Abstract Generating large-scale field-based guild data for assessing tree species sorting and distribution over tropical covers is difficult. In this study, we combined field, and the Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) datasets of tropical covers across a climate gradient to develop precision maps of abundant tree species. This assisted in the extraction of a large dataset of guilds with tree species assortment and occupancy. We observed parity in the distribution of local and regional species with an increase in the proportionate presence of local species over the climate gradient. We saw greater distribution of Fabaceae members in sites with relatively lesser rainfall. To address the impact of species sorting on the functional aspects of guilds, available R codes (), and three vegetation indices (VIs) as functional traits (Photochemical Reflectance Index, PRI, Chlorophyll/Carotenoid Index, CCI, and Normalized Difference Water Index, NDWI) were tested. Species assortment and spread affected the guild's functional diversity, as noticed in the abundance weighted guild means of VIs. We also observed a consistent increase in the mean CCI of all species across the climate gradient correlating positively with rainfall and negatively with vapour pressure deficit (VPD). This shows that CCI could be an adequate measure for large-scale ecological observations of these tropical regions. Wider amplitudes in the measured VIs of deciduous species demonstrated their adaptability to the climate gradient. Gradient-driven species assembly dynamics and functional traits variability indicates of tropical tree biodiversity feedback to the climate dynamics.


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    Title :

    Importance of AVIRIS-NG data in assessing the assemblage of guilds of tropical trees over a contrasting climate



    Published in:

    Advances in Space Research ; 73 , 2 ; 1397-1412


    Publication date :

    2022-09-12


    Size :

    16 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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