Lumber recovery of Douglas-fir from the Coast and Cascade Ranges of Oregon and Washington.

Willits, Susan; Fahey, Thomas D.

doi:10.2737/pnw-rp-400

Cited by 7 publications

(7 citation statements)

References 3 publications

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“…Historical changes in saw-log processing efficiency (Hodgson, 1931;Corder et al, 1972;Lane et al, 1973a, Hartman et al, 1976Willits and Fahey, 1988;Briggs, 1993) and waste disposition (Hodgson, 1931;Gedney, 1956;Cowlin and Forster, 1965;Manock et al, 1970;Corder et al, 1972;Schuldt and Howard, 1974;Bergvall et al, 1975;Hartman et al, 1976;Howard and Hiserote, 1978;Howard, 1984;Howard andWard, 1988, 1991;Larsen, 1990Larsen, , 1992 were compiled from historical summaries of the forest-products sector. In years without reported data, we used linear interpolation for estimating values.…”

Section: Lumber = Flumber Sawlogmentioning

confidence: 99%

Modeling carbon stores in Oregon and Washington forest products: 1900?1992

Harmon

Ferrell

et al. 1996

Climatic Change

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A new model, FORPROD, for estimating the carbon stored in forest products, considers both the manufacture of the raw logs into products and the fate of the products during use and disposal. Data for historical patterns of harvest, manufacturing efficiencies, and product use and disposal were used for estimating the accumulation of carbon in Oregon and Washington forest products from 1900 to 1992. Pools examined were long-and short-term structures, paper supplies, mulch, open dumps, and landfills. The analysis indicated that of the 1,692 Tg of carbon harvested during the selected period, only 396 Tg, or 23%, is currently stored. Long-term structures and landfills contain the largest fraction of that store, holding 74% and 20%, respectively. Landfills currently have the highest rates of accumulation, but total landfill stores are relatively low because they have been used only in the last 40 years. Most carbon release has occurred during manufacturing, 45% to 60% lost to the atmosphere, depending upon the year. Sensitivity analyses of the effects of recycling, landfill decomposition, and replacement rates of long-term structures indicate that changing these parameters by a factor of two changes the estimated fraction of total carbon stored less than 2%.

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Section: Lumber = Flumber Sawlogmentioning

confidence: 99%

Modeling carbon stores in Oregon and Washington forest products: 1900?1992

Harmon

Ferrell

et al. 1996

Climatic Change

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“…volume of long logs was based on best available information from mill utilization studies conducted by the Production of Goods and Services unit at the Pacific Northwest Research Station in Portland, Oregon, USA. Utilization of Douglas-fir was modeled on long-log equations for unmanaged stands developed by Willits and Fahey ( 1988). We based utilization of western hemlock and true fir species on regressions developed by S. Willits (personal communication) from a composite of western Oregon and Washington mill studies for western hemlock and true fir logs.…”

Section: Economic Modelmentioning

confidence: 99%

Alternative Silvicultural Regimes in the Pacific Northwest: Simulations of Ecological and Economic Effects

Hansen¹,

Garman²,

Weigand³

et al. 1995

Ecological Applications

124

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New silivicultural strategies to sustain both ecological and human communities are being developed and implemented on federal forest lands in the Pacific Northwest (PNW) United States. Two important stand‐level components of the new silviculture regimes are rotation age and retention level of live trees in harvest units. Ecologists have suggested that canopy tree retention and longer rotations will create patterns of stand structure in managed forest that are similar to those in natural forests, and promote long‐term ecological productivity and biodiversity. Forest economists, however, are concerned that canopy tree retention and long rotations may reduce wood production, although the high value of large logs produced by these new silvicultural regime may compensate for reduced growth rates. We used the forest model ZELIG to perform a factorial simulation experiment on long‐term responses of ecological and economic variables to nine retention levels and four rotation lengths. ZELIG output on forest structure and composition was input to a forest economics model that calculated net value of wood products in 1989 dollars. The simulated stand data were also linked with regression equations to predict the densities of 17 bird species as a function of tree size class distribution. Five replicates of each treatment were run for the 240‐yr simulation period. Results indicated that stand structure under each of the canopy tree retention levels was more similar to the pre‐treatment natural forest than following clear‐cutting. Variation in tree size under intermediate levels of retention, however, did not reach the level of the natural forest during the simulation period. Tree species composition was strongly related to retention level and rotation age. Shade‐intolerant Douglas‐fir (Pseudotsuga menziesii) lost dominance to shade‐tolerant species under intermediate retention levels and longer rotations. Wood production decreased significantly with increasing retention level and rotation age, with a notable threshold between retention levels of 0 and 5 trees per hectare. Net wood products value did not decrease as rapidly with retention level, and did not differ much among rotation ages, because of the high value of large logs. Bird species responded individualistically to retention level and rotation age. Some had peak densities under short‐rotation clear‐cutting, but most were associated with structurally complex, closed‐canopy forest. Consequently, bird species richness increased significantly with retention level and rotation age. Within the assumptions and limitations of our models, this application provided knowledge on trends and thresholds that can help land managers to choose silvicultural regimes that best balance their management objectives. We concluded that retention level and rotation age strongly influence ecological and economic responses in PNW forests; efforts are needed to reduce uncertainty about these effects.

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“…Lumber Recovery 1988, Fahey 1983, Parry et al 1996, Willits and Fahey 1988, but in this case regressions for rough green CRP on diameter were nonsignifi cant for both Douglas-fi r (p = 0.24) and ponderosa pine (p = 0.53). This was probably because of the small sample size and narrow log SED range (3.5 to 9 inches in Douglas-fi r and 3.0 to 8 inches in ponderosa pine).…”

Section: Resultsmentioning

confidence: 99%