2024 journal article
Stem Defect Rates and Ice Storm Damage for Families of Pinus taeda from Coastal and Piedmont Provenances Planted on a North Carolina Piedmont Site
Forest Science.
Abstract Twenty Pinus taeda L. families from both the Coastal Plain and Piedmont provenances in the southeastern United States were planted on an upper Piedmont site that experienced a severe ice storm at age 3 years. Storm damage and defect rates through age 11 years were compared with the seed transfer distance and the seed parents’ breeding values to develop prediction models for storm damage and rates of forking, stem break, and sawtimber potential. Warmer-source families had higher probability of limb or stem breaks and foliage injury from the storm. Taller trees were more likely to experience breaks and foliage injury, even after accounting for seed transfer distance. Trees with forks or fusiform rust (Cronartium quercuum f. sp. fusiforme) infection had a higher probability of breaks. Trees with limb breaks or foliage injury did not have reduced sawtimber potential, but broken stems reduced sawtimber potential. The storm did not cause immediate mortality, but trees with major limb breaks, stem breaks, or foliage injury were less likely to be alive at age 8 years. At age 11 years, families with the best combination of breeding values for forking, straightness, and rust resistance had a predicted 60% of stems having sawtimber potential, whereas families with the worst combination had 30%. Study Implications: Planting warmer-source Pinus taeda (loblolly pine) families farther north and inland may lead to greater growth but poses a risk of damage from cold temperatures and ice storms. Trees grown for solid-wood products must be relatively defect-free and require a longer rotation, whereas bioenergy and pulpwood can use smaller, defective trees. This analysis presents predictions of defect rates through age 11 years based on the seed source and breeding values using data from a planting in the upper Piedmont of North Carolina. Land managers can use these models to weigh the benefits and risks when choosing families for reforestation.