B061-0011
Invasive and Native Plant Trait Space Dynamics across an Aquatic-Terrestrial Continuum

Friday, 11 December 2020
Poster
Shruti Khanna1, Maria J. Santos2, Martin Reader2 and Susan Ustin3, (1)California Department of Fish and Wildlife, Stockton, CA, United States, (2)URPP Global Change and Biodiversity, University of Zurich, Geography, Zurich, Switzerland, (3)Univ California Davis, Davis, CA, United States
Abstract:
Global change has resulted in significant losses, degradation, and sorting of biodiversity with major implications for ecosystem functioning, requiring urgent monitoring capacity of patterns and links between biodiversity and ecosystem functioning. Imaging spectroscopy has been fundamental to this goal, as it combines the necessary spectral resolution that resolves biodiversity, species and biochemistry and physiological traits with fine spatial and temporal resolutions to assess patterns and determine dynamics. Here we use a time series of imaging spectroscopy data over distinct environments along the aquatic-terrestrial continuum to assess change in trait space in a system facing climate and land use changes and large rates of species invasions. We assess trait space dynamics over a period of 14 years, focusing on a set of vegetation indices that relate to chlorophyll and other pigments, LAI, leaf water content, and lignin, cellulose and salinity. We provide detailed examples for four distinct environmental conditions in the system: inundated islands, narrow shallow channels, wide river channel, and a large flooded tract with strong tidal exchange. We investigated which portion of the trait space can be attributed to community composition shifts and which are likely to be most affected by other global change drivers. Here we show how multiple dimensions along the aquatic-terrestrial system might have negative and positive effects on trait space and help our understanding of the variation in trait space in this vast ecosystem. We also show that remote sensing imaging spectroscopy data, while costly and requiring processing time, provides unprecedented opportunities to estimate the effects of global change drivers on traits that are linked to biodiversity structure, diversity, function, and services.