Terrace surfaces support the majority of tropical forests in the southern Peruvian Amazon. While these systems are important due to their spatial extent, relatively little work has been done to examine the relationships between environmental gradients and ecosystem characteristics, such as canopy traits, within these landscapes. Determining canopy traits across large areas of terrace landscapes has traditionally been difficult due to the high biological diversity of these forests and the effort involved in obtaining large sample sizes from canopy trees. However, emerging remote sensing technologies are allowing us to consider these relationships at high resolution across regions that have not been possible previously. Here we use data obtained by the Carnegie Airborne Observatory (CAO) in 2013 to remotely measure canopy traits across over 1,000 hectares of forest using high-fidelity imaging spectroscopy data from its Visible-Shortwave Imaging Spectrometer (VSWIR). We use these data to understand the relationship between these canopy foliar traits and underlying geomorphic gradients, identified by digital elevation models derived from the CAO high-resolution dual waveform LiDAR.
We found that canopy traits vary between flat, geomorphically stable, terrace surfaces and areas at low hillslope positions that are connected to active stream channels. Specifically, the foliar concentrations of rock-derived nutrients were elevated at low hillslope positions relative to the concentrations observed on the terrace surface. These variations are consistent with our previous results that rock-derived nutrients in soils increase along hillslopes that terminate in active streams in this landscape. This suggests that there are landscape level biotic responses to within-terrace environmental gradients, which are detectable using emerging remote sensing technologies. These results allow us to gain an understanding of drivers of the spatial organization of canopy traits in a lowland tropical forest ecosystem within an individual terrace landscape.