Imaging spectroscopy is emerging as a leading remote sensing method for quantifying plant biodiversity. The spectral variation hypothesis predicts that variation in plant hyperspectral reflectance is related to variation in taxonomic and functional identity. While most studies report some correlation between spectral and field-based (i.e., taxonomic and functional) expressions of biodiversity, the observed strength of association is highly variable, and the utility in applying spectral community properties to examine environmental drivers of communities remains unknown. We linked hyperspectral data acquired by airborne imaging spectrometers with precisely geolocated field plots to examine the spectral variation hypothesis along a temperate-to-boreal forest gradient in southern Québec, Canada. First, we examine the degree of association between spectral and field-based dimensions of canopy tree composition and diversity. Second, we ask whether the relationships between field-based community properties and the environment are reproduced when using spectral community properties. We found support for the spectral variation hypothesis with the strength of association generally greater for the functional than taxonomic dimension, but the strength of relationships was highly variable and dependent on the choice of method or metric used to quantify spectral and field-based community properties. Using a multivariate approach (comparisons of separate ordinations), spectral composition was moderately well correlated with field-based composition; however, the degree of association increased when univariately relating the main axes of compositional variation. Spectral diversity was most tightly associated with functional diversity metrics that quantify functional richness and divergence. For predicting canopy tree composition and diversity using environmental variables, the same qualitative conclusions emerge when hyperspectral or field-based data are used. Spatial patterns of canopy tree community properties were strongly related to the turnover from temperate-to-boreal communities, with most variation explained by elevation. Spectral composition and diversity provide a straightforward way to quantify plant biodiversity across large spatial extents without the need for a priori field observations. While commonly framed as a potential tool for biodiversity monitoring, we show that spectral community properties can be applied more widely to assess the environmental drivers of biodiversity, thereby helping to advance our understanding of the drivers of biogeographical patterns of plant communities.

中文翻译：

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将航空高光谱数据与冠层树木生物多样性联系起来：对光谱变化假设的检验


成像光谱学正在成为量化植物生物多样性的领先遥感方法。光谱变化假说预测植物高光谱反射率的变化与分类和功能特性的变化有关。虽然大多数研究报告了生物多样性的光谱和基于实地（即分类学和功能）表达之间的一些相关性，但观察到的关联强度变化很大，并且应用光谱群落属性来检查群落环境驱动因素的效用仍然未知。我们将机载成像光谱仪获取的高光谱数据与精确地理定位的野外图联系起来，以检验加拿大魁北克省南部温带到寒带森林梯度沿线的光谱变化假设。首先，我们检查冠层树木组成和多样性的光谱维度和基于场的维度之间的关联程度。其次，我们询问在使用光谱群落属性时是否再现了基于场的群落属性与环境之间的关系。我们发现对光谱变异假设的支持，功能维度的关联强度通常大于分类维度，但关系的强度变化很大，并且取决于用于量化光谱和基于场的群落属性的方法或度量的选择。使用多变量方法（单独排序的比较），光谱成分与基于场的成分具有中等程度的相关性；然而，当单变量关联成分变化的主轴时，关联程度会增加。 光谱多样性与量化功能丰富度和差异的功能多样性指标最密切相关。为了使用环境变量预测树冠树木的组成和多样性，当使用高光谱或基于现场的数据时，会得出相同的定性结论。冠层树木群落属性的空间模式与温带到寒带群落的更替密切相关，其中大多数变化由海拔解释。光谱组成和多样性提供了一种直接的方法来量化大空间范围内的植物生物多样性，而无需先验的现场观测。虽然通常被认为是生物多样性监测的潜在工具，但我们表明，光谱群落特性可以更广泛地应用于评估生物多样性的环境驱动因素，从而有助于增进我们对植物群落生物地理模式驱动因素的理解。