experiments would.greatly
reduce experiment size or increase precision because genetic
variation is absent. within a clone.
To devise a
slte samrlinR
scheme for discoverinP. the environ­
mental factors causinr: interactions, all available information about
.
the growth· of a Fpecies will be necessary.
RegionB.1 climatic
differences prohably will have been taken into account
revious stratification on the basis of
interactions;
;
-·-
-
altitude and
po ulation
in any
x environment
posnibly soil factors may prove
important at the genotypic level.
For practical
and economic
reasons a complete sampling by test plantations of all environmental
grndlents is imposeible.
The smaller -es.ch site experiment can be made,
ments can be sampled for a
given cost.
240 trees per site.
would mean a total of only
eedlinp;
in a
per site and
40
Using
6
the more environ­
ramets of 40 clones
Using full-sib
5-parent diFconn'=cted diallel desir,n '!ith
parer.ts,
the experiment would be
For identifyinp: sites,
seven
and by inference the environmental
factors which are interactinr: strongly with genotypes,
described methods of Burdon
( 1969)
20 seedlings
times as big.
(in MS)
may be uReful.
the previously
or Abou-el-Fi ttouRh
et al.
.
Recurrent selection for superior and stable performance
Selection must be carried out each generation in any multi­
cvclic breeding program.
the "best" sltes,
i.e.,
gel!etic differences and
fore st areas. This will be moFt effective
reµe8tahle results representative of large For this lAtter requirement,
selection
9upf"rinr
qins in stability are
hreP-din::i:.
we believe that a recurrent
pro1<ram
.
can be improved by select.inn:
ility as well as for
if done on
those knnwn to give- good resolution of
nerformance.
por;sible
is supported
Th;.;t r,-;1inr are feaE:ihle
p;enotypes for stab-
The assurrption
by re-Rults
that
from crop
for forei=:t crops is indicated
- 86 -
--
-----·-··
------
by the fact that most tree-breeding programs include r.ome families
less interactive with site than others.
Obviously,
balance exists bPt een size of the breeriing zone
and selecting
for
tability on the other.
determin_ed bv tradeoff between the
an optimum
on the one hand
This optimum will be
greatly increased coo;ts of
subdividing t e region by duplicating breeding Dro rams,
reduction in ge etic g9ins implicit in selecting
both stable an<l
versus the
genotypes that are
high vielding.
In any case,
nlanting material on several sites will always be
necesrary to enrure that GE inter8cti6ns do not bias selection.
To do this effectively requires p rior reseRrch crn interaction
natterns,
to deter ine which sites will best differentiate geno­
types.
v
GE
INTERACTIOI\
IN TREE BREEDING PRACTICE TODAY
Few published reports on family and clone x environment inter­
··.-.<-·
in the tree breeding literature since the
action have anpeared
--.
Shelbourne
(1972)
review.
Further, to the beRt of our knowledge
few breeding programs include experiments planted specifically to
investigate interactions.
diallel of P.
(Wilcox
1976).
An exception would he a disconnected
radiata recently planted on
12
sites in New Zealand
It is hoped more infnr ation on planned or newly
planted experiments will become available from participants at
this meeting:.
Tree-breeding
trative
climate,
regions have been delimited largely by adminis­
and political boundaries or on the basis of differences i n
soil and species performance.
initial subdivisions in the
improvement _cooperative with P.
company land holdings
Pacific Northwest,
In the southeast USA,
NC State University-Industry tree
taeda have been on the basis of
and broad physiogranhic differences.
In the
In-lustry-State-Federal cooperative programs
are in breeding zone
of ab ut
70,000
hectares,
subjectively
delimited to minimize within-zone clim tic differences.
Zones are
further divided into altitudinal bands of about 450 m--Weyerhaeuser
Company's pr".:)rram i0 divirled on al ti tu de and also on "tree farm"
�-
(large land holdinr:s).
six states.
__
,_.
---
In Australia attempts are being made to
coordinate breeding nrogr rns for P.
So far,
in. th
radiata that are existent in
face of Rome large GE interactions,
subdiVision iF mainly on nolitical/administrative boundarieB.
New Zealand,
been
fi.rst reneration
nrogeny testinR of
on a m re or ]eoc countrywide basis,
P.
radiate
In
has
th0ugh clones are
allocated to rpgional seed orchards in three different sets,
bas d on geogranhic and
In Scandinavia,
programs are severe
climatic differences.
the uroblems of regionalization of breeding
fLJr hath Scotn pinA And Norway spruce.
are hindered by complex ar1antation,
:·i
te int.f'!ractinnFi.
