Predicting Future Diameter Distributions Given Current Stand Attributes

This study discussed four methods to project a diameter distribution from age A1 to age A2. Method 1 recovers parameters of the distribution at age A2 from stand attributes at that age. Method 2 uses a stand-level model to grow the quadratic mean diameter, and then recovers the distribution parameters from that prediction. Method 3 grows the diameter distribution by assuming tree-level survival and diameter growth functions. Method 4 first converts the diameter distribution at age A1 into a list of individual trees before growing these trees to age A2. In a numerical example employing the Weibull distribution, methods 3 and 4 produced better results based on two types of error indices and the relative predictive error for each diameter class. Method 4 is a novel method that converts a diameter distribution into a list of individual-trees, and in the process, successfully links together diameter distribution, individual-tree, and whole stand models.

Forest Structural Estimates Derived Using a Practical, Open-Source Lidar-Processing Workflow

Lidar data is increasingly available over large spatial extents and can also be combined with satellite imagery to provide detailed vegetation structural metrics. To fully realize the benefits of lidar data, practical and scalable processing workflows are needed. In this study, we used the lidR R software package, a custom forest metrics function in R, and a distributed cloud computing environment to process 11 TB of airborne lidar data covering ~22,900 km2 into 28 height, cover, and density metrics. We combined these lidar outputs with field plot data to model basal area, trees per acre, and quadratic mean diameter. We compared lidar-only models with models informed by spectral imagery only, and lidar and spectral imagery together. We found that lidar models outperformed spectral imagery models for all three metrics, and combination models performed slightly better than lidar models in two of the three metrics. One lidar variable, the relative density of low midstory canopy, was selected in all lidar and combination models, demonstrating the importance of midstory forest structure in the study area. In general, this open-source lidar-processing workflow provides a practical, scalable option for estimating structure over large, forested landscapes. The methodology and systems used for this study offered us the capability to process large quantities of lidar data into useful forest structure metrics in compressed timeframes.

Application of allometric systems for compatible area-based LiDAR-assisted estimation in the Province of Nova Scotia

Light detection and ranging (LiDAR) is used to estimate tree, stand, and forest characteristics across large geographic areas. In the province of Nova Scotia, an enhanced forest inventory (EFI) was developed to provide high-resolution spatial forest inventory estimates across the landscape. For various forest attributes, independent LiDAR-based relationships were built leading to mathematical and biological inconsistency among forest attribute estimates. A systems approach, composed of allometric equations describing the relationships between volume per unit area, Lorey’s average height, basal area, quadratic mean diameter, and density, is developed to address these inconsistencies. Previous results showed that applying the systems approach provided reasonable and compatible estimates and eliminated inconsistency issues among forest attributes. This study evaluates application of the systems approach applied to eastern Nova Scotia using field data from a network of permanent sample plots and recent LiDAR acquisitions. The independent EFI estimates had inconsistencies of greater than 100% for basal area and implied stand-level form factor. These inconsistencies were eliminated using the systems approach. Results show that the systems approach can be scaled to larger landscape areas and that long-term field data can be leveraged to fit the allometric systems producing mathematically and biologically consistent estimates.

Assessment of natural regeneration of longleaf pine (Pinus palustris) 15 years post-regeneration control

We assessed natural regeneration of longleaf pine (Pinus palustris Mill.) using the data col-lected from the Escambia Experimental Forest in southern Alabama. Fifteen years following the regeneration control, natural regeneration of longleaf remained patchy across a wide range of site/stand conditions, with slightly more than half of all plots containing regeneration, but the den-sity of seedlings and saplings varied significantly. The abundance of seedlings ≤ 1-year-old was positively related to stand age and time since last fire, but negatively related to overstory basal area. The abundance of seedlings and saplings was positively related to stand age, but negatively related to time since last fire and overstory basal area. The probability of achieving ≥ 15,000 seedlings > 1-year-old but ≤ 1-m-tall ha-1 and ≥ 1,250 saplings > 1-m-tall ha-1 was, respectively, positively related to the ratio of time since last fire to overstory basal area and the ratio of quadratic mean diameter to site index. A longer fire interval (> two to three years) should be adopted to naturally regenerate longleaf. We did not find clear zones of exclusion present in natural regeneration even though over-story trees, seedlings and saplings tended to be repulsive spatially and > 80% grass stage seedlings and saplings occurred outside tree crowns.

Evaluation of planting design for cajuput development (Melaleuca cajuputi Powel) in KPH Bojonegoro

Development of cajuput plantation currently becomes the most important activity in KPH Bojonegoro since it provides an essential contribution to maintain the future viability of company. However, the growth performance of cajuput stand relatively varies one of which is influenced by planting design. This study aims to determine the optimum planting design for supporting cajuput stand development. It was conducted by evaluating two different planting designs that generally used for cajuput establishment, namely C1 (spacing 3 m x 1 m) and C2 (spacing 5 m x 1.5 m x 1.5 m). Five parameters were used to evaluate the growth performance and oil production of cajuput stand for each planting design, i.e., survival rate, quadratic mean diameter, basal area, harvesting biomass, and cajuput oil production. Data were collected by field measurement using a sampling plot 50 m x 50 m with six replications for each planting design. Comparison mean of cajuput growth performance between two planting designs were analyzed separately for each parameter using t-test. Results documented there were not a significant different for all parameters, except survival rate. The planting design C2 generated higher survival rate (94.9%) than planting design C1 (64.7%). The planting design C2 was recommended for cajuput development in KPH Bojonegoro. Besides requiring the lower planting density, the use of planting design C2 can optimize land utility with a similar productivity to planting design C1.

