2015 journal article
Modeling Climate Change Effects on the Height Growth of Loblolly Pine
Forest Science, 61(4), 703–715.
author keywords: Pinus taeda; provenance test; statistical model; universal response function; climate change
UN Sustainable Development Goal Categories
13. Climate Action
(Web of Science; OpenAlex)
15. Life on Land
(Web of Science)
Source: NC State University Libraries
Added: April 25, 2019
We present a statistical model to predict the effects of climate change on the height growth of loblolly pine (Pinus taeda L.) families in the southeastern United States. Provenance-progeny trials were used for assessing the response of loblolly pine seed sources to environmental change. Ordinary least squares, ridge regression, and LASSO regression were used to develop height growth prediction models. The approach integrates both genetic and environmental effects and is meant to overcome the critical limitations of population response function and transfer function methods by making full use of data from provenance trials. Prediction models were tested using a hypothetical future climate scenario with 5% decrease in precipitation and 0.5° C increase in maximum and minimum temperatures, relative to historical average values. Under this scenario, local families from the coastal plains of Georgia, Florida, and South Carolina showed the highest performance relative to the current climate in their native environments. As these seed sources were moved to colder northern and inland regions from their origin, we observed declines in their height growth. Similarly, the climatic change scenario suggested that performance of northern seed sources declined significantly when they were moved to more southern warmer regions. The statistical model can be used as a quantitative tool to model the effect of climatic variables on the performance of loblolly pine seed sources and may help to develop sound breeding deployment strategies.