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1 July 2005 A Visual Obstruction Technique for Photo Monitoring of Willow Clumps
Chad S. Boyd, Tony J. Svejcar
Author Affiliations +
Abstract

Quantifying woody plant biomass has often proven difficult in the field for reasons that include irregular plant morphology, between-observer variability, and lack of standardized techniques. One potential solution to these challenges is the use of ground-based photographic technology. Our objective was to develop a photo-based technique that could be used to monitor changes in willow (Salix spp.) biomass over time and estimate changes in biomass associated with herbivory. We focused on young willows (≤ 2 m in height) because this size class represents a critical life history stage for establishment of willow clumps. In August 2000 and 2001, we harvested 25 willow (Salix boothii Dorn.) clumps and clamped them in front of a fluorescent orange photoboard (150 × 200 cm). Clumps were defoliated of leaves and tips of current annual stem growth (referred to as “biomass”) by hand in 4 to 7 increments and photographed before and after each removal. Images were scanned to digital format and the degree of photoboard obstruction was determined with Adobe® Photoshop® 4.0 software. Regression analysis indicated that visual obstruction of the photoboard was a good predictor of total clump biomass (r2 = 0.89, P < 0.01) as well as biomass remaining following sequential defoliations (r2 = 0.92, P < 0.01). These results suggest our technique provides a reliable index of both willow biomass and utilization within the size class of willow tested. Results might differ with larger willows and increased woody biomass. The technique minimizes observer bias and provides a permanent photo record that can be reanalyzed at a later date if necessary.

Chad S. Boyd and Tony J. Svejcar "A Visual Obstruction Technique for Photo Monitoring of Willow Clumps," Rangeland Ecology and Management 58(4), 434-438, (1 July 2005). https://doi.org/10.2111/1551-5028(2005)058[0434:AVOTFP]2.0.CO;2
Received: 10 March 2004; Accepted: 27 December 2004; Published: 1 July 2005
KEYWORDS
browsing
image analysis
revegetation
utilization
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