ALBERT

Description: Intertree competition indices and effects were examined in 14 uneven-aged ponderosa pine (Pinus ponderosa var. scopulorum Engelm.) stands in eastern Montana. Location, height, diameter at breast height (DBH), basal area increment, crown ratio, and sapwood area were determined for each tree (DBH 〉3.8 cm) on one stem-mapped plot (0.2-0.4 ha) in each sample stand. Based on tree locations, various competition indices were derived for each sample tree and correlated with its growth efficiency by diameter class. In addition, trends in individual tree attributes by diameter class and level of surrounding competition were determined. For trees with a DBH

Description: As signatories to the United Nation Framework Convention on Climate Change, the US has been estimating standing dead tree (SDT) carbon (C) stocks using a model based on live tree attributes. The USDA Forest Service began sampling SDTs nationwide in 1999. With comprehensive field data now available, the objective of this study was to compare field- and model-based estimates of SDT C stocks across the US to evaluate potential directions for improving National Greenhouse Gas Inventory (NGHGI) reporting and C dynamics research. Field inventory data indicated that most forests have relatively little SDT C stocks (〈1 Mg/ha), whereas large SDT C stocks (〉25 Mg/ha) are infrequent. Models used for past NGHGIs to predict SDT C stocks do not accurately reflect what was observed in inventory plots, resulting in an overestimation (~100 per cent) of SDT C stocks at the national scale. These results indicate that the current estimate of the Nation’s total forest C stock is overestimated by ~4.2 per cent due to overestimation of SDT C stocks that are a relatively small component of the total forest C stock. A field-based approach is suggested for use in future C reporting efforts to reduce estimation bias.

Description: The contribution of understorey vegetation (UVEG) to forest ecosystem biomass and carbon (C) across diverse forest types has, to date, eluded quantification at regional and national scales. Efforts to quantify UVEG C have been limited to field-intensive studies or broad-scale modelling approaches lacking field measurements. Although large-scale inventories of UVEG C are not common, species- and community-level inventories of vegetation structure are available and may prove useful in quantifying UVEG C stocks. This analysis developed a general framework for estimating UVEG C stocks by employing per cent cover estimates of UVEG from a region-wide forest inventory coupled with an estimate of maximum UVEG C across the US Lake States (i.e. Michigan, Minnesota and Wisconsin). Estimates of UVEG C stocks from this approach reasonably align with expected C stocks in the study region, ranging from 0.86 ± 0.06 Mg ha –1 in red pine-dominated to 1.59 ± 0.06 Mg ha –1 for aspen/birch-dominated forest types. Although the data employed here were originally collected to assess broad-scale forest structure and diversity, this study proposes a framework for using UVEG inventories as a foundation for estimating C stocks in an often overlooked, yet important ecosystem C pool.

Description: Soil organic carbon (SOC) is the largest terrestrial carbon (C) sink on Earth; this pool plays a critical role in ecosystem processes and climate change. Given the cost and time required to measure SOC, and particularly changes in SOC, many signatory nations to the United Nations Framework Convention on Climate Change report estimates of SOC stocks and stock changes using default values from the Intergovernmental Panel on Climate Change or country-specific models. In the United States (US), SOC in forests is monitored by the national forest inventory (NFI) conducted by the Forest Inventory and Analysis (FIA) program within the US Department of Agriculture, Forest Service. The FIA program has been consistently measuring soil attributes as part of the NFI since 2001 and has amassed an extensive inventory of SOC in forest land in the conterminous US and southeast and southcentral coastal Alaska. That said, the FIA program has been using country-specific predictions of SOC based, in part, upon a model using SOC estimates from the State Soil Geographic (STATSGO) database compiled by the Natural Resources Conservation Service. Estimates obtained from the STATSGO database are averages over large map units and are not expected to provide accurate estimates for specific locations, e.g., NFI plots. To improve the accuracy of SOC estimates in US forests, NFI SOC observations were used for the first time to predict SOC density to a depth of 100 cm for all forested NFI plots. Incorporating soil-forming factors along with observations of SOC into a new estimation framework resulted in a 75 percent (48±0.78 Mg·ha −1 ) increase in SOC densities nationally. This substantially increases the contribution of the SOC pool – from approximately 44 percent (17 Pg) of the total forest ecosystem C stocks to 56 percent (28 Pg) – in the forest C budget of the US. This article is protected by copyright. All rights reserved.

Description: National-scale forest inventories have endeavoured to include holistic measurements of forest health inclusive of attributes such as downed dead wood and tree regeneration that occur in the forest understory. Inventories may require year-round measurement of inventory plots with some of these measurements being affected by seasonal obstructions (e.g. snowpacks and seasonal flooding). In order to assess the potential effects that snow/water obstructions may have on the measurement/analysis of forest seedlings across large scales, the differences in seedling abundance between two inventory measurements (~5-year remeasurement period) and as affected by snow/water depth was ascertained using a repeated forest inventory across the eastern US. Results indicate that there is a general trend of decreasing seedling density over time (–33.16 seedlings ha –1 year –1 ) in the eastern US, with snow/water depths in excess of 15 cm significantly affecting resulting estimates of seedling abundance. Although snow/water obstruction to seedling measurement occurred on ~9 per cent of inventory plots across the eastern US, snow was a much more common situation occurring on nearly 50 per cent of plots (at time 1, 2 or both) at high latitudes (〉45°). Given the statistically significant effect of snow/water on seedling abundance estimates, tree regeneration assessments should not include observations obstructed by snow/water depths that exceed minimum seedling heights. Furthermore, seedling abundance inventories may mitigate the influence of measurement obstructions by sampling only during the summer or incorporating climate information into their sampling logistics.

Description: Stand density index (SDI) was developed to quantify relative stand density in even-aged stands. Application of SDI in uneven-aged stands has been described mathematically but not justified biologically. Diameter-class trends in SDI and sapwood area across 14 uneven-aged ponderosa pine (Pinus ponderosa Dougl. ex P. & C. Laws.) stands in eastern Montana were examined to elucidate the biological underpinnings of the SDI summation method. Results indicate that the SDI summation method is biased in its apportionment of relative stand density across diameter classes in uneven-aged ponderosa pine stands. SDI apportions greater relative density to small trees than to larger ones. Therefore, SDI may overpredict site occupancy for reverse J-shaped diameter distributions with more small trees than large ones, and it may underpredict occupancy with nonreverse J-shaped diameter distributions. Application of the SDI summation method in uneven-aged ponderosa pine stands may be biologically justified only if site occupancy diameter-class trends are taken into account when interpreting SDI values. Replacing the self-thinning scaling factor of the SDI summation method with more biologically relevant scaling relationships may create improved relative density measures for uneven-aged stands.

Description: Accurately measuring the dimensions of coarse woody debris (CWD) is critical for ensuring the quality of CWD estimates and, hence, for accurately estimating forest ecosystem attributes (e.g., CWD carbon stocks). To improve the quality of CWD dimensional measurements, the distribution of taper (ratio of change in diameter and length) and relative size (RS; ratio of length and large-end diameter) of CWD pieces across the US were examined. Additionally, an outlier identification technique was developed by predicting the median and interquartile range of taper and RS as a function of large-end diameter, length, and decay class by major species group. The median CWD taper and RS across the US were 1.268 cm/m and 0.280 m/cm, respectively, with notable outliers. The taper and RS outlier identification protocol rapidly identified nearly 3% of study observations as outliers. Incorporation of CWD taper and RS outlier identification protocols into field data recorders may allow efficient control of measurement errors during field inventories.