Current issue: 55(5)
Under compilation: 56(1)
Newly developed positioning systems in cut-to-length harvesters enable georeferencing of individual trees with submeter accuracy. Together with detailed tree measurements recorded during processing of the tree, georeferenced harvester data are emerging as a valuable tool for forest inventory. Previous studies have shown that harvester data can be linked to airborne laser scanner (ALS) data to estimate a range of forest attributes. However, there is little empirical evidence of the benefits of improved positioning accuracy of harvester data. The two objectives of this study were to (1) assess the accuracy of timber volume estimation using harvester data and ALS data acquired with different scanners over multiple years and (2) assess how harvester positioning errors affect merchantable timber volume predicted and estimated from ALS data. We used harvester data from 33 commercial logging operations, comprising 93 731 harvested stems georeferenced with sub-meter accuracy, as plot-level training data in an enhanced area-based inventory approach. By randomly altering the tree positions in Monte Carlo simulations, we assessed how prediction and estimation errors were influenced by different combinations of simulated positioning errors and grid cell sizes. We simulated positioning errors of 1, 2, …, 15 m and used grid cells of 100, 200, 300 and 400 m2. Values of root mean square errors obtained for cell-level predictions of timber volume differed significantly for the different grid cell sizes. The use of larger grid cells resulted in a greater accuracy of timber volume predictions, which were also less affected by positioning errors. Accuracies of timber volume estimates at logging operation level decreased significantly with increasing levels of positioning error. The results highlight the benefit of accurate positioning of harvester data in forest inventory applications. Further, the results indicate that when estimating timber volume from ALS data and inaccurately positioned harvester data, larger grid cells are beneficial.
Studies of the spatial patterns of dominant plant species may provide significant insights into processes and mechanisms that maintain stand stability. This study was performed in a permanent 1 ha plot in evergreen and deciduous broad-leaved mixed forests on Tianmu Mountain. Based on two surveys (1996 and 2012), the dynamics of the spatial distribution pattern of the dominant population (Cyclobalanopsis myrsinifolia (Blume) Oersted) and the intra- and interspecific relationships between C. myrsinifolia and other dominant species populations were analyzed using Ripley’s K(r) function. We identified the importance value of a species in a community, which is the sum of the relative density, relative frequency, and relative dominance. The drivers of spatial distribution variation and the maintenance mechanisms of the forest were discussed. The results showed that the importance value of C. myrsinifolia within the community decreased over the past 16 years. The C. myrsinifolia population exhibited a significantly aggregated distribution within a spatial scale of 0–25 m in 1996 whereas it changed to a random distribution at scales larger than 5.5 m in 2012. From 1996 to 2012, the spatial distribution patterns between C. myrsinifolia and Cyclocarya paliurus (Batal.) Iljinsk. and between C. myrsinifolia and Cunninghamia lanceolata (Lamb.) Hook did not change significantly. In 1996, C. myrsinifolia and Daphniphyllum macropodum Miq. were positively associated at the scale of 0–25 m; this relationship was strongly significant at the scale of 6–10 m. However, there was no association between the populations of two species in terms of the spatial distribution at the scale of 0–25 m in 2012. Our findings indicate that the drivers of variation in the spatial distribution of the C. myrsinifolia population were intra- and interspecific mutual relationships as well the seed-spreading mechanism of this species.