Different management regimes consisting of range of site indices and planting densities were simulated to evaluate price premiums required for growing high-quality southern pines across the southern United States. Optimal management regimes were identified maximizing the land expectation value. Growing high-quality pines on longer rotations are economically feasible, however, forest landowners need premiums which ranged from $1.40/ton to $9.81/ton for 10-year rotation extension and increased significantly with rotation ages. In uneven-aged management, price premiums for 5-year cutting cycle extension ranged from $1.75/ton to $2.25/ton. Additionally, sawmill’s willingness-to-pay price premiums for high-quality pine sawtimber were calculated using a mail survey. Sawmills showed a considerable interest in paying price premiums which ranged from $4.22/ton to $12.98/ton. Factors affecting mean WTP price premiums were sawlog size, procurement radius, grade, mill’s capacity, and employees. These findings will help landowners in deciding whether to extend rotation ages of their forest for growing higher quality pines.

Forest management practices emphasizing stand structural complexity are of interest across the northern forest region of the United States because of their potential to enhance carbon storage. Our research is nested within a long-term study evaluating how silvicultural treatments promoting late-successional forest characteristics affect aboveground biomass development in northern hardwood forests. We are testing the hypothesis that biomass development (carbon storage) will be greater in structural complexity enhancement (SCE) treatments when compared to conventional uneven-aged treatments. SCE treatments were compared against selection systems (single-tree and group) modified to retain elevated structure. Manipulations and controls were replicated across 2-hectare treatment units at two study areas in Vermont, USA. Data on aboveground biomass pools (live trees and coarse woody material, standing dead and downed wood) were collected pre- and post-harvest then again a decade later in 2013. Species group-specific allometric equations were used to estimate live and standing dead biomass and downed log biomass was estimated volumetrically. We used Forest Vegetation Simulator to project "no-treatment" baselines specific to treatment units, allowing measured carbon responses to be normalized relative to differences in site-specific characteristics and pre-treatment conditions. Results indicate that 10 years post-harvest biomass development and carbon storage were greatest in SCE treatments compared to conventional treatments, with the greatest increases in coarse woody material (CWM) pools. Structural complexity enhancement treatments contained 12.67 Mg ha-1 carbon in CWM compared to 6.62 Mg ha-1 in conventional treatments and 8.84 Mg ha-1 in areas with no treatment. Percentage differences between post-harvest carbon and baseline values indicate that carbon pool values in SCE treatments returned closest to pre-harvest or untreated levels over conventional treatments. Total carbon storage in SCE aboveground pools was 15.90% below baseline conditions compared to 44.94% less in conventionally treated areas (P = 0.006). Results from CART models indicated treatment as the strongest predictor of aboveground C storage followed by site-specific variables, suggesting a strong influence of both on carbon pools. Structural enhancement treatments have potential to increase carbon storage in managed northern hardwoods based on these results. They offer an alternative for sustainable management integrating carbon, associated climate change mitigation benefits, and late-successional forest structure.

The Forest Vegetation Simulator (FVS) is a growth and yield modeling system widely-used for predicting stand and tree-level attributes for management and planning applications in North American forests. The accuracy of FVS predictions for a range of tree and stand level attributes depends a great deal on the performance of the diameter increment model and its predictions of change in diameter at breast height (DBH) over time. To address the challenge of predicting growth in highly variable and geographically expansive forest systems, FVS was designed to include an internal calibration algorithm that makes use of growth observations, when available, from permanent inventory plots. The basic idea is that observed growth rates on a collection of remeasured trees are used to adjust or "calibrate" FVS diameter growth predictions. Therefore, DBH modeling was the focus of this investigation. Five methods were proposed for local calibration of individual tree DBH growth predictions and compared to two sets of results generated without calibration. Data from the US Forest Service's Forest Inventory and Analysis (FIA) program were used to test the methods for eleven widely-distributed forest tree species in Virginia. Two calibration approaches were based on median prediction errors from locally-observed DBH increments spanning a five year average time interval. Two were based on simple linear regression models fitted to the locally-observed prediction errors, and one method employed a mixed effects regression model with a random intercept term estimated from locally-observed DBH increments. Data witholding, specifically a leave-one-out cross-validation was used to compare results of the methods tested. Results showed that any of the calibration approaches tested in general led to improved accuracy of DBH growth predictions, with either of the median-based methods or regression based methods performing better than the random-effects-based approach. Equivalence testing showed that median or regression-based local calibration methods met error tolerances within ± 12% of observed DBH increments for all species with the random effects approach meeting a larger tolerance of ± 17%. These results showed improvement over uncalibrated models, which failed to meet tolerances as high as ± 30% for some species in a newly-fitted DBH growth model for Virginia, and as high as ± 170% for an existing model fitted to data from a much larger region of the Southeastern United States. Local calibration of regional DBH increment models provides an effective means of substantially reducing prediction errors when a relatively small set of observations are available from local sources such as permanent forest inventory plots, or the FIA database. / MS / The Forest Vegetation Simulator (FVS) is a growth and yield model widely-used for predicting stand dynamics, management and decision support in North American forests. Diameter increment is a major component in modeling tree growth. The system of integrated analytical tools in FVS is primarily based on the performance of the diameter increment model and the subsequent use of predicted in diameter at breast height (DBH) over time in forecasting tree attributes. To address the challenge of predicting growth in highly variable and geographically expansive forest systems, FVS was designed to include an internal calibration algorithm that makes use of growth observations, when available, from permanent inventory plots. The basic idea was that observed growth rates on a small set of remeasured trees are used to adjust or “calibrate” FVS growth predictions. The FVS internal calibration was the subject being investigated here. Five alternative methods were proposed attributed to a specific site or stand of interest and compared to two sets of results, which were based on median prediction errors, generated without calibration. Results illustrated that median-based methods or regression based methods performed better than the random-effects-based approach using independently observed growth data from Forest Service FIA re-measurements in Virginia. Local calibration of regional DBH increment models provides an effective means of substantially reducing prediction errors. The results of this study should also provide information to evaluate the efficiency of FVS calibration alternatives and a possible method for future implementation.

Patch clearcutting can be put to effective use for landowners with relatively small stands of timber. This project was designed to determine how clearcut opening size and mid-rotation crop tree release affects the value and volume of sawtimber at the end of rotation. In 1960 patch clearcuts were established in three different diameters, 50ft (.05ac), 150ft (.41ac), and 250ft (1.13ac). Current stand data (2011) was collected to determine trees per acre, basal area, average tree diameter, volume, and value. These data were input into a growth simulator to determine future trees per acre, basal area, average tree diameter, volume, and value with a crop tree release treatment and a control to 2061. The 50ft openings yielded little merchantable volume at mid-rotation and were primarily composed by shade tolerant species. In the 150ft and 250ft openings, there was better species diversity and an increase in sawtimber volume and value. Using openings of 150ft or greater, landowners can regenerate commercially important species and manage their forests to produce valued timber and maintain aesthetics.

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