Evaluation of the performance of forest structural indices under different National forest inventory plot designs

Forest structure encompasses a variety of attributes related to the arrangement of the forest components (e.g., trees, shrubs, deadwood) in both horizontal and vertical dimensions. Several indices quantify the structure of the tree layer; however, the performance of these indices under a nested plot design, which is prevalent in National Forest Inventories, is poorly understood. Furthermore, the differences in plot design complicate the comparison among indices. The primary objective of this study is to evaluate the performance of distance-independent indices in the National Forest Inventory plots of two European countries where the nested plot designs differ the most: Spain and Finland. To achieve this, we simulated 39,600 one-hectare plots with different stand characteristics, and embedded the nested plots from both countries as well as the fixed-area plots corresponding to the areas of the largest plot without the tree-size restrictions applicable to the inner plots. We calculated four species composition indices, six indices that describe forest structural complexity, and two indices assessing forest complexity with composition. In our study, tree species richness, Shannon’s and Simpson’s Diversity Index suitably described the tree composition component. However, the performance of tree richness as an indicator can be heavily affected by the settings applied to simulate the plots. The sum of square roots of diameter differences and Shannon’s Diversity Index applied to the diameter classes along with the second L-moment were found to be the most effective indices for consistently quantifying forest structural complexity across different sample plot designs. The agreement among indices calculated for the different plot designs was positively related to tree density, i.e., nested designs and fixed-area provided a better representation of forest structure in stands with high tree densities.