Functional traits are defined as any attribute that influences establishment, survival, and individual fitness, being closely coupled to the environment and to biotic interactions. Spatial and temporal variations in resource utilization by plants result in chemical, metabolic, structural, and phenological differences, influencing the optical properties of leaves and canopies. These variations lead to unique optical patterns that are detectable by remote sensing, allowing for the separation of multiple levels of diversity, and improving the detection of changes in plant functional diversity and turnover. The Serra do Cipó region is a tropical and snow-free mountainous environment, characterized by an elevational gradient ranging from 800 to 1500m of altitude. Serra do Cipó is known for its high species diversity and endemism across the elevational gradient, which provides a unique natural environment to investigate functional trait diversity. Within this region, the Campo Rupestre (rupestrian grassland) environment encompasses a mosaic of vegetation types, including rocky outcrops, sandy grasslands, stony grasslands, waterlogged grasslands and peatbogs. At lower elevations, different savanna-like formations of Cerrado biome can be found, with varying degrees of woody and grassland cover. During the proposed internship, I will analyze individual plant trait data (Leaf Dry Matter Content; Leaf Mass per Area; Height, and Nitrogen and Carbon content) along with leaf spectroscopic measurements from 1650 individuals sampled at Serra do Cipó. I expect to obtain results that can support future work using aerial and orbital hyperspectral remote sensing, to scale up functional traits and ecosystem processes to larger scales. This analysis is the main basis of my PhD project, composing the second and third chapters of my thesis. This proposal aims specifically to: (i) develop structural equation models to understand the processes underlying trait-trait and trait-environment relationships; (ii) develop a framework for the use of "optical traits" as a way of identifying general processes underlying trait-based ecology; and (iii) upgrade the structure of the database built during the year of 2016/2017. The combination of hyperspectral remote sensing with sound ecological theory will allow me to evaluate species-trait variation between and within community assemblages at multiple scales, and to build a database that can be used to guide future satellite missions.
News published in Agência FAPESP Newsletter about the scholarship: