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Predicting redwood productivity using biophysical data, spatial statistics and site quality indicesAuthor(s): John-Pascal Berrill; Kevin L. O’Hara; Shawn Headley
Source: Gen. Tech. Rep. PSW-GTR-258. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station: 39-46
Publication Series: General Technical Report (GTR)
Station: Pacific Southwest Research Station
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DescriptionCoast redwood (Sequoia sempervirens (D. Don) Endl.) height growth and basal area growth are sensitive to variations in site quality. Site factors known to be correlated with redwood stand growth and yield include topographic variables such as position on slope, exposure, and the composite variable: topographic relative moisture index. Species composition is also a key driver of redwood stand growth and yield. We studied spatial patterns in species composition in terms of percent hardwood, and spatial patterns in topographic relative moisture index values across 109 ha (270 ac) of coast redwood forest on Jackson Demonstration State Forest in Mendocino County, California. We also examined how redwood height growth (in terms of site index) and basal area productivity varied across the study area. We performed Ordinary Kriging in ArcGIS to interpolate between plots. These continuous raster data sets were used to create contour maps to assess redwood productivity in the study area. These example applications demonstrate a potential framework and method to estimate forest growth, yield, and carbon stocks in natural forests along gradients of productivity.
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CitationBerrill, John-Pascal; O’Hara, Kevin L.; Headley, Shawn. 2017. Predicting redwood productivity using biophysical data, spatial statistics and site quality indices. In: Standiford, Richard B.; Valachovic, Yana, tech cords. Coast redwood science symposium—2016: Past successes and future direction. Proceedings of a workshop. Gen. Tech. Rep. PSW-GTR-258. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station: 39-46.
KeywordsGIS, interpolation, Kriging, semi-variance analysis, Sequoia sempervirens, uneven-aged, variogram
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