Managing plantation density through initial spacing and commercial thinning: Yield results from a 60-year-old red pine spacing trial experiment

We report on a 60-year-old Pinus resinosa spacing trial experiment located in Ontario (Canada) that included the combinations between six initial spacings (from 1.2–3.0 m) and the presence/absence of a commercial thinning (CT) regime, and their impacts on quadratic mean diameter (QMD) and stand volume yield. The CT regime, initiated at age 30, targeted a residual basal area (BA) of 38 m2 ha-1 after each of four entries. Without thinning, as initial spacing increased, QMD increased; gross and net volume production peaked in the 2.1–2.4 m spacings. With thinning, similar trends with spacing were evident for QMD, although piece sizes were larger and differences between spacing were lower. The immediate increase of average tree size caused by tree selection explained most of the differences in QMD between thinned and unthinned plots. Thinning to a common target BA resulted in similar standing volume across spacings. Cumulative gross yield was similar between spacings <2.1 m for both unthinned/thinned stands and decreased for thinned plots for wider spacings. Greater net volume production in thinned stands with the narrower spacings confirmed that mortality was captured. Lower gross and net production for wider spacings suggested that thinning resulted in under-utilized growing space.

Mean height or dominant height – what to prefer for modelling the site index of Estonian forests?

The availability of a large amount of data from reliable sources is important for forest growth modelling. A permanent plot where trees are repeatedly measured provides a clearer picture of stand alterations. Various factors, including forest management, affect forest growth and accuracy of its assessment. In Estonia, mean height as a regression height prediction at mean square diameter is commonly used in forest management practice. Alternatively, dominant height can be used. The main advantage of using dominant height instead of mean height is that the growth of dominant trees is not so strongly affected by stand density (thinning). The aim of our research was to investigate the difference between mean height and dominant height when used as stand height. The research was based on the Estonian Network of Forest Research Plots (ENFRP). As a result, we found that the average mean height change was significantly greater in the case of thinning when compared to undisturbed stand development, whereas, the average dominant height change in the case of thinning compared to undisturbed development was less significant. As a side result, we developed a regression model that can be used for calculating the dominant height of the main tree species using stand attributes (mean height, quadratic mean diameter and density) with a residual standard deviation of 0.466 m.

Stocking Diagrams for Silvicultural Guideline in Korean Pines and Japanese Larch

Appropriate management of stand density is necessary to avoid wasted growing space and overcrowding-induced self-thinning and therefore to optimize profitability. We developed a Gingrich-style stocking chart for Korean red pine (Pinus densiflora), Korean white pine (P. koraiensis), and Japanese larch (Larix kaempferi) in Korea. Datasets for even-aged stands were categorized into two censored datasets via relative density based on species-specific stand density indices to assign adequate plots for tree allometry. Censored plot data for maximum density on full stocking were used to develop A-level stocking based on mean individual tree area. In censored plot data for minimum density on full stocking, individual trees represented open-grown trees, and a crown competition factor of 100 was proposed as B-level stocking. Based on parameters estimated from allometry, stocking diagrams comprising quadratic mean diameter, number of trees, and basal area were correctly expressed. A-level stocking at the same quadratic mean diameter revealed that Korean white pine had the most trees and largest basal area, while Japanese larch had the fewest trees and smallest basal area. In contrast, B-level stocking disclosed that Japanese larch had the most trees and basal area, whereas Korean white pine had the fewest trees and smallest basal area. The stocking diagrams suggest that silvicultural treatments for these species should be species-specific.

The development of allometric systems of equations for compatible area-based LiDAR-assisted estimation

Light detection and ranging (LiDAR) is used to estimate tree, stand and forest characteristics across large geographic areas. In most analyses, several independent LiDAR-based allometric equations are built to predict various forest attributes. When each forest attribute is estimated independently, there is potential for predictions of forest attributes that are not mathematically or biologically consistent. Combined allometric equations can be considered a system of equations describing the stand structure. Mathematically compatible and biologically meaningful estimates can be derived by estimating key structural variables and solving for other components, rather than estimating each forest attribute separately and independently. In this study, we propose the development of a system of allometric equations describing the relationship between volume per unit area, Lorey’s average height, basal area, quadratic mean diameter (QMD) and density. The system of allometric equations is derived from extensive field data. Key structural attributes are predicted using LiDAR metrics, and the remaining structural variables are solved for using the system of allometric equations. Predictions of structural attributes from the system of allometric equations are compared with predictions from independent LiDAR-derived prediction equations. Results showed that applying the systems approach can provide reasonable and compatible estimates with lower required sample sizes, especially when multiple attributes need to be considered simultaneously. Testing the portability of the systems approach in more complex stand structures and across different LiDAR acquisitions will be required in the future.

Modelling outer- and inner-crown profiles based on tree status and cardinal directions in relation to competition for Larix kaempferi plantations in northeastern China

Using the branch data from 90 sample trees, we developed novel models of outer- and inner-crown profiles for the northern, eastern, southern, and western sides of planted Larix kaempferi (Lam.) Carrière trees in northeastern China via the integration of competition indices (CIs) based on nonlinear marginal regression (NMR). We also used nonparametric boundary regression (NBR) to model the crown-profile boundary. The largest crown radius and inflection points of sample trees were calculated using NBR and NMR. We determined that the CIs of the ratio of the diameter of the subject tree to the quadratic mean diameter (CI3) and ratio of the basal area of the subject tree to the mean basal area of the stand (CI5) were the best distance-independent CIs for incorporation into the models of outer- and inner-crown profiles, respectively. The CIs showed a significant effect on the outer-crown profile in all four directions for dominant, intermediate, and suppressed trees but did not show a significant effect on inner-crown profile. The outer-crown radius increased and inner-crown radius decreased with increasing CI3 and CI5, respectively. The crown profile on the northern side was the largest, which conformed to the regularity in the mean current increment of the sampled branches.