Alth1ur:h
provenance-site and
Breeders
enotype­
the situati0n in EJJrope for N0rwa,y
- 87 -
------�-- ----
spruce a pnea r s to he more straightforwa rd , a possibly complex rovenance a d a ptati n pi cture ma y e me rge fo r Douglas- f i r . Info rmati on on such matte r s o ften d o e s not ge t pub l i she d . The re fore , a major function o f d i scu s s i on a t thi s mee ti n g i s to i n f orm pa rtici pants o f oracti cal acti v i t i e s i n d i f f e r e n t bree d i n g pro grams, a n d to record the se i n d i scu ssion su mmari e s. LIST OF REFER ENC ES
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.·.·
i
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---
---
•
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•
•
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"---._--::
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------ ------ -
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--- ,
··
---
,
:
A.H.
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___
,
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1 4Q-1 5 .
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R . G . H i t c h i n r, s .
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qual i t y throiugh b re e d i ng.
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c o n t ro l o f w o r> n
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1 96 9 ,
Bre e d in g fo r d e l a y e d bu dbreak
i n P i c e a glauca ( Moe nch ) V o s s - - no t e n t i a l fro F t a v 0 i d an c e a n d
growth ga i n s .
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FO-FTB-69/2/5.
Pede r so n ,
D.G.
1 97 4 ,
The stabi l i t y o f va r i e tal performance o v e r
Here d i t y 33 : 2 1 7-2 8 ,
years,
2.
Ana l y s i n g va r i e t y tria l s .
Perkins, J . M.
1 972 .
T h e p r i n c i pa l c o m p o ne n t a n a l y si s o f
e n o t v pe e nv i ronm e n t a l i n t e ra c t i_ o n s a n rl physi c a l m e a su re F of the
H e re d i t y 2 9 : 5 1 -7 0.
e n v i ro nm e n t .
and
me n ta l
J.L.
Jink s .
c om po n e n
c r:'1 F - e r; .
H e rn c1 i
196q,
E n v i ronme n t a l
o f v ri. a h i l i t y .
t_ ,.. ? ?- : 7-3Q- 3C.6 .
- 91
-
III
a n rt ge n o tyne-e n v i r o n ­
M u l t i le l i ne
and
F i n th u s , M . J .
m e th o d .
1 97 3 .
E s t i mn te o f ge n o t y p i c va lue :
Eirnh v t i ca 22 : 1 2 1 - 1 2 3 .
a vroro E";ed
1 q74a .
G e n e t i c va r i a t i o n of Dou l a s - f i r i n th e
Re fe l d t , G . E .
or th e rn R o c k v Mo11 n t a i n s .
U . £ . D . A . For. Se rv. R s . N o t e
I N T- 1 1< 4 , 6 p .
1 974 b .
Local d i f fe r e n t i a t i on o f popu l a t i o n F o f R o c k y
Ca n . J . Fo r . R e s . 4 : 399-406 .
!- o u n ta i n Do u r ··lrt s- f i r .
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FAC/FORGEN 6 3 - 11/5 , 1 8 p .
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1 C1?2 .
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i t s study
n d i t s i m nl i c t i o s i n f o r e s t t r e e i m roveme n t .
IUFRO
G e ie t i c s i SRAC. Joi n t Symno E; i n .
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ExpP r i m e n t
t a t i n n , Tok v , 1 97 2 .
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1 96 4 .
R e ge n e ra t i o n a spe c t s o f t h e 50-ye a r- o l d
Pro c . 1 gG 4 A n n u .
tg. of the
Dn f].a s- f i r h e r d i t y st u d y .
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1 q7 0 .
Genot y pe -e nv i ronme n t i n t e ra c t i o n s i n fore s t
tr es.
IUFRO lor'.: i n g G r n u n i n Quan t i ta t i ve Ge n e t i c s.
U2DA Fo r e n t · E A rv i c e , s u t h e r
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ter , K.
1 96 .
t u n g , e r l 11 t e r t a m Be i ? i. e l
eier
o e l l vP r ru che .
z:; c h t e r
3.4 : 1 1 -2 1 9 .
S t 1J t e r , c . w
. F . } i l liams
n rt R . H . M o l l .
1 97 3 .
Eni sta Ri - i n
m a i z e ( Ze a ma v s L . ) :
S i g n i f i ca n c e i n n re d i c t io n s n f hybri d
p e r f o rman c e n .
Crop S c i .
1 3 : 1 9 5-200.
• .
Ta i , G . C . C .
cation
i
'
•
;
1 97 1 .
