Visser Marco D, Detto Matteo, Meunier Félicien, Wu Jin, Foster Jane R, Marvin David C, van Bodegom Peter M, Bongalov Boris, Nunes Matheus Henrique, Coomes David, Verbeeck Hans, Guzmán Q J Antonio, Sanchez-Azofeifa Arturo, Chandler Chris J, van der Heijden Geertje M F, Boyd Doreen S, Foody Giles M, Cutler Mark E J, Broadbent Eben N, Serbin Shawn P, Schnitzer Stefan, Rodríguez-Ronderos M Elizabeth, Sterck Frank, Medina-Vega José A, Pacala Stephen W
Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, USA.
Institute of Environmental Sciences, Leiden University, Leiden, the Netherlands.
Ecology. 2025 Apr;106(4):e70082. doi: 10.1002/ecy.70082.
Lianas, woody vines acting as structural parasites of trees, have profound effects on the composition and structure of tropical forests, impacting tree growth, mortality, and forest succession. Remote sensing could offer a powerful tool for quantifying the scale of liana infestation, provided the availability of robust detection methods. We analyze the consistency and global geographic specificity of spectral signals-reflectance across wavelengths-from liana-infested tree crowns and forest stands, examining the underlying mechanisms of these signals. We compiled a uniquely comprehensive database, including leaf reflectance spectra from 5424 leaves, fine-scale airborne reflectance data from 999 liana-infested canopies, and coarse-scale satellite reflectance data covering 775 ha of liana-infested forest stands. To unravel the mechanisms of the liana spectral signal, we applied mechanistic radiative transfer models across scales, establishing a synthesis of the relative importance of different mechanisms, which we corroborate with field data on liana leaf chemistry and canopy structure. We find a consistent liana spectral signal at canopy and stand scales across globally distributed sites. This signature mainly arises at the canopy level due to direct effects of more horizontal leaf angles, resulting in a larger projected leaf area, and indirect effects from increased light scattering in the near and short-wave infrared regions, linked to lianas' less costly leaf construction compared with trees on average. The existence of a consistent global spectral signal for lianas suggests that large-scale quantification of liana infestation is feasible. However, because the traits responsible for the liana canopy-reflectance signal are not exclusive to lianas, accurate large-scale detection requires rigorously validated remote sensing methods. Our models highlight challenges in automated detection, such as potential misidentification due to leaf phenology, tree life history, topography, and climate, especially where the scale of liana infestation is less than a single remote sensing pixel. The observed cross-site patterns also prompt ecological questions about lianas' adaptive similarities in optical traits across environments, indicating possible convergent evolution due to shared constraints on leaf biochemical and structural traits.
藤本植物，即作为树木结构寄生物的木质藤本，对热带森林的组成和结构有着深远影响，影响着树木的生长、死亡率和森林演替。如果有强大的检测方法，遥感技术可为量化藤本植物侵染规模提供有力工具。我们分析了受藤本植物侵染的树冠和林分的光谱信号（即不同波长下的反射率）的一致性和全球地理特异性，研究这些信号的潜在机制。我们编制了一个独特的综合数据库，包括5424片叶子的叶反射光谱、999个受藤本植物侵染的树冠的精细尺度机载反射数据，以及覆盖775公顷受藤本植物侵染林分的粗尺度卫星反射数据。为了解藤本植物光谱信号的机制，我们在不同尺度上应用了机理辐射传输模型，综合了不同机制的相对重要性，并通过藤本植物叶片化学和树冠结构的实地数据进行了验证。我们发现在全球分布的地点，树冠和林分尺度上存在一致的藤本植物光谱信号。这种特征主要出现在树冠层，是由于叶片角度更水平的直接影响，导致投影叶面积更大，以及近红外和短波红外区域光散射增加的间接影响，这与藤本植物平均而言比树木成本更低的叶片结构有关。藤本植物存在一致的全球光谱信号表明，大规模量化藤本植物侵染是可行的。然而，由于导致藤本植物树冠反射信号的特征并非藤本植物所特有，准确的大规模检测需要经过严格验证的遥感方法。我们的模型突出了自动检测中的挑战，例如由于叶片物候、树木生活史、地形和气候导致的潜在误识别，特别是在藤本植物侵染规模小于单个遥感像素的情况下。观察到的跨地点模式也引发了关于藤本植物在不同环境中光学特征适应性相似性的生态问题，表明由于叶片生化和结构特征的共同限制可能存在趋同进化。
