Andrew N. Gray

GAP SIZE, WITHIN-GAP POSITION AND CANOPY STRUCTURE EFFECTS ON CONIFER SEEDLING ESTABLISHMENT

1 Emergence, establishment and growth of Abies amabilis, Pseudotsuga menziesii and Tsuga heterophylla were studied for 2 years in variously sized canopy gaps created in four stands on the west slope of the Cascade Range in central Oregon and southern Washington, USA. Seedlings originating from seeds sown on controlled microsites were compared with natural seed rain. 2 Seedling establishment was greater in gaps than in closed-canopy areas, but was relatively low in portions of large gaps exposed to direct solar radiation, particularly for Tsuga. Some evidence of gap partitioning by regenerating seedlings was found, though all species were most abundant in shaded portions of gaps. 3 Seedling size increased with gap size, and was greatest at gap centres. Pseudotsuga growth was relatively low except in the largest gaps, Tsuga growth increased dramatically with gap size, and Abies growth responded the least to gap size. 4 Seedling establishment and growth differed among the four stands. Establishment in closed-canopy areas was lowest in stands with dense conifer canopies relatively close to the forest floor. Natural establishment of Tsuga in gaps was very low in mature stands but abundant in old-growth stands, reflecting differences in seed rain. 5 Silviculturally created openings may accelerate the development of multiple canopy layers in mature forests, but gap size and the availability of shade-tolerant tree seeds will also control the rate and spatial pattern of canopy development.

Vegetation and ecological characteristics of mixed-conifer and Red Fir forests at the Teakettle Experimental Forest

References Anonymous. 1970. Recommendations for an international standard for a mapping method in bird census work.

Influence of light and soil moisture on Sierran mixed-conifer understory communities

Sierra Nevada forests have high understory species richness yet we do not know which site factors influence herb and shrub distribution or abundance. We examined the understory of an old-growth mixed-conifer Sierran forest and its distribution in relation to microsite conditions. The forest has high species richness (98 species sampled), most of which are herbs with sparse cover and relatively equal abundance. Shrub cover is highly concentrated in discrete patches. Using overstory tree cover and microsite environmental conditions, four habitats were identified; tree cluster, partial canopy, gap, and rock/shallow soil. Herb and shrub species were strongly linked with habitats. Soil moisture, litter depth and diffuse light were the most significant environmental gradients influencing understory plant distribution. Herb cover was most strongly influenced by soil moisture. Shrub cover is associated with more diffuse light, less direct light, and sites with lower soil moisture. Herb richness is most affected by conditions which influence soil moisture. Richness is positively correlated with litter depth, and negatively correlated with direct light and shrub cover. Disturbance or management practices which change forest floor conditions, shallow soil moisture and direct light are likely to have the strongest effect on Sierran understory abundance and richness.

A review of the challenges and opportunities in estimating above ground forest biomass using tree-level models.

Accurate biomass measurements and analyses are critical components in quantifying carbon stocks and sequestration rates, assessing potential impacts due to climate change, locating bio-energy processing plants, and mapping and planning fuel treatments. To this end, biomass equations will remain a key component of future carbon measurements and estimation. As researchers in biomass and carbon estimation, we review the present scenario of aboveground biomass estimation, focusing particularly on estimation using tree-level models and identify some cautionary points that we believe will improve the accuracy of biomass and carbon estimates to meet societal needs. In addition, we discuss the critical challenges in developing or calibrating tree biomass models and opportunities for improved biomass. Some of the opportunities to improve biomass estimate include integration of taper and other attributes and combining different data sources. Biomass estimation is a complex process, when possible, we should make use of already available resources such as wood density and forest inventory databases. Combining different data-sets for model development and using independent data-sets for model verification will offer opportunities to improve biomass estimation. Focus should also be made on belowground biomass estimation to accurately estimate the full forest contribution to carbon sequestration. In addition, we suggest developing comprehensive biomass estimation methods that account for differences in site and stand density and improve forest biomass modeling and validation at a range of spatial scales.

