Abstract
In the context of uneven-aged mixed-species forest management, an individual-tree basal area increment model considering forest structural diversity was developed for oaks (Quercus spp.) using data collected from 11,860 observations in 845 sample plots from the 7th (2004), 8th (2009), and 9th (2014) Chinese National Forest Inventory in Hunan Province, south-central China. Since the data was longitudinal and had a nested structure, we used a linear mixed-effects approach to construct the model. We also used the variance function and an autocorrelation structure to describe within-plot heteroscedasticity and autocorrelation. Finally, the optimal mixed-effects model was determined based on the Akaike information criterion (AIC), Bayesian information criterion (BIC), log-likelihood (Loglik) and the likelihood ratio test (LRT). The results indicate that the reciprocal transformation of initial diameter at breast height (1/DBH), relative density index (RD), number of trees per hectare (NT), elevation (EL) and Gini coefficient (GC) had a significant impact on the individual-tree basal area increment. In comparison to the basic model developed using least absolute shrinkage and selection operator (LASSO) regression, the mixed-effects model performance was greatly improved. In addition, we observed that the heteroscedasticity was successfully removed by the exponent function and autocorrelation was significantly corrected by AR(1). Our final model also indicated that forest structural diversity significantly affected tree growth and hence should not be neglected. We hope that our final model will contribute to the scientific management of oak-dominated forests.
Highlights
The more than 500 extant species of oak (Quercus spp.) are widely distributed across the Northern Hemisphere, including Mesoamerica [1,2]
We hypothesized that the introduction of forest structural diversity and random effects would significantly improve model performance and we hope our model will contribute to forest significantly improve model performance and we hope our model will contribute to forest management strategies by predicting forest dynamics under different management scenarios
To avoid over overfitting and multicollinearity, we eliminated the variables of the candidate model with variance inflation factor (VIF) > 5
Summary
The more than 500 extant species of oak (Quercus spp.) are widely distributed across the Northern Hemisphere, including Mesoamerica [1,2]. Oak-dominated forests are of great ecological and economical importance [3,4]. Oaks are extensively used in soil and water conservation and restoration efforts since they have strong, adventitious root systems and exhibit a high tolerance to waterlogging [5,6,7]. Oaks are well adapted to fire and are frequently used for constructing forest fire belts [8]. Oaks play an important role in maintaining biodiversity. Caprio and Ellena [9] reported that the retention of native oaks is the key factor for the conservation of winter bird diversity in local deciduous woods. In addition to the ecological functions, oak timber is distinguished for its great strength, durability and beauty [10].
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