Presentation at Subtropical Forest Research Institute, Chinese Academy of Forestry, August 19, 2010

Topics to be presented  Variation in fertility  Seed orchard turnover  Optimal number of clones  Prediction of fertility prior to orchard establishment  Deployment of clones to a seed orchard  Thinning of seed orchards using the linear deployment algorithm  Biological seed production  Impact of growth and seed related characters on seed procurement

Material and Methods  Pinus sylvestris main tree species  Two types of material  Seed orchard data, collected by the authors and/or extracted and analysed from published works  Models developed using real data  Calculation of variance components using  ANOVA  ASReml  Microsoft Excel spreadsheets used for formulation of models and Excel-tool Solver for optimizing

Mathematical framework The sibling coefficient, , expresses the probability that successful gametes (sibs) will originate from the same parent compared to the case with no differences in parental fertility N is the census number of the parents p i is the probability that a gene in the offspring originates from parent i

Mathematical framework, cont’d The relationship between sibling coefficient and coefficient of variation (CV)  ≥1; if  =1, all individuals have the same fertility; if  =2, it means that the probability that two randomly drawn successful gametes share the same parent is twice that where fertilities are equal across the population

Variation in fertility Why focus on female fertility?  Seeds are the source of income from a seed orchard  Cones and seeds are used to audit the operation  About 2/3 of the tree improvement effect comes from the seed parents as half of the pollen parents are outside the orchard  Seeds from a known tree can be harvested and counted, which can be considered as the exact number of successful female gametes of the parent

Seed orchard (cf Table 2) Character Variance component among clones a single year  Variance component among clones over years  Variance component of clone-year interaction (years) Variance component among ramets within clone and year Heritabilit y (broad sense for individual year) AskerudSeeds/ ramet3813c (3) LångtoraSeeds/ ramet0b0b1.00** LustnäsetSeeds/ ramet5830c (2) Robertsfors Cones/ ramet ** SkaholmaSeeds/ ramet ** Sävar Cones/ rameta ** Gnievkovo Cones/ ramet 313c (2) Nebraska Cones/ ramet 10271c (2) Viitaselki Cones/ ramet * *940 Vilhelminmäki Female strobili/ ramet 2541c (2) Vilhelminmäki Cones/ ramet * *5281 Average all SOs Average for SO with clone-year interaction

Seed orchard turnover  A model was developed to evaluate the benefit of various options. Options and variables included in the model are:  Seed orchard size  Planting density  Type of orchard material (grafts, cuttings)  Establishment and management costs  Cone harvest and seed processing costs  Development over time of the seed orchard crop  Rate of genetic progress in long-term-breeding

Seed orchard turnover, cont’d  Genetic penalty, representing the gain differential between the seed orchard and a hypothetical new orchard incorporating the latest genetic progress in the breeding population  Impact of pollen contamination  How the genetic quality influences the value of the seeds  The orchards productive lifespan

Seed orchard turnover, cont’d  Optimal rotation age for Pinus sylvestris orchards is suggested to be around 30 years  Cone harvest starts at age 8  For Picea abies 40 years is optimal  Cone harvest starts at age 15

Optimal number of clones  Maximize a goodness criterion (“benefit”) for orchards. It’s a function of:  # of tested genotypes available for selection and planted in seed orchard  The contribution of pollen from:  The ramet itself  The closest neighbors  The rest of the orchard and contamination  Variation among genotypes for fertility  Frequency of selfing

Optimal number of clones, cont’d  Production of selfed genotypes  Gene diversity (=status number)  Influence of contamination  Genetic variation among candidates  Correlation between selection criterion (e.g. height in progeny test) and value for forestry (e.g. production in forests from the orchard)  # of clones harvested

Optimal number of clones, cont’d  Optimum # of clones in Pinus sylvestris is suggested to be 16, assuming ψ=2  If ψ=1.24 as mentioned before, then optimum # is 11

Prediction of fertility prior to orchard establishment  Fertility varies over years  Cumulative cone-yield data would provide greater reliability  Correlations between female fertility in clone archives and performance of the same clones in seed orchards was close to zero  Thus it’s not worthwhile to collect data as a selection criterion when designing new seed orchards

Deployment of clones to a seed orchard  “Linear deployment” means that clones are deployed proportional to their breeding values  A higher proportion of pollen from a clone constitutes a higher probability of self- fertilization, but seldom leads to fertile seed  Outcrossing pollen is more efficient than pollen that is delivered to ramets of the same clone

Deployment of clones to a seed orchard, cont’d  “Outcrossing effective number” is coined to describe the balance between # of ramets and the effective # of the realised seed crop  Comparison between optimal and linear deployment of clones, under same outcrossing effective number, produced similar results.  At low effective numbers, impact of selfing will be greater

Deployment of clones to a seed orchard, cont’d

 Pinus sylvestris seed orchards are suggested to be established with tested clones, linearly deployed according to their breeding values, with an effective number of clones based on number of ramets planted

Thinning of s.o. using the linear deployment algorithm  Thinning by linear deployment results simultaneously in greater genetic gain, higher effective clone #, lower thinning intensity  Gives more flexibility for future thinning, mass production of controlled crosses, selective harvest etc

Thinning of s.o. using the linear deployment algorithm Parameter Before thinning Max. NeMax. gain at given NeTruncation selection1 After thinning Clones Ramets Gain Ne g0 -- b 

Biological seed production  Seed orchards are often located on abandoned farm land, with favorable climate and soil conditions, which normally increases the seed production  seeds/m 2 or 10 kg/hectare would be possible  Seed orchards are generally young compared to seed stands, and thus seed production potential is underestimated  The studied seed orchards indicate a average biological seed production of 9 kg/hectare

Impact of growth and seed related characters on seed procurement  Growth, morphology and number of strobili have limited genetic variation, thus should not be considered when selecting clones for orchards = take care of it with cultural management  Seed-related characters have impact on seed procurement  Around ¼ of cones are situated in the top level of the crown, ½ in the middle and ¼ in bottom level

Impact of growth and seed related characters on seed procurement, cont’d  Cost for harvesting cones is dependent on tree height, thus pruning is recommended  Variation in fresh weight of cones – related to ripening- can have impact on seed procurement

Summary  When establishing a new seed orchard, little emphasis should be put on selecting clones with high fertility  A seed orchard with tested clones should contain clones, linearly deployed, resulting in an effective number of clones  Harvest of cones can often be started as soon as the first cones are available, but contaminating pollen can change the adaptability of the seed  For Pinus sylvestris, the optimal active life time of seed orchards seems to be 30 years, for Picea abies 40 years  Highs costs of cone harvest can be reduced by pruning the seed orchard trees

Thank you for your attention