Post‐fire conifer regeneration hinders digital estimation of understorey plant cover in subalpine forest vegetation. Issue 3 (26th September 2021)

• Record Type: Journal Article
• Authors: Wheeler, Brandi E.; Andrade, Andrew J.; Pansing, Elizabeth R.; Tomback, Diana F.
• Editors: Feilhauer, Hannes
• Is Part Of: Applied vegetation science. Volume 24:Issue 3(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-26
• Subjects: 1988 Yellowstone fires -- digital image analysis -- seral vegetation -- subalpine forest -- understorey plant cover -- visual estimation; Plant ecology -- Periodicals; Plant communities -- Periodicals; Plant populations -- Periodicals; Nature -- Effect of human beings on -- Periodicals; 581.705
• DOI: 10.1111/avsc.12609
• Languages: English
• ISSNs: 1402-2001

Abstract

Abstract: Question: Reliable estimates of understorey (non‐tree) plant cover following fire are essential to assess early forest community recovery. Photographic digital image analysis (DIA) is frequently used in seral, single‐strata vegetation, given its greater objectivity and repeatability compared to observer visual estimation; however, its efficacy in multi‐strata forest vegetation may be compromised, where various visual obstructions (coarse downed wood [CDW], conifer regeneration, and shadows) may conceal plant cover in the digital imagery. We asked whether vegetation complexity influences plant cover estimated by DIA relative to two visual methods: plot‐level (20 m 2 ) estimation (PLE) and quadrat‐level (1 m 2 ) estimation (QLE)? Location: Greater Yellowstone Ecosystem, USA. Methods: We estimated understorey plant cover in subalpine forest vegetation on permanent plots ( n = 141) at two study areas ~30 years after the 1988 Yellowstone fires to: (a) assess differences in visual obstructions between study areas in our digital imagery; (b) compare digital to visual estimates of plant cover; and (c) determine relationships between estimated plant cover and visual obstructions measured in situ. Results: Percent conifer regeneration pixels differed significantly (odds ratio = 8.34) between study areas which represented the greatest difference in visual obstructions. At the study area with lower conifer pixels, DIA estimated 9% (95% confidence interval [CI] = 3%–14%) and 16% (95% CI = 10%–21%) more understorey plant cover than PLE or QLE, respectively, but had comparable variability. At the study area with higher conifer pixels, DIA estimated 28% (95% CI = 24%–32%) and 22% (95% CI = 18%–26%) less understorey plant cover than PLE or QLE, respectively, and had more variability. Furthermore, plot‐level subcanopy regeneration (height>137 cm) density was negatively associated with digitally derived plant cover but showed no relationship with visually derived plant cover. Conclusions: Post‐fire conifer regeneration hindered the efficacy of DIA in estimating understorey plant cover. Digital estimation is advantageous in single‐strata vegetation but should not be used in complex, multi‐strata vegetation. Abstract : We compared the efficacy of photographic digital image analysis (DIA) and two observer visual methods in estimating understorey (non‐tree) plant cover following fire. In simple vegetation, DIA was more efficacious than either visual method. However, in multi‐strata vegetation, DIA underestimated plant cover, which was concealed by conifer regeneration. Site‐specific vegetation complexity should inform the use of digital or visual estimation