G e n o t y p i c stab i l i t y anrt l y i s a n d i t s a p p l i ­
to pota t o re g i o n a l t r i , l s .
Crop
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1 974 .
A me tho d for
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c lo na l g e ne ra ti on se e d l i n g s o f a n a se x u a l c r o p wi th F' pc c i. a l
a p;:- l i c t i o n t o a bree d i ?'l g pop11 la t i o n o +"' t h e pota to ( .So la num
The o re t i ca l a n d A p p l i e d Ge n e t i c s '-l 5 : 1 50- 1 56 .
t 11 b e ro su m L . ) .
•
---
1 97 5 .
A na l v s i s o f -ve n o t v r e - e n v i r o nm e n t i n t e ra c t i o
based
on t h e
Can . J . G e e t .
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- 92
Bre P. d i n;:- f r 1 r h e i f...h t growth
World Con su l t . F o r . Tree
-
Vari a t i on i n lon leaf p i n e
1 970.
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from severa l geograph i c snurc e s .
For .Sc i . 1 6 ( 1 ) _ : - 2 8-42 .
•
General and spe c i fi c c om b i n i n g a b i l i ty
1976.
.D.
Wilcox,
e E> t i ma t e s for h e i 1'h t p:rowth in th e nurserv from a d i sc o nne c t e d
N . Z . Fore t Serv i c e ,
rad i n t a .
d i a l l e l e xperiment in Pinu
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I n t e rna l Renart 93 ( unnubl i sh e d ) .
II
1 96 2 .
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Z Pflanze nzuch .
47 : 92-9G.
.•
Genotype - e n v i ronme n t i nt e ra c t i on i n north
1 973.
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c e n tral Un i te d Sta te s.
f::
ij
;;
Di fferent i a l p: o ne t i c re sponse
1970.
and J . Roberd s .
Zobe l , B . J .
to ferti l i se r F wi th i n tree sue c i e s .
Fore st Biology Worksh o p ,
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- ;;
·
I
·
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.
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L'
' .
-
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- 93 -
.
_ ____
__._ _ _
.IUFRO, .Joint .Meeting . on ..Adva.rwed .Generation Breeding, Bordeau:r:-Jwze 14-.18, 197.6_.. .
R E PORT O F S E S S I O N
THE
I MPACT O F GENOTY PE-ENV I RONMENT
ON TREE
.
-=-=-=-=-
C.J.A.
R E PO R T ER S
H. H . HATTEMER
R . JOHNSTONE
V . KRUSCHE
K . R . SHEPHERV
-
I NTERAC T I O N S
I MPROVEMENT STRATEGY
C HA I RMAN
7°
4
SHELBOURNE
VEFI NITI ONS
Two terms needed definitions before more detailed discuss ion
could proceed .
While it was accepted t hat there are more recent
concept s in
the lit erature, t he current understanding of t he s e t erms was acc ept ed as
follows
0
Genotype-environment interact ion ( GEI
response of populat ions, provenanc e s ,
)
is the d i fferent ial
families or single genotypes t o
environmental condit ions.
0
stability o f these pc:ipulat ions , provenanc e s ,
families or single
genotypes in t he maintenance o f a similar rank order within the array
t e st ed under a variety of condit ions .
2°
-
THE VIFFERENT KIN'DS OF G . E . I.
INVESTIGATION
There appeared to be three facet s to t h e invest igat ion o f GEI
0
by ANOVJ\ ,
0
The empirical fact o f t h e existence of GEI may be det ected
or
genetic correlation unal y s i s .
A n att empt muy t he n be made to explain
such GEI i n t e nn s o f
meas urabl e envi ronmental at tributes by using mul t i variat e t e c h n i que s .
- ''-
0
The final stage in an analysis of GE! would be where the findings
from the mult ivariat e analyse are t e sted with controlled experiment s
where part icular environmental component s are varied ,for example
in
phytotron or carefully derived field trial s . The t rait to be studied
and the environmental variable to be studied must be carefully specified.
3°
-
SELECTION FOR STABILITY OR STRATI FICATION
OF
THE ENVIRONMENT.
The results of t h e stat ist i cal analy s i s which indicat e GE!
will assist
in defining disj unct areas which must be separat ed as st rata for
breeding purpo ses
•
.
-
Alternat ively, the breeding programme need not be split by
zonation of plant ing areas as genotypes which po s s e s s stability
ay be
selected for inclusion in the seed orchard. This stability will be displa­
yed in progeny trials des igned t o invest igat e GE! over the whole range o f
t erritory included i n t h e afforestat ion programme .
;
i
- i
,