1. The growing pace of environmental change has increased the need for large‐scale monitoring of biodiversity. Declining intraspecific genetic variation is likely a critical factor in biodiversity loss, but is especially difficult to monitor: assessments of genetic variation are commonly based on measuring allele pools, which requires sampling of individuals and extensive sample processing, limiting spatial coverage. Alternatively, imaging spectroscopy data from remote platforms may hold the potential to reveal genetic structure of populations. In this study, we investigated how differences detected in an airborne imaging spectroscopy time series correspond to genetic variation within a population of Fagus sylvatica under natural conditions.
2. We used multi‐annual APEX (Airborne Prism Experiment) imaging spectrometer data from a temperate forest located in the Swiss midlands (Laegern, 47°28'N, 8°21'E), along with microsatellite data from F. sylvatica individuals collected at the site. We identified variation in foliar reflectance independent of annual and seasonal changes which we hypothesize is more likely to correspond to stable genetic differences. We established a direct connection between the spectroscopy and genetics data by using partial least squares (PLS) regression to predict the probability of belonging to a genetic cluster from spectral data.
3. We achieved the best genetic structure prediction by using derivatives of reflectance and a subset of wavebands rather than full‐analyzed spectra. Our model indicates that spectral regions related to leaf water content, phenols, pigments, and wax composition contribute most to the ability of this approach to predict genetic structure of F. sylvatica population in natural conditions.
4. This study advances the use of airborne imaging spectroscopy to assess tree genetic diversity at canopy level under natural conditions, which could overcome current spatiotemporal limitations on monitoring, understanding, and preventing genetic biodiversity loss imposed by requirements for extensive in situ sampling.

中文翻译：

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从机载成像光谱时间序列中得出的温带森林中的青青冈种群的种内遗传变异。

1. 随着环境变化步伐的加快，对生物多样性进行大规模监测的需求也越来越大。种内遗传变异的下降可能是造成生物多样性丧失的关键因素，但尤其难以监测：对遗传变异的评估通常基于对等位基因库的测量，这需要对个体进行采样并进行大量的样品处理，从而限制了空间覆盖范围。或者，来自远程平台的成像光谱数据可能具有揭示种群遗传结构的潜力。在这项研究中，我们调查了在自然条件下，机载成像光谱时间序列中检测到的差异如何对应于Fagus sylvatica种群内的遗传变异。
2. 我们使用了来自瑞士中部（Laegern，47°28'N，8°21'E）的温带森林的多年期APEX（机载棱镜实验）成像光谱仪数据，以及从F. sylvatica收集的微卫星数据网站。我们确定了叶片反射率的变化，独立于我们假设更可能对应于稳定遗传差异的年度和季节性变化。我们通过使用偏最小二乘（PLS）回归从光谱数据预测属于遗传簇的概率，在光谱学和遗传数据之间建立了直接联系。
3. 通过使用反射率导数和一部分波段而不是全部分析的光谱，我们获得了最佳的遗传结构预测。我们的模型表明，与叶片含水量，酚，色素和蜡组成有关的光谱区域对该方法预测自然条件下西番莲种群遗传结构的能力贡献最大。
4. 这项研究推进了使用航空成像光谱技术在自然条件下评估冠层水平树木遗传多样性的方法，这可以克服当前时空的限制，即监测，了解和防止因广泛的原地采样而造成的遗传生物多样性丧失。