Leaf aging of Amazonian canopy trees as revealed by spectral and physiochemical measurements
Leaf aging of Amazonian canopy trees as revealed by spectral and physiochemical measurements
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DOI：
10.1111/nph.13853
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发表时间：
2017-05-01
期刊：
影响因子：
9.4
通讯作者：
Gerard, France F.
中科院分区：
文献类型：
--
作者：
Chavana-Bryant, Cecilia;Malhi, Yadvinder;Gerard, France F.
叶片老化是叶片性状变化的基本驱动力，本文探讨了叶片反射率作为监测叶龄的工具，并建立了基于光谱的偏最小二乘回归（PLSR）模型。利用来自秘鲁南部12棵低地亚马逊河流域树冠树木的1099片叶子的物候学研究数据，建立了一个预测年龄的模型。水分（LWC）和磷（P-mass）含量以及单位面积叶质量（LMA）随年龄的增加而增加;叶氮（N-mass）和碳（C-mass）含量表现出单调但具有树特异性的年龄响应。我们观察到大的年龄相关的变化，叶光谱树木。与基于性状的模型相比，基于光谱的模型在预测叶龄方面更准确（R-2 = 0.86; %均方根误差（RMSE）= 33），使用单个（R-2 = 0.07-0.73; % RMSE = 7-38）和多个（R-2 = 0.76; % RMSE = 28）预测因子。基于光谱和性状的模型为光谱年龄模型奠定了生理化学基础。植被指数（维斯）包括归一化差异植被指数（NDVI）、增强植被指数2（EVI 2）、归一化差异水分指数（NDWI）和光合反射指数（PRI）都具有年龄依赖性。提供年龄证明-相关的叶片反射率变化，有重要影响的维斯用于监测冠层动态和生产力，并提出了一种新的方法来预测和监测叶龄对遥感具有重要意义。
Leaf aging is a fundamental driver of changes in leaf traits, thereby regulating ecosystem processes and remotely sensed canopy dynamics.We explore leaf reflectance as a tool to monitor leaf age and develop a spectra-based partial least squares regression (PLSR) model to predict age using data from a phenological study of 1099 leaves from 12 lowland Amazonian canopy trees in southern Peru.Results demonstrated monotonic decreases in leaf water (LWC) and phosphorus (P-mass) contents and an increase in leaf mass per unit area (LMA) with age across trees; leaf nitrogen (N-mass) and carbon (C-mass) contents showed monotonic but tree-specific age responses. We observed large age-related variation in leaf spectra across trees. A spectra-based model was more accurate in predicting leaf age (R-2 = 0.86; percent root mean square error (% RMSE) = 33) compared with trait-based models using single (R-2 = 0.07-0.73; % RMSE = 7-38) and multiple (R-2 = 0.76; % RMSE = 28) predictors. Spectra- and trait-based models established a physiochemical basis for the spectral age model. Vegetation indices (VIs) including the normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2), normalized difference water index (NDWI) and photosynthetic reflectance index (PRI) were all age-dependent.This study highlights the importance of leaf age as a mediator of leaf traits, provides evidence of age-related leaf reflectance changes that have important impacts on VIs used to monitor canopy dynamics and productivity and proposes a new approach to predicting and monitoring leaf age with important implications for remote sensing.