Monitoring stand structure in mature coastal Douglas-fir forests: effect of plot size

National and regional interest in the distribution and trends of forest habitat structure and diversity have placed demands on forest inventories for accurate stand-level data. A primary need in the coastal Pacific Northwest of the United States is information on the extent and rate of development of mature forest structure. The objective of this study was to evaluate alternative sampling schemes within a standard national cluster plot design able to efficiently determine density of large live trees and snags, tree mortality, and tree species richness. A simulation approach used stem maps from 19 permanent forest plots dominated by mature Pseudotsuga menziesii (Douglas-fir) of at least I ha in size that had been sampled for up to 23 years. Clustered subplots sampling between 0.5 and 81% of the stand area were randomly located in stands to select mapped trees. Estimation error analysis compared the percent difference between sample data and full-stand values by subplot size for 30 iterations per subplot size per stand. Comparison with analyses of regional inventory plots allowed greater inference concerning results. Samples of at least 40% of a stand (four 18 m radius subplots) were required to reduce errors for estimated density of large trees (greater than or equal to 122 cm DBH) below 25% of true density at least 66% of the time. For mortality, subplots sampling at least 50% of a stand were needed to reach errors below 50% of true mortality at least 66% of the time. However, for trees < 75 cm DBH, the standard inventory sample of 0.07 ha with four 7.3 m radius subplots did meet these accuracy levels for density and mortality. Relatively large plots were required to estimate species richness within one species of true richness, particularly for the relatively diverse smaller tree size classes. Efficient sampling of species richness could use species lists, instead of measuring many small trees on large plots. Reducing sample errors to acceptable levels will increase the utility of inventory plot data to evaluate stand structure, successional development, carbon sequestration, species diversity, and ground-truth for remote sensing. (C) 2002 Elsevier Science B.V. All rights reserved.