Evaluation of sampling strategies to estimate crown biomass

BackgroundDepending on tree and site characteristics crown biomass accounts for a significant portion of the total aboveground biomass in the tree. Crown biomass estimation is useful for different purposes including evaluating the economic feasibility of crown utilization for energy production or forest products, fuel load assessments and fire management strategies, and wildfire modeling. However, crown biomass is difficult to predict because of the variability within and among species and sites. Thus the allometric equations used for predicting crown biomass should be based on data collected with precise and unbiased sampling strategies. In this study, we evaluate the performance different sampling strategies to estimate crown biomass and to evaluate the effect of sample size in estimating crown biomass.MethodsUsing data collected from 20 destructively sampled trees, we evaluated 11 different sampling strategies using six evaluation statistics: bias, relative bias, root mean square error (RMSE), relative RMSE, amount of biomass sampled, and relative biomass sampled. We also evaluated the performance of the selected sampling strategies when different numbers of branches (3, 6, 9, and 12) are selected from each tree. Tree specific log linear model with branch diameter and branch length as covariates was used to obtain individual branch biomass.ResultsCompared to all other methods stratified sampling with probability proportional to size estimation technique produced better results when three or six branches per tree were sampled. However, the systematic sampling with ratio estimation technique was the best when at least nine branches per tree were sampled. Under the stratified sampling strategy, selecting unequal number of branches per stratum produced approximately similar results to simple random sampling, but it further decreased RMSE when information on branch diameter is used in the design and estimation phases.ConclusionsUse of auxiliary information in design or estimation phase reduces the RMSE produced by a sampling strategy. However, this is attained by having to sample larger amount of biomass. Based on our finding we would recommend sampling nine branches per tree to be reasonably efficient and limit the amount of fieldwork.

Adaptive ecosystem management in the Pacific Northwest: a case study from Coastal Oregon.

Introduction Context of the Northern Coast Range AMA Late-successional and Old-growth Forests Characteristics and features Issues Implementation Aquatic Ecosystems, Salmon, and Riparian Areas Characteristics and features Issues Implementation Social and Economic Involvement Issues Implementation Ecosystem Management Issues Implementation Discussion Adaptive management process Barriers to adaptive management Prospects for adaptive management Responses to this Article Acknowledgments Literature Cited

Soil Properties in Old-Growth Douglas-Fir Forest Gaps in the Western Cascade Mountains of Oregon

Abstract This was a study of vegetation and soil properties in tree-fall gaps in a coniferous forest of the Pacific Northwest. It had three objectives: (1) to determine if there are correlations between above-ground vegetation and below-ground soil properties within large 50 m diameter gaps, (2) to determine how large gaps influence forest soils compared with non-gap soils, and (3) to measure the effects of differently sized gaps on gap soils. To address these objectives, circular canopy gaps were created in old-growth Douglas-fir forests of the H. J. Andrews Experimental Forest in the western Oregon Cascade Mountains. To address the first objective, within-gap soil spatial patterns were compared with above ground distributions of both vegetation and large woody debris in two large gaps. Spatial and Pearson correlation analyses showed no consistent correlations between soil characteristics and above ground vegetation and coarse woody debris. With reference to the second objective, statistically significant differences between gap and non-gap soil characteristics were observed. Soil moisture, temperature and denitrification potentials were all elevated in forest 50 m diameter gaps and litter depth, labile C, soil respiration, &bgr;-gluosidase activity, and ectomytcorrhizal mat concentrations were all reduced. Comparisons between north and south gap soils, showed significant differences in soil characteristics in one but not the other 50 m gap. The third objective was addressed by documenting gap size effects on differences between gap and non gap soil characteristics in two gaps each of 10, 20, 30, and 50 m diameter. Differences between gap and nongap soil moisture, litter depth and ectomycorrhizal mat coverages were essentially the same regardless of gap size. Soil respiration rates and soil organic matter concentrations were similar in 10 m gaps but both lower in gaps 20 m and larger.

