English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Evaluation of basal area projection models for unthinned and thinned central Appalachian hardwood forest stands. Ivan Zhelev Anastasov Several basal area projection models, originally developed for pine plantations, were proposed for potential use in central hardwoods. The data came from five different studies that were established throughout the central Appalachian region. Analysis of variance was performed to detect significant differences among the different treatments and studies. The results indicated that there is a significant difference in basal area growth between unthinned and thinned plots as well as between the different studies. Each selected model was then fitted to the re-measured hardwood plot data, using a non-linear procedure. An assessment was perform on the analysis of variance outcome, residual distribution, and average bias separately for unthinned and thinned stands, in order to find the best equation for the data. The results indicated that all selected equations for this study can be applied in central hardwood stands for basal area growth modeling. Some model forms contained non-significant coefficient estimates that were excluded. The equations with a thinning modifier did not always exhibit better characteristics when compared to the model forms lacking an explicit thinning modifier. The best basal area projection model contained the smallest root mean square error and the highest coefficient of determination for the two treatments, the smallest bias when fit to the data for thinned plots, and a relatively small bias when fit to the data for unthinned plots. When tested for projection indifference by study, the best basal area projection model showed no major projection flaws and was finally approved.