Kasuya Research Forest, Kyushu University, 394 Tsubakuro, Sasaguri, Fukuoka, Japan.
School of Forestry and Resource Conservation, National Taiwan University, Roosevelt st 4-1, Taipei city, Taiwan.
Tree Physiol. 2018 Dec 1;38(12):1927-1938. doi: 10.1093/treephys/tpy124.
Clarifying the dynamics of fine roots is critical to understanding carbon and nutrient cycling in forest ecosystems. An optical scanner can potentially be used in studying fine-root dynamics in forest ecosystems. The present study examined image analysis procedures suitable for an optical scanner having a large (210 mm × 297 mm) root-viewing window. We proposed a protocol for analyzing whole soil images obtained by an optical scanner that cover depths of 0-210 mm. We tested our protocol using six observers with different experience in studying roots. The observers obtained data from the manual digitization of sequential soil images recorded for a Bornean tropical forest according to the protocol. Additionally, the study examined the potential tradeoff between the soil image size and accuracy of estimates of fine-root dynamics in a simple exercise. The six observers learned the protocol and obtained similar temporal patterns of fine-root growth and biomass with error of 10-20% regardless of their experience. However, there were large errors in decomposition owing to the low visibility of decomposed fine roots. The simple exercise revealed that a smaller root-viewing window (smaller than 60% of the original window) produces patterns of fine-root dynamics that are different from those for the original window size. The study showed the high applicability of our image analysis approach for whole soil images taken by optical scanners in estimating the fine-root dynamics of forest ecosystems.
阐明细根动态对于理解森林生态系统中的碳和养分循环至关重要。光学扫描仪可用于研究森林生态系统中的细根动态。本研究探讨了适用于具有较大（210mm×297mm）根视窗的光学扫描仪的图像分析程序。我们提出了一种用于分析整个土壤图像的方案，这些图像是通过光学扫描仪获得的，深度覆盖 0-210mm。我们使用六位具有不同根系研究经验的观察者来测试我们的方案。这些观察者根据方案，从根据协议记录的顺序土壤图像的手动数字化中获取数据。此外，该研究还在一项简单的练习中检验了土壤图像大小和细根动态估计准确性之间的潜在权衡。六位观察者学习了该方案，并获得了类似的细根生长和生物量的时间模式，误差在 10-20%之间，无论其经验如何。然而，由于分解的细根可见度低，分解过程中存在较大误差。简单的练习表明，较小的根视窗（小于原始视窗的 60%）会产生与原始视窗大小不同的细根动态模式。该研究表明，我们的图像分析方法对于通过光学扫描仪获取的整个土壤图像在估计森林生态系统的细根动态方面具有很高的适用性。
