Chen Yanni, Monks Logan, Rubio Vanessa E, Cox Alexander J, Swenson Nathan G
Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, 46556 USA.
Cary Institute of Ecosystem Studies, Millbrook, New York, 12545 USA.
Commun Earth Environ. 2025;6(1):694. doi: 10.1038/s43247-025-02696-1. Epub 2025 Aug 23.
Forest diversity and dynamics are governed by the interactions between organismal function and the abiotic and biotic environment. Functional traits have been widely employed in forest ecology to estimate key functional tradeoffs related to tree performance in a given environment. Hyperspectral reflectance data are utilized in ecology to predict functional trait values at the individual tree or pixel scale on broad spatial extents, but the diversity of functions captured by these traits is limited. Here, we demonstrate a novel integration of reflectance and to gene expression data for processes of interest to ecologists. We show linkages between the expression of ecologically important genes and reflectance data and the potential to transform the depth at which ecologists can rapidly estimate functional diversity.
森林多样性和动态受生物功能与非生物及生物环境之间相互作用的支配。功能性状已在森林生态学中广泛应用，以估计与特定环境中树木表现相关的关键功能权衡。高光谱反射率数据在生态学中用于在广阔空间范围内预测单株树木或像素尺度上的功能性状值，但这些性状所涵盖的功能多样性有限。在此，我们展示了一种将反射率数据与基因表达数据进行新颖整合的方法，用于生态学家感兴趣的过程。我们揭示了具有生态重要性的基因表达与反射率数据之间的联系，以及改变生态学家能够快速估计功能多样性深度的潜力。
