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1 January 2011 Field Test of Digital Photography Biomass Estimation Technique in Tallgrass Prairie
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Abstract

Fuel loading information is important for prescribed fire planning, evaluating wildfire risk, and understanding fire effects in grassland. Yet fuel loads in grasslands often go unmeasured because of the time required to clip plots and process samples, as well as limited access or proximity to a drying oven. We tested the digital photography biomass estimation technique for measuring fuel load in grasslands in two national parks in the eastern Great Plains. The method consists of using percentage image obstruction, as determined by digital photography, to estimate vegetation biomass based on a linear transformation (i.e., regressing dry clipped weights against percent digital obstruction). We used the technique with some modification and measured digital obstruction at two sites at Wilson's Creek National Battlefield, Missouri (WICR), and three sites at Tallgrass Prairie National Preserve, Kansas (TAPR). The method did not result in strong correlations at either of the two sites at WICR (Site 1: r2  =  0.02; Site 2: r2  =  0.32), but performed relatively well at TAPR (Site 1 [< 1 yr since burn]: r2  =  0.82; Site 2 [2 yr since burn]: r2  =  0.57; Site 3 [1 yr since burn]: r2  =  0.88). Linear regressions for the three sites at TAPR did not differ in slope (P > 0.05). In general, the denser the vegetation, the weaker the relationship between the vegetation biomass of clip plots and the percentage image obstruction of digital images. The digital photography technique may not be useful for estimating fuel loads in grasslands with relatively high biomass (> 80 g · 0.1 m−2) or digital image obstruction > 50%. Large amounts of litter may also potentially reduce the accuracy of the technique.

Sherry A. Leis and Lloyd W. Morrison "Field Test of Digital Photography Biomass Estimation Technique in Tallgrass Prairie," Rangeland Ecology and Management 64(1), 99-103, (1 January 2011). https://doi.org/10.2111/REM-D-09-00180.1
Received: 30 November 2009; Accepted: 1 September 2010; Published: 1 January 2011
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