Knowledge / Forestry / Tree improvement and forest genetics

Tree improvement and forest genetics

Forestry (B.Sc Forestry) · Forest biology and silviculture · free study notes for exams, placements and interviews

In short

Tree improvement is the planned use of genetics - selection, breeding, testing and mass multiplication - to raise the volume, form, wood quality, adaptability and pest resistance of planted trees; forest genetics is the underlying science of how variation in tree populations is created, partitioned and inherited. It matters because India's wood demand is met largely from plantations and farm forestry on a short rotation, where a 20-30% genetic gain in mean annual increment is cheaper than any silvicultural input. The work is done by ICFRE institutes (IFGTB Coimbatore, FRI Dehradun, TFRI Jabalpur, AFRI Jodhpur, IFP Ranchi), state forest departments and industry (ITC-Bhadrachalam, JK Paper, WIMCO poplar, Mysore Paper Mills). It is examined in B.Sc/M.Sc Forestry papers, ICAR AIEEA-PG and ARS/NET Forestry, and the Indian Forest Service, and is asked in interviews for plantation R&D, seed-centre and nursery/clonal-production roles.

Explained

Genetic variation and its sources

Population genetics used in forestry

Quantitative genetics: variance, heritability, gain

Selection and testing: the improvement cycle

  1. Define objectives and base population - species, site, product (pulp, plywood, timber, fodder, biofuel).
  2. Species and provenance trials - replicated, common-garden; eliminate unsuitable origins first.
  3. Plus-tree (CPT) selection - *Candidate Plus Trees* scored for volume, straightness, self-pruning, crown/branching, health. Methods: comparison-tree method (regression/check trees: compare the candidate with 4-6 best neighbours within ~30 m), baseline/absolute method in uniform plantations, subjective grading for rough work. A selected CPT must be confirmed by progeny testing; selection on phenotype alone is "mass selection".
  4. Multiplication and mating - scions grafted into a clone bank and Vegetative Multiplication Garden (VMG)/clonal multiplication area; controlled pollination for crosses.
  5. Progeny testing - open-pollinated (half-sib) or controlled-cross (full-sib) families in replicated designs (RCBD, incomplete blocks, single-tree plots) to estimate GCA, breeding value and heritability.
  6. Seed orchards - produce improved seed in quantity:
    • SSO (seedling seed orchard): raised from half-sib/full-sib families; cheap, doubles as a progeny test; rogued after assessment.
    • CSO (clonal seed orchard): grafts/rooted cuttings of tested clones in a non-adjacency/permuted-neighbourhood layout; higher and more predictable gain, risk of clonal incompatibility and flowering asynchrony.
    • Practice: isolation from unimproved stands (commonly 300-500 m or an isolation belt), ≥25-40 unrelated clones to keep Ne high, roguing of poor clones/families, flower stimulation (girdling, fertiliser, paclobutrazol in some species), supplemental mass pollination.
  7. Advanced generations - recurrent selection from the best within the best families, breeding-population management (e.g. sublining to control relatedness).
  8. Deployment - improved seed, or clonal forestry with tested clones; monitor and feed data back.

Mating designs and breeding methods

Vegetative propagation, biotechnology and markers

Indian legal and institutional framework

Key points

Formulas and examples

V_P = V_A + V_D + V_I + V_E - phenotypic variance = additive + dominance + epistatic + environmental (units = square of the trait unit, e.g. m²)
h² = V_A/V_P (narrow-sense); H² = V_G/V_P (broad-sense) - dimensionless, 0 to 1
From a half-sib (open-pollinated) family trial: V_A = 4σ²_f ; h² = 4σ²_f/(σ²_f + σ²_e). From full-sib families: σ²_f = ½V_A + ¼V_D
S = selection differential = (mean of selected trees − population mean); R = response = ΔG = h² × S
ΔG = i × h² × σ_P = i × h × σ_A ; i = selection intensity (standardised), σ_P = phenotypic SD, σ_A = additive SD
Gain per year = ΔG / (generation interval, years). If only one parent is selected (female side), gain = ½ of the two-parent value
Realised heritability h²_R = R/S (from an actual selection experiment)
GCA of a parent = (mean of its half-sib family) − (trial mean); Breeding value BV = 2 × GCA
Mid-parent heterosis (%) = 100 (F1 − MP)/MP, MP = (P1 + P2)/2; Better-parent heterosis uses the higher parent
Effective population size Ne = 4 Nm Nf/(Nm + Nf); inbreeding per generation ΔF = 1/(2Ne); F after t generations = 1 − (1 − ΔF)t
Nei's gene diversity He = 1 − Σ p_i² ; Gst = (Ht − Hs)/Ht ; Fis = 1 − Ho/He
Hardy-Weinberg: p² + 2pq + q² = 1 (p + q = 1)
CV (%) = 100 σ/mean - used to compare variability of trials and traits

Example 1 - heritability and breeding value from an open-pollinated progeny test. A 60-family half-sib trial of *Casuarina equisetifolia* at age 4 gives family variance σ²_f = 0.45 m² and within-family (error) variance σ²_e = 8.55 m² for height.

Example 2 - expected genetic gain and gain per year. 20,000 eucalypt candidates, σ_P = 4.0 m, h² = 0.25; the best 1% are selected (i = 2.67 for p = 0.01).

Example 3 - effective population size and inbreeding in a small orchard. A clonal orchard flowers unevenly: effectively 8 clones shed most pollen and 40 clones bear seed.

Example 4 - gene diversity and population differentiation. At one SSR locus in a teak seed source, allele frequencies are 0.50, 0.30, 0.20.

Example 5 - economics of clonal deployment (pulpwood farm forestry). Seedling route MAI = 10 m³/ha/yr; tested clones give a 30% gain → 13 m³/ha/yr. Rotation 7 years, 1,250 plants/ha.

Seedling seed orchard (SSO)Clonal seed orchard (CSO)Clonal plantation
MaterialHalf/full-sib seedlingsGrafts/rooted cuttings of tested clonesRamets of tested clones
Gain capturedAdditive (GCA) onlyAdditive (GCA) onlyAdditive + non-additive (GCA+SCA)
UniformityLowModerate (seed still segregates)Very high
Cost and skillLowMedium-highHigh (VMG, mist chamber, QC)
Genetic baseBroadModerateNarrow - needs clone mosaic
Doubles as progeny testYesNoNo
Trait groupTypical h²Implication
Height, diameter, volume0.10-0.30Many replications, large families, index selection
Stem straightness, branching0.15-0.35Visual scoring workable with replication
Wood specific gravity, fibre length0.40-0.60Few trees per family give reliable selection
Survival, pest incidenceLow and site-dependentMulti-site testing essential

Where it is used

Interview questions

Common mistakes

Related topics

Forest nursery and plantation forestry · Silviculture: principles and practices · Silviculture of important Indian trees · Plant taxonomy · Ecology and ecosystems · Forest seed technology and biotechnology.

Open in the Knowledge reader →Find jobs →