Loblolly pine (Pinus taeda) is the most important commercial species in the southern United States and as such, foresters must choose the most appropriate silvicultural prescriptions to maintain or improve the site quality of plantations and natural forests. Choosing the most appropriate silvicultural prescriptions can further increase the site quality of plantations or natural forests. The quality of a forest site can be estimated by several means, however, the most commonly used method is site index (SI). To date, there is no available SI model for intensively managed loblolly pine plantations in the Western Gulf Coastal Plain. To fill the gap, the scope of the East Texas Pine Plantation Research Project (ETPPRP) was expanded and permanent plots were established in intensively managed loblolly pine plantations across east Texas and western Louisiana. Using the data collected, this study developed a SI model specific to intensively managed loblolly pine plantations in the West Gulf Coastal Plain region. Data were fitted to six often commonly used SI functions models: Schumacher Algebraic Difference Approach (ADA) model, Chapman-Richards ADA model, Schumacher Generalized Algebraic Difference Approach (GADA) model, Chapman-Richards GADA model, Cieszewski GADA model, and McDill-Amateis GADA model. Results showed
that the Chapman-Richards GADA model and the McDill-Amateis GADA model were similar and best in their fit statistics. These two models were further compared to the existing models of Diéguez-Aranda et al. (2006) and Coble and Lee (2010), both of which were developed using data from extensively managed plantations and are currently utilized in forest management in the region. Both Chapman-Richards GADA and McDill-Amateis GADA models consistently predicted greater heights at younger ages on higher quality sites than the models of Diéguez-Aranda et al. (2006) and Coble and Lee (2010), however, the GADA models predicted shorter heights at older ages. Ultimately, the McDill-Amateis GADA model was chosen as the best model for its good fit statistics and ease of use. Foresters will be able to use this model to make silvicultural prescriptions better suited for intensively managed loblolly pine plantations in the West Gulf Coastal Plain.
Loblolly pine (Pinus taeda) is the most important commercial species in the southern United States and as such, foresters must choose the most appropriate silvicultural prescriptions to maintain or improve the site quality of plantations and natural forests. Choosing the most appropriate silvicultural prescriptions can further increase the site quality of plantations or natural forests. The quality of a forest site can be estimated by several means, however, the most commonly used method is site index (SI). To date, there is no available SI model for intensively managed loblolly pine plantations in the Western Gulf Coastal Plain. To fill the gap, the scope of the East Texas Pine Plantation Research Project (ETPPRP) was expanded and permanent plots were established in intensively managed loblolly pine plantations across east Texas and western Louisiana. Using the data collected, this study developed a SI model specific to intensively managed loblolly pine plantations in the West Gulf Coastal Plain region. Data were fitted to six often commonly used SI functions models: Schumacher Algebraic Difference Approach (ADA) model, Chapman-Richards ADA model, Schumacher Generalized Algebraic Difference Approach (GADA) model, Chapman-Richards GADA model, Cieszewski GADA model, and McDill-Amateis GADA model. Results showed
that the Chapman-Richards GADA model and the McDill-Amateis GADA model were similar and best in their fit statistics. These two models were further compared to the existing models of Diéguez-Aranda et al. (2006) and Coble and Lee (2010), both of which were developed using data from extensively managed plantations and are currently utilized in forest management in the region. Both Chapman-Richards GADA and McDill-Amateis GADA models consistently predicted greater heights at younger ages on higher quality sites than the models of Diéguez-Aranda et al. (2006) and Coble and Lee (2010), however, the GADA models predicted shorter heights at older ages. Ultimately, the McDill-Amateis GADA model was chosen as the best model for its good fit statistics and ease of use. Foresters will be able to use this model to make silvicultural prescriptions better suited for intensively managed loblolly pine plantations in the West Gulf Coastal Plain.
Loblolly pine (Pinus taeda) is the most important commercial species in the southern United States and as such, foresters must choose the most appropriate silvicultural prescriptions to maintain or improve the site quality of plantations and natural forests. Choosing the most appropriate silvicultural prescriptions can further increase the site quality of plantations or natural forests. The quality of a forest site can be estimated by several means, however, the most commonly used method is site index (SI). To date, there is no available SI model for intensively managed loblolly pine plantations in the Western Gulf Coastal Plain. To fill the gap, the scope of the East Texas Pine Plantation Research Project (ETPPRP) was expanded and permanent plots were established in intensively managed loblolly pine plantations across east Texas and western Louisiana. Using the data collected, this study developed a SI model specific to intensively managed loblolly pine plantations in the West Gulf Coastal Plain region. Data were fitted to six often commonly used SI functions models: Schumacher Algebraic Difference Approach (ADA) model, Chapman-Richards ADA model, Schumacher Generalized Algebraic Difference Approach (GADA) model, Chapman-Richards GADA model, Cieszewski GADA model, and McDill-Amateis GADA model. Results showed
that the Chapman-Richards GADA model and the McDill-Amateis GADA model were similar and best in their fit statistics. These two models were further compared to the existing models of Diéguez-Aranda et al. (2006) and Coble and Lee (2010), both of which were developed using data from extensively managed plantations and are currently utilized in forest management in the region. Both Chapman-Richards GADA and McDill-Amateis GADA models consistently predicted greater heights at younger ages on higher quality sites than the models of Diéguez-Aranda et al. (2006) and Coble and Lee (2010), however, the GADA models predicted shorter heights at older ages. Ultimately, the McDill-Amateis GADA model was chosen as the best model for its good fit statistics and ease of use. Foresters will be able to use this model to make silvicultural prescriptions better suited for intensively managed loblolly pine plantations in the West Gulf Coastal Plain.