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Discerning Oriental from European beech by leaf spectroscopy: Operational and physiological implications


D'Odorico, Petra; Schuman, Meredith Christine; Kurz, Mirjam; Csilléry, Katalin (2023). Discerning Oriental from European beech by leaf spectroscopy: Operational and physiological implications. Forest Ecology and Management, 541:121056.

Abstract

European beech (Fagus sylvatica L.) forests have recently experienced severe diebacks that are expected to increase in future. Oriental beech (Fagus sylvatica spp. orientalis (Lipsky) Greut. & Burd) is a potential candidate for
assisted migration (AM) in European forests due to its greater genetic diversity and potentially higher drought
resistance. Yet AM entails not only benefits, but also risks, and it is therefore important to monitor the progression
of introduced (sub)species. Here, we demonstrate the potential of leaf spectroscopy to replace resourceintensive
genetic analysis and field phenotyping for the discrimination and characterization of these two beech subspecies.

We studied two European beech forests, one in France and one in Switzerland, where Oriental beech from the Greater Caucasus was introduced over 100 years ago. During two summers (2021, 2022), we measured leaf spectral reflectance, leaf morphological and biochemical traits from genotyped adult trees. Subspecies prediction models were developed separately for top-of-canopy leaves (amenable to remote sensing) and bottom-of-canopy leaves (easier to harvest) using partial least squares discriminant analysis (PLS-DA) and different sets of spectral predictors.

Morphological, biochemical and spectra-derived leaf traits indicated that Oriental beech trees at the sites studied were characterized by higher lignin and nitrogen per unit leaf area than European beech, suggesting more protein-rich leaves on a per-area basis. The model based on top-of-canopy leaf reflectance spectra in the short-wave-infrared region (SWIR I: 1450–1750 nm) most accurately distinguished Oriental from European beech (BA = 0.86 ± 0.08, k = 0.72 ± 0.15), closely followed by models based on SWIR II, and on spectra-derived traits (BA ≥ 0.84, k ≥ 0.67).

This study provides a proof-of-principle for the development of spectroscopy-based approaches when monitoring
introduced species, subspecies or provenances. Our findings hold promise for upscaling to large forest areas using airborne remote sensing.

Abstract

European beech (Fagus sylvatica L.) forests have recently experienced severe diebacks that are expected to increase in future. Oriental beech (Fagus sylvatica spp. orientalis (Lipsky) Greut. & Burd) is a potential candidate for
assisted migration (AM) in European forests due to its greater genetic diversity and potentially higher drought
resistance. Yet AM entails not only benefits, but also risks, and it is therefore important to monitor the progression
of introduced (sub)species. Here, we demonstrate the potential of leaf spectroscopy to replace resourceintensive
genetic analysis and field phenotyping for the discrimination and characterization of these two beech subspecies.

We studied two European beech forests, one in France and one in Switzerland, where Oriental beech from the Greater Caucasus was introduced over 100 years ago. During two summers (2021, 2022), we measured leaf spectral reflectance, leaf morphological and biochemical traits from genotyped adult trees. Subspecies prediction models were developed separately for top-of-canopy leaves (amenable to remote sensing) and bottom-of-canopy leaves (easier to harvest) using partial least squares discriminant analysis (PLS-DA) and different sets of spectral predictors.

Morphological, biochemical and spectra-derived leaf traits indicated that Oriental beech trees at the sites studied were characterized by higher lignin and nitrogen per unit leaf area than European beech, suggesting more protein-rich leaves on a per-area basis. The model based on top-of-canopy leaf reflectance spectra in the short-wave-infrared region (SWIR I: 1450–1750 nm) most accurately distinguished Oriental from European beech (BA = 0.86 ± 0.08, k = 0.72 ± 0.15), closely followed by models based on SWIR II, and on spectra-derived traits (BA ≥ 0.84, k ≥ 0.67).

This study provides a proof-of-principle for the development of spectroscopy-based approaches when monitoring
introduced species, subspecies or provenances. Our findings hold promise for upscaling to large forest areas using airborne remote sensing.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Department of Chemistry
07 Faculty of Science > Institute of Geography
08 Research Priority Programs > Global Change and Biodiversity
Dewey Decimal Classification:910 Geography & travel
540 Chemistry
Scopus Subject Areas:Life Sciences > Forestry
Physical Sciences > Nature and Landscape Conservation
Physical Sciences > Management, Monitoring, Policy and Law
Uncontrolled Keywords:Management, Monitoring, Policy and Law, Nature and Landscape Conservation, Forestry
Language:English
Date:1 August 2023
Deposited On:08 Jun 2023 11:26
Last Modified:29 Jun 2024 01:36
Publisher:Elsevier
ISSN:0378-1127
OA Status:Hybrid
Publisher DOI:https://doi.org/10.1016/j.foreco.2023.121056
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)