Effect of inventory method on niche models: Random versus systematic error

Abstract Data from large-scale biological inventories are essential for understanding and managing Earths ecosystems. The Forest Inventory and Analysis Program (FIA) of the U.S. Forest Service is the largest biological inventory in North America; however, the FIA inventory recently changed from an amalgam of different approaches to a nationally-standardized approach in 2000. Full use of both data sets is clearly warranted to target many pressing research questions including those related to climate change and forest resources. However, full use requires lumping FIA data from different regionally-based designs (pre-2000) and/or lumping the data across the temporal changeover. Combining data from different inventory types must be approached with caution as inventory types represent different probabilities of detecting trees per sample unit, which can ultimately confound temporal and spatial patterns found in the data. Consequently, the main goal of this study is to evaluate the effect of inventory on a common analysis in ecology, modeling of climatic niches (or species-climate relations). We use non-parametric multiplicative regression (NPMR) to build and compare niche models for 41 tree species from the old and new FIA design in the Pacific coastal United States. We discover two likely effects of inventory on niche models and their predictions. First, there is an increase from 4 to 6% in random error for modeled predictions from the different inventories when compared to modeled predictions from two samples of the same inventory. Second, systematic error (or directional disagreement among modeled predictions) is detectable for 4 out of 41 species among the different inventories: Calocedrus decurrens , Pseudotsuga menziesii , and Pinus ponderosa , and Abies concolor . Hence, at least 90% of niche models and predictions of probability of occurrence demonstrate no obvious effect from the change in inventory design. Further, niche models built from sub-samples of the same data set can yield systematic error that rivals systematic error in predictions for models built from two separate data sets. This work corroborates the pervasive and pressing need to quantify different types of error in niche modeling to address issues associated with data quality and large-scale data integration.

Washington's forest resources, 2002-2006: five-year Forest Inventory and Analysis report.

This report highlights key findings from the most recent (2002-2006) data collected by the Forest Inventory and Analysis Program across all ownerships in Washington. We present basic resource information such as forest area, land use change, ownership, volume, biomass, and carbon sequestration; structure and function topics such as biodiversity, older forests, dead wood, and riparian forests; disturbance topics such as insects and diseases, fire, invasive plants, and air pollution; and information about the forest products industry in Washington, including data on tree growth and mortality, removals for timber products, and nontimber forest products. The appendixes describe inventory methods and design in detail and provide summary tables of data and statistical error for the forest characteristics sampled.

Changes in land use and housing on resource lands in Washington state, 1976–2006

Changes in human land use patterns have wide-ranging social, economic and ecological implications. How urban and residential areas develop to accommodate population increase can have varying effects on forest and agricultural production from resource lands. Estimates of the amount and type of land use change differ substantially with definitions and analytical methods used. The purpose of this study was to apply a robust manual image classification method to assess changes in land use and housing density across Washington state for a 30-year period. Digital imagery from 1976, 1994, and 2006 was classified to land use, classifications were assigned to a systematic-random grid of 44,554 photointerpretation points on nonfederal lands, and houses were identified within 80-ac circles around each nonurban point. Population in the state increased by 2.5 million people (66 percent) over the 30-year period, during which time 1.16 million acres were converted from forest and agriculture land use classes to residential and urban land uses. The greatest changes were in western Washington, where forest lands declined at a rate of 0.2 percent per year and intensive agricultural lands declined at a rate of 0.7 percent per year. Twenty percent of nonfederal land in western Washington was in developed land uses in 2006. The density of housing structures on lands that remained in forest and agricultural land uses also increased over the period of interest, particularly in areas close to developed land uses. The rate of housing increase on resource lands was greater from 1994 to 2006 than from 1976 to 1994 in eastern Washington, but declined in western Washington. This method of assessing land use change compared favorably with other approaches, and had the advantage that it could be applied consistently to a longer period of time and allowed detailed assessment of patterns at local scales.