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    Logs are an important structural feature of forest ecosystems, and their abundance affects many resources and forest processes, including fire regimes, soil productivity, silviculture, carbon cycling, and wildlife habitat. Consequently, logs are often sampled to estimate their frequency, percent cover, volume, and weight. The line-intersect method (LIM) is one of the most widely used methods to obtain these estimates and has been shown to produce unbiased estimates of log characteristics. With the traditional LIM the diameters of each log at the point of its intersection with the sampling transect are used to estimate log characteristics. Based on a simulation study and a large set of empirical data, we found that use of intersect log diameters to define size classes provided biased estimates of log characteristics. The bias varied by diameter class. Results from the simulation study showed that log frequency and volume were overestimated in small-diameter log classes and underestimated in large diameter classes. Similarly, results from our empirical analysis showed a 40% overestimate of log volume in the smallest diameter class (15-25 cm), and a 31% underestimate of volume in the largest diameter class (>50 cm). Just as size classes of snags and trees are best defined by their diameter-at breast height (DBH), size classes of logs should be defined by their large-end diameters (LEOs). When large-end diameters of logs were used instead of diameters measured at the point of transect intersection, bias was substantially reduced or eliminated. These results indicate that line-intersect sampling could be substantially improved by including measurements of LEOs to estimate log characteristics. Our results have far-reaching implications for estimates of log characteristics, such as estimates of fuel loading and subsequent wildfire risk, carbon source and sink dynamics, silviculture, nutrient cycling, and habitat for wildlife. Without our suggested correction to line-intersect sampling, many forest resources associated with log characteristics will not be estimated accurately, affecting a plethora of log-based management and research programs.

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    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.


    Bate, Lisa J.; Torgersen, Torolf R.; Wisdom, Michael J.; Garton, Edward O. 2009. Biased estimation of forest log characteristics using intersect diameters. Forest Ecology and Management. 258: 635-640.


    coarse woody debris, down woody material, fuel management, logs, intersect diameter, line-intersect sampling, silviculture, wildlife

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