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 m²) estimation (PLE) and quadrat-level (1 m²) estimation (QLE)?

中文翻译：

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火后针叶树更新阻碍了亚高山森林植被下层植物覆盖的数字估计

问题：火灾后对林下（非树木）植物覆盖的可靠估计对于评估早期森林群落恢复至关重要。摄影数字图像分析 (DIA) 经常用于单层植被，因为与观察者视觉估计相比，它具有更高的客观性和可重复性；然而，它在多层森林植被中的功效可能会受到影响，其中各种视觉障碍物（粗倒木 [CDW]、针叶树再生和阴影）可能会隐藏数字图像中的植物覆盖。我们询问植被复杂性是否会影响由 DIA 相对于两种视觉方法估计的植物覆盖率：地块级 (20 m ² ) 估计 (PLE) 和样方级 (1 m ² ) 估计 (QLE)？