School of Geography, Planning and Spatial Sciences, University of Tasmania, Sandy Bay, Tasmania, Australia.
School of Biological Sciences, University of Tasmania, Sandy Bay, Tasmania, Australia.
Plant Cell Environ. 2024 Dec;47(12):4992-5006. doi: 10.1111/pce.15083. Epub 2024 Aug 9.
Drought is one of the main factors contributing to tree mortality worldwide and drought events are set to become more frequent and intense in the face of a changing climate. Quantifying water stress of forests is crucial in predicting and understanding their vulnerability to drought-induced mortality. Here, we explore the use of high-resolution spectroscopy in predicting water stress indicators of two native Australian tree species, Callitris rhomboidea and Eucalyptus viminalis. Specific spectral features and indices derived from leaf-level spectroscopy were assessed as potential proxies to predict leaf water potential (Ψ), equivalent water thickness (EWT) and fuel moisture content (FMC) in a dedicated laboratory experiment. New spectral indices were identified that enabled very high confidence linear prediction of Ψ for both species (R > 0.85) with predictive capacity increasing when accounting for a breakpoint in the relationships using segmented regression (E. viminalis, R > 0.89; C. rhomboidea, R > 0.87). EWT and FMC were also linearly predicted to a high accuracy (E. viminalis, R > 0.90; C. rhomboidea, R > 0.80). This study highlights the potential of spectroscopy as a tool for predicting measures of plant water noninvasively, enabling broader applications for monitoring and managing plant water stress.
干旱是导致全球树木死亡的主要因素之一,在气候变化的背景下,干旱事件将变得更加频繁和剧烈。量化森林的水分胁迫对于预测和理解它们对干旱引起的死亡率的脆弱性至关重要。在这里,我们探索了高分辨率光谱学在预测两种澳大利亚本地树种(Callitris rhomboidea 和 Eucalyptus viminalis)水分胁迫指标中的应用。从叶片水平的光谱中得出的特定光谱特征和指数被评估为预测叶片水势(Ψ)、等效水厚(EWT)和燃料水分含量(FMC)的潜在替代物,这是在专门的实验室实验中进行的。确定了新的光谱指数,这些指数能够非常高置信度地预测两种物种的 Ψ(R > 0.85),并且当使用分段回归考虑关系中的断点时,预测能力会增加(E. viminalis,R > 0.89;C. rhomboidea,R > 0.87)。EWT 和 FMC 也可以高精度地进行线性预测(E. viminalis,R > 0.90;C. rhomboidea,R > 0.80)。本研究强调了光谱学作为一种非侵入式预测植物水分措施的工具的潜力,从而能够更广泛地应用于监测和管理植物水分胁迫。