A model for estimating understory vegetation response to fertilization and precipitation in loblolly pine plantationsThis article is part of a larger document. View the larger document here.
A model form is presented, where the model contains regressors selected for inclusion based on biological rationale, to predict how fertilization, precipitation amounts, and overstory stand density affect understory vegetation biomass. Due to time, economic, and logistic constraints, datasets of large sample sizes generally do not exist for understory vegetation. Thus, we wanted to see if the model form would provide reasonable estimates of understory biomass using a limited range of values for the regressors when estimating parameters.
Data from three loblolly pine (Pinus taeda L.) plantations located in the Western Gulf of the Southeastern United States were used to obtain parameter estimates for the biologically derived model form. Stand density index was used as the measure of stand density. Our model predicts that additional amounts of fertilizer and precipitation can increase understory vegetation biomass. However, at some point, depending on precipitation amounts and stand density, increases in fertilization and precipitation will produce decreases in understory vegetation biomass because of simultaneous increases in loblolly pine production. Based on validation results using data from independent studies in the Western Gulf, the model form provides reasonable estimates of understory biomass for regressor values beyond the range used in parameter estimation. Future research needs to concentrate on estimating parameters for the presented model form using a more complete dataset.