Leaf-Level Field Spectroscopy to Discriminate Invasive Species (Psidium guajava L. and Hovenia dulcis Thunb.) from Native Tree Species in the Southern Brazilian Atlantic Forest

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2023-02, Vol.15 (3), p.791
• Main Authors: Mallmann, Caroline, Pereira Filho, Waterloo, Dreyer, Jaqueline, Tabaldi, Luciane, Durgante, Flavia
• Format: Article
• Language: English
• Subjects: Biodiversity; Ecosystems; Environmental economics; Flowers & plants; Forests; Habitats; Hovenia dulcis; Indigenous species; Introduced species; invasive alien species; Invasive plants; Invasive species; Leaf area; leaf functional traits; Leaves; linear discriminant analysis; Moisture content; Morphology; Native species; Nonnative species; Optical properties; Parameterization; Phenology; Photosynthetic pigments; Physiology; Pigments; Plant species; Psidium guajava; Reflectance; Regression analysis; Regression models; Remote sensing; Spectral reflectance; Spectroscopy; Trees; Water content
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs15030791

Invasive species are known to have potential advantages over the native community and can be expressed in their leaf functional traits. Thus, leaf-level traits with spectral reflectance can provide valuable insights for distinguishing invasive trees from native trees in complex forest environments. We conducted field spectroscopy measurements in a subtropical area, where we also collected trait data for 12 functional traits of invasive (Psidium guajava and Hovenia dulcis), and native species (Psidium cattleianum and Luehea divaricata). We found that photosynthetic pigments were responsible for the greatest interspecific variability, especially in the green region of the spectrum at 550 nm, therefore contributing to detection of invasive species. In addition, according to LDA and stepwise procedures, the most informative reflectance spectra were concentrated in the visible range that is closely related to pigment absorption features. Furthermore, we aimed to understand the leaf optical properties of the target invasive species by using a combination of narrow bands and linear regression models. P. guajava showed high correlations with specific leaf area, Car/Chl and relative water content. H. dulcis had a strong correlation with water content, specific leaf area and Chla/Chlb. Overall, this methodology proved to be appropriate for discriminating invasive trees, although parameterization by species is necessary.