Biological invasions, one of the most pervasive components of global change, can cause irreversible alterations in the composition and functioning of ecosystems. This includes changes of eco-physiological traits of plant communities. Satellite remote sensing provides the means to map surrogates of ecosystem composition and functioning such as eco-physiological traits over large spatial extents. In this study, Sentinel-2 and Sentinel-3 Copernicus satellite data resampled to 20 m2 spatial resolution was used to characterize the annual cycle of spectral eco-physiological traits in 176 patches invaded by Ailanthus altissima (Mill.) Swingle in Sardinia (Italy) and in their corresponding and surrounding non-invaded areas. The overall aim was to examine if and how eco-physiological traits differed between A. altissima and native vegetation classes. A set of spectral eco-physiological indices proxies related to leaf chlorophyll and carotenoid content (Chlorophyll Vegetation Index − CVI, Structure Intensive Pigment Index 3 − SIPI3), productivity and canopy biomass (Enhanced Vegetation Index − EVI, Leaf Area Index − LAI), leaf water content (Normalized Multi-band Drought Index − NMDI, Moisture Stress Index − MSI), daily evapotranspiration (ET), and soil features (Coloration Index − CI) were calculated. The monthly trends of these indices in invaded patches and the seasonal differences between invaded and non-invaded cells were analyzed using linear mixed models (LMMs). One-way Analysis of Variance (ANOVA), and Estimated Marginal Means (EMMs) were used to test the differences between invaded and non-invaded cells. Our results highlighted the effectiveness of Sentinel-2 and -3 data in capturing the temporal trends of spectral eco-physiological traits. Most significant differences between invaded and non-invaded cells were observed during summer, with invaded cells featuring higher productivity, canopy biomass, and leaf water content, while leaf carotenoid content and bare soil cover was lower. Overall, our findings based on satellite-based remote sensing analysis provide further evidence of the competitive advantages A. altissima has over native vegetation, particularly in summer, when vegetation in Mediterranean-type ecosystems faces an intense drought stress. Such spatially explicit information facilitates the identification and selection of field sites for proximal measurements of the alterations and potential impacts attributed to A. altissima invasion.

Assessing eco-physiological patterns of Ailanthus altissima (Mill.) Swingle and differences with native vegetation using Copernicus satellite data on a Mediterranean Island

Bagella, Simonetta;Bacchetta, Gianluigi;Podda, Lina;Brundu, Giuseppe
2025-01-01

Abstract

Biological invasions, one of the most pervasive components of global change, can cause irreversible alterations in the composition and functioning of ecosystems. This includes changes of eco-physiological traits of plant communities. Satellite remote sensing provides the means to map surrogates of ecosystem composition and functioning such as eco-physiological traits over large spatial extents. In this study, Sentinel-2 and Sentinel-3 Copernicus satellite data resampled to 20 m2 spatial resolution was used to characterize the annual cycle of spectral eco-physiological traits in 176 patches invaded by Ailanthus altissima (Mill.) Swingle in Sardinia (Italy) and in their corresponding and surrounding non-invaded areas. The overall aim was to examine if and how eco-physiological traits differed between A. altissima and native vegetation classes. A set of spectral eco-physiological indices proxies related to leaf chlorophyll and carotenoid content (Chlorophyll Vegetation Index − CVI, Structure Intensive Pigment Index 3 − SIPI3), productivity and canopy biomass (Enhanced Vegetation Index − EVI, Leaf Area Index − LAI), leaf water content (Normalized Multi-band Drought Index − NMDI, Moisture Stress Index − MSI), daily evapotranspiration (ET), and soil features (Coloration Index − CI) were calculated. The monthly trends of these indices in invaded patches and the seasonal differences between invaded and non-invaded cells were analyzed using linear mixed models (LMMs). One-way Analysis of Variance (ANOVA), and Estimated Marginal Means (EMMs) were used to test the differences between invaded and non-invaded cells. Our results highlighted the effectiveness of Sentinel-2 and -3 data in capturing the temporal trends of spectral eco-physiological traits. Most significant differences between invaded and non-invaded cells were observed during summer, with invaded cells featuring higher productivity, canopy biomass, and leaf water content, while leaf carotenoid content and bare soil cover was lower. Overall, our findings based on satellite-based remote sensing analysis provide further evidence of the competitive advantages A. altissima has over native vegetation, particularly in summer, when vegetation in Mediterranean-type ecosystems faces an intense drought stress. Such spatially explicit information facilitates the identification and selection of field sites for proximal measurements of the alterations and potential impacts attributed to A. altissima invasion.
2025
Impact
Invasive non-native plant
Multispectral
Sentinel
Spectral eco-physiological trait
Thermal
Tree-of-heaven
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/440547
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