Phenotypic and optical plant trait variation across space and time in the seasonal tropics: patterns, drivers and consequences

Here, I explore trait-based ecology to understand how the environment shapes plant trait variation at multiple scales, combining remote sensing technologies and plant ecology. In the second chapter, the patterns and drivers of land surface phenology were assessed for the Meridional Espinhaço Range in Brazil. The TIMESAT algorithm was used to extract the phenological indicators from a14-year time series of MODIS/NDVI satellite images. Water and light availability, modulated by topography, are the most likely drivers of land surface phenology in the region, determining the start, end, and length of the growing season, while temperature had an important role in determining the rates of leaf development and the strength of vegetation seasonality. In chapter three, I tested if the generalities of global patterns of plant form and function dimension held in finer scales in the seasonally dry tropics, and its relation with the an elevational and topo-edaphic environmental gradient. Leaf functional data (LMA, LDMC and leaf area) and plant height from 1650 individual comprising all life-forms of locally co-occurring plants was gathered, at five sites along an elevational gradient, sampling all vegetation types found within each elevation, at the southern portion of the Espinhaço range, known as Serra do Cipó, in Minas Gerais. The phenotypic organization of plant form and function found at global scales was similar to the one found among locally co-occurring species in campo rupestre. The whole-plant size dimension varied along the elevational gradient, however, the leaf economics dimension (LES) behaved differently than plant size, and no variation of key LES traits along environmental gradients was found. In chapter four, the ability of spectroscopy to estimate leaf functional traits and to differentiate plants comprising different growth forms was investigated. Leaf reflectance spectra was able to accurately predict leaf functional traits from different growth forms, but the models lost precision towards higher LMA values, pointing out a saturation point from spectroscopy and/or a limitation from the modelling approach adopted in this study. Grasses and woody plants were the most spectrally dissimilar, while forbs represented an intermediary spectral group. In chapter five the influence of taxonomic levels on the relationship between spectral and functional diversity was investigated. Interspecific variation was greater than intraspecific variation for functional and spectral traits, but the amount of intraspecific variation was a specific response of each species. Leaf age may be contributing more than expected to intraspecific spectral variability, hampering the delineation of a full parallel with trait-based ecology. The variance partition showed that both, functional and spectral traits varied mainly at the family level, indicating that both are evolutionary conserved. This study contributes to the construction of theories linking spectral to functional and taxonomic diversity, helping to build a biodiversity monitoring system based on remote sensing. (AU)