Tue, Aug 16, 2022: 5:00 PM-6:30 PM
ESA Exhibit Hall
Background/Question/MethodsIn the context of plant community responses to climate change, intraspecific variability can make important contributions to overall trait diversity and allow for greater population resilience. Hyperspectral remote sensing (spectranomics) links functional traits to the spectral signature of plant canopies and has been used to quantify variability between species. However, very few studies using this technique address within-species variability. Here we used hyperspectral images of plots dominated by sugar maple (Acer saccharum) in southern Quebec, Canada, to test for relationships between canopy reflectance measurements and three environmental gradients related to climate: elevation, slope, and aspect. Regions of the electromagnetic spectrum most strongly correlated with these gradients were then interpreted with respect to potential underlying functional leaf traits, based on the literature.
Results/ConclusionsA redundancy analysis (RDA) of reflectance spectrum variation showed that the three predictors explained 28% of the total variance, indicating significant intraspecific variation along these gradients. Elevation and slope were most strongly related to the main axis of the RDA, with axis scores of 0.85 and 0.83, respectively. The influence of aspect was weaker, with an axis score of 0.24. Based on wavelengths most strongly correlated with the RDA axes, underlying functional traits likely include leaf pigment concentrations (decreasing with elevation) and possibly some structural morphological traits such as leaf sugar content. Overall, we conclude that hyperspectral imaging can be used to detect relationships between climate and intraspecific variability, giving an opportunity for a better assessment of the changes that are happening now and that are going to happen in the North American ecosystems. However, further studies will be necessary to identify more precisely the most relevant traits and the physiological limits of sugar maple with respect to the expression of these traits.
Results/ConclusionsA redundancy analysis (RDA) of reflectance spectrum variation showed that the three predictors explained 28% of the total variance, indicating significant intraspecific variation along these gradients. Elevation and slope were most strongly related to the main axis of the RDA, with axis scores of 0.85 and 0.83, respectively. The influence of aspect was weaker, with an axis score of 0.24. Based on wavelengths most strongly correlated with the RDA axes, underlying functional traits likely include leaf pigment concentrations (decreasing with elevation) and possibly some structural morphological traits such as leaf sugar content. Overall, we conclude that hyperspectral imaging can be used to detect relationships between climate and intraspecific variability, giving an opportunity for a better assessment of the changes that are happening now and that are going to happen in the North American ecosystems. However, further studies will be necessary to identify more precisely the most relevant traits and the physiological limits of sugar maple with respect to the expression of these traits.